DETAILED ACTION
Notice of Pre-AIA or AIA Status
Claims 19-22, 24-33 and 35-39 are currently presented for Examination.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
3. The amendment filed on September 09, 2025 has been entered and considered by the examiner.
By the amendment, claims 19-22, 24-33, and 35 are amended and claim 34 is cancelled and claims 37-39 are newly added. In light of the amendment made, examiner still maintained the 101 and 103 rejection and is explanation is provided below. See office action.
Response to 101 Arguments
Applicant arguments
The amended claim 19 recites a specific technical solution to problems in electrical condition monitoring systems, particularly addressing the challenge of monitoring an electrical device "when the electrical device is in operation". It does so using specialized sensing hardware and a defined module-based processing that generates residual signals, performs FFT to create a "temporally-changing Fourier spectrum," identifies significant phenomena using a crawling technique with statistical criteria, and compares a real-time model against stored models to generate operating-condition information. This technical arrangement is supported by the published application, which states that the system generates "a corresponding temporally-changing Fourier spectrum including signal harmonic components for at least one of the current or the voltage" and that the spectrum can be formed "by performing a Fast Fourier Transform (FFT) ... (optionally, or a calculated residual current or a calculated residual voltage)" (paragraph [0070]). The specification also discloses the linear-model/residual current data expressly recited in amended claim 19(ii)(a)-(d):"(i) generate a linear model describing the electrical device;(ii) use the linear model to create a model of predicted current of the electrical device from measured voltages obtained from the electrical device; (iii) compare the model of predicted current with a measured current of the electrical device to create a residual current data; (iv) perform Fast Fourier Transform (FFT) on the residual current data to create the temporally-changing Fourier spectrum" (paragraphs [0087]- [0091]).
Accordingly, amended claim 19 expressly recites a concrete technical architecture rooted in signal acquisition and module-based signal processing on operating equipment, rather than a mere abstract process. By requiring specialized sensing hardware and specific processing modules, the amended claim is implemented in practical monitoring systems while the device is energized and operating. Further, the Applicant respectfully submits that the amended claim 19 integrates the alleged abstract idea into a practical application through specific technical implementations. Amended claim 19 recites a concrete pipeline of sensing, residual modeling, FFT-based spectral analysis, crawling-based local maxima identification with statistical significance selection, and model comparison via dedicated modules to generate operating-condition information during device operation. The specification details this coordinated, practical workflow: "configuring a user interface for user entry of input... operating the data processing arrangement to at least partially filter out... distortion... operating the data processing arrangement to identify at least one local maximum... operating the data processing arrangement to calculate locations... to create afamily of possible local maxima... operating the data processing arrangement to identify a significant local maximum... operating the data processing arrangement to generate a real-time model... [and] operating the data processing arrangement to access one or more stored models... and to compare... to generate information indicative of an operating condition of the electrical device “Even if the claims were considered to be directed to an abstract idea (which Applicant disputes), the claims add significantly more. The claimed system combines specialized sensing hardware, residual-model/FFT spectral generation, a defined crawling technique with statistically significant selection, distortion filtering, and module-based real-time model generation and comparison an unconventional technical combination that provides improved reliability. The specification ties these features to better predictions and reduced false positives: "identification of such clustering of a family of a plurality of local maxima is beneficial in providing more reliable predictions and hence avoiding false alarms (namely, false positives')" (US 2021/0018542 Al, p. 11).
Examiner response
Examiner respectfully disagrees. Although amended claim 19 recites sensing hardware and multiple processing “modules”, the focus of the claim remains the mathematical and mental analysis of data, which falls with the judicial exception for abstract ideas. Claim recitation “generating a linear model”, “predicting current from voltage”, “comparing predicted and measured signals to obtain a residual”, “performing FFT”(a mathematical algorithm), “identifying local maxima and minima”(mathematical analysis), selecting significant peaks using statistical criteria”, “labeling the peak with a phenomenon description” and “comparing a real-time model to stored model” constitute mathematical operations, statistical evaluations and data interpretation- all of which fall under “mathematical concepts” and “mental process” identified in the 2019 PEG as abstract ideas. Applicant characterizes these steps as “technical improvement”, but the underlying operations remain purely mathematical, regardless of the context in which they are applied. The alleged “crawling technique” and “identification of local maxima/minima” are merely analytical methods for processing data, not improvements to a technological tool.
Applicant argues that the use of sensors, modules and a user interface integrate the practical application, in which the Examiner disagrees. As previously stated in the office action- In accordance with Step 2A, Prong 2, the judicial exception is not integrated into a practical application. In particular, the claim 19 the additional elements of “the electrical condition monitoring system includes the sensing arrangement for temporally sensing an electrical supply to and/or sensing an electrical supply generated by electrical device in case of a generator and generates corresponding sensed data by processing the sensed electrical supply to and/or from the electrical device, wherein the sensed data includes information associated with at least one of a supply of voltage or a supply of current to and/or the sensed data includes information associated with at least one of supply voltage or a supply of current from the electrical device,” and “presenting to the user” is a mere data gathering and outputting step and thus it falls under insignificant pre-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g) and is well-understood, routine or conventional. ((See MPEP 2106.05 (d)(II)(i))) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). The additional elements of the electrical condition monitoring system includes a data processing arrangement including a data processor, wherein the data processing arrangement comprises a filtering module, a spectrum analysis module, a real-time model generation module, and a model comparison module and “user interface are merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f);
The instant claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. Given the broadest reasonable interpretations of the claimed subject matter, the claimed embodiment is not an improvement to another technological field. These limitations do not provide for an improvement in computer functions or any other improvement (e.g. sensor, FFT technology, model generation technology or improve any physical component of an electrical device). Instead, it uses a generic processor to perform routine signal analysis and mathematical modeling, and presents the results to a user. To show that the involvement of a computer assists in improving the technology, the claims must recite the details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. The claims do not apply or involve a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition. The claims do not apply or perform the abstract idea with a particular machine, MPEP 2106.06b. The claims to do transform or reduce a particular article to a different state or thing (data remains data when processed by a computer), MPEP 2106.05c. The claims do not apply or use the abstract idea in a meaningful way beyond generally linking the use of the abstract idea to a particular technological environment (i.e., a processor), such that the claims are a drafting effort to monopolize the abstract idea (i.e., the claims do not integrate the abstract idea into a practical application of the abstract idea). Accordingly, the claims are not patent eligible under 35 U.S.C. 101. Even though the applicant argues the disclosed invention is described in the specification are not mental step, the claim provides no meaningful limitations that are more than the judicial exception.
Response to prior art Arguments
Applicant arguments
Accordingly, Dowling and HOSEK, either alone or in combination, fail to teach or suggest the limitations of amended independent claim 19 that now recite: generating a real-time linear model; predicting current from sensed voltage; forming residual current by comparison of predicted and measured current; applying FFT to the residual current; employing a crawling technique to define and locate local maxima bounded by minima; selecting statistically significant peaks; and labeling the significant local maximum with a phenomenon description in the user interface.
Examiner response
Applicant argues that Dowling only teaches FFT of “raw current” and does not disclose the claimed “crawling technique” for identifying local maxima is not persuasive.
Dowling teaches performing FFTs on current signals to produce spectra (col 3 line 4-6 and col 5 lines 37-41). Also teaches performing FFTs on multiple probe signal over the same time window (col 15, line 66 -col 16 line 9, thereby generating temporally changing spectra. It also identifies maximum spectral peaks and candidates’ peaks (see col 18 line 65 -col 19 line 15). Then. It evaluates candidate peaks by examining adjacent spectral interval on each side and requiring at least a 12dB roll off (col 18, line 65 -col 19 line 5) and eliminating peaks lacking sufficient side roll-off. It is the Examiner position that these above steps necessarily require identifying values that increase toward a peak (before the peak) and decrease from a peak (after the peak)- the exact same behavior of the claimed crawling technique. The claimed defined the crawling technique by function, not by any particular movement or algorithmic label, and Dowling’s peak-identification algorithm meets these functions. Additionally, Dowling’s peal-validation algorithm inherently segments the entire spectrum into local maxima and minima regions. This meets the claims requirement to divide the spectrum into maxima joined by minima. Thus, Dowling teaches the crawling technique.
Applicant argues Dowling lacks statistical significance and is not supported. Dowling teaches using absolute threshold (e.g., 45 dB to classify spectra peaks (col 24, line 6-20); calculating deviation from the mean to determine imbalance (col 22 line 33-50) and setting threshold based on standard deviation monitoring (col 22 line 33-50). These above sections correspond directly to the claim’s “significant local maximum…in terms of absolute value or standard deviations form the mean value”.
Applicant argues Dowling does not teach labeling significant peaks. This is unpersuasive. Dowling describes displaying rotor conditions, stator conditions, current and voltage imbalance and event flags indicating detected phenomenon (col 10 lines 15-25 and col 10 lines 33-40). Once Dowling’s algorithm identifies the significant peak (e.g., rotor fault band, fifth harmonic, shaft frequency sideband), that diagnosed is displayed. This satisfies the limitation requiring the UI labeling of the significant maximum with the associated phenomenon description.
Applicant argues Hosek does not teach generating predicted current form voltages and subtracted measure current to obtain to a residual current is incorrect. Hosek teaches constructing linear neural network models as a diagnostic observer (see para 20). Hosek teaches predicting motor current based on system states and voltages inputs (see para 277). It teaches calculating modeled current based on voltage and velocity (see para 313). It also teaches computing the residual as “difference between actual and modeled current”. (see para 277, para 313). This sections exact match the claim’s requirement to generate a linear model, predict current from voltage and subtract to form a residual current signal. Thus, Hosek cures any modeling/prediction/residual gaps that may exist in Dowling.
Applicant argues there is no reason to combine Dowling and Hosek, however, this argument is not persuasive. Dowling analyzes current signals to detect motor faults. Hosek provides a method to produce a residual signal that suppresses nominal behavior and enhances faults signatures. Thus, a person in the ordinary skill of the art would recognize that applying Dowling’s FFT and peak-detection/spectrum-analysis to a cleaner fault-sensitive residual is a predictable improvement.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 19 and 35 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. The claim contains multiple unclear, ambiguous, and grammatically defective limitations, as detailed below.
Claim 19 and 35 recites both: “electrical condition monitoring system,” and “electrical conditioning monitoring system.” These terms appear to refer to different systems, creating uncertainty regarding what structure is actually being claimed. Accordingly, the claim is indefinite.
Claim 19 and 35 recites “sensed data includes information associated with at least one of a supply of voltage or a supply of current to and/or the sensed data includes information associated with at least one of supply voltage or a supply of current from the electrical device” This clause is unclear because: It contains contradictory “at least one of… or… and/or…” constructions, repeats the same requirement twice with different grammar and lacks clear delineation of whether voltage/current is being sensed to or from the device. The scope of the limitation cannot be determined with reasonable certainty.
Claim 19 and 35 recites: “analyzing the analysis data,” and “generate the analysis data.” However, “analysis data” is not introduced prior to these references. This results in a lack of antecedent basis and renders the claim indefinite.
Claim 19 and 35 recites “the same phenomenon,” “a phenomenon description,” and “corresponding to the phenomenon,” but no “phenomenon” is initially introduced. Accordingly, these terms lack antecedent basis and render the claim indefinite
Claim 19 and 35 recites the data processing arrangement “comprises” distinct modules (filtering module, spectrum analysis module, real-time model generation module, model comparison module), but then also recites that the data processor is configured to perform all the listed steps. It is unclear whether: the modules perform the steps, the data processor performs the steps, or the processor merely controls the modules. This ambiguity in functional attribution renders the claim indefinite.
Claim 19 and 35 recites “a significant local maximum in terms of an absolute value or number of standard deviations from a mean value.” However, no threshold, numerical value, statistical window, or objective boundary for “significant” is provided. The term is subjective and lacks clear metes and bounds.
Claim 19 and 35 recites “create a family of possible local maxima,” “identify… a significant local maximum from the family of possible local maxima.” The phrase “possible local maxima” is unclear because: It is not defined how a local maximum is “possible”. Thus, the limitation is indefinite.
Claim 19 and 35 In step (vi), the claim recites: “compare… the real-time model with the one or more stored models…” However, the claim never explicitly introduces “the real-time model” prior to this reference. Accordingly, this term lacks antecedent basis.
Claims 20-22, 24-33 and 37-39 are dependent claims of claim 19 and do not cure the deficiencies of claim 19 and thus rejected as well.
Claim Rejections - 35 USC §101
5. 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
6. Claims 19-22, 24-33 and 35-39 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. These claims are directed to an abstract idea without significantly more.
(Step 1) Is the claims to a process, machine, manufacture, or composition of matter?
Claims: 19-22, 24-35 and 37-39 are directed to system or device, which falls into the one of the statutory category.
Claim: 35 is directed to process or method, which falls into the one of the statutory category.
Claim:36 is directed to a computer program, product comprising a non-transitory computer-readable storage medium that falls into the one of the statutory category.
(Step 2A) (Prong 1) Is the claim directed to a law of nature, a natural phenomenon, or an abstract idea? (Judicially recognized exceptions)?
Claim 1, 35, 36 recites
(ii) filter out changes in magnitudes and frequencies of signal harmonic components caused due to electrical distortions including switching noise; (Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgement or observation that could be performed in the human mind or with the aid of pencil and paper therefore it falls within the “Mental Process” grouping of abstract ideas)
generate a linear model describing the electrical device; (Creating a mathematical formula or equation to describe a system is a fundamental mathematical concept. This can be done with pen and paper and general knowledge of linear regression.)
use the linear model to create a model of predicted current of the electrical device from measured voltages obtained from the electrical device; (Applying a mathematical model to input data is a calculation that can be done manually.)
compare the model of predicted current with a measured current of the electrical device to create a residual current data; (Creating residual data by comparing values is a simple subtraction operation.)
perform Fast Fourier Transform (FFT) on the residual current data to create the temporally-changing Fourier spectrum; (The FFT is a well-known mathematical algorithm for converting time-domain data to the frequency domain. While computationally intensive for large datasets, the underlying process is an algorithm that can be theoretically performed by a human, aided by basic tools like pen and paper.)
identify the at least one local maximum on the temporally-changing Fourier spectrum using a crawling technique to divide an entirety of the temporally-changing Fourier spectrum into local maxima joined to one another at local minima, wherein the crawling technique identifies the at least one local maximum on the temporally-changing Fourier spectrum by determining a value that increases towards the at least one local maximum or a value that decreases from the at least one local maximum; (The crawling technique for identifying local maxima, as described (determining a value that increases or decreases), is a method of organizing and analyzing data, which can be done mentally or manually with a pen and paper.)
identify the significant local maximum in terms of an absolute value or number of standard deviations from a mean value; (Determining significance based on absolute value or standard deviations is a statistical calculation and a mental process.)and
label the significant local maximum with the phenomenon description in the user interface for presenting to the user. (Associating a label with a data point and presenting it on a user interface is a function that a human can perform.)
(Steps (a) through (g) involve abstract mathematical process that can be performed using pen and paper or basic mathematical concepts, and thus is considered a mental process in the context of patent eligibility. The steps involve mathematical modeling, data manipulation, and analysis algorithms that do not require a specific, unconventional machine implementation to be carried out.)
(iii) analyzing the analysis data and to analyze the analysis data based on the input to obtain information indicative of an operating condition of the electrical device; (Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgement that could be performed in the human mind or with the aid of pencil and paper therefore it falls within the “Mental Process” grouping of abstract ideas)
(iv) calculate locations on the temporally- changing Fourier spectrum where the same phenomenon appears to create a family of possible local maxima; (The process relies heavily on mathematical concepts, including: Fourier Analysis/Transforms, Finding local maxima involves differentiation (finding the first derivative and setting it to zero) and the second derivative test to classify points, Specific mathematical algorithms, such as the Fast Fourier Transform (FFT), are used for efficient computation of the Fourier spectrum. The theory of extrema in mathematical analysis is applied to precisely define and locate the highest points (peaks) in the spectrum.)
(v) identify a significant local maximum from the family of possible local maxima corresponding to the phenomenon and to generate the analysis data from a magnitude of the significant local maximum; (Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgement that could be performed in the human mind or with the aid of pencil and paper therefore it falls within the “Mental Process” grouping of abstract ideas. Determining which of several possible local maxima is "significant" often involves subjective judgment, domain expertise, and decision-making, which are cognitive functions.)
and
(vi) access one or more stored models of operation of the electrical device, and to compare the real-time model with the one or more stored models to generate information indicative of an operating condition of the electrical device. (Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgement that could be performed in the human mind or with the aid of pencil and paper therefore it falls within the “Mental Process” grouping of abstract ideas. The core steps of "comparing" and "generating information" are considered fundamental mental operations.)
Step 2A, Prong 2: Does the claim recite additional elements that integrate the judicial exception into a practical application?
In accordance with Step 2A, Prong 2, the judicial exception is not integrated into a practical application. In particular, the claim 19 and 35 recites the additional elements of “the electrical condition monitoring system includes the sensing arrangement for temporally sensing an electrical supply to and/or sensing an electrical supply generated by the electrical device in case of a generator and generates corresponding sensed data by processing the sensed electrical supply to and/or from the electrical device, wherein the sensed data includes information associated with at least one of a supply of voltage or a supply of current to and/or the sensed data includes information associated with at least one of supply voltage or a supply of current from the electrical device, wherein the sensing arrangement comprises current sensing device to measure the supply of current and a voltage sensing device to measure the supply of voltage” is a mere data gathering step and thus it falls under insignificant pre-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g). Claim 19 and 35 recites the additional elements of the electrical condition monitoring system includes a data processing arrangement including a data processor, wherein the data processing arrangement comprises a filtering module, a spectrum analysis module, a real-time model generation module, and a model comparison module and “user interface that is configured for user entry of input” and claim 36 recites the additional elements of computer program product comprising a non-transitory computer-readable storage medium having computer-readable instructions stored thereon, the computer-readable instructions being executable by a computerized device comprising processing hardware to execute the method of claim 35 which are merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f); An electrical condition monitoring system that is connectable to an electrical device, wherein the electrical condition monitoring system includes a sensing arrangement that is configured to electrically connect the electrical conditioning monitoring system to the electrical device and to monitor the electrical device when the electrical device is in operation in the preamble just link the claim to a technological environment. The use of this language is not anything significantly more than the abstract idea, specifically because it is generally linking the use of judicial exception to a particular field of use. These additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
In accordance with Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. In accordance with Step 2A, Prong 2, the judicial exception is not integrated into a practical application. In particular, claim 19 and 35 recites the additional elements of “the electrical condition monitoring system includes the sensing arrangement for temporally sensing an electrical supply to and/or sensing an electrical supply generated by the electrical device in case of a generator and generates corresponding sensed data by processing the sensed electrical supply to and/or from the electrical device, wherein the sensed data includes information associated with at least one of a supply of voltage or a supply of current to and/or the sensed data includes information associated with at least one of supply voltage or a supply of current from the electrical device, wherein the sensing arrangement comprises current sensing device to measure the supply of current and a voltage sensing device to measure the supply of voltage” which is a mere data gathering steps and thus it falls under insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g) and is well-understood, routine or conventional. ((See MPEP 2106.05 (d)(II)(i))) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). Claim 19 and 35 recites the additional elements of the electrical condition monitoring system includes a data processing arrangement including a data processor, wherein the data processing arrangement comprises a filtering module, a spectrum analysis module, a real-time model generation module, and a model comparison module and “user interface that is configured for user entry of input” and claim 36 recites the additional elements of computer program product comprising a non-transitory computer-readable storage medium having computer-readable instructions stored thereon, the computer-readable instructions being executable by a computerized device comprising processing hardware to execute the method of claim 35 which are merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f); An electrical condition monitoring system that is connectable to an electrical device, wherein the electrical condition monitoring system includes a sensing arrangement that is configured to electrically connect the electrical conditioning monitoring system to the electrical device and to monitor the electrical device when the electrical device is in operation in the preamble just link the claim to a technological environment. The use of this language is not anything significantly more than the abstract idea, specifically because it is generally linking the use of judicial exception to a particular field of use. Thus, the claims 1, 35 and 36 are not patent eligible.
Claim 20 further recites wherein in (ii), at least one of the current or the voltage that is supplied to and/or from the electrical device is a calculated residual current or a residual voltage, and wherein the calculated residual current or residual voltage is calculated by comparing a model of predicted current with a measured current of the electrical device to generate residual current data or residual voltage data. Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgement that could be performed in the human mind or with the aid of pencil and paper therefore it falls within the “Mental Process” grouping of abstract ideas. The claim does not include any additional element, thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 21 further recites computes parameter differences between the real-time model and the one or more stored models, and to generate a predictive model describing the parameter differences to generate the information indicative of an operating condition of the electrical device. Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgement that could be performed in the human mind or with the aid of pencil and paper therefore it falls within the “Mental Process” grouping of abstract ideas. The claim does not include any additional element, thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 22 further recites generates one or more alerts relating to: (a) energy utilization and/or generation trends of the electrical device; (b) Carbon Dioxide (equivalent) generation being caused and/or saved by the electrical device; (c) maintenance, replacement or repair of the electrical device; and (d) a state of insulation of the electrical device. Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgement that could be performed in the human mind or with the aid of pencil and paper therefore it falls within the “Mental Process” grouping of abstract ideas. The claim does not include any additional element, thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 24 further recites the user interface is further configured for user entry of user defined parameters for generating a range of multivariate cells in a database of the electrical condition monitoring system and the data processing arrangement is further configured to update the sensed data of the electrical device in their respective multivariate cells, wherein the multivariate cells store the temporally-changing Fourier spectrum associated with the sensed data and the one or more stored models associated with the electrical device. The steps of "user entry of user defined parameters" and "generating a range of multivariate cells" to analyze and update data can be seen as a method of organizing human activity or a mental process that a person could theoretically perform, perhaps less efficiently, using established mathematical techniques. The user interface, as described, uses conventional components (user entry, display) at a high level of generality, which is often insufficient to overcome an abstract idea rejection. The claim does not include any additional element, thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 25 further recites compute by extrapolation and/or interpolation data for unpopulated multivariate cells from neighboring multivariate cells that are based on at least one of: voltage measurements, current measurements, frequency measurements. Extrapolation and interpolation are estimation techniques that use mathematical relationships. A claim that merely recites a mathematical formula or calculation, without more, is generally an abstract idea. The claim does not include any additional element; thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 26 further recites decimate data points in the sensed data based on calculated frequency to determine a number of relevant data points for generating the temporally-changing Fourier spectrum. Decimation (down sampling) and Fourier analysis are well-established mathematical concepts used in digital signal processing (DSP). The claim describes a process of applying these concepts to data (sensed data) to produce a result (Fourier spectrums). Performing calculations, even complex ones like Fourier transforms and decimation, is often considered an abstract idea if the claim merely involves taking data, processing it through an algorithm, and outputting new data without a specific technical application beyond data manipulation. The claim does not include any additional element, thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 27 further recites characterized in that the electrical device includes at least one of: a synchronous 1-phase electrical motor, a synchronous multi-phase electrical motor, a synchronous 3-phase electrical motor, a switched reluctance motor, a switched stepper motor, a D.C. electrical motor, a compressor, a pump, a fan, a conveyor, an agitator, a blender, a blower, a mixer, a Permanent Magnet (PM) motor, a PM generator, a power transformer, an air conditioner, a ventilator, an oven, a solar panel, a synchronous 1-phase electrical generator, a synchronous multi-phase electrical generator, a synchronous 3-phase electrical generator, a D.C. electrical generator, or a Permanent Magnet (PM) generator. This limitation is no more than generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h). The claim does not include any additional element, thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 28 further recites wherein the user interface is further configured for user entry of machine parameters describing the electrical device, and wherein the machine parameters include at least one of: a generic nominal operating voltage, a nominal operating current, a nominal supply frequency, a nominal rotational speed, a number of vanes on an impeller of the electrical device, bearing type codes of the electrical device or belt drive dimensions of the electrical device. The act of observing or determining physical parameters of an electrical device (voltage, speed, etc.) can be performed by a human mentally or using basic pen and paper methods. The data points themselves are informational in nature and, in a generic form, are mental processes or mathematical concepts. A generic user interface that merely provides fields for entering this information via a generic computer is not enough to be considered patent-eligible subject matter. The claim does not include any additional element, thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 29 further recites user interface is further configured for user entry of machine parameters describing analysis type to be executed by the data processing arrangement, wherein the analysis type allows user-setting of temporal resolution and a sensing data sample length. The act of defining parameters like "temporal resolution" and "sensing data sample length" for data analysis is a type of observation, evaluation, or judgment. These activities are considered mental processes that humans perform to manage data or organize human activity. The description of a generic UI for entering parameters does not, by itself, suggest an improvement and it is merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f); The claim does not include any additional element, thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 30 further recites user interface is further configured to allow user setting of voltage and/or current readings from the electric device at a sample rate of up to 10 Mega Hertz. Under the broadest reasonable interpretation, this limitation uses computer as a tool to perform mental process that includes an evaluation or judgement that could be performed in the human mind or with the aid of pencil and paper therefore it falls within the “Mental Process” grouping of abstract ideas. The description of a generic UI for user setting does not, by itself, suggest an improvement and it is merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f); The claim does not include any additional element, thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 31 further recites the user interface is further configured to allow user-selection for implementing D-Q phase and A-B phase transformation, computed in the data processing arrangement, of the sensed data, wherein the D-Q phase transformation transfers three-phase stator and rotor quantities into a single rotating reference frame to eliminate an effect of time-varying inductances, wherein the A-B phase transformation refers to a mathematical transformation that is implemented to simplify an analysis of a three- phase stator and rotor. Mathematical formulas and transformations are considered abstract ideas, as they can be performed mentally or with a pen and paper. The D-Q and A-B transformations, which convert three-phase quantities into a simpler reference frame, are mathematical methods for analyzing motor performance. Merely claiming the mathematical concept itself, or its automation on a general-purpose computer, would likely be found to be directed to an abstract idea. The description of a generic UI for user selection does not, by itself, suggest an improvement and it is merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f); The claim does not include any additional element, thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 32 further recites create a linear model of one or more relationships between voltage and current signals obtained from the electrical device. Under the broadest reasonable interpretation, this limitation covers mental process including an evaluation or judgement that could be performed in the human mind or with the aid of pencil and paper therefore it falls within the “Mental Process” grouping of abstract ideas. The claim does not include any additional element; thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 33 further recites compute an analysis of at least one of a numerical algorithm for Sub-Space State-Space System Identification (N4SID), a Multivariable Output Error State Space (MOESP) algorithm, a Past Outputs Multivariable Output Error State-Space (PO-MOESP) algorithm or Canonical Variate Analysis (CVA) to generate the real-time model based on the sensed data. With the broadest reasonable interpretation, the cited features contain steps people go through in their minds (or using pen and paper since it includes evaluation or judgment), or by mathematical calculation are “within the realm of abstract ideas. So, it falls under the mental process or mathematical concepts of abstract ideas. The claim does not include any additional element; thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 35 further recites calculate a magnitude of a significant local maximum identified from the family of possible local maxima corresponding to a phenomenon in the temporally-changing Fourier spectrum, generate a trend graph based on the calculated magnitude, wherein the trend graph is indicative of past, present, and extrapolated future levels corresponding to a particular fault in the electrical device, and display the trend graph in association with one or more of. (a) information related to the particular fault in the electrical device, (b) suggested faults, (c) an operating condition of the electrical device over different time periods, or (d) energy wastage due to faults in the electrical device. Calculating a magnitude from a Fourier spectrum, identifying a local maximum, generating a trend graph, and extrapolating future levels are all mathematical processes or methods of organizing human activity (e.g., data analysis). These steps can be performed by a person with a calculator and graphing paper, even if doing so manually would be inefficient. Therefore, the claim is likely an abstract idea because it describes a well-known analytical method (Fourier analysis and trend graphing) and lacks a concrete application in a specific, non-abstract way that provides an "inventive concept" to make it patent eligible. The mere association with a "particular fault in the electrical device" is a field of use, not a concrete, patent-eligible application in itself.
Claim 38 further recites wherein each multivariate cell is defined by a range of operational parameters comprising at least a load value and a speed or frequency value, and stores an average and standard deviation of parameter values corresponding to the sensed data received during operation of the electrical device. The processes described—collecting data, storing it in defined categories (cells), and performing statistical calculations (average, standard deviation)—are operations that can, in theory, be performed by a human mind or using a pencil and paper. The claim does not include any additional element; thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim 39 further recites generate a mathematical relationship across the multivariate cells in form of a multidimensional surface to estimate expected parameter values for unpopulated combinations of operational parameters. The act of creating a mathematical model or relationship (like generating a multidimensional surface to estimate parameters), is fundamentally an exercise of human thought and logic. It can be performed entirely within the human mind or with simple tools like a pen and paper. The claim as described is also "directed to" an abstract idea (the mathematical concept of generating a relationship across multivariate data). The claim does not include any additional element; thus, it does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception.
Claim Rejections - 35 USC § 103
7. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
8. Claims 19-21, 24-28, 30, 32 and 35-38 are rejected under 35 U.S.C. 103 as being unpatentable over Dowling et al. (US PAT NO: US6144924A) in view of HOSEK et al. (PUB NO: US 20140201571 A1)
Regarding claim 1, 35 and 36
Dowling teaches an electrical condition monitoring system that is connectable to an electrical device, wherein the electrical condition monitoring system includes a sensing arrangement that is configured to electrically connect the electrical the electrical conditioning monitoring system to the electrical device to monitor the electrical device when the electrical device is in operation, (see col 1 line 8-10-apparatus for evaluating motor performance and assessing motor condition while the motor is operating. see fig 1 and col 11 line 59-63 The system 10 further includes a plurality of individual sensors or probes shown collectively as 40, for monitoring predetermined electrical and mechanical variables of the motor 30 and transmission means 36)
Dowling teaches a computer program product comprising a non-transitory computer-readable storage medium having computer-readable instructions stored thereon, the computer-readable instructions being executable by a computerized device comprising processing hardware to execute the method of claim 35.(see fig 1)
wherein:
(i) the electrical condition monitoring system includes the sensing arrangement for temporally sensing an electrical supply to and/or sensing an electrical supply generated by the electrical device in case of a generator and generates corresponding sensed data by processing the sensed electrical supply to and/or from the electrical device, wherein the sensed data includes information associated with at least one of a supply of voltage or a supply of current to and/or the sensed data includes information associated with at least one of supply voltage or a supply of current from the electrical device, where the sensing arrangement comprises current sensing device to measure the supply of current and a voltage sensing device to measure the supply of voltage; (see col 3 line 1-3-sensing an instantaneous current signal supplied to the motor as a function of time for a period of time for at least one electrical phase of the motor; see fig 1 and col 11 line 59-63 The system 10 further includes a plurality of individual sensors or probes shown collectively as 40, for monitoring predetermined electrical and mechanical variables of the motor 30 and transmission means 36, and for converting the monitored characteristics into electrical signals for processing by the processor 12. See col 12 line 5-8- The current probes 42, 44, 46 can be inductive or Hall effect or any other type which converts current in a conductor into a related voltage signal. See also col 24 line 31-33- The present invention also uses the data signals collected by the current and voltage sensors 42-52 to determine motor efficiency.)
(ii) (ii) the electrical condition monitoring system includes a data processing arrangement including a data processor, wherein the data processing arrangement comprises a filtering module, a spectrum analysis module, a real-time model generation module, and a model comparison module;
(ii) the electrical condition monitoring system includes a data processing arrangement including a data processor, wherein the data processing arrangement comprises a filtering module, a spectrum analysis module, a real-time model generation module, and a model comparison module; (see fig 1 and see col 9 and 10- Referring to the drawings, wherein the same reference numerals indicate like elements throughout the Several figures, there is shown in FIG. 1 a functional Schematic block diagram of a preferred embodiment of a processor based motor monitor System 10 which operates in accordance with the methods of the present invention)
wherein the filtering module is configured to filter out changes in magnitudes and frequencies of signal harmonic components caused due to electrical distortions including switching noise; (see col 18 line 5-20-In addition, the line frequency peak and glitches are eliminated from consideration by requiring that the first three frequency lines on each side of a candidate peak be monotonically decreasing in magnitude. After elimination of false peaks, the highest peak in the range of interest is selected for each of the three spectra (i.e., Ia, Ib, Ic). Step 90 is an alternate way of eliminating broad peaks. Step 90 measures the RMS noise level to determine a noise floor in the spectra and screen out non-discrete peaks using the current spectra and the list of candidate peaks, by measuring the RMS noise level of the spectrum range and deleting spectral components within ±0.3 Hz of the peaks. In addition, any peaks whose amplitude at a point halfway to the noise floor is greater than the FFT window roll-off plus a tolerance for noise are eliminated, in order to eliminate nondiscrete signals.)
(d)perform Fast Fourier Transform (FFT), by the spectral analysis module, on the residual current data to create the temporally-changing Fourier spectrum; (see col 3 line 4-6-generating a Fourier transform on the sensed current signal over at least a portion of the period of time to provide a current signal spectra; see col 5 line 37-40 and line 40-41 -performing a Fourier Transform on the sensed current signal over at least a portion of the period of time to provide a current signal spectra; locating a peak in the current signal spectrum at a fifth harmonic of line frequency; see col 15 line 66-67 to col 16 line 1-9-All of the FFTs (of the different probe signals) are taken over the same time interval. At step 76, one probe signal is selected as a reference and then at step 78, the reference signal value is subtracted from all of the other probe data signals. Finally, in step 80, the phase deviation for each of the probes is stored (a value of zero is stored for the probe selected as the reference) in memory, such as the RAM 16. As a result of this process, the reference signal is at zero degrees, and the other probe data signals are referred to in relation to the reference signal.)
(e) identify, by the spectrum analysis module, at least one local maximum on the temporally-changing Fourier spectrum using a crawling technique to divide an entirety of the temporally-changing Fourier spectrum into local maxima joined to one another at local minima, wherein the crawling technique identifies the at least one local maximum on the temporally-changing Fourier spectrum by determining a value that increases towards the at least one local maximum or a value that decreases from the at least one local maximum; (see fig 13 and col 6 line 39-41- peak locating means for locating a maximum peak in a predetermined frequency range of the current Signal Spectra and a peak indicative of line frequency; see col 18 line 65-67 to col 19 line 1-5-In step 88, the highest spectral peak is identified using the current sensor data, and all peaks within 12 dB of the highest peak are identified as candidate peaks. Broad peaks are eliminated by requiring that for the first three frequency intervals on each side of a candidate peak, one of the intervals must show a 12 Db drop in amplitude (i.e., there must be significant roll-off from the local maxima. see col 17 line 35-60- First, at step 84, the predetermined range of speed indicating frequencies narrows down the range of the spectrum that must be examined for shaft frequency, by estimating the range of the shaft sideband frequency to be from (0 9·fsynch+fline) up to but not including (fsynch+fline). Spectral analysis is conducted at step 86 on the current data obtained from the current probes 42-46 by examining, for example, 32.768 seconds of current data. First, the DC component of the current signal is subtracted out. The DC component is calculated as the average value of the current signal over the 32,768 points. Then, a 32,768 point window, such as the Kaiser-Bessel, is applied to the current signal by multiplying the 32,768 point current signal by an equal length standard FFT window, such as the Hanning or Kaiser-Bessel. The Kaiser-Bessel window is preferred because it provides superior selectivity in the frequency domain. The FFT is calculated using a standard Cooley-Tukey algorithm and dividing the resulting spectra by N, where N is the number of points. Adjustments are then made to the amplitude to compensate for window effects. Finally, a one-sided spectrum is calculated by eliminating the negative AC frequency components, doubling all of the remaining (positive) AC components and selecting the spectral lines from DC to the folding frequency (half sampling rate) FIG. 13 shows a Simulated measurement from an induction motor operating at a power factor of 0.85.)
(f) identify, by the spectral analysis module, a significant local maximum in terms of an absolute value or number of standard deviations from a mean value; (see col 18 line 20-23- In step 92, the best shaft frequency peak in each of the three spectra is selected as the maximum amplitude of each of the peaks remaining after step 90. see col 22 line 33-50-At Step 138, winding unbalance is calculated, based on current unbalance, as: Current unbalance-Voltage unbalance, where Voltage unbalance is calculated as the maximum deviation from the mean divided by the mean multiplied by 100 and current unbalance is similarly calculated as the maximum deviation from the mean divided by the mean multiplied by 100. If the calculated winding unbalance is higher than a particular threshold, then a Stator fault is reported. In the presently preferred embodiment, if the calculated winding unbalance is greater than approximately 3.0%, than a stator fault is reported. Although a value of 3.0% is specified, an alternative method of establishing thresholds, as opposed to or in addition to using a preestablished value, is to monitor the motor system 30 for a period of time and then Setting thresholds based on standard deviation calculations for determining faults. See col 24 line 6-20-At Step 154, a comparison is made to a predetermined threshold, in the presently preferred embodiment 45 dB. If the absolute dB value is greater than or equal to the threshold then the rotor is normal, which is reported to the user at Step 156. However, if the absolute dB value is less than the threshold, execution proceeds to step 158 to examine the fifth harmonic sidebands. Sidebands around the fundamental frequency can have significant amplitude because of belt transmission and air gap asymmetries, as well as broken rotor bars. Thus the indicator is supplemented by fifth harmonic information. At Step 158, the peaks (t1 spectral line) around the following frequencies: f(5-2's) f(5- 4's) and f(5-6s) are located. A picket fence is used to calculate the true peak amplitudes and then find the highest peak of the three currents.)
and (g) label the significant local maximum with a phenomenon description in a user interface for presenting to a user. (see col 10 line 15-25-A keypad 18 is presently employed as the primary user input device to permit a user to communicate with the processor 12. The keypad 18 includes a plurality of buttons or switches for inputting information or commands. In the presently preferred embodiment, the keypad 18 includes buttons for instructing the system 10 to display previously recorded or stored data, including power data and motor condition flag histories for designated time periods, power quality data, such as per phase voltage and current data, and power conversion data, such as input power, output power and motor speed. See col 10 line 33-40-A display 20 is connected to the processor 12 for displaying output from the processor 12. The display 20 provides information to a user, such as the per phase voltage and current data, power data and motor identification information, as well as event flag information for alerting the user of a potential problem with the motor system, such as a problem with the motor rotor, the stator, current, voltage, performance, or loading.)
(iii) the electrical monitoring system includes the user interface that is configured for user entry of input for analyzing the analysis data and the data processor is configured to analyze the analysis data based on the input to obtain information indicative of an operating condition of the electrical device; (see col 10 line 15-25-A keypad 18 is presently employed as the primary user input device to permit a user to communicate with the processor 12. The keypad 18 includes a plurality of buttons or switches for inputting information or commands. In the presently preferred embodiment, the keypad 18 includes buttons for instructing the system 10 to display previously recorded or stored data, including power data and motor condition flag histories for designated time periods, power quality data, such as per phase voltage and current data, and power conversion data, such as input power, output power and motor speed. See col 10 line 33-40-A display 20 is connected to the processor 12 for displaying output from the processor 12. The display 20 provides information to a user, such as the per phase voltage and current data, power data and motor identification information, as well as event flag information for alerting the user of a potential problem with the motor system, such as a problem with the motor rotor, the stator, current, voltage, performance, or loading.)
(iv) the data processing arrangement is operable to calculate, by the spectrum analysis module, locations on the temporally- changing Fourier spectrum where the same phenomenon appears to create a family of possible local maxima; (see col 6 line 39-41- peak locating means for locating a maximum peak in a predetermined frequency range of the current Signal Spectra and a peak indicative of line frequency; see col 18 line 65-67 to col 19 line 1-5-In step 88, the highest spectral peak is identified using the current sensor data, and all peaks within 12 dB of the highest peak are identified as candidate peaks. Broad peaks are eliminated by requiring that for the first three frequency intervals on each side of a candidate peak, one of the intervals must show a 12 Db drop in amplitude (i.e., there must be significant roll-off from the local maxima).
(v) the data processing arrangement is operable to identify, by the spectrum analysis module, a significant local maximum from the family of possible local maxima corresponding to the phenomenon and to generate the analysis data from a magnitude of the significant local maximum; (see col 18 line 20-23- In step 92, the best shaft frequency peak in each of the three spectra is selected as the maximum amplitude of each of the peaks remaining after step 90.)
Dowling does not teach (a) generate a linear model, by the real-time comparison module, describing the electrical device and (b) use the linear model, by the real-time comparison module, to create a model of predicted current of the electrical device from measured voltages obtained from the electrical device; (c) compare, by the model comparison module, the model of predicted current with a measured current of the electrical device to create a residual current data (vi) the data processing arrangement is operable to access, by the model comparison module, one or more stored models of operation of the electrical device, and to compare, by the model comparison module, the real-time model with the one or more stored models to generate information indicative of an operating condition of the electrical device.
In the related field of invention, HOSEK teaches (a) generate a linear model, by the real-time generation module, describing the electrical device; (see para 20-the use of multiple linear neural network models for robot fault diagnosis, and the use of a diagnostic observer for detecting faults in a simulated electro-hydraulic actuator.)
(b) use the linear model, by the real-time comparison module, to create a model of predicted current of the electrical device from measured voltages obtained from the electrical device; (c) compare, by the model comparison module, the model of predicted current with a measured current of the electrical device to create a residual current data; (see para 277-This method assumes that there is either a set of motor current data stored a priori or there is a robot dynamic model available that can predict the motor current based on the present and past robot states. The current thus predicted is compared with the current measured at the individual motors to obtain the current residual. See para 313-The pre-processing layer calculates modeled current based on the voltage and velocity recorded; it then calculates the residual as a difference between the actual and modeled current)
(vi) the data processing arrangement is operable to access, by the model comparison module, one or more stored models of operation of the electrical device, and to compare, by the model comparison module, the real-time model with the one or more stored models to generate information indicative of an operating condition of the electrical device. (See para 197-198- The energy dissipation-based condition monitoring can be implemented in a real system in one of the following two ways: The first approach assumes that there exist move sequences that the robot repeats over an extended period of time. Such move sequences can be used as templates for health monitoring and fault diagnostics. Data on energy dissipation, torque and other motion characteristics can be measured for a normal robot and stored for future use. The second approach involves the development of a "normal" robot model, e.g., using neural networks, and using this model to compute the energy dissipation in a normal robot. This model-computed energy dissipation can be compared to the actual energy dissipation to determine if there is an increase in energy dissipation over time. The following types of faults can be detected through this approach: Disintegration of motor magnets, stator misalignment, higher connector resistance, higher belt tension, increase in friction in any of the moving components, defective ball bearings, presence of brake drag, incorrect commutation angle and malfunction of a phase. see para 484-Data obtained from a normal robot can be used to build a neural network model of the robot dynamics, and this model can be used as a reference model for health monitoring and fault diagnostics. FIG. 21 shows a comparison of model predicted Z axis torque with the actual torque.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to modify the method for evaluating and reporting motor condition and performance as disclosed by Dowling to include (a) generate a linear model, by the real-time comparison module, describing the electrical device and (b) use the linear model, by the real-time comparison module, to create a model of predicted current of the electrical device from measured voltages obtained from the electrical device; (c) compare, by the model comparison module, the model of predicted current with a measured current of the electrical device to create a residual current data (vi) the data processing arrangement is operable to access, by the model comparison module, one or more stored models of operation of the electrical device, and to compare, by the model comparison module, the real-time model with the one or more stored models to generate information indicative of an operating condition of the electrical device as taught by HOSEK in the system of Dowling for component condition monitoring and fault diagnosis having a data collection function that acquires time histories of selected variables for one or more components, a pre-processing function that calculates specified characteristics of the time histories, an analysis function for evaluating the characteristics to produce one or more hypotheses of a condition of the one or more components, a reasoning function for determining the condition of the one or more components from the one or more hypotheses, and a manager function that determines the selected variables acquired by the data collection function, triggers data processing in the pre-processing function for calculating the specified characteristics, initiates evaluation of the characteristics by the analysis function to yield the hypotheses, and triggers derivation of the component conditions by the reasoning function. (See para 0025, HOSEK)
Regarding claim 20
Dowling does not teach wherein in (ii), at least one of the current or the voltage that is supplied to and/or from the electrical device is a calculated residual current or a residual voltage, and wherein the calculated residual current or residual voltage is calculated by comparing a model of predicted current with a measured current of the electrical device to generate residual current data or residual voltage data.
However, HOSEK further teaches wherein, in (ii), at least one of the current or the voltage that is supplied to and/or from the electrical device is a calculated residual current or a residual voltage, and wherein the calculated residual current or residual voltage is calculated by comparing a model of predicted current with a measured current of the electrical device to generate residual current data or residual voltage data. (see para 277- This method assumes that there is either a set of motor current data stored a priori or there is a robot dynamic model available that can predict the motor current based on the present and past robot states. The current thus predicted is compared with the current measured at the individual motors to obtain the current residual. The residual is monitored over time and a significant drift in its value indicates the onset of a fault. A change in the current residual can be result of the following two causes. It could reflect a change in the motor physical properties such as phase angle, demagnetization or misalignment. It could also reflect a change in the external resistance to the motor rotation, that requires in a higher torque output from the motor. In addition to the torque residual, the integral of the torque residual over an entire move sequence is also monitored)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to modify the method for evaluating and reporting motor condition and performance as disclosed by Dowling to include wherein in (ii), at least one of the current or the voltage that is supplied to and/or from the electrical device is a calculated residual current or a residual voltage, and wherein the calculated residual current or residual voltage is calculated by comparing a model of predicted current with a measured current of the electrical device to generate residual current data or residual voltage data as taught by HOSEK in the system of Dowling for component condition monitoring and fault diagnosis having a data collection function that acquires time histories of selected variables for one or more components, a pre-processing function that calculates specified characteristics of the time histories, an analysis function for evaluating the characteristics to produce one or more hypotheses of a condition of the one or more components, a reasoning function for determining the condition of the one or more components from the one or more hypotheses, and a manager function that determines the selected variables acquired by the data collection function, triggers data processing in the pre-processing function for calculating the specified characteristics, initiates evaluation of the characteristics by the analysis function to yield the hypotheses, and triggers derivation of the component conditions by the reasoning function. (See para 0025, HOSEK)
Regarding claim 21
Dowling does not teach the data processing arrangement is further configured to compute parameter differences between the real-time model and the one or more stored models, and to generate a predictive model describing the parameter differences to generate the information indicative of an operating condition of the electrical device.
However, HOSEK further teaches the data processing arrangement is further configured to compute parameter differences between the real-time model and the one or more stored models, and to generate a predictive model describing the parameter differences to generate the information indicative of an operating condition of the electrical device. (see para 242-Data processing may take one of several forms. One form is system identification, which involves estimation of a set of base parameters that comprise an analytical model of the system. Another form is the development of neural network models that model either the entire system or only certain nonlinear effects that do not have analytical model. see para 402-403-The purpose of this on-demand routine is to identify the parameters of the rigid-body dynamic model of the robot or aligner. Differences in the parameters indicate changing properties of the robot (aligner) properties, often due to a developing fault. The identification process is automatic. The HMFD system commands the robot to follow predetermined trajectories and monitors the positions and torques during the robot motion. The structure of the dynamic model is selected to reflect all important mechanical components of the system and includes actuator dynamics associated with the motors of the robot. In order to achieve reliable results, the model is formulated in terms of the base parameters, and the trajectories are optimized for the resulting structure of the dynamic model.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to modify the method for evaluating and reporting motor condition and performance as disclosed by Dowling to include the data processing arrangement is further configured to compute parameter differences between the real-time model and the one or more stored models, and to generate a predictive model describing the parameter differences to generate the information indicative of an operating condition of the electrical device as taught by HOSEK in the system of Dowling for component condition monitoring and fault diagnosis having a data collection function that acquires time histories of selected variables for one or more components, a pre-processing function that calculates specified characteristics of the time histories, an analysis function for evaluating the characteristics to produce one or more hypotheses of a condition of the one or more components, a reasoning function for determining the condition of the one or more components from the one or more hypotheses, and a manager function that determines the selected variables acquired by the data collection function, triggers data processing in the pre-processing function for calculating the specified characteristics, initiates evaluation of the characteristics by the analysis function to yield the hypotheses, and triggers derivation of the component conditions by the reasoning function. (See para 0025, HOSEK)
Regarding claim 24
Dowling further teaches wherein the user interface is further configured for user entry of user defined parameters for generating a range of multivariate cells in a database of the electrical condition monitoring system and the data processing arrangement is further configured to update the sensed data of the electrical device in their respective multivariate cells, wherein the multivariate cells store the temporally-changing Fourier spectrum associated with the sensed data. (see col 2 line 10-31-The present invention provides a probe configuration for obtaining motor data and a processor for analyzing the motor data. A memory is included for storing motor data (e.g., in a database), which allows for comparisons to be made between the motor's present condition and performance and motor historical data to determine the presence of trends, and data on similar “sister” motors to ascertain normality with respect to a population of similar motors. The database accumulates knowledge about the motor, which may be sorted by load. The information provided by the present invention is useful for changing operating load, scheduling maintenance, planning for replacement, or even shutting down, as is appropriate. Furthermore, the system compares multiple motors under similar operating conditions so that comparisons can be made, which are useful, for instance, in making purchasing decisions. See col 10 line 15-25-A keypad 18 is presently employed as the primary user input device to permit a user to communicate with the processor 12. The keypad 18 includes a plurality of buttons or switches for inputting information or commands. In the presently preferred embodiment, the keypad 18 includes buttons for instructing the system 10 to display previously recorded or stored data, including power data and motor condition flag histories for designated time periods, power quality data, such as per phase voltage and current data, and power conversion data, such as input power, output power and motor speed. See col 26 line 66-67 to col 27 line 1-3-Distributions are calculated for a population of each type of motor for each load interval for which there is enough data to make a meaningful comparison.)
Dowling does not teach wherein the multivariate cells store the one or more stored model associated with electrical device.
However, HOSEK further teaches wherein the multivariate cells store the one or more stored model associated with electrical device. (See fig 2 (element 220) para 197-198- The energy dissipation-based condition monitoring can be implemented in a real system in one of the following two ways: The first approach assumes that there exist move sequences that the robot repeats over an extended period of time. Such move sequences can be used as templates for health monitoring and fault diagnostics. Data on energy dissipation, torque and other motion characteristics can be measured for a normal robot and stored for future use. The second approach involves the development of a "normal" robot model, e.g., using neural networks, and using this model to compute the energy dissipation in a normal robot. This model-computed energy dissipation can be compared to the actual energy dissipation to determine if there is an increase in energy dissipation over time. The following types of faults can be detected through this approach: Disintegration of motor magnets, stator misalignment, higher connector resistance, higher belt tension, increase in friction in any of the moving components, defective ball bearings, presence of brake drag, incorrect commutation angle and malfunction of a phase. see para 240- A majority of the faults are characterized by changes in values of two or more physical characteristics which are strongly correlated to each other. In such cases, the Hotelling's T-square statistic will used as the performance metric to detect sudden changes. To detect slow drifts in a multivariate framework, the Multivariate EWMA charts will be used. Both of these methods yield a single scalar quantity which is a measure of the square of the deviation from the nominal and accounts for the covariance between variables in a multivariate framework.)
Regarding claim 25
Dowling further teaches wherein the data processing arrangement is further configured to compute by extrapolation and/or interpolation data for unpopulated multivariate cells from neighboring multivariate cells that are based on at least one of: voltage measurements, current measurements, frequency measurements. (see col 26 line 29-36-The present invention, via software, reduces the volume of data collected by the monitor system 10 (or any online motor monitor system), by first categorizing the data by load. In the preferred embodiment the data is segregated into 5% (of load) intervals. The data within each of these intervals is characterized by a small set of parameters: mean value, standard deviation, skew, kurtosis, max, min, number of observations, and upper and lower confidence limits. See col 26 line 66-67 to col 27 line 1-3-Distributions are calculated for a population of each type of motor for each load interval for which there is enough data to make a meaningful comparison. Motors outside of the distribution are identified and highlighted to warn the user of an anomalous, possibly dangerous situation. see also col 15 and line 1-6- the Sampled digital data received from the electrical and mechanical Sensors 40 in a manner hereinafter described and generates highly accurate outputs in the form of discrete data or plots of data versus time (traces) corresponding to particular electrical and mechanical parameters from which specific problems and faults can be identified)
Regarding claim 26
Dowling further teaches wherein the data processing arrangement is further configured to decimate data points in the sensed data based on calculated frequency to determine a number of relevant data points for generating the temporally-changing Fourier spectrum. (see col 27 line 13-34-The present invention provides a default configuration for the motor 30, so that the user is not necessarily required to enter any set up information. After the three current probes 42-46 and the three voltage probes 48-52 are connected, a plurality of signal samples are collected, for instance 200 samples from each sensor 42-52. The DC component is eliminated from each data signal and a threshold is defined. In the preferred embodiment, the threshold is defined by requiring that the peak voltage and current in any data signal be at least half the peak voltage or current of the data signal with the greatest peak voltage or current. If the threshold is not met, the system 10 informs the user of a faulty voltage or current connection, as appropriate. Each of the (six) data signals is then band-limited, demodulated, and a phasor for each signal is calculated. The signals are bandlimited by a low pass filter and demodulated by performing a time domain Hilbert demodulation. That is, the analytic signal is formed from the original signal as the real part and the Hilbert transform as the quadrature part. To avoid end effects resulting from filtering and demodulation, the first and last 50 points of the in-phase and quadrature components are eliminated. see col 26 line 29-36-The present invention, via software, reduces the volume of data collected by the monitor system 10 (or any online motor monitor system), by first categorizing the data by load)
Regarding claim 27
Dowling further teaches wherein the electrical device includes at least one of: a synchronous 1-phase electrical motor, a synchronous multi-phase electrical motor, a synchronous 3-phase electrical motor, a switched reluctance motor, a switched stepper motor, a D.C. electrical motor, a compressor, a pump, a fan, a conveyor, an agitator, a blender, a blower, a mixer, a Permanent Magnet (PM) motor, a PM generator, a power transformer, an air conditioner, a ventilator, an oven, a solar panel, a synchronous 1-phase electrical generator, a synchronous multi-phase electrical generator, a synchronous 3-phase electrical generator, a D.C. electrical generator, or a Permanent Magnet (PM) generator. (See FIG. 1 is a functional Schematic block diagram of a preferred embodiment of a System for analysis of a three phase motor in accordance with the present invention; see col 33 line 12-17-Referring now to FIG. 12, a phasor bar 300 in accordance with the present invention is shown illustrating the per-phase Voltages and currents of a Synchronous motor at 0 leading or capacitate power factor.)
Regarding claim 28
Dowling further teaches wherein the user interface is further configured for user entry of machine parameters describing the electrical device, and wherein the machine parameters include at least one of: nominal operating voltage, nominal operating current, nominal supply frequency, nominal rotational speed, number of vanes on an impeller of the electrical device, bearing type codes of the electrical device or belt drive dimensions of the electrical device. (See col 10 line 15-30-A keypad 18 is presently employed as the primary user input device to permit a user to communicate with the processor 12. The keypad 18 includes a plurality of buttons or switches for inputting information or commands. The keypad 18 includes buttons for instructing the system 10 to display previously recorded or stored data, including power data and motor condition flag histories for designated time periods, power quality data, such as per phase voltage and current data, and power conversion data, such as input power, output power and motor speed. The keypad 18 also preferably includes one or more buttons related to motor identification information)
Regarding claim 30
Dowling further teaches wherein the user interface is further configured to allow user setting of voltage and/or current readings from the electric device at a sample rate of up to 10 Mega Hertz. (see col 13 line 27-36- The system 10 further includes a plurality of individual analog-to-digital (A/D) converters 64 shown collectively in FIG. 1. The A/D converters 64 function in a manner well known in the art to receive the conditioned and filtered analog output signals from the corresponding signal conditioner 62 and convert the received analog signals at a predetermined sampling rate into digital signals (i.e., a stream or array of digital data) for data manipulation and analysis by the processor 12. A typical sampling rate could be 1,000 samples per second for each signal.)
Regarding claim 32
Dowling does not teach wherein the data processing arrangement is further to create a linear model of one or more relationships between voltage and current signals obtained from the electrical device.
However, HOSEK further teaches wherein the data processing arrangement is further configured to create a linear model of one or more relationships between voltage and current signals obtained from the electrical device. (See para 20- the use of multiple linear neural network models for robot fault diagnosis, and the use of a diagnostic observer for detecting faults in a simulated electro-hydraulic actuator. See para 424-The following faults can be identified using this approach: weakening of motor magnets, play in motor bearings. In addition, the motor winding resistance can also be derived from the measured current and voltage using the voltage-current relationship above.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to modify the method for evaluating and reporting motor condition and performance as disclosed by Dowling to include wherein the data processing arrangement is further configured to create a linear model of one or more relationships between voltage and current signals obtained from the electrical device as taught by HOSEK in the system of Dowling for component condition monitoring and fault diagnosis having a data collection function that acquires time histories of selected variables for one or more components, a pre-processing function that calculates specified characteristics of the time histories, an analysis function for evaluating the characteristics to produce one or more hypotheses of a condition of the one or more components, a reasoning function for determining the condition of the one or more components from the one or more hypotheses, and a manager function that determines the selected variables acquired by the data collection function, triggers data processing in the pre-processing function for calculating the specified characteristics, initiates evaluation of the characteristics by the analysis function to yield the hypotheses, and triggers derivation of the component conditions by the reasoning function. (See para 0025, HOSEK)
Regarding claim 37
Dowling further teaches calculate a magnitude of a significant local maximum identified from the family of possible local maxima corresponding to a phenomenon in the temporally-changing Fourier spectrum, (see col 18 line 20-23- In step 92, the best shaft frequency peak in each of the three spectra is selected as the maximum amplitude of each of the peaks remaining after step 90.)
generate a trend graph based on the calculated magnitude, wherein the trend graph is indicative of past, present, and extrapolated future levels corresponding to a particular fault in the electrical device, and display the trend graph in association with one or more of. (a) information related to the particular fault in the electrical device, (b) suggested faults, (c) an operating condition of the electrical device over different time periods, or (d) energy wastage due to faults in the electrical device. (see col 26 line 37-55- observations, and upper and lower confidence limits. Key Statistical information resulting from the above data reduction process is Saved and trended, i.e., plotted against time, to determine non-Zero Slope. While a periodic one-time analysis can detect Serious problems for a short time span recorded during motor operation, historical trending can provide advanced warning of impending problems. By recording accurate measurements at different times and plotting the resulting records over time or otherwise automatically. Searching for trends over time, patterns can be detected that indicate a particular parameter is degrading or changing, indicating an impending fault condition while the motor is still operating within acceptable limits. Thresholds are established and if a trend develops that either crosses the threshold or is approaching a threshold, the user is warned of a developing problem. By using the techniques of the present invention, motor faults are detected when they are too Small to be of concern, and trended, so that if getting worse, the point at which an operator will want to take a corrective measure can be projected. See col 10 line 33-40- A display 20 is connected to the processor 12 for displaying output from the processor 12. The display 20 provides information to a user, such as the per phase Voltage and current data, power data and motor identification information, as well as event flag information for alerting the user of a potential problem with the motor System, such as a problem with the motor rotor, the stator)
Regarding claim 38
Dowling further teaches wherein each multivariate cell is defined by a range of operational parameters comprising at least a load value and a speed or frequency value, and stores an average and standard deviation of parameter values corresponding to the sensed data received during operation of the electrical device. (see col 9 line 60-67- Preferably the processor 12 includes or has access to a memory, which preferably includes a read only memory (ROM) 14 employed for storing fixed information, such as executable processor code and/or fixed data parameters or parameter ranges, and a random access memory (RAM) 16 of a predetermined size which is adapted for temporary storage of data accumulated for analysis. See col 16 line 25-36- When sensors are employed in which the phase shift or Sensitivity is a function of frequency or current amplitude, this effect is compensated for by either determining the functional relationship between the dependent and independent parameter (for example, effect of frequency, the independent parameter, on-phase shift, the dependent parameter) and adjusting the phase values in accordance with measured line frequency or by creating a table relating the correction to the independent parameter, and looking up the appropriate correction for each case of the independent parameter in the table (e.g., a look-up table stored in memory such as the RAM 16). see col 26 line 29-36-The present invention, via software, reduces the volume of data collected by the monitor system 10 (or any online motor monitor system), by first categorizing the data by load. In the preferred embodiment the data is segregated into 5% (of load) intervals. The data within each of these intervals is characterized by a small set of parameters: mean value, standard deviation, skew, kurtosis, max, min, number of observations, and upper and lower confidence limits.)
9. Claim 22 is rejected under 35 U.S.C. 103 as being unpatentable over Dowling et al. (US PAT NO: US6144924A) in view of HOSEK et al. (PUB NO: US 20140201571 A1) and further in view of Mortazavizadeh et al ("A review on condition monitoring and diagnostic techniques of rotating electrical machines." Physical Science International Journal 4.3 (2014): 310.)
Regarding claim 22
Dowling further teaches wherein the data processing arrangement generates one or more alerts relating to:
(a) energy utilization and/or generation trends of the electrical device; (see col 10 line 34-40-The display 20 provides information to a user, such as the per phase voltage and current data, power data and motor identification information, as well as event flag information for alerting the user of a potential problem with the motor system, such as a problem with the motor rotor, the stator, current, voltage, performance, or loading. )
(c) maintenance, replacement or repair of the electrical device; (see col 15 line 5-12-In addition, the present invention automatically detects such faults and indicates same to the user in high-level text messages, such as “stator winding fault”. Only the particular identified problem(s) need then be repaired, be it on the motor 30, transmission 36, or load 38, thereby saving the cost of a complete motor system overhaul)and
However, the combination of Dowling and HOSEK does not teach generate one or more alerts relating to: (b) Carbon Dioxide (equivalent) generation being caused and/or saved by the electrical device; (d) a state of insulation of the electrical device.
In the related field of invention, Mortazavizadeh teaches generates one or more alerts relating to: (b) Carbon Dioxide (equivalent) generation being caused and/or saved by the electrical device; (d) a state of insulation of the electrical device. (see page 322 and section 2.3-Insulation degradation can be monitored chemically by the presence of special matter in the coolant gas or by detection some particular gases such as ozone, carbon monoxide or even more complex hydrocarbons, like acetylene and ethylene. Electrical discharge activity heat and some other electrical and mechanical faults may lead to insulation degradation. The product materials can be gas, liquid or solid. Each of them needs a particular detection method)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to modify the method for evaluating and reporting motor condition and performance as disclosed by Dowling to include generate one or more alerts relating to: (b) Carbon Dioxide (equivalent) generation being caused and/or saved by the electrical device; (d) a state of insulation of the electrical device as taught by Mortazavizadeh in the system of Dowling and HOSEK in order to determine the conditions of each part of motor, various testing and monitoring methods have been developed. A motor failure may yield an unexpected interruption at the industrial plant, with consequences in costs, product quality, and safety. (see Abstract, Mortazavizadeh)
10. Claim 29 is rejected under 35 U.S.C. 103 as being unpatentable over Dowling et al. (US PAT NO: US6144924A) in view of HOSEK et al. (PUB NO: US 20140201571 A1) and further in view of Reed et al. (PUB NO: US 2018/0136449 A1)
Regarding claim 29
The combination of Dowling and HOSEK does not teach wherein the user interface is further configured for user entry of machine parameters describing analysis type to be executed by the data processing arrangement, and wherein the analysis type allows user-setting of temporal resolution and a sensing data sample length.
In the related field of invention, Reed teaches wherein the user interface is further configured for user entry of machine parameters describing analysis type to be executed by the data processing arrangement, wherein the analysis type allows user-setting of temporal resolution and a sensing data sample length. (see para 006- Also disclosed herein are systems for temporal compressive sensing, comprising: an algorithm that calculates the time slice datasets from the one or more measurement datasets captured for each data acquisition period and the series of coefficients; thereby generating a series of time slice datasets for each of the one or more data acquisition periods that has a time resolution exceeding the time resolution determined by the length of the data acquisition period. see para 47- For example, in some embodiments, the experimental parameter to be temporally modulated may be selected from the group consisting of rotational orientation of the sample, linear translation and/or tilt of the electron probe in one dimension, linear translation and/or tilt of the electron probe in two dimensions, linear translation of the sample in one dimension, linear translation of the sample in two dimensions, and linear translation of the sample in three dimensions, or any combination thereof. In some embodiments, the radiation incident on the sample (or scene) is focused to a narrow beam (i.e., having a beam diameter that is small relative to the cross-sectional area of the sample or scene to be imaged or analyzed) and the experimental parameter to be temporally modulated is the position of the beam relative to the sample (or vice versa).)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to modify the method for evaluating and reporting motor condition and performance as disclosed by Dowling to include wherein the user interface is further configured for user entry of machine parameters describing analysis type to be executed by the data processing arrangement, wherein the analysis type allows user-setting of temporal resolution and a sensing data sample length as taught by Reed in the system of Dowling and HOSEK for temporal compressive sensing are disclosed, where within each of one or more sensor array data acquisition periods, one or more sensor array measurement datasets comprising distinct linear combinations of time slice data are acquired, and where mathematical reconstruction allows for calculation of accurate representations of the individual time slice datasets.. (see Abstract, Reed)
11. Claim 31 is rejected under 35 U.S.C. 103 as being unpatentable over Dowling et al. (US PAT NO: US6144924A) in view of HOSEK et al. (PUB NO: US 20140201571 A1) and further in view of Schad et al. ("Permanent Magnet Synchronous Motor Variable Frequency Drive System." International Foundation for Telemetering, 2017.)
Regarding claim 31
Dowling further teaches wherein the user interface is further configured to allow user-selection for implementing A-B phase transformation, computed in the data processing arrangement, wherein the A-B phase transformation refers to a mathematical transformation that is implemented to simplify an analysis of a three- phase stator and rotor. (see table 1 and col 5 line 14-28- comparing the real power for each of the three electrical phases and selecting two phases having the highest real power consumption; an determining a motor phase having a stator fault, wherein for a motor sequence of ABC, if the two selected phases are A and B, then the phase with the stator fault is phase A, if the two selected phases are B and C, then the phase with the stator fault is phase B, and if the two selected phases are A and C, then the phase with the stator fault is phase C, and for a motor sequence of ACB, if the two selected phases are A and B, then the phase with the stator fault is phase A, if the two selected phases are B and C, then the phase with the stator fault is phase B, and if the two selected phases are A and C, then the phase with the stator fault is phase C.)
However, the combination of Dowling and HOSEK does not teach wherein the user interface is further configured to allow user-selection for implementing D-Q phase computed in the data processing arrangement, of the sensed data, wherein the D-Q phase transformation transfers three-phase stator and rotor quantities into a single rotating reference frame to eliminate an effect of time-varying inductances.
In the related field of invention, Schad teaches wherein the user interface is further configured to allow user-selection for implementing D-Q phase computed in the data processing arrangement, of the sensed data, wherein the D-Q phase transformation transfers three-phase stator and rotor quantities into a single rotating reference frame to eliminate an effect of time-varying inductances. (see page 8-The Park transformation is next adopted in order to completely eliminate the effect of time-varying inductances, by combining all stator and rotor quantities into single rotating reference frame. The Park operation transforms the two-axis orthogonal stationary reference frame quantities into rotating reference frame quantities. Similar to jumping onto a merry go round before taking photos of a subject, the transform jumps the αβ stator field reference on the rotating frame of the rotor field, resulting in a two phase DQ system)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to modify the method for evaluating and reporting motor condition and performance as disclosed by Dowling to include wherein the user interface is further configured to allow user-selection for implementing D-Q phase computed in the data processing arrangement, of the sensed data, wherein the D-Q phase transformation transfers three-phase stator and rotor quantities into a single rotating reference frame to eliminate an effect of time-varying inductances as taught by Schad in the system of Dowling and HOSEK in order to discuss a permanent magnet synchronous motor (PMSM) variable frequency drive (VFD) system developed for an all-terrain Wifi-HaLow connected (802.11ah, 900 MHz) modular electric vehicle that competed in the Mars University Rover Challenge (URC). The quadrature axis flux linkage for each motor was estimated using on-board voltage and current measurements. A synchronous control algorithm tracked the electromagnetic operating parameters, which are highly dependent on variations in motor construction and load conditions. A feed-forward model-driven observer solution calculated flux linkage angles by direct-quadrature-zero transformation of three phase shunt currents using DSP processors.. (see Abstract, Schad)
12. Claim 33 is rejected under 35 U.S.C. 103 as being unpatentable over Dowling et al. (US PAT NO: US6144924A) in view of HOSEK et al. (PUB NO: US 20140201571 A1) and further in view of Lalimore (PUB NO: US 20140372091 A1)
Regarding claim 33
The combination of Dowling and HOSEK does not teach wherein the data processing arrangement is further configured to compute an analysis of at least one of a numerical algorithm for Sub-Space State-Space System Identification (N4SID), a Multivariable Output Error State Space (MOESP) algorithm, a Past Outputs Multivariable Output Error State-Space (PO-MOESP) algorithm or Canonical Variate Analysis (CVA) to generate the real-time model based on the sensed data.
In the related field of invention, Lalimore teaches wherein the data processing arrangement is further configured to compute an analysis of at least one of a numerical algorithm for Sub-Space State-Space System Identification (N4SID), a Multivariable Output Error State Space (MOESP) algorithm, a Past Outputs Multivariable Output Error State-Space (PO-MOESP) algorithm or Canonical Variate Analysis (CVA) to generate the real-time model based on the sensed data. (see para 007- A method and system for forming a dynamic model for the behavior of machines from sensed data. The method and system can include observing, with at least one sensor, a machine in operation; recording data from the at least one sensor about at least one characteristic of the machine in operation; fitting an input-output N(ARX)-LPV dynamic model to the recorded machine data; utilizing a CVA-(N)LPV realization method on the dynamic model; constructing a dynamic state space (N)LPV dynamic model based on the utilization of the CVA-(N)LPV realization method; generating a dynamic model of machine behavior; and at least one of controlling and modifying machine dynamic response characteristics based upon the generated dynamic model of machine behavior.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to modify the method for evaluating and reporting motor condition and performance as disclosed by Dowling to include wherein the data processing arrangement is further configured to compute an analysis of at least one of a numerical algorithm for Sub-Space State-Space System Identification (N4SID), a Multivariable Output Error State Space (MOESP) algorithm, a Past Outputs Multivariable Output Error State-Space (PO-MOESP) algorithm or Canonical Variate Analysis (CVA) to generate the real-time model based on the sensed data as taught by Reed in the system of Dowling and HOSEK for obtaining a dynamic model from a set of data which may include outputs and inputs together with machine structure and operation conditions may be referred to as a realization method or algorithm. It may further be viewed as a transformation on observed data about the machine state and operating condition to a dynamic model describing the machine behavior that can entail various combinations of machine structure, operating conditions, past outputs and inputs, and any resulting future outputs so as to be able to predict future behavior with some fidelity. (see para 0029, Lalimore)
13. Claim 39 is rejected under 35 U.S.C. 103 as being unpatentable over Dowling et al. (US PAT NO: US6144924A) in view of HOSEK et al. (PUB NO: US 20140201571 A1) and further in view of Bazzi et al. (PUB NO: US20170346433A1)
Regarding claim 39
The combination of Dowling and HOSEK does not teach wherein the data processing arrangement is further configured to generate a mathematical relationship across the multivariate cells in form of a multidimensional surface to estimate expected parameter values for unpopulated combinations of operational parameters.
In the related field of invention, Bazzi teaches wherein the data processing arrangement is further configured to generate a mathematical relationship across the multivariate cells in form of a multidimensional surface to estimate expected parameter values for unpopulated combinations of operational parameters.(see para 15-18-In some embodiments, generating the three-dimensional surface model can include applying a quadratic and linear locally weighted scatterplot smoothing (LOWESS) on the measured data for the motor drive under stator flux weakening operation. In some embodiments, generating the three-dimensional surface model can include applying a cubic interpolation on the measured data for the motor drive under a slightly weakened flux operation. The three-dimensional surface model generated with the cubic interpolation can result in a maximum-efficiency stator flux of the motor drive. In some embodiments, generating the three-dimensional surface model can include applying a polynomial interpolation on the measured data for the motor drive under a rated flux operation. In some embodiments, generating the three-dimensional surface model can include applying a linear interpolation on the measured data. Although discussed and illustrated as a three-dimensional surface model, in some embodiments, the surface model can be greater than three dimensions. The three-dimensional surface model can estimate an efficiency of the motor drive at the control parameter and at unmeasured load values. The processing device can be configured to determine an optimal efficiency of the motor drive for the different load values and the unmeasured load values based on the three-dimensional surface model. The processing device can be configured to adjust operation of the motor drive in real-time to perform at estimated configurations in response to load values based on the three-dimensional surface model. see also para 38-40 and fig 18)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to modify the method for evaluating and reporting motor condition and performance as disclosed by Dowling to include wherein the data processing arrangement is further configured to generate a mathematical relationship across the multivariate cells in form of a multidimensional surface to estimate expected parameter values for unpopulated combinations of operational parameter as taught by Bazzi in the system of Dowling and HOSEK for optimizing operation efficiency of a motor drive and, in particular, to systems and methods including behavioral modeling of the loss or efficiency of the motor drive to accurately determine optimal performance of the motor drive. (see para 0002, Bazzi)
Conclusion
12. Claims 19-22, 24-33 and 35-39 is/are rejected.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US 20200088795 A1 KASSAB
Discussing the method for monitoring the performance of electric motors, in particular, a method for monitoring the performance of multi-phase electric motors that have stator windings connected in a wye configuration.
US 20150293177 A1 Ottewill et al.
Discussing the method for diagnosing the state of electromechanical systems in which electrical rotating machinery is used on the basis of analysis of impedance estimated from current and voltage, measured during an operation of the electromechanical system.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/PURSOTTAM GIRI/Examiner, Art Unit 2186
/RENEE D CHAVEZ/Supervisory Patent Examiner, Art Unit 2186