DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This office action is in response to application number 18/178,309 filed on 11/19/2023, in which
Claims 1-20 are presented for examination. Applicant amends Claims 1-2, 4-8, 11, 15, cancels Claims 12 and 16, and adds new Claims 19 and 20.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 6/12/2023 and the information disclosure statement (IDS) submitted on 5/28/2024 have been received and considered by the examiner.
Response to Arguments
Applicant’s arguments, see pgs. 2 and 18-19, filed 11/19/2025, with respect to the objections to the drawing have been fully considered but are not fully persuasive. The objections for FIGs. 1-3 for unclear or missing labels and one remaining instance of reference character 120 missing on pg. 12, para 0057 are maintained. The remaining objections to the drawing set forth in the office action of 8/20/2025 have been withdrawn.
Applicant’s arguments, see pgs. 3-11 and 19, filed 11/19/2025, with respect to the objections to the specification and abstract have been fully considered and are persuasive. The objections to the specification of 8/20/2025 have been withdrawn.
Applicant’s arguments, see pgs. 13-17 and 19, filed 11/19/2025, with respect to the objections to the claims have been fully considered and are persuasive. The objections to the claims set forth in the office action of 8/20/2025 have been withdrawn. However, in light of the new Claims 19 and 20 updated objections are made. Further details are provided below.
Applicant’s arguments, see pgs. 19-20, filed 11/19/2025, with respect to the rejection of Claims 1-18 under 35 U.S.C. 112(b) have been fully considered and are persuasive. The rejection of Claims 1-18 under 35 U.S.C. 112(b) set forth in the office action of 8/20/2025 have been withdrawn. However, new Claims 19 and 20 introduce new rejections under 35 U.S.C. 112(b) and an additional rejection, for Claim 17, under 35 U.S.C. 112(b) is included for clarity. Further details are provided below.
Applicant’s arguments, see pg. 20, filed 11/19/2025, with respect to the rejection of Claim 16 under 35 U.S.C. 112(d) have been fully considered and are persuasive. The rejection of Claim 16 under 35 U.S.C. 112(d) set forth in the office action of 8/20/2025 has been withdrawn.
Applicant’s arguments, see pg. 20-23, filed 11/19/2025, with respect to the rejection of Claim 1-10 under 35 U.S.C. 103 have been fully considered and are persuasive. The rejection of Claims 1-10 under 35 U.S.C. 103 set forth in the office action of 8/20/2025 has been withdrawn. A summary of the allowable subject matter is provided below. Applicant’s arguments, see pg. , filed 11/19/2025, with respect to the have been fully considered but are not persuasive.
Applicant argues that to monitor each device individually Dister relies on each device having a unique vibrational characteristic and does not teach or make obvious combining multiple bearings having the same type into groups and associating a deconstructed signal to that group as a whole. Applicant further argues that Dister teaches away from allowing a component signal to be associated with a group of multiple bearings by disclosing ways to distinguish individual elements. And further, Dister does not disclose a system that can deconstruct a bulk signal that results in signals which can be associated with an entire group of multiple bearings having the same type.
Examiner respectfully disagrees. Claim 11, unlike Claim 1, only broadly recites monitoring the health of a plurality of bearing groups and associating component signals to a corresponding bearing group, including two or more bearings sharing at least one attribute, without specifying any combinations of bearing groups and component signals. Dister, [col 4, lines 54-67], does discuss that their system can analyze vibration data of a machine where the machine includes vibrating components, such as a bearing, where the vibration data can identify the health of the machine and any degradation to a component needing replacement. Dister, [col 1, lines 31-65], also sates that a total vibration is the sum of the vibration of its elements including bearings and other components, such as a shaft or rotational element that has at least two bearings which may be identical. Dister, [col 12, lines 35-50], further explains that although the invention is primarily intended for ball bearings of a bearing, it can also be used to identify “defects among bearings or other vibration generating components that are identical.” Finally, although Dister can distinguish as specifically as an individual bearing, Dister [col 2], explains that the invention narrows the vibration transmission path to an associated component, which can be any type of vibrating component, and as stated earlier includes a bearing or a shaft with two identical bearings.
Therefore, in light of the amendments, an updated rejection under 35 U.S.C. 103 is provided for Claims 11, 13-15, and 17-18. In light of the new claims, a new rejection under 35 U.S.C. 103 is provided for Claims 19 and 20. Further details are provided below.
Drawings
The drawings are objected to because:
FIGs. 1-3, pg. 8, para 0046: “processor 100,” “memory unit 104,” “sensors 108,” and “user interface 112” are not clearly labeled or indicated, with representative shapes, and could be more clear or labeled and
FIG. 4/5, pg. 12, para 0057: “bearing frequency 120” (one instance remaining).
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Objections
Claims 19 and 20 are objected to because of the following informalities:
Claim 19 (lines 2-3 and 4) and Claim 20 (lines 2-3 and 4) recite “compiling the at least one component signal over a predetermined period of time to produce a compiled data set” and “monitoring the at least one component signal over time to produce a compiled data set.” There is insufficient explanation of what “[compiling/monitoring] the at least one […] signal [over time]” and “compiled data set” refers to and instead should be explicitly stated or more clearly described. The specification [pgs. 13-14, para 0062] supports collecting data from at least one baler, or compiling data from multiple balers, over time to map anticipated wear of a bearing type or group over time, where the data is vibration data and compared to a model or rate, and where [pg. 11, para 0052] the data could be deconstructed into component signals. Therefore, for examination purposes the claims will be interpreted as compiling vibration data over time, from one or multiple balers, and comparing the compiled dataset that could be deconstructed into a signal, against a model or rate.
Appropriate correction is required.
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 17 and 19 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.
Claim 1 recites the limitation "the X, Y, and Z axis.” There is insufficient antecedent basis for this limitation in the claim.
Claim 19 (line 4) recites the limitation "the anticipated life cycle.” There is insufficient antecedent basis for this limitation in the claim.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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 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.
Claims 11, 13-15, and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Monteyne, PG Pub US-2020/0093067-A1 (herein "Monteyne"), in view of Dister et al., Patent No. US-6,053,047-A (herein "Dister").
Regarding Claim 11, Monteyne discloses: […] in a baler having a frame and a vibrational power within the frame. See [Monteyne, FIG. 1 and pg. 5, paras 0076-0078 and pg. 6, para 0100], which describe the vibration sensor mounted to the frame used to monitor the frequency relating to the baler wrapping operations, "[0076] One embodiment of such a sensor is illustrated in FIG. 1. [0077] In FIG. 1 an acoustic or vibration sensor such as (but not limited to) a microphone or other sensor 31 is capable of generating an electrical or electronic output signal on detection of a change in a waveform such as that resulting from the presence of the protrusions described above, the waveform arising as the rollers 18a-18d and/or the belt 19 move during wrapping operations. [0078] Microphone or sensor 31 is illustrated secured to the interior front wall of the bale-forming chamber 17 but it could be located at a variety of alternative places on or in the baler 10. […] or it could be a vibration detector that is activated by oscillation of the part of a frame, or machine frame member, forming part of the baler 10 and to which it is secured" and "[0100] As explained, in embodiments of the invention in which the microphone/sensor 31 is positioned to be activated by vibration or oscillation of the machine frame 11 or a member forming part of the machine frame, a degree of filtering of the waveforms detected by the microphone/sensor 31 occurs." See also [Monteyne, pg. 5, paras 0079-0080], which explains that the vibration sensor is coupled to a processor, "[0079] The microphone/sensor 31 is operatively connected to a processor and/or electronic circuit represented schematically by numeral 32. The processor/circuit 32 may take a variety of forms as will occur to the person of skill in the art. […]. [0080] FIG. 1 shows the microphone/sensor 31 connected by a cable to the processor/circuit 32, but various other connection methods, including wireless connection methods, are possible within the scope of the invention." Finally see [Monteyne, pg. 6, para 0094], which explains that the system can include detectors for frequency, "[…] other waveform parameters, such as but not limited to frequency or phase, may be detected and used as indicators of successful or unsuccessful bale wrapping. Such embodiments may include components or sub-systems such as spectrum or frequency detectors or analysers; or phase detectors."
Monteyne does not explicitly disclose: (Currently Amended) A method of monitoring a health of a plurality of bearing groups […] an accelerometer […], the method comprising: […] deconstructing the bulk signal into two or more component signals; associating at least one of the component signals with a corresponding bearing group including two or more bearings having at least one shared attribute; comparing the at least one component signal to a corresponding set of operational parameters; and outputting an alert However, [Monteyne, pg. 6, para 0094], does explain that the system can include detectors for frequency and further [Monteyne, pgs. 6-7, paras 0101-0105] uses a filter to process the vibration data.
However, Dister teaches: […] an accelerometer [fixedly coupled to the frame . See [Dister, col 2, lines 25-32], which explains a vibration sensor is mounted to the machine, "To measure and analyze the above-mentioned increase in amplitude, the present invention includes a diagnostic system having a vibration sensor mounted on a machine to sense vibrations and an electronic device called a diagnostic module, operatively couple to the vibration sensor, to evaluate the vibrations. Vibration signals from the sensor are sent to the diagnostic module which has software for processing and analyzing the vibration signals" and [Dister, col 6-7, lines 60-67 and 1-22], which explains that a vibration sensors is mounted to collect vibration data, where the vibration sensor is an accelerometer, "At least one vibration sensor is mounted on the motor 14 to monitor its operation and to collect vibration data from the motor 14. An accelerometer is used as the vibration sensors in the preferred embodiment, however, other types of vibration sensors may be used. […]. Since accelerometers sense vibration primarily in one direction, a plurality of accelerometers generally is desirable to detect the vibrations generated in different directions and in different parts of some equipment. Thus, a vibration sensor as described herein may include more than one accelerometer in order to sense all significant vibration directions. […]. In the preferred embodiment, the motor 14 is equipped with an accelerometer 80 for taking sampled vibration data relating to the operation of the motor 14. As shown in FIGS. 1 and 2, a three-axis accelerometer 80 is located near a load side 84 of the motor 14. It will be appreciated that the accelerometer may alternatively be located elsewhere on the motor 14 […]. […]. However, the invention may be carried out with one or more two-axis and/or single-axis accelerometers."
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the invention, to use the accelerometer of Dister in place of the vibration sensor of Monteyne. As taught by Dister, an accelerometer is a known type of vibration sensor, which can be used to measure in either one-, two-, or three-axis directions [Dister, col 6-7, lines 60-67 and 1-22]. Doing so would be technically feasible, with no inventive effort. Furthermore, the resulting system, using an accelerometer, would yield predictable results since an accelerometer is a type of vibration sensor.
Dister further teaches: (Currently Amended) A method of monitoring a health of a plurality of bearing groups […] the method comprising: […] deconstructing the bulk signal into two or more component signals; associating at least one of the component signals with a corresponding bearing group including two or more bearings having at least one shared attribute; […]. See [Dister, col 1, lines 5-11], which explains that the system is used for diagnostic the health of machine, "The invention described below generally relates to a system for diagnosing the health of a dynamoelectric machine, and more particularly, to a system and method for analyzing vibration signatures to predict and to detect changes in the condition of various parts of a dynamoelectric machine" and [Dister, col 1, lines 46-59], which explains that the health is monitored using the vibration signals of the components, which can include the bearings, "A machine's vibration signature is composed of the sum of the vibration signals produced by and/or transmitted through each component of the machine. The vibration signals produced by a component include forcing frequencies that vary with the rotational speed of the machine. For example, the forcing frequencies for a bearing include those of the inner race, the outer race and the ball track, and can diameter, the pitch diameter, the contact angle and the number of balls. The forcing frequencies are sometimes referred to as the critical frequencies. The health of a particular component can be analyzed by considering the shape and magnitude of the vibration signals at the critical frequency or at harmonics of the critical frequency." See [Dister, col 9, lines 6-39], which explains that the processor demodulates the vibration data into multiple frequencies and processes the vibration signals for analysis, "The processing performed on the vibration data by the processor 90 includes a process referred to as demodulation. One demodulation technique, sometimes referred to as enveloping, is performed by the processor 90 to synthesize the digital vibration data 100 into a form usable for failure analysis. The digital vibration data 100 enters the processor 90 and passes through a band pass filter 102 […] to form a filtered signal 104. The filtered signal 104 passes through a rectifier 106 […] which forms a rectified signal 108. The rectified signal 108 passes through a low pass filter 110 which removes the high frequencies to form a relatively low frequency signal 112. The low frequency signal 112 is passed through a capacitor 114 to produce a demodulated signal 116. A fast Fourier transform (FFT) is performed on the demodulated signal 116 by FFT operator 118 to produce a vibration spectrum 120. […]. The FFTs of the vibration signal data are discretized over N number of points to facilitate processing. […]. The vibration spectrum 120 can be analyzed by the host computer 66 to determine the health of the motor 14. […] other suitable techniques may be employed. For example, wavelet transforms may be taken of the sensor data […]." See also [Dister, col 10, lines 52-67], which explains that the frequencies can also be analyzed by amplitude peaks, "By examining the frequency associated with the peak in amplitude, the bearing which is the source of the sudden peak may be identified. As described earlier, the two bearings have different vibration characteristics, and therefore have different critical frequencies. The bearings also have harmonics at slightly different frequencies in the vicinity of the resonant frequency. This is illustrated in FIG. 8, which is a magnified view of a portion of the FFT shown in FIGS. 6 and 7. A first amplitude peak 152 is associated with the first bearing 22, for example, while a second amplitude peak 154 is associated with the second bearing 24. A sudden increase in amplitude at either of the peaks 152 or 154 would indicate a performance degradation in the bearing associated with that peak. Thus, the source of any irregular vibrations may be pinpointed to a single bearing, allowing maintenance efforts to be narrowly focused." See also [Dister, col 4, lines 54-67], which explains that the system can be used for analyzing vibration data of a machine where the machine includes vibrating components, such as a bearing, and the vibration data can identify the health of machine and pinpoint any degradation to a component needing replacement, “The invention includes a system and method for analyzing vibration data from a vibration sensor which is connected to a machine, where the machine has two or more vibration-generating components such as bearings, at least one of the vibration-generating components having different vibration characteristics than the others, with respect to the sensor. Analysis of the data allows irregularities in the operation of the machine (i.e., a degradation in health of the machine) to be pinpointed to the individual component, such as a bearing, which is causing the irregularities. Thus a component failure or near-failure, such as deterioration of a bearing, can be readily identified to allow prompt and efficient correction by replacement of the component,” and [Dister, col 1, lines 31-67], which further explains that a total vibration is the sum of the vibration of its elements including bearings and other components, such as a shaft or rotational element that has at least two bearings which may be identical, “Vibration analysis is an established nonintrusive technique for measuring the health of mechanical components in rotating machines. Every rotating machine exhibits a characteristic vibration signature which varies with the design, manufacture, application and wear of each component. Vibration may be generated by machine bearings including, for example, the bearing races, balls and ball races, misalignment of gears, motors, or shafts, and imbalance of rotors, gears, pistons and fans. […]. A machine's vibration signature is composed of the sum of the vibration signals produced by and/or transmitted through each component of the machine. The vibration signals produced by a component include forcing frequencies that vary with the rotational speed of the machine. For example, the forcing frequencies for a bearing include those of the inner race, the outer race and the ball track, and can be calculated as a function of the rotational velocity, the ball diameter, the pitch diameter, the contact angle and the number of balls. The forcing frequencies are sometimes referred to as the critical frequencies. The health of a particular component can be analyzed by considering the shape and magnitude of the vibration signals at the critical frequency or at harmonics of the critical frequency. Dynamoelectric machines such as motors generally have a shaft rotatably connected to the rest of the machine via at least two bearings, one toward either end of the machine. Prior to failure such bearings usually experience a degradation in performance which is accompanied by an increase in vibrations. Since the bearings may be identical, it is generally difficult to determine from analysis of a vibration signal […].” See also [Dister, col 12, lines 35-50], which further explains that the system can identify “defects among bearings or other vibration generating components that are identical,” and [Dister, col 2, lines 25-49], which explains that the invention narrows the vibration transmission path to an associated component, which be any type of vibrating component, “To measure and analyze the above-mentioned increase in amplitude, the present invention includes a diagnostic system having a vibration sensor mounted on a machine to sense vibrations and an electronic device called a diagnostic module, operatively couple to the vibration sensor, to evaluate the vibrations. Vibration signals from the sensor are sent to the diagnostic module which has software for processing and analyzing the vibration signals. For example, from known critical frequencies of vibration-generating components of the machine, the diagnostic module can scan a plurality of harmonic frequencies of each of the critical frequencies, measure the amplitude of the vibration signal at each harmonic frequency, and compare the amplitudes to amplitudes at adjacent harmonic frequencies. The diagnostic module can identify frequencies associated with each of the components by scanning for a relatively large increase in amplitude at a harmonic frequency of that component. That means that that harmonic frequency is near a resonant frequency of a transmission path between the vibration sensor and the respective vibration-generating component. The diagnostic system can then analyze the shape and magnitude of the vibration signal around that harmonic frequency to evaluate the health of that vibration-generating component.”
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the invention, to modify Monteyne with Dister to use a controller to deconstruct the signals and associate signals to components. Doing so allows the system to identify the signal of each bearing or component, which can help pinpoint the component or area of the machine that is failing [Dister, col 1, lines 46-59], to minimize teardown of the equipment [Dister, col 2, lines 1-9].
Dister further teaches: […] comparing the at least one component signal to a corresponding set of operational parameters; and outputting an alert . See [Dister, col 5, lines 27-42], which explains that the different bearing vibrations can be compared to the vibration characteristics or signature, "Referring briefly to FIGS. 3a and 3b, the first bearing 22 has a first outer race 26, a first inner race 27, and a first set of balls 28 therebetween. The second bearing 24 similarly has a second outer race 30, a second inner race 31, and a second set of balls 32 therebetween. The first bearing 22 has different vibration characteristics than the second bearing 24 […]. In the illustrated embodiment this is accomplished by the bearing 22 having a different number of balls than the bearing 24. […]. Since differences in bearing geometry produce differences in bearing vibrations, this difference in the number of balls produces a different vibration signature (different vibration characteristics for the bearing 22 when compared with the bearing 24." Also see [Dister, col 9, lines 44-57], which explains that the vibration characteristics, or frequencies of interest, can be supplied by the manufacturer and stored for comparison, "Referring now additionally to FIGS. 6 and 7, in the vibration spectrum 120 from the FFT operator 118 generally there is a lot of noise around the frequencies of interest 140. The sources of vibration, such as bearings, each produce vibrations at least one frequency of interest, such as a bearing critical frequency. These frequencies of interest will vary between the two bearings due to the differences in vibration characteristics of the bearings, as explained above. The frequencies of interest 140 may be supplied by the manufacturer of the part which is the source of vibrations, and these frequencies may be entered into the memory 67 of the diagnostic module 44 using the keypad 60 of the display 50. Storage of the critical frequencies in memory is illustrated in step 200 of FIG. 6." Finally see [Dister, col 6, lines 10-22], which explains the system has an interface for displaying the information of the diagnostic module, including faults and warnings and overall functions of the components, "The system 10 also includes an interface device coupled to the motor diagnostic module 44. The interface device 50 includes a display 54 for displaying information relating to the operation of the motor 14. […]. The display 54 displays data or other information relating to the operation of the motor 14. For example, the display 54 may display a set of discrete motor condition indicia such as, for example, fault indicia, caution indicia, and normal operation 20 indicia. Additionally, the display 54 may display a variety of functions that are executable by the motor 14 and/or the diagnostic module 44."
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the invention, to further modify Monteyne with Dister to compare the component signal to a parameter and alert the user when the component signal is not within the parameter. Doing so accounts for variations in the vibrational frequency which can vary based on parameters of a bearing [Dister, col 10, lines 52-67], where these parameters are set by the manufacturer and can be used to identify, for that bearing type, if the bearing is operating out of spec [Dister, col 9, lines 44-57]. This further supports the system to pinpoint which component or area of the machine is failing [Dister, col 1, lines 46-59] to help minimize teardown of the equipment [Dister, col 2, lines 1-9]. Further, using a display allows the system to indicate a faulty or warning condition to the user for the specific bearing or component [Dister, col 6, lines 17-22].
Regarding Claim 13, Monteyne as modified discloses the limitations of Claim 11.
Monteyne does not explicitly disclose: (Original) […] deconstructing the bulk signal into two or more component signals includes running the bulk signal through a form of Fourier transform. However, Monteyne does teach [Monteyne, pgs. 6-7, paras 0101-0105] using a filter to process the vibration data.
However, Dister teaches: (Original) […] deconstructing the bulk signal into two or more component signals includes running the bulk signal through a form of Fourier transform. See [Dister, col 9, lines 20-33], which explains that a fast Fourier transform, or other transforms, can be used to demodulate the signals, “A fast Fourier transform (FFT) is performed on the demodulated signal 116 by FFT operator 118 to produce a vibration spectrum 120. […]. The FFTs of the vibration signal data are discretized over N number of points to facilitate processing. […]. The vibration spectrum 120 can be analyzed by the host computer 66 to determine the health of the motor 14. […] other suitable techniques may be employed. For example, wavelet transforms may be taken of the sensor data […]."
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the invention, to further modify Monteyne with Dister to use a Fourier transform to deconstruct the signal. Using an FFT is a commercially available method for processing signals which allows the signals to analyzed by a computer for monitoring the health of a component [Dister, col 9, lines 20-30].
Regarding Claim 14, Monteyne as modified discloses the limitations of Claim 11.
Monteyne does not explicitly disclose: (Original) […] associating a component signal with a corresponding bearing group includes: calculating a bearing frequency for each bearing group; associating a component signal with a given bearing group based at least in part on the calculated bearing frequency. Monteyne does teach [Monteyne, pg. 2, para 0028], that the system can use speed as a parameter for monitoring wrapping vibrational frequency ranges.
However, Dister teaches: (Original) […] associating a component signal with a corresponding bearing group includes: calculating a bearing frequency for each bearing group; associating a component signal with a given bearing group based at least in part on the calculated bearing frequency. See again [Dister, col 10, lines 52-67], which explains that the frequency is associated to each bearing. Also see again [Dister, col 5, lines 27-42], which explains that the different bearing vibrations can be compared to the vibration characteristics or signature and [Dister, col 9, lines 44-57], which explains that the vibration characteristics, or frequencies of interest, can be supplied by the manufacturer and stored for comparison.
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the invention, to further modify Monteyne with Dister to associate the component signals to a bearing frequency. Doing so accounts for different bearing vibration characteristics and their critical frequencies [Dister, col 10, lines 52-67], which allows the system to pinpoint which component or area of the machine is failing [col 1, lines 46-59], to help minimize teardown of the equipment [col 2, lines 1-9].
Regarding Claim 15, Monteyne as modified discloses the limitations of Claim 14.
Monteyne does not explicitly disclose: (Currently Amended) […] deconstructing the bulk signal into two or more component signals includes deconstructing . However, [Monteyne, pg. 6, para 0094], does explain that the system can include detectors for frequency.
However, Dister teaches: (Currently Amended) […] deconstructing the bulk signal into two or more component signals includes deconstructing . See again [Dister, col 9, lines 6-39], which explains that the processor demodulates the vibration data into multiple frequencies and processes the vibration signals for analysis and [Dister, col 10, lines 52-67], which explains that the frequencies can also be analyzed by amplitude peaks.
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the invention, to modify Monteyne with Dister to deconstruct the signals by frequency. Doing so allows the system to identify the signal of each bearing can help pinpoint which component or area of the machine is failing [Dister, col 1, lines 46-59] this helps minimize teardown of the equipment [Dister, col 2, lines 1-9].
Regarding Claim 17, Monteyne as modified discloses the limitations of Claim 11.
Monteyne does not disclose: (Original) […] outputting a bulk signal representative of the vibrational power within the frame includes outputting a bulk signal representative of the vibrational power within the frame along the X, Y, and Z axis.
However, Dister teaches: (Original) […] outputting a bulk signal representative of the vibrational power within the frame includes outputting a bulk signal representative of the vibrational power within the frame along the X, Y, and Z axis. See again [Dister, col 2, lines 25-32], which explains a vibration sensor is mounted to the machine to collect and output vibration signals to the diagnostic module for processing and analyzing. See also [Dister, col 6-7, lines 60-67 and 1-22], which explains that the vibration sensor is a three-axis accelerometer, "An accelerometer is used as the vibration sensors in the preferred embodiment, however, other types of vibration sensors may be used. […]. Since accelerometers sense vibration primarily in one direction, a plurality of accelerometers generally is desirable to detect the vibrations generated in different directions and in different parts of some equipment. Thus, a vibration sensor as described herein may include more than one accelerometer in order to sense all significant vibration directions. Other multiple-axis sensors may be alternatively or additionally employed. […], a three-axis accelerometer 80 is located near a load side 84 of the motor 14."
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the invention, to further modify Monteyne with Dister to use a three-axis measurement for the frame vibration. Doing so ensures that all vibrations, including some which may only be generated in one direction, are captured and accounted for in the vibration analysis [Dister, col 6-7, lines 66-67 and 1-5].
Regarding Claim 18, Monteyne as modified discloses the limitations of Claim 11.
Monteyne does not disclose: (Original) […] each bearing in a given bearing group is a first bearing type, and wherein the corresponding set of operational parameters is based at least in part on the first bearing type.
However, Dister teaches: (Original) […] each bearing in a given bearing group is a first bearing type, and wherein the corresponding set of operational parameters is based at least in part on the first bearing type. See again [Dister, col 5, lines 27-42], which explains that the different bearing vibrations can be compared to the vibration characteristics or signature and [Dister, col 9, lines 44-57], which explains that the vibration characteristics, or frequencies of interest, can be supplied by the manufacturer and stored for comparison.
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the invention, to further modify Monteyne with Dister to base the operating parameters on a bearing type. Doing so accounts for variations in the vibrational frequency which can vary based on parameters of bearing [Dister, col 10, lines 52-67], where these parameters are set by the manufacturer and can be used to identify, for that bearing type, if the bearing is operating out of spec [Dister, col 9, lines 44-57]. This further supports the system to pinpoint which component or area of the machine is failing [Dister, col 1, lines 46-59] this helps minimize teardown of the equipment [Dister, col 2, lines 1-9].
Claims 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Monteyne in view of Dister, and further in view of Samadani et al., PG Pub US-2019/0250069-A1 (herein "Samadani").
Regarding Claim 19, Monteyne as modified discloses the limitations of Claim 11.
Monteyne does not disclose: (NEW) […] compiling the at least one component signal over a predetermined period of time to produce a compiled data set, and comparing the compiled data set to a statistical model of the anticipated life-cycle of the corresponding bearing group.
However, Samadani teaches: (NEW) […] compiling the at least one component signal over a predetermined period of time to produce a compiled data set, and comparing the compiled data set to a statistical model of the anticipated life-cycle of the corresponding bearing group. See [Samadani, pgs. 5-6, paras 0064-0066], which explains that a vibration sensor is used to detect defects in the wheelset, including the condition of bearings, where a signal is captured and fed to a model, such as a neural network, trained using frequency and time for detecting the defect and providing an alert, “[0064] In preferred embodiments, WHS 300 may use data from vibration sensor 302, and/or temperature sensor 306 to identify and diagnose possible defects and anomalies in the wheelset. […]. [0065] The AI algorithms may comprise one or more classifiers, neural network models or other machine learning models, for example, support vector machines or random forests to predict and classify the condition of bearings into separate categories […]. The models may be trained using time and frequency domain features extracted from historical field and lab data. When a new signal is captured by the sensor, the features are extracted from it and are fed to the trained model for fault classification and severity analysis. If the algorithm detects an alarm or defect condition, it automatically verifies the condition by retrying its measurement and analysis to rule out the effect of transient conditions and reduce the number of false alarms. If the alarm or defect condition is verified as positive or valid then the alarm or defect condition may be transmitted to a remote operations center 222 or a remote server. […]. [0066] The vibration sensor 302, in preferred embodiments, produces a signal indicative of vibrations sensed in the wheelset. Vibration data may be collected from a vibration sensor 302, which may be an analog piezo-electric accelerometer or acoustic microphone mounted on or near the bearing adapter. The signal from vibration sensor 302 may be converted to digital samples using an analog-to-digital converter 308. The vibration sensor 302 will preferably include a wide frequency response and dynamic range and will preferably have a high resonant frequency. […]. In certain embodiments, vibration sensor 302 may be embedded directly in the bearing adapter without any physical contact to the sensor enclosure to avoid introducing any potential unwanted frequency content from the enclosure to the measured signal.” See also [Samadani, pg. 5, para 0056], which explains that the system uses a temporal analysis for the data, “A temporal analysis module processes data to determine changes in values over time. For example, a WSN 104 is measuring the temperature of a bearing. Said module will determine the change in temperature readings over a specific time period allowing further analysis to be done such as trending,” and [Samadani, pg. 6, para 0072], which further explains that the temporal analysis is performed on a time schedule or as needed basis for periodic analysis, “In some embodiments, the application processor 310 may be periodically awoken by the processor and wireless radio system 312 based on a time schedule, to perform the analysis. In other embodiments, it may be desirable for application module 310 to perform analyses on an as needed basis instead of doing continuous periodic analyses.” Finally see [Samadani, pg. 7, para 0083], which explains that the system performs a health check, including bearing temperature and vibration analysis, periodically based on an elapsed amount of time or mileage, provided by the management unit or a preset threshold, “At 504, WHS 300 begins to perform a wheelset health check. The health check consists of two parts, a check of bearing temperature based on readings from temperature sensor 306, shown in FIGS. 3 and 11, to determine imminent failures, and an analysis of a vibration signal generated by accelerometer 302, shown in FIGS. 3 and 8, to predict failures in both the bearing and the wheel portions of the wheelset. Both the bearing temperature check and the analysis of the vibration signal occur periodically, determined by an elapsed time or by mileage traveled by the railcar 103, as determined by wheel position sensor 304, shown in FIG. 3, by using a GPS signal provided by CMU 101 or based on one or more user configurable thresholds. The rates at which the temperature check and vibration analysis take place may be variable, dependent upon previous analysis. For example, if a previous analysis determines that a low severity fault in the wheel or bearing is detected, the periodic rate may be shortened to check more often to make sure that the fault has not grown more severe over time.”
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the invention, to modify Monteyne with Samadani to include comparing the signal, captured over time, to a model. Doing so allows the system to the track the severity of a fault based on how it changes over time [Samadani, pg. 7, para 0083] and further, comparing to a model, using machine learning techniques, allows for predicting failure modes that existing systems cannot predict which provides for more accurate and reliable predictions [Samadani, pg. 1, para 0007].
Regarding Claim 20, Monteyne as modified discloses the limitations of Claim 11.
Monteyne does disclose: wherein comparing the at least one component signal to a corresponding set of operational parameters includes monitoring the at least one component signal over time to produce a compiled data set, calculating a power level growth rate based at least in part on the compiled data set, and outputting a signal if the calculated power level growth rate exceeds a predetermined maximum value.
However, Samadani teaches: (NEW) […] monitoring the at least one component signal over time to produce a compiled data set, calculating a power level growth rate based at least in part on the compiled data set, and outputting a signal if the calculated power level growth rate exceeds a predetermined maximum value. See [Samadani, pgs. 7-8, paras 0083-0086], which explains that the system periodically checks the vibration signal based on a threshold or based on analysis of the previous check to track fault severity, and further consists of analyzing the vibration data using a machine learning model to determine the defect and severity for providing an alert, where the faults are classified based on a comparison to predetermined thresholds, “[0083] […]. At 504, WHS 300 begins to perform a wheelset health check. The health check consists of two parts, a check of bearing temperature based on readings from temperature sensor 306, shown in FIGS. 3 and 11, to determine imminent failures, and an analysis of a vibration signal generated by accelerometer 302, shown in FIGS. 3 and 8, to predict failures in both the bearing and the wheel portions of the wheelset. Both the bearing temperature check and the analysis of the vibration signal occur periodically, determined by an elapsed time or by mileage traveled […], by using a GPS signal provided by CMU 101 or based on one or more user configurable thresholds. The rates at which the temperature check and vibration analysis take place may be variable, dependent upon previous analysis. For example, if a previous analysis determines that a low severity fault in the wheel or bearing is detected, the periodic rate may be shortened to check more often to make sure that the fault has not grown more severe over time. [0084] […]. [0085] With further reference to FIG. 5, at 516, the periodic check of the vibration data from accelerometer 302 occurs. The analysis of the vibration data has two parts, one regarding the vibration from the bearing portion of the wheelset at 518 […], and another part regarding the vibration from the wheel portions of the wheelset at 520, […]. In either case, at 522 an alarm or wheelset health message may be sent off-unit, depending upon the type of defect which is been detected and the severity of the defect, as determined by the machine learning models. […]. [0086] FIG. 6 shows a flow chart depicting the process by which faults are detected in the bearing portion of the wheelset. After the WHS 300 is awoken, by any of the methods previously discussed, vibration signal 600 is collected for a predetermined period of time. Speed signals 601 and weight data 605 may also be collected. In certain embodiments, the analysis may only be performed if the speed of the railcar is determined to be within in a pre-determined range. In Layer 1 (Critical Bearing Detection) 602 of the flow chart, it is determined if there is a critical defect in the bearing. If the (RMS of) overall vibration level is determined, at 604, to be above a predetermined threshold, it will be impossible to do Layer 2 (Fault Classification) and Layer 3 (Severity Analysis), as the vibration would make it impossible to do the feature extraction necessary for either fault classification or severity analysis. Vibration levels above the predetermined threshold generally indicate an immediate fault in the bearing, sometimes referred to as a “growling bearing”. If a critical bearing fault is detected at 603, that is, when the overall vibration level is above the predetermined threshold, an alarm is immediately generated at 606 and transmitted off-unit. Speed signal 601 and weight data 605 may also be inputs to the Layer 1 analysis.”
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the invention, to modify Monteyne with Samadani to include to monitoring the growth of a signal over time and providing an alert. Doing so allows the system to the track the severity of a fault based on how it changes over time [Samadani, pg. 7, para 0083] and further, providing an alert allows for incorporating remote monitoring [Samadani, pg. 2, para 0026 and pg. 3, para 0034] or monitoring by a third party for maintenance decision making [Samadani, pg. 5, paras 0059-0060], especially for communicating the severity of the defect or the health status so that appropriate actions can be taken [Samadani, pg. 8, paras 0088 and 0090] in real time [Samadani, pg. 1, para 0006].
Allowable Subject Matter
Claims 1-10 are allowed.
As allowable subject matter has been indicated, applicant's reply must either comply with all formal requirements or specifically traverse each requirement not complied with. See 37 CFR 1.111(b) and MPEP § 707.07(a).
The following is a statement of reasons for the indication of allowable subject matter:
The arts of record, especially Dister et al., Patent No. US-6,053,047-A, do not singularly or in combination disclose the baler comprising a frame, one or more wheels, an accelerometer coupled to the frame to output the total vibrational power of the frame, and a bale forming system that contains four rotational elements each with their own axis coupled to the frame by bearings, where the first and third bearings share the same type and the second and fourth bearings share the same type, and further the first and third elements are parallel and the second and fourth elements are parallel, as recited in independent Claim 1.
The uniqueness of the claimed invention is, as recited in Claim 1, that the controller deconstructs the bulk output signal of the accelerometer into a first and second component signal, which are associated with a first bearing group containing the first and third bearing and a second bearing group containing the second and fourth bearing, respectively.
Dister being the closest prior art discloses a bearing vibration health and diagnostics system, which uses vibration sensors and a diagnostic module to identify frequencies and amplitudes, analyze the signal, and associate the vibration signals to a component or bearing group for assigning a health status. However, there are no teachings in Dister pertaining to the claimed association of the deconstructed signal to specific first and second bearing groups of parallel rotational elements.
Therefore, the allowable subject matter found in the claims that has not been found to have been taught or disclosed in the prior art found at this time is all the claimed limitations of independent Claim 1. The dependent claims, Claims 2-10, also contain allowable subject matter by virtue of their dependency on the base claim, Claim 1.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Reference B, Casadei et al., PG Pub US-2022/0346324-A1 discusses a round baler system with various rollers for rotating crop in a baling chamber and mounted to the frame using bearings.
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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/E.M.H./Examiner, Art Unit 3664
/KITO R ROBINSON/Supervisory Patent Examiner, Art Unit 3664