DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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.
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 01 July 2026 has been entered.
Claims 15, 18-19, 21, 23, and 24-28 are pending.
Claims 15, 18-19, 21, 23, and 24-28 are rejected, grounds follow.
Priority
Application’s status as a 35 USC 371 national stage application of PCT application PCT/EP2022/052941 is acknowledged.
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Response to Arguments
Applicant’s arguments, see Remarks Page 5, filed 01 July 2026, with respect to the rejection(s) of claim(s) 15-18, 21 and 24 under 35 USC 103 in view of “Curtlett”, “Moore” and “Henry” have been fully considered and are persuasive. Because the independent claims now include the subject matter previously presented in dependent claim 22 (rejected further in view of Kohn et al., US Pg-Pub 2013/0321167) the amended claims overcome the references applied to independent claims 15 and 24 in the previous office action. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Kohn, consistent with the rejection applied to claim 22 in the previous office action. Applicant does not appear to have made any argument in support of the eligibility of Claims 15 and 24 over the previous rejection articulated with respect to Claim 22.
Examiner notes for clarity of the record that dependent Claims 25-28 are newly presented and applicant did not elect to present separate arguments regarding the allowability of these claims. Examiner has evaluated these claims in view of the overall body of prior art to determine their status. See below for detailed rejection(s) and/or objection(s).
Claim Objections
Applicant is advised that should claim 23 be found allowable, claim 27 will be objected to under 37 CFR 1.75 as being a substantial duplicate thereof. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
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 26-28 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 26 recites the limitation "the block-by-block transmission" in Claim 26 line 2. There is insufficient antecedent basis for this limitation in the claim.
Claim 27 recites the limitation “the employed individual model” in claim 27 line 2. There is insufficient antecedent basis for this limitation in the claim.
Dependent Claim(s) 28 inherit(s) the deficiencies of its respective parent(s).
Claim Rejections - 35 USC § 103
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.
Claim(s) 15-18, 21, and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Curlett et al., Object-Oriented Approach for Gas Turbine Engine Simulation, NASA technical memorandum 106970 (1995), in view of Moore et al., US Pg-Pub 2019/0005005, in view of Henry et al., US Pg-Pub 2016/0084181 and in view of Kohn et al., US Pg-Pub 2013/0321167.
Regarding Claims 15 and 24, Curlett teaches:
(Claim 15 representative) An […] integrating model (see Page 1, “The aerothermodynamic simulation of the engine plays a pivotal role in the entire life cycle of turbine engines”) for a technical system (i.e. turbine engine) composed of an electric machine (see e.g. fig. 3, page 11, nb. inasmuch as the engine includes sensors powered by electricity and transmitting electrical signals, the turbine is at least partly composed of an electric machine.) the integrating model comprising:
a machine-machine interface; (see fig. 6, page 17 and page 16 “the source, model data, and the customer deck API can be compiled into a customer deck for distribution. It is our intent to automate, as much as possible, the process of moving from the generalized NASA model to the customer model.”)
and a plurality of individual models (see fig. 3, page 11, and page 10 “A component is defined as a code module (or object) that takes inputs and produces outputs and has little other interaction with the system.” having each assigned a raw model (see Page 12 “A component may be as simple as multiplying a number on an input port by two and writing it to an output port; or it may be as complex as a 3D Navier-Stokes code with ports containing large grids of data.”) and a data pre-processing, (see page 15, section 11.3 Table Interpolation Classes: A set of classes was developed that makes handling of component maps and other tabular data much easier. These classes decouple the data, file parser, interpolation routines, and scaling relations for flexibility and efficiency while maintaining a single, simple, consistent interface.”)
wherein different individual models model different parts of the technical system (e.g. “shaft”, “Compressor” etc.) and have different raw models (the models are different object oriented classes, see e.g. fig. 2 depicting the inheritance tree) and a different data pre-processing, (see appendix A, describing the ways that data is pre-processed when transferred between components, particularly Page 20, section A.3 “This variation has a smart connector between two components. The connector is referred to as "smart" because it can connect two different types of data if it has a suitable translation function to go from one type to the other.”)
and wherein at least one of the individual models is interchangeable for a part of the technical system; (See Page 12 “For example, suppose a new compressor component was needed with a different surge margin calculation. The class PsNewCompressor could be derived from the PsCompressor class (see Appendix C). Only the surge-margin( ) method would need to be re-implemented in PsNewCompressor; everything else would be inherited from PsCompressor”)
[…] and modeling a part of the technical system using the changed configuration of the individual models. (see Page 16, table 1 heading “one general executable” particularly features for “More Dynamic (configuration can be changed on-the-fly from the user interface)” and “Better suited for conceptual/preliminary design (configuration changing)” and “Optimizer (AI) can modify configuration”)
Curlett differs from the claimed invention in that:
Curlett does not clearly articulate: [the integrating model] is cloud-based
Nor: with the different raw models programmed in different programming languages
Nor: switchable logic elements disposed between pairs of the individual models, with the switchable logic elements configured to connect or disconnect the pairs of the individual models for data exchange between the pairs of the individual models
Nor the technical system is configured to continuously record measurement signals from a sensor of the electric machine with a sampling rate in a kHz-range and transmitting the recorded continuous measurement signals in blocks for use in the integrating model even when data cannot be transmitted in real time.
However, Moore teaches a cloud-based (see fig. 1 and e.g. [0031] “FIG. 1 illustrates a cloud computing environment associated with industrial systems in accordance with an example embodiment. FIG. 1 illustrates generally an example of portions of an asset management platform (AMP) 100. As further described herein, one or more portions of an AMP can reside in a cloud computing system 120, in a local or sandboxed environment, or can be distributed across multiple locations or devices.”) component model for a drive (e.g. wind turbine, see fig. 2 and Moore [0040] “In this example, the virtual model 200 is a digital representation of a wind turbine.”) where components may be switched out freely ([0024] “Accordingly, as long as the components maintain the common data frame as an input and an output, the components can simply be removed and replaced without affecting the remaining components of the algorithm ensemble.”) which includes programming in different programming languages ([0024] “a user such as a data scientist, programmer can use any of multiple programming languages (e.g., Java, Python, R) to design an algorithm without worrying about how it affects the other algorithms included in the algorithm ensemble.”)
Moore and Curlett are analogous art because they are from the same field of endeavor of component based simulation of operational plants, and contain overlapping structural and functional similarities; each reference represents a drive system with a plurality of programmatic models which cooperate to estimate operational performance of a larger system.
One of ordinary skill in the art before the effective filing date of the application could have modified the teachings of Curlett to use a pluggable framework including diverse programming languages for the interior raw models of the various components of Curlett, as suggested by Moore.
One of ordinary skill in the art could have been motivated to make this modification in order to permit efficient optimization of the components and permitting seamlessly switching between different algorithms, as suggested by Moore ([0063] “the pluggable framework provided herein permits the efficient optimization of which components within an algorithm ensemble should be applied to various problems by permitting a mechanism to seamlessly switch between different component algorithms.”)
And, Henry teaches a complex model (see fig. 4 and Henry [0054] “plurality of fresh intake air flow estimations, determined according the estimation models described above, that are input into multiple switches and a complex model to determine a final fresh intake air flow.”) of a drive ([0014] “The approach described herein may be employed in a variety of engine types, and a variety of engine-driven systems.”) which disposes switchable logic elements between individual models (fig. 4, Switch 402, 406, disposed between the estimation models 404, and 410; see [0056]) with the switchable logic elements configured to connect or disconnect the pairs of the individual models ([0055] “While five separate steady-state estimations are illustrated in control diagram, it is to be understood that the diagram is illustrative in nature and not limiting, and thus other switch configurations are possible.” ) for data exchange between the pairs of the individual models (see e.g. [0056] “The output from switch 406 (which may be referred to as the steady-state estimation) is fed into the complex predictor/corrector model 410.”)
Henry and Curlett are analogous art because they are from the same field of endeavor of component based simulation of operational plants, and contain overlapping structural and functional similarities; each reference represents a drive system with a plurality of programmatic models which cooperate to estimate operational performance of a larger system.
One of ordinary skill in the art could have modified the teachings of Curlett to incorporate switches between models, as suggested by Henry, for connecting and disconnecting pairs of components with one another, such as selecting between PsCompressor and PsNewCompressor of Curlett to realize the exhortation of Curlett to permit reconfiguration of the model in the general purpose executable.
One of ordinary skill in the art could have motivated to make this modification in order to permit easier reconfiguration as suggested by Curlett More Dynamic (configuration can be changed on-the-fly from the user interface)” and “Better suited for conceptual/preliminary design (configuration changing)” and because Henry suggests that switches are suitable for connecting outputs of components to inputs of other components based a predetermined configuration ([0055] “The multi-port switch selects one estimation, based on a predetermined switch configuration… The estimation output from the multi-port switch may be selected based on operating conditions, based on a minimum value, or other configuration.”)
And, Kohn teaches continuously ([0010] “A ring buffer (corresponding to a first-in-first-out, or FIFO, buffer) is understood here as a buffer that continuously stores data in a particular time period, and overwrites these data after the expiration of a specified time in order to make storage space available for new data.”) recording sensor data measurements (fig. 2a and [0023] “Data elements 100, 103, 106, 109 contain bits 0 . . . 7 of the MSB (most significant byte), which contains the measured sensor data. First data subelements 101, 104, 107, 110 contain bits 8 . . . 11 of the LSB (least significant byte), which contains the measured sensor data.”) that may be transferred in blocks to the destination application ([0024] “Instead of the constant reading out of sensor data, application unit 201 periodically receives data blocks with data stored in sensor module 200.”) even when data is not transmitted in real-time (see Kohn e.g. [0024] “Instead of the constant reading out of sensor data, application unit 201 periodically receives data blocks with data stored in sensor module 200. This results in a reduction of energy consumption, because application unit 201 can e.g. change over into sleep mode between the block-by-block reading of the sensor data.”)
Kohn is analogous art because it is reasonably pertinent to the same problem confronted by applicant of how to supply measured data to a data-ingesting application.
One of ordinary skill in the art before the effective filing date of the application could have modified the teachings of Curlett to include recording and transmitting measurement data in blocks, as suggested by Kohn.
One of ordinary skill in the art before the effective filing date of the application could have been motivated to make this modification in order to reduce energy consumption by the data transfer, as suggested by Kohn. ([0024] “This results in a reduction of energy consumption, because application unit 201 can e.g. change over into sleep mode between the block-by-block reading of the sensor data.”)
With respect to the sensors having a sampling rate in a kHz-range, Although Kohn is silent as to the sampling rate of the sensors, Examiner takes Official Notice that using sensors with a sampling rate in the kHz range would be an obvious matter of routine design choice for rotary systems, well within the capabilities of one of ordinary skill to select based on the desired temporal resolution of the sensed data. Although not specifically relied upon in the rejection, in the interest of compact prosecution examiner provides the following examples of prior art supporting this conclusion:
Pfeifer et al., US Pg-Pub 2010/0262401 [0010] “ In this case, a dynamic pressure signal is first of all measured by at least one pressure sensor in or on, and/or behind the compressor of the turbine, in which case a dynamic pressure signal means that the rate of change of the pressure signal is recorded. Preferred sampling rates for recording the pressure signal are in the kHz range. “ [0046] “In particular, a measurement is dynamic when the sampling rate is in the kHz range or higher. The measured pressure signal is in this case created by the compressor rotor blade passing the guide vane in the individual compressor stages during operation”
Beylotte et al., US Pg-Pub 2014/0262514 [0060] “A sensor on a turbine-driven drilling component, or other component rotating at about 2,500 revolutions per minute, could have a sampling rate of about 60 kHz (i.e., 1440*2500/60). In a corresponding manner, a decrease in desired resolution for the angle of twist may decrease the sampling frequency. For a resolution of one degree, a sensor on a shaft rotating at 300 revolutions per minute may have a sampling frequency of about 1,800 Hz (i.e., 360*300/60), whereas a sensor on a shaft rotating at 2,500 revolutions per minute may have a sampling rate of about 15 kHz (i.e., 360*2500/60).”
Graham-Hansen et al., US Pg-Pub 2010/0082295 “[0038] The signals containing measurement data to be evaluated and operating condition parameters are captured from various sources. Some signals are captured from sources that are strictly synchronous at high data rates (RPM sampling up to 100 MHz, dynamic signals at 41 kHz, etc.).”
Claim 24 recites substantively the same subject matter, except embodied as a method. mutatis mutandis, this claim is likewise obvious over the teachings of Curlett, Moore, Henry, and Kohn for the same reasons articulated with respect to claim 1, above.
Regarding Claims 18 and 25, Curlett in view of Moore, Henry and Kohn teaches all of the limitations of parent claims 13 and 24, respectively;
Curlett further discloses:
(Claim 18 representative) wherein the data pre-processing or post-processing is provided for communication between the individual models. (see e.g. Page 20, particular A.3 and A.4 “This variation has a smart connector between two components. The connector is referred to as "smart" because it can connect two different types of data if it has a suitable translation function to go from one type to the other.”)
Regarding Claim 21, Curlett in view of Moore and in view of Henry teaches all of the limitations of parent claim 25,
Curlett further discloses
wherein changing the data pre-processing when exchanging an individual model of the integrating model. (see page 25, components store information describing their required data sources (e.g. “//maps used by compressor” see page 15 section 11.3 for more information) to the extent that components are interchangeable, see page 12 cited supra. and that smart connectors may handle translating between different types of data as necessary when connecting two components, Curlett therefore also discloses the changing of the pre-processing component as necessary, e.g. Page 20 section A.3 “in this model the system must know when to and when not to call the translation function in the station”)
Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Curlett in view of Moore, Henry and Kohn, further in view of Citriniti et al., US 2018/0174057.
Regarding Claim 19, Curlett in view of Moore and Henry teaches all of the limitations of parent claim 13,
Curlett in view of Moore and Henry differs from the claimed invention in that:
The references do not appear to clearly articulate wherein the machine-machine interface model is a REST API interface.
However, Citriniti teaches a modeling system (see fig. 1 “Predictive models”) which may be for a drive (see [0001] “wind turbine”) where the machine-to-machine interface ([0047] “The data lenses provide endpoints that are accessible to the predictive models 122 such that the predictive models can call an API or otherwise access the endpoint to retrieve particular data stored within the logically organized data 118.”) is a REST API ([0086] “The accessed data is exposed through the data lenses as one or more endpoints, such as Representational State Transfer (REST) API endpoints. External predictive models may query these endpoints to extract the data from the underlying logical model”)
Curlett and Citriniti are analogous art because they are from the same field of endeavor of component based simulation of operational plants, and contain overlapping structural and functional similarities; each reference represents a drive system with a plurality of programmatic models which cooperate to estimate operational performance of a larger system.
One of ordinary skill in the art before the effective filing date of the application could have modified the teachings of Curlett to include a machine-machine interface which is a REST API, as suggested by Citriniti.
One of ordinary skill in the art before the effective filing date of the application could have been motivated to make this modification in order to enable the predictive model to retrieve data from the underlying asset without understanding how the data is extracted and/or stored, as suggested by Citriniti ([0047] “In this manner, embodiments provide the ability for the predictive models 122 to retrieve data derived from and/or related to the underlying assets 102 without requiring a full understanding the manner in which the intermediate data 108 is stored or extracted from the assets 102.”)
Claim(s) 23 and 27 is/are rejected under 35 U.S.C. 103 as being unpatentable over Curlett in view Moore, Henry, and Kohn, further in view of Kothare et al., US Pg-Pub 2004/0064202.
Regarding Claims 23 and 27, Curlett in view of Moore, Henry, and Kohn teaches all of the limitations of parent claims 24 and 24, respectively;
The combination differs from the claimed invention in that:
(Claim 23 representative) the references do not appear to clearly articulate further comprising changing a sampling rate or a block size depending on the individual model used.
However, Kothare teaches that sample rate may be selected to match the rate at which a model is designed to operate ([0142] “Re-sampling and interpolation are other pre-processing possibilities for data that may have been sampled too fast (re-sampling) or too slowly (interpolation). Generally the sample rate may be selected to match the rate at which the model-based controller is designed to operate, so these pre-processing steps may not be necessary in most cases.”)
Kothare is analogous art because it is reasonably pertinent to the same problem confronted by applicant of how to supply measured data to a data-ingesting application.
One of ordinary skill in the art before the effective filing date of the application could have modified the teachings of Curlett in view of Kohn to include changing the sampling rate of the data sources to match the ingestion rate of the models, as suggested by Kohn.
One of ordinary skill in the art before the effective filing date of the application could have been motivated to make this modification in order to reduce the amount of re-sampling and/or interpolation required prior to providing the data to the model, as suggested by Kothare ([0142] “Re-sampling and interpolation are other pre-processing possibilities for data that may have been sampled too fast (re-sampling) or too slowly (interpolation). Generally the sample rate may be selected to match the rate at which the model-based controller is designed to operate, so these pre-processing steps may not be necessary in most cases.”)
Allowable Subject Matter
The following is a statement of reasons for the indication of allowable subject matter: While Curlett, Moore, Henry, Kohn, Kothare, and Citriniti teach many of the limitations of the claimed invention as outlined in the rejections above; none of the references of record, alone or in reasonable combination, teach or fairly suggest all of the limitations of the claimed invention, particularly:
(Claim 26)
Further comprising varying a repetition rate of the block-by-block transmission of the measurement signals to adapt to different transmission bandwidths.
(Claim 28)
Wherein the block size is dependent on the employed individual model.
(Excerpted)
…in combination with the remaining features and limitations of the independent claim and any intervening claim(s).
Claims 26 and 28 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Conclusion
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/J.T.S./Examiner, Art Unit 2119
/MOHAMMAD ALI/Supervisory Patent Examiner, Art Unit 2119
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