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 .
Claims 1-9 are presented for examination.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statements (IDS) were submitted on April 24, 2023; May 10, 2024; December 5, 2024; February 18, 2025; and July 10, 2025. The information disclosure statement filed December 5, 2024 fails to comply with 37 CFR 1.98(a)(3)(i) because it does not include a concise explanation of the relevance, as it is presently understood by the individual designated in 37 CFR 1.56(c) most knowledgeable about the content of the information, of each reference listed that is not in the English language (specifically, of the Japanese Office action). It has been placed in the application file, but the information referred to therein has not been considered.
With this exception, the submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Specification
Examiner objects to the specification for containing various grammatical informalities. Examiner has attached a marked-up copy of the specification indicating where errors have occurred. To the extent that the markings are not self-explanatory and are not corrected, Examiner will enumerate the remaining objections in a subsequent Office Action.
Claim Objections
Claim 9 is objected to because of the following informalities: “applying visualization algorithm” and “data that contributes” should be “applying a visualization algorithm” and “data that contribute”, respectively. Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “abnormal classification unit,” “operating variables deriving unit,” “power plant operating variables weighting unit,” and “abnormal status diagnosis basis generating unit” in claims 1-4.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-7 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim limitations “abnormal classification unit,” “operating variables deriving unit,” “power plant operating variables weighting unit,” and “abnormal status basis generating unit” invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed functions and to clearly link the structure, material, or acts to the functions. Therefore, Applicant has not shown that it was in possession of the claimed invention as of the effective filing date. See rejection under 35 USC § 112(b) infra for further analysis.
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 1-7 and 9 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 limitations “abnormal classification unit,” “operating variables deriving unit,” “power plant operating variables weighting unit,” and “abnormal status diagnosis basis generating unit” invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed functions and to clearly link the structure, material, or acts to the functions.
As an initial matter, it should be noted that the specification does not recite hardware at any point in the specification. Therefore, it is unclear whether the “abnormal classification unit” or any other unit is to be construed as a hardware unit, a software unit, or some combination of the above. The specification discusses the “abnormal classification unit” at the bottom of page 7 of the specification as filed, but does little more than repeat the claimed functions. The same is true of the “operating variables deriving unit” (bottom of page 7 of the specification as filed), the “power plant operating variables weighting unit” (middle of page 8 of the specification as filed), and “abnormal status diagnosis basis generating unit” (page 5 of the specification as filed). No algorithm sufficient for performing the claimed functions, beyond merely repeating the functions themselves, is disclosed.
Therefore, the claims are indefinite and are rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. For purposes of examination, any computer software that performs the claimed functions will be deemed to read on the claims.
Applicant may:
(a) Amend the claims so that the claim limitations will no longer be interpreted as limitations under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed functions, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the functions recited in the claims, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the functions so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed functions, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed functions and clearly links or associates the structure, material, or acts to the claimed functions, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed functions. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Claim 1 recites the limitations “the abnormal status” and “the weighted power plant operating variables”. There is insufficient antecedent basis for these limitations in the claim.
Claim 4 recites the limitations “the power plant system,” "the valve leakage," “the pump failure,” “the heat exchanger failure,” and “the coolant leakage”. There is insufficient antecedent basis for these limitations in the claim.
Claim 5 recites the limitation “the physical variables”. There is insufficient antecedent basis for this limitation in the claim.
Claim 7 recites the limitation “the abnormal procedure”. There is insufficient antecedent basis for this limitation in the claim.
Claim 9 recites the limitation “the virtual input change data”. There is insufficient antecedent basis for this limitation in the claim.
All claims dependent on a claim rejected hereunder are also rejected for being dependent on a rejected base claim.
Claim Rejections - 35 USC § 101
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.
Claims 1-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The analysis of the claims will follow the 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (“2019 PEG”).
Claim 1
Step 1: For purposes of this rejection, it will be assumed that the claim is directed to the statutory category of machines.
Step 2A Prong 1: The claim recites, inter alia:
[C]lassifying the abnormal status into a plurality of failures in an abnormal scenario in which a plurality of scenarios related to the abnormal status are stored: This limitation could encompass mentally classifying the abnormal status.
[D]eriving operating variables affecting an abnormal status diagnosis result for each of the plurality of classified failures: This limitation could encompass mentally deriving the operating variables.
[P]roviding a weight to the variables related to the abnormal status from among the operating variables: This limitation could encompass mentally weighting the variables.
[T]racking the basis of an abnormal status diagnosis from the abnormal status diagnosis result generated through the weighted power plant operating variables: This limitation could encompass mentally tracking the basis of the diagnosis.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The claim further recites that the method is performed on a “device comprising: an abnormal classification unit …; an operating variables deriving unit …; a power plant operating variables weighting unit …; and an abnormal status diagnosis basis generating unit”. However, these amount to mere instructions to apply the judicial exception using a generic computer. MPEP § 2106.05(f).
Step 2B: The claim does not contain significantly more than the judicial exception. The analysis at this step mirrors that of step 2A, prong 2. As an ordered whole, the claim is directed to a mentally performable process of tracking the basis of an abnormal status diagnosis for a power plant. Nothing in the claim provides significantly more than this. As such, the claim is not patent eligible.
Claim 2
Step 1: Presumed a machine, as above.
Step 2A Prong 1: The claim recites, inter alia, that “providing the weight to the variables related to the abnormal status from among the operating variables provides the weight to physical variables that are classified in consideration of physical correlation of a power plant system related to the abnormal status and are related to the abnormal status.” This limitation could encompass mentally providing the weight.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The claim further recites that the providing is performed by a “power plant operating variables weighting unit,” which amounts to a mere instruction to apply the judicial exception using a generic computer. MPEP § 2106.05(f).
Step 2B: The claim does not contain significantly more than the judicial exception. The claim further recites that the providing is performed by a “power plant operating variables weighting unit,” which amounts to a mere instruction to apply the judicial exception using a generic computer. MPEP § 2106.05(f).
Claim 3
Step 1: Presumed a machine, as above.
Step 2A Prong 1: The claim recites, inter alia, “classif[ying] the abnormal scenario to include at least one of valve leakage, pump failure, heat exchanger failure, and coolant leakage”. This limitation could encompass mentally classifying the abnormal scenario.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The claim further recites that the classification is performed by an “abnormal classification unit,” which amounts to a mere instruction to apply the judicial exception using a generic computer. MPEP § 2106.05(f).
Step 2B: The claim does not contain significantly more than the judicial exception. The claim further recites that the classification is performed by an “abnormal classification unit,” which amounts to a mere instruction to apply the judicial exception using a generic computer. MPEP § 2106.05(f).
Claim 4
Step 1: Presumed a machine, as above.
Step 2A Prong 1: The claim recites, inter alia, “deriving the operating variables affecting the abnormal status diagnosis result for each of the plurality of classified failures comprises deriving of a flow rate of the power plant system related to a corresponding valve when the failure is classified as the valve leakage, a flow rate and a pressure of the power plant system related to a corresponding valve when the failure is classified as the pump failure, a temperature of the power plant system related to a corresponding heat exchanger when the failure is classified as the heat exchanger failure, and a leakage area radiation level when the failure is classified as the coolant leakage.” This limitation could encompass mentally deriving one of the above four quantities.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The claim further recites that the derivation is performed by an “operating variables deriving unit,” which amounts to a mere instruction to apply the judicial exception using a generic computer. MPEP § 2106.05(f).
Step 2B: The claim does not contain significantly more than the judicial exception. The claim further recites that the derivation is performed by an “operating variables deriving unit,” which amounts to a mere instruction to apply the judicial exception using a generic computer. MPEP § 2106.05(f).
Claim 5
Step 1: Presumed a machine, as above.
Step 2A Prong 1: The claim recites that “the physical variables related to the abnormal status are written with reference to an abnormal procedure or an actual power plant operation history.” Writing the physical variables under these conditions is mentally performable.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. See claim 1 analysis.
Step 2B: The claim does not contain significantly more than the judicial exception. See claim 1 analysis.
Claim 6
Step 1: Presumed a machine, as above.
Step 2A Prong 1: The claim recites, inter alia, that “the abnormal status diagnosis basis is the operating variables that can be distinguished from a different abnormal status, and is used for validation of abnormal status diagnosis logic”. This limitation could encompass mentally diagnosing an abnormal status based on the operating variables and mentally using that diagnosis for validation of status diagnosis logic.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The claim further recites that the logic is “used in an abnormal status diagnosis system.” This limitation merely restricts the judicial exception to the field of use of abnormal status diagnosis. MPEP § 2106.05(h).
Step 2B: The claim does not contain significantly more than the judicial exception. The claim further recites that the logic is “used in an abnormal status diagnosis system.” This limitation merely restricts the judicial exception to the field of use of abnormal status diagnosis. MPEP § 2106.05(h).
Claim 7
Step 1: Presumed a machine, as above.
Step 2A Prong 1: The claim recites that “the abnormal status diagnosis basis is used to validate diagnosis logic described in the abnormal procedure, and the abnormal procedure describes the operating variables that vary when the abnormal status occurs.” This limitation could encompass mentally using the diagnosis basis to validate the diagnosis logic for an abnormal procedure that describes operating variables.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. See claim 1 analysis.
Step 2B: The claim does not contain significantly more than the judicial exception. See claim 1 analysis.
Claim 8
Step 1: The claim recites a method; therefore, it is directed to the statutory category of processes.
Step 2A Prong 1: The claim recites, inter alia:
[G]enerating an abnormal status diagnosis result … by learning power plant operation data: This limitation could encompass mentally generating the diagnosis result by observing power plant operation data.
[E]xtracting variable values that affect the abnormal status diagnosis result by performing an impact analysis for the abnormal status diagnosis result … before generating the abnormal status diagnosis result: This limitation could encompass mentally extracting the variable values by mentally performing an impact analysis.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The claim further recites that certain limitations are performed using a “neural network model”, “at a final stage of the neural network model” and “on a fully connected layer”. However, these are mere instructions to apply the judicial exception using a generic computer programmed with a generic class of computer algorithm. MPEP § 2106.05(f).
Step 2B: The claim does not contain significantly more than the judicial exception. The analysis at this step mirrors that of step 2A, prong 2. As an ordered whole, the claim is directed to a mentally performable process of generating a basis for an abnormal status diagnosis of a power plant. Nothing in the claim provides significantly more than this. As such, the claim is not patent eligible.
Claim 9
Step 1: A process, as above.
Step 2A Prong 1: The claim recites, inter alia, that “the extracting the variable values that affect the abnormal status diagnosis result comprises … generating visualized input change data by applying [a] visualization algorithm, analyzing an impact of the input change data on a change in the abnormal status diagnosis result …, and extracting the input change data that contribute[] most to deriving the change in the abnormal status diagnosis result.” This limitation could encompass visualizing the input change data using a pen and paper, mentally analyzing the impact of the change data on the diagnosis, and mentally extracting the change data that contribute most to deriving the change in the abnormal status diagnosis result.
Step 2A Prong 2: This judicial exception is not integrated into a practical application. The claim further recites that the analysis of the impact is performed “through calculation of the neural network model with the virtual input change data as an input” and that the generation of the input change data occurs “virtually”. However, these are mere instructions to apply the judicial exception using a generic computer programmed with a generic class of computer algorithm. MPEP § 2106.05(f).
Step 2B: The claim does not contain significantly more than the judicial exception. The claim further recites that the analysis of the impact is performed “through calculation of the neural network model with the virtual input change data as an input” and that the generation of the input change data occurs “virtually”. However, these are mere instructions to apply the judicial exception using a generic computer programmed with a generic class of computer algorithm. MPEP § 2106.05(f).
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.
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.
Claims 1-3 and 5-7 are rejected under 35 U.S.C. 103 as being unpatentable over Rao et al. (US 20190188584) (“Rao”) in view of Loewen et al. (US 20180261068) (“Loewen”).
Regarding claim 1, Rao discloses “[a] device for tracking a basis of an abnormal status diagnosis using a neural network model (small and enriched sub-dataset is used for building and training a deep-learning neural network model with improved predictable capability to detect and predict plant/equipment process failures – Rao, paragraph 15), the device comprising:
an abnormal classification unit for classifying the abnormal status into a plurality of failures in an abnormal scenario in which a plurality of scenarios related to the abnormal status are stored1 (method of building and deploying a scalable failure model for prediction, detection, and prevention of plant process failures includes generating an improved dataset to be used as input to the failure model – Rao, paragraph 56; see also paragraphs 95 (disclosing the classification of process observations as normal, pre-failure, post-failure, etc. [i.e., classifying the status into a plurality of failure types]), 119 (disclosing that the reduced dataset and determined latent variables may be stored in a database));
an operating variables deriving unit for deriving operating variables affecting an abnormal status diagnosis result for each of the plurality of classified failures (sub-dataset is further reduced by applying a projection-to-latent-structure (PLS) model by transforming remaining process variables onto a lower-dimensional subspace with PLS techniques [variables in the lower-dimensional subspace = operating variables]; contribution coefficients indicating statistical contribution of each remaining process variable to the failure indicator [abnormal status diagnosis result] are determined – Rao, claim 22; failure indicator is associated with one or more failures in the industrial process [i.e., there may be a plurality of failures] – id. at claim 11);
a … plant operating variables weighting unit for providing a weight to the variables related to the abnormal status from among the operating variables (contribution coefficients [weights] indicating a statistical contribution of each process variable [variables] to a failure indicator [i.e., the variables are related to abnormal status] are determined [using a weighting unit] – Rao, claim 22); and
an abnormal status diagnosis basis generating unit for tracking the basis of an abnormal status diagnosis from the abnormal status diagnosis result generated through the weighted … plant operating variables (after providing the remaining process variables in ranked order of the determined contribution coefficients, one or more process variables having contribution coefficients showing insignificant statistical contribution or with high certainty in statistical confidence [i.e., the remaining process variables form the basis of the failure/abnormal status diagnosis] – Rao, claim 22).”
Rao appears not to disclose explicitly the further limitations of the claim. However, Loewen discloses that the plant in question is a “power plant (Loewen paragraph 16 discusses radiation monitoring for nuclear power plants) ….”
Loewen and the instant application both relate to power plant safety systems and are analogous. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rao to implement the method for a power plant, as disclosed by Loewen, and an ordinary artisan could reasonably expect to have done so successfully. Doing so would increase the safety of the plant by allowing potential catastrophic failures to be detected beforehand. See Loewen, paragraph 5.
Regarding claim 2, the rejection of claim 1 is incorporated. Rao further discloses that “the … plant operating variables weighting unit for providing the weight to the variables related to the abnormal status from among the operating variables provides the weight to physical variables that are classified in consideration of physical correlation2 of a … plant system related to the abnormal status and are related to the abnormal status (contribution coefficients [weights] indicating a statistical contribution of each process variable [physical variables] to a failure indicator [i.e., the variables are related to abnormal status] are determined [using a weighting unit] – Rao, claim 22; variables may be related to flow rate and temperatures [i.e., they are physical variables] – id. at paragraph 114).”
Rao appears not to disclose explicitly the further limitations of the claim. However, Loewen discloses that the plant in question is a “power plant (Loewen paragraph 16 discusses radiation monitoring for nuclear power plants) ….” It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rao to implement the method for a power plant, as disclosed by Loewen, and an ordinary artisan could reasonably expect to have done so successfully. Doing so would increase the safety of the plant by allowing potential catastrophic failures to be detected beforehand. See Loewen, paragraph 5.
Regarding claim 3, Rao, as modified by Loewen, discloses that “the abnormal classification unit classifies the abnormal scenario to include at least one of valve leakage, pump failure, heat exchanger failure, and coolant leakage (Rao paragraph 110 discloses that the system predicts, inter alia, valve failures [leakages]).”
Regarding claim 5, Rao, as modified by Loewen, discloses that “the physical variables related to the abnormal status are written with reference to an abnormal procedure or an actual power plant operation history (collected data may include measurements for various measurable process variables including flow rate, temperature, and reflux stream temperature [physical variables that may be related to an abnormal procedure]; collected data reflect the operation conditions of a representative plant during a particular sampling period and are archived in a historian database for failure modeling purposes [i.e., for modeling an abnormal status] – Rao, paragraph 114).”
Regarding claim 6, Rao, as modified by Loewen, discloses that “the abnormal status diagnosis basis is the operating variables that can be distinguished from a different abnormal status, and is used for validation of abnormal status diagnosis logic used in an abnormal status diagnosis system (small set of process variables may be used as inputs to build and train a model; the method may partition the sub-dataset over time and reserve some known failure event data [operating variables that distinguish abnormal statuses] to validate the model [abnormal status diagnosis logic used in an abnormal status diagnosis system] – Rao, paragraph 100).”
Regarding claim 7, Rao, as modified by Loewen, discloses that “the abnormal status diagnosis basis is used to validate diagnosis logic described in the abnormal procedure, and the abnormal procedure describes the operating variables that vary when the abnormal status occurs3 (small set of process variables may be used as inputs to build and train a model; the method may partition the sub-dataset over time and reserve some known failure event data [i.e., data used to establish an abnormal status diagnosis basis] to validate the model [diagnosis logic] – Rao, paragraph 100; in the iterative modeling, feature inputs showing less contribution statistically to the output predictions of the model are dropped, and only a small subset of features remains for building a final feature model [i.e., the model operates on variables that vary when an abnormal status occurs] – id. at paragraph 13).”
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Rao in view of Loewen and further in view of Gubel et al. (US 20170298807) (“Gubel”).
Regarding claim 4, the rejection of claim 1 is incorporated. Rao further discloses that “the operating variables deriving unit for deriving the operating variables affecting the abnormal status diagnosis result for each of the plurality of classified failures comprises deriving of a flow rate of the … plant system related to a corresponding valve when the failure is classified as the valve leakage (collected [derivation of] data may include measurements for manipulated variables such as the reflux flow rate as set by a valve – Rao, paragraph 114; model predicts valve failures [e.g., leakages] up to one month ahead – id. at paragraph 110), a flow rate and a pressure of the … plant system related to a corresponding valve when the failure is classified as the pump failure (collected data may include measurements for a reflux flow rate as set by a valve and pressure in a column as controlled by the valve – Rao, paragraph 114; model is able to predict valve failures – id. at paragraph 110; see also paragraph 73 (disclosing that a pump is among the systems analyzed)) ….”
Rao appears not to disclose explicitly the further limitations of the claim. However, Loewen discloses “a power plant system (Loewen paragraph 16 discusses radiation monitoring for nuclear power plants) …, and [deriving] a leakage area radiation level when the failure is classified as the coolant leakage (radiation of a particular-energy gamma ray associated with a specific radionuclide that can only leak from a primary coolant loop in a nuclear reactor may be detected – Loewen, paragraph 24).” It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rao to detect radiation levels in the case of coolant leakage, as disclosed by Loewen, and an ordinary artisan could reasonably expect to have done so successfully. Doing so would increase the safety of the power plant by ensuring that coolant issues can be accurately detected before a catastrophic accident occurs. See Loewen, paragraph 24.
Neither Rao nor Loewen appears to disclose explicitly the further limitations of the claim. However, Gubel discloses “deriving … a temperature of the … system related to a corresponding heat exchanger when the failure is classified as the heat exchanger failure (observed increase in the temperature of the coolant [system related to heat exchanger] may indicate a malfunction such as a failure of a heat exchanger [i.e., this temperature is measured/derived] – Gubel, paragraph 19) ….”
Gubel and the instant application both relate to detection of mechanical failures and are analogous. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combination of Rao and Loewen to monitor the temperature of a heat exchanger system to determine whether it has failed, as disclosed by Gubel, and an ordinary artisan could reasonably expect to have done so successfully. Doing so would allow the user to perform timely maintenance on the system before more catastrophic failure occurs. See Gubel, paragraph 19.
Claims 8-9 are rejected under 35 U.S.C. 103 as being unpatentable over Rao in view of Cheng et al. (US 20190391574) (“Cheng”).
Regarding claim 8, Rao discloses “[a] method for generating a basis of an abnormal status diagnosis using a neural network model (small and enriched sub-dataset is used for building and training a deep-learning neural network model with improved predictable capability to detect and predict plant/equipment process failures [abnormal status diagnoses] – Rao, paragraph 15), the method comprising: …
extracting variable values that affect the abnormal status diagnosis result by performing an impact analysis for the abnormal status diagnosis result … before generating the abnormal status diagnosis result (input data preparation module reduces a sub-dataset by determining contribution coefficients [performing an impact analysis] indicating statistical contribution of remaining process variables [variables that affect the abnormal status diagnosis result] to a failure indicator – Rao, claim 22; model execution module executes the built and trained failure model after training on the reduced dataset [i.e., the execution of the model, or the generation of the diagnosis result, occurs after the extraction of the variable values] – id. at claim 12).”
Rao appears not to disclose explicitly the further limitations of the claim. However, Cheng discloses “generating an abnormal status diagnosis result at a final stage of the neural network model by learning power plant operation data and the neural network model (topology inspired neural-network anomaly detection (TINA) may be used to train on a normal period and test on a testing period; TINA may be used to conduct anomaly detection; if reconstruction error increases, then an abnormal event has occurred [i.e., an abnormal status diagnosis has occurred] – Cheng, paragraph 54; see also paragraphs 23 (disclosing that the output neurons [final stage] process weighted input from a last set of hidden neurons), 24 (discussing training [learning] operations of the network), 34 (disclosing that the data come from a nuclear power plant)); and
performing an … analysis … on a fully connected layer (neural network layers on which analysis may be performed include fully connected layers – Cheng, paragraph 26) ….”
Cheng and the instant application both relate to anomaly detection and are analogous. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rao to use the neural network to generate abnormal status diagnoses for a power plant, as disclosed by Cheng, and an ordinary artisan could reasonably expect to have done so successfully. Doing so would prevent catastrophic failure by allowing any anomalies to be detected early. See Cheng, paragraph 34.
Regarding claim 9, the rejection of claim 8 is incorporated. Rao further discloses that “the extracting the variable values that affect the abnormal status diagnosis result comprises virtually generating visualized input change data by applying [a] visualization algorithm (input data preparation module reduces the sub-dataset by transforming remaining process variables of the reduced dataset into a projection latent structure [input change data] by projecting [algorithm] the remaining process variables onto a lower-dimensional subspace – Rao, claim 22; see also paragraph 127 (disclosing the use of displays, i.e., visualization)), analyzing an impact of the input change data on a change in the abnormal status diagnosis result … with the virtual input change data as an input (based on the projection [virtual impact change data], contribution coefficients indicating statistical contribution of remaining process variables to the failure indicator [abnormal status diagnosis result] are determined [note that the contribution coefficients show an impact of the input data on the result] – Rao, claim 22), and extracting the input change data that contribute[] most to deriving the change in the abnormal status diagnosis result (remaining process variables are provided in ranked order, and based on the ranking, one or more process variables having contribution coefficients showing insignificant statistical contribution are removed [the remaining data being those that contribute the most to the result] – Rao, claim 22).”
Rao appears not to disclose explicitly the further limitations of the claim. However, Cheng discloses “analyzing an impact … through calculation of the neural network model (system uses topology-inspired neural-network anomaly detection to train on a normal period and test on a testing period [i.e., it analyzes the impact of data on a determination of an anomaly] – Cheng, paragraph 54) ….” It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Rao to use a neural network model to perform the analysis, as disclosed by Cheng, and an ordinary artisan could reasonably expect to have done so successfully. Doing so would allow the system to detect trends that are too complex to be detected by humans and other computer-based systems. See Cheng, paragraph 23.
Conclusion
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/RYAN C VAUGHN/ Primary Examiner, Art Unit 2125
1 This language is inscrutable at best. Examiner is interpreting it to mean roughly that the abnormal classification unit is responsible for classifying abnormalities and storing the classifications.
2 As above, this language borders on the nonsensical. Examiner will interpret it as meaning roughly that the weights are for physical variables that relate to an abnormal status of plant operation .
3 Here again the language is inscrutable. Examiner is construing it to mean roughly that the diagnosis logic is validated using data used to form a basis of the diagnosis and that the model operates on variables that vary when an abnormal status diagnosis occurs.