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 .
Drawings
The drawings are objected to because the drawings appear to have the English labels placed over Chinese character labels. The Chinese character labels should be removed so that the English labels can be clearly seen. 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.
Specification
The disclosure is objected to because of the following informalities:
The Specification contains numerous grammatical errors including missing punctuation, missing spaces, extra punctuation, etc. The specification should be amended to correct these errors.
Appropriate correction is required.
Claim Objections
Claims 1-9 are objected to because of the following informalities:
Claims 1-9 contain multiple grammatical errors including missing spaces, extra punctuation, etc. Further, Applicant is reminded of the correct form of claims which requires that the claims be the object of a sentence starting with “I (or we) claim,” “The invention claimed is” (or the equivalent). Each claim should begin with a capital letter and end with a period; and periods may not be used elsewhere in the claims except for abbreviations (See MPEP 608.01).
Appropriate correction is required.
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 1-9 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 1 includes the recites that the central server is based on the power plant scale coefficient βi. On page 4, lines 10-13, the specification states that the central server aggregates the model parameters of each power station client based on the power station scale coefficient. This appears to be the language that should be found in the claim. However, on page 9, lines 25-28, the specification uses similar language to that found in the claim and does not describe how the central server is based on the power plant scale coefficient. Since it is unclear how the central server is based on this coefficient, it does not convey to one skilled in the relevant art that the inventors had possession of the claimed invention. Claims 2-9 depend from claim 1 and are rejected for the same reason.
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 1-9 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.
As discussed above, claim 1 recites that the central server is based on the power plant scale coefficient. Since the specification does not explain how the central server is based on a coefficient, it is unclear how this claim limitation would be accomplished. Claims 2-9 depend from claim 1 and are rejected for the same reason.
Claim 1 recites the limitation "the suspension condition" in the first and second line following S24. There is insufficient antecedent basis for this limitation in the claim.
Claim 1 recites the limitation "the fault diagnosis classification model”" in S3. There is insufficient antecedent basis for this limitation in the claim.
Claims 2-9 depend from claim 1 and inherit insufficient antecedent basis for the limitations recited in claim 1.
Claim 1 also recites two equation variable/parameters, LSig and LAss, which are not defined in the claims or in the specification. Since these quantities are not defined, the claim 1 and the dependent claims 2-9 are also indefinite for this reason.
Claim 5 recites limitations for five input layers one that is specified as “environment (temperature, humidity, light).” The use of parenthesis here renders the claim indefinite because it is unclear whether the limitations recited in parenthesis are required to meet the limitations of the claim.
Claim 8 recites an FCN network. Claim 8 and its dependent claim 9 are indefinite because it is unclear what FCN means in the claim. The acronym FCN has not been defined in the claims or the specification.
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 abstract idea without significantly more.
Per step 1 of the Subject Matter Eligibility Test (See MPEP 2106), claim 1 is directed to an method or process which falls within a statutory category (See MPEP 2106.03).
Per step 2A, prong 1, claim 1 recites:
S1. Obtain the operating data of various batteries in each energy storage station and perform preprocessing operations on the data;
S2. Use the preprocessed power station operating parameters to use the feature extraction network in each power station client to extract power station operating fault features;
S22. Feature extraction model training;
In the feature extraction network model training stage, all operating parameters of each power station are used as input data of the feature extraction network to implement the training of the feature extraction network model;
S23. Parameter update and aggregation of the feature extraction model;
The central server is based on the power plant scale coefficient βi Realize the aggregation of model parameters of each power station client;
S24. The feature extraction network completes training;
When the model parameters of each client server are accepted to meet the suspension condition, the training of the feature extraction network of each client server is stopped;
The feature extraction network model is the electric energy residual sensing network BRAN. The feature extraction network model includes the electric energy residual sensing module; the electric energy residual sensing module includes the Mixing module and the sensing layer; the Mixing module is voltage, current, battery Coulomb efficiency, and battery temperature. , the weighted values of the environment (temperature, humidity, light) after passing through 5 layers of convolution layers and 4 layers of deconvolution layers are used to obtain weighted fusion features; the perception layer implements feature sensing operations on voltage, current, battery Coulombic efficiency, and battery temperature. , realize the feature sensing operation of the internal operating parameters of the battery, and extract the deep operating features inside the battery; finally, the weighted fusion features are deeply fused with the deep sensing features of the sensing layer to obtain the deep features of the power station's electric energy; the environmental parameters include ambient temperature, environment Humidity, ambient light data;
The BRAN network implements parameter aggregation at the central server, and uses the following loss function to update and optimize the BRAN feature extraction network;
Equation 4
Equation 5
Equation 6
Equation 7
Among them, Ltot is the total loss function of the BRAN network, LDis is the feature distance loss function, LSca is the power plant scale loss function, LVar is the model parameter variance loss function; a, β, γ are the characteristic distance coefficient, power plant scale coefficient and parameter variance coefficient respectively.; N is the number of models; li is the operating parameter; Ks1, Ks2 Model output features; Gs1, GN is a function of power plant scale; Vs1, Vs2 is the variance between client model parameters;
S3. Use the aggregate feature extraction network to implement feature extraction of a single operating parameter on the client server of each power station, and train the fault diagnosis classification model;
S4. Collect the operating parameters of the power station and input them into the feature extraction network and fault diagnosis network to realize fault diagnosis of the power station.
These limitations are generally directed to collecting data from batteries in energy storage stations for input training and using a model for fault diagnosis. The limitations for training and using the model are defined by mathematical operations and equations and therefore the claim 1 falls into the mathematical concepts grouping (See MPEP 2106.04(a)(2)).
The additional elements are S21. Establish a client-central server distributed learning framework; and after each client completes an iterative training, the model parameters are uploaded to the central server.
Per step 2A, prong 2, The abstract idea is not integrated into a practical application because the limitations to a client and central server are instructions to implement the abstract idea on a computer and amount to mere instructions to apply the abstract idea (See MPEP 2106.05(f)).
Per step 2B, claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception for the same reason.
Claims 2-9 depend from claim 1 and do not recite any further additional elements. Claims 2-9 only recite further details of the abstract idea, therefore claims 2-9 are rejected for the same reason.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
CN 114910793 to Liang et al. teaches SOH estimation method of a series battery pack of energy storage power station that includes training a model to estimate the SOH of the battery back.
CN 114487836 to Wu et al. teaches battery state analysis that includes cleaning the data during preprocessing.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MANUEL L BARBEE whose telephone number is (571)272-2212. The examiner can normally be reached M-F: 9-5:30..
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shelby A Turner can be reached at 571-272-6334. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MANUEL L BARBEE/Primary Examiner, Art Unit 2857