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 .
Response to Amendment
Receipt is acknowledged of the Preliminary Amendment filed on June 21, 2024. Accordingly, claims 1-16 are currently pending in the application.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on August 26, 2024 is being considered by the examiner.
Claim Interpretation
According to MPEP 2112.02: Process Claims, it is noted that “Under the principles of inherency, if a prior art device, in its normal and usual operation, would necessarily perform the method claimed, then the method claimed will be considered to be anticipated by the prior art device” (emphasis added). It is also noted in that same MPEP section that “The Federal Circuit upheld the Board’s finding that "Donley inherently performs the function disclosed in the method claims on appeal when that device is used in ‘normal and usual operation’" and found that a prima facie case of anticipation was made out” (emphasis added). Id. at 138, 801 F.2d at 1326. It was up to applicant to prove that Donley's structure would not perform the claimed method when placed in ambient light.).”
With regard to claims 13-16, these claims present an apparatus according to the method of claims 1-12. Therefore, the argument made against claims 1-12 also applies, mutatis mutandis, to claims 13-16. In addition, it is clearly seen that claims 1-12 are process claims which present a process of using the system as claimed in claims 13-16, respectively.
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 1-16 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.
There are two separate requirements set forth in the second paragraph of 35 U.S.C. 112:
(A) the claims must set forth the subject matter that applicants regard as their invention; and
(B) the claims must particularly point out and distinctly define the metes and bounds of the subject matter that will be protected by the patent grant.
With regard to claim 1, it is unclear whether it claims “a method for measuring electrical equipment of a system for supplying power” or “a machine learning method”.
Firstly, claim 1 recites a limitation, “assessing a state of the electrical equipment based on the adapted measurement values at least one machine learning method”, which appears to be incomplete for showing no connection between “assessing a state of the electrical equipment based on the adapted measurement values” and “at least one machine learning method” (emphasis added). This limitation is so vague about what it is truly meant.
Secondly, claim 1 fails to particularly point out and distinctly define the metes and bounds of the subject matter that will be protected by the patent grant. The subject matter of “a machine learning method” is unclear to a person skilled in the art to determine what steps of functions are necessary to be performed in this “machine learning method”.
Finally, claim 1 further recites limitations, “electrical equipment” and “equipment parameters”, which appear to be so vague (i.e., structure parameters such as dimension and size, design parameters such as shape and material, or operating parameters such as voltage, current and power) that it is not clear to a hypothetical person possessing the ordinary level of skill in the pertinent art how to interrelate “measurement values” with “equipment parameters” into the concept for state analysis of electrical equipment. In other words, it is not clear how to identify specific parameters of the equipment for “adapting the measurement values to a uniform evaluation basis using the equipment parameters” for monitoring and analysing the state of electrical equipment.
With regard to claims 2-16, these claims are rejected at least by virtue of their dependencies directly or indirectly from the base claim 1.
The essential purpose of patent examination is to determine whether or not the claims are precise, clear, correct, and unambiguous to ensure that the scope of the claims is clear so the public is informed of the boundaries of what constitutes infringement of the patent. Therefore, the uncertainties of claim scope should be removed as much as possible.
For examining purposes, the application will be examined as best understood.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 2, 7-9, 12-14 and 16 are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by Frotscher et al. (DE 10 2018 131 388 A1).
Frotscher et al. teaches monitoring gases in an insulating household comprising:
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With regard to claims 1, 13 and 16, a method for measuring electrical equipment (FIG. 1, on-load tap changer S) of a system (FIG. 1, electrical equipment EB such as a transformer) for supplying power, the electrical equipment (FIG. 1, on-load tap changer S) comprising a housing (FIG. 1, housing, such as a tank or boiler) with an insulating fluid (FIG. 1, insulating fluid IM and IM’), the method comprising: recording measurement values (at least one characteristic value such as gas quantity or gas composition) representing dissolved gases (FIG. 1, dissolved gases GG and GG’) in the insulating fluid (FIG. 1, insulating fluid IM and IM’); determining equipment parameters (resistance temperature and load current); adapting the measurement values (at least one characteristic value such as gas quantity or gas composition) to a uniform evaluation basis using the equipment parameters (resistance temperature and load current) (using evaluation unit AE in FIG. 1); assessing a state of the electrical equipment (FIG. 1, on-load tap changer S) based on the adapted measurement values (at least one characteristic value such as gas quantity or gas composition) at least one machine learning method (using evaluation unit AE in FIG. 1); and outputting the state (using evaluation unit AE in FIG. 1) (For more details, please read: Abstract; paragraphs: [0040]-[0046] and [0049]-[0054]; and claims 1-14).
With regard to claim 13, an apparatus (FIG. 1, evaluation unit AE) for analysing a state of electrical equipment (FIG. 1, on-load tap changer S) of a system (FIG. 1, electrical equipment EB such as a transformer) for supplying power, the electrical equipment (FIG. 1, on-load tap changer S) comprising a housing (FIG. 1, housing, such as a tank or boiler) with an insulating fluid (FIG. 1, insulating fluid IM and IM’), the apparatus (FIG. 1, evaluation unit AE) comprising: an interface (FIG. 1, evaluation unit AE) for recording measurement values (at least one characteristic value such as gas quantity or gas composition) representing dissolved gases in the insulating fluid (FIG. 1, insulating fluid IM and IM’) and/or equipment parameters (resistance temperature and load current); an evaluation unit (FIG. 1, evaluation unit AE), which is designed to carry out the method according to claim 1 (For more details, please read: Abstract; paragraphs: [0040]-[0046] and [0049]-[0054]; and claims 1-14).
With regard to claim 16, a system (FIG. 1, electrical equipment EB such as a transformer) for supplying power, the system (FIG. 1, electrical equipment EB such as a transformer) comprising: at least one item (a selector and a diverter switch) of electrical equipment (FIG. 1, on-load tap changer S); and the apparatus (FIG. 1, evaluation unit AE) for analysing the state (condition assessment) of the electrical equipment (FIG. 1, on-load tap changer S) according to claim 13.
With regard to claim 2, checking the recorded measurement values (at least one characteristic value such as gas quantity or gas composition) or the equipment parameters (resistance temperature and load current) for plausibility (Paragraph: [0023]; and claim 4).
With regard to claim 7, the electrical equipment (FIG. 1, on-load tap changer S) is a tap changer (FIG. 1, on-load tap changer S) and the equipment parameters (resistance temperature and load current) comprise tap-changer-specific data (application-specific design parameters of the on-load tap-changer) (Paragraph: [0034]).
With regard to claim 8, in addition to the tap-changer-specific data (application-specific design parameters of the on-load tap-changer), specific characteristic variables of the insulating fluid (FIG. 1, insulating fluid IM and IM’) (a mineral transformer oil or an alternative insulating liquid, such as a synthetic ester) or operational data or transformer-specific data are determined (Paragraph: [0012]).
With regard to claim 9, the measurement values (at least one characteristic value such as gas quantity or gas composition) are additionally adapted to a uniform evaluation basis by the specific characteristic variables of the insulating fluid (FIG. 1, insulating fluid IM and IM’) or the operational data or the transformer-specific data (Paragraphs: [0040]-[0042]).
With regard to claim 12, outputting a recommended action or carrying out the recommended action relating to the operation of the electrical equipment (FIG. 1, on-load tap changer S) depending on the determined state and/or the uncertainty indicator (a message is output if the gas amount is equal to the defined limit value or exceeds the defined limit value) (Paragraph: [0023]; and claim 4).
With regard to claim 14, an output unit (FIG. 1, evaluation unit AE), which is designed to output a state of the electrical equipment (FIG. 1, on-load tap changer S) (For more details, please read: Abstract; paragraphs: [0040]-[0046] and [0049]-[0054]; and claims 1-14).
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.
Claims 3-6, 10, 11 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Frotscher et al.
Frotscher et al. teaches all that is claimed as discussed in the rejections of claims 1, 2, 7-9, 12-14 and 16 above including the output unit (FIG. 1, evaluation unit AE) and the evaluation unit (FIG. 1, evaluation unit AE), but it does not specifically teach the following features:
determining a probability of a validity of the state of the electrical equipment, wherein the state is output with the validity probability.
determining an indicator that indicates an uncertainty about the probability of the validity of the state; and outputting the indicator.
the uncertainty indicator is determined depending on an availability of the recorded measurement values or an availability of the equipment parameters.
missing measurement values or missing equipment parameters are determined by at least one statistical evaluation method.
the statistical evaluation method for determining the missing measurement values or the missing equipment parameters is based on an imputation method.
the machine learning method for carrying out the state assessment is based on a regression method, a neural network, a support vector machine, a linear-discriminant analysis, or on a Gaussian process regression.
the output unit is furthermore designed to output an indicator that indicates an uncertainty about the probability of the validity of the state.
It is well-known to one having ordinary skill in the art that machine learning methods are algorithms that enable systems to learn from data (availability of the recorded measurement values or an availability of the equipment parameters) to make predictions (“determining a probability of a validity”, “an uncertainty about the probability of the validity”, or “missing measurement values or missing equipment parameters”) or decisions (“outputting the indicator” that “indicates an uncertainty about the probability of the validity of the state”). Key examples include supervised learning (Linear Regression for predicting continuous values, Decision Trees for classification/regression tasks, or Support Vector Machines (SVM) effective for high-dimensional classification), and neural networks for powers complex tasks, which are applied in areas like recommendation engines, fraud detection, and image recognition. Therefore, the features of the claims as mentioned right above are merely one of several obvious possibilities from which a person skilled in the art, without inventive step, would choose, according to the circumstances, to solve the problem at hand.
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the monitoring gases in an insulating household of Frotscher et al. to utilize commonly available features as discussed above since such an arrangement is beneficial to enable an evaluation unit to learn from data to make predictions or decisions. Such an implementation can significantly increase the effectiveness of the evaluation unit for analysing a state of electrical equipment.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Applicants’ attention is invited to the followings whose inventions disclose similar devices.
Bertsch et al. (US 2002/0116148 A1) teaches a method and a system for maintenance planning for a technical device.
Fantana et al. (US 2006/0259277 A1) teaches a method and system for systematic evaluation of evaluation parameters of technical operational equipment.
Cheim (CA 3088836 A1) teaches methods and devices for a condition classification of a power network asset of a power network asset.
Cao (CN 115358353 A) teaches a transformer fault diagnosis method of multi-source fusion.
CONTACT INFORMATION
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HOAI-AN D. NGUYEN whose telephone number is (571) 272-2170. The examiner can normally be reached MON-THURS (7:00 AM - 5:00 PM).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, LEE E. RODAK can be reached at 571-270-5628. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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HOAI-AN D. NGUYEN
Primary Examiner
Art Unit 2858
/HOAI-AN D. NGUYEN/ Primary Examiner, Art Unit 2858