Prosecution Insights
Last updated: October 01, 2026
Application No. 18/713,562

METHOD FOR AUTOMATICALLY DIAGNOSING A PART

Non-Final OA §101
Filed
May 24, 2024
Priority
Dec 02, 2021 — FR 2112840 +1 more
Examiner
LEE, SANGKYUNG
Art Unit
Tech Center
Assignee
Safran S.A.
OA Round
1 (Non-Final)
60%
Grant Probability
Moderate
1-2
OA Rounds
6m
Est. Remaining
70%
With Interview

Examiner Intelligence

Grants 60% of resolved cases
60%
Career Allowance Rate
98 granted / 163 resolved
At TC average
Moderate +10% lift
Without
With
+10.3%
Interview Lift
resolved cases with interview
Typical timeline
2y 11m
Avg Prosecution
37 currently pending
Career history
198
Total Applications
across all art units

Statute-Specific Performance

§101
25.2%
-14.8% vs TC avg
§103
55.6%
+15.6% vs TC avg
§102
11.5%
-28.5% vs TC avg
§112
7.3%
-32.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 163 resolved cases

Office Action

§101
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 . Information Disclosure Statement The information disclosure statement (IDS) submitted on 05/24/2024 was in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. 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 1-8 and 10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Specifically, representative Claim 1 recites: A method for automatically diagnosing a part of a rotating machine carried out on based on a non-stationary time vibratory signal generated by the rotating machine during at least one phase during which a rotation speed of the rotating machine varies as a function of time, the method comprising: - building a diagram from the signal, comprising the following sub- steps of: o splitting the signal into a plurality of sub-signals, each sub- signal corresponding to a time interval associated with at least one rotation speed of the rotating machine and being quasi-stationary over the time interval; o for each sub-signal, calculating the Fourier transform of the sub-signal in order to obtain a vibratory energy for each frequency of the Fourier transform of the sub-signal; o building the diagram, the diagram being a matrix having a plurality of rows each corresponding to a rotation speed of the rotating machine, ordered in ascending order, and a plurality of columns each corresponding to a frequency of the Fourier transform divided by a rotation speed of the rotating machine, ordered in ascending order, the matrix comprising, for each row and each column, the vibratory energy of the sub-signal corresponding to the rotation speed of the rotating machine of the row for the frequency of the Fourier transform of the column; - supervisedly training an artificial neural network to obtain an artificial neural network trained capable of providing, from the diagram, a class of operation included in a set of classes of operation including at least one class of nominal operation and one class of defective operation, the artificial neural network being trained on a training database including a plurality of training diagrams, each training diagram being built from a non-stationary time signal generated by a training rotating machine of a same type as the rotating machine and being associated with one class of operation from the set of classes of operation; - using the trained artificial neural network on the diagram built to provide a class of operation of the rotating machine. The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements.” Step 1: under the Step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter. The above claim is considered to be in a statutory category (process). Step 2A, Prong One: under the Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, it falls into the groupings of subject matter when recited as such in a claim limitation that falls into the grouping of subject matter when recited as such in a claim limitation, that covers mathematical concepts - mathematical relationships, mathematical formulas or equations, mathematical calculations and mental processes – concepts performed in the human mind including an observation, evaluation, judgement, and/or opinion. For example, the limitations of “building a diagram from the signal, comprising the following sub-steps of: splitting the signal into a plurality of sub-signals (paras. [0034]-[0036] of instant application), each sub- signal corresponding to a time interval associated with at least one rotation speed of the rotating machine and being quasi-stationary over the time interval (para. [0037] of instant application); for each sub-signal, calculating the Fourier transform of the sub-signal in order to obtain a vibratory energy for each frequency of the Fourier transform of the sub-signal (para. [0038] of instant application)” are mental processes and mathematical calculations. The limitation of “splitting the signal into a plurality of sub-signals, each sub- signal corresponding to a time interval associated with at least one rotation speed of the rotating machine and being quasi-stationary over the time interval” corresponds mental processes (observation) and the limitation of building a diagram from the signal and calculating the Fourier transform of the sub-signal in order to obtain a vibratory energy for each frequency of the Fourier transform of the sub-sign” is indicative of mathematical calculations. Further, limitation of “building the diagram, the diagram being a matrix having a plurality of rows each corresponding to a rotation speed of the rotating machine, ordered in ascending order, and a plurality of columns each corresponding to a frequency of the Fourier transform divided by a rotation speed of the rotating machine, ordered in ascending order, the matrix comprising, for each row and each column, the vibratory energy of the sub-signal corresponding to the rotation speed of the rotating machine of the row for the frequency of the Fourier transform of the column (paras. [0034]-[0038] of instant application),” “supervisedly training an artificial neural network to obtain an artificial neural network trained capable of providing, from the diagram, a class of operation included in a set of classes of operation including at least one class of nominal operation and one class of defective operation, the artificial neural network being trained on a training database including a plurality of training diagrams, each training diagram being built from a non-stationary time signal generated by a training rotating machine of a same type as the rotating machine and being associated with one class of operation from the set of classes of operation (paras. [0048]-[0068] of instant application),” and “using the trained artificial neural network on the diagram built to provide a class of operation of the rotating machine (paras. [0048]-[0053], [0062]-[0070] of instant application)” are mathematical calculations. Building a diagram and training and using a ANN is an indicative of mathematical calculations. Machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are merely mathematical calculations. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mathematical calculations and/or human mind, then it falls within the “Mathematical Concepts” and/or “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. Similar limitations comprise the abstract ideas of Claims 8 and 10. Step 2A, Prong Two: under the Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application. In this step, we evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception. This judicial exception is not integrated into a practical application. Therefore, none of the additional elements indicate a practical application. Therefore, the claims are directed to a judicial exception and require further analysis under the Step 2B. Step 2B: The above claims comprise the following additional elements: In Claim 1: a method for automatically diagnosing a part of a rotating machine carried out on based on a non-stationary time vibratory signal generated by the rotating machine during at least one phase during which a rotation speed of the rotating machine varies as a function of time (preamble); In Claim 8: a calculator configured to implement the steps of the method according to claim 1 (preamble); and In Claim 10: a non-transitory computer-readable storage medium comprising instructions which, when executed by a computer, cause the same to implement the steps of the method according to claim 1 (preamble). The additional elements such as the rotating machine, calculator, and a non-transitory computer-readable storage medium in claims 1, 8, and 10 are recited at a high-level of generality without descriptions of its specific structure/features to perform the claimed features for producing the mental and mathematical process addressed above (MPEP 2106.05(d)). Further, the additional element of “a method for automatically diagnosing a part of a rotating machine carried out on based on a non-stationary time vibratory signal generated by the rotating machine during at least one phase during which a rotation speed of the rotating machine varies as a function of time” is preamble statements reciting purpose or intended use (See MPEP 2111.02(II)). Claim 1 does not present tangible or physical elements/components and/or integration of improvements to be indicative of specific features/structure/acts, for example, how and or with what to build the diagram, supervisedly training and using the trained artificial neural network on the diagram built. The pending claims are not patent eligible since a claim for a new abstract idea is still an abstract idea (see MPEP 2106.05(a).I) and an improvement in the abstract idea itself is not an improvement in technology (see MPEP 2106.05(a).II and MPEP 2106.05(a).II: Examples that the courts have indicated may not be sufficient to show an improvement to technology include: iii. Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48)). This is just a processor running mathematics and mental processes. Similar limitations comprise the abstract ideas of Claims 8 and 10. Therefore, the independent claims 1, 8, and 10 are ineligible. Regarding claims 2-7, All features recited in these claims are abstract ideas and/or further defines or describes the abstract ideas. The explanation for the rejection of Claims 2-7, therefore are incorporated herein and applied to Claim 1. These claims therefore stand rejected for similar reasons as explained in above Claim 1. No prior art rejection is being made for independent claims 1, 8, and 10 because the prior art does not disclose or make obvious features of “building the diagram, the diagram being a matrix having a plurality of rows each corresponding to a rotation speed of the rotating machine, ordered in ascending order, and a plurality of columns each corresponding to a frequency of the Fourier transform divided by a rotation speed of the rotating machine, ordered in ascending order, the matrix comprising, for each row and each column, the vibratory energy of the sub-signal corresponding to the rotation speed of the rotating machine of the row for the frequency of the Fourier transform of the column;," as is current claimed, in the combination, and as best understood. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to SANGKYUNG LEE whose telephone number is (571)272-3669. The examiner can normally be reached Monday-Friday 8:30am-5:00pm. 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 RODARK 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. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /SANGKYUNG LEE/Examiner, Art Unit 2858 /CHRISTOPHER P MCANDREW/Primary Examiner, Art Unit 2858
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Prosecution Timeline

May 24, 2024
Application Filed
Sep 01, 2026
Non-Final Rejection mailed — §101 (current)

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Prosecution Projections

1-2
Expected OA Rounds
60%
Grant Probability
70%
With Interview (+10.3%)
2y 11m (~6m remaining)
Median Time to Grant
Low
PTA Risk
Based on 163 resolved cases by this examiner. Grant probability derived from career allowance rate.

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