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 .
Status of Claims
This is a final office action in response to the amendment filed 09 June 2026. Claims 1, 6, and 11 have been amended. Claims 2-5, 7-10, 12-15, and 24 have been canceled. Claims 1, 6, 11, 16-23, and 25-29 remain pending and have been examined.
Response to Amendment
Applicant’s amendment to claims 1, 6, and 11 has been entered.
Applicant’s amendment is sufficient to overcome the pending 35 U.S.C. 101 rejection. The 35 U.S.C. 101 rejection is respectfully withdrawn.
Response to Arguments
Applicant’s arguments regarding the 35 U.S.C. 101 rejection have been fully considered by examiner, and are persuasive. The amendment filed herein integrates the data collection and analysis abstract concept into a practical application by analyzing sensor data to control an active damping system mechanically coupled to the physical infrastructure to suppress vibrations associated with the detected structural deterioration in a manner that provides a meaningful limitation to the data collection and analysis steps. The control of the damping system using the claimed anomaly detection steps is a technical solution to a technical problem. Therefore, the 35 U.S.C. 101 rejection is respectfully withdrawn. However, the 35 U.S.C. 101 rejection is overcome because of claim language rejected under 35 U.S.C. 112(a) as new matter. If the claim language related to the 112(a) rejection is withdrawn, the 35 U.S.C. 101 rejection would be proper and restated.
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.
Claims 1, 6, 11, 16-23, and 25-29 are rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement. The claims 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 had possession of the claimed invention.
The amended claim language of independent claims 1, 6, and 11 includes the following subject matter not described in the specification: “… transmitting a control signal to an active damping system mechanically coupled to the physical infrastructure, the control signal causing the active damping system to suppress vibrations associated with the detected structural deterioration.” Paragraph [0030] of the Specification discloses “an acceleration sensor installed on a bridge” to detect “deterioration of the strength of the bridge” but does not disclose or otherwise suggest “… transmitting a control signal to an active damping system mechanically coupled to the physical infrastructure, the control signal causing the active damping system to suppress vibrations associated with the detected structural deterioration.” Therefore, Applicant did not possess priority to the limitation as claimed at the time of filing and the newly added limitation represents "new matter" not previously disclosed. Claims 19-20 and 25 depend from claim 1 and inherit all the deficiencies of claim 1. Claims 23-24 and 27-28 depend from claim 6 and inherit all the deficiencies of claim 6. Claims 16-18, 26, and 29 depend from claim 11 and inherit all of the deficiencies of claim 11.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant’s disclosure:
Genov et al. (US 11,154,251) - training a machine learning model to classify occurrences of the state; receiving a new time series data stream; determining whether a current sample in the new time series data stream is an occurrence of the state by determining a classified feature vector, the classified feature vector determined by passing the current sample and samples in at least one continuous sampling window into the trained machine learning model, each continuous sampling window including a plurality of preceding samples from the time series data, an epoch for each respective continuous sampling window determined according to a respective exponential decay rate; and outputting the determination of whether the current sample is an occurrence of the state.
Klein (US 7,027,953) - A vibrational analysis system diagnosis the health of a mechanical system by reference to vibration signature data from multiple domains. Features are extracted from signature data by reference to pointer locations. The features provide an indication of signature deviation from a baseline signature in the observed domain. Several features applicable to a desired fault are aggregated to provide an indication of the likelihood that the fault has manifested in the observed mechanical system. The system may also be used for trend analysis of the health of the mechanical system.
Montreuil et al. (US 2011/0153236) - system comprises a sensor data receiver for receiving real time sensor data including at least one measured value measured in real time by at least one sensor installed on a conductor of the electrical network in the facility while the electrical network is in use; an anomaly detector for retrieving an anomaly detection rule from an anomaly detection rule database, the rule having an identification of a required input, a formula, and a threshold reference value, for a detection of an anomaly; receiving the real time sensor data from the sensor data receiver and extracting at least one relevant measured value from the at least one measured value using the identification of the required input; comparing the at least one relevant measured value to the threshold reference value according to the formula to determine one of a presence and an absence of the anomaly in the real time sensor data; an event generator controlled by the processor for retrieving and providing anomaly monitoring data if the anomaly is determined to be present by the processor, the anomaly monitoring data including an indication of a monitoring course of action to be carried out to address the anomaly determined to be present.
Patil et al. (US 9,979,675) - An anomaly detection process can then be utilized to detect anomalies for a class of data at a selected aggregate. An example anomaly detection process includes receiving telemetry data originating from a plurality of client devices, selecting a class of data from the telemetry data, converting the class of data to a set of metrics, aggregating the set of metrics according to a component of interest to obtain values of aggregated metrics over time for the component of interest, determining a prediction error by comparing the values of the aggregated metrics to a prediction, detecting an anomaly based at least in part on the prediction error, and transmitting an alert message of the anomaly to a receiving entity.
Su et al. (US 10,685,159) - a data-driven anomaly detection method is used to account for both challenges and opportunity facing analog functional safety. An embodiment is based on a collection of in-field analog data, both runtime operational mode (e.g., in-field operation) and test mode, in a context of system operation, by using the inherent observability of functional and design-for-x (DFx) features. In this context, the x in DFx represents a type of “design-for” monitoring feature, including DFT (Design-for-Testability), DFD (Design-for-Debug), DFV (Design-for-Validation), or the like. A machine learning method, with these dynamic time-series data as training data (from the in-field analog data), is developed for anomaly detection of upcoming real-time test data.
Applicant's amendment necessitated the new grounds of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LETORIA G KNIGHT whose telephone number is (571)270-0485. The examiner can normally be reached M-F 9am-5pm.
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/L.G.K/Examiner, Art Unit 3623 /RUTAO WU/Supervisory Patent Examiner, Art Unit 3623
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