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 .
Summary
Claims 1-15 are pending. Claims 1-15 are rejected herein. This is a Final Rejection as necessitated by the amendment and arguments (hereinafter “the Response”) dated 30 June 2026.
Claim Rejections - 35 USC § 112(b)
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.
Claim(s) 15 is/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.
Regarding claim 15: Claim 15 recites that the energized work product is a “battery powered product.” However the work product is not within the scope of claim 1. Claim 1 only recites that the system has a sensor that captures sound signal data that is representative of sound emitted by an energized work product. Therefore any further limitation of the work product that does not have a direct bearing on the sound it produces (e.g. the sound emitted is within a certain frequency range or decibel level), does not appear to provide any further limitation to the subject matter of claim 1. Therefore it is unclear what further limitation the language of claim 15 is intended to apply to claim 1.
Claim Rejections - 35 USC § 112(d)
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim(s) 15 is/are rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Regarding claim 15: Claim 15 recites that the energized work product is a “battery powered product.” However the work product is not within the scope of claim 1. Claim 1 only recites that the system has a sensor that captures sound signal data that is representative of sound emitted by an energized work product. Therefore any further limitation of the work product that does not have a direct bearing on the sound it produces (e.g. the sound emitted is within a certain frequency range or decibel level), does not provide any further limitation to the subject matter of claim 1. Therefore claim 15 is in improper dependent form for failing to limit its parent claim.
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.
Claim(s) 1-6, 8-12, and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over GEIB et al. (US 8655571) in view of CLAUSSEN et al. (WO 2020222845) and BERTIN et al. (US 20130002852).
Regarding claims 1, 3, 4, and 8: GEIB discloses: A system (24 in FIG. 1) comprising: a sensor (acoustic sensors 22 in FIG. 1; col. 2 lines 13-20); and a real time computer system (24 in FIG. 1) comprising: at least one processor (28) with a real-time operating system (Inherent in the operation of any computer); and a memory (26) having algorithmic modules stored thereon executable by the processor, the modules comprising: a digital signal processing module configured to window sound signal data captured by a sensor (time domain windows as discussed in col. 4 lines 54-67), the sound signal data representative of sound emitted by an energized work product under quality inspection (gas turbine engine in col. 1 lines 42-53); a feature extraction component is configured to extract acoustic features from each sound window (MFCC coefficients in col. 3 lines 25-39); and an anomaly detector module configured to operate a machine learning-based model to execute acoustic anomaly detection according to results of a classification operation on the acoustic features (col. 4 lines 1-13).
GEIB does not disclose that the computer is deployed onto the backplane of a PLC.
CLAUSSEN however does teach that it is known to install a computer (external module in para. 14-15) on the backplane of a PLC (para. 15) and receive sensor data for an industrial process (para. 14-15). CLAUSSEN also teaches that the at least one processor is configured as an artificial intelligence accelerator comprising: a main central processing unit (CPU) configured to operate the real-time operating system and interface with the PLC control loop (para. 24); and at least one real-time CPU configured to operate algorithms of the anomaly detector module (para. 24), thus meeting the limitations of claim 3. CLAUSSEN also teaches Streaming Hybrid Architecture Vector Engine (SHAVE) cores that use a parallel processing unit specific for neural network evaluation in real-time (para. 24), thus meeting the limitations of claim 4. CLAUSSEN also teaches a USB driver for controlling streaming of sound data received from the sensor (para. 21), thus meeting the limitations of claim 8.
One skilled in the art at the time the application was effectively filed would be motivated to use a computer installed on the backplane of a PLC in this way because it provides hardware-based protection for the PLC against cyberattacks (para. 14 of CLAUSSEN).
GEIB in view of CLAUSSEN does not disclose that the computer is triggered to perform the automated acoustic anomaly detection based on receiving a trigger sent from the PLC, the trigger being sent in response to an arrival of the energized work product at an inspection station.
BERTIN however does teach a computer (controller 102 in FIG. 1, 4) that is triggered (by trigger device 418 in FIG. 4) to perform the automated anomaly detection (with camera 104; para. 33-34) based on receiving a trigger, the trigger being sent in response to an arrival of the energized work product at an inspection station (“Trigger device 418 may be one or more sensors that are upstream and/or downstream from camera 104 and sense the passing of components. For example, trigger device 418 may be a programmable limit switch, a motion sensor, another vision system, or any other device that discerns the presence and/or timing of components as they pass.” In para. 54.
One skilled in the art at the time the application was effectively filed would be motivated to use the trigger of BERTIN based on detecting the presence of the work product as taught by BERTIN on the acoustically tested work product moving through a factory work process as taught by GEIB in view of CLAUSSEN because it ensures that the work product is always in the same position for testing (para. 54 of BERTIN) which allows for more consistent detection leading to more accurate anomaly detection.
Regarding claims 2 and 10: GEIB discloses: the acoustic features include Mel-frequency cepstral coefficients (col. 3 lines 25-39).
Regarding claims 5 and 11: GEIB discloses: the anomaly detector module is further configured to: generate a normal classification or an abnormal classification for the acoustic features (fault detection and diagnosis, steps 114 and 116 in FIG. 2; col. 52-67) and treat the abnormal classification as a detected acoustic anomaly (fault detection 116 in FIG. 2), and respond with one or more trigger events (col. 4 lines 18-32).
GEIB does not disclose sending the classification for the acoustic features to the PLC.
CLAUSSEN however does teach sending the classification as input to the PLC (para. 18) and sending an abnormal classification as a data point input to the PLC for controlling the automation system (para. 18); and responding with one or more trigger events (para. 18; “Connections 105 may…interface with elements of the industrial processes, including but not limited to valves, sensors, and actuators. Connections 105 may transmit control data to, and receive operating data from, any appropriate elements of the industrial process. Data, such as sensor data, from connections 105 is received on backplane 104, and is used by PLC resources 102 to analyze the operation of the industrial process and to control the elements of the industrial process by transmitting commands to the elements of the industrial process via backplane 104 and connections 105.”).
One skilled in the art at the time the application was effectively filed would be motivated to use the PLC interface of CLAUSSEN to control an industrial process such as the fault detection of GEIB, because it provides an interconnection between the automation hardware and flexibility of programming and processing in computer software (para. 2 of CLAUSSEN).
Regarding claims 6 and 12: GEIB discloses: the trigger events include: an alert for display on a human machine interface in response to an anomaly detection (Faults are reported to a maintenance scheduler. Col. 4 lines 18-22).
GEIB does not explicitly disclose a display on a human machine interface, however the Examiner takes Official Notice that it is known in the art for monitoring systems to send alerts to personnel about systems faults and required maintenance so that personnel are informed about the work they are supervising. This Official Notice, first taken in the Non-Final Rejection dated 13 April 2026, has not been timely traversed by the Applicant and is therefore considered Applicant Admitted Prior Art.
Regarding claims 9 and 14: GEIB discloses: A real-time computer-based method for automated acoustic anomaly detection (24 in FIG. 1), the method comprising: windowing sound signal data captured by a sensor (time domain windows as discussed in col. 4 lines 54-67), the sound signal data representative of sound emitted by an energized work product under quality inspection (gas turbine engine in col. 1 lines 42-53); extracting acoustic features from each sound window (MFCC coefficients in col. 3 lines 25-39); and operating a machine learning-based model to execute acoustic anomaly detection according to results of a classification operation on the acoustic features (col. 4 lines 1-13).
GEIB does not disclose that the computer is deployed on a PLC.
CLAUSSEN however does teach that it is known to install a computer (external module in para. 14-15) on the backplane of a PLC (para. 15) and receive sensor data for an industrial process (para. 14-15). CLAUSSEN also teaches a USB driver for controlling streaming of sound data received from the sensor (para. 21), thus meeting the limitations of claim 14. CLAUSSEN also teaches that the at least one processor is configured as an artificial intelligence accelerator comprising: a main central processing unit (CPU) configured to operate the real-time operating system and interface with the PLC control loop (para. 24); and at least one real-time CPU configured to operate algorithms of the anomaly detector module (para. 24). CLAUSSEN also teaches Streaming Hybrid Architecture Vector Engine (SHAVE) cores that use a parallel processing unit specific for neural network evaluation in real-time (para. 24).
One skilled in the art at the time the application was effectively filed would be motivated to use a computer installed on the backplane of a PLC in this way because it provides hardware-based protection for the PLC against cyberattacks (para. 14 of CLAUSSEN).
GEIB in view of CLAUSSEN does not disclose that the computer is triggered to perform the automated acoustic anomaly detection based on receiving a trigger sent from the PLC, the trigger being sent in response to an arrival of the energized work product at an inspection station.
BERTIN however does teach a computer (controller 102 in FIG. 1, 4) that is triggered (by trigger device 418 in FIG. 4) to perform the automated anomaly detection (with camera 104; para. 33-34) based on receiving a trigger, the trigger being sent in response to an arrival of the energized work product at an inspection station (“Trigger device 418 may be one or more sensors that are upstream and/or downstream from camera 104 and sense the passing of components. For example, trigger device 418 may be a programmable limit switch, a motion sensor, another vision system, or any other device that discerns the presence and/or timing of components as they pass.” In para. 54.
One skilled in the art at the time the application was effectively filed would be motivated to use the trigger of BERTIN based on detecting the presence of the work product as taught by BERTIN on the acoustically tested work product moving through a factory work process as taught by GEIB in view of CLAUSSEN because it ensures that the work product is always in the same position for testing (para. 54 of BERTIN) which allows for more consistent detection leading to more accurate anomaly detection.
Claim(s) 7 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over GEIB, CLAUSSEN, and BERTIN in view of BIRKHOFER et al. (US 20240381881).
Regarding claims 7 and 13: GEIB as modified by CLAUSSEN does not teach routing a work product to a production line that performs remedial measures.
BIRKHOFER however does teach using sensor data (para. 36, 41-42) in an automated PLC factory environment (abstract; para. 47) to flag and divert a faulty product (para. 5) to a different production line for remedial measures (repackaging in para. 5).
One skilled in the art at the time the application is effectively filed would be motivated to use acoustic sensors for anomaly detection as taught by GEIB in an automated production environment as taught by BIRKHOFER because acoustic analysis provides a sophisticated way to diagnose faults in complex machines (col. 2 line 56-col. 3 line 9 of GEIB), and automated redirection of faulty product uses time and production resources more efficiently (para. 56-57 of BIRKHOFER), saving material and labor costs.
Response to Amendment/Argument
The amendments to the claims to overcome the previous objections are acknowledged and said objections are accordingly withdrawn.
The amendments to the claims to overcome the previous rejections under 35 U.S.C. 112 are acknowledged and said rejections are accordingly withdrawn. Please note that there are new 112 rejections for added claim 15.
The amendments to the claims to overcome the previous rejections under 35 U.S.C. 101 are acknowledged and said rejections are accordingly withdrawn.
The Applicant has argued (page 8 of the Response) that the prior art of record does not teach the added limitations of claim 1, namely that the arrival of the work product triggers the acoustic testing. The Examiner agrees with this statement and BERTIN has been introduced to address this limitation as necessitated by amendment.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. BADIC et al. (DE 112018006743) has been added to the Notice of References Cited for teaching that it is known to have a work product move down a manufacturing line while powered by a battery. Please note that the foreign version of BADIC has not been included with this office action because it is 657 pages long.
Applicant's amendment necessitated the new ground(s) 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 NATHANIEL J KOLB whose telephone number is (571)270-7601. The examiner can normally be reached M-F 9-5 EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Laura M Sweeney can be reached at 571-272-2160. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/NATHANIEL J KOLB/Examiner, Art Unit 2855
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