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 .
Prior arts cited in this office action:
Gao (WO 2021036641 A1, hereinafter “Gao”)
Zhang et al. (CN 105097057 A, hereinafter “Zhang”)
Veronesi et al. (US 20230244836 A1, hereinafter “Veronesi”)
Response to Arguments
Applicant's arguments filed 06/22/2026 have been fully considered but they are moot in view of new ground of rejections set forth below.
Claim Rejections - 35 USC § 103
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Gao (WO 2021036641 A1, hereinafter “Gao”) and in view of Zhang et al. (CN 105097057 A, hereinafter “Zhang”) and in view of Veronesi et al. (US 20230244836 A1, hereinafter “Veronesi”).
Regarding claims 1, 12 and 20:
Gao teaches a system for monitoring a coupling, the coupling comprising a
visual failure indicator provided by a manufacturer thereof (Gao Abstract page 1 lines 1-15, where Gao teaches a system and method for monitoring coupling mismatch), the system
comprising:
a processing circuity configured for:
receiving image data from the at least one optical sensor, the image data including data of a region of interest of the safety coupling and devoid of the visual failure indicator of the safety
coupling (Gao Abstract page 1 lines 1-5, 12-20, where Gao teaches obtaining a video acquiring a starting frame image of the zoomed-in vibration video, determining a to-be-detected axis in the starting frame image, and determining a plurality of detection points based on the to-be-detected axis);
analyzing the image data to detect a change in a relative position between a first and a second part of the safety coupling (Gao Abstract page 1 lines 1-5, 12-20, page 2 lines 13-21, page 3 lines 15-28, where Gao teaches It can be seen that in this embodiment of the application, the original vibration video of the preset area collected by the imaging device is received, and the motion amplification algorithm is performed on the original vibration video to obtain the amplified vibration video; The initial frame image, the axis to be detected is determined in the initial frame image, and multiple detection points are determined based on the axis to be detected; the target tracking algorithm is performed on the multiple detection points in the zoomed-in vibration video to obtain A plurality of detection point position sets corresponding to the plurality of detection points; generating a vibration restoration model of the axis to be detected based on the plurality of detection point position sets, receiving vibration data returned by the vibration restoration model; according to the vibration The data determines that the coupling corresponding to the shaft to be detected is in a mismatched state. In this way, the detection efficiency of the coupling mismatch phenomenon is improved, thereby achieving the purpose of quickly troubleshooting the equipment shaft failure, and improving the user experience;
evaluating health of the safety coupling by determining whether the detected change is a fault associated with a failure mode of the safety coupling (Gao page 8 lines 1-30, where Gao teaches Perform a feature point extraction operation on the multiple detection point image sets to obtain multiple feature sets corresponding to the multiple detection point image sets, and any one feature set in the multiple feature sets includes: multiple feature vectors .
Step 206: Obtain a preset vibration model, and use the multiple feature point sets as the input of the vibration model to obtain the vibration restoration model.
Step 207: Receive vibration data returned by the vibration restoration model.
Step 208: Determine, according to the vibration data, that the coupling corresponding to the shaft to be detected is in a mismatch state.
The detailed description of the above steps 201 to 208 can refer to the corresponding steps of the coupling mismatch detection method described in FIG. 2, which will not be repeated here);
outputting an indicator of said health of said safety coupling based on said evaluating (Gao page 9 line 37-page 10 line 12, where Gao teaches when the user selects "Output Data", the display interface displays the vibration recovery generated after the vibration recovery The vibration data output by the model; when the user selects "data analysis", the coupling mismatch detection device analyzes the vibration data output by the vibration restoration model and displays the analysis result on the display interface) .
Gao fails to explicitly teach wherein the coupling monitoring system and method is for safety monitoring.
However, it is clear that the system of Gao is directed to provide safter. Nevertheless, Zhang teaches a fault diagnostic aid system and method wherein . With the application and development of fault diagnosis technology to detection, identification, prediction and intervention as core state detecting and fault diagnosis system is thus wide and deep used in the nuclear field and gradually establishes a corresponding computer-assisted system, so that when the emergency fault, it can correctly diagnosing the fault and take corresponding measure to guarantee and improve the safety and reliability of the nuclear reactor operation. Nuclear reactor is a large complex system, real time operating data containing a non-linear, high coupling mass, analysis using data of all of the traditional method system to grasp the comprehensive operation state of the reactor difficult. is a complex problem can be visual, visualized, fault diagnosis system for reactor sulfuring schedule, the invention aims at claims a nuclear reactor main pump failure based on gray level image assistant diagnosis system, it can well solve the problem (Zhang [0002], [0030]).
Therefore, taking the teachings of Gao and Zhang as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the application to use images from image sensor to monitor changes in the coupling and provide corresponding alert, such that appropriate safety action can be taken based on the change in the coupling shown in the analysis of the images taken by the image sensor(s).
Gao in view of Zhang fails to explicitly teach wherein the fault is detected prior to detectability of the visual failure indicator of the safety coupling.
However, Veronesi teaches a system for pipeline modeling wherein image of areas of a pipeline is received and analyzed using a data processor. The data post-processor 126 may determine visual characteristics for the portions of the pipe. Data post-processor 126 may determine visual characteristics of the pipe based on the failure likelihood for the individual portions. Data post-processor 126 may determine one or more layers of visual characteristics for the individual portions of the pipe based on the portions' respective failure likelihood. In brief overview, the different layers may include failure likelihood, priority risk zones, consequence severity, and/or criticality of failure. Data post-processor 126 may select visual indicators for the failure likelihood layer based on the predicted failure likelihoods for the individual portions of the pipe. For example, data post-processor 126 may store a set of colors that may each correspond to a different failure likelihood value in visual indicator database 132 (e.g., a relational database that stores relationships between different likelihood of risk values and visual indicators). In some embodiments, the set of colors may correspond to a color scale from blue to red with dark blue corresponding to the lowest failure likelihood and dark red corresponding to the highest failure likelihood (Veronesi [0059]-[0063]).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the application to analyze the coupling, in order to determine the likelihood of failure based on training or otherwise labels a training data set if the failures identified in the labels satisfy a criterion stored in memory 114. For example, for a training data set, model manager 124 may check historical failure database 130 (e.g., a relational database that stores a list of failures for individual portions of different pipes and about and reasons for the respective failures) to identify the failures for the portions of the pipe in the data set (Veronesi [0050]).
Regarding claims 2 and 14:
Gao in view of Zhang and in view of Veronesi teaches wherein determining whether the detected change is a fault associated with a failure mode comprises classifying the severity of the change (Zhang Abstract, [0006], [0011]) .
Regarding claims 3 and 15:
Gao in view of Zhang and in view of Veronesi teaches further comprising determining a probability of the fault to develop into a failure of the safety coupling (Zhang Abstract, [0006], [0011]).
Regarding claims 4 and 16:
Gao in view of Zhang and in view of Veronesi teaches further comprising calculating a trend or rate of the fault in developing into a failure of the safety coupling (Zhang Abstract, [0006], [0011]).
Regarding claim 5:
Gao in view of Zhang and in view of Veronesi teaches wherein one of the first and second parts of the safety coupling is static and the other part is dynamic, and wherein analyzing the image data comprises taking into account mobility of the dynamic part of the safety coupling (Gao figs. 4 and page 9-page 10).
Regarding claim 6:
Gao in view of Zhang and in view of Veronesi teaches wherein analyzing the image data comprises selecting a first point on the first perimeter and a second point on the second perimeter of the safety coupling, and calculating a distance between the first and the second point, to detect the change in the relative position (Gao figs. 4 and page 9-page 10).
Regarding claim 7:
Gao in view of Zhang and in view of Veronesi teaches further comprising re-selecting at least one of the first and the second points (Gao figs. 4, page 3 lines 21-26, page 9-page 10).
Regarding claim 8:
Gao in view of Zhang and in view of Veronesi teaches wherein the change in the relative position comprises a parallel displacement between the first perimeter and the second perimeter of the safety coupling (Gao figs. 4, page 3 lines 21-26, page 9-page 10).
Regarding claim 9:
Gao in view of Zhang and in view of Veronesi teaches wherein the change in the relative position comprises an angular change between the first perimeter and the second perimeter, or sections thereof (Gao figs. 4, page 3 lines 21-26, page 9-page 10).
Regarding claims 10 and 17:
Gao in view of Zhang and in view of Veronesi teaches wherein the system further comprises at least one sub system comprising:
at least one optical sensor configured to capture an image of said region of interest of the safety coupling for processing by said processing circuitry, wherein the region of interest comprises:
at least a portion of a first perimeter of a first part of the safety coupling and at least a portion of a second perimeter of a second part of the safety coupling(Gao figs. 4, page 3 lines 21-26, page 9-page 10).
Regarding claims 11 and 18:
Gao in view of Zhang and in view of Veronesi teaches wherein the output indicator further comprises instructions configured to guide a user for taking appropriate measures (Gao page 1 and page 2 lines 13-21).
Regarding claim 13:
Gao in view of Zhang and in view of Veronesi teaches wherein the image data of less than an entire perimeter of the valve comprises image data of about 10% to about 50% of the entire perimeter of the safety coupling (Gao figs. 3 and 4, page 3 lines 21-26, page 9-page 10; Zhang [0030]).
Regarding claim 19:
Gao in view of Zhang and in view of Veronesi teaches wherein the safety coupling is a fuel breakaway valve (Zhang [0030]-[0032]).
Conclusion
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 WEDNEL CADEAU whose telephone number is (571)270-7843. The examiner can normally be reached Mon-Fri 9:00-5:00.
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/WEDNEL CADEAU/Primary Examiner, Art Unit 2632 August 20, 2026
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