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 .
This office action is in response to communication filed on March 13, 2026.
Claims 18-25 have been elected without traverse.
Claims 26-34 have been withdrawn.
Information Disclosure Statement
As required by M.P.E.P. 609(C), the applicant’s submission of the Information Disclosure Statement dated January 23, 2024 is acknowledged by the examiner and the cited references have been considered in the examination of the claims now pending. As required by M.P.E.P 609, a copy of the PTOL-1449 initialed and dated by the examiner is attached to the office action.
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 18-25 are rejected under 35 U.S.C. 103 as being unpatentable over Stewart et al. (US20190100989A1) in further view of “Automatic Detection of Manufacturing Equipment Cycles Using Time Series” (publicly accessible January 31, 2020); hereinafter referred to as Automatic.
Regarding claim 18, Stewart teaches an automated machine monitoring system, comprising:
a first sensor arranged to detect a first parameter associated with a first machine (A number of devices may be incorporated in the universal monitoring device to monitor and measure pump operations ... The universal monitoring device may include one or more of these sensors/devices ... a fluid pressure sensor may be used ... relay measurement fluid pressure data)([0014] and [0015]; a first sensor (e.g., fluid pressure sensor) is used to detect a first parameter (e.g., fluid pressure) with a machine (e.g., pump));
a first processor functionally coupled to receive data associated with the first parameter originating from the first sensor, the first processor being able to process the data associated with the first parameter … to detect first machine cycles (The fluid pressure sensor may relay measurement fluid pressure data to a processor ... The processor includes logic that can determine or calculate at least one of the cycle count)([0015]); and
an interface device able to display at least the data or items of information from among the processed data and the items of information relating to the data (The universal monitoring device may also transmit the sensor data and calculated data in real-time as they become available to the remote data analysis module and/or on-site operator's computing device, which may be a mobile telephone, tablet computer ... or any suitable computer, for data display, report generation, alert generation, and further analysis)([0011]; items of information data (e.g., calculated cycle count) is displayed on devices (e.g., tablet)).
Stewart differs from the claim in that Stewart fails to teach processing data using at least one time-frequency decomposition, one phase clustering, one cross-correlated time-frequency pseudo-distribution, and one peak detection on a common energy to detect machine cycles.
However, processing data to detect machine cycles using at least one time-frequency decomposition, one phase clustering, one cross-correlated time-frequency pseudo-distribution, and one peak detection on a common energy is taught by Automatic (The computation of one or more PMCs should be fully automated ... To achieve this, several methodical steps and calculation loops are necessary ... calculation of the PMC cycle time(s) with smoothing methods ... calculation of the PMC cycle time(s) with the peak clustering method ... Absolute value of power peak ... K-means-clustering ... the determined PMC is examined for similarity to all time series subsequences ... the similarity search by means of the cross-correlation function (CCF) is sufficiently accurate ... If the cross corrcoeff between PMC and a time-series subsequence exceeds)(pages 3, 4, and 5).
The examiner notes Stewart and Automatic teach a detecting machine cycles. As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Stewart to include the processing of Automatic such that data is processed using at least one time-frequency decomposition, one phase clustering, one cross-correlated time-frequency pseudo-distribution, and one peak detection on a common energy to detect machine cycles.
One would be motivated to make such a combination to provide the advantage of detecting machine cycles in a robust manner (page 1, Automatic).
Regarding claim 19, Stewart-Automatic teach the system according to claim 18,
wherein the first processor is placed in a first machine module associated with the first machine (Stewart - referring to FIG. 2, in a preferred embodiment, the universal monitoring device ... can be affixed to an exterior surface ... of the pump housing ... includes sensors and data analysis logic … a microcontroller or microprocessor)([0011] and [0012]; a machine module (i.e., universal monitoring device) includes a processor and is associated with a machine (e.g., pump)); and
wherein the first machine module is functionally connected to the interface device by means of a network (Stewart - The power end monitoring device 24 and the fluid end monitoring device 26 may communicate ... other devices, such as a data collection or analysis device 30, and devices coupled to the global computer network (Internet) 32 via a wired or wireless communication … including WiFi, Bluetooth ... or another suitable protocol or technology)([0011]).
Regarding claim 20, Stewart-Automatic teach the system according to claim 18,
wherein the first sensor is functionally connected to a first machine module associated with the first machine (Stewart - referring to FIG. 2, in a preferred embodiment, the universal monitoring device ... can be affixed to an exterior surface ... of the pump housing ... includes sensors and data analysis logic)([0011]; a machine module (i.e., universal monitoring device) includes sensors and is associated with a machine (e.g., pump)); and
wherein the first processor is placed in a computing device, the computing device being functionally connected to the first machine module and to the interface device by means of a network (Stewart - The power end monitoring device 24 and the fluid end monitoring device 26 may communicate ... other devices, such as a data collection or analysis device 30, and devices coupled to the global computer network (Internet) 32 via a wired or wireless communication … … including WiFi, Bluetooth ... or another suitable protocol or technology … remote data analysis module ... which may be a mobile telephone, tablet computer ... or any suitable computer, for data display, report generation, alert generation, and further analysis)([0011]; devices such as a computing device (i.e., collection/analysis device (e.g., computer)) communicate with a universal monitoring device via a network (e.g., Wifi); a computer includes processors).
Regarding claim 21, Stewart-Automatic teach the system according to claim 18,
wherein the first sensor is functionally connected to a first machine module associated with the first machine (Stewart - referring to FIG. 2, in a preferred embodiment, the universal monitoring device ... can be affixed to an exterior surface ... of the pump housing ... includes sensors and data analysis logic)([0011]; a machine module (i.e., universal monitoring device) includes sensors and is associated with a machine (e.g., pump)); and
wherein the first processor is placed in the interface device, the interface device being functionally connected to the first machine module by means of a network (Stewart - The power end monitoring device 24 and the fluid end monitoring device 26 may communicate ... other devices, such as a data collection or analysis device 30, and devices coupled to the global computer network (Internet) 32 via a wired or wireless communication … … including WiFi, Bluetooth ... or another suitable protocol or technology … remote data analysis module ... which may be a mobile telephone, tablet computer ... or any suitable computer, for data display, report generation, alert generation, and further analysis)([0011]; devices such as an interface device (i.e., devices coupled to internet (e.g., tablet)) communicate with a universal monitoring device via a network (e.g., Wifi); a tablet includes processors).
Regarding claim 22, Stewart-Automatic teach the system according to claim 18, wherein the first sensor is placed in a position from among on the first machine, in the first machine, and in a first machine module associated with the first machine (Stewart - universal monitoring device ... may be affixed, mounted, or incorporated into any portion of a piece of equipment)([0011]).
Regarding claim 23, Stewart-Automatic teach the system according to claim 18, comprising moreover a second sensor arranged to detect a second parameter associated with the first machine, the second sensor being functionally connected to the first processor (Stewart - The universal monitoring device may include one or more sensors ... The power end monitoring device 24 and the fluid end monitoring device 26 … may communicate with each other and with other devices, such as a data collection or analysis device 30, and devices coupled to the global computer network (Internet) 32 via a wired or wireless communication … a fluid pressure sensor may be used ... relay measurement fluid pressure data … The accelerometer can be mounted on an exterior surface of the fluid end and/or power end of the pump. The accelerometer is configured to measure or sense the movement or vibrations of the pump)([0011], [0015], and [0016]; monitoring includes a first universal monitoring device (i.e., fluid end monitoring) including a first sensor (e.g., fluid pressure sensor) to detect a first parameter (e.g., fluid pressure) and a second universal monitoring device (i.e., power end monitoring) including a second sensor (e.g., accelerometer) to detect a second parameter (e.g., movement or vibrations), the devices are all functionally connected to each via wired or wireless communication).
Regarding claim 24, Stewart-Automatic teach the system according to claim 18, wherein the first sensor is able to detect at least one from among a vibration, a sound, a pressure, a movement, an acceleration, a temperature, a magnetic field, an electromagnetic field, and a light (Stewart - Examples include: strain gauge, pressure sensor, accelerometer, vibration sensor, piezoelectric element, proximity sensor, linear variable displacement transducer (LVDT), load cell, and flow meter)([0014]).
Regarding claim 25, Stewart-Automatic teach the system according to claim 18,
comprising moreover a second sensor arranged to detect a second parameter associated with a second machine (Stewart - The universal hydraulic fracturing site equipment monitoring system and method may be used on a number of different pieces of equipment ... such as positive displacement pumps, slurry blender … charge pump ... and other equipment. It is desirable to monitor the operation of these equipment … a piezoelectric element may be incorporated within the universal monitoring device ... The piezoelectric element is configured to generate a voltage in response to applied mechanical stress)([0007] and [0017]; a second machine (e.g., another pump) can be monitored using a second sensor (e.g., piezoelectric element) to measure a second parameter (e.g., voltage)); and
a second processor functionally coupled to receive data associated with the second parameter originating from the second sensor (Stewart - The generated voltage can be relayed to a processor ... The processor includes logic that can determine or calculate at least one of the cycle count)([0017]), the second processor being able to process the data associated with the second parameter by at least one of the following actions consisting of carrying out a time-frequency decomposition, carrying out a phase clustering, carrying out a cross-correlated time-frequency pseudo- distribution, and carrying out a peak detection on a common energy to detect second machine cycles (as noted previously, although processing data to detect machine cycles using at least one time-frequency decomposition, one phase clustering, one cross-correlated time-frequency pseudo-distribution, and one peak detection on a common energy is not disclosed by Steward, said processing is disclosed by Automatic (The computation of one or more PMCs should be fully automated ... To achieve this, several methodical steps and calculation loops are necessary ... calculation of the PMC cycle time(s) with smoothing methods ... calculation of the PMC cycle time(s) with the peak clustering method ... Absolute value of power peak ... K-means-clustering ... the determined PMC is examined for similarity to all time series subsequences ... the similarity search by means of the cross-correlation function (CCF) is sufficiently accurate ... If the cross corrcoeff between PMC and a time-series subsequence exceeds)(pages 3, 4, and 5). The examiner notes Stewart and Automatic teach a detecting machine cycles. As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify Steward to include the processing of Automatic such that data is processed using at least one time-frequency decomposition, one phase clustering, one cross-correlated time-frequency pseudo-distribution, and one peak detection on a common energy to detect machine cycles. One would be motivated to make such a combination to provide the advantage of detecting machine cycles in a robust manner (page 1, Automatic)).
Conclusion
The prior art made of record on form PTO-892 and not relied upon is considered pertinent to applicant's disclosure. Applicant is required under 37 C.F.R. § 1.111(c) to consider the reference fully when responding to this action. The document cited therein and enumerated below teaches a method and apparatus for monitoring machine cycles.
US20030153997A1
US20150338312A1
US5446672
US7904254B2
US8175818B2
US9869722B1
US10916259B2
CN112101662B
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Yongjia Pan whose telephone number is (571)270-1177. The examiner can normally be reached Monday - Friday, 9:00 AM - 5:00 PM EST.
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/YONGJIA PAN/Primary Examiner, Art Unit 2118
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