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41.发明申请公开(公告)号：US20200184351A1
公开(公告)日：2020-06-11
申请号：US16215345
申请日：2018-12-10
Applicant: Oracle International Corporation
Inventor： Guang C. Wang , Kenny C. Gross
Abstract: The system receives original time-series signals from sensors in a monitored system. Next, the system detects and removes spikes from the original time-series signals to produce despiked original time-series signals, which involves using the original time-series data to optimize a damping factor, which is applied to a threshold for a spike-detection technique, and using the spike-detection technique with the optimized damping factor to detect the spikes. The system then generates despiked synthetic time-series signals, which are statistically indistinguishable from the despiked original time-series signals. The system also includes synthetic spikes, which have the same temporal, amplitude and width distributions as the spikes in the original time-series signals, in the despiked synthetic time-series signals to produce synthetic time-series signals with spikes. The system uses the synthetic time-series signals with spikes to train an inferential model, and uses the inferential model to perform prognostic-surveillance operations on subsequently-received signals from the monitored system.
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42.发明申请公开(公告)号：US20200151618A1
公开(公告)日：2020-05-14
申请号：US16186365
申请日：2018-11-09
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Guang C. Wang , Edward R. Wetherbee
Abstract: During operation, the system obtains time-series sensor signals gathered from sensors in an asset during operation of the asset in an outdoor environment, wherein the time-series sensor signals include temperature signals. Next, the system produces thermally-compensated time-series sensor signals by performing a thermal-compensation operation on the temperature signals to compensate for variations in the temperature signals caused by dynamic variations in an ambient temperature of the outdoor environment. The system then trains a prognostic inferential model for a prognostic pattern-recognition system based on the thermally-compensated time-series sensor signals. During a surveillance mode for the prognostic pattern-recognition system, the system receives recently-generated time-series sensor signals from the asset, and performs a thermal-compensation operation on temperature signals in the recently-generated time-series sensor signals. Finally, the system applies the prognostic inferential model to the thermally-compensated, recently-generated time-series sensor signals to detect incipient anomalies that arise during operation of the asset.
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43.发明申请公开(公告)号：US20200081817A1
公开(公告)日：2020-03-12
申请号：US16128071
申请日：2018-09-11
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Guang C. Wang
Abstract: During operation, the system obtains the time-series sensor signals, which were gathered from sensors in a monitored system. Next, the system classifies the time-series sensor signals into stair-stepped signals and un-stair-stepped signals. The system then replaces stair-stepped values in the stair-stepped signals with interpolated values determined from un-stair-stepped values in the stair-stepped signals. Next, the system divides the time-series sensor data into a training set and an estimation set. The system then trains an inferential model on the training set, and uses the trained inferential model to replace interpolated values in the estimation set with inferential estimates. Next, the system switches roles of the training and estimation sets to produce a new training set and a new estimation set. The system then trains the inferential model on the new training set, and uses the trained inferential model to replace interpolated values in the new estimation set with inferential estimates.
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44.发明申请公开(公告)号：US20190243407A1
公开(公告)日：2019-08-08
申请号：US16052638
申请日：2018-08-02
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Guang C. Wang , Steven T. Jeffreys , Alan Paul Wood , Coleen L. MacMillan
Abstract: The disclosed embodiments relate to a system that compactly stores time-series sensor signals. During operation, the system receives original time-series signals comprising sequences of observations obtained from sensors in a monitored system. Next, the system formulizes the original time-series sensor signals to produce a set of equations, which can be used to generate synthetic time-series signals having the same correlation structure and the same stochastic properties as the original time-series signals. Finally, the system stores the formulized time-series sensor signals in place of the original time-series sensor signals.
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公开(公告)号：US12158548B2
公开(公告)日：2024-12-03
申请号：US17735245
申请日：2022-05-03
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Matthew T. Gerdes , Guang C. Wang , Timothy D. Cline , Kenny C. Gross
Abstract: Systems, methods, and other embodiments associated with acoustic fingerprint identification of devices are described. In one embodiment, a method includes generating a target acoustic fingerprint from acoustic output of a target device. A similarity metric is generated that quantifies similarity of the target acoustic fingerprint to a reference acoustic fingerprint of a reference device. The similarity metric is compared to a threshold. In response to a first comparison result of the comparing of the similarity metric to the threshold, the target device is indicated to match the reference device. In response to a second comparison result of the comparing of the similarity metric to the threshold, it is indicated that the target device does not match the reference device.
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Patent Agency Ranking
46.发明授权公开(公告)号：US12038830B2
公开(公告)日：2024-07-16
申请号：US17090151
申请日：2020-11-05
Applicant: Oracle International Corporation
Inventor： Rui Zhong , Guang C. Wang , Kenny C. Gross , Ashin George , Zexi Chen
CPC classification number: G06F11/3688 , G06F11/3692 , G06F21/602 , G06N20/00
Abstract: A double-blind comparison is performed between prognostic-surveillance systems, which are located on a local system and a remote system. During operation, the local system inserts random faults into a dataset to produce a locally seeded dataset, wherein the random faults are inserted into random signals at random times with variable fault signatures. Next, the local system exchanges the locally seeded dataset with a remote system, and in return receives a remotely seeded dataset, which was produced by the remote system by inserting different random faults into the same dataset. Next, the local system uses a local prognostic-surveillance system to analyze the remotely seeded dataset to produce locally detected faults. Finally, the local system determines a performance of the local prognostic-surveillance system by comparing the locally detected faults against actual faults in the remotely seeded fault information. The remote system similarly determines a performance of a remote prognostic-surveillance system.
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公开(公告)号：US11822036B2
公开(公告)日：2023-11-21
申请号：US17495880
申请日：2021-10-07
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： James Rohrkemper , Yifan Wu , Guang C. Wang , Kenny C. Gross
IPC: G01V3/10
CPC classification number: G01V3/10
Abstract: Embodiments for passive spychip detection through polarizability and advanced pattern recognition are described. For example a method includes inducing a magnetic field in a passive component of a target system while the target system is emitting EMI with changes in amplitude repeating at a time interval; generating a time series of measurements of a combined magnetic field strength of the induced magnetic field and the EMI; executing a frequency-domain to time-domain transformation on the time series of measurements to create time series signals of combined magnetic field strength over time at a specific frequency range; monitoring the time series signals with an ML model trained to predict correct signal values to determine whether predicted and measured values of the time series agree; and indicating that the target device may contain a passive spychip where anomalies are detected, and is free of passive spychips where no anomalies are detected.
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公开(公告)号：US11782429B2
公开(公告)日：2023-10-10
申请号：US17368840
申请日：2021-07-07
Applicant: Oracle International Corporation
Inventor： Richard P. Sonderegger , Kenneth P. Baclawski , Guang C. Wang , Anna Chystiakova , Dieter Gawlick , Zhen Hua Liu , Kenny C. Gross
CPC classification number: G05B23/0221 , G05B13/0265 , G05B15/02 , G06N20/00 , G05B2223/02
Abstract: The disclosed embodiments relate to a system that automatically adapts a prognostic-surveillance system to account for aging phenomena in a monitored system. During operation, the prognostic-surveillance system is operated in a surveillance mode, wherein a trained inferential model is used to analyze time-series signals from the monitored system to detect incipient anomalies. During the surveillance mode, the system periodically calculates a reward/cost metric associated with updating the trained inferential model. When the reward/cost metric exceeds a threshold, the system swaps the trained inferential model with an updated inferential model, which is trained to account for aging phenomena in the monitored system.
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49.发明授权公开(公告)号：US11775873B2
公开(公告)日：2023-10-03
申请号：US16005495
申请日：2018-06-11
Applicant: Oracle International Corporation
Inventor： Guang C. Wang , Kenny C. Gross , Dieter Gawlick
Abstract: First, the system obtains time-series sensor data. Next, the system identifies missing values in the time-series sensor data, and fills in the missing values through interpolation. The system then divides the time-series sensor data into a training set and an estimation set. Next, the system trains an inferential model on the training set, and uses the inferential model to replace interpolated values in the estimation set with inferential estimates. If there exist interpolated values in the training set, the system switches the training and estimation sets. The system trains a new inferential model on the new training set, and uses the new inferential model to replace interpolated values in the new estimation set with inferential estimates. The system then switches back the training and estimation sets. Finally, the system combines the training and estimation sets to produce preprocessed time-series sensor data, wherein missing values are filled in with imputed values.
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公开(公告)号：US11740122B2
公开(公告)日：2023-08-29
申请号：US17506200
申请日：2021-10-20
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Yixiu Liu , Matthew T. Gerdes , Guang C. Wang , Kenny C. Gross , Hariharan Balasubramanian
Abstract: Systems, methods, and other embodiments associated with autonomous discrimination of operation vibration signals are described herein. In one embodiment, a method includes partitioning a frequency spectrum of output into a plurality of discrete bins, wherein the output is collected from vibration sensors monitoring a reference device; generating a representative time series signal for each bin while the device is operated in a deterministic stress load; generating a PSD for each bin by converting each signal from the time domain to the frequency domain; determining a maximum power spectral density value and a peak frequency value for each bin; selecting a subset of the bins that have maximum PSD values exceeding a threshold; assigning the representative time series signals from the selected subset of bins as operation vibration signals indicative of operational load on the reference device; and configuring a machine learning model based on at least the operation vibration signals.
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