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公开(公告)号：US20220138499A1
公开(公告)日：2022-05-05
申请号：US17090112
申请日：2020-11-05
Applicant: Oracle International Corporation
Inventor： Guang C. Wang , Kenny C. Gross , Zexi Chen
Abstract: The disclosed embodiments relate to a system that trains an inferential model based on selected training vectors. During operation, the system receives training data comprising observations for a set of time-series signals gathered from sensors in a monitored system during normal fault-free operation. Next, the system divides the observations into N subgroups comprising non-overlapping time windows of observations. The system then selects observations with a local minimum value and a local maximum value for all signals from each subgroup to be training vectors for the inferential model. Finally, the system trains the inferential model using the selected training vectors. Note that by selecting observations with local minimum and maximum values to be training vectors, the system maximizes an operational range for the training vectors, which reduces clipping in estimates subsequently produced by the inferential model and thereby reduces false alarms.
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92.发明申请公开(公告)号：US20220138090A1
公开(公告)日：2022-05-05
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
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：US11308404B2
公开(公告)日：2022-04-19
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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公开(公告)号：US11307569B2
公开(公告)日：2022-04-19
申请号：US16282087
申请日：2019-02-21
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Ashin George , DeJun Li
Abstract: The system receives a set of present time-series signals gathered from sensors in the asset. Next, the system uses an inferential model to generate estimated values for the set of present time-series signals, and performs a pairwise differencing operation between actual values and the estimated values for the set of present time-series signals to produce residuals. The system then performs a sequential probability ratio test (SPRT) on the residuals to produce SPRT alarms with associated tripping frequency (TF). While the TF exceeds a TF threshold, the system iteratively adjusts sensitivity parameters for the SPRT to reduce the TF, and performs the SPRT again on the residuals. The system then uses a logistic regression model to compute a risk index for the asset based on the TF. If the risk index exceeds a threshold, the system generates a notification indicating that the asset needs to be replaced.
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公开(公告)号：US11275144B2
公开(公告)日：2022-03-15
申请号：US16820807
申请日：2020-03-17
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Edward R. Wetherbee , Andrew Lewis , Michael Dayringer , Guang C. Wang , Kenny C. Gross
Abstract: Systems, methods, and other embodiments associated with automated calibration of electromagnetic interference (EMI) fingerprint scanning instrumentation based on radio frequencies are described. In one embodiment, a method for detecting a calibration state of an EMI fingerprint scanning device includes: collecting electromagnetic signals with the EMI fingerprint scanning device for a test period of time at a geographic location; identifying one or more peak frequency bands in the collected electromagnetic signals; comparing the one or more peak frequency bands to assigned radio station frequencies at the geographic location to determine if a match is found; and generating a calibration state signal based at least in part on the comparing to indicate whether the EMI fingerprint scanning device is calibrated or not calibrated.
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Patent Agency Ranking
公开(公告)号：US20210263828A1
公开(公告)日：2021-08-26
申请号：US16801590
申请日：2020-02-26
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Sanjeev Raghavendrachar Sondur , Guang Chao Wang
Abstract: A model-based approach to determining an optimal configuration for a data center may use an environmental chamber to characterize the performance of various data center configurations at different combinations of temperature and altitude. Telemetry data may be recorded from different configurations as they execute a stress workload at each temperature/altitude combination, and the telemetry data may be used to train a corresponding library of models. When a new data center is being configured, the temperature/altitude of the new data center may be used to select a pre-trained model from a similar temperature/altitude. Performance of the current configuration can be compared to the performance of the model, and if the model performs better, a new configuration based on the model may be used as an optimal configuration for the data center.
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97.发明授权公开(公告)号：US11055396B2
公开(公告)日：2021-07-06
申请号：US16506803
申请日：2019-07-09
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Michael H. S. Dayringer , Andrew J. Lewis , Guang C. Wang
Abstract: The disclosed embodiments provide a system that detects unwanted electronic components in a target asset. During operation, the system generates a sinusoidal load for the target asset. Next, the system obtains target electromagnetic interference (EMI) signals by monitoring EMI signals generated by the target asset while the target asset is executing the sinusoidal load. The system then generates a target EMI fingerprint from the target EMI signals. Finally, the system compares the target EMI fingerprint against a reference EMI fingerprint for the target asset to determine whether the target asset contains unwanted electronic components.
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98.发明申请公开(公告)号：US20210158202A1
公开(公告)日：2021-05-27
申请号：US16691321
申请日：2019-11-21
Applicant: Oracle International Corporation
Inventor： Kenneth P. Baclawski , Dieter Gawlick , Kenny C. Gross , Zhen Hua Liu
IPC: G06N20/00 , G06F16/2458 , G06N7/00 , G06F16/28
Abstract: We describe a system that performs prognostic-surveillance operations based on an inferential model that dynamically adapts to evolving operational characteristics of a monitored asset. During a surveillance mode, the system receives a set of time-series signals gathered from sensors in the monitored asset. Next, the system uses an inferential model to generate estimated values for the set of time-series signals, and then performs a pairwise differencing operation between actual values and the estimated values for the set of time-series signals to produce residuals. Next, the system performs a sequential probability ratio test (SPRT) on the residuals to produce SPRT alarms. When a tripping frequency of the SPRT alarms exceeds a threshold value, which is indicative of an incipient anomaly in the monitored asset, the system triggers an alert. While the prognostic-surveillance system is operating in the surveillance mode, the system incrementally updates the inferential model based on the time-series signals.
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99.发明申请公开(公告)号：US20200218801A1
公开(公告)日：2020-07-09
申请号：US16244006
申请日：2019-01-09
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Ashin George
Abstract: The disclosed embodiments relate to a system that determines whether an inferential model is susceptible to spillover false alarms. During operation, the system receives a set of time-series signals from sensors in a monitored system. The system then trains the inferential model using the set of time-series signals. Next, the system tests the inferential model for susceptibility to spillover false alarms by performing the following operations for one signal at a time in the set of time-series signals. First, the system adds degradation to the signal to produce a degraded signal. The system then uses the inferential model to perform prognostic-surveillance operations on the time-series signals with the degraded signal. Finally, the system detects spillover false alarms based on results of the prognostic-surveillance operations.
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100.发明授权公开(公告)号：US10669164B2
公开(公告)日：2020-06-02
申请号：US15884851
申请日：2018-01-31
Applicant: Oracle International Corporation
Inventor： Kenny C. Gross , Sanjeev Sondur
IPC: C02F1/16 , H05K7/20 , C02F1/04 , C02F1/26 , C02F103/08
Abstract: The disclosed embodiments relate to a system that performs low-temperature desalination. During operation, the system feeds cold saline water through a liquid-cooling system in a computer data center, wherein the cold saline water is used as a coolant, thereby causing the cold saline water to become heated saline water. Next, the system feeds the heated saline water into a vacuum evaporator comprising a water column having a headspace, which is under a negative pressure due to gravity pulling on the heated saline water in the water column. This negative pressure facilitates evaporation of the heated saline water to form water vapor. Finally, the system directs the water vapor through a condenser, which condenses the water vapor to produce desalinated water.
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