公开(公告)号：US20230121897A1

公开(公告)日：2023-04-20

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

IPC: G01N29/44 ,  G01N29/46 ,  G01N29/14 ,  G06N20/00

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.

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

IPC: G01H1/00 ,  G06N20/00 ,  G01H17/00 ,  G01M15/12

CPC classification number: G01H1/003 ,  G01H17/00 ,  G06N20/00 ,  G01M15/12

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.