JOINT TRAINING METHOD FOR PREDICTING REMAINING USEFUL LIFE OF INDUSTRIAL SYSTEMS USING TIME-SERIES DATA
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United States of America
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Nov 7, 2024
app pub date -
Apr 30, 2024
filing date -
Apr 30, 2024
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Abstract
A method for using time-series data to predict remaining useful life of industrial equipment in cases where limited time-series training data is available is described. The method includes steps of monitoring the industrial equipment to sense historical time-series data associated with the industrial equipment using at least one sensor, storing the historical time-series data from the at least one sensor, accessing the historical time-series data and pre-processing the historical time-series data to extract higher-level features associated with the remaining useful life of the industrial equipment, and applying a jointly trained health predictor to the higher-level features using a computing device by executing a set of instructions from a non-transitory machine readable memory using a processor of the computing device to determine a prediction for the remaining useful life of the industrial equipment.
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