CPC G05B 23/0221 (2013.01) [G05B 13/0265 (2013.01); G05B 15/02 (2013.01); G06N 20/00 (2019.01); G05B 2223/02 (2018.08)] | 19 Claims |
1. A method for automatically adapting a prognostic-surveillance system to account for aging phenomena in a monitored system, the prognostic-surveillance system comprising one or more machine-learning models, the method comprising:
receiving time-series signals associated with measurements obtained at one or more sensors in the monitored system;
analyzing, using a trained inferential machine-learning model, the time-series signals to detect incipient anomalies associated with the monitored system;
periodically determining a reward/cost metric associated with using an additional trained inferential machine-learning model trained to account for aging phenomena in the monitored system;
responsive to determining that the reward/cost metric exceeds a threshold, using the additional trained inferential machine-learning model to account for one or more aging phenomena in the monitored system;
using the additional trained inferential machine-learning model in the prognostic-surveillance system;
detecting, by the prognostic-surveillance system and using the additional trained inferential learning model, an incipient anomaly in the monitored system; and
in response to the detecting, performing a servicing operation on the monitored system to remediate the incipient anomaly.
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