Condition Monitoring with Time Series Data Based on Probabilistic Model
2021 24TH INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS 2021)(2021)
摘要
As many systems become automated, system maintenance is becoming more critical. It is important always to monitor the system condition to maintain the system more efficiently and stably. In this paper, we propose a probability-based algorithm that analyzes time-series data of a complex system. We evaluate various system conditions with high accuracy by analyzing critical data among time-series data with GMM-based probability.
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关键词
Gaussian mixture model (GMM), Data selection, Condition monitoring, Condition-based maintenance (CBM), Prognostics and health management (PHM)
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