センサデータに基づく設備の異常検知及びその原因特定

抄録

Maintenance tasks allow us to find faults in its early stage, and extend service life of facilities. Now, facilities and systems, which maintenance tasks are done under status monitoring, tend to be increasing, but there are still a lot of facilities that are executed under time plan maintenance. In this study, anomaly detection method is proposed with forecast error variance decomposition based on data provided from each sensor assembled in facilities.