One Class SVMに基づく水力発電所軸受異常振動予兆の発見(2)

Takashi ONODA, Norihiko ITO, Kenji SHIMIZU, Nobukatsu NOBE, Hideki MURAKAWA
Kyushu Electric Power Co.,Inc. collects different sensor data and weather information to maintain the safety of hydropower plants while the plants are running. This paper shows results of unusual condition of bearing vibration detection from the collected different sensor data and weather information by using one class support vector machine. The result shows that our approach may be useful for unusual condition detection in bearing vibration and maintaining hydropower plants.
doi:10.11517/pjsai.jsai05.0.97.0 fatcat:zc643rn3ofcsln65fu4zojbhlm