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Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)
Unusual Condition Mining for Risk Management of Hydroelectric Power Plants
Hong Kong, China
December 18-December 22
ISBN: 0-7695-2702-7
Takashi Onoda, Central Research Institute of Electric Power Industry, Japan
Norihiko Ito, Central Research Institute of Electric Power Industry, Japan
Hironobu Yamasaki, Kyushu Electric Power Co.,Inc., Japan
Kyushu Electric Power Co.,Inc. collects different sensor data and weather information to maintain the safety of hydroelectric power plants while the plants are running. In this paper, we consider that the abnormal condition sign may be unusual condition. This paper shows results of unusual condition patterns of bearing vibration detected 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 patterns detection in bearing vibration and maintaining hydroelectric power plants.
Citation:
Takashi Onoda, Norihiko Ito, Hironobu Yamasaki, "Unusual Condition Mining for Risk Management of Hydroelectric Power Plants," icdmw, pp.694-698, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006
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