Interactive Trouble Condition Sign Discovery for Hydroelectric Power Plants

Kyushu Electric Power Co.,Inc. collects different sensor data and weather information (hereafter, operation data) to maintain the safety of hydroelectric power plants while the plants are running. It is very rare to occur trouble condition in the plants. And it is hard to construct an experimental power generation plant for collecting the trouble condition data. Because its cost is too high. In this situation, we have to find trouble condition sign. In this paper, we consider that the rise inclination of special unusual condition data gives trouble condition sign. And we propose a trouble condition sign discovery method for hydroelectric power plants by using a one class support vector machine and a normal support vector machine. This paper shows the proposed method is useful method as a method of risk management for hydroelectric power plants.