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Interactive Trouble Condition Sign Discovery for Hydroelectric Power Plants

机译:水力发电厂的交互式故障状况标志发现

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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.
机译:九州电力公司收集不同的传感器数据和天气信息(以下称操作数据)以维护水力发电厂在运行时的安全。在工厂中发生故障的情况很少见。而且,很难建立一个用于收集故障状态数据的实验性发电厂。因为它的成本太高。在这种情况下,我们必须找到故障状态标志。在本文中,我们认为特殊异常状况数据的上升倾向给出了故障状况的征兆。并提出了一种利用一类支持向量机和常规支持向量机的水电厂故障状态标志发现方法。本文表明,该方法是一种有效的方法,可作为水电厂风险管理的一种方法。

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