决策树分类方法在水轮机组故障诊断的应用研究

由于引起水轮发电机组振动的原因较为复杂,检修人员通常很难全面把握故障征兆确定故障原因。针对此对C4.5决策树分类算法进行研究,应用决策树分类的方法对水电机组故障征兆进行分类。该方法利用典型水电机组故障特征向量建立故障诊断决策树,从而实现对水电机组振动故障的诊断。

Decision Tree Classification for Fault Diagnosis of Hydro-turbine Generating Unit

Due to the complexity of the causes of hydropower unit vibration, the maintenance staff it is often difficuh to fully grasp the fault symptoms to determine the cause of the problem. This paper focuses on the C4.5 decision tree learning algorithm, application of decision tree classification method to fault diagnosis of hydroelectric units. The party through the typical fault characteristics to establish fault diagnosis decision tree, and finally implement the classification of the fault features of hydropower unit vector.