基于BP神经网络的水轮机调速系统故障诊断

Fault Diagnosis in Hydraulic Turbine Governor Based on BP Artificial Neural Network

调速系统在发电机及电力系统中有着举足轻重的地位 ,能迅速地找出调速系统故障并及时地排除故障 ,对电力系统的安全运行具有重大意义。文中通过对葛洲坝水力发电厂二江电厂调速系统大量故障现象、故障原因、故障样本的收集、分析和整理 ,利用BP神经网络建立了水轮发电机调速系统智能诊断模型。该网络采用了三层结构、17个输入量、13个输出量的故障诊断系统 ,较完善地反映了调速系统的故障类型。经故障诊断实例检验 ,该系统诊断结果正确 ,有良好的实用价值。

The governing system of hydraulic turbine generator plays an important role in power system. It is significant to find out the faults of governing system and remove them quickly. This paper sets up a new fault diagnosis model of the hydraulic turbine generator governing system with the advanced ANN (artificial neural net). This 17-in-13-out model consists of three layers. It is proved that this model can find the fault accurately.