电力电子电路的诊断具有相当的复杂性,主要原因之一是由于功率器件的损坏造成主电路结构的改变.而晶闸管是整流装置中最容易损坏的器件,因此,晶闸管的故障诊断成为电力电子电路故障诊断的首要重点.提出一种用前向神经网络来诊断三相全控桥整流电路晶闸管故障的方法.对电路发生故障时输出的波形进行分析,用故障波形的采样数据制作的样本对神经网络进行训练,将训练好的神经网络用于故障诊断.仿真和实验表明该方法是有效的.

The diagnosis of the power electronic circuit is very intricate. One of the main reasons is that the structure of the circuit will change if the power device is not working .The thyristor is the easiest to be mangled. So diagnosing the malfunction is the most important about the diagnosis of the power electronic circuit. The paper puts forward a malfunction diagnosis of the thyristors of three-phase full-bridge controlled rectifier with BP neural network. After analyzing the output waveforms of malfunctioning circuit and training a BP neural network with the sampling data of malfunctioning waveforms, a well training BP neural network is constructed and used to diagnose the malfunction. The simulation and experiment demonstrate that this method is valid.

TM1 TP183

教育部重点实验室基金