基于小波变换-神经网络的电力电子电路故障诊断论文.docVIP

摘  要  随着电力电子技术的迅速发展，对电力电子电路故障诊断技术的研究越来越具有 重要的意义。本课题主要针对电力电子电路故障时输出电压波形的特点，利用小波变 换理论提取故障特征，形成特征向量，并以神经网络作为故障分类器，实现了三相全 控桥式整流电路晶闸管开路故障的诊断。 本文首先对电力电子电路故障诊断研究的背景和意义进行了介绍，阐明了电力电 子电路故障诊断的特点,概括了小波变换的基础理论,分析了小波基的各项性质，为选 择小波基提供依据。以三相桥式全控整流电路为例，研究了基于 Matlab/Simulink 的电路故障仿真方法，获得了整流电路各故障状态下的输出电压波形和原始数据，并 根据小波分析良好的时频局部化特性，对故障信号进行小波变换，利用小波变换的模 极大值检测故障波形的突变点，确定故障发生时刻；利用小波多分辨率分析将信号分 解在不同的频带之内，对各个频带内的小波系数进行能量统计分析，形成表征信号的 特征向量，提取原始数据各频段的能量值作为故障分类的特征向量。利用 BP 神经网 络良好的非线性映射特性，作为故障分类器。论文给出了基于 Matlab 的 BP 神经网络 的设计方法、实际训练和测试的仿真结果，仿真结果表明，基于小波特征向量提取的 BP 神经网络故障诊断系统是有效的。 关键词：电力电子电路；故障诊断；小波变换；多分辨率分析；BP 神经网络 Abstract With the rapid development of the power electronic technology, it has great significance to study power electronic circuit fault diagnosis technology. According to the characteristics of the output voltage waveform in power electronic circuits, this paper uses wavelet transform to extract faulty features, forming feature vector, and use neural network as a fault classifier, achieve diagnosis of open fault in a three-phase full-controlled thyristor bridge rectifier circuit. In this paper, at first, the significance and background of the power electronic circuit fault diagnosis are introduced, and the characteristics of power electronic circuit fault diagnosis fault diagnosis are explained, the basic theory of wavelet transform is summarized, and various properties of the wavelet base are analyzed in order to choice wavelet bases. Taking the Three-phase full-controlled rectifier circuit for example, study the simulation method of the circuit failure based on the Matlab / Simulink, the rectifier output waveform and the raw data of various fault status are obtained. Wavelet transform is used to deal with faculty signal, based on the good characteristics of wavelet analysis at time-frequency localization, the wavelet transform modulus maxima is used to detect of faculty the mutation point. The analysis of wavelet multi-resolution is also used to decompose the signal in different f