基于傅里叶变换和神经网络的逆变器故障检测与诊断  

Fault Detection and Isolation of Inverter Based on FFT and Neural Network

作　　者：崔博文[1] 任章[2] 

机构地区：[1]集美大学机械工程学院厦门,361021 [2]北京航空航天大学自动化科学与电气工程学院,北京100083

出　　处：《电工技术学报》2006年第7期37-43,共7页Transactions of China Electrotechnical Society

基　　金：福建省自然科学基金计划资助项目(E0440005);福建省教育厅科研项目(JAO04230)

摘　　要：提出了一种基于傅里叶变换和神经网络的逆变器故障检测与诊断方法。利用加窗傅里叶变换提取逆变器输出信号的正序对称分量,提出了谱残差和相对谱残差的概念,利用获得的基本谱残差实现了逆变器的故障检测。通过对谱残差和谱相位的对比分析,提出了一种简单的故障判断逻辑,实现了逆变器故障桥臂定位。最后利用神经网络方法,实现了故障元件的分离。仿真结果表明了本文方法的有效性。The paper presents a approach based on FFT and neural network to detect and isolate in inverter. The positive sequence symmetrical component of the inverter output is obtained by windowing FFT, and the concept of spectral residual and relative spectral residual are presented in the paper. Firstly, the fundamental residual spectral is computed by FFT with fixed width window function, and the switch fault occurred in the inverter is detected. Secondly, an simple judge strategy for locating the faulty bridge with switch fault is proposed by using spectral residual and its phase, and the inverter bridge with switch fault are positioned. Thirdly, the fault switch is isolated using neural network. The simulation results show that the method can detect and isolate the fault effectively.

关 键 词：快速傅里叶变换 神经网络 逆变器 故障检测 故障定位 

分 类 号：TP27[自动化与计算机技术—检测技术与自动化装置]