基于小波分析与神经网络的电子设备故障诊断

Electronic Device Fault Diagnosis Based on Wavelet Analysis and Neural Network

电子设备在长期运行过程中由于受到各种因素的影响,不可避免地会出现故障。如何对电子设备的故障进行有效诊断具有重要的应用价值。为提高电子设备故障的诊断精度,本文提出了一种基于小波分析和RBF神经网络的电子设备故障诊断方法,该方法首先利用小波分析提取故障样本的小波系数,然后利用RBF神经网络训练小波系数实现故障诊断。基于MATLAB的仿真实验结果表明,所提出的方法是一种有效的电子设备故障诊断方法。

Electronic devices are inevitably prone to malfunctions during long-term operation due to various factors. How to effectively diagnose faults in electronic devices has important application value. To improve the accuracy of electronic device fault diagnosis, this paper proposes a method based on wavelet analysis and RBF neural network for electronic device fault diagnosis. This method first uses wavelet analysis to extract the wavelet coefficients of fault samples, and then uses RBF neural network to train wavelet coefficients for fault diagnosis. The simulation experiment results based on MATLAB show that the proposed method is an effective method for diagnosing electronic device faults.