应用小波神经网络诊断车辆柴油机供油系统故障

摘要

In order to effectively diagnose vehicle diesel engine oil system failure, it is necessary to combine the wavelet transform with BP (Back Propagation) neural network. To extract fault feature vectors using wavelet transform and enter it in the BP neural network, we will realize the fault diagnosis of diesel engine fuel supply system. Simulation results show that the wavelet neural network fault diagnosis accuracy rate is relatively high, and the result is relatively good.%为有效诊断车辆柴油机供油系统故障,将小波变换与BP(Back Propagation)神经网络相结合.利用小波变换提取故障特征向量输入BP神经网络,实现对柴油机供油系统故障的诊断.仿真结果表明小波神经网络故障诊断准确率较高,诊断效果较好.