基于HHT/PNN的故障信息融合诊断方法

A Fault Information Fusion Diagnosis Method Based on HHT/PNN

为提高动态随机故障诊断能力,提出了基于HHT/PNN的故障信息融合诊断方法.利用HHT提取信号的瞬时频率和瞬时幅值特征,采用过程神经元网络实现对时域幅值、瞬时频率和瞬时幅值3种故障特征的融合诊断.对基于HHT/PNN和基于神经网络的2种故障诊断方法进行了比较.仿真结果表明:对于动态随机故障,基于HHT/PNN的故障信息融合诊断方法比基于神经网络的故障诊断方法的故障诊断准确度高.

A Fault information fusion diagnosis method based on HHT/PNN was brought forward to improve the diagnosis ability of dynamic and random fault. HHT was used to extract the instantaneous frequency feature and the instantaneous amplitude feature. Three fault features were fused by PNN to make fault diagnosis. The fault diagnosis method based on HHT/PNN was compared with the method based on Neural Networks. The simulation results show that for the dynamic and random fault, the fault information fusion diagnosis method based on HHT/ PNN can get higher fault diagnosis veracity than the fault diagnosis method based on Neural Networks.