基于HHT变换的起动电动机特征信号时频分析

Time frequency analysis of characteristic signalof starting motor based on HHT transform

摘要:

针对车辆起动电动机电气和机械故障发生时特征信号的时变不平稳特性,进行了时频域分析处理,提出了利用现代信号处理方法对故障信号提取特征向量的方法,主要对起动电动机的电枢和轴承故障进行诊断。在构建电机故障测试实验平台的基础上,利用破坏性实验构造了故障类型,测取了电枢电流和振动信号,分别采用小波分析理论和HHT变换对信号进行分析,通过分解再重构的方式将信号分解成了频率由高到低的不同分量,并获得了故障的特征频率,提取了特征向量。实验结果表明,基于HHT变换的现代信号处理方法在处理时变非平稳信号方面比小波分析理论更具有自适应性,更易识别。

Abstract:

For the vehicle starting motor electrical and mechanical fault signal characteristics of time-varying non-stationary characteristics of time-frequency analysis, put forward the feature vector with modern signal processing method to extract fault signal,Fault diagnosis of the armature and the bearing of the starting motor.In the foundation of motor fault test platform, the destructive test of fault types, measured the armature current and the vibration signal, Using the theory of wavelet analysis and HHT transform to analyze the signals respectively, through the decomposition and reconstruction method decomposes the signal into different frequency components from high to low, and obtained the characteristic frequency of fault, extract the feature vector.The experimental results show that the modern signal processing method based on HHT transform is more adaptive than the wavelet analysis theory in the processing of time-varying non-stationary signals.