小波变换技术在电机故障诊断上的应用

电机失效的主要原因是电机轴承故障,以电流信号为基础的谱分析方法,反映故障的谐波分量幅值较小,容易被基频和电流噪声淹没.采用小波变换技术对电机轴承类故障进行诊断,将传感器采集到的振动信号用db10、db1、db5正交小波基进行4层小波分解,并对第1层细节信号d1作Hilbert包络和谱分析.实验结果表明:小波分解方法能够检测出轴承故障的特征频率,db1正交小波基得到的故障频率最为明显,与传统方法相比,小波技术在电机故障诊断中具有很大优越性.

Application of wavelet transform technology in motor failure diagnosis

The main reason why the motor fails is the motor bearing failure.The chart analysis method based on the current signal,gives less reflection of the harmonic wave component amplitude of failure,with the result that the fundamental frequency and the current crackling are more likely to be submerged.The motor failure diagnosis using the wavelet transform technology permits the collection of the vibration signal using the sensor with the perpendicular wavelet basic of db10,db1,db5 making four layer wavelet decomposing,and to d_1 making the Hilbert package chart of the first layer detail signal.The experiment result shows that the wavelet-decomposing method can checkout the characteristic frequency of bearing failure,and the use of the db1 perpendicular wavelet offers the obvious failure frequency.The wavelet technique has a great advantage over the conventional method in the motor failure diagnosis.