提升小波变换在煤矿轴承故障诊断中的应用研究

Application research of lifting wavelet transform in fault diagnosis of coal mine bearing

针对煤矿关键设备中滚动轴承故障诊断问题,提出将提升小波变换应用到煤矿轴承故障诊断中,介绍了提升小波变换原理,并设计了自适应提升小波预测器和升级滤波器。仿真结果表明,轴承故障信号实际测量值与理论值平均误差小于3%,说明利用提升小波变换能够实现噪声条件下轴承故障信号的准确识别。

In view of fault diagnosis problem of antifriction bearing in mine critical equipment,the paper proposed to apply lifting wavelet transform to fault diagnosis of coal mine bearing,introduced principle of lifting wavelet transform,and designed adaptive lifting wavelet predictor and upgraded filter.The simulation results show that average error of actual measurement value and theoretical value of bearing fault signal is less than 3%,which indicates that the use of lifting wavelet transform enables accurate identification of bearing fault signal under noisy conditions.