基于自适应提升小波的漏磁信号降噪

Noise Reduction for MFL Signals Based on Adaptive Lifting Wavelet

为了解决在故障诊断中漏磁信号的噪声干扰问题,在研究了提升小波基本理论原理和特点的基础之上,提出了自适应提升小波的改进算法,并在阈值处理时引入了综合门限阈值法。应用该算法对实际采集的钢丝绳漏磁信号进行去噪处理,并将该去噪效果与现用的传统小波去噪效果进行了比较。仿真结果表明,基于自适应提升小波方法的方案比传统小波变换有更好的去噪效果。

The improved algorithm of adaptive lifting wavelet is proposed to solve the problem of noise suppression in the magnetic flux leakage（MFL） inspecting signals in fault diagnosis according to the basic theory and characteristics of adaptive lifting wavelet and comprehensive threshold processing. To verify the effectiveness of the improved lifting scheme, it is applied and compared to the traditional wavelet transform in the MFL inspecting signals noise reduction of wirerope. The simulated results show that the improved adaptive lifting wavelet scheme has achieved the noise reduction better than that by traditional wavelet transform.