基于小波阈值和ACMD的滚动轴承瞬时转频估计

Estimation of Rolling Bearing Instantaneous Frequency Based on Wavelet Threshold and ACMD

针对变转速工况下滚动轴承瞬时转频估计精度受噪声影响大的问题,提出一种基于小波阈值和自适应chirp模式分解(ACMD)的转频估计方法。该方法首先利用小波阈值对原始信号做降噪处理,然后对降噪后的信号做ACMD,得到高时频分辨率时频谱,最后利用峰值搜索算法从时频图中估计瞬时转频。通过对轴承仿真信号和实测信号的分析,证明了该方法能准确估计出瞬时转频,同时增强了噪声鲁棒性,为后续变工况轴承无转速计诊断工作奠定了基础。

In view of the problem that the estimation accuracy of rolling bearing instantaneous frequency was greatly affected by noise under the condition of variable speed,a method of frequency estimation based on wavelet threshold and adaptive chirp mode decomposition was proposed.Firstly,wavelet threshold was used to denoise the original signal,and then adaptive chirp mode decomposition was used to get the high time-frequency resolution time spectrum.Finally,peak search algorithm was used to estimate the instantaneous frequency conversion from the time-frequency map.Through the analysis of the simulation signal and the measured signal of the bearing,it was proved that the method can accurately estimate the instantaneous rotating frequency,and enhance the noise robustness,which laid a foundation for the subsequent diagnosis work of the bearing without tachometer under variable working conditions.