基于自适应自相关谱峭度图的滚动轴承故障诊断方法

自相关谱峭度图通过最大重叠离散小波包变换对信号频谱进行分割,并选取最大峭度值所对应频带内的信号进行诊断分析.针对自相关谱峭度图方法在分割频带时因遵循二叉树结构而导致的频带划分区域固定问题,提出一种基于自适应自相关谱峭度图方法的滚动轴承故障诊断方法.自适应自相关谱峭度图方法以改进的经验小波变换为基础,对原始信号傅里叶谱进...

Rolling Bearing Fault Diagnosis Method Based on Adaptive Autogram

In Autogram method, the signal spectrum was divided by the maximum overlap discrete wavelet packet transform, and the signals in the frequency band corresponding to the maximum kurtosis value were selected for diagnostic analysis. However, the method followed the binary tree structure when the frequency band was divided, and the division area of this structure was fixed. A fault diagnosis method of rolling bearings was proposed based on adaptive Autogram to solve this problem. The improved empirical wavelet transform was used as the basis of adaptive Autogram. In this process, the original signal Fourier spectrum was enveloped and smoothed and then segmented, thus achieving the purpose of frequency band was adaptively divided by Autogram. The simulation signals and experimental data were analyzed through the proposed method, and the analysis results were compared with the existing fast kurtogram and Autogram. The results show that the optimal demodulation frequency band may be accurately detected by the proposed method, and the fault characteristics are more obvious.