Adaptive wavelet envelope detection based on AR model and spectral entropy

被引：0
|
作者：
He X. [1 ]
Gao H. [1 ]
Guo L. [1 ]
Wu Y. [1 ]
机构：
[1] School of Mechanical Engineering, Southwest Jiaotong University, Chengdu
来源：
Gao, Hongli | 1600年 / Chinese Mechanical Engineering Society卷 / 28期
关键词：
Auto regressive (AR) prediction; Envelope detection; Spectral entropy; Wavelet transform;
D O I：
10.3969/j.issn.1004-132X.2017.03.016
中图分类号：
学科分类号：
摘要：
For the envelope problems of traditional fault diagnosis, a method of adaptive complex analytic wavelet envelope detection was proposed based on AR model and spectral entropy herein. The method eliminated the stationary components for linear prediction from the mechanical vibration signals by AR model, and extracted the non-stationary components of resonance damping. The generated signals were enveloped by complex analytic wavelet in different frequency bands, the best envelope was selected based on the correlation between the spectral entropy and the band-pass filter in the frequency domain. This method owns higher adaptivity, better robustness and envelope effectiveness than that of the traditional one. Thus it has favorable prospect in engineering applications. © 2017, China Mechanical Engineering Magazine Office. All right reserved.
引用
收藏
页码：348 / 352
页数：4
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