Multi-scale autocorrelation via morphological wavelet slices for rolling element bearing fault diagnosis

Chuan Li; Ming Liang; Yi Zhang; Shumin Hou

doi:10.1016/j.ymssp.2012.03.012

ScienceGate Book Chapters

JOURNAL ARTICLE

Multi-scale autocorrelation via morphological wavelet slices for rolling element bearing fault diagnosis

Chuan Li Ming Liang Yi Zhang Shumin Hou

Year: 2012 Journal: Mechanical Systems and Signal Processing Vol: 31 Pages: 428-446 Publisher: Elsevier BV

DOI: 10.1016/j.ymssp.2012.03.012

Get Full-Text PDF Get Analytical Report

Keywords:

Rolling-element bearing Autocorrelation Wavelet Fault (geology) Bearing (navigation) Spectrogram Noise (video) Vibration Autocorrelation technique SIGNAL (programming language) Pattern recognition (psychology) Computer science Representation (politics) Acoustics Algorithm Artificial intelligence Mathematics Physics Statistics Geology

Metrics

Cited By

7.74

FWCI (Field Weighted Citation Impact)

Refs

0.97

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Machine Fault Diagnosis Techniques

Physical Sciences → Engineering → Control and Systems Engineering

Gear and Bearing Dynamics Analysis

Physical Sciences → Engineering → Mechanical Engineering

Advanced machining processes and optimization

Physical Sciences → Engineering → Mechanical Engineering

Multi-scale autocorrelation via morphological wavelet slices for rolling element bearing fault diagnosis

Metrics

Citation History

Topics

Related Documents

Rolling element bearing fault diagnosis using autocorrelation and continuous wavelet transform

Fault diagnosis of rolling element bearing using cyclic autocorrelation and wavelet transform

Rolling element bearing fault diagnosis using wavelet packets

Rolling element bearing fault diagnosis using wavelet transform

Rolling Element Bearing Fault Diagnosis Using Complex Gaussian Wavelet