Rolling Element Bearing Fault Diagnosis Based on Multiscale General Fractal Features

Author:

Wen Weigang1,Fan Zhaoyan2,Karg Donald2,Cheng Weidong1

Affiliation:

1. School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China

2. Department of Mechanical Engineering, University of Connecticut, Storrs, CT 06269, USA

Abstract

Nonlinear characteristics are ubiquitous in the vibration signals produced by rolling element bearings. Fractal dimensions are effective tools to illustrate nonlinearity. This paper proposes a new approach based on Multiscale General Fractal Dimensions (MGFDs) to realize fault diagnosis of rolling element bearings, which are robust to the effects of variation in operating conditions. The vibration signals of bearing are analyzed to extract the general fractal dimensions in multiscales, which are in turn utilized to construct a feature space to identify fault pattern. Finally, bearing faults are revealed by pattern recognition. Case studies are carried out to evaluate the validity and accuracy of the approach. It is verified that this approach is effective for fault diagnosis of rolling element bearings under various operating conditions via experiment and data analysis.

Funder

Fundamental Research Funds for the Central Universities

Publisher

Hindawi Limited

Subject

Mechanical Engineering,Mechanics of Materials,Geotechnical Engineering and Engineering Geology,Condensed Matter Physics,Civil and Structural Engineering

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