Feature Extraction of Bearing Status Based on Multi-Scale Bistable Stochastic Resonance Array

DOI

10.2991/icmmbe-16.2016.32How to use a DOI?

Keywords

Multi-Scale Bistable Array; Stochastic Resonance; Bearing; Feature Extraction

Abstract

Multi-scale bistable array (MSBA), which combines normalized scale transform, stochastic resonance effect driven by colored noise and parallel array, can be applied to weak signal detection under heavy noise. The experimental application in incipient fault feature detection of rolling element bearing has verified the effectiveness of MSBA model. This paper studies feature extraction method of rolling element bearing status degradation based on enhanced detection effect of MSBA model. Integrated features are proposed using local spectrum kurtosis and local signal-to-noise ratio of fundamental component of bearing faults. Different sizes of damages are planted on outer race of bearings for experimental validation.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaofei Zhang
AU  - Jingwei Gao
AU  - Lijun Song
AU  - Shuming Yang
PY  - 2016/09
DA  - 2016/09
TI  - Feature Extraction of Bearing Status Based on Multi-Scale Bistable Stochastic Resonance Array
BT  - Proceedings of the6th International Conference on Mechatronics, Materials, Biotechnology and Environment (ICMMBE 2016)
PB  - Atlantis Press
SP  - 165
EP  - 170
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmbe-16.2016.32
DO  - 10.2991/icmmbe-16.2016.32
ID  - Zhang2016/09
ER  -