Application of Rank-order Morphological Filtering and Sample Entropy in Feature Extraction of Rotor Fault

DOI

10.2991/mems.2012.132How to use a DOI?

Keywords

rank-order morphological filter; sample entropy; feature extraction; rotor

Abstract

After deeply analyzing the relation between reason and symptom of rotor fault, the sample entropy was introduced into the fault diagnosis field of rotating machinery. Combined with rank-order morphological filtering and sample entropy, a novel feature extraction method was proposed for rotor. Firstly, the line structure element was selected for rank-order morphological filter to denoise the original signal. Secondly, the sample entropy of de-noised signal was calculated, the de-noised signal types were normal, unbalanced, misalignment, oil-film whirl and rubbing. Finally, the sample entropy was served as fault feature to evaluate the different fault condition. Practical results prove that the proposed method is effective on fault diagnosis of rotating machinery.

Copyright

© 2012, 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/).

Download article (PDF)

TY  - CONF
AU  - Zhang Wenbin
AU  - Guo Dewei
AU  - Pu Yasong
AU  - Zhou Yanjie
AU  - Teng Ruijing
AU  - Su Yanping
PY  - 2012/12
DA  - 2012/12
TI  - Application of Rank-order Morphological Filtering and Sample Entropy in Feature Extraction of Rotor Fault
BT  - Proceedings of the 1st International Conference on Mechanical Engineering and Material Science (MEMS 2012)
PB  - Atlantis Press
SP  - 501
EP  - 504
SN  - 1951-6851
UR  - https://doi.org/10.2991/mems.2012.132
DO  - 10.2991/mems.2012.132
ID  - Wenbin2012/12
ER  -