Application of multi-feature based on LMD in fault Feature extraction of bearing Type

DOI

10.2991/icitmi-15.2015.190How to use a DOI?

Keywords

kurtosis;approximate entropy;LMD;APEN

Abstract

This paper presents a application of kurtosis and approximate entropy in rolling bearing fault diagnosis.First use the method of LMD adaptive decomposed he rolling bearing vibration signal into different time scales of PF component , then filtered to get PF component, and rebuilt a new weighted optimization reconstruction fusion PF component, finally have the rolling bearing vibration signal feature extraction and realize fault diagnosis.

Copyright

© 2015, 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  - Xiaoxuan Qi
AU  - Changyuan Xu
PY  - 2015/10
DA  - 2015/10
TI  - Application of multi-feature based on LMD in fault Feature extraction of bearing Type
BT  - Proceedings of the 4th International Conference on Information Technology and Management Innovation
PB  - Atlantis Press
SP  - 1130
EP  - 1133
SN  - 2352-538X
UR  - https://doi.org/10.2991/icitmi-15.2015.190
DO  - 10.2991/icitmi-15.2015.190
ID  - Qi2015/10
ER  -