A new gear fault diagnosis method based on improved local mean decomposition

DOI

10.2991/ifmeita-16.2016.33How to use a DOI?

Keywords

Feature extraction, Local mean decomposition (LMD), Fault diagnosis

Abstract

A new vibration feature extraction method based on improved local mean decomposition (LMD) is presented in this paper. Local mean decomposition is a novel adaptive time-frequency analysis method, which is widely used in rotating machinery fault diagnosis. However, traditional LMD decomposition results method is sensitive to noise. In order to eliminate influence of noise, Hermite-LMD is introduced. Firstly, the vibration signal is decomposed by Hermite-LMD method. Then, the fault frequency of gear is found through the envelope spectrum analysis of the first PF component. The effectiveness of the proposed method is verified by the simulation data and the practical gear fault diagnosis.

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  - Yu Wei
AU  - Minqiang Xu
AU  - Yongbo Li
PY  - 2016/01
DA  - 2016/01
TI  - A new gear fault diagnosis method based on improved local mean decomposition
BT  - Proceedings of the 2016 International Forum on Management, Education and Information Technology Application
PB  - Atlantis Press
SP  - 180
EP  - 183
SN  - 2352-5398
UR  - https://doi.org/10.2991/ifmeita-16.2016.33
DO  - 10.2991/ifmeita-16.2016.33
ID  - Wei2016/01
ER  -