Proceedings of the 2016 International Forum on Management, Education and Information Technology Application

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

Authors
Yu Wei, Minqiang Xu, Yongbo Li
Corresponding Author
Yu Wei
Available Online January 2016.
DOI
https://doi.org/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.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2016 International Forum on Management, Education and Information Technology Application
Part of series
Advances in Social Science, Education and Humanities Research
Publication Date
January 2016
ISBN
978-94-6252-166-7
ISSN
2352-5398
DOI
https://doi.org/10.2991/ifmeita-16.2016.33How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - 2016 International Forum on Management, Education and Information Technology Application
PB  - Atlantis Press
SN  - 2352-5398
UR  - https://doi.org/10.2991/ifmeita-16.2016.33
DO  - https://doi.org/10.2991/ifmeita-16.2016.33
ID  - Wei2016/01
ER  -