A new gear fault diagnosis method based on improved local mean decomposition
Yu Wei, Minqiang Xu, Yongbo Li
Available Online January 2016.
- https://doi.org/10.2991/ifmeita-16.2016.33How to use a DOI?
- Feature extraction, Local mean decomposition (LMD), Fault diagnosis
- 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.
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 -