Application of multi-feature based on LMD in fault Feature extraction of bearing Type
Authors
Xiaoxuan Qi, Changyuan Xu
Corresponding Author
Xiaoxuan Qi
Available Online October 2015.
- 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/).
Cite this article
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 -