Intelligent Fault Classification of Rolling Bearing at Variable Speed Based on Reconstructed Phase Space
- 10.2991/jrnal.2014.1.1.18How to use a DOI?
- Fault classification; Time delay; embedded dimension; phase space reconstruction; principal components analysis
Rolling bearing is a common mechanical part which is subject to be damaged. It is important to monitor the condition of bearing. An effective mean is to extract faulty features of bearing from the vibration signal. In this paper, a method is introduced to realize intelligent classification of bearing state. The vibration signal is reconstructed into phase space by estimating the time delay and embedded dimension of time series. After reconstruction, fault classification is accomplished through normalized principal component analysis. It is testified that this method is effective for classifying fault of bearing by experiment and data analysis.
- © 2013, 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 - JOUR AU - Weigang Wen AU - Weidong Cheng PY - 2014 DA - 2014/06/30 TI - Intelligent Fault Classification of Rolling Bearing at Variable Speed Based on Reconstructed Phase Space JO - Journal of Robotics, Networking and Artificial Life SP - 97 EP - 102 VL - 1 IS - 1 SN - 2352-6386 UR - https://doi.org/10.2991/jrnal.2014.1.1.18 DO - 10.2991/jrnal.2014.1.1.18 ID - Wen2014 ER -