Condition Monitoring of Rolling Bearings using Statistical Linguistic Analysis
- 10.2991/jimet-15.2015.223How to use a DOI?
- rolling bearing, condition monitoring, statistical linguistic analysis, rank index
Defective rolling bearings generally provoke a demonstration of nonstationary and nonlinear properties. As a result, condition monitoring of a rolling bearing seems challenging due to difficulties in fault feature extraction. This study introduces statistical linguistic analysis (SLA) to investigate rolling bearing vibration data. By SLA, original vibration data are allowed to be distilled into a rank index sequence, which preserves fundamental dynamics hidden in the original data. Afterwards, a correlation coefficient is defined for detecting a change of conditions of rolling bearings. Consequently, this study develops a novel method for condition monitoring or rolling bearings using SLA. Moreover, the feasibility of the proposed method is assessed by using a set of full-lifecycle vibration data from a realistic rolling bearing. The results showed that the proposed method has the capability of detecting a change of running conditions of rolling bearings.
- © 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 - Jinshan Lin AU - Chunhong Dou PY - 2015/12 DA - 2015/12 TI - Condition Monitoring of Rolling Bearings using Statistical Linguistic Analysis BT - Proceedings of the 2015 Joint International Mechanical, Electronic and Information Technology Conference PB - Atlantis Press SP - 1182 EP - 1185 SN - 2352-538X UR - https://doi.org/10.2991/jimet-15.2015.223 DO - 10.2991/jimet-15.2015.223 ID - Lin2015/12 ER -