Reliability Prediction Method Based on State Space Model for Rolling Element Bearing

doi:10.1007/s12204-015-1629-4

上海交通大学学报（英文版） ›› 2015, Vol. 20 ›› Issue (3): 317-321.doi: 10.1007/s12204-015-1629-4

Reliability Prediction Method Based on State Space Model for Rolling Element Bearing

LI Hong-kun1 (李宏坤), ZHANG Zhi-xin2* (张志新), LI Xiu-gang3 (李秀刚), REN Yuan-jie1 (任远杰)

(1. Dalian Xinyu Science Technology Development Center Co. Ltd., Dalian 116024, Liaoning, China; 2. School of Mechanical Engineering, Dalian University, Dalian 116622, Liaoning, China; 3. Shenyang Blower Works Group Corporation, Shenyang 110869, China)

发布日期:2015-06-11
通讯作者: ZHANG Zhi-xin (张志新) E-mail:zhangzhixin@dlu.edu.cn

Reliability Prediction Method Based on State Space Model for Rolling Element Bearing

LI Hong-kun1 (李宏坤), ZHANG Zhi-xin2* (张志新), LI Xiu-gang3 (李秀刚), REN Yuan-jie1 (任远杰)

(1. Dalian Xinyu Science Technology Development Center Co. Ltd., Dalian 116024, Liaoning, China; 2. School of Mechanical Engineering, Dalian University, Dalian 116622, Liaoning, China; 3. Shenyang Blower Works Group Corporation, Shenyang 110869, China)

Published:2015-06-11
Contact: ZHANG Zhi-xin (张志新) E-mail:zhangzhixin@dlu.edu.cn

摘要/Abstract

摘要： Reliability analysis based on equipment’s performance degradation characteristics is one of the significant research areas in reliability research. Nowadays, many researches are carried on multi-sample analysis. But it is limited for a single equipment reliability prediction. Therefore, the method of reliability prediction based on state space model (SSM) is proposed in this research. Feature energy of the monitored signals is extracted with the wavelet packet analysis and the associated frequency band energy with online monitored data. Then, degradation feature is improved by moving average filtering processing taken as input pair model parameter of SSM to be estimated. In the end, state space predicting model of degradation index is established. The probability density distribution of the degradation index is predicted, and the degree of reliability is calculated. A real testing example of bearing is used to demonstrate the rationality and effectiveness of this method. It is a useful method for single sample reliability prediction.

关键词: reliability prediction, state space model, feature extraction, wavelet analysis, moving average

Abstract: Reliability analysis based on equipment’s performance degradation characteristics is one of the significant research areas in reliability research. Nowadays, many researches are carried on multi-sample analysis. But it is limited for a single equipment reliability prediction. Therefore, the method of reliability prediction based on state space model (SSM) is proposed in this research. Feature energy of the monitored signals is extracted with the wavelet packet analysis and the associated frequency band energy with online monitored data. Then, degradation feature is improved by moving average filtering processing taken as input pair model parameter of SSM to be estimated. In the end, state space predicting model of degradation index is established. The probability density distribution of the degradation index is predicted, and the degree of reliability is calculated. A real testing example of bearing is used to demonstrate the rationality and effectiveness of this method. It is a useful method for single sample reliability prediction.

Key words: reliability prediction, state space model, feature extraction, wavelet analysis, moving average

中图分类号:

TB 114.3

LI Hong-kun1 (李宏坤), ZHANG Zhi-xin2* (张志新), LI Xiu-gang3 (李秀刚), REN Yuan-jie1 (任远. Reliability Prediction Method Based on State Space Model for Rolling Element Bearing[J]. 上海交通大学学报（英文版）, 2015, 20(3): 317-321.

LI Hong-kun1 (李宏坤), ZHANG Zhi-xin2* (张志新), LI Xiu-gang3 (李秀刚), REN Yuan-jie1 (任远杰). Reliability Prediction Method Based on State Space Model for Rolling Element Bearing[J]. Journal of shanghai Jiaotong University (Science), 2015, 20(3): 317-321.

参考文献 10

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[6]	Xu Z G, Ji Y D, Zhou D H, et al. Real-time reliability prediction for a dynamic system based on the hidden degradation process identification [J]. IEEE Transactions on Reliability, 2008, 57(2), 230-242.
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Reliability Prediction Method Based on State Space Model for Rolling Element Bearing

Reliability Prediction Method Based on State Space Model for Rolling Element Bearing

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