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.
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
.
DOI: 10.1007/s12204-015-1629-4
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