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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.
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. 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 In the end, state probability 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 m ethod for single sample reliability prediction