An ADT life prediction method based on the wavelet-packet band energy

Vibration signal is often used as the monitoring data of electromechanical products health state. In order to solve the problem that is how to use the vibration data collected from Accelerated Degradation Testing (ADT) to predict the life and reliability of electromechanical product under normal conditions, this paper studies the ADT life prediction methods based on wavelet packet band energy extraction. Firstly, based on the fact that wavelet packet analysis can decompose the signal in frequency domain effectively and present all frequency domain features and details in time domain, ADT vibration data based wavelet packet band energy extraction is presented. Secondly, we propose a life prediction method combined the drift of Brownian motion (DBM) with band energy feature extraction. Finally, the application in the ADT of brush DC motor verified that the proposed method can effectively extract the features of the product life status and can accurately predict the life and reliability of the product under the normal conditions..