Life Prediction of Constant-Stress Accelerated Degradation Testing Using Time Series Method and Grey Theory

2010 ◽  
Vol 118-120 ◽  
pp. 616-620 ◽  
Author(s):  
Li Wang ◽  
Xiao Yang Li ◽  
Tong Min Jiang ◽  
Ting Ting Huang

This paper proposes a new life prediction method using time series and grey theory to predict product life based on Constant-Stress Accelerated Degradation Testing (CSADT) data. CSADT degradation data is modeled using time series method and predicted using grey theory. A four electric stress levels CSADT of miniature bulb is conducted to verify the proposed method. A comparison among life prediction by the proposed method, traditional methods, and real life of miniature bulb is processed. The result shows that life prediction by the proposed method is more accurate than traditional methods.

2016 ◽  
Vol 40 (4) ◽  
pp. 631-644 ◽  
Author(s):  
Fu-Qiang Sun ◽  
Xiao-Yang Li ◽  
Tong-Min Jiang

For the long-life and highly-reliable product, accelerated degradation testing (ADT) method is an effective approach for evaluating life and reliability. However, most of previous researches have been focusing on the ADT method based on single performance parameter. The statistical analysis method of constant-stress ADT (CSADT) with multiple performance parameters based on Principal Component Analysis (PCA) and Support Vector Machine (SVM) is proposed in this paper. PCA is utilized to process the CSADT data in order to reduce the dimension of performance parameters. Then, SVM is applying in modelling the degradation process of the principal components. The engineering example proves that the method is feasible and efficient.


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