J Shanghai Jiaotong Univ Sci ›› 2019, Vol. 24 ›› Issue (6): 805-810.doi: 10.1007/s12204-019-2126-y

• • 上一篇    

Imprecise Probability Method with the Power-Normal Model for Accelerated Life Testing

YIN Yichao(殷毅超), HUANG Hongzhong (黄洪钟), LIU Zheng (刘征)   

  1. (Center for System Reliability and Safety, University of Electronic Science and Technology of China, Chengdu 611731, China)
  • 出版日期:2019-12-15 发布日期:2019-12-07
  • 通讯作者: HUANG Hongzhong (黄洪钟) E-mail: hzhuang@uestc.edu.cn

Imprecise Probability Method with the Power-Normal Model for Accelerated Life Testing

YIN Yichao(殷毅超), HUANG Hongzhong (黄洪钟), LIU Zheng (刘征)   

  1. (Center for System Reliability and Safety, University of Electronic Science and Technology of China, Chengdu 611731, China)
  • Online:2019-12-15 Published:2019-12-07
  • Contact: HUANG Hongzhong (黄洪钟) E-mail: hzhuang@uestc.edu.cn

摘要: We present a new nonparametric predictive inference (NPI) method using a power-normal model for accelerated life testing (ALT). Combined with the accelerating link function and imprecise probability theory, the proposed method is a feasible way to predict the life of the product using ALT failure data. To validate the method, we run a series of simulations and conduct accelerated life tests with real products. The NPI lower and upper survival functions show the robustness of our method for life prediction. This is a continuous research, and some progresses have been made by updating the link function between different stress levels. We also explain how to renew and apply our model. Moreover, discussions have been made about the performance.

关键词: accelerated life testing (ALT), power-normal model, lower and upper survival functions, nonparametric predictive inference (NPI), imprecise probability

Abstract: We present a new nonparametric predictive inference (NPI) method using a power-normal model for accelerated life testing (ALT). Combined with the accelerating link function and imprecise probability theory, the proposed method is a feasible way to predict the life of the product using ALT failure data. To validate the method, we run a series of simulations and conduct accelerated life tests with real products. The NPI lower and upper survival functions show the robustness of our method for life prediction. This is a continuous research, and some progresses have been made by updating the link function between different stress levels. We also explain how to renew and apply our model. Moreover, discussions have been made about the performance.

Key words: accelerated life testing (ALT), power-normal model, lower and upper survival functions, nonparametric predictive inference (NPI), imprecise probability

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