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Volume 42 Issue 3
Mar.  2016
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Journal of Beijing University of Aeronautics and Astronautics  > 2016  >  42(3): 576-582.
CAI Zhongyi, CHEN Yunxiang, ZHANG Zhengmin, et al. Reliability assessment method of nonlinear step-stress accelerated degradation data[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(3): 576-582. doi: 10.13700/j.bh.1001-5965.2015.0459(in Chinese)
Citation: CAI Zhongyi, CHEN Yunxiang, ZHANG Zhengmin, et al. Reliability assessment method of nonlinear step-stress accelerated degradation data[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(3): 576-582. doi: 10.13700/j.bh.1001-5965.2015.0459(in Chinese)
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Reliability assessment method of nonlinear step-stress accelerated degradation data

doi: 10.13700/j.bh.1001-5965.2015.0459

  • Equipment Management & Safety Engineering College, Air Force Engineering University, Xi'an 710051, China

Funds:  Defense Advanced Research Project
  • Received Date: 08 Jul 2015
  • Publish Date: 20 Mar 2016
    Abstract
  • Aiming at nonlinear degradation data in the occasion of step-stress accelerated degradation test (SSADT), a reliability assessment method for degradation data based on Wiener process is put forward in consideration of individual performance degradation variation. Firstly, the process and performance degradation data model of SSADT are analyzed. Secondly, the nonlinear Wiener process is used to describe the nonlinear degradation process of products. The time scale model is used to change nonlinear data into linear data, and the drift coefficient of Wiener process is regarded as a random variable. A lifetime model of nonlinear degradation data is built in consideration of individual variation. According to the collected SSADT data, the two-step maximum likelihood estimation method is used to determine the unknown parameters in the lifetime model. Finally, an example of laser degradation data is analyzed to show that the presented model is matching well and the assessment result is more accurate.

     

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