Reliability Evaluation of Two-Phase Degradation Process with a Fuzzy Change-Point

被引:4
|
作者
Liu K. [1 ]
Dang W. [1 ]
Zou T. [1 ,2 ]
Lü C. [1 ]
Li P. [1 ,2 ]
Zhang H. [1 ]
机构
[1] Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing
[2] Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing
基金
中国国家自然科学基金;
关键词
fuzzy change-point; membership function; reliability evaluation; statistical analysis; TB; 114.3; two-phase degradation; Wiener process;
D O I
10.1007/s12204-021-2323-3
中图分类号
学科分类号
摘要
For some products, degradation mechanisms change during testing, and therefore, their degradation patterns vary at different points in time; these points are called change-points. Owing to the limitation of measurement costs, time intervals for degradation measurements are usually very long, and thus, the value of change-points cannot be determined. Conventionally, a certain degradation measurement is selected as the change-point in a two-phase degradation process. According to the tendency of the two-phase degradation process, the change-point is probably located in the interval between two neighboring degradation measurements, and it is a fuzzy variable. The imprecision of the change-point may lead to the incorrect product’s reliability evaluation results. In this paper, based on the fuzzy theory, a two-phase degradation model with a fuzzy change-point and a statistical analysis method are proposed. First, a two-phase Wiener degradation model is developed according to the membership function of the change-point. Second, the reliability evaluation is carried out using maximum likelihood estimation and a fuzzy simulation approach. Finally, the proposed methodology is verified via a case study. The results of the study show that the proposed methodology can achieve more believable reliability evaluation results compared with those of the conventional approach. © 2021, Shanghai Jiao Tong University.
引用
收藏
页码:867 / 872
页数:5
相关论文
共 50 条
  • [1] Bayesian analysis of two-phase degradation data based on change-point Wiener process
    Wang, Pingping
    Tang, Yincai
    Bae, Suk Joo
    He, Yong
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2018, 170 : 244 - 256
  • [2] Two-phase degradation data analysis with change-point detection based on Gaussian process degradation model
    Chen, Zhen
    Li, Yaping
    Zhou, Di
    Xia, Tangbin
    Pan, Ershun
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2021, 216
  • [3] Reliability modeling for a two-phase degradation system with a change point based on a Wiener process
    Gao, Hongda
    Cui, Lirong
    Dong, Qinglai
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2020, 193
  • [4] Bayesian Approach for Two-Phase Degradation Data Based on Change-Point Wiener Process With Measurement Errors
    Wang, Pingping
    Tang, Yincai
    Bae, Suk Joo
    Xu, Ancha
    IEEE TRANSACTIONS ON RELIABILITY, 2018, 67 (02) : 688 - 700
  • [5] A Bayesian approach to modeling two-phase degradation using change-point regression
    Bae, Suk Joo
    Yuan, Tao
    Ning, Shuluo
    Kuo, Way
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2015, 134 : 66 - 74
  • [6] Reliability evaluation of LCD based on two-phase Wiener degradation process
    Yan, Wei-An, 1882, Chinese Institute of Electronics (36):
  • [7] Real-time reliability evaluation of two-phase Wiener degradation process
    Yan, Wei-an
    Song, Bao-wei
    Duan, Gui-lin
    Shi, Yi-min
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2017, 46 (01) : 176 - 188
  • [8] Reliability Modeling of Two-phase Gamma Degradation Process
    Duan, Fengjun
    Wang, Guanjun
    2017 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE QUALITY, RELIABILITY AND SECURITY COMPANION (QRS-C), 2017, : 620 - 621
  • [9] Two-Phase Degradation Process Model With Abrupt Jump at Change Point Governed by Wiener Process
    Kong, Dejing
    Balakrishnan, Narayanaswamy
    Cui, Lirong
    IEEE TRANSACTIONS ON RELIABILITY, 2017, 66 (04) : 1345 - 1360
  • [10] Change-Point Detection in Two-Phase Regression with Inequality Constraints on the Regression Parameters
    Nosek, K.
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2014, 43 (05) : 932 - 946