Generalized exponential-dispersion process model for degradation analysis under nonlinear condition

被引:4
作者
Duan, Fengjun [1 ]
Wang, Guanjun [2 ]
机构
[1] Nanjing Univ Finance & Econ, Sch Econ, Nanjing, Peoples R China
[2] Southeast Univ, Sch Math, Nanjing, Peoples R China
关键词
exponential-dispersion process; maximum likelihood estimation; Monte Carlo simulation; reliability evaluation; state-dependent degradation; INVERSE GAUSSIAN PROCESS; GAMMA PROCESS; TESTS;
D O I
10.1002/qre.3027
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The regular exponential-dispersion (ED) process with a nonlinear path can be used to model degradation processes of many products, while it has the shortage that the degradation increment is only age-dependent, which limits its application in some circumstances. To overcome this shortage, two extensions of the ED process are suggested. For many degradation phenomena with self-modulating mechanisms, the degradation increment during the next time interval may depend on the current degradation state. To describe this degradation phenomenon, an improved ED process model with state-dependent degradation increment and a nonlinear path is proposed. Further, as an extension of the regular ED process and the improved ED process models, the generalized improved ED process is introduced, in which the degradation increment during an interval is both age- and state-dependent. For the three discussed models, the MLE method is applied to estimate the model parameters. The numerical integration and Monte Carlo (MC) simulation methods are used to evaluate the reliability. Finally, two sets of fatigue crack size data are used to illustrate the proposed models and methods.
引用
收藏
页码:957 / 970
页数:14
相关论文
共 44 条
[1]  
[Anonymous], 1993, An introduction to the bootstrap
[2]   Degradation models and implied lifetime distributions [J].
Bae, Suk Joo ;
Kuo, Way ;
Kvam, Paul H. .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2007, 92 (05) :601-608
[3]   Nonparametric optimal designs for degradation tests [J].
Balakrishnan, Narayanaswamy ;
Qin, Chengwei .
JOURNAL OF APPLIED STATISTICS, 2020, 47 (04) :624-641
[4]   Optimal design of accelerated destructive degradation tests with block effects [J].
Cai, Jiaxiang ;
Ye, Zhi-Sheng .
IISE TRANSACTIONS, 2021, 54 (01) :73-90
[5]   TRANSFORMED LEVY PROCESSES AS STATE-DEPENDENT WEAR MODELS [J].
Cha, Ji Hwan ;
Mercier, Sophie .
ADVANCES IN APPLIED PROBABILITY, 2019, 51 (02) :468-486
[6]   Random-Effect Models for Degradation Analysis Based on Nonlinear Tweedie Exponential-Dispersion Processes [J].
Chen, Zhen ;
Xia, Tangbin ;
Li, Yaping ;
Pan, Ershun .
IEEE TRANSACTIONS ON RELIABILITY, 2022, 71 (01) :47-62
[7]   Tweedie Exponential Dispersion Processes for Degradation Modeling, Prognostic, and Accelerated Degradation Test Planning [J].
Chen, Zhen ;
Xia, Tangbin ;
Li, Yanting ;
Pan, Ershun .
IEEE TRANSACTIONS ON RELIABILITY, 2020, 69 (03) :887-902
[8]   Optimal degradation-based burn-in policy using Tweedie exponential-dispersion process model with measurement errors [J].
Chen, Zhen ;
Pan, Ershun ;
Xia, Tangbin ;
Li, Yanting .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2020, 195
[9]   Bayesian analysis for the transformed exponential dispersion process with random effects [J].
Duan, Fengjun ;
Wang, Guanjun .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2022, 217
[10]   Planning of step-stress accelerated degradation test based on non-stationary gamma process with random effects [J].
Duan, Fengjun ;
Wang, Guanjun .
COMPUTERS & INDUSTRIAL ENGINEERING, 2018, 125 :467-479