Residual life prediction for complex systems with multi-phase degradation by ARMA-filtered hidden Markov model
文献类型：期刊论文
| 作者 | Sheng, Zhidong1; Hu, Qingpei2 ; Liu, Jian3; Yu, Dan2,4
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| 刊名 | QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT
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| 出版日期 | 2019-01-02 |
| 卷号 | 16期号:1页码:19-35 |
| 关键词 | System reliability residual life prediction multi-phase degradation hidden Markov model |
| ISSN号 | 1684-3703 |
| DOI | 10.1080/16843703.2017.1335496 |
| 英文摘要 | The performance of certain critical complex systems, such as the power output of ground photovoltaic (PV) modules or spacecraft solar arrays, exhibits a multi-phase degradation pattern due to the redundant structure. This pattern shows a degradation trend with multiple jump points, which are mixed effects of two failure modes: a soft mode of continuous smooth degradation and a hard mode of abrupt failure. Both modes need to be modeled jointly to predict the system residual life. In this paper, an autoregressive moving average model-filtered hidden Markov model is proposed to fit the multi-phase degradation data with unknown number of jump points, together with an iterative algorithm for parameter estimation. The comprehensive algorithm is composed of non-linear least-square method, recursive extended least-square method, and expectation-maximization algorithm to handle different parts of the model. The proposed methodology is applied to a specific PV module system with simulated performance measurements for its reliability evaluation and residual life prediction. Comprehensive studies have been conducted, and analysis results show better performance over competing models and more importantly all the jump points in the simulated data have been identified. Also, this algorithm converges fast with satisfactory parameter estimates accuracy, regardless of the jump point number. |
| 资助项目 | National Center for Mathematics and Interdisciplinary Sciences (CAS) ; Key Laboratory of Systems and Control (CAS) |
| WOS研究方向 | Engineering ; Operations Research & Management Science ; Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000456947900002 |
| 出版者 | NCTU-NATIONAL CHIAO TUNG UNIV PRESS |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/32307]  |
| 专题 | 系统科学研究所 |
| 通讯作者 | Hu, Qingpei |
| 作者单位 | 1.Univ Sci & Technol China, Sch Management, Hefei, Anhui, Peoples R China 2.Chinese Acad Sci, Qual & Data Sci Ctr, Acad Math & Syst Sci, Beijing, Peoples R China 3.Univ Arizona, Dept Syst & Ind Engn, Tucson, AZ 85721 USA 4.Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Sheng, Zhidong,Hu, Qingpei,Liu, Jian,et al. Residual life prediction for complex systems with multi-phase degradation by ARMA-filtered hidden Markov model[J]. QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT,2019,16(1):19-35. |
| APA | Sheng, Zhidong,Hu, Qingpei,Liu, Jian,&Yu, Dan.(2019).Residual life prediction for complex systems with multi-phase degradation by ARMA-filtered hidden Markov model.QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT,16(1),19-35. |
| MLA | Sheng, Zhidong,et al."Residual life prediction for complex systems with multi-phase degradation by ARMA-filtered hidden Markov model".QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT 16.1(2019):19-35. |
入库方式： OAI收割
来源：数学与系统科学研究院
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