Degradation modeling-based remaining useful life estimation: A review on approaches for systems with heterogeneity

被引:36
|
作者
Zhang, Zhengxin [1 ]
Si, Xiaosheng [1 ]
Hu, Changhua [1 ]
Kong, Xiangyu [1 ]
机构
[1] High Tech Res Inst Xian, Dept Automat, Xian 710025, Shaanxi Provinc, Peoples R China
关键词
Remaining useful life estimation; heterogeneity; degradation modeling; data-driven; stochastic model; INVERSE GAUSSIAN PROCESS; RESIDUAL-LIFE; MARKOV MODEL; HEALTH MANAGEMENT; SPECIAL SECTION; MAINTENANCE MODEL; RELIABILITY MODEL; PROGNOSTICS; PREDICTION; STATE;
D O I
10.1177/1748006X15579322
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Prognostics and health management has drawn increasing attention and gained deepening recognition and widening applications during the past decades. Due to offering guidance for sequential managements involving inspection schedule, maintenance, replacement, and spare parts ordering, remaining useful life estimation has been termed as the kernel technology of prognostics and health management and is the focus of this research in the field of reliability. Heterogeneity is widespread in the inner states of a system and its related working environments. This article provides a review on approaches for degradation modeling and remaining useful life estimation, with an emphasis on the heterogeneity in the systems. Approaches for three kinds of heterogeneity, including the unit-to-unit variability, the variability in time-varying operating conditions, and the diversity of tasks and workloads of a system during its lifetime, are summarized consecutively, and the corresponding methods are provided. Merits and drawbacks are summed up, respectively, following each approach. In addition, several possible future research directions are provided at the end of this article.
引用
收藏
页码:343 / 355
页数:13
相关论文
共 50 条
  • [11] A Metaheuristic Approach to Remaining Useful Life Estimation of Systems Subject to Multiple Degradation Mechanisms
    Duong, Pham L. T.
    Raghavan, Nagarajan
    2017 IEEE INTERNATIONAL CONFERENCE ON PROGNOSTICS AND HEALTH MANAGEMENT (ICPHM), 2017, : 227 - 233
  • [12] Prognosis of Degradation through a Dynamic Estimation of Remaining Useful Life
    Laayouj, N.
    Jamouli, H.
    El Hail, M.
    2016 5TH INTERNATIONAL CONFERENCE ON SYSTEMS AND CONTROL (ICSC), 2016, : 126 - 133
  • [13] Remaining useful life estimation under degradation and shock damage
    Wang, Hai-Kun
    Li, Yan-Feng
    Liu, Yu
    Yang, Yuan-Jian
    Huang, Hong-Zhong
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY, 2015, 229 (03) : 200 - 208
  • [14] Stochastic degradation process modeling and remaining useful life estimation with flexible random-effects
    Zhang, Zhengxin
    Hu, Changhua
    Si, Xiaosheng
    Zhang, Jianxun
    Zheng, Jianfei
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2017, 354 (06): : 2477 - 2499
  • [15] Remaining useful life estimation based on Wiener degradation processes with random failure threshold
    Tang Sheng-jin
    Yu Chuan-qiang
    Feng Yong-bao
    Xie Jian
    Gao Qin-he
    Si Xiao-sheng
    JOURNAL OF CENTRAL SOUTH UNIVERSITY, 2016, 23 (09) : 2230 - 2241
  • [16] Remaining useful life estimation based on Wiener degradation processes with random failure threshold
    Sheng-jin Tang
    Chuan-qiang Yu
    Yong-bao Feng
    Jian Xie
    Qin-he Gao
    Xiao-sheng Si
    Journal of Central South University, 2016, 23 : 2230 - 2241
  • [17] Remaining useful life estimation based on Wiener degradation processes with random failure threshold
    唐圣金
    于传强
    冯永保
    谢建
    高钦和
    司小胜
    Journal of Central South University, 2016, 23 (09) : 2230 - 2241
  • [18] Remaining Useful Life Estimation Based on Wiener Degradation Process With Mixed Random Effects
    Duan, Feng Jun
    Wang, Guan Jun
    Wei, Wan Meng
    2020 ASIA-PACIFIC INTERNATIONAL SYMPOSIUM ON ADVANCED RELIABILITY AND MAINTENANCE MODELING (APARM), 2020,
  • [19] A Review of Remaining Useful Life Prediction Approaches for Mechanical Equipment
    Zhang, Yangyang
    Fang, Liqing
    Qi, Ziyuan
    Deng, Huiyong
    IEEE SENSORS JOURNAL, 2023, 23 (24) : 29991 - 30006
  • [20] Multivariate Relevance Vector Regression Based Degradation Modeling and Remaining Useful Life Prediction
    Wang, Xiuli
    Jiang, Bin
    Wu, Shaomin
    Lu, Ningyun
    Ding, Steven X.
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2022, 69 (09) : 9514 - 9523