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Failure mode division and remaining useful life prognostics of multi-indicator systems with multi-fault

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  • Wu, Bin
  • Zhang, Xiaohong
  • Shi, Hui
  • Zeng, Jianchao

Abstract

Modern large-scale industrial systems are complex in structure, and their health states are usually reflected by multiple indicators. The performance degradation of multiple indicators surpasses respective threshold, causing multiple system faults, and multiple failure modes such as redundancy, fusion, and competition among different fault combinations exist, introducing new challenges when predicting remaining useful life (RUL) of the system. This study aims to establish a unified multi-failure mode division framework and the RUL prediction model under different failure modes for multi-indicator systems. Firstly, combination relationship between different fault types caused by multi-indicators outweighing their threshold is analyzed, and different redundancy, fusion, and competition failure modes are defined. Next, the formal fault type definition and its remaining time before occurrence under different failure modes are provided. The distribution calculation model of remaining time for different fault types is derived. The corresponding system's RUL prediction model under multi-fault competition is established, and degradation modeling, parameter estimation, and RUL distribution calculation are performed using the state-space model. Eventually, the validity of the RUL prediction model according to multiple failure modes is verified by numerical experiments. Taking XJTU-SY bearing and C-MAPSS datasets as two examples, the applicability and feasibility of the given method are proved.

Suggested Citation

  • Wu, Bin & Zhang, Xiaohong & Shi, Hui & Zeng, Jianchao, 2024. "Failure mode division and remaining useful life prognostics of multi-indicator systems with multi-fault," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
  • Handle: RePEc:eee:reensy:v:244:y:2024:i:c:s095183202400036x
    DOI: 10.1016/j.ress.2024.109961
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    References listed on IDEAS

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    1. Jiao, Ruihua & Peng, Kaixiang & Dong, Jie & Zhang, Chuanfang, 2020. "Fault monitoring and remaining useful life prediction framework for multiple fault modes in prognostics," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    2. Xin, Jiyu & Akiyama, Mitsuyoshi & Frangopol, Dan M., 2023. "Sustainability-informed management optimization of asphalt pavement considering risk evaluated by multiple performance indicators using deep neural networks," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
    3. Yang, Ningning & Wang, Zhijian & Cai, Wenan & Li, Yanfeng, 2023. "Data Regeneration Based on Multiple Degradation Processes for Remaining Useful Life Estimation," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    4. Li, Yaohan & Dong, You & Guo, Hongyuan, 2023. "Copula-based multivariate renewal model for life-cycle analysis of civil infrastructure considering multiple dependent deterioration processes," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    5. Li, Xilin & Teng, Wei & Peng, Dikang & Ma, Tao & Wu, Xin & Liu, Yibing, 2023. "Feature fusion model based health indicator construction and self-constraint state-space estimator for remaining useful life prediction of bearings in wind turbines," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    6. Xiao, Chenyu & Zheng, Pai, 2023. "Integrated system-level prognosis for hybrid systems subjected to multiple intermittent faults," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
    7. Wu, Shaomin & Castro, Inma T., 2020. "Maintenance policy for a system with a weighted linear combination of degradation processes," European Journal of Operational Research, Elsevier, vol. 280(1), pages 124-133.
    8. Ta, Yuntian & Li, Yanfeng & Cai, Wenan & Zhang, Qianqian & Wang, Zhijian & Dong, Lei & Du, Wenhua, 2023. "Adaptive staged remaining useful life prediction method based on multi-sensor and multi-feature fusion," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    9. Eslami Baladeh, Aliakbar & Taghipour, Sharareh, 2022. "Reliability optimization of dynamic k-out-of-n systems with competing failure modes," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
    10. Bautista, Lucía & Castro, Inma T. & Landesa, Luis, 2022. "Condition-based maintenance for a system subject to multiple degradation processes with stochastic arrival intensity," European Journal of Operational Research, Elsevier, vol. 302(2), pages 560-574.
    11. Li, Yasong & Zhou, Zheng & Sun, Chuang & Peng, Jun & Nandi, Asoke K. & Yan, Ruqiang, 2023. "Life-cycle modeling driven by coupling competition degradation for remaining useful life prediction," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
    12. Xiong, Jiawei & Zhou, Jian & Ma, Yizhong & Zhang, Fengxia & Lin, Chenglong, 2023. "Adaptive deep learning-based remaining useful life prediction framework for systems with multiple failure patterns," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    13. Fang, Guanqi & Pan, Rong & Wang, Yukun, 2022. "Inverse Gaussian processes with correlated random effects for multivariate degradation modeling," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1177-1193.
    14. Bin Liu & Xiujie Zhao & Yiqi Liu & Phuc Do, 2021. "Maintenance optimisation for systems with multi-dimensional degradation and imperfect inspections," International Journal of Production Research, Taylor & Francis Journals, vol. 59(24), pages 7537-7559, December.
    15. Pang, Zhenan & Li, Tianmei & Pei, Hong & Si, Xiaosheng, 2023. "A condition-based prognostic approach for age- and state-dependent partially observable nonlinear degrading system," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    16. Dui, Hongyan & Zhang, Yulu & Bai, Guanghan, 2024. "Analysis of variable system cost and maintenance strategy in life cycle considering different failure modes," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    17. Kumar, Anil & Parkash, Chander & Vashishtha, Govind & Tang, Hesheng & Kundu, Pradeep & Xiang, Jiawei, 2022. "State-space modeling and novel entropy-based health indicator for dynamic degradation monitoring of rolling element bearing," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    18. Zeng, Zhiguo & Barros, Anne & Coit, David, 2023. "Dependent failure behavior modeling for risk and reliability: A systematic and critical literature review," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    19. Lin, Wenyi & Chai, Yi & Fan, Linchuan & Zhang, Ke, 2024. "Remaining useful life prediction using nonlinear multi-phase Wiener process and variational Bayesian approach," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    20. Wen, Pengfei & Zhao, Shuai & Chen, Shaowei & Li, Yong, 2021. "A generalized remaining useful life prediction method for complex systems based on composite health indicator," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    21. Fang, Guanqi & Pan, Rong & Hong, Yili, 2020. "Copula-based reliability analysis of degrading systems with dependent failures," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
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