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A reliability evaluation method for electromagnetic relays based on a novel degradation-threshold-shock model with two-sided failure thresholds

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  • Xiang, Shihu
  • Zhao, Changdong
  • Hao, Songhua
  • Li, Kui
  • Li, Wenhua

Abstract

Electromagnetic relays are widespread in modern technological systems. It is imperative to accurately evaluate their reliability, so that operation and maintenance activities can be appropriately planned to guarantee the safe and stable operation of the system. However, the existing reliability evaluation methods for relays neglect welding phenomena, which can be viewed as shocks negatively affecting reliability. Moreover, the existing degradation-threshold-shock (DTS) models assume a one-sided failure threshold, but relays have two-sided thresholds according to their special failure mechanism. Thus, the evaluation methods may overestimate reliability, and the DTS models are inapplicable. To solve these problems, a DTS model with two-sided failure thresholds is proposed with the consideration of multi-source uncertainties to capture the failure mechanism of relays. A maximum likelihood estimation method for the model parameters is proposed via the moment generating function, the limit analysis, and the formula of conditional probability. Furthermore, lower and upper bounds of reliability are derived through the event analysis, and three approximation methods are proposed based on Monte Carlo simulations, the neglect of correlation, and several means of the bounds, respectively. Finally, a real case is used to compare the proposed method with the existing methods to show the effectiveness of the proposed method.

Suggested Citation

  • Xiang, Shihu & Zhao, Changdong & Hao, Songhua & Li, Kui & Li, Wenhua, 2023. "A reliability evaluation method for electromagnetic relays based on a novel degradation-threshold-shock model with two-sided failure thresholds," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
    • Handle: RePEc:eee:reensy:v:240:y:2023:i:c:s0951832023004635
    DOI: 10.1016/j.ress.2023.109549
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    References listed on IDEAS

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    1. Tingting Huang & Yuepu Zhao & David W. Coit & Loon-Ching Tang, 2021. "Reliability assessment and lifetime prediction of degradation processes considering recoverable shock damages," IISE Transactions, Taylor & Francis Journals, vol. 53(5), pages 614-628, May.
    2. Levitin, Gregory & Xing, Liudong & Xiang, Yanping, 2021. "Optimal multiple replacement and maintenance scheduling in two-unit systems," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    3. Jin, Guang & Matthews, David E. & Zhou, Zhongbao, 2013. "A Bayesian framework for on-line degradation assessment and residual life prediction of secondary batteries inspacecraft," Reliability Engineering and System Safety, Elsevier, vol. 113(C), pages 7-20.
    4. Ye, Kewei & Wang, Han & Ma, Xiaobing, 2023. "A generalized dynamic stress-strength interference model under δ-failure criterion for self-healing protective structure," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    5. Modibbo, Umar Muhammad & Arshad, Mohd. & Abdalghani, Omer & Ali, Irfan, 2021. "Optimization and estimation in system reliability allocation problem," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    6. Zhang, Zhengxin & Si, Xiaosheng & Hu, Changhua & Lei, Yaguo, 2018. "Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods," European Journal of Operational Research, Elsevier, vol. 271(3), pages 775-796.
    7. Chen, Jun-Yu & Feng, Yun-Wen & Teng, Da & Lu, Cheng & Fei, Cheng-Wei, 2022. "Support vector machine-based similarity selection method for structural transient reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    8. Kong, Xuefeng & Yang, Jun, 2020. "Reliability analysis of composite insulators subject to multiple dependent competing failure processes with shock duration and shock damage self-recovery," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    9. Shamstabar, Yousof & Shahriari, Hamid & Samimi, Yaser, 2021. "Reliability monitoring of systems with cumulative shock-based deterioration process," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
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    Cited by:

    1. Mei, Fabin & Chen, Hao & Yang, Wenying & Zhai, Guofu, 2024. "A hybrid physics-informed machine learning approach for time-dependent reliability assessment of electromagnetic relays," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
    2. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2024. "Corrective maintenance minimizing expected mission losses in shock exposed multistate production-storage systems," Reliability Engineering and System Safety, Elsevier, vol. 252(C).

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