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Importance measure for K-out-of-n: G systems under dynamic random load considering strength degradation

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  • Lyu, Dong
  • Si, Shubin

Abstract

Taking the importance analysis of the compressor rotor system as an opportunity and combining the structural characteristics of the blade, this paper proposes a dynamic importance measure considering component strength degradation for the k-out-of-n: G system under dynamic random load. The k-out-of-n: G system consists of n components, and it works if and only if at least k components are functioning. As an effective analytical tool in the reliability field, the application of importance measures in critical equipment and complex systems is a problem worthy of study. Based on the stress-strength interference (SSI) model, the two most common degradation patterns are incorporated into the modeling of importance measure, i.e., the component strength degrades with the times of load action or degrades with time. The dynamic importance measure not only provides a continuous and dynamic analysis method for the computation of the component importance but also effectively reflects the effects of strength degradation, which will help to identify the weaknesses of systems comprehensively and accurately. A numerical case is presented to illustrate the application of the importance measure and shows some unique properties. Meanwhile, a Monte Carlo (MC) simulation method is developed to validate the results of the proposed importance measure.

Suggested Citation

  • Lyu, Dong & Si, Shubin, 2021. "Importance measure for K-out-of-n: G systems under dynamic random load considering strength degradation," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
  • Handle: RePEc:eee:reensy:v:216:y:2021:i:c:s0951832021004105
    DOI: 10.1016/j.ress.2021.107892
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    References listed on IDEAS

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    Cited by:

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    2. Zhang, Chengjie & Qi, Faqun & Zhang, Ning & Li, Yong & Huang, Hongzhong, 2022. "Maintenance policy optimization for multi-component systems considering dynamic importance of components," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    3. Liu, Mingli & Wang, Dan & Si, Shubin, 2024. "Solving algorithm design for the cost minimization reliability optimization model driven by a novel cost-based importance measure," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    4. Ma, Chengye & Du, Yongjun & Zhang, Yuchun & Cai, Zhiqiang, 2022. "Marginal and joint failure importance for K-terminal network edges under counting process," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    5. Liu, Mingli & Wang, Dan & Zhao, Jiangbin & Si, Shubin, 2022. "Importance measure construction and solving algorithm oriented to the cost-constrained reliability optimization model," Reliability Engineering and System Safety, Elsevier, vol. 222(C).

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