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A newly formulated resilience measure that considers false alarms

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  • Yoon, Joung Taek
  • Youn, Byeng D.
  • Yoo, Minji
  • Kim, Yunhan

Abstract

Engineering resilience is a measure of a system's ability to maintain its functionality by resisting and recovering from adverse events. Although false alarms often occur in engineering practice, existing quantitative measures of engineering resilience do not consider false alarms. This makes it difficult to estimate the true degree of resilience and impedes efforts to design a resilient engineered system. This paper thus proposes a new resilience measure that considers false alarms. Two types of false alarms, Type I (false fault) and Type II (false health), are considered and quantified based upon conditional probability theory. A new resilience measure, which considers false alarm rates and reliability, is then formulated in a probabilistic manner. Compared to the conventional resilience measure, the newly formulated resilience measure can estimate system resilience more rigorously and accurately. The effectiveness of the proposed resilience measure is demonstrated via numerical and electro†hydrostatic actuator case studies.

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  • Yoon, Joung Taek & Youn, Byeng D. & Yoo, Minji & Kim, Yunhan, 2017. "A newly formulated resilience measure that considers false alarms," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 417-427.
    • Handle: RePEc:eee:reensy:v:167:y:2017:i:c:p:417-427
    DOI: 10.1016/j.ress.2017.06.013
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    References listed on IDEAS

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    Cited by:

    1. Levitin, Gregory & Finkelstein, Maxim & Huang, Hong-Zhong, 2019. "Scheduling of imperfect inspections for reliability critical systems with shock-driven defects and delayed failures," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 89-98.
    2. Yoo, Minji & Kim, Taejin & Yoon, Joung Taek & Kim, Yunhan & Kim, Sooho & Youn, Byeng D., 2020. "A resilience measure formulation that considers sensor faults," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    3. Mottahedi, Adel & Sereshki, Farhang & Ataei, Mohammad & Qarahasanlou, Ali Nouri & Barabadi, Abbas, 2021. "Resilience estimation of critical infrastructure systems: Application of expert judgment," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    4. Yodo, Nita & Wang, Pingfeng, 2018. "A control-guided failure restoration framework for the design of resilient engineering systems," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 179-190.
    5. Adel Mottahedi & Farhang Sereshki & Mohammad Ataei & Ali Nouri Qarahasanlou & Abbas Barabadi, 2021. "The Resilience of Critical Infrastructure Systems: A Systematic Literature Review," Energies, MDPI, vol. 14(6), pages 1-32, March.
    6. Yoon, Joung Taek & Youn, Byeng D. & Yoo, Minji & Kim, Yunhan & Kim, Sooho, 2019. "Life-cycle maintenance cost analysis framework considering time-dependent false and missed alarms for fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 181-192.
    7. Compare, Michele & Bellani, Luca & Zio, Enrico, 2019. "Optimal allocation of prognostics and health management capabilities to improve the reliability of a power transmission network," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 164-180.

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