A resilience measure formulation that considers sensor faults. (July 2020)

• Record Type: Journal Article
• Authors: Yoo, Minji; Kim, Taejin; Yoon, Joung Taek; Kim, Yunhan; Kim, Sooho; Youn, Byeng D.
• Is Part Of: Reliability engineering & system safety. Volume 199(2020)
• Publication Date: 2020-07
• Subjects: Resilience -- Resilience measure -- Sensor faults -- Prognostics and health management (PHM) -- Electro‐hydrostatic actuator (EHA); Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2019.02.025
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: To the best of our knowledge, a resilience measure that considers sensor faults is proposed for the first time. The effect of sensor faults on system resilience is studied via a probabilistic manner. The effectiveness of the proposed resilience measure is demonstrated through comparison with existing measures and through a case study. Abstract: Resilience is the probability that the system will not fail through resistance and recovery efforts. Most resilience studies to date have been performed with an assumption of no false alarms. However, in real-world settings, there are many possible causes of false alarms; one major cause is sensor faults. Therefore, this study proposes a newly formulated engineering resilience measure that considers sensor faults. The proposed measure is formulated in a probabilistic manner, and includes accurate system health state estimation, system reliability, and sensor reliability. In this research, the effectiveness of the proposed resilience measure is demonstrated by implementing prognostics and health management (PHM) into an electro-hydrostatic actuator (EHA). In the system, the sensor states affect the resilience of the system by misjudging the estimation of the system health state. The study shows how the proposed idea correctly estimates the resilience of the system under sensor degradation and fault. Finally, the accuracy of the proposed measure is compared with the two prior resilience measures. It is determined that the results of the proposed measure are superior for systems with low sensor reliability.