度量(数据仓库)
可靠性工程
弹性(材料科学)
预言
可靠性(半导体)
概率逻辑
断层(地质)
计算机科学
工程类
风险分析(工程)
数据挖掘
人工智能
热力学
物理
地质学
医学
功率(物理)
地震学
量子力学
作者
Minji Yoo,Tae‐Jin Kim,Joung Taek Yoon,Yunhan Kim,Soo‐Ho Kim,Byeng D. Youn
标识
DOI:10.1016/j.ress.2019.02.025
摘要
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.
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