Reliability modeling for multi-state systems with a protective device considering multiple triggering mechanism
Reliability modeling for multi-state systems with a protective device considering multiple triggering mechanism
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DOI：
10.1177/1748006x211013325
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发表时间：
2021-05
期刊：
影响因子：
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通讯作者：
Xian Zhao;Rong Li;Yu Fan;Qingan Qiu
中科院分区：
文献类型：
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作者：
Xian Zhao;Rong Li;Yu Fan;Qingan Qiu
安全关键系统的故障可能造成不可挽回的经济损失和重大的安全隐患，因此提高安全关键系统的可靠性至关重要。在工程领域中，冲击环境下的系统通常需要配备防护装置以减少外部损伤，而现有文献中没有考虑到这一点。研究了具有竞争失效模式的多状态系统在保护装置支持下的可靠性问题。根据系统故障模式，提出了基于状态和冲击次数的保护装置触发机制。也就是说，一旦系统状态或冲击的累积次数分别超过相应的临界阈值，则触发保护装置。在被触发之后，保护装置可以降低对系统的破坏性冲击的概率。当连续有效冲击的次数达到阈值时，保护装置失效。基于所建立的模型，采用有限马尔可夫链嵌入方法，推导出包括系统寿命和剩余寿命分布函数以及保护装置期望动作时间的可靠性指标。此外，两个基于年龄的更换策略，以及基于条件的更换策略，以适应不同的维修方案，并获得相应的最优解。基于发动机冷却系统的应用的数值例子来验证结果。
Failures of safety-critical systems may result in irretrievable economic losses and significant safety hazards, thus enhancing the reliability of safety-critical system is crucial. As applied widely in engineering fields, protective devices are commonly equipped for the systems operating in shock environment to reduce external damage, which has not been taken into consideration in existing literatures. This paper investigates the reliability of multi-state systems with competing failure patterns supported by a protective device. According to the system failure modes, state-based and shock number-based triggering mechanism of the protective device are developed. That is, the protective device is triggered once the system state or cumulative number of shocks exceeds corresponding critical thresholds respectively. After being triggered, the protective device can reduce the probability of damaging shocks for the system. The protective device fails when the number of consecutive valid shocks reaches a threshold. Based on the constructed model, a finite Markov chain imbedding approach is employed to derive reliability indices including distribution functions of system lifetime and residual lifetime, together with expected operating time of the protective device. Moreover, two age-based replacement policies together with a condition-based replacement policy are developed to accommodate different maintenance scenarios and corresponding optimal solutions are acquired. Numerical illustrations based on the application of cooling systems in engines are presented to validate the results.