考虑竞争失效准则的广义k- of-n: F系统的任务中止策略

IF 1.7 4区 工程技术 Q3 ENGINEERING, INDUSTRIAL
Shuai Cao, Xiaoyue Wang
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引用次数: 1

摘要

对于潜艇、太阳能照明系统等安全关键系统,任务中止是满足一定故障条件下提高系统生存能力的有效途径。本文给出了广义k- of- n: F系统的双变量任务中止策略,该系统在存在至少m个不重叠的kc个连续失效部件或至少kt个失效部件时失效。当不重叠的kc连续失效组件数量达到预定值或失效组件总数超过预定值时,任务终止,然后启动救援程序。采用两步有限马尔可夫链嵌入法推导了任务可靠性和系统生存性。以任务可靠性最大化为目标,以任务失效总成本最小化为目标,以系统失效总成本最小化为目标,建立了优化模型。最后以太阳能照明系统为例,说明了所提策略的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mission abort strategy for generalized k-out-of-n: F systems considering competing failure criteria
For safety-critical systems such as submarines and solar lighting system, mission abort is an effective way to enhance system survivability when a certain malfunction condition is met. This paper contributes by presenting a bivariate mission abort policy for generalized k-out-of- n: F systems that fail if there are at least m non-overlapping kc consecutive failed components or at least kt failed components. When the number of non-overlapping kc consecutive failed components reaches a preset level or the total number of failed components exceeds a predetermined value, the mission is aborted, and then a rescue procedure is initiated. Mission reliability and system survivability are derived by employing a two-step finite Markov chain imbedding approach. The optimization models are formulated with the purpose of maximizing the mission reliability, and minimizing the expected total cost of mission failure and system failure, respectively. A numerical example based on a solar lighting system is presented to illustrate the applicability of the proposed policies.
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来源期刊
CiteScore
4.50
自引率
19.00%
发文量
81
审稿时长
6-12 weeks
期刊介绍: The Journal of Risk and Reliability is for researchers and practitioners who are involved in the field of risk analysis and reliability engineering. The remit of the Journal covers concepts, theories, principles, approaches, methods and models for the proper understanding, assessment, characterisation and management of the risk and reliability of engineering systems. The journal welcomes papers which are based on mathematical and probabilistic analysis, simulation and/or optimisation, as well as works highlighting conceptual and managerial issues. Papers that provide perspectives on current practices and methods, and how to improve these, are also welcome
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