A model-based safety analysis approach for airborne systems using state traversals

L. Zhuang, Zhong Lu, Haijing Song, Xihui Liang
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Abstract

Safety analysis is an important task in both the development and certification of civil aircraft. The traditional safety analysis is significantly dependent on the skills and experiences of analysts. A model-based safety analysis approach is proposed for airborne systems based on the model built with Simulink. This study builds Simulink models of typical failure modes as well as the fault injection methods. The responses of system performances are monitored by traversing all failure combinations based on a state space reduction method. The system will be in an unsafe condition when the responses exceed their thresholds. The minimal cut sets of the system are obtained automatically by recording the failure combinations leading to the unsafe condition. Finally, a lateral-directional flight control system is taken as a practical example to illustrate the application and effectiveness of our proposed method. The result shows that our method has higher accuracy and the causes of the unsafe conditions can be determined by the automatic generation of the minimal cut sets. Additionally, the cumbersome work of building a traditional safety analysis model such as the fault tree, the Markov model, or the dependence diagram can be avoided.
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基于模型的机载系统状态遍历安全分析方法
安全分析是民用飞机研制和审定中的一项重要工作。传统的安全分析在很大程度上依赖于分析人员的技能和经验。基于Simulink建立的模型,提出了一种基于模型的机载系统安全分析方法。本研究建立了典型故障模式的Simulink模型以及故障注入方法。基于状态空间约简法遍历所有故障组合,监测系统性能的响应。当响应超过阈值时,系统将处于不安全状态。通过记录导致不安全状态的故障组合,自动得到系统的最小割集。最后,以横向飞行控制系统为例,说明了该方法的应用和有效性。结果表明,该方法具有较高的精度,并且可以通过最小割集的自动生成来确定不安全条件的原因。此外,还可以避免建立传统安全分析模型(如故障树、马尔可夫模型或依赖图)的繁琐工作。
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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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