飞行控制系统组件化故障模式与影响分析方法

doi:10.3969/j.issn.1001-2400.2016.02.030

Abstract

Abstract:

The conventional approaches of failure mode and effect analysis (FMEA) have not considered the mutual-influence between failure modes as well as the component-based design of systems. In this paper, we propose a new compositional approach of FMEA. We use fuzzy numbers instead of accurate numbers to describe the risk factors such as occurrence, severity, and detection in FMEA. To improve the accuracy of conventional FMEA, we construct the hierarchical FMEA graph and the respective influence matrix for each component. Then we derive the influence vector for the failure modes and leverage this vector to amend the risk priority numbers of conventional FMEA. The analysis of a practical flight control system shows the usability of our approach. Simulation results show that our compositional approach is more efficient than the non-compositional approach.

Key words: failure mode and effect analysis, component-based design, fuzzy number, graph theory

MA Yong;MA Jianfeng;SUN Cong;ZHANG Shuang;CUI Xining;LI Yahui. Component-based failure mode and effect analysis for flight control systems[J].Journal of Xidian University, 2016, 43(2): 174-179.

References

［1］ CHANG K H, CHENG C H. Evaluating the Risk of Failure Using the Fuzzy OWA and DEMATEL Method ［J］. Journal of Intelligent Manufacturing, 2011, 22: 113-129.
［2］ CHIN K S, WANG Y M, POON G K K, et al. Failure Mode and Effects Analysis Using a Group-based Evidential Reasoning Approach ［J］. Computers ＆ Operations Research, 2009, 36(6): 1768-1779.
［3］ SHAWULU H N. Software Failure Analysis at Architecture Level Using FMEA ［J］. International Journal of Software Engineering and Its Applications, 2012, 6(1): 61-74.
［4］ POUR G. Component-based Software Development Approach: New Opportunities and Challenges ［C］//Proceedings of Technology of Object-Oriented Languages: 26. Los Alamitos: IEEE Computer Society, 1998: 376-383.
［5］ MANDAL S, MAITI J. Risk Analysis Using FMEA: Fuzzy Similarity Value and Possibility Theory Based Approach ［J］. Expert Systems with Applications, 2014, 41: 3527-3537.
［6］ GARGAMA H, CHATURVEDI S K. Criticality Assessment Models for Failure Mode Effects and Criticality Analysis Using Fuzzy Logic ［J］. IEEE Transactions on Reliability, 2011, 60(1): 102-110.
［7］ LIU H C, LIU L, BIAN Q H, et al. Failure Mode and Effects Analysis Using Fuzzy Evidential Reasoning Approach and Grey Theory ［J］. Expert Systems with Applications, 2011, 38(4): 4403-4415.
［8］ WANG Y M, CHIN K S, POON G K K, et al. Risk Evaluation in Failure Mode and Effects Analysis Using Fuzzy Weighted Geometric Mean ［J］. Expert System with Applications, 2009, 36: 1195-1207.
［9］ ZHANG Z F, CHU X N. Risk Prioritization in Failure Mode and Effects Analysis under Uncertainty ［J］. Expert Systems with Applications, 2011, 38(1): 206-214.
［10］ MAISA M S, ANA P H G, THIAGO P, et al. A Multidimensional Approach to Information Security Risk Management Using FMEA and Fuzzy Theory ［J］. International Journal of Information Management, 2014, 34(6): 733-740.
［11］ LIU H C, LIU L, LIU N. Risk Evaluation Approaches in Failure Mode and Effects Analysis: a Literature Review ［J］. Expert Systems with Applications, 2013, 40(2): 828-838.
［12］ YAGER R R. A Procedure for Ordering Fuzzy Subsets of the Unit Interval ［J］. Information Sciences, 1981, 24(2): 143-161.

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Component-based failure mode and effect analysis for flight control systems

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