DocumentCode :
2697902
Title :
Apply degree of match & fuzzy rule based mode for FMECA in flight control system
Author :
Gan, Luping ; Li, Yanfeng ; Xiao, Ning-Cong ; Liu, Yu ; Huang, Hong-Zhong
Author_Institution :
Sch. of Mechatron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear :
2012
fDate :
15-18 June 2012
Firstpage :
176
Lastpage :
179
Abstract :
Failure Mode, Effects and Criticality Analysis (FMECA) is used widely in engineering practices such as aerospace, medical facilities, naval vessels and shipping, which improves the reliability and safety of the products significantly. It can eliminate potential failures, errors and problems from design, system and process. To overcome the drawback in the traditional Risk Priority Number (RPN) [1], Gargama, H. proposes a model based on the combination DM (Degree of Match) and fuzzy rule-base employing fuzzy logic method [2]. Consider the situation that the different expert may has different opinions and knowledge backgrounds, they will give different criteria. Due to the incomplete information, less data and various uncertainties, three traditional risk factors O (Occurrence), S (Severity) and D (Detectability) can be treated as fuzzy numbers, therefore, the fuzzy linguistic terms provides a very appropriate way for modeling this case. The degree of matching is used to estimate the matching between the experimental team members´ assessed information and the fuzzy number by transformation the assessed information into convex normalized fuzzy sets. An engineering example, flight control system (FCS) in unmanned vehicle, is presented to demonstrate the proposed fuzzy FMECA method. The illustrated example has shown that the proposed method advances the reliability and safety for it can model various uncertainties effectively.
Keywords :
aerospace control; autonomous aerial vehicles; case-based reasoning; control engineering computing; fuzzy logic; fuzzy reasoning; fuzzy set theory; D; DM; FCS; O; RPN; S; convex normalized fuzzy sets; degree of match; detectability; failure mode effect and criticality analysis; flight control system; fuzzy FMECA method; fuzzy linguistic terms; fuzzy logic; fuzzy numbers; fuzzy rule-based mode; occurrence; product reliability improvement; product safety improvement; risk factors; risk priority number; severity; unmanned vehicle; Aerospace control; Delta modulation; Educational institutions; Fuzzy logic; Fuzzy sets; Reliability; Uncertainty; FMECA; degree of matching; evidential reasoning; fuzzy rule-base;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2012 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4673-0786-4
Type :
conf
DOI :
10.1109/ICQR2MSE.2012.6246214
Filename :
6246214
Link To Document :
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