Paper
28 February 2024 Risk assessment of aircraft anti-skid braking system based on improved fuzzy FMEA
Zhao Wang, Shengli Zhang, Desen Gou, Kai Liu
Author Affiliations +
Proceedings Volume 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023); 130711M (2024) https://doi.org/10.1117/12.3025525
Event: International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 2023, Shenyang, China
Abstract
A risk assessment method based on improved fuzzy FMEA is proposed to solve the problem of frequent failures caused by complex working environment of aircraft anti-skid braking system. On the basis of analyzing the application of FMEA, the fuzzy language of fault evaluation is established according to fuzzy set theory, and the standardized evaluation matrix of failure mode is established. is established according to fuzzy set theory, and the standardized evaluation matrix of failure mode is constructed by quantitatively describing expert experience through triangular fuzzy numbers; Then the grey relational-TOPSIS model is nested to calculate the comprehensive closeness degree of various failure modes, and the grey relational-TOPSIS model is nested to calculate the comprehensive closeness degree of various failure modes. Then the grey relational-TOPSIS model is nested to calculate the comprehensive closeness degree of various failure modes, and the final risk assessment conclusion is obtained. The research results show that the improved fuzzy FMEA is better than the The research results show that the improved fuzzy FMEA is better than the FMEA in evaluating risk of aircraft anti-skid braking system,and has good practical application value.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Zhao Wang, Shengli Zhang, Desen Gou, and Kai Liu "Risk assessment of aircraft anti-skid braking system based on improved fuzzy FMEA", Proc. SPIE 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 130711M (28 February 2024); https://doi.org/10.1117/12.3025525
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KEYWORDS
Fuzzy logic

Risk assessment

Matrices

Analytical research

Inspection

Design

Lithium

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