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Article type: Research Article
Authors: Duan, Xiaosai*; | Yu, Suihuai | Chu, Jianjie | Cong, Yangfan
Affiliations: Key Laboratory of Industrial Design and Ergonomics, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi’an, China
Correspondence: [*] Address for correspondence: Xiaosai Duan, Key Laboratory of Industrial Design and Ergonomics, Northwestern Polytechnical University, No. 127 Friendship West Road, 710072, Xi’an, China. E-mails: [email protected], [email protected].
Abstract: BACKGROUND:The cockpit of an aircraft is the main place where the pilot controls the aircraft on a mission. An excellent cockpit environment not only ensures the pilot’s basic survival needs but also improves the comfort level and alleviates fatigue when performing missions. OBJECTIVE:On the basis of domestic and international airworthiness standards, a top-down refinement method is deployed to determine the initial goal, and the environmental criteria are fully discussed and balanced in a dynamic process to build a comprehensive evaluation system for environmental factors in the aircraft cockpit. METHODS:Based on the fuzzy comprehensive evaluation theory, an evaluation model for environmental factors is constructed by combining analytic hierarchical analysis (AHP) and particle swarm optimization (PSO). Then the feasibility of the evaluation model is verified by an illustrative example. RESULTS:The results suggest that the light environment gains the highest score among the 4 environmental criteria followed by the thermal environment, while both sound environment and microenvironment have relatively low scores. CONCLUSION:As for the 27 environmental sub-criteria, temperature, illumination, lighting clarity, light-color coordination, noise duration and pressure score the highest. The evaluation findings can provide important environmental control criteria for the subsequent environmental control system in the cockpit of the aircraft.
Keywords: Aircraft cockpit, environmental factor index, fuzzy comprehensive evaluation, analytic hierarchy process, index weight, particle swarm optimization
DOI: 10.3233/WOR-220583
Journal: Work, vol. 77, no. 1, pp. 171-184, 2024
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