基于潜航员认知建模的动态作业风险概率评估

Compared with other complex operation systems, manned deep submergence operation has the characteristics of closed and narrow extreme environment, as well as the nature of long-endurance and high-load tasks. Once the manned deep submerging accident occurs, it is likely to cause major consequences. Therefore, it is urgent to develop a dynamic probability assessment method that can quantitatively assess the cognitive behavior performance and operational risk of oceanauts. The method for modeling the cognitive behavior of oceanauts based on knowledge and experience is proposed, which integrates more performance influencing factors into the IDAC human reliability analysis method, and develops the cognitive environment simulation program for probabilistic assessment of operational risk through system dynamics method to simulate the dynamic HEP of oceanauts. Taking a manned deep submerging mission as an example, the feasibility of the proposed method is verified. The research results would help to accurately identify key risk tasks, and guide technicians to overcome relevant technical problems, so as to improve the overall work efficiency of the human-machine-environment system in the cabin.