To address the problems of incomplete parameter characterization, imperfect feature extraction and inac-curate health evaluation caused by the weak correlation of physical information, mission process and environmental stress in the health state evaluation of aircraft air-conditioning system, this paper proposes an intelligent health evaluation and degradation warning method fusing mission profile and Principal Component Analysis-Mahalanobis Distance (PCA-MD) to provide a set of general solutions for intelligent health evaluation of aviation equipment complex systems. First, this paper analyses the functional structure and typical failures of the air conditioning system, constructs a health characterization parameter system including the total level and the system level, and captures the coupled failure characteristics of the systems. Second, the impact of the flight mission on the air conditioning system is analyzed to design a health parameter spectrum based on the mission profile, which fully expresses the differences of the health parameters in the different mission phases. Third, a health baseline model based on Euclidean paradigm is constructed, which can comprehensively consider the influence of maintenance and inspection, as well as the environmental changes on the health baseline. Fourth, a health evaluation and degradation early warning method based on PCA-MD is proposed, which resolves the problem of the irreversibility of the covariance matrix in the construction of the health indexes and the inconsistency of the dimensions of the matrix based on the spectrum of the health parameters through the introduction of PCA, so as to achieve the efficient construction of health indexes, accurate evaluation of health state and early warning identification of performance degradation. Finally, this paper carries out an application validation study on the 1 474 practical data samples of the air conditioning system of a A320 airplane. The comparative results have validated the feasibility, practicability, and superiority of the proposed method.

The multi-mission environment and complex working conditions of long-term storage put forward strict requirements on the effective risk suppression and accurate safety evaluation of missile equipment. However, missile equipment is a typical man-machine-environment coupling complex system. Traditional safety analysis and evaluation methods cannot meet the requirements of its dynamic change and accurate quantification. Therefore, this paper proposes a safety dynamic evaluation method for missile equipment based on hierarchical safety control structure model to realize accurate safety evaluation under the long-term storage mission situation. First, according to the mission profile characteristics of missile equipment, a multi-view architecture model of process, mission, function, information and organization is constructed to achieve the accurate description of mission process and resource. Then, a hierarchical safety control structure model is proposed to determine the accident causal factors and accident chain of the targeted mission. Meanwhile, based on the mission characteristics of missile equipment, a human performance evaluation system is constructed for long-term storage in a complex and changeable environment, achieving accurate evaluation of human error rate under the man-machine-environment coupling condition. Moreover, a safety dynamic feedback evaluation method integrating STAMP and CREAM is proposed to obtain the accident rate of the missile mission through simulation. Finally, a case study of the missile test mission is performed. The proposed method specifies 6 typical accident chains of 3 categories of coordination, control and feedback in the man-machine-environment coupling scenario. Meanwhile, the accuracy of the accident rate is improved by 70. 08%, which verifies the effectiveness and superiority of the proposed method.