KEYWORDS: Data modeling, Matrices, Performance modeling, Education and training, Mathematical optimization, Inspection, General packet radio service, Failure analysis, Systems modeling, Reliability
Developing a maintenance strategy for the whole life cycle of the aero-engine is an essential part of aircraft operation and management. Accurately characterizing the degradation state of aero-engines throughout their whole life cycle and developing corresponding maintenance plans to ensure safe operation and reduce maintenance costs are critical considerations that demand immediate attention. First, the state space is divided based on the main performance monitoring data of the aero-engine, and a hidden Markov model-based engine degradation state characterization model is constructed. Next, the Baum-Welch algorithm is employed to solve the model parameters, and the transition matrix is obtained based on the state transition rules. Subsequently, the optimal maintenance strategy is determined using the policy iteration algorithm with the goal of minimizing the overall life cycle maintenance cost. Finally, the feasibility and effectiveness of the proposed method are verified by utilizing actual detection data of the aero-engine as an example.
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