In order to ensure the safety of the aircraft structure in complex service environment, it is necessary to formulate a reasonable inspection and maintenance plan. The inspection and repair of aircraft structure needs to determine the inspection time based on the crack growth prediction results, and the crack growth prediction is affected by a variety of random and cognitive uncertain factors. In order to effectively control such random uncertainties and track the actual crack growth process by using the prediction results of physical knowledge-based models and observation results of manual inspections, this paper proposes an intelligent digital-twin-based strategy for the inspection and maintenance of aircraft skin cracks. Taking the aircraft skin with single edge crack near a rivet hole as the object of study, this strategy takes advantages of the reduced order fracture mechanics simulation, the fatigue crack growth model, the data of crack length inspections, and the framework of the dynamic Bayesian network, comprehensively considering the uncertainties of the initial crack size, crack growth model parameters, differential pressure load in flight, measurement error etc., in order to dynamically adjust the inspection and maintenance time according to the probabilistic damage diagnosis and prognosis results. Based on the proposed method, the intelligent inspection scheme is developed respectively for three hypothetical specimens with different initial crack sizes and crack growth model parameters, and the evolution of crack sizes distribution and update of related random parameters distribution with the data of inspection is shown. Simulation results show that the proposed method can effectively control the uncertainty of crack size and related random parameters, track the actual crack growth process, and formulate the dynamic inspection and maintenance strategy for cracked aircraft skin. The method proposed in this paper can provide a referencing basis for intelligent inspection and maintenance of aircraft skin cracks in the future.
In Chinese