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Timely and effective maintenance of aircraft structures is essential for ensuring operational safety, reducing operating costs, and extending service life. However, in current engineering practice, aircraft structural maintenance is often accompanied by a lack of complete and reliable load data, which leads to inaccurate strength and fatigue assessments of in-service aircraft structures and severely restricts subsequent structural modification and redesign. To address this inverse problem of load prediction, this paper proposes an inversion method for the extreme value of aircraft structural equivalent fatigue load based on historical maintenance data. First, historical maintenance records of aircraft structures are statistically analyzed, and the statistical fatigue life is determined by incorporating confidence and reliability assessment methods. Then, a numerical simulation model of the aircraft structure is established to obtain the predicted fatigue life under given loading conditions. Finally, an optimization framework is constructed in which the absolute difference between the predicted fatigue life and the statistical fatigue life is minimized, with the extreme value of the structural equivalent fatigue load treated as the design variable. Through iterative optimization, the structural equivalent fatigue load extreme value that best matches the actual service loading condition is identified. To verify the effectiveness of the proposed method, an aircraft kicker plate angle is selected as a case study, and the inversion results are compared with experimental data obtained from component-level fatigue tests. The results show that the prediction error of the proposed method is within 10%, demonstrating higher accuracy than conventional life prediction approaches based directly on strain data. These results indicate that the proposed method enables accurate inversion of the extreme value of aircraft structural equivalent fatigue load and provides useful guidance for aircraft structural modification design.
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