Governed by: Ministry of Industry and Information Technology of the People's Republic of China
Sponsored by: Northwestern Polytechnical University  Chinese Society Aeronautics and Astronautics
Address: Aviation Building,Youyi Campus, Northwestern Polytechnical University
Research on Loads Predicting Method of Key Structure of Aircraft Based on Neural Network
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AVIC Xi’an Aircraft Design and Research Institute

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V215.5

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    Abstract:

    The load prediction based on the data used in aircraft plays an important role in the damage analysis and life prediction of aircraft, which can provide technical support for the active on-condition maintenance of aircraft. In this paper, forward neural network is used to establish the load model of shear force, bending moment and torque of the tail wing root of a large transport aircraft. Compared with the load calculated by finite element model, the prediction errors of the neural network model meet the engineering requirements, and compared with the prediction results of the multivariate linear regression model, the results show that the prediction accuracy of the neural network model is better than that of the multivariate linear regression model. The neural network model provides a feasible method for measuring the loads on key structures of a large transport aircraft.

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xue haifeng, ZHANG YANJUN, NING YU. Research on Loads Predicting Method of Key Structure of Aircraft Based on Neural Network[J]. Advances in Aeronautical Science and Engineering,2025,16(1):151-157,168

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History
  • Received:May 05,2024
  • Revised:October 31,2024
  • Adopted:November 25,2024
  • Online: December 23,2024
  • Published:
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