Impact load identification base on LSTM neural network

It is difficult to obtain the accurate dynamic model of engineering structures and it is also impossible to directly measure the impact load exerted on the structures. To solve this problem, this paper uses Long Short-Term Memory (LSTM) neural network to identify the impact load on a vertical tail structure model. Firstly, combining with the “memory” characteristics of LSTM neural network and the relationship between impact load and responses of the vertical tail model structure, a time domain identification method of impact load based on LSTM neural network is proposed. A finite element model of vertical tail structure model is taken as research objects to identify the impact load. Furthermore, the impact load identification experiments are performed on the vertical tail structure model, the results show that the average peak error of the impact load identified by the proposed method is 3.49%, and the load time history identified by the proposed method has a high degree of coincidence with the real one, which verifies the effectiveness of the proposed impact load identification method.