基于串联LSTM网络的振动台子结构试验模拟

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Abstract Substructural shaking table test has the advantages of real-time testing and numerical analysis, and can realize the recurrence of earthquake response of large-scale or even full-scale model. The real-time numerical solution of the numerical substructure in the substructural shaking table test is one of the key factors that affects the test accuracy and system stability, and determines whether the test can be successfully implementation. To improve the performance of numerical substructure analysis, the long short-term memory network (LSTM) was introduced into the substructure shaking table test, and the neural network models to simulate the physical substructure and the numerical substructure were modeled respectively. The time-delay was introduced into the training data to simulate the time-delay effect caused by the system delay. A 5-story steel frame structure model was selected to verify the neural network model. The results show that the network models have good accuracy, stability and time delay compensation ability, and the calculation efficiency can meet the real-time control requirements. The proposed neural network model can be used to solve the numerical substructure of the substructural shaking table test.

Key words： neural network LSTM；substructural shaking table test real time hybrid test ')" href="#">structure experiment technology

Received: 13 October 2022 Published: 15 December 2023

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	WANG Yumei
	JI Jinbao
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WANG Yumei,JI Jinbao,WANG Dongyue. Simulation of shaking table substructure tests based on series LSTM network[J]. JOURNAL OF VIBRATION AND SHOCK, 2023, 42(23): 80-86.

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2023/V42/I23/80

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