Structural system identification based on multibranch BPNN

Hongnan Li; Hao Yang; Dongsheng Li

doi:10.1117/12.539095

29 July 2004 Structural system identification based on multibranch BPNN

Hongnan Li, Hao Yang, Dongsheng Li

Proceedings Volume 5391, Smart Structures and Materials 2004: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems; (2004) https://doi.org/10.1117/12.539095
Event: Smart Structures and Materials, 2004, San Diego, CA, United States

Abstract

System identification is especially important for structural health monitoring and vibration control. It is one of the critical factors to control structural vibration with high quality and evaluate whether control method can be applied or not. In this paper, a kind of multi-branch BPNN model is proposed to identify structural dynamic system. In this model, the primary factors that affect structure's dynamic response, namely structure state variables and seismic inputs, are separately treated as the branches of the model, which is expected to enhance prediction precision. The aim of identification is to make the trained model be able to accurately predict structure's future dynamic response. When the model is established, it can be trained with collected dynamic response and seismic wave data. The vibration law of the structure is deposited in the weights of the trained multi-branch BPNN model. Then the model can be used to predict structure's future dynamic response. In this paper, a numerical example is given. The analytic result turns out that the proposed identification model can accurately predict structure's future dynamic response after being trained.

Citation Download Citation

Hongnan Li, Hao Yang, and Dongsheng Li "Structural system identification based on multibranch BPNN", Proc. SPIE 5391, Smart Structures and Materials 2004: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, (29 July 2004); https://doi.org/10.1117/12.539095

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