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.© (2004) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call