A novel dynamic model parameter updating methodology of a sluice based on vibration response

Abstract

Accurate dynamic model of the sluice plays an important role in the structural health monitoring and performance evaluation. It is difficult for the established model to truly and comprehensively reflect the overall mechanical characteristics of the sluice because of parameter uncertainty. Structural dynamic model updating based on vibration response is a feasible approach, but it relies on the modal parameters identification and reliable surrogate model. Therefore, a novel dynamic model parameter updating methodology of a sluice is proposed. Firstly, an improved stochastic subspace identification method based on adaptive variational mode decomposition is proposed to accurately obtain sluice modal parameters. Secondly, Kriging surrogate model based on orthogonal test method and particle swarm optimization is introduced. The mathematical surrogate model reflecting the strong non-linear relationship between modal parameters and material parameters with high sensitivity is constructed. Finally, taking the minimum relative error between the calculated and identified values of the sluice modal parameters as the objective function, whale optimization algorithm is used to optimize and the dynamic model parameter of the sluice is updated. A case of sluice physical model shows that the proposed method is feasible and reliable, which lays a great foundation for the structural health diagnosis of sluices.