Finite Element Model Updating of Tower Crane Based on Improved Interval Inverse Response Surface Method

Abstract

The finite element model updating technology is widely used in the mechanical and other fields. Because of the influence of many factors, there are many uncertain errors between the actual structure (such as tower crane) and the finite element model, resulting in the distortion of the finite element analysis results. Therefore, it is of great significance to study the finite element model updating with uncertain parameters. In this paper, the finite element model of a tower crane is updated considering the uncertainty of parameters. In order to improve the efficiency of model updating, the response surface model is introduced to replace the finite element model of tower crane. Considering the fact that the RBF neural network has the advantage of high precision fitting for complex problems, an improved interval inverse response surface method is proposed to update the tower crane with uncertain parameters. The feasibility of this method is proved by an example of spring-mass calculation, and the actual tower crane structure is modified. This method improves the deficiency of the interval inverse response surface method, whose result has a good calculation accuracy and efficiency.