Structural damage identification method based on multi-objective ant lion optimization and sparse regularization

Abstract

The invention discloses a structural damage identification method which combines multi-objective ant lion optimization and sparse regularization. The method comprises the following steps: a finite element model is established according to structural design parameters, modal parameters such as natural frequency and vibration mode of the structure are extracted; according to the principle of model updating, the objective function is established by using the relative frequency variation of the damaged structure and the calculated structure as well as the modal confidence criterion; the objectivefunction is optimized by using weighting strategy and trace sparse regularization; multi-objective ant lion optimization algorithm is used to optimize the objective function until the iterative termination condition is reached; finally, the optimal solution is the result of damage identification. At the same time, the invention optimize a plurality of objective functions, more accurately search for an optimal solution, and introduces a trace sparse regularization and weighting strategy to respectively improve noise robustness and identification accuracy, reduce the influence of noise and damage sensitivity of measurement response on identification result, and has better noise robustness and higher identification accuracy.

Description

technical field [0001] The invention belongs to the field of structural health monitoring, and relates to structural damage identification technology, in particular to a structural damage identification method integrating multi-objective antlion optimization and trace sparse regularization. Background technique [0002] With the rapid development of the global economy and technology, the number of various types of civil infrastructure, such as bridges and structures such as buildings, is increasing, and their scale is also increasing. Once these infrastructures are built and put into operation, their performance will gradually deteriorate due to adverse factors such as harsh service environment, long-term overload operation, and failure to repair and reinforce in time after damage. If the damage of the core components of the structure deteriorates to a certain extent, the damage will spread to each component, eventually leading to the destruction of the overall structure, an...

AI Technical Summary

Problems solved by technology

However, when each quantitative function is weighted, the method of determining the weighting coefficient is slightly inaccurate and difficult to grasp. At the same time, the weighted quantitative function is integrated into a single objective function, and the solution obtained by optimizing it has certain randomness

Images