Structural damage detection based on an ant lion optimizer algorithm and trace sparse regularization

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Journal of Vibration and Shock ›› 2019, Vol. 38 ›› Issue (16) : 71-76.

CHEN Chengbin1，YU Ling1,2，PAN Chudong1，CHEN Zepeng1

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Abstract

Classical swarm intelligence (SI) based structural damage detection (SDD) methods have some common deficiencies, such as low identified accuracy and low robustness.In order to solve the above problems, a novel method based on the ant lion optimizer (ALO) algorithm and trace sparse regularization was proposed to solve the SDD problem.First of all, the SDD inverse problem was transformed into a constrained optimization problem in mathematics.According to the model updating principle, the objective function of the SDD optimization problem was defined by the structural modal parameters.Then, the trace sparse constraint was introduced into the objective function.Finally, the validity of the proposed method was verified by numerical simulations of a simply-supported beam in damage patterns and by measurement data of a steel-tube simply-supported beam.The SDD results show that the proposed SDD method can effectively update the finite element model (FEM).Under different noise levels and damage patterns, the proposed method can accurately locate damages and quantify damage severities.

Key words

Structural damage detection / antlion optimization algorithm / trace sparse regularization / constrained optimization problem / model updating

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CHEN Chengbin1，YU Ling1,2，PAN Chudong1，CHEN Zepeng1. Structural damage detection based on an ant lion optimizer algorithm and trace sparse regularization[J]. Journal of Vibration and Shock, 2019, 38(16): 71-76

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