Damage detection based on improved particle swarm optimization using vibration data

Authors:
Fei Kang;Jun-Jie Li;Qing Xu
Affiliations:
Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian 116024, China;Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian 116024, China;Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian 116024, China
Venue:
Applied Soft Computing
Year:
2012

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Abstract

An immunity enhanced particle swarm optimization (IEPSO) algorithm, which combines particle swarm optimization (PSO) with the artificial immune system, is proposed for damage detection of structures. Some immune mechanisms, selection, receptor editing and vaccination are introduced into the basic PSO to improve its performance. The objective function for damage detection is based on vibration data, such as natural frequencies and mode shapes. The feasibility and efficiency of IEPSO are compared with the basic PSO, a differential evolution algorithm and a real-coded genetic algorithm on two examples. Results show that the proposed strategy is efficient on determining the sites and the extents of structure damages.