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论文类型：期刊论文

发表时间：2012-08-01

发表刊物：APPLIED SOFT COMPUTING

收录刊物：SCIE、EI

卷号：12

期号：8

页面范围：2329-2335

ISSN号：1568-4946

关键字：Damage identification; Particle swarm optimization; Artificial immune system; Modal parameter; Swarm intelligence

摘要：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. (C) 2012 Elsevier B. V. All rights reserved.