期刊
APPLIED SOFT COMPUTING
卷 12, 期 8, 页码 2329-2335出版社
ELSEVIER
DOI: 10.1016/j.asoc.2012.03.050
关键词
Damage identification; Particle swarm optimization; Artificial immune system; Modal parameter; Swarm intelligence
资金
- National Natural Science Foundation of China [90815024, 51109028]
- Fundamental Research Funds for the Central Universities [DUT11RC(3)38]
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.
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