4.7 Article

Damage detection based on improved particle swarm optimization using vibration data

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

  1. National Natural Science Foundation of China [90815024, 51109028]
  2. Fundamental Research Funds for the Central Universities [DUT11RC(3)38]

向作者/读者索取更多资源

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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