Damage Identification of Beam Structures Using an Improved Big Bang-Big Crunch Algorithm

DOI

10.2991/caai-18.2018.28How to use a DOI?

Keywords

swarm intelligence; Big Bang-Big crunch; structural damage identification; beam structure; frequency domain

Abstract

Beam Structures are crucial components in constructions, and damage identification of beam structures is an important research filed in engineering. Swarm intelligence algorithms have been widely used in structural damage identification for the past few years. The Big Bang-Big Crunch algorithm is one of swarm intelligence techniques with advantages of simple implementation and high efficiency. However, it is easily trapped in local optimal results and difficult of tackling with a global optimum problem, such as structural damage identification. To overcome this drawback, an improved Big Bang-Big Crunch algorithm is proposed with taking some measures. Numerical examples illustrate that damage identification of beam structures using the frequency-domain data has been realized by the improved algorithm. The improved Big Bang-Big Crunch algorithm can identify the structural damage precisely and is insensitive to measurement noises.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhiyi Yin
AU  - Jike Liu
AU  - Zhongrong Lyu
PY  - 2018/08
DA  - 2018/08
TI  - Damage Identification of Beam Structures Using an Improved Big Bang-Big Crunch Algorithm
BT  - Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)
PB  - Atlantis Press
SP  - 119
EP  - 122
SN  - 2589-4919
UR  - https://doi.org/10.2991/caai-18.2018.28
DO  - 10.2991/caai-18.2018.28
ID  - Yin2018/08
ER  -