Damage Identification of Beam Structures Using an Improved Big Bang-Big Crunch Algorithm
- https://doi.org/10.2991/caai-18.2018.28How to use a DOI?
- swarm intelligence; Big Bang-Big crunch; structural damage identification; beam structure; frequency domain
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.
- © 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/).
Cite this article
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 - https://doi.org/10.2991/caai-18.2018.28 ID - Yin2018/08 ER -