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Structural Engineering and Mechanics Volume 68, Number 6, December25 2018 , pages 735-745 DOI: https://doi.org/10.12989/sem.2018.68.6.735 |
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An improved Big Bang-Big Crunch algorithm for structural damage detection |
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Zhiyi Yin, Jike Liu, Weili Luo and Zhongrong Lu
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| Abstract | ||
| The Big Bang-Big Crunch (BB-BC) algorithm is an effective global optimization technique of swarm intelligence with drawbacks of being easily trapped in local optimal results and of converging slowly. To overcome these shortages, an improved BB-BC algorithm (IBB-BC) is proposed in this paper with taking some measures, such as altering the reduced form of exploding radius and generating multiple mass centers. The accuracy and efficiency of IBB-BC is examined by different types of benchmark test functions. The IBB-BC is utilized for damage detection of a simply supported beam and the European Space Agency structure with an objective function established by structural frequency and modal data. Two damage scenarios are considered: damage only existed in stiffness and damage existed in both stiffness and mass. IBB-BC is also validated by an existing experimental study. Results demonstrated that IBB-BC is not trapped into local optimal results and is able to detect structural damages precisely even under measurement noise. | ||
| Key Words | ||
| swarm intelligence; BB-BC algorithm; benchmark test function; damage detection; frequency domain | ||
| Address | ||
| Zhiyi Yin, Jike Liu and Zhongrong Lu: Department of Applied Mechanics and Engineering, School of Aeronautics and Astronautics, Sun Yat-sen University, Guangzhou, Guangdong Province, 510006, P.R. China Weili Luo: School of Civil Engineering, Guangzhou University, Guangzhou, Guangdong Province, 510006, P.R. China | ||