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https://doi.org/10.21595/jve.2017.18571
Title: | Structural health monitoring of 3d frame structures using finite element modal analysis and genetic algorithm | Authors: | Tiachacht, S Bouazzouni, A Khatir, K Behtani, A Zhou, Y.-L.M Wahab, M.A |
Keywords: | Benchmarking Damage detection Finite element method Floors Genetic algorithms Modal analysis Optimization Structural frames 3D frames Damage assessments Damage Identification Damaged structures Experimental benchmarks Finite element modal analysis New applications Optimization problems Structural health monitoring |
Issue Date: | 2018 | Publisher: | JVE International | Citation: | Tiachacht, S, Bouazzouni, A, Khatir, K, Behtani, A, Zhou, Y.-L.M, Wahab, M.A (2018). Structural health monitoring of 3d frame structures using finite element modal analysis and genetic algorithm. Journal of Vibroengineering 20 (1) : 202-214. ScholarBank@NUS Repository. https://doi.org/10.21595/jve.2017.18571 | Rights: | Attribution 4.0 International | Abstract: | In this paper, we present a new application based on Genetic Algorithm (GA) to detect damage in 3D frame structures. Finite Element Method (FEM) is used to build models for intact and damaged structures. The identification of damage is formulated as an optimization problem using GA and the changes in natural frequencies. A 3D frame structure with two floor is used, as a numerical example, for damage identification. The proposed method is then applied to identify some removed elements. The results obtained using FEM is validated using experimental benchmark test of a 3D frame structure with eight floors. The results show that the proposed technique gives good damage identification compared with literature [1]. Furthermore, there is no error recorded in the prediction of location, however a small error is recorded in detecting damage severity. It is concluded that GA is an efficient tool to quantify single and multiple damages with high precision in 3D frame structures. © JVE INTERNATIONAL LTD. | Source Title: | Journal of Vibroengineering | URI: | https://scholarbank.nus.edu.sg/handle/10635/179050 | ISSN: | 13928716 | DOI: | 10.21595/jve.2017.18571 | Rights: | Attribution 4.0 International |
Appears in Collections: | Elements Staff Publications |
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