Damage assessment of suspension footbridge using vibration measurement data combined with a hybrid bee-genetic algorithm
Abstract Optimization algorithms (OAs) are a vital tool to deal with complex problems, and the improvement of OA is inseparable from practical strategies and mechanisms. Among the OAs, Bee Algorithm (BA) is an intelligent algorithm with a simple mechanism and easy implementation, in which effectiven...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-24445-6 |
| _version_ | 1811215897397821440 |
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| author | Lan Ngoc-Nguyen Hoa Ngoc-Tran Samir Khatir Thang Le-Xuan Quyet Huu-Nguyen G. De Roeck Thanh Bui-Tien Magd Abdel Wahab |
| author_facet | Lan Ngoc-Nguyen Hoa Ngoc-Tran Samir Khatir Thang Le-Xuan Quyet Huu-Nguyen G. De Roeck Thanh Bui-Tien Magd Abdel Wahab |
| author_sort | Lan Ngoc-Nguyen |
| collection | DOAJ |
| description | Abstract Optimization algorithms (OAs) are a vital tool to deal with complex problems, and the improvement of OA is inseparable from practical strategies and mechanisms. Among the OAs, Bee Algorithm (BA) is an intelligent algorithm with a simple mechanism and easy implementation, in which effectiveness has been proven when handling optimization problems. Nevertheless, BA still has some fundamental drawbacks, which can hinder its effectiveness and accuracy. Therefore, this paper proposes a novel approach to tackle the shortcomings of BA by combining it with Genetic Algorithm (GA). The main intention is to combine the strengths of both optimization techniques, which are the exploitative search ability of BA and the robustness with the crossover and mutation capacity of GA. An investigation of a real-life suspension footbridge is considered to validate the effectiveness of the proposed method. A baseline Finite Element model of the bridge is constructed based on vibration measurement data and model updating, which is used to generate different hypothetical damage scenarios. The proposed HBGA is tested against BA, GA, and PSO to showcase its effectiveness in detecting damage for each scenario. The results show that the proposed algorithm is effective in dealing with the damage assessment problems of SHM. |
| first_indexed | 2024-04-12T06:30:03Z |
| format | Article |
| id | doaj.art-2f6b4f52ad234428bf3e69fd6bb8b989 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-12T06:30:03Z |
| publishDate | 2022-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-2f6b4f52ad234428bf3e69fd6bb8b9892022-12-22T03:44:02ZengNature PortfolioScientific Reports2045-23222022-11-0112111410.1038/s41598-022-24445-6Damage assessment of suspension footbridge using vibration measurement data combined with a hybrid bee-genetic algorithmLan Ngoc-Nguyen0Hoa Ngoc-Tran1Samir Khatir2Thang Le-Xuan3Quyet Huu-Nguyen4G. De Roeck5Thanh Bui-Tien6Magd Abdel Wahab7Laboratory Soete, Department of Electrical Energy, Metals, Mechanical Constructions, and Systems, Faculty of Engineering and Architecture, Ghent UniversityDepartment of Bridge and Tunnel Engineering, Faculty of Civil Engineering, University of Transport and CommunicationsFaculty of Civil Engineering, Ho Chi Minh City Open UniversityDepartment of Bridge and Tunnel Engineering, Faculty of Civil Engineering, University of Transport and CommunicationsDepartment of Bridge and Tunnel Engineering, Faculty of Civil Engineering, University of Transport and CommunicationsDepartment of Civil Engineering, KU LeuvenDepartment of Bridge and Tunnel Engineering, Faculty of Civil Engineering, University of Transport and CommunicationsFaculty of Mechanical-Electrical and Computer Engineering, School of Engineering and Technology, Van Lang UniversityAbstract Optimization algorithms (OAs) are a vital tool to deal with complex problems, and the improvement of OA is inseparable from practical strategies and mechanisms. Among the OAs, Bee Algorithm (BA) is an intelligent algorithm with a simple mechanism and easy implementation, in which effectiveness has been proven when handling optimization problems. Nevertheless, BA still has some fundamental drawbacks, which can hinder its effectiveness and accuracy. Therefore, this paper proposes a novel approach to tackle the shortcomings of BA by combining it with Genetic Algorithm (GA). The main intention is to combine the strengths of both optimization techniques, which are the exploitative search ability of BA and the robustness with the crossover and mutation capacity of GA. An investigation of a real-life suspension footbridge is considered to validate the effectiveness of the proposed method. A baseline Finite Element model of the bridge is constructed based on vibration measurement data and model updating, which is used to generate different hypothetical damage scenarios. The proposed HBGA is tested against BA, GA, and PSO to showcase its effectiveness in detecting damage for each scenario. The results show that the proposed algorithm is effective in dealing with the damage assessment problems of SHM.https://doi.org/10.1038/s41598-022-24445-6 |
| spellingShingle | Lan Ngoc-Nguyen Hoa Ngoc-Tran Samir Khatir Thang Le-Xuan Quyet Huu-Nguyen G. De Roeck Thanh Bui-Tien Magd Abdel Wahab Damage assessment of suspension footbridge using vibration measurement data combined with a hybrid bee-genetic algorithm Scientific Reports |
| title | Damage assessment of suspension footbridge using vibration measurement data combined with a hybrid bee-genetic algorithm |
| title_full | Damage assessment of suspension footbridge using vibration measurement data combined with a hybrid bee-genetic algorithm |
| title_fullStr | Damage assessment of suspension footbridge using vibration measurement data combined with a hybrid bee-genetic algorithm |
| title_full_unstemmed | Damage assessment of suspension footbridge using vibration measurement data combined with a hybrid bee-genetic algorithm |
| title_short | Damage assessment of suspension footbridge using vibration measurement data combined with a hybrid bee-genetic algorithm |
| title_sort | damage assessment of suspension footbridge using vibration measurement data combined with a hybrid bee genetic algorithm |
| url | https://doi.org/10.1038/s41598-022-24445-6 |
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