A Multi-Objective Sensor Placement Method Considering Modal Identification Uncertainty and Damage Detection Sensitivity
Structural Health Monitoring relies on accurate modal identification and effective damage detection to assess structural performance and safety. However, traditional sensor placement methods struggle to balance modal identification uncertainty, which arises from limited sensor coverage and measureme...
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MDPI AG
2025-03-01
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| author | Xue-Yang Pei Yuan Hou Hai-Bin Huang Jun-Xing Zheng |
| author_facet | Xue-Yang Pei Yuan Hou Hai-Bin Huang Jun-Xing Zheng |
| author_sort | Xue-Yang Pei |
| collection | DOAJ |
| description | Structural Health Monitoring relies on accurate modal identification and effective damage detection to assess structural performance and safety. However, traditional sensor placement methods struggle to balance modal identification uncertainty, which arises from limited sensor coverage and measurement noise and damage detection sensitivity, which requires sensors to be optimally positioned to capture structural stiffness variations. To address this challenge, this study proposes a multi-objective sensor placement optimization method based on the Non-Dominated Sorting Genetic Algorithm. The method introduces two key objective functions: minimizing modal identification uncertainty by leveraging Bayesian modal identification theory and information entropy and maximizing damage detection sensitivity by incorporating an entropy-based measure to quantify the uncertainty in stiffness variation estimation. By formulating the problem as Pareto-based multi-objective optimization, the method efficiently explores a trade-off between the two competing objectives and provides a diverse set of optimal sensor placement solutions. The proposed approach is validated through numerical experiments on a simply supported beam and a benchmark bridge structure, demonstrating that different optimization objectives lead to distinct sensor placement patterns. The results show that solutions prioritizing modal identification distribute sensors across the structure to improve global response estimation, while solutions favoring damage detection concentrate sensors in critical areas to enhance sensitivity. The proposed method significantly improves sensor placement strategies by offering a systematic and flexible framework for SHM applications, enabling engineers to tailor monitoring strategies based on specific structural assessment needs. |
| format | Article |
| id | doaj-art-2e97ff9fe0984be78d1932f2e6b2b557 |
| institution | DOAJ |
| issn | 2075-5309 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
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| series | Buildings |
| spelling | doaj-art-2e97ff9fe0984be78d1932f2e6b2b5572025-08-20T02:59:14ZengMDPI AGBuildings2075-53092025-03-0115582110.3390/buildings15050821A Multi-Objective Sensor Placement Method Considering Modal Identification Uncertainty and Damage Detection SensitivityXue-Yang Pei0Yuan Hou1Hai-Bin Huang2Jun-Xing Zheng3School of Civil Engineering, Yancheng Institute of Technology, Yancheng 224051, ChinaSchool of Civil Engineering, Yancheng Institute of Technology, Yancheng 224051, ChinaSchool of Civil and Transportation Engineering, Hebei University of Technology, Tianjin 300401, ChinaSchool of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, ChinaStructural Health Monitoring relies on accurate modal identification and effective damage detection to assess structural performance and safety. However, traditional sensor placement methods struggle to balance modal identification uncertainty, which arises from limited sensor coverage and measurement noise and damage detection sensitivity, which requires sensors to be optimally positioned to capture structural stiffness variations. To address this challenge, this study proposes a multi-objective sensor placement optimization method based on the Non-Dominated Sorting Genetic Algorithm. The method introduces two key objective functions: minimizing modal identification uncertainty by leveraging Bayesian modal identification theory and information entropy and maximizing damage detection sensitivity by incorporating an entropy-based measure to quantify the uncertainty in stiffness variation estimation. By formulating the problem as Pareto-based multi-objective optimization, the method efficiently explores a trade-off between the two competing objectives and provides a diverse set of optimal sensor placement solutions. The proposed approach is validated through numerical experiments on a simply supported beam and a benchmark bridge structure, demonstrating that different optimization objectives lead to distinct sensor placement patterns. The results show that solutions prioritizing modal identification distribute sensors across the structure to improve global response estimation, while solutions favoring damage detection concentrate sensors in critical areas to enhance sensitivity. The proposed method significantly improves sensor placement strategies by offering a systematic and flexible framework for SHM applications, enabling engineers to tailor monitoring strategies based on specific structural assessment needs.https://www.mdpi.com/2075-5309/15/5/821multi-objective sensor placementmodal identification uncertaintydamage detection sensitivityPareto optimizationnon-dominated sorting genetic algorithm |
| spellingShingle | Xue-Yang Pei Yuan Hou Hai-Bin Huang Jun-Xing Zheng A Multi-Objective Sensor Placement Method Considering Modal Identification Uncertainty and Damage Detection Sensitivity Buildings multi-objective sensor placement modal identification uncertainty damage detection sensitivity Pareto optimization non-dominated sorting genetic algorithm |
| title | A Multi-Objective Sensor Placement Method Considering Modal Identification Uncertainty and Damage Detection Sensitivity |
| title_full | A Multi-Objective Sensor Placement Method Considering Modal Identification Uncertainty and Damage Detection Sensitivity |
| title_fullStr | A Multi-Objective Sensor Placement Method Considering Modal Identification Uncertainty and Damage Detection Sensitivity |
| title_full_unstemmed | A Multi-Objective Sensor Placement Method Considering Modal Identification Uncertainty and Damage Detection Sensitivity |
| title_short | A Multi-Objective Sensor Placement Method Considering Modal Identification Uncertainty and Damage Detection Sensitivity |
| title_sort | multi objective sensor placement method considering modal identification uncertainty and damage detection sensitivity |
| topic | multi-objective sensor placement modal identification uncertainty damage detection sensitivity Pareto optimization non-dominated sorting genetic algorithm |
| url | https://www.mdpi.com/2075-5309/15/5/821 |
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