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学者姓名：陈涛
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Abstract ：
Structural modal parameters are crucial for monitoring the condition of bridges. Operational modal analysis (OMA) has garnered great attention in vibration-based structural health monitoring of bridges because it only requires vibration measurements from multiple sensors. Slight asynchronization often occurs in these measurements during the monitoring process. Applying classical OMA methods, such as the natural excitation technique (NExT) combined with the eigensystem realization algorithm (ERA), to asynchronous vibration measurements can lead to significant errors in modal parameters. To address this issue, this study proposes a modal assurance criterion (MAC)-based time synchronization technique to generate reliable synchronous vibration measurements for modal identification. The MAC-based method takes advantage of the proportionality of modal components and is only capable of detecting nonsynchronized issues between single-degree-of-freedom (SDOF) signals. A variational mode extraction (VME) technique is employed to iteratively decompose bridge vibration measurements into SDOF components. The VME technique eliminates the need for artificially predefining the number of modes, which was required in many signal decomposition techniques. After time synchronization, the proposed method employs the NExT-ERA-based automatic OMA method for modal identification. The effectiveness of the proposed method is demonstrated using vibration measurements from both the finite element model of a highway bridge and field monitoring data from an actual bridge. The results show that the proposed method successfully synchronizes vibration signals and identifies mode shapes, even in the presence of modal node phenomena.
Keyword ：
asynchronous detection asynchronous detection bridge bridge health monitoring health monitoring modal analysis modal analysis signal decomposition signal decomposition
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| GB/T 7714 | Chen, Tao , Yang, Xiao-Mei , Yang, Shu-Han et al. Variational Mode Extraction-Guided Automated Asynchronous Operational Modal Analysis for Bridges [J]. | STRUCTURAL CONTROL & HEALTH MONITORING , 2025 , 2025 (1) . |
| MLA | Chen, Tao et al. "Variational Mode Extraction-Guided Automated Asynchronous Operational Modal Analysis for Bridges" . | STRUCTURAL CONTROL & HEALTH MONITORING 2025 . 1 (2025) . |
| APA | Chen, Tao , Yang, Xiao-Mei , Yang, Shu-Han , Yao, Xiao-Jun , Zheng, Yong-Xiang . Variational Mode Extraction-Guided Automated Asynchronous Operational Modal Analysis for Bridges . | STRUCTURAL CONTROL & HEALTH MONITORING , 2025 , 2025 (1) . |
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Abstract ：
The prediction model for mechanical properties of RAC was established through the Bayesian optimization-based Gaussian process regression (BO-GPR) method, where the input variables in BO-GPR model depend on the mix ratio of concrete. Then the compressive strength prediction model, the material cost, and environmental factors were simultaneously considered as objectives, while a multi-objective gray wolf optimization algorithm was developed for finding the optimal mix ratio. A total of 730 RAC datasets were used for training and testing the predication model, while the optimal design method for mix ratio was verified through RAC experiments. The experimental results show that the predicted, testing, and expected compressive strengths are nearly consistent, illustrating the effectiveness of the proposed method.
Keyword ：
compressive strength compressive strength mix ratio mix ratio multi-objective optimization multi-objective optimization prediction model prediction model recycled coarse aggregate recycled coarse aggregate
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| GB/T 7714 | Chen, Tao , Wu, Di , Yao, Xiaojun . Prediction Model-based Multi-objective Optimization for Mix-ratio Design of Recycled Aggregate Concrete [J]. | JOURNAL OF WUHAN UNIVERSITY OF TECHNOLOGY-MATERIALS SCIENCE EDITION , 2024 , 39 (6) : 1507-1517 . |
| MLA | Chen, Tao et al. "Prediction Model-based Multi-objective Optimization for Mix-ratio Design of Recycled Aggregate Concrete" . | JOURNAL OF WUHAN UNIVERSITY OF TECHNOLOGY-MATERIALS SCIENCE EDITION 39 . 6 (2024) : 1507-1517 . |
| APA | Chen, Tao , Wu, Di , Yao, Xiaojun . Prediction Model-based Multi-objective Optimization for Mix-ratio Design of Recycled Aggregate Concrete . | JOURNAL OF WUHAN UNIVERSITY OF TECHNOLOGY-MATERIALS SCIENCE EDITION , 2024 , 39 (6) , 1507-1517 . |
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Abstract ：
Vortex-induced vibration is a type of wind-induced vibration occurring frequently in large-span sea-crossing bridges under relatively low wind speeds, posing a threat to the structural fatigue performance and driving comfort. Identifying the instantaneous occurrence moments of vortex-induced vibration is a prerequisite for establishing a data-driven prediction model for vortex-induced vibration, and it is of great significance for the monitoring and early warning of vortex-induced vibration performance in bridges. To automatically detect the occurrence moments of vortex-induced vibration and establish a correlation model between vortex-induced vibration amplitude and environmental factors, this study proposes a fuzzy C-means clustering-based classification method. In order to detect the occurrence moments of vortex-induced vibration more finely, only short-term or even instantaneous structural vibration indicators were selected and transformed for distribution as clustering features. The entire detection process could be carried out unsupervised, reducing the manual cost of obtaining vortex-induced vibration information from massive monitoring data. Finally, actual vortex-induced vibration test data from a certain overseas bridge was utilized to verify the feasibility of this method. Based on the classification results, the correlation between vortex-induced vibration amplitude and environmental variables was determined, providing valuable guidance for predicting vortex-induced vibration amplitudes.
Keyword ：
clustering clustering correlation correlation performance analysis performance analysis sea-crossing bridge sea-crossing bridge vortex-induced vibration vortex-induced vibration
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| GB/T 7714 | Chen, Tao , Wu, Yi-Lun , Yang, Xiao-Mei et al. Vortex-Induced Vibration Performance Analysis of Long-Span Sea-Crossing Bridges Using Unsupervised Clustering [J]. | JOURNAL OF MARINE SCIENCE AND ENGINEERING , 2024 , 12 (10) . |
| MLA | Chen, Tao et al. "Vortex-Induced Vibration Performance Analysis of Long-Span Sea-Crossing Bridges Using Unsupervised Clustering" . | JOURNAL OF MARINE SCIENCE AND ENGINEERING 12 . 10 (2024) . |
| APA | Chen, Tao , Wu, Yi-Lun , Yang, Xiao-Mei , Yang, Shu-Han . Vortex-Induced Vibration Performance Analysis of Long-Span Sea-Crossing Bridges Using Unsupervised Clustering . | JOURNAL OF MARINE SCIENCE AND ENGINEERING , 2024 , 12 (10) . |
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