A Novel Monitoring Method of Wind-Induced Vibration and Stability of Long-Span Bridges Based on Permanent Scatterer Interferometric Synthetic Aperture Radar Technology
Long-span structures are highly vulnerable to wind-induced vibrations, which can pose a significant threat to their structural stability and safety. This paper introduces a novel monitoring method that combines Permanent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technology with Auto-Regressive Moving Average (ARMA) models, providing an innovative approach to monitoring wind-induced vibrations in large-span bridges. While previous studies have focused on individual techniques, this integrated approach is largely unexplored and offers a new perspective for structural health monitoring. By collating a series of SAR images and examining phase alterations on the bridge surface, a three-tiered detection methodology is employed to identify stable points accurately. The surface deformation data are then analyzed alongside wind speed and weather data to construct a comprehensive model elucidating the relationship between the bridge and vibrations. The ARMA model is used for real-time monitoring and assessment. Experimental results demonstrate that this method offers precise, real-time monitoring of wind-resistant stability. By leveraging the spatial accuracy and long-term monitoring capability of PS-InSAR, along with the time-series forecasting strength of ARMA models, the method enables data-driven analysis of bridge vibrations. It also provides comprehensive coverage under various conditions, enhancing the safety of long-span bridges through advanced predictive analytics.
Authors
- Jie Ma (ORCID: https://orcid.org/0000-0001-9272-656X)
- Xiaojun Xue (ORCID: https://orcid.org/0009-0005-2915-5254)
- Hanqing Zhu
- Haoyang Zheng (ORCID: https://orcid.org/0000-0002-5439-053X)
- Guoliang Zhi (ORCID: https://orcid.org/0009-0000-1508-6191)
Institutions
- Shanxi University (CN)
- Southeast University (CN)
Publication Details
- Journal
- Sensors
- Published
- 2025-05-24
- DOI
- https://doi.org/10.3390/s25113316
- Citations
- 4
- Primary Topic
- Structural Health Monitoring Techniques
- Type
- article
- Field-Weighted Citation Impact
- 3.81
Funders
- National Natural Science Foundation of China
- Government of Jiangsu Province