Monitoring and detection of steel bridge diseases: A review

Fatigue, corrosion, and bolt loosening are the main causes of structural performance degradation and collapse in steel bridges. Accurate monitoring of steel bridge diseases is a basic premise for ensuring high-quality operation and maintenance of steel bridges. In this regard, a summary and analysis were conducted on the classification of steel bridge diseases, monitoring and detection methods, application statuses, and major difficulties. The main causes, research status, and development trends of steel bridge diseases are discussed. The results showed that, for fatigue crack problems, fatigue crack initiation has a small scale, high difficulty in monitoring and detection, few methods, and low accuracy. As the cracks grow, the difficulty of monitoring and detection decreases, the number of methods increases, and the accuracy improves. Fatigue crack monitoring and detection are affected by the environmental and vehicular loads. Superficial corrosion features are evident in steel bridges, and corrosion identification methods and technologies are rapidly developing. Monitoring and detecting corrosion in concealed areas is difficult and requires further improvements in monitoring and detection technologies and their accuracy. Monitoring and detection methods and supporting equipment for bolt loosening in steel bridges are rapidly developing. The development of intelligent monitoring and detection technologies and supporting equipment is an important research topic that urgently needs to be addressed for the full-lifecycle operation and maintenance of steel bridges and the sustainable development of bridge engineering. Developing new intelligent sensing components based on high-performance materials and sensing element design theory to improve the monitoring and detection perception ability is an important development direction for steel bridge monitoring and detection. Research on intelligent monitoring and detection technologies, standardized indicators, and related topics based on intelligent operations and maintenance provide great support for the development of steel -bridge disease monitoring and detection. (c) 2024 Periodical Offices of Chang 'an University. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY -NCND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).