A Comprehensive Review of Structural Health Monitoring for Steel Bridges: Technologies, Data Analytics, and Future Directions

Structural health monitoring (SHM) of steel bridges is a vital discipline dedicated to ensuring the longevity, safety, and reliability of critical transportation infrastructure. This comprehensive review paper synthesizes the current state of the art in SHM technologies and methodologies as applied to steel bridges, drawing from a wide body of literature. The review traces the historical evolution of SHM from its foundational principles of vibration-based monitoring and operational evaluation to the contemporary era of data-driven and intelligent systems. It provides a detailed examination of core technological themes, including the deployment of various sensing systems such as wireless sensor networks, fiber optics, and piezoelectric transducers; the revolutionary impact of data interrogation techniques like machine learning, artificial intelligence, and statistical pattern recognition; and the integration of novel inspection methodologies such as digital image correlation, computer vision, and robotic systems. The paper further explores specialized applications for damage detection, including fatigue life assessment and the monitoring of specific components like expansion joints. Throughout the analysis, the review identifies persistent challenges, including the cost of deployment, data management complexities, and the need for real-world validation. The synthesis concludes that the future of SHM for steel bridges lies in the synergistic integration of diverse sensing technologies with advanced computational analytics, moving the field from periodic, reactive inspections towards continuous, proactive, and predictive infrastructure management. This evolution promises to enhance the resilience, safety, and economic sustainability of steel bridge networks worldwide.