2026, Vol. 7, Issue 1, Part A

This paper assesses the effectiveness of SHM systems in detecting structural deficiencies in bridges, exploring the technologies used and evaluating the integration of SHM in bridge management practices.

SHM systems provide early warnings of structural failures, allowing for timely maintenance that extends bridge lifespan and reduces costs.

This review highlights various SHM methods, including traditional visual inspections, as well as advanced techniques such as fiber optic sensors, acoustic emissions, and vibration-based monitoring. The paper also discusses the integration of SHM data with predictive maintenance strategies and machine learning algorithms to improve the accuracy of damage detection. Additionally, the future of SHM systems in bridge infrastructure is explored, including the potential for automation and the role of artificial intelligence in analyzing SHM data.

The findings indicate that while SHM systems provide valuable insights into bridge health, further research is needed to overcome the current limitations and to develop more cost-effective, reliable, and scalable systems for use in diverse environmental conditions.