Enhancing Concrete Bridge Inspections with Preventive Maintenance and Data Fusion Techniques for User Safety

Abstract

As a critical link between the West Coast and East Coast of Peninsular Malaysia, the Banding Bridge supports thousands of vehicles daily. Persistent structural issues such as cracks and corrosion pose significant risks, endangering lives and disrupting traffic. Urgent advanced inspection and maintenance are necessary to ensure user safety. This study proposes a concrete bridge inspection system utilizing a fusion of GNSS and vibration data to enable the Malaysian road agencies to monitor bridge health. Through visual inspection analysis, the system could identify critical damage such as slab holes and corrosion. Comparing data from the system with the visual inspection data successfully demonstrated the system’s effectiveness. The results show a vibration signal of up to 1.0000 m/s recorded in a dataset taken at point KB21 at span 13. A visual inspection rating of 3 indicates that the bridge needs to be improved. These results emphasize adopting advanced technology to enhance bridge health to prevent accidents, causing tragic fatalities. This study contributes to the field by illustrating data fusion as a reliable, evidence-based method for enhancing bridge structural health. The results are expected to encourage Malaysian road agencies to improve visual inspections by adding new tools to provide actionable insights. The comparative data could improve the authority's decision-making and preventive maintenance efficiency. Future research could explore real-time monitoring and predictive analytics to advance bridge maintenance practices further while addressing weaknesses proactively.