Automation of structural health monitoring of concrete bridges in Malta using computer vision

Abstract

Maintaining the structural integrity of concrete bridges is essential for smooth transportation, and Structural Health Monitoring (SHM) plays a significant role in it. However, traditional SHM processing is time-consuming, subjective and expensive, presenting limitations on the accuracy of damage assessment. Conducting bridge surveys with the traditional SHM approach typically requires the closure of the structure and routing vehicle traffic through alternative roads, potentially leading to traffic congestion. Thus, the role of automated SHM of concrete bridges is essential to mitigate these limitations and nuisances. Our work evaluates the automation of concrete bridge inspection through the application of computer vision techniques on data captured using climbing robots and unmanned aerial vehicles. This approach seeks to facilitate ongoing monitoring, prompt damage identification, and aid preventive maintenance functionalities. The automated SHM approach enables a proactive strategy for bridge maintenance, hence minimising inspection time, bridge closure and maintenance costs. The findings emphasise the solution’s capability to highlight defects in the form of crack identification and quantification. Additionally, the technology facilitates adherence to European infrastructure safety rules and fosters sustainable engineering practices by prolonging the service life of bridges. The computer vision techniques address the specific difficulties in the maintenance of concrete bridges in Malta, thereby enhancing structural integrity and establishing a baseline for implementing other innovative infrastructure solutions. The project DiHICS received funding from Xjenza Malta and the Ministry for Science and Technology of the People's Republic of China (MOST), through the SINO-MALTA Fund 2023 Call (Science and Technology Cooperation).