Journal of Traffic and Transportation Engineering (English ed. Online) (Apr 2024)
Research progress on intelligent operation and maintenance of bridges
Abstract
In the context of the increasing scale of bridges and the increasing service life of bridges, it is very important to carry out efficient, accurate and intelligent bridge operation and maintenance. In recent years, advanced equipment, technology and intelligent algorithms have developed rapidly. It is necessary to apply advanced equipment and algorithms to bridge operation and maintenance business to facilitate the digitalization and intelligence of bridge operation and maintenance. To grasp the research progress on the bridge intelligent operation and maintenance, this paper summarizes the research progress in recent years from the aspects of intelligent detection equipment and technology, intelligent monitoring equipment and technology, intelligent data analysis, intelligent evaluation and early warning, and intelligent repair and maintenance. According to the review, more and more smart devices have been used to replace human beings to detect dangerous and hidden bridge components. At the same time, image processing, radar and other technologies have been used to analyze component damage more objectively and quantitatively. To solve the shortcomings of traditional sensors such as short life and low robustness, more non-contact measurement methods have been proposed. Scholars have proposed various intelligent algorithms to process the massive amount of bridge health monitoring data to improve the quality of the data. To achieve the rapid perception of bridge status and timely early warning of structural abnormalities, different from traditional theoretical calculations, scholars have tried to use data-driven methods to intelligently evaluate and early warning of bridge structural status. In terms of intelligent repair and maintenance, more intelligent algorithms have been used to optimize structural maintenance strategies and determine the best maintenance time by integrating multi-source heterogeneous data. All these provide strong support for the automation, digitization and intelligence of bridge operation and maintenance.