Intelligent Pavement Damage Monitoring Research in China

• Published in: IEEE access Vol. 7; pp. 45891 - 45897
• Main Authors: Zhang, Bing, Liu, Xianlin
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial intelligence; Control equipment; Damage; Feature extraction; feature matrix; intelligent detection; Interdisciplinary subjects; Maintenance engineering; Monitoring; Pavements; point cloud data; real-time data processing; Road construction; road damage monitoring; Roads; Roads & highways; Software; unmanned control equipment; China
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2019.2905845

The development of artificial intelligence technology is of vital significance to the progress of human civilization. Through the development of this aspect in recent years, China has achieved unprecedented gains in equipment and software technology, such as road damage monitoring. However, it is difficult to deal with a large amount of data and real-time data. In addition, China is the third largest country in the world in terms of land area, with well-developed roads and more and more road construction, which increases the workload of road damage monitoring. In order to solve these problems, a research scheme of intelligent pavement damage monitoring is proposed. The main idea of the scheme is to obtain point cloud data by scanning the road surface with unmanned control equipment, carry out Harris, star and sift detection on the pictorial point cloud data, and then judge the damaged area by combining with the characteristic matrix of the damaged data. Through the processing of point cloud data obtained by the existing manned control equipment, it is found that it has a good effect on the monitoring of pavement crack damage. From the actual results obtained, it can be judged that the pavement damage of single crack and multi-crack can be determined. Intelligent development is an application that integrates multiple interdisciplinary subjects. This research can provide some development ideas for intelligent road monitoring, and at the same time, it is hoped to contribute to the development and integration of interdisciplinary subjects.