Intelligent Multi-drive Inspection and Positioning Method for Water Environment of Cable Pipe Corridor Based on Artificial Intelligence

Abstract

Abstract The running environment of underground power cables is hidden, and it is difficult to identify the cables in the parallel cable trench, which is not conducive to the rapid troubleshooting and accurate positioning of faults. However, the traditional manual inspection method has some defects, such as difficulty in finding, recording, low efficiency and inconvenient re-use of inspection information. Based on the above background, the purpose of this study is to explore the intelligent multi drive inspection and positioning method for water environment of cable pipe gallery based on artificial intelligence. Based on the analysis of the existing cable tunnel water environment inspection technology, this paper introduces the basic theory of machine vision and artificial intelligence to analyze the requirements of the water environment inspection and positioning method of the cable pipe gallery. Firstly, an intelligent multi drive inspection and positioning overall structure is designed. Secondly, aiming at the problem of unattended cable tunnel water environment inspection and navigation positioning, A monocular vision navigation scheme based on guide line is developed, which includes two parts: walking along the line and detecting the fixed point. Through the intelligent multi drive inspection and positioning method, the work efficiency of the water environment inspection of the cable tunnel is greatly improved. The reference error of the identification method is less than 1.8%. At the same time, the inspection data can be completely saved, which is conducive to the early warning of cable equipment defects and the analysis of the development trend, and the reliable and stable operation level of the field equipment and power grid of the cable tunnel is improved.