Automatic Location Algorithm for 3D Space Inspection Points in Substation Based on Deep Learning

The traditional way of substation inspection mainly depends on manual inspection, which is not only inefficient, but also easily influenced by environment, weather and other factors, and it is difficult to ensure the accuracy and reliability of inspection. Therefore, it is of great significance to study a method that can automatically, efficiently and accurately complete the location of 3D patrol points in substation. In this article, the convolutional neural network (CNN) in deep learning (DL) is used to automatically extract and classify the features of substation images, and then the patrol points are located in combination with the 3D spatial coordinate system. The results show that the algorithm in this article is excellent in automatic location of 3D patrol points in substation, and it has higher classification accuracy and stability than the traditional algorithm. In this article, the algorithm can adapt to the diversity of features in different environmental conditions, accurately extract the feature information in substation images, and at the same time use 3D spatial coordinate system to locate patrol points, which improves the positioning accuracy. This algorithm has obvious advantages and important application value in automatic location of 3D patrol points in substation, which provides strong support for the development of smart grid.