Intelligent Analysis of Substation Images Based on Deep Machine Learning Technology

With the large-scale construction of smart grids in my country, as well as the continuous improvement of power system dispatch automation and substation automation technology, the work of ensuring and coordinating the smooth operation of substations continues to deepen. With the development of science and technology, deep learning and machine learning technologies are becoming more and more intelligent. Nowadays, deep learning has made great achievements in the fields of target detection, image recognition, character recognition, etc., serving the work of substations. The purpose of this article is to study the intelligent analysis of substation images based on deep machine learning technology. Starting from the analysis of images, this paper uses deep machine learning technology as the technical support for intelligent analysis of substation images, combines deep machine learning technology with substation image detection, and focuses on the application of deep machine learning technology in substation image intelligent analysis, improve the intelligent level of substations and ensure the safe and stable operation of substations. Experimental data shows that the correct recognition rate of the BP neural network proposed in this paper for the normal operation of substation equipment and the heating fault of the three types of arresters are 98.06%, 98.25%, 99%, and 98.75%, respectively. It can be concluded that the BP neural network has a high image recognition accuracy rate and it is suitable for the actual work of infrared detection of lightning arresters in substations.