The Component Detection of Electric Energy Measurement Device Based on SSD Model

Abstract

With the rapid development of the power grid, the site construction and operation environment is more extensive and complex, the installation work of the electric energy metering device is heavy, and it is easy to not regulate, and it is very difficult for managers to conduct real-time and effective supervision and testing. Therefore, combined with the successful application of deep learning in target detection, we propose a measuring device component detection method based on deep learning SSD model to detect the installation quality, saving time and manpower. The experimental results show that our method can ensure the detection accuracy and speed, which is of great significance for the implementation and monitoring of power system installation specification.