Intelligent Inspection Robot Scene Recognition under Convolutional Neural Network

Abstract

With the rapid development of technology, intelligent substation detection robots are becoming a new favorite in the industry. It not only improves the detection efficiency of the substation, but also improves the detection accuracy. At the same time, the integration of multiple advanced technologies endows these robots with unique functions and characteristics. Substation is an important component of the power system, and its working state directly affects the stability of power supply. Traditional, usually manual inspection methods are not only inefficient but also prone to errors. The emergence of intelligent inspection robots has completely changed the inspection method of substations, allowing for large-scale inspections in a short period of time, with much higher accuracy than manual operations. The total number of surveyed data within 24 hours for the intelligent inspection robot scene recognition using convolutional neural networks is 198, with only 2 unmeasured data. However, it can be seen that the intelligent inspection robot scene recognition using convolutional neural networks can quickly and accurately recognize.