Research on Automatic Identification and Monitoring System of New Power System Construction Based on Computer Vision

With the continuous advancement of the construction of new power system, the operation and maintenance mode of traditional power system has been difficult to meet the demand of intelligent and automation development. The construction of new power system needs to take into account the economy and stability, and new technology and new equipment should be actively utilized in the construction process to promote the upgrading and transformation of the new energy power system, a new type of power system automatic identification and monitoring system based on computer vision is proposed. The system combines deep learning technology with image processing and target recognition algorithms to realize automated monitoring and anomaly detection of power equipment status. In the face of the environmental challenges and energy security pressures posed by fossil energy sources, the widespread utilization of clean energy sources such as wind and solar energy is particularly urgent. The construction of new energy power systems needs to overcome many challenges such as the complexity of technology development, the balance of cost-effectiveness, and the guarantee of power system stability and reliability, etc. A system architecture containing data acquisition, algorithm processing and monitoring feedback is designed and the core algorithms and technical implementations are described in detail. In the experimental validation, this paper evaluates the accuracy, real-time and robustness of the system through multiple sets of experiments, and the results show that the system has high recognition accuracy and operational efficiency, which can effectively improve the intelligent management level of the power system. Finally, this paper summarizes the research results and looks forward to the potential application of this technology in future complex power scenarios.