Research on Power Line Communication Based on Deep Learning for Electromechanical Equipment Electricity Acquisition Terminals

Abstract

The purpose is to use power line communication technology to re-optimize the power acquisition terminals of electromechanical equipment and improve the efficiency of information acquisition and management of the system grid. This paper analyzes the power and signal composite modulation mode of power line data communication in distributed power grids. Combined with the topology of the communication network in the power transmission process, the management mode of integration of power lines and wireless communication equipment is redesigned. Firstly, the characteristics of power line communication and wireless channel are analyzed. Aiming at the problem that most communication network operators use the fixed relay for communication, the main network communication mode is selected for optimization. Then, the information fusion method is adopted to integrate the network structure of the enterprise, network, and physical layer. The management of wireless communication equipment is carried out by reasonably allocating power resources. Additionally, the structure of the power acquisition terminal model is designed based on strict standards and practice. Finally, the communication fusion method is used for experimental simulation. The results show that when the input current is 1A, the experimental, theoretical value of the system is 3A, and the actual instrument output is close to 5A. When the input current is 6A, the instrument output of the system is 7.5A. Therefore, loading a reasonable load impedance value in the system can optimize the current output value of the model. The paper has important reference value for optimizing electromechanical equipment and power acquisition terminal.