Research on On-Line Monitoring System of Flexible DC Converter Valve Submodule Based on Machine Vision

Abstract

In this paper, a flexible DC converter valve sub-module online monitoring system based on machine vision is designed and implemented. The system uses machine vision technology to acquire and analyze the surface state and operating parameters of the flexible DC converter valve submodule in real time. By introducing Lesit life model and linear damage accumulation algorithm, the system can accurately evaluate the fatigue damage of submodules and predict their remaining service life. This paper discusses the algorithm design of the monitoring system in detail, including image processing, feature extraction, damage recognition and life prediction module, and verifies the effectiveness of the algorithm through system simulation. The simulation results show that the designed system can accurately identify the minor damage of the submodule and predict its development trend under various working conditions, and the prediction error is controlled within a reasonable range. Through accurate data analysis, the advantages of the monitoring system in real-time, accuracy and reliability are verified. The application of this system not only improves the safety and stability of the flexible HVDC system, but also provides a new idea and method for the on-line monitoring technology of power equipment.