Intelligent detection method of abnormal state of power equipment based on infrared and visible image information

Abstract

Infrared thermal imaging cameras are usually used to detect the thermal state of the equipment. According to the heat radiation situation and temperature value emitted by the equipment, the thermal failure of the equipment is inferred, and whether the equipment is working is verified properly. This paper analyzes the thermal imaging principle of infrared technology and the characteristics of infrared images, and quantifies the surface temperature indicators of insulators. Through infrared and visible light image information, the pollution degree of insulators can be detected, and the abnormal condition of the equipment can be checked. The evaporation of moisture on the surface of the insulator mainly depends on the assumption that the surface heats up. A method for analyzing heat on the surface of wet-contaminated insulators is proposed, and the judgment conditions for arc generation in the drying zone and the drying zone and the heating models of the insulators in different operating conditions are established. The computer simulation results reveal the distribution of heat on the surface of insulators under different operating conditions, and the influence of the occurrence of drying zone and drying zone arc on leakage current and heating. The infrared thermal imaging test results of wet-contaminated insulators show that the model is reasonable and provides theoretical support for infrared thermal imaging detection of insulator contamination levels.