Research on thermal state diagnosis of substation equipment based on infrared image

Abstract

In thermal state diagnosis of substation equipment, problems such as low precision and slow speed usually exist. Aiming at the problems, an improved diagnostic scheme is proposed in this article. First, an infrared weak target extraction method based on local variance mapping and genetic algorithm threshold calculation is used to segment the region with abnormal thermal state in the equipment. Then the relationship between image gray parameters and temperature parameters of equipment region is established, and the improved relative temperature difference method is implemented to complete the classification and diagnosis of the thermal state of the equipment, and the abnormal area of the thermal state is captured and positioned at the same time. The experiment results show that the extraction accuracy and efficiency of the abnormal thermal area are improved based on the proposed scheme, which improves the fault tolerance of the thermal state diagnosis of the equipment and further ensures the operational stability of the substation and the entire power system.