Application of visible light-infrared image fusion technology in power system fault detection

Abstract

Infrared thermal imaging is widely used in industrial inspection due to its advantages such as passive identification, non-contact detection, long detection distance and strong environmental adaptability. In power systems, infrared thermal imaging can be used to carry out live detection of power equipment to prevent or examine potential risk and threats. This paper provides a fault detection method for power equipment through the visible light-infrared image fusion technology. The information of infrared image is collected through infrared thermal imager, and the infrared image is preprocessed. The scale invariant feature transform (SIFT) feature point detection algorithm is used to extract the difference between visible light image and infrared image. The feature points are screened and registered by random sample consensus (RANSAC) algorithm to realize the fusion of the visible light image and the infrared image of the power equipment, so as to detect the working status of the power equipment and accurately locate the fault source when a fault occurs.