Electrical Fault Detection Equipment Based on Infrared Image Fusion

Abstract

Maintaining the safe and stable operation of power equipment is the first task of power system operation and maintenance. The equipment in normal operation may have various faults, so it needs to be located, detected and repaired. In order to improve the on-line detection efficiency of electrical equipment, diagnose the operation state of equipment in time and locate faults, this project proposes a multi focus infrared and visible image fusion algorithm based on NSST and adaptive PCNN. Taking the power equipment as the research object, the infrared image of the power equipment is compared with the visible image, and the feature points are selected, so as to realize the image registration. After image registration, the registered visible and infrared images are fused and reconstructed, and the effective features of the two kinds of images are integrated into one image. The target image constructed by fusion not only has thermal energy information, but also has object texture, highlights the target, and can detect the fault location without power failure. It has certain practical significance for quickly removing the fault point of power equipment.