Fault Prediction in Electrical Assets Using Infrared Thermography

Abstract

An infrared thermography technique is discussed in this paper to locate and diagnose the electrical equipment issue. Overheating is among major problems for an electrical device and entire power system. These overheated hotspots must be detected so that the fault can be predicted before it occurs. We used a thermal image of an electrical device taken from a infrared camera to apply our method to detect the hot region and find the maximum temperature and minimum temperature in the image. Image de-noising is done with the help of morphological reconstruction followed by Watershed transformation for image segmentation to identify and separate the region having high pixel intensity as we know that area with high pixel intensity will also have high temperature. Our method achieved near to exact maximum and minimum temperature of electrical device.