Analysis of artificial intelligence techniques applied to thermographic inspection for automatic detection of electrical problems

Abstract

Electrical energy is among the most important resources used nowadays, in the modern world. Despite this, there is a considerable waste of much of what is spent on power generation, since some of the energy generated does not reach the final consumer. One of the scopes addressed by smart cities is the optimal use of the basic resources available to the population, such as electricity. Thermographic inspection is a technique that allows non-invasive sensing. Through it, it is possible to analyze components and electrical equipment by capturing the temperature of its surface. With the aim of finding electrical faults and reducing losses, this work studies the use of thermography, computational algorithms and artificial intelligence techniques to automatically detect electrical problems.