Este artigo foi apresentado no evento 22nd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES), 2018

Agradecimentos: This work is currently under development and is part of the R&D code project PD-0063-3014/2016 ANEEL. The authors are grateful for the support of CPFL- Companhia Paulista de Força e Luz, Unicamp and Kasco R&D Technology

Abstract: An automatic recognizer system based in Artificial Intelligence for thermographic images of the electric power distribution network is proposed in this article. The infrared thermography is usually used to conduct inspections in electrical power distribution lines, assisted by a human...

Abstract: An automatic recognizer system based in Artificial Intelligence for thermographic images of the electric power distribution network is proposed in this article. The infrared thermography is usually used to conduct inspections in electrical power distribution lines, assisted by a human operator, which is usually responsible for operating all the equipment, selecting the hottest spots in the image (corresponding to the places needing maintenance), making reports and calling the technical team, which will do the repairs. The proposed automatic diagnosis system aims to replace the manual inspection operation using image processing algorithms. An old method of segmentation for thermal images known as JSEG is implemented and tested and a Deep Learning Neural Network is responsible to recognize the segmented elements. A comparison between the exclusive Deep Learning based image recognition with the same method preceded by the JSEG segmentation algorithm is done in this article, showing better performance with this previous segmentation of the thermographic images

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