%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2022/09.22.22.53
%2 sid.inpe.br/sibgrapi/2022/09.22.22.53.54
%@doi 10.1109/SIBGRAPI55357.2022.9991806
%T PTL-AI Furnas Dataset: A Public Dataset for Fault Detection in Power Transmission Lines Using Aerial Images
%D 2022
%A Oliveira, Frederico Santos de,
%A Carvalho, Marcelo de,
%A Campos, Pedro Henrique Tancredo,
%A Soares, Anderson da Silva,
%A Cândido Júnior, Arnaldo,
%A Quirino, Ana Cláudia Rodrigues da Silva,
%@affiliation Universidade Federal de Mato Grosso (UFMT)
%@affiliation Eletrobras-Furnas
%@affiliation Eletrobras-Furnas
%@affiliation Universidade Federal de Goiás (UFG)
%@affiliation Universidade Estadual Paulista (UNESP)
%@affiliation Eletrobras-Furnas
%B Conference on Graphics, Patterns and Images, 35 (SIBGRAPI)
%C Natal, RN
%8 24-27 Oct. 2022
%S Proceedings
%K object detection, power transmission lines, fault detection.
%X We present a new images dataset called PTL-AI Furnas Dataset as a new benchmark for fault detection in power transmission lines. This dataset has 6,295 images, with resolution 1280×720, extracted from the maintenance process of the energy transmission lines at Furnas company. It contains annotations of 17,808 components classified as baliser, bird nest, insulator, spacer and stockbridge. Furnas is a company that generates or transmits electricity to 51% of households in Brazil and more than 40% of the nations electricity passes through their grid enabling generating the dataset in different backgrounds and climatic conditions. We performed experiments using data augmentation techniques to train Faster R-CNN, Single-Shot Detects (SSD) and YoloV5 models. The benchmark result was obtained using the metrics of Mean Average Precision (mAP) and the Mean Average Recall (mAR) with values mAP=91.9% and mAR=89.7%. The PTL-AI Furnas Dataset is publicly available at https://github.com/freds0/PTL-AI Furnas Dataset.
%@language en
%3 oliveira-33_inpe.pdf