High-Voltage Disconnector State Identification: synthetic and real images of substation disconnectors

<p>This dataset contains the training and test images used in the work detailed in the article: Barpp Gomes, V., Marchesi, B., Gruber, Y.A.&nbsp;<em>et al.</em> Exploring Synthetic Data for Training Deep Learning Models for High-Voltage Disconnector State Identification. <em>J Control Autom Electr Syst</em> (2025). <a href="https://doi.org/10.1007/s40313-025-01204-2">https://doi.org/10.1007/s40313-025-01204-2</a></p> <p>Contais about 940,000 synthetic (CGI-rendered) and 60,000 real (camera-captured) samples of four types of substation disconnectors, on both open and closed states:</p> <ul> <li>230 kV center break (type 1, as indicated in the article);</li> <li>230 kV center break (type 2);</li> <li>230 kV double side break</li> <li>525 kV horizontal semi-pantograph</li> </ul> <p>Each zip file contains images of one type of substation disconnector. Images are sized 320x128 and are organized in folders, as follows:</p> <ul> <li>00_train_synth: Synthetic training images.</li> <li>01_train_real: A small set of real training images, as indicated in the article.</li> <li>02_test_real_normal1: One set of real test images.</li> <li>03_test_real_normal2: Another set of real test images, from a different time period.</li> <li>04_test_real_maneuvers: A special set of real test images in which the switches have been operated (are in different states).</li> </ul>