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

This dataset contains the training and test images used in the work detailed in the article: Barpp Gomes, V., Marchesi, B., Gruber, Y.A. et al. Exploring Synthetic Data for Training Deep Learning Models for High-Voltage Disconnector State Identification. J Control Autom Electr Syst (2025). https://doi.org/10.1007/s40313-025-01204-2 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: 230 kV center break (type 1, as indicated in the article); 230 kV center break (type 2); 230 kV double side break 525 kV horizontal semi-pantograph Each zip file contains images of one type of substation disconnector. Images are sized 320x128 and are organized in folders, as follows: 00_train_synth: Synthetic training images. 01_train_real: A small set of real training images, as indicated in the article. 02_test_real_normal1: One set of real test images. 03_test_real_normal2: Another set of real test images, from a different time period. 04_test_real_maneuvers: A special set of real test images in which the switches have been operated (are in different states).