title: AUTOMATIC DEFECT RECOGNITION FOR ELECTRICAL EQUIPMENT WITH ARTIFICIAL NEURAL NETWORKS
abstract: Local heating is a sign of the development of defects in electrical equipment. It is detected by thermal imaging control. The result is thermal images of working electrical equipment – thermograms, which are analyzed using a visual assessment. However, in order to reduce the human factor in processing a large number of thermograms taken from unmanned aerial vehicles, the development of an automated defect recognition system has been proposed. The paper presents the results of recognizing defects
journal: Bulletin of the South Ural State University series Power Engineering