Modified YOLOv5-based Insulation Detection for Substation High-voltage Electrical Equipment
High-voltage electrical primary equipment is an important guarantee for safe and stable operation of transfor-ming substations.Performances of electrical equipment insulation materials and accuracies of detection equipment are sus-ceptive to vagaries of whether conditions of substations such as high and low temperatures,humidity,dust,salt spray,etc.In view of this the present work made a preliminary attempt to utilize advanced AI in the identification of insulation state of substation high-voltage electrical equipment.The main efforts entailed the enhanced treatment and feature calibra-tion of equipment infrared radiation images,and the introduction of loss functions and data augmentation into YOLOv5 network algorithm.The proposed idea was indicated by experiment superior in enhancement detection of equipment insula-tion state and IoU index compared with the selected reference method.