Research and Application of Intelligent Detection of Transmission Line Insulator Fault Based on UAV Aerial Video Images
Along with the continuous improvement of our economy,the demand of national power is also increasing.Among them,insulators are widely used in high voltage transmission lines to play the role of insulation and support.Long time exposure or long-term use,will lead to its stain and deterioration,more prone to flashover discharge and other dangerous phenomena.Therefore,insulator fault detection becomes an important part of power grid inspection.But ordinary manual inspection is not only heavy work,high cost and high risk,so intelligent drone inspection comes into being.Using UAV for power inspection not only improves work efficiency,but also reduces field work and inspection cost.Due to the unsatisfactory effect of traditional image processing technology on insulator feature extraction of UAV and the low universality of detection method,an insulator identification and positioning method is proposed in this paper.The correction technology is based on YOLOv4 algorithm,which greatly improves the accuracy and has good performance and certain universality in insulator detection under different environments.
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