Research on self-explosion defect detection of insulator based on improved YOLOv7

Insulator defect detection of transmission lines is one of the important tasks in the operation of power systems. Therefore, the self-explosion defect of insulators has become an important task in power inspection. Therefore, this article proposes an improved YOLOv7 based algorithm for detecting self-exploding defects in insulators. Firstly, select the loss function WIoU to reduce the missed detection rate; Then, use the CARAFE module for feature recombination to improve the detection accuracy of the model; Finally, the CBAM attention mechanism is cited to further improve the model performance. Through experimental verification, the improved YOLOv7 model has good detection performance, with mAP@.5% and Recall increased by 1.3% and 2.4% respectively, making it more suitable for detecting self-exploding defects in insulators.