Research on Insulator Detection Algorithm for High-Speed Rail Contact Network
To satisfy the requirements of intelligent inspection at a greater level,a rotated insulator target detection algorithm based on the improved YOLOv5 is proposed to solve the inadequacy of conventional detection algorithms used for contact networks in high-speed rails,e.g.,low accuracy and non-consideration of insulation direction.First,Coordinated Attention(CA)and criss-cross attention mechanisms are introduced to efficiently extract the effective features and position information of insulators.The Reparameterization Visual Geometry Group(RepVGG)backbone network architecture is used to effectively improve the model representation and detection speed.In the backbone network of the detection head,the Alignment Convolution(AC)module is used to solve the tilt and feature misalignment of the insulator target,as well as to adjust the alignment degree of the prediction frame to the actual target.Finally,the Rotation Complete Intersection over Union(R-CIoU)is used to calculate the rotation loss function,which can be used to accurately position the prediction frame.Experimental results show that the proposed algorithm can detect different directions of insulators and that the mean Average Precision(mAP)can reach 97.5％while the detection speed is improved,thus satisfying the requirements of insulator target detection at a greater level.
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