Rotating insulator detection based on improved YOLOv5
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School of Mechanical Engineering,Shenyang Jianzhu University,Shenyang 110000, China

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    Abstract:

    To realize the precise positioning and quick recognition of insulators on a line that transmits electricity.A rotatingg target detection algorithm was proposed based on YOLOv5(You Only Look Once v5).A rotatingg retangular frame containing three types of labels was proposed for selfexploding insulators,It can improve the detection effect of the model and the convergence rate of the model.Use a Hardswish activation function to accelerate the computation and improve the numerical stability of the model. replace the Conv structure with the Ghost module structure,to reduce the number of parameters in the model and improve the detection efficiency of the model.Replace the CIOU Loss(Complete IoU loss) function with the EIOU Loss(Efficient IoU Loss) function and add a SLL(Smooth L1 Loss) about angle for regression of rectangular box angle,It can position the insulator more accurately and improve the detection effect of the model. The experimental results show that the improved insulator fault detection algorithm reduce the calculation amount of YOLOv5s model by 48.7% and the model size by 44.5%,Inference speed increase 2.9%,The overall detection accuracy of the model is 97.7%.In addition,it can also meet the realtime requirements of mobile deployment

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  • Received:
  • Revised:
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  • Online: January 08,2024
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