改进YOLOv5的绝缘子旋转目标检测
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沈阳建筑大学机械工程学院 沈阳 110000

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TP

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辽宁省科技重大专项(2020JH1/10100012)资助


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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    摘要:

    为实现输电线路绝缘子的精确定位与快速识别,提出了一种基于YOLOv5(You Only Look Once v5)的旋转目标检测算法。针对绝缘子自爆故障,提出了一种三标签的旋转矩形框标注方法,能够提升模型的检测效果和收敛速度;引入Hardswish激活函数加速计算,同时提高模型的数值稳定性;用Ghost module代替Conv结构,以此来降低模型的参数量,提升模型的检测效率;将位置损失使用的CIOU Loss(Complete IoU loss)函数改进为EIOU Loss(Efficient IoU Loss)函数,添加一个角度损失函数SLL(Smooth L1 Loss),用于矩形框角度的回归,使模型能更精准的定位绝缘子的位置,提高模型的检测效果。实验表明,改进的绝缘子故障检测算法相较于YOLOv5s模型的浮点计算量减小了487%,模型大小降低了445%,推理速度提升29%,模型的整体检测精度能达到977%,同时还能满足移动端部署的实时性要求。

    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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张珂,余锟铻,石怀涛.改进YOLOv5的绝缘子旋转目标检测[J].电子测量技术,2023,46(15):52-58

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  • 在线发布日期: 2024-01-08
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