摘要
【目的】针对高速铁路接触网绝缘子在复杂背景下检测效率不高的问题提出一种检测算法。【方法】首先对样本数据集进行大规模扩充,在原有YOLOv5s算法的基础上,为有效的提升模型的表征力,增加ECA注意力机制,进行无降维的跨信道方式来聚焦绝缘子位置信息;使用BiFPN特征金字塔网络,进行多尺度的特征融合来丰富语义信息;选用Meta-ACON自适应控制激活函数,在函数允许的最大范围内,严格把控函数的上下限,防止模型出现失控现象;将原有GIOU损失函数更换为EIOU损失函数,从梯度的角度对锚框进行更深一步的划分,进而提升网络的收敛速度。【结果】实验结果表明,通过对YOLOv5s改进后的检测算法,可以对绝缘子进行更精确的定位与识别,准确率达到了99.4%。【结论】所提出的检测算法为绝缘子定位检测提供了更加准确快捷的方法。
【Purpose】A detection algorithm is proposed to address the issue of low detection efficiency of highspeed railway contact line insulators in complex backgrounds.【Methods】On the basis of the original YOLOv5s algorithm,in order to effectively improve the representation power of the model and increase the ECA attention mechanism,a cross-channel method without dimensionality reduction is carried out to focus on the position information of insulators.The BiFPN feature pyramid network is used to enrich the semantic information by multiscale feature fusion.The Meta-ACON adaptive control activation function is selected and the upper and lower limits of the function is strictly controlled within the maximum range allowed by the function to prevent the model from running out of control.The original GIOU loss function is replaced with the EIOU loss function,and the anchor box is further divided from the perspective of gradient,so as to improve the convergence speed of the network.【Results】Acoording to the experimental results,the improved detection algorithm of YOLOv5s can be used to locate and identify the insulator more accurately,and the accuracy rate reaches 99.4%.【Conclusion】The proposed detection algorithm provides a more accurate and faster method for insulator positioning detection.
作者
刘仕兵
周诗涵
但业光
Liu Shibing;Zhou Shihan;Dan Yeguang(School of Electrical and Automation Engineering,East China Jiaotong University,Nanchang 330013,China)
出处
《华东交通大学学报》
2024年第1期105-112,共8页
Journal of East China Jiaotong University
基金
轨道交通基础设施性能监测与保障国家重点实验室开放课题(GJJ210652)。
