基于探地雷达的沥青路面厚度检测研究

Research on Asphalt Pavement Thickness Detection based on Ground Penetrating Radar

在道路养护过程中,对路面厚度的有效检测至关重要。传统的钻芯取样法难以满足日益增长的检测需求,而随着现代科学技术的发展,探地雷达等新型无损检测技术逐渐应用于道路检测与养护中。针对沥青路面厚度检测的实际需求,结合探地雷达检测技术和数字图像处理算法,对探地雷达图像进行分析和处理,以实现沥青路面厚度的自动提取。分别采用Canny算法、连通区域检测算法对探地雷达图像进行处理,并结合gprMax软件正演模拟数据对以上方法的准确性进行对比分析。结果表明,Canny算法具有更好的效果,与实地钻孔取芯测量的厚度相比,其相对误差约为4.13%,可以较好地实现探地雷达图像中沥青路面厚度的快速智能提取。

During the process of road maintenance, it is very important to detect the pavement thickness effectively.The traditional drilling core sampling method is difficult to meet the increasing testing demand. With the development of modern science and technology, new nondestructive testing techniques of ground penetrating radar(GPR)are gradually applied in road testing and maintenance. According to the actual demand of asphalt pavement thickness detection, combined GPR detection technology and digital image processing algorithm, the GPR image was analyzed and processed to automatic extract the asphalt pavement thickness. The GPR image was processed by Canny algorithm and the connected area detection algorithm respectively, and the accuracy of the above methods was compared and analyzed by the forward simulation data of gprMax software. The results show that the Canny algorithm has a better effect. Compared with the thickness measured by field coring, the relative error of Canny algorithm is about4.13%, which can better realize the fast intelligent detection of asphalt pavement thickness in GPR images.