基于改进的扩展共中心点（XCMP）方法的探地雷达沥青路面层厚度实时预测
Real-Time Asphalt Pavement Layer Thickness Prediction Using Ground-Penetrating Radar Based on a Modified Extended Common Mid-Point (XCMP) Approach
AI总结：
针对传统表面反射法在非均匀介电特性路面厚度预测中的不足，本研究提出基于边缘检测的改进XCMP方法，实现天线对飞行时间的实时估计与沥青路面厚度自动预测，现场测试表明其平均误差1.86%显著优于传统方法的5.73%。
摘要：
传统表面反射法已被广泛用于使用探地雷达（GPR）测量沥青路面层介电常数。对于深度方向介电常数变化的服役中路面厚度估计，该方法可能不准确，使用带有空气耦合GPR天线的扩展共中心点方法（XCMP）可以解决此问题。然而，影响XCMP方法厚度预测精度的因素尚未得到研究。需要手动获取关键因素，这阻碍了其实时应用。本研究调查了影响因素，并开发了一种改进的XCMP方法，能够对深度方向介电特性非均匀的服役中沥青路面进行自动厚度预测。进行了敏感性分析，这要求准确估计来自天线对的飞行时间（TOFs）。提出了一种基于边缘检测的改进XCMP方法，以实现实时TOFs估计，进而进行介电常数和厚度预测。使用多通道GPR系统进行了现场测试以进行验证。表面反射和XCMP设置均已进行。结果表明，推荐使用改进的XCMP方法，其平均预测误差为1.86%，比表面反射法（5.73%）更准确。
英文摘要：
The conventional surface reflection method has been widely used to measure the asphalt pavement layer dielectric constant using ground-penetrating radar (GPR). This method may be inaccurate for in-service pavement thickness estimation with dielectric constant variation through the depth, which could be addressed using the extended common mid-point method (XCMP) with air-coupled GPR antennas. However, the factors affecting the XCMP method on thickness prediction accuracy haven't been studied. Manual acquisition of key factors is required, which hinders its real-time applications. This study investigates the affecting factors and develops a modified XCMP method to allow automatic thickness prediction of in-service asphalt pavement with non-uniform dielectric properties through depth. A sensitivity analysis was performed, necessitating the accurate estimation of time of flights (TOFs) from antenna pairs. A modified XCMP method based on edge detection was proposed to allow real-time TOFs estimation, then dielectric constant and thickness predictions. Field tests using a multi-channel GPR system were performed for validation. Both the surface reflection and XCMP setups were conducted. Results show that the modified XCMP method is recommended with a mean prediction error of 1.86%, which is more accurate than the surface reflection method (5.73%).
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