论文部分内容阅读
Ground Penetrating Radar(GPR) is an effective Non-Destructive Testing(NDT) technique for highway pavement surveys, which is able to acquire continuous pavement data compared with traditional core drilling method. In this study, we proposed an accurate and efficient method to estimate the thickness of each pavement layer using an air-coupled GPR system. For this work, the main difficulties are estimating each pavement layer’s time delay and dielectric constant. We first give the basic signal model for pavement evaluation, and then present an Intrinsic Mode Functions(IMFs) product detector to determine each pavement layer’s time delay. This method is based on Empirical Mode Decomposition(EMD), which is an adaptive signal decomposition procedure and proved to be suitable for suppressing noises in GPR signal. The dielectric constant was determined by metal reflection measurement. The laboratory and highway experiments illustrate that the proposed thickness estimation method yields reasonable result, thus meets the requirements of practical highway pavement survey with massive GPR data.
Ground Penetrating Radar (GPR) is an effective Non-Destructive Testing (NDT) technique for highway pavement surveys, which is able to acquire continuous pavement data compared with traditional core drilling method. In this study, we propose an accurate and efficient method to estimate the thickness of each pavement layer using an air-coupled GPR system. For this work, the main difficulties are estimated each pavement layer’s time delay and dielectric constant. We first give the basic signal model for pavement evaluation, and then present an Intrinsic Mode Functions This method is based on Empirical Mode Decomposition (EMD), which is an adaptive signal decomposition procedure and proved to be suitable for suppressing noises in GPR signal. The dielectric constant was determined by metal reflection measurement. The laboratory and highway protocols illustrate that the proposed thickness estimation method yields reasonab le result, thus meets the requirements of practical highway pavement survey with massive GPR data.