LAUSR

Thickness detection of concrete pavement is a critical step in construction completion acceptance and serves as an important metric for subsequent pavement performance evaluations. The crux of thickness evaluation lies in determining the interface reflection echo propagation sound time. Based on the acoustic impedance difference between the surface layer and contact layer, pavement can be classified into two types: large-difference and small-difference. By examining the singularity of the detection signal, we employed the improved correlation coefficient method and the wavelet transform maximum value method to identify the interface reflection echo sound time. This study refines the traditional correlation coefficient method by using the surface direct wave as the reference signal, simplifying the signal analysis process. In actual detection, for the type of concrete pavement with large differences in acoustic impedance, the average relative error between the improved correlation coefficient method and the core drilling method can be reduced to 1.7%; for the type with small differences, the average relative error of the detection results obtained using the wavelet transform modulus maximum method can be reduced to 1.9%, showcasing high accuracy.