Wavelet-Spectrogram Analysis of Surface Wave Technique for In Situ Pavement Stiffness Measurement

Accurate, quick, and nondestructive in situ tests for measuring pavement stiffness, or elastic modulus, are an increasingly important element in pavement management systems. This is due to the increasing number of aged road networks and the limited budget allocated by the government for pavement monitoring and maintenance. This paper aims to propose a new wavelet-spectrogram analysis of surface wave (WSSW) technique for nondestructive testing and in situ measurement of pavement surface layers. The proposed technique was developed on the basis of the spectral analysis of surface wave (SASW) and modified data analysis of the ultrasonic surface wave (USW) methods. This technique uses two receivers to detect and record the signals of the surface wave propagating on a pavement surface. In wavelet analysis, the received signals are transformed into a time-frequency domain and displayed in a spectrogram. The spectrogram was generated on the basis of the mother wavelet of the Gaussian derivative (GoD). A wavelet filtration technique was also used in the time-frequency spectrogram to diminish the effect of the noise signal recorded during field measurement. The unwrapped phase of a different spectrum was generated from a selected wave energy in the spectrogram to obtain a phase velocity; this was performed through a linear regression analysis for calculating the value of the slope of a phase velocity. The elastic modulus of the pavement surface layer can be obtained via a linear relationship of assumed density, measured phase velocity, and assumed Poisson’s ratio of pavement materials. The results can be used to show that the proposed technique can be of practical use for in situ elastic modulus measurement on flexible and rigid pavements. It can also be used to determine any changes that might occur in the stiffness of the pavement surface layer.

Language

  • English

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 01683011
  • Record Type: Publication
  • Files: TRIS, ASCE
  • Created Date: Oct 11 2018 11:28AM