Applied Sciences (Jan 2022)

A Characterization Method for Pavement Structural Condition Assessment Based on the Distribution Parameter of the Vehicle Vibration Signal

  • Weiguo Wang,
  • Shishi Zhou,
  • Qun Yang

DOI
https://doi.org/10.3390/app12020683
Journal volume & issue
Vol. 12, no. 2
p. 683

Abstract

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A pavement structural survey plays a vital role in road maintenance and management. This study was intended to explore the feasibility of a non-stop pavement structure assessment method by analyzing the vibration data from a vehicle sensor. In this study, three falling weight deflectometer (FWD) tests and four vehicle vibration tests were conducted on five pavement structures. The FWD test results show that the continuously reinforced composite pavement has a higher structural stiffness than the semi-rigid base asphalt pavement. According to the statistical distribution of vehicle acceleration, a distribution parameter, the peak probability density (PPD), was proposed. The correlation coefficient (−0.722) of the center deflection (D1) and PPD indicates a strong correlation between the two variables. Therefore, PPD is strongly correlated with pavement structural stiffness. This study proposed a novel characterization method for pavement structural conditions based on the distribution parameter of the vehicle vibration signal.

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