Sensor-based pavement diagnostic using acoustic signature for moduli estimation

Abstract

The diffusion of smart infrastructures for smart cities provides new opportunities for the improvement of both road infrastructure monitoring and maintenance management. Often pavement management is based on the periodic assessment of the elastic modulus of the bound layers (i.e., asphalt concrete layers) by means of traditional systems, such as Ground Penetrating Radar (GPR) and Falling Weight Deflectometer (FWD). Even if these methods are reliable, well-known, and widespread, they are quite complex, expensive, and are not able to provide updated information about the evolving structural health condition of the road pavement. Hence, more advanced, effective, and economical monitoring systems can be used to solve the problems mentioned above. Consequently, the main objective of the study presented in this paper is to present and apply an innovative solution that can be used to make smarter the road pavement monitoring. In more detail, an innovative Non-Destructive Test (NDT)-based sensing unit was used to gather the vibro-acoustic signatures of road pavements with different deterioration levels (e.g. with and without fatigue cracks) of an urban road. Meaningful features were extracted from the aforementioned acoustic signature and the correlation with the elastic modulus defined using GPR and FWD data was investigated. Results show that some of the features have a good correlation with the elastic moduli of the road section under investigation. Consequently, the innovative solution could be used to evaluate the variability of elastic modulus of the asphalt concrete layers, and to monitor with continuity the deterioration of road pavements under the traffic loads.