The use of the Intelligent Asphalt Compaction Analyzer (IACA) to estimatethe stiffness of an asphalt pavement during its construction is addressedin this paper. For a given asphalt mix, the Master Curves for the dynamic modulus are first determined through the AASHTO TP62-03 (1) test procedure. These Master Curves are then used to calibrate the IACA to estimate the modulus of the pavement during its construction. The modulus at severallocations on the compacted pavement was determined through Falling WeightDeflectometer (FWD) tests after the pavement has cooled down to ambient temperature. Comparison of the estimated and measured modulus at 21 degree Celsius shows that the IACA can be used as a quality control tool to during the construction of an asphalt pavement. Contrary to existing techniquesin the literature the IACA uses a neural network and pattern-recognition techniques to estimate the stiffness. The neural network is designed to read in the entire frequency spectrum of the vibrations of the roller and classify these vibrations into different levels. The IACA is then calibratedto convert these levels of vibration into a modulus value representing the stiffness of the asphalt mat. This two step process produces stiffness measurements that are more accurate than those reported elsewhere in the literature. The IACA provides the measurement over the entire pavement and is non-destructive in nature. Further, the proposed method also allows for the easy verification of the estimated modulus through FWD tests on the completed pavement.
Abstract