ANN modeling of pull-off adhesion of concrete layers

When making and repairing concrete floors it is vital to properly prepare the interlayer bonding surface. The measure of the bond is the value of pull-off adhesion fb experimentally determined in building practice by the semi-destructive (SDT) pull-off method. In this paper it is proposed to assess pull-off adhesion by jointly the optical laser triangulation method and the acoustic impulse response method, using artificial neural networks (ANN), on the basis of a few parameters (independent of top layer thickness) determined by these methods. The proposed non-destructive (NDT) pull-off adhesion assessment method is devoid of the drawbacks and inconveniences of the pull-off method and makes possible the reliable mapping of the adhesion level on the tested surface without local damage to the latter.