NDT sensor fusion in road pavement structural condition surveys

The analysis of the sensor fusion results for the data acquired during the field trials on the A22 Brennero Motorway showed that the combination of the sensor outputs (GPR and IRT, especially) provides more information on the road pavement subsurface condition than the individual sensors as well as increasing the degree of validity of the survey results.

Moreover, the cross-referencing of the individual sensor outputs should be used for verification of the “existence” of the detected defects in order to decrease the number of false positive alarms. For instance, while the GPR analysis showed to be efficient in the detection of subsurface defects such as delaminations between the layers and material/structural changes as well as the sites of transition between the road pavement and bridge deck, IRT provides the segregation map for the entire lane thus allowing assessment of the condition of the regions not covered by the GPR antennas as well as the “global picture” of road surface around the detected defects.

The corresponding examples include delaminations close to the lane borderline, deteriorated joint in the middle of the lane, structural changes (e.g., patching and overlays), local variations in the material properties (e.g., trapped moisture, asphalt degradation), surface defects (e.g., cracking, potholes), etc. In general, it was concluded that IRT significantly extends the quality of the subsurface condition information extracted from GPR, while ACU can be used as an additional tool for mapping of the surface level defect locations and changes in the material properties.

Spatially referenced decision-level sensor fusion output report:

RPB HealTec post-processing software for the automated analysis of the synchronised IRT, GPR and ACU datastreams and decision level sensor fusion: