Data Fusion of Non-destructive Testing Methods for Bridge Deck Condition Assessment

Highway agencies explore the use of non-destructive testing (NDT) for assessing the condition of their infrastructure in the most cost-effective manner. NDTs can provide as-built construction quality, as well as in service condition assessment especially for older structures where some critical information and/or maintenance records are often not available. In many cases, the use of NDTs requires “ground true” data for either calibration or validation. Surveys for obtaining such information is often challenging for in service structures, time consuming and costly. Objective of this paper is to present a data fusion approach for forensic investigation of bridge decks, in which Ground Penetrating Radar (GPR) is used to assess the current condition combined with a Laser Scanner system to verify the bridge design features. The data fusion approach proposed in this study considers using GPR based condition data combined with geometric measurements of the bridge deck obtained from the Laser Scanner system. Such novel fusion approach permits to more accurately measure the current bridge deck conditions in terms of thickness of the bridge deck and rebar depth to assess deterioration. Furthermore, detection of variations in the rebar depth suggested the implementation of a correction procedure for the reflection amplitude of the GPR signal based on true rebar depths instead of the two-way travel time, which is commonly applied. This innovative analysis approach provided a more refined assessment of delaminated areas in the bridge deck. The data fusion and suggested analysis methodology was tested on a pre-stressed concrete bridge in Italy. The approach proposed in this study can be used elsewhere for assessing the condition of bridge decks. The merging of such methods is particularly valuable for bridges were construction drawing and records may not be available, and/or there is potential concern of a deviation between design and as-built characteristics (i.e., where quality assurance and quality control records may be questionable).