Knowledge Extraction Algorithms Dedicated for Identification of Steel Bars in Reinforced Concrete Structures

The purpose of this paper is to present knowledge extraction algorithms, dedicated for new electromagnetic system used to evaluate steel bars in reinforced concrete structures. All stages of the rebar identification process have been presented. At the first step, relations between parameters of the tested structure and measured waveform are extracted. For this purpose, a dedicated association rules learning algorithm is proposed. In the next stage, the collected data are filtered and smoothed. Finally, classification models are implemented, tested and evaluated. The experimental verification of the applied techniques was carried out, and the selected results are presented.