The purpose of this paper is to present a multi-sensor approach to the detection and inspection of steel bars in reinforced concrete structures. In connection with our past experience related to non-destructive testing of different materials, we propose using two potentially effective methods: active infrared thermography with microwave excitation and the eddy current technique. In this article active infrared thermography with microwave excitation is analyzed both by numerical modeling and experiments. This method, based on thermal imaging, due to its characteriatics should be considered as a preliminary method for the assessment of relatively shallowly located steel bar reinforcements. The eddy current technique, on the other hand, allows for more detailed evaluation and detection of deeply located rebars. In this paper a series of measurement results, together with the initial identification of certain features of steel reinforcement bars will be presented.

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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.

Abstract. The aim of this paper is to present an expert system for identification of the basic reinforcement concrete structures parameters like: rebars diameter, thickness of a concrete cover and a kind of rebar's alloy (class). The results of measurement carried out by the eddy current transducers were utilized for the designed system. Measured waveforms are represented by two kinds of attributes, the d-factors represent a waveform shape, and a maximal amplitude. In order to extract an association rules between the specific attributes and the structure parameters a rough set theory was used.