Steel bars identification in reinforced concrete structures by using ANN and magnetic fields

This work proposes a methodology for non destructive testing (NDT) of reinforced concrete structures, using superficial magnetic fields and artificial neural networks, in order to identify the size and position of steel bars, embedded into the concrete. For the purposes of this paper, magnetic induction curves were obtained by using a finite element program. Perceptron Multilayered (PML) ANNs, with Levemberg-Marquardt training algorithm were used. The results presented very good agreement with the expect ones, encouraging the development of real systems based upon the proposed methodology. This work proposes a new methodology for the inspection of steel bar immersed in concrete structures, based in the analysis of magnetic induction curves, created at the region of the structure by electromagnetic devices specially designed for this purpose. The analysis of the magnetic induction curves is done by means of artificial neural networks. For the purpose of this paper, the magnetic inductions values were simulated using a finite element program (6). 1. The Proposed Methodology The methodology proposed in this paper for the localization and identification of steel bars in reinforced concrete structures consists in the utilization of artificial neural networks for pattern classification of electro- magnetic signatures presented by the steel bars embedded into the concrete, at the concrete surface, when static and/or quasi-static electromagnetic fields are generated in the region of the concrete structure. The presence of the steel bars within the concrete will slightly disturb the field distribution at the concrete surface. This field perturbation will depend of the size, position and number of bars within the concrete. Each bars configuration will produce an unique deviation curve, called magnetic signature of the bar (or bars). When a large number of samples are taken, artificial neural networks can be used to create an input/output relationship between the magnetic signature and the bar (or bars) configuration. In order to obtain a better comprehension of the proposed methodology, it will used to identify a steel bar embedded in the concrete. First of all, hundreds of curves of induction magnetic deviations must be obtained. For the purpose of this paper, they were generated using a finite element program (6). The curves represent variations of the position and size of the bar into the concrete. Figure (1a) illustrate the variations of the position of the bar in the horizontal axis, and figure 1b illustrate the variations in the vertical axis. They represent 5 variations in the horizontal position (stepped by 2.5 mm) and 30 variations in the vertical position (stepped by 2 mm). By this way, 150 variations in the position were considered. Beyond this, 7 sizes were considered for