Identification of steel bars immersed in reinforced concrete based on experimental results of eddy current testing and artificial neural network analysis - De Alcantara, Naasson [UNESP] (Taylor & Francis, 2013)
This paper presents an experimental research on the use of eddy current testing (ECT) and artificial neural networks (ANNs) in order to identify the gauge and position of steel bars immersed in concrete structures. The paper presents details of the ECT probe and concrete specimens constructed for the tests, and a study about the influence of the concrete on the values of measured voltages. After this, new measurements were done with a greater number of specimens, simulating a field condition and the results were used to generate training and validation vectors for multilayer perceptron ANNs. The results show a high percentage of correct identification with respect to both, the gauge of the bar and of the thickness of the concrete cover. © 2013 Copyright Taylor and Francis Group, LLC.
Keywords: artificial neural networks; eddy current testing; non-destructive testing; reinforced concrete; Concrete cover; Concrete specimens; Experimental research; Field conditions; Measured voltages; Multi layer perceptron; Non destructive testing; Steel bars; Bars (metal); Concrete construction; Eddy current testing; Gages; Neural networks; Reinforced concrete; Concretes