Abstract
In reinforced concrete, as known, the steel bar, damping totally the traction stress, they are mainly subject to breakage. Then, as required by current legislation, it is necessary a check protocol of the specimens characterizing any defects since the typology of defect, often, determines its intended use. From this, the choice to use non-invasive technique such as Non-Destructive Testing and Evaluation (NDT / NDE) based on Eddy Currents is necessary. Starting from a campaign of Eddy Currents measurements potentially affected by uncertainty and/or imprecision, in this work we propose a new fuzzy approach based on Computing with Words techniques where a word is considered a label of a fuzzy set of points shared by similarities coming to an adaptive bank of fuzzy rules structured by classes possibly updated by the Expert’s knowledge. The numerical results obtained by means of the proposed approach are comparable with the results carried out by Fuzzy Similarities techniques already established in the literature.
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Calcagno, S., Foresta, F.L. (2019). Advanced Computational Intelligence Techniques to Detect and Reconstruct Damages in Reinforced Concrete for Industrial Applications. In: Esposito, A., Faundez-Zanuy, M., Morabito, F., Pasero, E. (eds) Neural Advances in Processing Nonlinear Dynamic Signals. WIRN 2017 2017. Smart Innovation, Systems and Technologies, vol 102. Springer, Cham. https://doi.org/10.1007/978-3-319-95098-3_17
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DOI: https://doi.org/10.1007/978-3-319-95098-3_17
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