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  • NDT data fusion for the enhancement of defect visualization in concrete
    Cotič Smole, Patricia, 1987- ...
    Ground penetrating radar (GPR) and active thermography are well known non-destructive testing (NDT) methods for structural visualization and defect detection in concrete. However, for both methods, ... the probability of detection is strongly depth-dependent and each method suffers from an almost blind region at a specific depth. In this study we propose the use of unsupervised clustering techniques for fusion of GPR and thermographic phase contrast data to enhance defect visualization in concrete. The evaluatin was carried out on the basis of experimental data acquired on laboratory concrete test specimens, which contain inbuilt anomalies varying in shape, material and position. To achive an optimal fusion of radar depth slices and thermographic phase contrast images along the depth axis, we derive sensitivity curves for both NDT methods and use the probability mass information to further improve the fusion results. Results show that the fuzzy c-means algorithm may contribute to an enhanced detection probability of defects below high density reinforcement. For defects with a concrete cover from 1.5 to 2 cm, the use of weighted clustering is particularly suggested. In general, complex defect types and shapes could be better resolved by using the Gustafson-Kessel algorithm or noise clustering. In addition, we demonstrate the application of the Dempster-Shafer theory to quantitatively evaluate the effectiveness of fused data on the basis of joint mass probability.
    Vir: Damage assessment of structures X : selected, peer reviewed papers from the 10th International Conference on Damage Assessment of Structures (DAMAS 2013), July 8-10, 2013, Dublin, Ireland (Str. 175-182)
    Vrsta gradiva - prispevek na konferenci
    Leto - 2013
    Jezik - angleški
    COBISS.SI-ID - 16662617

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