NDT Data Fusion for the Enhancement of Defect Visualization in Concrete

Abstract:

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 the fusion of GPR and thermographic phase contrast data to enhance defect visualization in concrete. The evaluation 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 achieve 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.

• Periodical: Key Engineering Materials (Volumes 569-570)
• Pages: 175-182
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.569-570.175
• Online since: July 2013
• Authors: Patricia Cotič, Ernst Niederleithinger, Vlatko Bosiljkov, Zvonko Jagliċiċ
• Keywords: Active Thermography, Concrete, Data Fusion, Ground Penetrating Radar (GPR), Nondestructive Testing (NDT)

References

[1] D.M. McCann, M.C. Forde, Review of NDT methods in the assessment of concrete and masonry structures, NDT&E International. 34 (2001) 71-84.

DOI: 10.1016/s0963-8695(00)00032-3

[2] R. Beutel, H.W. Reinhardt, C.U. Grosse, A. Glaubitt, M. Krause, Ch. Maierhofer, D. Algernon, H. Wiggenhauser, M. Schickert, Comparative performance tests and validation of NDT methods for concrete testing, Journal of Nondestructive Evaluation. 27 (2008).

DOI: 10.1007/s10921-008-0037-1

[3] P. Shokouhi, H. Wiggenhauser, Multi-probe ultrasonic testing for detection of delamination in concrete bridge decks, Transportation Research Board (TRB) 90th Annual Meeting, Washington, D.C., January 23-27, 2013. (accessed at URL http: /amonline. trb. org/1sl7d2/1).

[4] P. Cotic, Z. Jaglicic, E. Niederleithinger, U. Effner, S. Kruschwitz, C. Trela, V. Bosiljkov, Effect of moisture on the reliability of void detection in brickwork masonry using radar, ultrasonic and complex resistivity tomography, Materials and Structures, 2013, doi: 10. 1617/s11527-012-0011-3.

DOI: 10.1617/s11527-012-0011-3

[5] Ch. Maierhofer, Ch. Köpp, L. Binda, L. Zanzi, J.R. Santiago, B. Knupfer, B. Johansson, C. Modena, F. Porto, M. Marchisio, F. Gravina, M. Falci, J.C. Ruiz, M. Tomazevic, V. Bosiljkov, Ch. Hennen, Project Report EUR 21696 EN – Onsiteformasonry project – On-site investigation techniques for the structural evaluation of historic masonry buildings, European Comission, Luxembourg: Office for Official Publications of the European Communities, Brussels, 141 pages, (2006).

[6] Ch. Maierhofer, M. Röllig, Application of active thermography to the detection of safety relevant defects in civil engineering structures, Proceedings OPTO 2009 & IRS² 2009, SENSOR+TEST Conferences 2009, Nürnberg, Germany, May 26-28, (2009).

DOI: 10.5162/irs09/i2.2

[7] Ch. Maierhofer, G. Zacher, C. Kohl, J. Wöstmann, Evaluation of radar and complementary echo methods for NDT of concrete elements, Journal of Nondestructive Evaluation. 27 (2008) 47-57.

DOI: 10.1007/s10921-008-0030-8

[8] C. Kohl, M. Krause, Ch. Maierhofer, J. Wöstmann, 2D-and 3D-visualisation of NDT-data using data fusion technique, Materials and Structures. 38 (2005) 817-826.

DOI: 10.1007/bf02481654

[9] E. Niederleithinger, G. Wilsch, P. Cotic, Improvement of Spectroscopic Measurement Results on Concrete by Advanced Clustering Methods, Proceedings of the 16th Int. Conf. on Information Fusion, Istanbul, Turkey, July 9-12, 2013. (sent for publication).

[10] Z. Liu, D.S. Forsyth, J.P. Komorowski, K. Hanasaki, T. Kirubarajan, Survey: State of the art in NDE data fusion techniques, IEEE Transactions on Instrumentation and Measurement. 56 (2007) 2435-2451.

DOI: 10.1109/tim.2007.908139

[11] X.E. Gros (ed. ), Application of NDT data fusion, Kluwer Academic Publishers, Boston, (2001).

[12] J.D. Daniels (ed. ), Ground-penetrating radar – 2nd ed., The Institution of Electrical Engineers, London, (2004).

[13] X.P. Maldague, S. Marinetti, Pulse Phase Infrared Thermography, J. Appl. Phys. 79 (1996) 2694-2698.

DOI: 10.1063/1.362662

[14] R. Arndt, Square pulse thermography in frequency domain, in: V.P. Vavilov, D. D Burleigh (eds. ), Thermosense XXX, Proceedings of the SPIE, 2008, pp. 69390X-69390X-12.

DOI: 10.1117/12.777697

[15] F. Höppner, F. Klawonn, R. Kruse, T. Runkler, Fuzzy Cluster Analysis: Methods for classification, data analysis and image recognition, John Wiley & Sons Ltd., Chichester, (1999).

[16] J.C. Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York, (1981).

[17] D. Gustafson, W. Kessel, Fuzzy clustering with a fuzzy covariance matrix, in: 1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes, 1978, pp.761-766. doi: 10. 1109/CDC. 1978. 268028.

DOI: 10.1109/cdc.1978.268028

[18] R.N. Dave, Characterization and detection of noise in clustering, Pattern Recognition Letters. 12 (1991) 657-664.

DOI: 10.1016/0167-8655(91)90002-4

[19] N.R. Pal, K. Pal, J.M. Keller, J.C. Bezdek, A Possibilistic Fuzzy c-Means Clustering Algorithm, IEEE Transaction on Fuzzy Systems. 13 (2005) 517-530.

DOI: 10.1109/tfuzz.2004.840099

[20] D.G. Altman, J.M. Bland, Diagnostic tests. 1: Sensitivity and specificity, BMJ. 308 (1994) 1552.

[21] G. Shafer, A Mathematical Theory of Evidence, Princeton University Press, Princeton, (1976).

[22] X.E. Gros, J. Bousigue, K. Takahashi, NDT data fusion at pixel level, Ndt & E International. 32 (1999) 283-292.

DOI: 10.1016/s0963-8695(98)00056-5