Full Matrix Capture for Ultrasonic Imaging through Brazed Surfaces

ABSTRACT Brazing is a common joining technique employed in industry to assemble sheet metal components. A metal filler wire is melted, wetting the substrate surfaces, after which it solidifies, producing a strong bond between the base material sheets. As in all joining techniques, process and material variations can lead to imperfections in brazed joints. The primary brazing imperfections studied in this investigation are lack of adhesion, porosity and inclusions in the filler material, melting of the base metal, as well as unwanted deviations in braze geometry. Several non-destructive evaluation techniques can detect the overall presence of these imperfections by comparing the joint to an ideal sample. These approaches, however, do not achieve the desired precision in quantification of the individual imperfection types, and necessitate high reproducibility in braze joint geometry. The primary difficulty in quantifying the individual imperfections is that the size and shape of both the filler and substrate materials are not known sufficiently well prior to inspection. To overcome this difficulty, ultrasonic inspection using the full matrix data acquisition method with post processing has been utilized to both detect and correct for the top braze surface in imaging the above-mentioned internal imperfections.


[1] Schwartz, M. M., 2003, Brazing, Second Edition, Materials Park, Ohio  : ASM International, Materials Park, Ohio.

[2] Brittish Stantdards Institution, 2000, "Brazing. Destructive tests of brazed joints,"EN 12797:2000.

[3] Doering, E. R., 1992, “Three-Dimensional Flaw Reconstruction Using a Real- Time X-Ray Imaging System,” Iowa State University.

[4] Lindgren, E., 2014, “Detection, 3-D Positioning, and Sizing of Small Pore Defects Using Digital Radiography and Tracking,” EURASIP J. Adv. Signal Process., 2014(1), p. 9.

[5] Grubsky, V., Romanov, V., Shoemaker, K., and Tikhoplav, R., 2014, “Recent Progress on 3D Backscatter X-Ray NDE Physical Optics Corporation.”

[6] Runnemalm, A., and Broberg, P., 2014, “Surface Crack Detection Using Infrared Thermography and Ultraviolet Excitation,” QIRT2014 Conférence.

[7] Broberg, P., and Runnemalm, A., 2012, “Detection of Surface Cracks in Welds Using Active Thermography,” (April), pp. 16–20.

[8] Rodríguez-Martin, M., Lagüela, S., González-Aguilera, D., and Arias, P., 2014, “Cooling Analysis of Welded Materials for Crack Detection Using Infrared Thermography,” Infrared Phys. Technol., 67, pp. 547–554.

[9] An, Y.-K., Min Kim, J., and Sohn, H., 2014, “Laser Lock-in Thermography for Detection of Surface-Breaking Fatigue Cracks on Uncoated Steel Structures,” NDT E Int., 65, pp. 54–63.

[10] Jeune, L. Le, Robert, S., Dumas, P., Membre, A., and Prada, C., “Adaptive Ultrasonic Imaging with the Total Focusing Method for Inspection of Complex Components Immersed in Water.”

[11] Grotenhuis, R. T. E. N., Chen, A., Hong, A., and Verma, Y., 2016, “Application of a FMC / TFM Ultrasonic System to Inspection of Austenitic Welds,” pp. 1–9.

[12] Holmes, C., Drinkwater, B. W., and Wilcox, P. D., 2005, “Post-Processing of the Full Matrix of Ultrasonic Transmit–receive Array Data for Non-Destructive Evaluation,” NDT E Int., 38(8), pp. 701–711.

[13] Zhang, J., Hunter, A., Drinkwater, B. W., and Wilcox, P. D., 2012, “Monte Carlo Inversion of Ultrasonic Array Data to Map Anisotropic Weld Properties,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, 59(11), pp. 2487–2497.

[14] Humeida, Y., Wilcox, P. D., Todd, M. D., and Drinkwater, B. W., 2014, “A Probabilistic Approach for the Optimisation of Ultrasonic Array Inspection Techniques,” NDT E Int., 68, pp. 43–52.

[15] Wydra, A., Chertov, A. M., Maev, R. G., Kube, C. M., Du, H., and Turner, J. A., 2015, “Grain Size Measurement of Copper Spot Welding Caps Via Ultrasonic Attenuation and Scattering Experiments,” Res. Nondestruct. Eval., 26(4), pp. 225–243.

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