Model-assisted ultrasonic calibration using intentionally embedded defects for in-process weld inspection

Mohseni, Ehsan and Javadi, Yashar and Sweeney, Nina E. and Lines, David and MacLeod, Charles N. and Vithanage, Randika K.W. and Qiu, Zhen and Vasilev, Momchil and Mineo, Carmelo and Lukacs, Peter and Foster, Euan and Pierce, S. Gareth and Gachagan, Anthony (2021) Model-assisted ultrasonic calibration using intentionally embedded defects for in-process weld inspection. Materials and Design, 198. 109330. ISSN 0261-3069 (https://doi.org/10.1016/j.matdes.2020.109330)

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Abstract

Automated in-process Non-Destructive Testing (NDT) systems are rapidly gaining traction within the manufacturing industry as they reduce manufacturing time and costs. When considering calibration and verification of such systems, creating defects of known geometry and nature during the deposition of a weld can: (I) help examine the capability of the automated system to detect and characterise defects, (II) be used to form a database of signals associated with different defect types to train intelligent defect classification algorithms, and (III) act as a basis for in-process gain calibration during weld inspection at high temperatures, where the ultrasound beam can be skewed as a result of velocity gradients. In view of this, this paper investigates two unique methodologies for introducing: (a) lack of fusion weld defects by embedding tungsten in the weld and (b) creating artificial weld cracks by quenching to imitate the real cracking scenarios. According to the results of Phased Array Ultrasound Testing (PAUT) inspections, the methodologies used for embedding the artificial defects were successful. The validity of inspections was also verified by extracting micrographs from the defective sections of the welds, and model-based simulations were carried out to gain a better understanding of the wave propagation path and interaction with the generated defects.

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