Imaging and defect characterisation using multi-view ultrasonic data in nondestructive evaluation

Student thesis: Doctoral ThesisEngineering Doctorate (EngD)


Ultrasonic arrays are used in nondestructive testing for a wide range of inspections. The Full Matrix Capture (FMC) acquisition technique allows the capture of all the information possibly measurable by the probe. The Total Focusing Method (TFM) forms images by post-processing the FMC data, superseding conventional phased array techniques. By exploiting the wave mode conversions and the internal wave reflections in the specimen, multiple ultrasonic images may be formed, an approach termed multi-view imaging. Multi-view imaging increases the chance of obtaining a high response from a hypothetical defect in the specimen by considering multiple insonification paths.
This thesis investigates several areas relevant to multi-view imaging and defect characterisation. The defect response varies greatly with several variables including its shape, location, orientation, and the inspection set-up. As a consequence, the defect may have a strong response in a view, but be invisible in another one. A fast ultrasonic model which predicts the defect response in any view is introduced to help design sensitive inspections. The model is also used to build a database of reference scatterers against which the unknown defect is compared to characterise it. This technique makes it possible to determine the approximate shape, size and orientation of flaws which are too small to be well resolved on a TFM image.
The structural noise ultimately limits the detectability in ultrasonic images by creating a speckle pattern obscuring the defect. The peak amplitude of the speckle is a quantity relevant to the calculation of probabilities of detection and false alarm, but has been little studied in the literature. This thesis pursues its analysis.
Delay-and-sum is a widespread imaging approach. The presence of wall reflections may significantly degrade the image by adding artefacts. Replacing the summation by the median, a novel approach, is shown to efficiently suppress these artefacts.
Date of Award29 Sep 2020
Original languageEnglish
Awarding Institution
  • The University of Bristol
SupervisorPaul D Wilcox (Supervisor) & Anthony J Croxford (Supervisor)

Cite this

Imaging and defect characterisation using multi-view ultrasonic data in nondestructive evaluation
Budyn, N. S. (Author). 29 Sep 2020

Student thesis: Doctoral ThesisEngineering Doctorate (EngD)