Model updating using limited experimental data for the quantification of ultrasonic array inspection.

  • Harry Bloxham

Student thesis: Doctoral ThesisDoctor of Philosophy (PhD)

Abstract

Ultrasonic non-destructive testing inspections using phased arrays are performed on a wide range of components and materials. All real inspections su↵er, to varying extents, from coherent noise including image artefacts and speckle caused by complex geometries and grain scatter respectively. By its nature, this noise is not reduced by averaging; however, it degrades the signal to noise ratio of defects and ultimately limits their detectability. When evaluating the e↵ectiveness of an inspection, a large pool of data from samples containing a range of di↵erent defects is important to estimate the probability of detection of defects and to help characterise them. For a given inspection, coherent noise is easy to measure experimentally but hard to model realistically. Conversely, the ultrasonic response of defects can be simulated relatively easily.
This thesis investigates a novel method of simulating realistic array data by combining noise- free simulations of defect responses with coherent noise taken from experimental data. This technique, referred to as the superposition technique, was validated both experimentally using samples with physical defects present and against FE models. It has been shown to provide accurate results over the full range of signal to noise ratios where the defect remains detectable. The work presented here expands the available modelling capabilities for ultrasonic imaging data for high noise inspections which has traditionally been dicult to achieve.
Date of Award25 Jun 2019
Original languageEnglish
Awarding Institution
  • The University of Bristol
SupervisorPaul D Wilcox (Supervisor) & Alexander Velichko (Supervisor)

Cite this

Model updating using limited experimental data for the quantification of ultrasonic array inspection.
Bloxham, H. (Author). 25 Jun 2019

Student thesis: Doctoral ThesisDoctor of Philosophy (PhD)