Investigation into distinguishing between small volumetric and crack-like defects using multi-view total focusing method images
Author(s) -
Jie Zhang,
Tom Barber,
Andrew Nixon,
Paul D. Wilcox
Publication year - 2017
Publication title -
aip conference proceedings
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.177
H-Index - 75
eISSN - 1551-7616
pISSN - 0094-243X
DOI - 10.1063/1.4974590
Subject(s) - computer vision , artificial intelligence , computer science , amplitude , image processing , image (mathematics) , ultrasonic sensor , pattern recognition (psychology) , materials science , acoustics , optics , physics
In the post-processing of ultrasonic array full matrix capture (FMC) data from an immersion inspection to image a region of interest (ROI), the total focusing method (TFM) can be used to generate multiple image views for the same region through exploiting reflections off geometric features, mode conversions at interfaces and using different paths for transmitted and received waves. They are termed as the multi-view TFM (MTFM) images. In this paper, the feasibility of using MTFM images to distinguish between small volumetric and crack-like defects is investigated through the analysis of the images from various simulated and experimentally-measured FMC array data sets. It is found that the presence of a defect of a particular type will typically be observable in some or all of the views with different image amplitudes. Different types of defect have large amplitudes in different views and this can be used to classify the defect type. Finally, the use of this approach is demonstrated in the experimental insp...
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