In ultra-wideband non-destructive testing of large multilayered polymers, data collection and reduction can be achieved by applying compressed sensing techniques. In this work, using effective modelling of possible defects, such as air gaps between layers, we construct defect dictionaries and use them as support data for a signal similarity-based classifier, which will automatically extract the main characteristics of the inspected defect.
Original languageEnglish
Title of host publicationInternational Conference on Infrared, Millimeter and Terahertz Wave
Subtitle of host publicationIRMMWTHz’16
PublisherIEEE
Pages1-2
Number of pages2
ISBN (Electronic)978-1-4673-8485-8
ISBN (Print)978-1-4673-8486-5
Publication statusPublished - 2016
EventInternational Conference on Infrared, Millimeter and Terahertz Wave: IRMMWTHz - Copenhagen, Denmark
Duration: 25 Sep 201630 Sep 2016

Conference

ConferenceInternational Conference on Infrared, Millimeter and Terahertz Wave
CountryDenmark
CityCopenhagen
Period25/09/1630/09/16

    Research areas

  • compressed sensing , Non-Destructive Testing, dictionary learning

ID: 26646625