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Ultrasonic classification of thin layers within multi-layered structures
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-6216-6132
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
2010 (English)In: Measurement science and technology, ISSN 0957-0233, E-ISSN 1361-6501, Vol. 21, no 1Article in journal (Refereed) Published
Abstract [en]

Methods for non-destructive inspection of layered materials are becoming more and more popular as a way of assuring product integrity and quality. In this paper, we present a model-based technique using ultrasonic measurements for classification of thin bonding layers within three-layered materials. This could be, for example, an adhesive bond between two thin plates, where the integrity of the bonding layer needs to be evaluated. The method is based on a model of the wave propagation of pulse-echo ultrasound that first reduces the measured data to a few parameters for each measured point. The model parameters are then fed into a statistical classifier that assigns the bonding layer to one of a set of predefined classes. In this paper, two glass plates are bonded together with construction silicone, and the classifiers are trained to determine if the bonding layer is intact or if it contains regions of air or water. Two different classification methods are evaluated: nominal logistic regression and discriminant analysis. The former is slightly more computationally demanding but, as the results show, it performs better when the model parameters cannot be assumed to belong to a multivariate Gaussian distribution. The performance of the classifiers is evaluated using both simulations and real measurements.

Place, publisher, year, edition, pages
2010. Vol. 21, no 1
National Category
Signal Processing Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Signal Processing; Industrial Electronics
Identifiers
URN: urn:nbn:se:ltu:diva-8311DOI: 10.1088/0957-0233/21/1/015701Local ID: 6cff9560-6d64-11de-9f57-000ea68e967bOAI: oai:DiVA.org:ltu-8311DiVA: diva2:981203
Note
Validerad; 2010; Bibliografisk uppgift: Paper ID: 015701; 20090710 (johanc)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved

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Hägglund, FredrikCarlson, Johan E.Andersson, Tobias
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