<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The focus of the present research is to investigate possibilities of volumetric defect detection in thin film coatings on glass substrates by means of high definition imaging with no complex optical systems, such as lenses, and to determine development and construction feasibility of a defectoscope employing the investigated methods. Numerical simulations were used to test the proposed methods. Three theoretical models providing various degrees of accuracy and feasibility were studied.</p></abstract>

The focus of the present research is to investigate possibilities of volumetric defect detection in thin film coatings on glass substrates by means of high definition imaging with no complex optical systems, such as lenses, and to determine development and construction feasibility of a defectoscope employing the investigated methods. Numerical simulations were used to test the proposed methods. Three theoretical models providing various degrees of accuracy and feasibility were studied.

Development of Mathematical Models for Detecting Micron Scale Volumetric Defects in Thin Film Coatings

Ventspils University College, 101 Inženieru Str., Ventspils, LV-3601, LATVIA

Latvian Journal of Physics and Technical Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The focus of the present research is to investigate possibilities of volumetric defect detection in thin film coatings on glass substrates by means of high...

Development of Mathematical Models for Detecting Micron Scale Volumetric Defects in Thin Film Coatings

Pubblicato online: 20 mag 2016

Pagine: 38 - 47

DOI: https://doi.org/10.1515/lpts-2016-0012

Parole chiave
deconvolution, compressive sampling, ℓ minimization, numeric simulation, thin film coatings

© 2016 G. Gaigals et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Development of Mathematical Models for Detecting Micron Scale Volumetric Defects in Thin Film Coatings

Pubblicato online: 20 mag 2016

Pagine: 38 - 47

DOI: https://doi.org/10.1515/lpts-2016-0012

Parole chiavedeconvolution, compressive sampling, ℓ minimization, numeric simulation, thin film coatings

© 2016 G. Gaigals et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
deconvolution, compressive sampling, ℓ minimization, numeric simulation, thin film coatings