Daniel O�Connor
Model-based defect detection on structured surfaces having optically unresolved features
O�Connor, Daniel; Henning, Andrew J.; Sherlock, Ben; Leach, Richard; Coupland, Jeremy; Giusca, Claudiu L.
Authors
Andrew J. Henning
Ben Sherlock
RICHARD LEACH RICHARD.LEACH@NOTTINGHAM.AC.UK
Chair in Metrology
Jeremy Coupland
Claudiu L. Giusca
Abstract
In this paper, we demonstrate, both numerically and experimentally, a method for the detection of defects on structured surfaces having optically unresolved features. The method makes use of synthetic reference data generated by an observational model that is able to simulate the response of the selected optical inspection system to the ideal structure, thereby providing an ideal measure of deviation from nominal geometry. The method addresses the high dynamic range challenge faced in highly parallel manufacturing by enabling the use of low resolution, wide field of view optical systems for defect detection on surfaces containing small features over large regions.
Journal Article Type | Article |
---|---|
Acceptance Date | Sep 21, 2015 |
Publication Date | Oct 13, 2015 |
Deposit Date | Sep 20, 2018 |
Print ISSN | 1464-4258 |
Publisher | IOP Publishing |
Peer Reviewed | Peer Reviewed |
Volume | 54 |
Issue | 30 |
Pages | 8872-8877 |
DOI | https://doi.org/10.1364/AO.54.008872 |
Public URL | https://nottingham-repository.worktribe.com/output/1105884 |
Publisher URL | https://www.osapublishing.org/ao/abstract.cfm?uri=ao-54-30-8872 |
Additional Information | eStaffProfile Description: , eStaffProfile Brief Description of Type: |
You might also like
Surface texture measurement for additive manufacturing
(2015)
Journal Article
Study of weighted fusion methods for the measurement of surface geometry
(2016)
Journal Article
Metrology for additive manufacturing
(2016)
Journal Article
Phase and fringe order determination in wavelength scanning interferometry
(2016)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search