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Proceedings Paper

Effective and efficient optics inspection approach using machine learning algorithms
Author(s): Ghaleb M. Abdulla; Laura Mascio Kegelmeyer; Zhi M. Liao; Wren Carr
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Paper Abstract

The Final Optics Damage Inspection (FODI) system automatically acquires and utilizes the Optics Inspection (OI) system to analyze images of the final optics at the National Ignition Facility (NIF). During each inspection cycle up to 1000 images acquired by FODI are examined by OI to identify and track damage sites on the optics. The process of tracking growing damage sites on the surface of an optic can be made more effective by identifying and removing signals associated with debris or reflections. The manual process to filter these false sites is daunting and time consuming. In this paper we discuss the use of machine learning tools and data mining techniques to help with this task. We describe the process to prepare a data set that can be used for training and identifying hardware reflections in the image data. In order to collect training data, the images are first automatically acquired and analyzed with existing software and then relevant features such as spatial, physical and luminosity measures are extracted for each site. A subset of these sites is "truthed" or manually assigned a class to create training data. A supervised classification algorithm is used to test if the features can predict the class membership of new sites. A suite of self-configuring machine learning tools called "Avatar Tools" is applied to classify all sites. To verify, we used 10-fold cross correlation and found the accuracy was above 99%. This substantially reduces the number of false alarms that would otherwise be sent for more extensive investigation.

Paper Details

Date Published: 2 December 2010
PDF: 8 pages
Proc. SPIE 7842, Laser-Induced Damage in Optical Materials: 2010, 78421D (2 December 2010); doi: 10.1117/12.867648
Show Author Affiliations
Ghaleb M. Abdulla, Lawrence Livermore National Lab. (United States)
Laura Mascio Kegelmeyer, Lawrence Livermore National Lab. (United States)
Zhi M. Liao, Lawrence Livermore National Lab. (United States)
Wren Carr, Lawrence Livermore National Lab. (United States)

Published in SPIE Proceedings Vol. 7842:
Laser-Induced Damage in Optical Materials: 2010
Gregory J. Exarhos; Vitaly E. Gruzdev; Joseph A. Menapace; Detlev Ristau; M. J. Soileau, Editor(s)

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