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Algorithm assessment for layup defect segmentation from laser line scan sensor based image data

Meister, Sebastian and Wermes, Mahdieu A. M. and Stüve, Jan and Groves, Roger M. (2020) Algorithm assessment for layup defect segmentation from laser line scan sensor based image data. In: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020 (11379), pp. 139-153. Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020, 27. April - 01. Mai, Anaheim, CA, USA. doi: 10.1117/12.2558434. ISBN 978-151063535-7. ISSN 0277-786X.

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Official URL: https://doi.org/10.1117/12.2558434

Abstract

The Automated Fiber Placement process is established in the aerospace industry for the production of composite components. This technique places several narrow material strips in parallel. Within current industrial Automated Fiber Placement processes the visual inspection takes typically up to 50 % of overall production time. Furthermore, inspection quality highly depends on the inspector. Therefore, automation of visual inspection offers a great improvement potential. To ensure reliable defect detection the segmentation of individual defects must be investigated. For this reason, this paper focusses on an assessment of defect segmentation algorithms. Therefore, 29 structural, statistical and spectral algorithms from related work were assessed, theoretically, using the 12 most relevant criteria as assessed from literature and process requirements. Then, seven most auspicious algorithms were analysed in detail. For reasons of determinism, Neural Network approaches are not part of this paper. Manually labelled prepreg defect images from a laser line scan sensor were used for tests. The test samples contain five defect types with 50 samples of each. Additionally, layups without defects were analysed. It was concluded that Adaptive Thresholding works best for global defect segmentation. The Cell Wise Standard Deviation Thresholding performs also quite well, but is very sensitive to grid size. Feasible algorithms perform reliable defect segmentation for layed up material.

Item URL in elib:https://elib.dlr.de/135181/
Document Type:Conference or Workshop Item (Speech, Other)
Title:Algorithm assessment for layup defect segmentation from laser line scan sensor based image data
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Meister, SebastianSebastian.Meister (at) dlr.dehttps://orcid.org/0000-0002-8193-1143
Wermes, Mahdieu A. M.Mahdieu.Wermes (at) dlr.deUNSPECIFIED
Stüve, JanJan.Stueve (at) dlr.dehttps://orcid.org/0000-0003-1483-2476
Groves, Roger M.R.M.Groves (at) tudelft.nlhttps://orcid.org/0000-0001-9169-9256
Date:April 2020
Journal or Publication Title:Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
DOI :10.1117/12.2558434
Page Range:pp. 139-153
Editors:
EditorsEmailEditor's ORCID iD
Huang, HaiyingSPIEUNSPECIFIED
ISSN:0277-786X
ISBN:978-151063535-7
Status:Published
Keywords:Image Segmentation, Automated Fiber Placement, Inline Inspection, Adaptive Thresholding, Computer Vision, Composite Manufacturing, Laser Line Scan Sensor
Event Title:Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020
Event Location:Anaheim, CA, USA
Event Type:international Conference
Event Dates:27. April - 01. Mai
Organizer:SPIE
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:fixed-wing aircraft
DLR - Research area:Aeronautics
DLR - Program:L AR - Aircraft Research
DLR - Research theme (Project):L - Structures and Materials (old)
Location: Stade
Institutes and Institutions:Institute of Composite Structures and Adaptive Systems > Composite Process Technology
Deposited By: Meister, Sebastian
Deposited On:12 Oct 2020 13:45
Last Modified:02 Jul 2021 09:51

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