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

Sebastian Meister, Mahdieu Amin Mahdieu Wermes, Jan Stüve, Roger M. Groves

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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.

Original languageEnglish
Title of host publicationSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020
EditorsHaiying Huang, Hoon Sohn, Daniele Zonta
PublisherSPIE
Volume11379
ISBN (Electronic)9781510635357
DOIs
Publication statusPublished - 2020
EventSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020 - None, United States
Duration: 27 Apr 20208 May 2020

Conference

ConferenceSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020
CountryUnited States
CityNone
Period27/04/208/05/20

Keywords

  • Adaptive Thresholding
  • Automated Fiber Placement
  • Composite Manufacturing
  • Computer Vision
  • Image Segmentation
  • Inline Inspection
  • Laser Line Scan Sensor

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  • Cite this

    Meister, S., Wermes, M. A. M., Stüve, J., & Groves, R. M. (2020). Algorithm assessment for layup defect segmentation from laser line scan sensor based image data. In H. Huang, H. Sohn, & D. Zonta (Eds.), Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2020 (Vol. 11379). [1137918] SPIE. https://doi.org/10.1117/12.2558434