Defect Detection In Fibered Material Using Methods Of Machine Learning

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Date
2019
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Abstract
SILON s.r.o is manufacturer of polyester fibres which get used in wide range of applications, many of them requiring highest quality material. Due to manufacturing processes, some fibres are not drawn properly and stay in the fiber as bundles, or brittle, thick threads. Proposed lab station should automate process of quality check of each batch. It consists of linescan camera scanner and computer with software for detection and analysis of defects.
Keywords
EEICT, polyester fiber, fluorescence, Rhodamine B, scanner, linescan camera, quality check, defect detection, CNN, convolutional neural network, FCN, fully convolutional network
Persistent identifier
http://hdl.handle.net/11012/186685
Document type
Peer reviewed
Document version
xmlui.vut.verze.Publishers's version
Source
Proceedings of the 25st Conference STUDENT EEICT 2019. s. 331-334. ISBN 978-80-214-5735-5
http://www.feec.vutbr.cz/EEICT/
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