TU Darmstadt / ULB / TUprints

A computer vision system for saw blade condition monitoring

Jourdan, Nicolas ; Biegel, Tobias ; Knauthe, Volker ; Buelow, Max von ; Guthe, Stefan ; Metternich, Joachim (2022)
A computer vision system for saw blade condition monitoring.
In: Procedia CIRP, 104
doi: 10.26083/tuprints-00021265
Article, Secondary publication, Publisher's Version

[img] Text
1-s2.0-S2212827121010842-main.pdf
Copyright Information: CC BY-NC-ND 4.0 International - Creative Commons, Attribution NonCommercial, NoDerivs.
Download (895kB)
Item Type: Article
Type of entry: Secondary publication
Title: A computer vision system for saw blade condition monitoring
Language: English
Date: 2022
Place of Publication: Darmstadt
Publisher: Elsevier
Journal or Publication Title: Procedia CIRP
Volume of the journal: 104
DOI: 10.26083/tuprints-00021265
Corresponding Links:
Origin: Secondary publication
Abstract:

Tool condition monitoring is a key component of predictive maintenance in smart manufacturing. Predicting excessive tool wear in machining processes becomes increasingly difficult if different materials need to be processed. We propose a novel computer vision-based system for saw blade condition monitoring that is independent of the processed materials and combines deep learning with classic computer vision. Our approach allows for accurate condition monitoring of blade wear which can further be used for predictive maintenance. Additionally, the system can classify different defect types such as missing blade teeth, thus preventing the production of scrap parts.
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-212658
Additional Information:

Erscheint auch in: CIRP CMS 2021 - 54th CIRP Conference on Manufacturing Systems, 2021
Classification DDC: 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
600 Technik, Medizin, angewandte Wissenschaften > 670 Industrielle und handwerkliche Fertigung
Divisions: 20 Department of Computer Science > Interactive Graphics Systems
Date Deposited: 06 May 2022 10:25
Last Modified: 03 Mar 2023 10:10
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/21265
PPN: 505422700
Export:
Actions (login required)
View Item View Item
OAI 2.0 -Basis-URL: https://tuprints.ulb.tu-darmstadt.de/cgi /oai2 TUprints verwendet EPrints 3 .
Drucken | Impressum | Datenschutzerklärung