Titelangaben
Friedrich, Markus ; Gerber, Theresa ; Dumler, Jonas ; Döpper, Frank:
A system for automated tool wear monitoring and classification using computer vision.
In: Procedia CIRP.
Bd. 118
(2023)
.
- S. 425-430.
ISSN 2212-8271
DOI: https://doi.org/10.1016/j.procir.2023.06.073
Abstract
This paper presents an approach for automated monitoring and classification of face milling tool wear using computer vision. A test setup with low-cost equipment for in-machine application is developed and used to generate an image dataset from worn and new tools. Different types of filters and segmentation techniques are applied and compared for image preprocessing. For wear detection, both classification and regression models using convolutional neural networks are evaluated. Best results were obtained with a combined model. This demonstrates that optical wear monitoring is feasible with low-cost equipment. However, potentials for improvement were identified in manual labeling and image quality.
Weitere Angaben
Publikationsform: | Artikel in einer Zeitschrift |
---|---|
Begutachteter Beitrag: | Ja |
Keywords: | Computer Vision; Convolutional Neural Networks; Tool Condition Monitoring; Milling Process |
Institutionen der Universität: | Fakultäten > Fakultät für Ingenieurwissenschaften > Lehrstuhl Umweltgerechte Produktionstechnik > Lehrstuhl Umweltgerechte Produktionstechnik - Univ.-Prof. Dr.-Ing. Frank Döpper |
Titel an der UBT entstanden: | Ja |
Themengebiete aus DDC: | 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften |
Eingestellt am: | 25 Jul 2023 06:05 |
Letzte Änderung: | 25 Jul 2023 13:47 |
URI: | https://eref.uni-bayreuth.de/id/eprint/86198 |