Machine Vision for As-Built Modeling of Complex Draped Composite Structures.

as-built composites digital-twin draping fibers finite elements machine vision textiles

Journal

Materials (Basel, Switzerland)
ISSN: 1996-1944
Titre abrégé: Materials (Basel)
Pays: Switzerland
ID NLM: 101555929

Informations de publication

Date de publication:
02 Feb 2021
Historique:
received: 31 12 2020
revised: 21 01 2021
accepted: 27 01 2021
entrez: 5 2 2021
pubmed: 6 2 2021
medline: 6 2 2021
Statut: epublish

Résumé

The transition in the use of fiber composite structures from special applications to application in the mass market is accompanied by high demands in quality assurance. The consequential costs of unclear process design, unknown fiber orientations, and uncertainty regarding the effects of any fiber angle deviations can lead to market considerations (higher costs/time for development) in mass production that advise against the use of fiber composites, despite their superiority compared with conservative materials. Active monitoring of the deposited reinforcement layers and an evaluation of the real fiber orientation can form the basis of a robust industrial use of fiber composites by a first-time right production that is able to reduce the process variability. This paper describes the application of an image analysis system to provide both geometric topology and local reinforcement fiber orientation feedback to a finite-element (FE) model. The application during an industrial composite part production is described, and the possibilities of using it for the improvement of the lightweight character, the reduction of rejects, and the realization of a quality management system are shown. The determined component data are made directly available for use in numerical simulations and, thus, they serve as a non-destructive evaluation of the components under real conditions in which all production-dependent influences that affect the fiber orientation are incorporated.

Identifiants

pubmed: 33540727
pii: ma14030682
doi: 10.3390/ma14030682
pmc: PMC7867240
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Innosuisse - Schweizerische Agentur für Innovationsförderung
ID : 35197.1 IP-ENG

Références

Sensors (Basel). 2018 Jan 19;18(1):
pubmed: 29351240

Auteurs

Oliver Döbrich (O)

Institute of Polymer Engineering, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Klosterzelgstrasse 2, 5210 Windisch, Switzerland.

Ayoh Anderegg (A)

Institute of Polymer Engineering, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Klosterzelgstrasse 2, 5210 Windisch, Switzerland.

Nicolas Gort (N)

Institute of Polymer Engineering, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Klosterzelgstrasse 2, 5210 Windisch, Switzerland.

Christian Brauner (C)

Institute of Polymer Engineering, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Klosterzelgstrasse 2, 5210 Windisch, Switzerland.

Classifications MeSH