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Optimization of Surface Preparation and Painting Processes for Railway and Automotive Steel Sheets

Autor(en): (Central Campus Győr, Széchenyi István University, H-9026 Győr, Hungary)
(Central Campus Győr, Széchenyi István University, H-9026 Győr, Hungary)
(Department of Transport Infrastructure, Ukrainian State University of Science and Technologies, UA-49005 Dnipro, Ukraine)
ORCID (Central Campus Győr, Széchenyi István University, H-9026 Győr, Hungary)
ORCID (Department of Planning and Design of Railway Infrastructure, Technical University Dresden, D-01069 Dresden, Germany)
ORCID (Central Campus Győr, Széchenyi István University, H-9026 Győr, Hungary)
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Infrastructures, , n. 2, v. 8
Seite(n): 28
DOI: 10.3390/infrastructures8020028
Abstrakt:

The article deals with DIC (Digital Image Correlation) tests on steel plates used in the automotive and railway industries, as well as in the construction industry. The most critical part of DIC tests is the quality of proper surface preparation, painting, and random patterns. The paint mediates the deformation of the optical systems, and its quality is paramount. The authors’ goal in this research is to determine the optimal dye–cleaning–drying time parameters for DIC studies. Commercially available surface preparation and cleaning agents were tested alongside commercially available spray paints. Standard and specific qualification procedures were applied for the measurements. Once the appropriate parameters were determined, the results were validated and qualified by GOM ARAMIS tests. Based on the results, DIC measurements can be performed with higher accuracy and safety in laboratorial and industrial conditions, compared to the traditional deformation measurements executed by dial gauges or linear variable differential transformers.

Copyright: © 2023 the Authors. Licensee MDPI, Basel, Switzerland.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10722743
  • Veröffentlicht am:
    22.04.2023
  • Geändert am:
    10.05.2023
 
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