Digital image processing algorithm for industrial on-site roughness evaluation in Ti-alloy machining

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Digital image processing algorithm for industrial on-site roughness evaluation in Ti-alloy machining

RIBEIRO CARVALHO Sílvia Daniela, ARAUJO Anna Carla, HOROVISTIZ Ana, DAVIM João Paulo

Abstract. The surface texture is normally observed after the machining process, but nowadays it is important to use on-site analysis to improve the process automatically via smart processing. This study introduces a contactless roughness inspection method employing digital image processing on Ti6Al4V samples in turning using three different feed. Texture analysis with grey-level co-occurrence matrix (GLCM) extracted features that were correlated with the arithmetic average roughness (Ra), leading to the establishment of predictive models. The study encompassed diverse image testing, incorporating variations in resolution and brightness distributions. It was found that the pixel pair spacing (PPS) in GLCM analysis was influenced by the image resolution and feed rate. The predictive models developed with high-quality images, i.e., higher resolution and better brightness distribution, yielded similar results to those created using lower-quality images.

Keywords
Machining, Surface Quality, Texture, Digital Image Processing, Ti6Al4V

Published online 4/24/2024, 8 pages
Copyright © 2024 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: RIBEIRO CARVALHO Sílvia Daniela, ARAUJO Anna Carla, HOROVISTIZ Ana, DAVIM João Paulo, Digital image processing algorithm for industrial on-site roughness evaluation in Ti-alloy machining, Materials Research Proceedings, Vol. 41, pp 1982-1989, 2024

DOI: https://doi.org/10.21741/9781644903131-219

The article was published as article 219 of the book Material Forming

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

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