Original scientific paper

https://doi.org/10.17559/TV-20191212122953

Investigation of Correlation between Image Features of Machined Surface and Surface Roughness

Ilija Svalina orcid.org/0000-0003-2375-7367 ; Mechanical Engineering Faculty in Slavonski Brod, Josip Juraj Strossmayer University of Osijek, Trg I. Brlić Mažuranić 2, HR-35000 Slavonski Brod, Croatia
Sara Havrlišan* orcid.org/0000-0002-7650-0269 ; Mechanical Engineering Faculty in Slavonski Brod, Josip Juraj Strossmayer University of Osijek, Trg I. Brlić Mažuranić 2, HR-35000 Slavonski Brod, Croatia
Katica Šimunović orcid.org/0000-0001-5748-7110 ; Mechanical Engineering Faculty in Slavonski Brod, Josip Juraj Strossmayer University of Osijek, Trg I. Brlić Mažuranić 2, HR-35000 Slavonski Brod, Croatia
Tomislav Šarić orcid.org/0000-0002-6339-7936 ; Mechanical Engineering Faculty in Slavonski Brod, Josip Juraj Strossmayer University of Osijek, Trg I. Brlić Mažuranić 2, HR-35000 Slavonski Brod, Croatia

Abstract

Alternative approach to surface roughness evaluation is mostly based on the analysis of digital images of machined surfaces i.e. on extracting various features from the matrix mathematically representing a digital image. This paper analyses correlation between 23 different digital image features and the surface roughness for two different materials: aluminium and stainless steel. Machined surfaces for both materials were acquired by face milling. Factorial design 6 × 5 × 2 with two replicates was conducted for each material with cutting parameters being varied on various numbers of levels. Based on the correlation coefficients the results showed that the best ranked features regardless of the machined material were the features based on statistic measures.

Keywords

correlation; digital image features of machined surface; face milling; image features ranking; surface roughness

Hrčak ID:

234156

URI

https://hrcak.srce.hr/234156

Publication date:

15.2.2020.

Visits: 1.854 *