Comparison of surface extraction techniques performance in computed tomography for 3D complex micro-geometry dimensional measurements

Torralba, M. ; Jiménez, R. ; Yagüe-Fabra, J.A. (Universidad de Zaragoza) ; Ontiveros, S. ; Tosello, G.

Resumen: The number of industrial applications of computed tomography (CT) for dimensional metrology in 100–103 mm range has been continuously increasing, especially in the last years. Due to its specific characteristics, CT has the potential to be employed as a viable solution for measuring 3D complex micro-geometries as well (i.e., in the sub-mm dimensional range). However, there are different factors that may influence the CT process performance, being one of them the surface extraction technique used. In this paper, two different extraction techniques are applied to measure a complex miniaturized dental file by CT in order to analyze its contribution to the final measurement uncertainty in complex geometries at the mm to sub-mm scales. The first method is based on a similarity analysis: the threshold determination; while the second one is based on a gradient or discontinuity analysis: the 3D Canny algorithm. This algorithm has proven to provide accurate results in parts with simple geometries, but its suitability for 3D complex geometries has not been proven so far. To verify the measurement results and compare both techniques, reference measurements are performed on an optical coordinate measuring machine (OCMM). The systematic errors and uncertainty results obtained show that the 3D Canny adapted method slightly lower systematic deviations and a more robust edge definition than the local threshold method for 3D complex micro-geometry dimensional measurements.

Idioma: Inglés

DOI: 10.1007/s00170-018-1950-9

Año: 2018

Publicado en: INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 97, 1-4 (2018), 441-453
ISSN: 0268-3768

Factor impacto JCR: 2.496 (2018)

Categ. JCR: ENGINEERING, MANUFACTURING rank: 23 / 49 = 0.469 (2018) - Q2 - T2
Categ. JCR: AUTOMATION & CONTROL SYSTEMS rank: 29 / 62 = 0.468 (2018) - Q2 - T2

Factor impacto SCIMAGO: 0.987 - Computer Science Applications (Q1) - Control and Systems Engineering (Q1) - Software (Q1) - Mechanical Engineering (Q1) - Industrial and Manufacturing Engineering (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MINECO/DPI2015-69403-C3-1-R
Financiación: info:eu-repo/grantAgreement/ES/UZ/CUD2016-TEC-09

Tipo y forma: Article (PostPrint)

Área (Departamento): Área Ing. Procesos Fabricación (Dpto. Ingeniería Diseño Fabri.)