4.6 Article

Assessment of Gradient-Based Algorithm for Surface Determination in Multi-Material Gap Measurements by X ray Computed Tomography

Journal

MATERIALS
Volume 13, Issue 24, Pages -

Publisher

MDPI
DOI: 10.3390/ma13245650

Keywords

computed tomography; multi-material measurements; gap measurements; surface determination algorithm; gradient-based algorithm

Funding

  1. Gobierno de Aragon [T56_20R]
  2. FEDER 2014-2020 Construyendo Europa desde Aragon
  3. Spanish government - Ministerio de Ciencia, Innovacion y Universidades (MCIU) [RTI2018-097191-BI00]
  4. Agencia Estatal de Investigacion (AEI)
  5. Fondo Europeo de Desarrollo Regional (FEDER)

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X-ray computed tomography is one of the most promising measurement techniques for the dimensional evaluation of industrial components. However, the inherent complexity of this technology also involves important challenges. One of them is to develop surface determination algorithms capable of providing measurement results with better accuracy in any situation-for example, for single and multi-material parts, inner and outer geometries, with and without image artefacts, etc.-and reducing user influence. The surface determination is particularly complex in the case of multi-material parts, especially when they are separated by small air gaps. In previous works, two gradient-based algorithms were presented, that showed less measurement variability throughout the whole part, and reduced the computational cost and operator influence compared to threshold-based algorithms. This work focuses on the evaluation of the performance of these algorithms when used in a scenario so complex that parts of it are made of one or more materials (metal-metal and polymer-metal) with gaps inside. For this purpose, a set of multi-material reference standards is used. The presented gradient-based algorithms show measurement errors comparable to commercial threshold-based algorithms, but with the capability of obtaining accurate measurements in smaller gaps, apart from reducing the user influence on the measurement process.

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