Andreas Reh, Christian Gusenbauer, Johann Kastner, Eduard GröllerORCID iD, Christoph Heinzl
MObjects - A Novel Method for the Visualization and Interactive Exploration of Defects in Industrial XCT Data
IEEE Transactions on Visualization and Computer Graphics (Proceedings of IEEE Scientific Visualization 2013), 19(12):2906-2915, December 2013. [ paper] [ video] [evaluation questionnaire]

Information

  • Publication Type: Journal Paper with Conference Talk
  • Workgroup(s)/Project(s):
  • Date: December 2013
  • Journal: IEEE Transactions on Visualization and Computer Graphics (Proceedings of IEEE Scientific Visualization 2013)
  • Volume: 19
  • Number: 12
  • Location: Atlanta, Georgia, USA
  • Lecturer: Andreas Reh
  • Event: IEEE Scientific Visualization 2013
  • Conference date: 13. October 2013 – 18. October 2013
  • Pages: 2906 – 2915
  • Keywords: porosity, carbon fiber reinforced polymers, parameter space analysis, MObjects, 3D X-ray computed tomography

Abstract

This paper describes an advanced visualization method for the analysis of defects in industrial 3D X-Ray Computed Tomography (XCT) data. We present a novel way to explore a high number of individual objects in a dataset, e.g., pores, inclusions, particles, fibers, and cracks demonstrated on the special application area of pore extraction in carbon fiber reinforced polymers (CFRP). After calculating the individual object properties volume, dimensions and shape factors, all objects are clustered into a mean object (MObject). The resulting MObject parameter space can be explored interactively. To do so, we introduce the visualization of mean object sets (MObject Sets) in a radial and a parallel arrangement. Each MObject may be split up into sub-classes by selecting a specific property, e.g., volume or shape factor, and the desired number of classes. Applying this interactive selection iteratively leads to the intended classifications and visualizations of MObjects along the selected analysis path. Hereby the given different scaling factors of the MObjects down the analysis path are visualized through a visual linking approach. Furthermore the representative MObjects are exported as volumetric datasets to serve as input for successive calculations and simulations. In the field of porosity determination in CFRP non-destructive testing practitioners use representative MObjects to improve ultrasonic calibration curves. Representative pores also serve as input for heat conduction simulations in active thermography. For a fast overview of the pore properties in a dataset we propose a local MObjects visualization in combination with a color-coded homogeneity visualization of cells. The advantages of our novel approach are demonstrated using real world CFRP specimens. The results were evaluated through a questionnaire in order to determine the practicality of the MObjects visualization as a supportive tool for domain specialists.

Additional Files and Images

Additional images and videos

Additional files

Weblinks

BibTeX

@article{reh-2013,
  title =      "MObjects - A Novel Method for the Visualization and
               Interactive Exploration of Defects in Industrial XCT Data",
  author =     "Andreas Reh and Christian Gusenbauer and Johann Kastner and
               Eduard Gr\"{o}ller and Christoph Heinzl",
  year =       "2013",
  abstract =   "This paper describes an advanced visualization method for
               the analysis of defects in industrial 3D X-Ray Computed
               Tomography (XCT) data. We present a novel way to explore a
               high number of individual objects in a dataset, e.g., pores,
               inclusions, particles, fibers, and cracks demonstrated on
               the special application area of pore extraction in carbon
               fiber reinforced polymers (CFRP). After calculating the
               individual object properties volume, dimensions and shape
               factors, all objects are clustered into a mean object
               (MObject). The resulting MObject parameter space can be
               explored interactively. To do so, we introduce the
               visualization of mean object sets (MObject Sets) in a radial
               and a parallel arrangement. Each MObject may be split up
               into sub-classes by selecting a specific property, e.g.,
               volume or shape factor, and the desired number of classes.
               Applying this interactive selection iteratively leads to the
               intended classifications and visualizations of MObjects
               along the selected analysis path. Hereby the given different
               scaling factors of the MObjects down the analysis path are
               visualized through a visual linking approach. Furthermore
               the representative MObjects are exported as volumetric
               datasets to serve as input for successive calculations and
               simulations. In the field of porosity determination in CFRP
               non-destructive testing practitioners use representative
               MObjects to improve ultrasonic calibration curves.
               Representative pores also serve as input for heat conduction
               simulations in active thermography. For a fast overview of
               the pore properties in a dataset we propose a local MObjects
               visualization in combination with a color-coded homogeneity
               visualization of cells. The advantages of our novel approach
               are demonstrated using real world CFRP specimens. The
               results were evaluated through a questionnaire in order to
               determine the practicality of the MObjects visualization as
               a supportive tool for domain specialists.",
  month =      dec,
  journal =    "IEEE Transactions on Visualization and Computer Graphics
               (Proceedings of IEEE Scientific Visualization 2013)",
  volume =     "19",
  number =     "12",
  pages =      "2906--2915",
  keywords =   "porosity, carbon fiber reinforced polymers, parameter space
               analysis, MObjects, 3D X-ray computed tomography",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2013/reh-2013/",
}