visualization for non-destructive testing

Visualization for

Non-Destructive Testing

Eduard Gröller

Institute of Computer Graphics and Algorithms

Vienna University of Technology

Artem Amirkhanov et al.

Industrial 3D X-ray Computed Tomography (3DXCT)

Projections 3D VolumeReconstruction


Industrial 3D X-ray Computed Tomography (3DXCT)

3DXCT Advantages

Powerful technique for generating a digital 3D

volumetric dataset of a specimen from 2D

projections

Wide range of materials

Full characterization of the specimen’s

exterior and interior structures without

destroying or disassembling it

Used for non-destructive testing and quality

control


Fuzzy CT

Metrology

Amirkhanov, A., Heinzl, Ch., Kuhn, Ch., Kastner, J., Gröller,

E.: Fuzzy CT Metrology: Dimensional Measurements on

Uncertain Data. In Proceedings of the 29th Spring

conference on Computer Graphics (SCCG 2013), 2013.

Geometric Tolerancing

Features of interest: measurement plan

Properties of features are evaluated

Common tolerances

Straightness

Circularity

Flatness


Industrial 3DXCT Metrology


Measurement

Plan

Measurements

Coordinate Measurement Machine

Measurement

Plan

Measurements

Software

Actual

Specimen

Extracted

Surface Model

3DXCTConventional

Overview


Measurement

Plan

Measurements

Extracted

Surface Model

Material

Interface

Uncertainty

Reconstructed

3D Volume

Statistical

Analysis

Overview


Measurements Material

Interface

Uncertainty

Reference

Shapes3D Labels Measurement plots

Unce

rta

inty

Vis

ualiz

ation

Levels-of-DetailOverview Details

Video Demonstration

Artem Amirkhanov 10

Visualization

of Carbon Fiber

Reinforced Polymers

Reh, A., Plank, B., Kastner, J., Gröller, E., Heinzl, C.: Porosity Maps –

Interactive Exploration and Visual Analysis of Porosity in Carbon Fiber

Reinforced Polymers. Computer Graphics Forum, 31(3pt3):1185–1194, 2012.

Reh, A., Gusenbauer, C., Kastner, J., Gröller, E., Heinzl, C.: MObjects—A Novel

Method for the Visualization and Interactive Exploration of Defects in

Industrial XCT Data. IEEE Transactions on Visualization and Computer

Graphics, 19(12): 2906–2915, 2013.

T118_NII-Shonan-Meeting_Mar2014_2.pptx

T118_NII-Shonan-Meeting_Mar2014_2.pptx

Carbon Fiber Reinforced Polymers (CFRP)

Fiber bundles with a twill-weave pattern

Carbon Fiber Reinforced Polymers (CFRP)

Fiber bundles with a twill-weave pattern

Epoxy resin

Epoxy resin(matrix)

Fiber bundlesin x direction

Fiber bundlesin z direction

Pores in the matrix

Pores inside thefiber bundles X

Y

Porosity Determination Workflow

UltrasonicTesting

ActiveThermography

Qu

anti

tati

ve P

oro

sity

[%]

CFRP Components

Ultrasonic CalibrationCurve

Heat Conduction Model

Mean Object (MObject)

Many pores(shape variation not visible)

MObject visualization(mean shape is visible)

Porosity Determination Workflow

Qu

anti

tati

ve P

oro

sity

[%]

UltrasonicTesting

ActiveThermography

Ultrasonic CalibrationCurve

Heat Conduction Model

CFRP Components

X-Ray ComputedTomography

MObjectVisualization

2

3

4

Data Acquisition

XCT Measurement

Beam HardeningCorrection

Data Mapping

1

3

4

Pre-processing and Pore Properties

AnisotropicDiffusion

Otsu Thresholding

ConnectedComponents

Filter

Property Calculation

1 2

• Volume• Dimension X• Dimension Y• Dimension Z• Shape factor• Directional shape factors

MObject Calculation

Individual Objects

MObject

1 2

3

4

Homogeneity Visualization

Local MObjectsVisualization

Color-coded Homogeneity Visualization of the Average Cell Property Deviation

Results: Homogeneity Visualization

0.02

-0.02

0

Deviation from avg. pore volume [mm³]

Results: Homogeneity Visualization

0.17

-0.17

0

Deviation from avg. pore dimension X [mm]

1 2

3

4

MObject Set Visualization and Exploration

Radial MObjectSet Visualization

Parallel MObjectSet Visualization

Scaling throughVisual Linking

RepresentativeMObjects

MObject Set Calculation

Parallel MObject Set Visualization

Global MObject

3 shapefactor classes

Separation of the long and thin shaped micro pores in

x and z direction

Porosity Determination

Visualization Tasks

Task 1: Quantitative

porosity

Task 2:Porosity overview

Task 3:Local pore properties

Task 4:Best viewpoint

Overview

Visualization Pipeline

Pre-ComputationVisual Analysis of

Porosity

Visual Analysis ofPorosity

Data Acquisition

Porosity Maps Parallel Coordinates

View

Interactive Exploration

Best Viewpoint Widget

Visual Analasys of Porosity

Porosity Maps

Porosity Map calculation Porosity Map

high

low

Task 2: Porosity overview

Visual Analysis of Porosity

3 Stages of Interactive Exploration and Visualization

Porosity Overview Region of Interest Pore ClassificationPorosity Overview

Porosity Visualization

Porosity Maps




Porosity Overview Region of Interest Pore ClassificationRegion of Interest


Porosity Maps Interaction




Porosity Overview Region of Interest Pore ClassificationPore Classification


Parallel Coordinates Interaction

Task 3: Local pore properties

Volume – Dimension X – Dimension Y – Dimension Z – Shape Factor



Good viewpoint Bad viewpoints

Rate the quality of viewpoints Calculation by user-defined parameters

Task 4: Best viewpoint



Parameterized Sphere

Quality Value Calculation

Viewing Sphere

Viewpoint Viewing Sphere(Cylindrical sticks)

Viewing Sphere(Colored sphere)

Task 4: Best viewpoint

Pipeline for the Interactive Exploration and Visual Analysis of Porosity in Carbon Fiber Reinfored

Polymers

Summary

Vis. For Non-Destructive Testing: Outlook

Complex, novel and challenging data

Temporal changes of workpieces

Comparative visualization

Uncertainty visualization

Parameter space analysis

Ensemble visualization

Aggregated visualization

…

Eduard Gröller

Thank You for Your Attention

Acknowledgments

Artem Amirkhanov

Christian Gusenbauer

Christoph Heinzl

Johann Kastner

Christoph Kuhn

Bernhard Plank

Andreas Reh

…

Questions ?

Comments?

Visualization for Non-Destructive Testing

Abstract: New materials like carbon fiber reinforced polymers (CFRP) require novel non-destructive testing approaches. 3D X-Ray Computed Tomography (XCT) is a scanning modality for the analysis and visualization of features and defects in industrial work pieces. Several application scenarios are discussed in this respect:

Porosity maps allow the characterization of porosity in carbon fiber reinforced polymers. Besides quantitative porosity determination and the calculation of local pore properties, i.e., volume, surface, dimensions and shape factors, we employ a drill-down approach to explore pores in a CFRP specimen.

MObjects are an aggregated approach for the visualization and interactive exploration of defects in industrial XCT. Mean objects (MObject) and mean object sets (MObjectSets) are visualized in a radial and parallel arrangement. Non-destructive testing practitioners use representative MObjects to improve ultrasonic calibration curves and as input for heat conduction simulations in active thermography.

Fuzzy CT Metrology can be used for dimensional measurement on uncertain data. Using 3D XCT the location of the specimen surface is estimated. Our technique provides the domain experts with uncertainty visualizations, which extend the XCT metrology workflow on different levels. The developed techniques are integrated into a tool utilizing linked views, smart 3D tolerance tagging and plotting functionalities.

Due to the rapid development of scanning devices, material sciences and non-destructive testing constitute a challenging application domain for innovative visualization research.

Eduard Gröller

References

Eduard Gröller

Amirkhanov, A., Heinzl, Ch., Kuhn, Ch., Kastner, J., Gröller, E.: Fuzzy CT Metrology: Dimensional Measurements on Uncertain Data. In Proceedings of the 29th Spring conference on Computer Graphics (SCCG 2013), 2013.

Reh, A., Plank, B., Kastner, J., Gröller, E., Heinzl, C.: Porosity Maps – Interactive Exploration and Visual Analysis of Porosity in Carbon Fiber Reinforced Polymers. Computer Graphics Forum, 31(3pt3):1185–1194, 2012. doi: 10.1111/j.1467-8659.2012.03111.x

Reh, A., Gusenbauer, C., Kastner, J., Gröller, E., Heinzl, C.: MObjects—A Novel Method for the Visualization and Interactive Exploration of Defects in Industrial XCT Data. IEEE Transactions on Visualization and Computer Graphics, 19(12): 2906–2915, 2013. doi: 10.1109/TVCG.2013.177

Weissenböck, J., Amirkhanov, A., Li, W., Reh, A., Amirkahanov, A., Gröller, E., Kastner, J., Heinzl, Ch.: FiberScout: An Interactive Tool for Exploring and Analyzing Fiber Reinforced Polymers. 2014 IEEE Pacific Visualization Symposium, doi: 10.1109/PacificVis.2014.52

Heinzl Ch.: Analysis and Visualization of Industrial CT Data, PhD thesis, Vienna University of Technology, 2009 (http://www.cg.tuwien.ac.at/research/publications/2009/heinzl-2008-thesis/)

Amirkhanov, A.: Visualization of Industrial 3DXCT Data, PhD thesis, Vienna University of Technology, 2012

visualization for non-destructive testing

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