The Largest Open Access Portal of Nondestructive Testing (NDT)

The comparison of many 3D volumes to find subtle differences is tedious, time-consuming and error-prone. Previously we presented Dynamic Volume Lines [1], a novel tool for the interactive visual analysis and comparison of ensembles of 3D volumes, which are linearized using Hilbert spacing-filling curve and represented as 1D line plots. In this paper we further demonstrate the usefulness and capabilities of our method by conducting a detailed visual analysis and evaluation of an artificial specimen from simulated 3D X-Ray Computed Tomography (XCT) and a real-world XCT titanium alloy specimen.

This work introduces methods for analyzing the three imaging modalities delivered by Talbot-Lau grating interferometry X-ray computed tomography (TLGI-XCT). The first problem we address is providing a quick way to show a fusion of all three modalities. For this purpose the tri-modal transfer function widget is introduced. The widget controls a mixing function that uses the output of the transfer functions of all three modalities, allowing the user to create one customized fused image. A second problem prevalent in processing TLGI-XCT data is a lack of tools for analyzing the segmentation process of such multimodal data. We address this by providing methods for computing three types of uncertainty: From probabilistic segmentation algorithms, from the voxel neighborhoods as well as from a collection of results. We furthermore introduce a linked views interface to explore this data. The techniques are evaluated on a TLGI-XCT scan of a carbon-fiber reinforced dataset with impact damage. We show that the transfer function widget accelerates and facilitates the exploration of this dataset, while the uncertainty analysis methods give insights into how to tweak and improve segmentation algorithms for more suitable results.

The open source software open_iA is presented, which facilitates non-destructive testing tasks such as feature extraction, quantification and visualization involving industrial computed tomography datasets. open_iA provides a general framework for visualizing and processing volumetric datasets, including a 3D view, axis-aligned slicers, as well as a wide variety of image processing algorithms for pre-processing of the data for the subsequent analysis. Pluggable modules provide tailored analysis tools for specific scenarios. In this work the structure of the tool open_iA itself and a selection of its modules are outlined.

We present a tool which supports CT specialists in exploring the parameter and result space of volume segmentation pipelines. In a preprocessing step, the user samples the parameter space of a number of pipelines to be analysed. Our sampling tool supports arbitrary pipeliness that can be parametrized via the command line. The user can then explore the space of possible results of the sampled pipelines in an interactive visualization tool. This visualization tool highlights the variation resulting from different parametrizations and pipelines, and allows exploring the influence of each parameter. We evaluate our tool on the multimodal segmentation of a carbon-fiber-reinforced polymer (CFRP) specimen with impact damage, scanned with a Talbot-Lau Grating Interferometer Computed Tomography device.

Industrial 3D X-ray computed tomography (3DXCT) is increasingly applied as a technique for metrology applications. In contrast to comventional metrology tools such as coordinate measurement machines (CMMs). 3DXCT only estimates the exact position of the specimen’s surface and is subjected to a specific set of artifact types. These factors result in uncertainty that is present in the data. Previous work by Amirkhanov et. al [2] presented a tool prototype that is taking such uncertainty into account when measuring geometric tolerances such as straightness, circularity, or flatness. In this paper we extend the previous work with two more geometric tolerance types: cylindricity and angularity. We provide methods and tools for visualization, inspection, and analysis of these tolerances. For the cylindricity tolerance we employ neighboring profiles visualization, box-plot overview, and interactive 3D view. We evaluate applicability and usefulness our methods on a new TP03 data set, and present results and new potential use cases.