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Study of Flow Behavior of Granular Material Inside Cylindrical Silo Using Ultrafast X-Ray Imaging Technique

Waktola S., Bieberle A., Barthel F., Bieberle M., Hampel U., Grudzień K., Babout L.

Image Processing & Communications

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2017

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Vol. 22, no. 2

49--56

EN

This paper presents an application of an ultrafast electron beam X-ray CT scanner for investigating the gravitational flow behavior of granulates through cylindrical silo model. The CT scanner allows obtaining crosssectional images of the granular material distribution with a spatial resolution of approximately 1 mm and a time resolution of 2 kHz. In order to conduct a deep analysis of the granular flow concentration changes, two image processing algorithm steps were applied. The first step deals with preprocessing and re-centering stacks of raw images. The second step divides the preprocessed image into several concentric rings and calculates the mean value to study radial concentration changes. Independent analysis of granular concentration in each ring provides useful knowledge to study the silo discharging during mass flow and funnel flow.

2

3D Reconstruction of Funnel Flow Boundary Using Automatic Point Set Extraction

Waktola S., Grudzien K., Babout L.

Image Processing & Communications

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2015

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Vol. 20, no. 3

35--43

EN

The paper presents an automatic point set extraction method for reconstructing 3D tomography images of funnel flow boundary. The method clearly shows the boundary between the funnel flow and stagnant zone during silo discharging process. After adjusting the contrast of the original X-ray CT image and applying filter function, the intensity profile of the image shows a high jump corresponding to the local flow boundary position at a specific height of the silo model. By extracting and connecting those jump points gave us a boundary line of the funnel flow from the stagnant. The outcome of segmented image opens a door for analysing further about funnel flow in 3D images.

3

3D Segmentation of Funnel Flow Boundary During Silo Emptying

Waktola S., Babout L., Grudzien K.

Image Processing & Communications

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2014

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Vol. 19, no. 2-3

141--149

EN

The paper presents an automatic method for segmenting 3D tomography images of a funnel flow area, during silo emptying process. For generating 3D images the silo model was scanned using X-ray Computed Tomography (CT) system. The method has been applied for a chosen single slice from 3D image. The image segmentation is based on the variance of pixels calculation in defined interrogation window (or kernel). The analysis of Signalto- Noise-Ratio (SNR) of the given image allows to improve the contrast in the image and facilitate the detection the boundary between funnel area and stagnant zone. The obtained results of image segmentation show a high potential in the silo flow investigation using in-situ experiment using X-ray visualization. Additionally, the study indicates that, the separation of the silo area into the funnel and stagnant zone parts is a very challenging task especially for the top and bottom area of silo where the contrast is the smallest.