A1 Journal article (refereed), original research

A Novel Machine Vision Based Image Analysis Method for the Analysis of Mixing Elements in Rotary Drums


Open Access publication

Publication Details
Authors: Koiranen Tuomas, Melanen Tuomas, Ilonen Jarmo, Eerola Tuomas, Lensu Lasse, Kälviäinen Heikki
Publisher: Taylor & Francis: STM, Behavioural Science and Public Health Titles
Publication year: 2017
Language: English
Related Journal or Series Information: Chemical Engineering Communications
Start page: 1
End page: 8
Number of pages: 8
ISSN: 0098-6445
eISSN: 1026-7379
JUFO-Level of this publication: 1
Open Access: Open Access publication

Abstract

Mixing performance in continuous rotary drums has been studied. The video analysis method was developed to evaluate different configurations of straight lifters in the rotary drum. The method converts a captured video into a single image, called stack image. The color marker tracking was estimated based on the color saturation of the stack image. Coefficients of variation and mixing indices were calculated from the color saturation profiles for different straight blade lifter configurations. The video analysis method was confronted to the impulse response of acid concentrations in water solutions. The developed analysis method has been superior with viscous fluids compared to traditional tracer impulse method in mixing evaluations. Water and 1% CMC-water solution were used in this mixing study for covering broadly different viscous materials. The drum lengthwise results for one lifter configuration were obtained from a single experiment due to the block representation of the image analysis method. It enables mixing analysis of axial segments and interaction analysis of mixer configurations. Thus, the axial mixing can be studied in more detail with rotary drums. The increase of lifters, residence time, and tip speed improved axial mixing in the studied experimental setup.


Last updated on 2018-19-10 at 07:55