Analysis of electrical resistance tomography (ERT) data using least-squares regression modelling in industrial process tomography

Khanal, Manoj and Morrison, Rob (2009) Analysis of electrical resistance tomography (ERT) data using least-squares regression modelling in industrial process tomography. Measurement Science & Technology, 20 4: Article number 045503.


Author Khanal, Manoj
Morrison, Rob
Title Analysis of electrical resistance tomography (ERT) data using least-squares regression modelling in industrial process tomography
Journal name Measurement Science & Technology   Check publisher's open access policy
ISSN 0957-0233
Publication date 2009-03-10
Year available 2009
Sub-type Article (original research)
DOI 10.1088/0957-0233/20/4/045503
Volume 20
Issue 4
Start page Article number 045503
Total pages 9
Editor P. Hauptmann
Place of publication Bristol, England
Publisher IOP Publishing
Collection year 2010
Language eng
Subject 840399 First Stage Treatment of Ores and Minerals not elsewhere classified
091404 Mineral Processing/Beneficiation
Abstract Analysis of electrical resistance tomography (ERT) data using least-squares regression modelling in industrial process tomographs has been tested. Potential differences measured between electrodes in rings have been used to carry out the regression modelling to investigate the location and size of a disturbance present in the system. Extensive experiments have been carried out with ERT to test a suitable regression algorithm to extract the disturbance. Current analysis has been performed for a single disturbance known to be present in the system. For the environment considered, the least-squares regression reported in this paper demonstrates an alternative approach for analysis of tomography data in industrial applications. The position (concentric or off-centre) and the size of the disturbance (in concentric cases) can be well defined by the reported regression modelling approach. However, it is still a challenge to define the size of the off-centre disturbance.
Keyword Hydro-cyclone
Industrial process tomography
Interpretation
Regression modelling
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Thu, 26 Nov 2009, 13:04:33 EST by Karen Holtham on behalf of Julius Kruttschnitt Mineral Research Centre