Published April 2009 | Version v1
Journal article

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

  • 1. CSIRO, Exploration and Mining, Queensland Centre for Advanced Technologies, PO Box 883, Kenmore, QLD 4069 (Australia)
  • 2. The University of Queensland, Sustainable Minerals Institute, Julius Kruttschnitt Mineral Research Centre, QLD 4068 (Australia)

Description

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

Availability note (English)

Available from http://dx.doi.org/10.1088/0957-0233/20/4/045503

Additional details

Identifiers

DOI
10.1088/0957-0233/20/4/045503;
PII
S0957-0233(09)05069-3;

Publishing Information

Journal Title
Measurement Science and Technology
Journal Volume
20
Journal Issue
4
Journal Page Range
[8 p.]
ISSN
0957-0233
CODEN
MSTCEP

INIS