Reduction of tomographic data for use in the control of multiphase processes

S. J. R. Simons; X. Ni; Robert M. West; Richard A Williams

doi:10.1080/00986449908912141

Reduction of tomographic data for use in the control of multiphase processes

S. J. R. Simons, X. Ni, Robert M. West, Richard A Williams

School of Engineering & Physical Sciences

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

The imaging of phase distributions in vessels using tomographic techniques offers benefits in relation to improved and more efficient control schemes arising from comprehensive data acquisition. However, such image measurements are multivariate in nature and require statistical treatment. Therefore, the modelling of a multiphase process by tomography is different from the conventional process modelling where the measurements are univariate. In this paper, principal component analysis is used to extract useful information from tomographic images and to estimate the dynamic behaviour of mixing processes.

Original language	English
Pages (from-to)	99-115
Number of pages	17
Journal	Chemical Engineering Communications
Volume	175
Issue number	1
DOIs	https://doi.org/10.1080/00986449908912141
Publication status	Published - 1999

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title = "Reduction of tomographic data for use in the control of multiphase processes",

abstract = "The imaging of phase distributions in vessels using tomographic techniques offers benefits in relation to improved and more efficient control schemes arising from comprehensive data acquisition. However, such image measurements are multivariate in nature and require statistical treatment. Therefore, the modelling of a multiphase process by tomography is different from the conventional process modelling where the measurements are univariate. In this paper, principal component analysis is used to extract useful information from tomographic images and to estimate the dynamic behaviour of mixing processes.",

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AB - The imaging of phase distributions in vessels using tomographic techniques offers benefits in relation to improved and more efficient control schemes arising from comprehensive data acquisition. However, such image measurements are multivariate in nature and require statistical treatment. Therefore, the modelling of a multiphase process by tomography is different from the conventional process modelling where the measurements are univariate. In this paper, principal component analysis is used to extract useful information from tomographic images and to estimate the dynamic behaviour of mixing processes.

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DO - 10.1080/00986449908912141

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JO - Chemical Engineering Communications

JF - Chemical Engineering Communications

SN - 0098-6445

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Reduction of tomographic data for use in the control of multiphase processes

Abstract

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