Process data visualisation with biplots

In this paper a modern methodology of biplots is introduced as a means for monitoring the behaviour of process systems. This sophisticated methodology allows for the projection of high-dimensional data to a low-dimensional subspace that can be visualised by a human operator. The projections are high...

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Main Authors: Gardner, S., Le Roux, N., Aldrich, Chris
Format: Journal Article
Published: Elsevier 2005
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/45724
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author Gardner, S.
Le Roux, N.
Aldrich, Chris
author_facet Gardner, S.
Le Roux, N.
Aldrich, Chris
author_sort Gardner, S.
building Curtin Institutional Repository
collection Online Access
description In this paper a modern methodology of biplots is introduced as a means for monitoring the behaviour of process systems. This sophisticated methodology allows for the projection of high-dimensional data to a low-dimensional subspace that can be visualised by a human operator. The projections are highly graphical in nature, and rich in information regarding variation in process variables, correlations among these variables, as well as class separation, taking into account the multivariate character of the data. Moreover, as is shown by way of two case studies, process disturbances can be visualised and explored quantitatively by superimposing alpha-bags on biplots.
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format Journal Article
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institution Curtin University Malaysia
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publishDate 2005
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spelling curtin-20.500.11937-457242017-02-28T01:42:10Z Process data visualisation with biplots Gardner, S. Le Roux, N. Aldrich, Chris Hydrometallurgy Froth flotation Process control Modelling In this paper a modern methodology of biplots is introduced as a means for monitoring the behaviour of process systems. This sophisticated methodology allows for the projection of high-dimensional data to a low-dimensional subspace that can be visualised by a human operator. The projections are highly graphical in nature, and rich in information regarding variation in process variables, correlations among these variables, as well as class separation, taking into account the multivariate character of the data. Moreover, as is shown by way of two case studies, process disturbances can be visualised and explored quantitatively by superimposing alpha-bags on biplots. 2005 Journal Article http://hdl.handle.net/20.500.11937/45724 Elsevier restricted
spellingShingle Hydrometallurgy
Froth flotation
Process control
Modelling
Gardner, S.
Le Roux, N.
Aldrich, Chris
Process data visualisation with biplots
title Process data visualisation with biplots
title_full Process data visualisation with biplots
title_fullStr Process data visualisation with biplots
title_full_unstemmed Process data visualisation with biplots
title_short Process data visualisation with biplots
title_sort process data visualisation with biplots
topic Hydrometallurgy
Froth flotation
Process control
Modelling
url http://hdl.handle.net/20.500.11937/45724