Estimation of particle size in hydrocyclone underflow streams by use of Multivariate Image Analysis
Photographic images were collected of the underflow slurry stream of a laboratory-scale hydrocyclone classifying Merensky, UG2 and Platreef platinum group metal ores. Textural descriptors of the images derived by means of a steerable pyramid algorithm could be used to predict the mean particle size...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
Elsevier Ltd
2014
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| Online Access: | http://hdl.handle.net/20.500.11937/9943 |
| _version_ | 1848746095332556800 |
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| author | Aldrich, Chris Uahengo, F. Kistner, M. |
| author_facet | Aldrich, Chris Uahengo, F. Kistner, M. |
| author_sort | Aldrich, Chris |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Photographic images were collected of the underflow slurry stream of a laboratory-scale hydrocyclone classifying Merensky, UG2 and Platreef platinum group metal ores. Textural descriptors of the images derived by means of a steerable pyramid algorithm could be used to predict the mean particle size of the underflow slurry streams. The model consisted of a linear discriminant classifier that first identified the underflow as comprising coarse, intermediate or fine particle flow. Use of the centroids or mean particle sizes of these three classes could explain on average approximately 81% of the variance in the mean particle sizes of the underflow streams. These measurements can be performed online, and could form the basis for more advanced control of hydrocyclones and mineral processing circuits in general. |
| first_indexed | 2025-11-14T06:27:48Z |
| format | Journal Article |
| id | curtin-20.500.11937-9943 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:27:48Z |
| publishDate | 2014 |
| publisher | Elsevier Ltd |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-99432017-09-13T14:56:20Z Estimation of particle size in hydrocyclone underflow streams by use of Multivariate Image Analysis Aldrich, Chris Uahengo, F. Kistner, M. Photographic images were collected of the underflow slurry stream of a laboratory-scale hydrocyclone classifying Merensky, UG2 and Platreef platinum group metal ores. Textural descriptors of the images derived by means of a steerable pyramid algorithm could be used to predict the mean particle size of the underflow slurry streams. The model consisted of a linear discriminant classifier that first identified the underflow as comprising coarse, intermediate or fine particle flow. Use of the centroids or mean particle sizes of these three classes could explain on average approximately 81% of the variance in the mean particle sizes of the underflow streams. These measurements can be performed online, and could form the basis for more advanced control of hydrocyclones and mineral processing circuits in general. 2014 Journal Article http://hdl.handle.net/20.500.11937/9943 10.1016/j.mineng.2014.08.018 Elsevier Ltd restricted |
| spellingShingle | Aldrich, Chris Uahengo, F. Kistner, M. Estimation of particle size in hydrocyclone underflow streams by use of Multivariate Image Analysis |
| title | Estimation of particle size in hydrocyclone underflow streams by use of Multivariate Image Analysis |
| title_full | Estimation of particle size in hydrocyclone underflow streams by use of Multivariate Image Analysis |
| title_fullStr | Estimation of particle size in hydrocyclone underflow streams by use of Multivariate Image Analysis |
| title_full_unstemmed | Estimation of particle size in hydrocyclone underflow streams by use of Multivariate Image Analysis |
| title_short | Estimation of particle size in hydrocyclone underflow streams by use of Multivariate Image Analysis |
| title_sort | estimation of particle size in hydrocyclone underflow streams by use of multivariate image analysis |
| url | http://hdl.handle.net/20.500.11937/9943 |