Fault condition detection for a copper flotation process based on a wavelet multi-scale binary froth image
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | REM. Revista Escola de Minas (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0370-44672015000200177 |
Resumo: | AbstractConsidering the difficulty of detecting the fault condition of copper flotation in real-time, a new fault condition detection method based on the wavelet multi-scale binary image is proposed. Firstly, the froth gray image is decomposed into approximation sub-images and detailed sub-images by wavelet transformation, whereby the approximation sub-images of different scales are restructured and binarized. Then a new feature that is directly related to froth morphology, namely the equivalent size feature, is obtained by calculating the white area of each binary image according to the space-frequency relationship of a two-dimensional wavelet transformation. After this, the equivalent size distribution of the froth image can be obtained through the equivalent size feature. At last, the equivalent size distributions of different froth images are compared in order to classify the froth images under different flotation conditions. Experiment results, together with the industrial field data, show that this method can simply and effectively detect fault conditions in the copper flotation process. |
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REM. Revista Escola de Minas (Online) |
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Fault condition detection for a copper flotation process based on a wavelet multi-scale binary froth imagecopper flotationfault working condition detectionwavelet multi-scale binary froth imageequivalent size featureAbstractConsidering the difficulty of detecting the fault condition of copper flotation in real-time, a new fault condition detection method based on the wavelet multi-scale binary image is proposed. Firstly, the froth gray image is decomposed into approximation sub-images and detailed sub-images by wavelet transformation, whereby the approximation sub-images of different scales are restructured and binarized. Then a new feature that is directly related to froth morphology, namely the equivalent size feature, is obtained by calculating the white area of each binary image according to the space-frequency relationship of a two-dimensional wavelet transformation. After this, the equivalent size distribution of the froth image can be obtained through the equivalent size feature. At last, the equivalent size distributions of different froth images are compared in order to classify the froth images under different flotation conditions. Experiment results, together with the industrial field data, show that this method can simply and effectively detect fault conditions in the copper flotation process.Escola de Minas2015-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0370-44672015000200177Rem: Revista Escola de Minas v.68 n.2 2015reponame:REM. Revista Escola de Minas (Online)instname:Escola de Minasinstacron:ESCOLA DE MINAS10.1590/0370-44672015680195info:eu-repo/semantics/openAccessMing,LuWei-hua,GuiTao,PengWei,Caoeng2015-10-09T00:00:00Zoai:scielo:S0370-44672015000200177Revistahttp://www.scielo.br/remhttps://old.scielo.br/oai/scielo-oai.phpeditor@rem.com.br1807-03530370-4467opendoar:2015-10-09T00:00REM. Revista Escola de Minas (Online) - Escola de Minasfalse |
dc.title.none.fl_str_mv |
Fault condition detection for a copper flotation process based on a wavelet multi-scale binary froth image |
title |
Fault condition detection for a copper flotation process based on a wavelet multi-scale binary froth image |
spellingShingle |
Fault condition detection for a copper flotation process based on a wavelet multi-scale binary froth image Ming,Lu copper flotation fault working condition detection wavelet multi-scale binary froth image equivalent size feature |
title_short |
Fault condition detection for a copper flotation process based on a wavelet multi-scale binary froth image |
title_full |
Fault condition detection for a copper flotation process based on a wavelet multi-scale binary froth image |
title_fullStr |
Fault condition detection for a copper flotation process based on a wavelet multi-scale binary froth image |
title_full_unstemmed |
Fault condition detection for a copper flotation process based on a wavelet multi-scale binary froth image |
title_sort |
Fault condition detection for a copper flotation process based on a wavelet multi-scale binary froth image |
author |
Ming,Lu |
author_facet |
Ming,Lu Wei-hua,Gui Tao,Peng Wei,Cao |
author_role |
author |
author2 |
Wei-hua,Gui Tao,Peng Wei,Cao |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Ming,Lu Wei-hua,Gui Tao,Peng Wei,Cao |
dc.subject.por.fl_str_mv |
copper flotation fault working condition detection wavelet multi-scale binary froth image equivalent size feature |
topic |
copper flotation fault working condition detection wavelet multi-scale binary froth image equivalent size feature |
description |
AbstractConsidering the difficulty of detecting the fault condition of copper flotation in real-time, a new fault condition detection method based on the wavelet multi-scale binary image is proposed. Firstly, the froth gray image is decomposed into approximation sub-images and detailed sub-images by wavelet transformation, whereby the approximation sub-images of different scales are restructured and binarized. Then a new feature that is directly related to froth morphology, namely the equivalent size feature, is obtained by calculating the white area of each binary image according to the space-frequency relationship of a two-dimensional wavelet transformation. After this, the equivalent size distribution of the froth image can be obtained through the equivalent size feature. At last, the equivalent size distributions of different froth images are compared in order to classify the froth images under different flotation conditions. Experiment results, together with the industrial field data, show that this method can simply and effectively detect fault conditions in the copper flotation process. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-06-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0370-44672015000200177 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0370-44672015000200177 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0370-44672015680195 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Escola de Minas |
publisher.none.fl_str_mv |
Escola de Minas |
dc.source.none.fl_str_mv |
Rem: Revista Escola de Minas v.68 n.2 2015 reponame:REM. Revista Escola de Minas (Online) instname:Escola de Minas instacron:ESCOLA DE MINAS |
instname_str |
Escola de Minas |
instacron_str |
ESCOLA DE MINAS |
institution |
ESCOLA DE MINAS |
reponame_str |
REM. Revista Escola de Minas (Online) |
collection |
REM. Revista Escola de Minas (Online) |
repository.name.fl_str_mv |
REM. Revista Escola de Minas (Online) - Escola de Minas |
repository.mail.fl_str_mv |
editor@rem.com.br |
_version_ |
1754122199004872704 |