{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/41052"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/41052","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Development of a video-based slurry sensor for on-line ash analysis","abstract":"The implementation of process control in fine coal processing operations has traditionally been limited by the lack of adequate on-line ash sensors. Several nuclear based analyzers are available, yet none have seen widespread acceptance by the coal industry. This is due largely to their high cost, the influences of seam type and pyrite content on accuracy, and the inconvenience of having radioactive sources in a plant. Thus, reliable process control of fine coal circuits is often unobtainable due to the lack of on-line monitoring devices for ash content in process slurry streams. Recently, a video-based slurry sensor for ash analysis of coal tailings has been developed which provides a low cost, reliable ash-monitoring system suitable for use as a process control sensor. The video-based slurry sensor is mounted in a small sump which is continuously fed with coal tailings. The slurry presentation system uses a pressurized tube to rapidly acquire samples of tailings slurry. The video-based sensor employs a black-and-white television camera to acquire live images of the slurry samples. These images are then processed by the PC-based image analysis system to rapidly determine ash content. An adaptive calibration system is used in conjunction with manual monitoring and sampling to provide a means for continuous improvement of the measurement accuracy. Problems with sample illumination and sample presentation have plagued previous developments of on-line optical sensors. The video-based slurry sensor developed in this work uses a unique sample presentation system to provide high-quality slurry images online. The possibilities of using this technology in other mineral processing applications are abundant.","abstract_html":"The implementation of process control in fine coal processing operations has traditionally been limited by the lack of adequate on-line ash sensors. Several nuclear based analyzers are available, yet none have seen widespread acceptance by the coal industry. This is due largely to their high cost, the influences of seam type and pyrite content on accuracy, and the inconvenience of having radioactive sources in a plant. Thus, reliable process control of fine coal circuits is often unobtainable due to the lack of on-line monitoring devices for ash content in process slurry streams. Recently, a video-based slurry sensor for ash analysis of coal tailings has been developed which provides a low cost, reliable ash-monitoring system suitable for use as a process control sensor. The video-based slurry sensor is mounted in a small sump which is continuously fed with coal tailings. The slurry presentation system uses a pressurized tube to rapidly acquire samples of tailings slurry. The video-based sensor employs a black-and-white television camera to acquire live images of the slurry samples. These images are then processed by the PC-based image analysis system to rapidly determine ash content. An adaptive calibration system is used in conjunction with manual monitoring and sampling to provide a means for continuous improvement of the measurement accuracy. Problems with sample illumination and sample presentation have plagued previous developments of on-line optical sensors. The video-based slurry sensor developed in this work uses a unique sample presentation system to provide high-quality slurry images online. The possibilities of using this technology in other mineral processing applications are abundant.","abstract_has_math":false,"creators":["Dunn, Peter L."],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Mining and Minerals Engineering","degree_department":"Mining and Minerals Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Adel, Gregory T."],"committee_members":["Luttrell, Gerald H.","Yoon, Roe-Hoan"],"year":1996,"date_issued":"1996-11-05","date_published":"1996-11-05","updated_at":"2026-07-22T22:19:24Z","subjects":["coal preparation","image analysis","optical sensors"],"languages":["en"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-02132009-171601"],"render_values":[{"text":"etd-02132009-171601","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/41052","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Adel, Gregory T."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Luttrell, Gerald H.","Yoon, Roe-Hoan"]},{"key":"dc:contributor.department","label":"Department","values":["Mining and Minerals Engineering"]},{"key":"dc:creator","label":"Author","values":["Dunn, Peter L."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T21:29:10Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T21:29:10Z","2009-02-13"]},{"key":"dc:date.issued","label":"Date","values":["1996-11-05"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.dcmitype","label":"Dc Type Dcmitype","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mining and Minerals Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["coal preparation","image analysis","optical sensors"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-02132009-171601"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/41052"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The implementation of process control in fine coal processing operations has traditionally been limited by the lack of adequate on-line ash sensors. 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These images are then processed by the PC-based image analysis system to rapidly determine ash content. An adaptive calibration system is used in conjunction with manual monitoring and sampling to provide a means for continuous improvement of the measurement accuracy. Problems with sample illumination and sample presentation have plagued previous developments of on-line optical sensors. The video-based slurry sensor developed in this work uses a unique sample presentation system to provide high-quality slurry images online. The possibilities of using this technology in other mineral processing applications are abundant."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["BTD"]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Development of a video-based slurry sensor for on-line ash analysis"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Adel, Gregory T."],"dc:contributor.committeemember":["Luttrell, Gerald H.","Yoon, Roe-Hoan"],"dc:contributor.department":["Mining and Minerals Engineering"],"dc:creator":["Dunn, Peter L."],"dc:date.accessioned":["2014-03-14T21:29:10Z"],"dc:date.available":["2014-03-14T21:29:10Z","2009-02-13"],"dc:date.issued":["1996-11-05"],"dc:description.abstract":["The implementation of process control in fine coal processing operations has traditionally been limited by the lack of adequate on-line ash sensors. 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These images are then processed by the PC-based image analysis system to rapidly determine ash content. An adaptive calibration system is used in conjunction with manual monitoring and sampling to provide a means for continuous improvement of the measurement accuracy. Problems with sample illumination and sample presentation have plagued previous developments of on-line optical sensors. The video-based slurry sensor developed in this work uses a unique sample presentation system to provide high-quality slurry images online. 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