The simulation and identification of flotation processes by use of a knowledge based model

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dc.contributor.authorReuter M.A.
dc.contributor.authorvan Deventer J.S.J.
dc.date.accessioned2011-05-15T16:01:51Z
dc.date.available2011-05-15T16:01:51Z
dc.date.issued1992
dc.description.abstractThis paper illustrates the application of a knowledge based system to perform fault-diagnosis, dynamic simulation and the optimization of batch and continuous flotation processes. The proposed approach is essentially useful to simulate ill-defined dynamic processes where existing fundamental and empirical models fail owing to their lack of generality. A generalized kinetic model is defined and linked to a knowledge base via adjustment objects in order to perform flotation process simulation. The kinetic model and the accompanying knowledge base are also applied to produce the bounds to a generalized linear programming model of a generalized flotation plant to assist in its optimal design. It is shown that the proposed approach could be used to simulate flotation data for batch and continuous operations. In contrast with most existing models, no curve-fitting is required, as the kinetic model utilises experimental data directly. Also, adjustment factors are defined in an intelligent way in the knowledge-based system so as to relate the operating conditions to the kinetics of flotation. In this way, a generalised description of kinetic behaviour is effected. It is shown how the generalized kinetic model is applied to perform fault diagnosis i.e. to identify the process conditions within a flotation cell or bank, and to recommend process conditions which could improve flotation behaviour. © 1992.
dc.description.versionArticle
dc.identifier.citationInternational Journal of Mineral Processing
dc.identifier.citation35
dc.identifier.citation02-Jan
dc.identifier.issn3017516
dc.identifier.urihttp://hdl.handle.net/10019.1/12186
dc.subjectComputer simulation
dc.subjectFroth flotation
dc.subjectKnowledge based systems
dc.subjectLinear programming
dc.subjectMathematical models
dc.subjectOptimization
dc.subjectZinc ore treatment
dc.subjectBatch processes
dc.subjectKnowledge representation
dc.subjectProcess identification
dc.subjectSpharelite
dc.subjectZinc sulfide recovery
dc.subjectOre treatment
dc.titleThe simulation and identification of flotation processes by use of a knowledge based model
dc.typeArticle
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