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fuzzy logic in flotation of coper

  • PERFORMANCE OF A FLOTATION COLUMN FUZZY

    The controller, which is based on a fuzzy logic inference system of Mamdani type with heuristically developed rules, works in real time and has the possibility of load rejection control as well as servo control of two controlled variables.

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  • Control of a flotation column using fuzzy logic inference

    Abstract. This paper describes a fuzzy controller that was developed for the control, in real time, of three main variables of the column flotation process. Column flotation is a solidsolid separation process based on the physical and chemical properties of mineral particle surfaces. It is applied to the concentration of low grade ores

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  • Using fuzzy logic for on line trend analysis IEEE

    Using fuzzy logic, the system determines current and past process states and reports on DCS signals regarding significant changes up or down. When such a change occurs, a message is sent to the computer console to indicate the trend and its corresponding time scale.

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  • Flotation Control Incorporating Fuzzy Logic and Image Analysis

    the system translates the fuzzy processing data in to a control system output. Thereby , combining this three step process, a PLC with fuzzy logic capabilities can sensibly determine the proper control response to system inputs based on collective predefined criteria. Fuzzy logic thereby taps into the process knowledge of the

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  • FUZZY BASED MODELING AND CONTROL OF AN INDUSTRIAL

    fuzzy based modeling and control of an industrial flotation column Article in Chemical Engineering Communications 201(7) 183; March 2014 with 29 Reads DOI 10.1080/00986445.2013.790815

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  • A Fuzzy Logic Model to Predict the Bioleaching Efficiency

    A fuzzy logic system is a nonlinear mapping of an input data (feature) vector into a scalar output . It con [18] tains four components fuzzifier, rules, inference engine, and defuzzifier. In this research, the fuzzy modeling process was supported by Fuzzy Logic Toolbox of the Matlab software (version 7.4.0). The standard method of

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  • A Fuzzy Logic Model to Predict the Bioleaching Efficiency

    Multiplicity of the chemical, biological, electrochemical and operational variables and nonlinear behavior of metal extraction in bioleaching environments complicate the mathematical modeling of these systems. This research was done to predict copper and iron recovery from a copper flotation concentrate in a stirred tank bioreactor using a fuzzy logic model.

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  • Flotation of Copper Ores Mineral Processing amp; Metallurgy

    Flotation of Copper Ores. An air pressure of 15 lb. is ample for the Pachuca mixer and 25 cu. ft. of free air per minute is sufficient volume for mixing 250 tons of minus 48 mesh pulp, and of course should be furnished from a low pressure compressor.

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  • Flotation Control Incorporating Fuzzy Logic and Image

    Abstract. This knowledge is built into a data base under the form of fuzzy logic. This is in the form of fuzzy sets for the range of velocities, grades, recoveries etc. The following figure (Fig. 1) is a fuzzy set example for velocity with five membership functions, Very Slow, Slow, OK, Fast and Very Fast.

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  • Control of a flotation column using fuzzy logic inference

    Employing of similar models of fuzzy logic (fuzzy inference system) and neural network, in cone crusher control (Moshghbar et al 1995) and control of flotation column (Carvalho et al 2002 amp; Viehia

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