Predictive Modeling of the Performance of the Hydrocyclone with Different Cone Combination

Feng Qin He; Hua Lin Wang; Yong Hong Tan; Jian Gang Wang; Ping Zhou; Chun K. Seong

doi:10.4028/www.scientific.net/AMM.190-191.147

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On Anti-Noise-Algorithm of Optical-Polarization-Sensing Localization
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Optimization of Valve Block Shape Using CFD
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OSG-Based Modeling of the Flexural Deformation of the Crane’s Main Arm
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Practicably Optimal Point and its Solution in Deterministic System
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Predictive Modeling of the Performance of the Hydrocyclone with Different Cone Combination
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Research on Production Quality Control and Efficiency Measurement Based on DEA-Benchmark Model
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Research on Production Scheduling Method and the Application in Switch Machine Production Enterprise
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Revenue-Sharing Contract of Three-Level Supply Chain under Disruption
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Rough Set of Optimized Probabilistic Neural Network in Identification of Blue and White Ceramic from Jingdezhen
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 190-191Predictive Modeling of the Performance of the...

Predictive Modeling of the Performance of the Hydrocyclone with Different Cone Combination

Abstract:

The gypsum dehydration hydrocyclones, with cone combination of 20-10° (bi-conical), 10° (single-cone) and 8-10 ° (bi-conical), were investigated in this article. Sampled data were obtained from the separation experiments. The MATLAB neural network toolbox was used to build 3-layer BP neural network models. The resultant of separation performance prediction errors show that it is feasible to build a predictive separation model for hydrocyclones with neural network. And the built model can serve as an effective method for the design of cyclones.