Soft Sensing of Overflow Particle Size Distributions in Hydrocyclones Using a Combined Method |
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Authors: | Zhe Sun, , Huangang Wang,
,Zengke Zhang, þ
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Affiliation: | aDepartment of Automation, Tsinghua University, Beijing 100084, China |
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Abstract: | Precise, real-time measurements of overflow particle size distributions in hydrocyclones are ne-cessary for accurate control of the comminution circuits. Soft sensing measurements provide real-time,flexible, and low-cost measurements appropriate for the overflow particle size distributions in hydrocyclones.Three soft sensing methods were investigated for measuring the overflow particle size distributions in hy-drocyclones. Simulations show that these methods have various advantages and disadvantages. Optimal Bayesian estimation fusion was then used to combine three methods with the fusion parameters determined according to the performance of each method with validation samples. The combined method compensates for the disadvantages of each method for more precise measurements. Simulations using real operating data show that the absolute root mean square measurement error of the combined method was always about 2% and the method provides the necessary accuracy for beneflciation plants. |
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Keywords: | soft sensing overflow particle size distribution machine learning identification |
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