Mining: Bowl dehydrator design for coal slurry processing

Gangfeng, Zheng; Jiawei, Zha; Rui, Cao; Wang, Pengpeng; Lv, Kai

doi:10.1016/s0015-1882(14)70105-3

Cited by 1 publication

(1 citation statement)

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“…There are many kinds of automatic filter presses that have been successfully used in the mineral processing industry, such as the Larox-PF automatic filter press developed by Larox in Finland [7] [8][9] and the BPF automatic filter press in China [10] . Simultaneously, a new design of bowl dehydrator with a spiral screen is built and developed by Zheng Gangfeng and his colleagues at Anhui University of Science and Technology in China, the effect of filter press dehydration of coal improved efficiently [11] . Since the dehydration process of the automatic pressure filter is relatively complicated, and the stability of the index and the efficiency of the dehydration process affected by the reasonableness of the control parameter setting of the dehydration process, the optimization research of the filter press dehydration process control has received more attention.…”

Section: Introductionmentioning

confidence: 99%

Optimization of the Dewatering Process for Concentrate Pressure Filtering by Support Vector Regression

Liu

You

2021

Preprint

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In order to better improve the efficiency of the concentrate filter press dehydration operation, this paper studies the mechanism and optimization methods of the filter press dehydration process. Machine learning models of RBF-OLS, RBF-GRNN and support vector regression (SVR) are constructed respectively, and Perform laboratory simulation and industrial simulation separately. SVR achieves the best accuracy in industrial simulation, the simulated mean relative error (MRE) of moisture and processing capacity are respectively 1.57% and 3.81%. Finally, a simulation model of the filter press dehydration process established by SVR, and the optimtical simulation results Obtained by optimization method based on control variables. The results show that the machine learning method of SVR and optimization methods based on control variables are applied to industry, which can not only ensure the stability of expected production indicators, but also shorten the filter press dehydration cycle to less than 85% of the original.

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Section: Introductionmentioning

confidence: 99%