Intelligent control method of deep cone thickener under filling scene

A technology of deep cone thickener and intelligent control, which is applied in separation methods, chemical instruments and methods, wet separation, etc., and can solve the problems of relying on manual experience and lack of self-adaptability

Active Publication Date: 2019-08-06
UNIV OF SCI & TECH BEIJING
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide an intelligent control method for deep cone thickeners in the filling scene, so as

Method used

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  • Intelligent control method of deep cone thickener under filling scene
  • Intelligent control method of deep cone thickener under filling scene
  • Intelligent control method of deep cone thickener under filling scene

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Embodiment 1

[0068] like figure 1 As shown, the intelligent control method of the deep cone thickener under the filling scene provided by the embodiment of the present invention includes:

[0069] S101, acquiring historical record data and real-time monitoring data monitored during the actual filling process;

[0070] S102, establishing an underflow concentration control model to control the underflow concentration and overflow water turbidity, the underflow concentration control model includes: a neural network planner, a flocculant controller, and a mud layer pressure controller; wherein,

[0071] The neural network planner is trained offline through historical record data, and the underflow concentration target value and overflow water turbidity warning line value are input into the trained neural network planner, and the neural network planner outputs the optimal rake speed setting value, flocculant addition ratio and mud layer pressure setting value;

[0072] The flocculant controll...

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Abstract

The invention provides an intelligent control method of a deep cone thickener under a filling scene, and the intelligent control method can improve the control precision of underflow concentration. The method comprises the following steps of: establishing an underflow concentration control model to control the underflow concentration, offline training a neural network planner through historical record data, and outputting an optimal rake frame rotation speed setting value, an optimal flocculant addition ratio and an optimal mud layer pressure setting value; dynamically adjusting a flocculant addition flow setting value according to real-time monitoring data and the optimal flocculant addition ratio by a flocculant controller; adjusting an underflow flow setting value by a mud layer pressure controller to enable a deep cone thickener mud layer pressure monitoring value tracks the optimal mud layer pressure set value; and applying the obtained optimal rake rotation speed setting value, flocculant addition setting value and underflow flow setting value to the actual filling process in real time, and transmitting monitoring data generated in real time to the underflow concentration control model in real time for online learning and training of the underflow concentration control model. The invention relates to the field of mine tailings disposal.

Description

technical field [0001] The invention relates to the field of mine tailings disposal, in particular to an intelligent control method for a deep cone thickener in a filling scene. Background technique [0002] As one of the thickeners, the deep cone thickener is a large-scale sedimentation tool that is widely used. It can concentrate the low-concentration solid-liquid mixture to form a high-concentration mixture through gravity sedimentation, and play the role of water reduction and concentration. . In the process of controlling the deep cone thickener, the concentration of the underflow and the turbidity of the overflow water are the core control indicators. In most of the actual production process, the control of the concentration of the underflow of the thickener is generally carried out by the operator based on personal experience. The set value of the underflow flow and the set value of the flocculant addition flow are adjusted to indirectly make the underflow concentrat...

Claims

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Application Information

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IPC IPC(8): B01D21/32B01D21/30B03B5/60
CPCB01D21/30B01D21/305B01D21/32B03B5/60
Inventor 班晓娟何润姿袁兆麟刘婷王贻明
Owner UNIV OF SCI & TECH BEIJING
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