Leaching rate prediction and optimization operation method in wet metallurgical leaching process

A technology of hydrometallurgy and operation optimization, applied in the direction of electrical program control, process efficiency improvement, comprehensive factory control, etc., can solve the problems of high energy consumption, rough production operation, dragging process, etc., and achieve the effect of uniform temperature distribution

Inactive Publication Date: 2009-09-09
NORTHEASTERN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The general production operation of the domestic leaching process is rough, the leaching time is long, and the energy consumption is large, which directly drags down the subsequent processes. Therefore, the Ministry of Science and Technology approved the establishment of a project to tackle key problems in the optimization technology of the hydrometallurgical leaching process, requiring the development of independent intellectual property rights. The advanced leaching process optimization control software system, and apply the research results to establish the leaching process automation production line in the demonstration base, and gradually promote the application in various hydrometallurgical factories, so as to promote the leapfrog development of my country's hydrometallurgical industry

Method used

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  • Leaching rate prediction and optimization operation method in wet metallurgical leaching process
  • Leaching rate prediction and optimization operation method in wet metallurgical leaching process
  • Leaching rate prediction and optimization operation method in wet metallurgical leaching process

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0155] Example 1: Prediction model of leaching rate of leaching tank 1#

[0156] 1. Prediction model independent variables and dependent variables: the temperature of the leaching liquid in the leaching tank (CAO_TEM, K), the PH value of the leaching liquid in the leaching tank (CAO_PH), and the SO 2 Flow (CAO_SO 2 , Ml / s), the flow rate of sulfuric acid (CAO_H 2 SO 4 , L / s), leaching time (TIME, s), leaching rate (JINCHULV, %).

[0157] 2. Data set: Collect the two-month production data (independent variable and dependent variable) of the leaching tank of the leaching production line. The online data is collected every 30 seconds, and there are 65 valid samples in the training set.

[0158] In practical applications, the process data comes from the field, and is affected by factors such as the accuracy, reliability of the measuring instrument and the field measurement environment, and various measurement errors are inevitable. The use of low-precision or invalid measurement data ...

Embodiment 2

[0175] Example 2: Online optimization of leaching tank 1#:

[0176] 1. Optimize the target variable and optimize the independent variable: take the economic benefit of the leaching tank as the optimization target, the temperature of the leaching liquid (CAO_TEM, K) and its loss (QT) in the leaching tank, and the input SO 2 Flow (CAO_SO 2 , Ml / s) and its loss (Qs), the flow of sulfuric acid (CAO_H 2 SO4 , L / s) and its loss (Q1), stirring motor loss (Qd), leaching time (TIME, s), leaching rate (y, %).

[0177] 2. Establish a production optimization model: collect two-month production data from the leaching tank of the leaching production line, online data is collected every 30 seconds, and 65 valid samples in the training set. The difference between the collected sensor measurement data and the above prediction result and the real value is composed of input and output data pairs, and the data modeling method is called for training to obtain the parameters in the data model, and the ...

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Abstract

The invention relates to a leaching rate prediction and optimization operation method in the wet metallurgical leaching process. The method comprises the following steps: predicting a leaching rate by an established mixing model and giving optimization operation instructions, wherein an integrative dynamic mechanism model of the leaching process is established, and a material balance equation and an energy balance equation are gradually established in the leaching process on the basis of the ore-leaching dynamic principle of the integrative dynamic mechanism model. The device comprises a leaching rate prediction and optimization operation system in the leaching process, a host computer, a PLC and a field sensing transmitting part which comprises a pH value detecting instrument, a temperature detecting instrument, a flow detecting instrument, and the like. With the technical scheme, the leaching process can be greatly improved, the production can be constantly kept in an optimal state, the consumption of raw materials and energy sources is reduced, the operation period of equipment is prolonged and the relation change between supply and demand on markets can be reflected in time.

Description

Technical field [0001] The invention belongs to the field of hydrometallurgy, and in particular provides a method for predicting and optimizing the leaching rate of the hydrometallurgical leaching process, that is, providing a method for predicting the leaching rate, and designing the most reasonable operating conditions for the leaching process to reduce costs. Background technique [0002] With the gradual decrease of high-grade ore, the hydrometallurgical industry has begun to receive great attention from countries all over the world. The general process flow of the whole process of hydrometallurgy is: ① ore raw material pretreatment (grinding); ② ore raw material leaching; ③ solid-liquid separation, solution purification, enrichment and separation (extraction); ④ recovery of compounds or metals from solution . [0003] The rapid development of hydrometallurgical technology is mainly due to its advantages in the following aspects: [0004] (1) It can process low-grade material...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B19/418G05B13/04C22B3/08
CPCY02P10/20Y02P90/02
Inventor 何大阔毛志忠尤富强胡广浩张淑宁黄瑛
Owner NORTHEASTERN UNIV
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