Detection method of key variables in hydrometallurgical dense washing process

A dense washing, hydrometallurgical technology, applied in measuring devices, instruments, etc., can solve problems such as slow speed, obstruction, and difficult sedimentation

Active Publication Date: 2017-01-18
NORTHEASTERN UNIV LIAONING
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] (2) In the coagulation and sedimentation zone, the solid particles in the suspension have formed tighter flocs, and the flocs continue to settle, but at a slower speed;
[0009] (3) In the interference settlement area, some particles settle due to their own weight, and some particles are hindered by dense particles, making it difficult to continue to settle;
Modeling research on dense washing process is still in the exploratory stage

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Detection method of key variables in hydrometallurgical dense washing process
  • Detection method of key variables in hydrometallurgical dense washing process
  • Detection method of key variables in hydrometallurgical dense washing process

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0125] Implementation of a forecasting method for key variables on a thickener line.

[0126] The specific implementation process is as follows:

[0127] 1) Auxiliary variable selection: The selection of auxiliary variables is the first step in establishing the soft sensor model. This step determines the input information matrix of the soft sensor, thus directly determining the structure and output of the soft sensor model. It is crucial. The selection of auxiliary variables includes the selection of variable type, the selection of variable number and the selection of detection point location.

[0128] In the dense washing process, we select feed concentration, feed flow, underflow flow, and overflow flow as auxiliary variables.

[0129] 2) Data collection and processing: Data collection was carried out on-site during the dense washing process. The specific measuring instruments are the corresponding instruments introduced above, and the corresponding production condition d...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a hydrometallurgy thick washing process key variable real-time prediction method which comprises the steps of process data acquisition, auxiliary variable selection and standardization processing, hybrid model establishment and the like. The method is characterized by establishing a parallel structure hybrid model formed based on a mechanism model and a data driver model; and taking the model based on data driving as an error compensation model of the mechanism model. The invention further provides a software system for carrying out thick washing process key variable prediction. The software system comprises a main program, a database and a man-machine interaction interface. The software system takes a model computer of a hydrometallurgy process control system as a hardware platform. The method is applied to the thick washing process of some hydrometallurgy factory and can predicate overflow concentration and underflow concentration, and the predication results are within the predetermined error range. The advantages of the method are that the method is simple in model, high in explainability, good in extrapolation performance and high in prediction precision.

Description

technical field [0001] The invention belongs to the technical field of hydrometallurgy. In particular, it provides a method for detecting the underflow concentration in the dense washing process of hydrometallurgy, that is, it provides a method for predicting the underflow concentration in real time. Background technique [0002] Hydrometallurgy technology is an ancient modern science and technology with great development prospects. Compared with traditional pyrometallurgy, hydrometallurgy technology is convenient for the separation and recovery of polymetallic resources, does not produce flue gas pollution, and is environmentally friendly. The advantages of environmental friendliness. Especially in view of the complex, difficult-to-select and low-grade mineral resources in my country, hydrometallurgy technology is more superior. It should be said that hydrometallurgy can better meet the requirements of sustainable development of mineral resources today. [0003] In recent...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G01D21/02
Inventor 牛大鹏徐宁张淑宁方文郭振宇杨晓东
Owner NORTHEASTERN UNIV LIAONING
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap