Flotation recovery rate prediction method based on image characteristic analysis

A flotation recovery rate and image feature technology, which is applied in the analysis of materials, material analysis by optical means, measurement devices, etc., can solve the problems that the recovery rate cannot be detected online and cannot be accurately predicted, and can solve the problem that the recovery rate cannot be detected online. Effect

Inactive Publication Date: 2011-05-25
CENT SOUTH UNIV
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problem that the recovery rate cannot be detected online and to avoid the problem that the conventional method cannot be accurately predicted, to provide a mineral recovery rate prediction method based on the analysis of the foam image characteristics, and to provide reference information for the optimization operation of the mineral flotation process

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
  • Flotation recovery rate prediction method based on image characteristic analysis
  • Flotation recovery rate prediction method based on image characteristic analysis
  • Flotation recovery rate prediction method based on image characteristic analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0010] The hardware structure of the foam image analysis system is as follows: figure 1 As shown, it is mainly composed of a camera 1, a light source 2, an optical fiber 3, an image acquisition card 4, and a computer 5. In the figure, the camera 1 is used to photograph the foam layer 6, and is installed vertically directly above the flotation tank 7, with a distance of 200 cm from the overflow tank 8.

[0011] The resolution of camera 1 is set to 1024×768, the shutter is set to 323uS, the working distance is 110cm, the focal length of the lens is 55mm, the field of view is 16cm×12cm, powered by 12V DC power supply, and the measurement accuracy is 6.4-6.8pixels / mm.

[0012] The light source 2 uses a 200W high-frequency fluorescent lamp, the color temperature is 4500K, the power supply is 220V@50HZ, the light source 2 is close to the camera 1, and the horizontal distance is 10cm.

[0013] The color CCD camera 1 acquires the image of the foam layer, digitizes the video signal an...

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 discloses a flotation recovery ratio predicting method that is based on image characteristic analysis. The invention uses an industrial camera to obtain a foam image base of a mineral dressing process, adopts a relative red component to extract color characteristic, combines the morphology and the watershed method to cut up the foam image and extract size characteristic, utilizes the pixel analyzing method for to extract bearing capacity characteristic, and adopts the correlation analyzing method of image pairs to extract dynamic characteristics of foam speed and damage ratio, etc. The flotation recovery ratio predicting method adopts the least square supporting vector machine (LSSVM) for setting up a flotation recovery ratio predicting model, uses the image characteristics as inputs of the model, adopts the noise data eliminating method of dynamic stacks and realizes model parameter optimization through the 10-fold cross validation. The flotation recovery ratio predicting method can be used for predicting the flotation recovery ratio prediction of minerals and realizing operation optimization in the flotation production, and consequently can improve the recovery ratio of the minerals and reduce the wasting of mineral resources.

Description

[technical field] [0001] The invention relates to a foam image feature analysis and a mineral recovery rate prediction method in the beneficiation process, in particular to a foam feature analysis and recovery rate prediction method for light metal flotation. [Background technique] [0002] Flotation is the most widely used beneficiation method in mineral processing, which involves extremely complex physical and chemical processes. The purpose of mineral flotation is to improve the grade of raw ore and meet the requirements of reduction smelting. As a key indicator of the flotation process, the recovery rate directly affects the quality and output of the concentrate. However, the flotation process is long, with many influencing factors and serious coupling, so it is impossible to realize the online detection of the recovery rate. For a long time, the dressing plant has analyzed the recovery rate through off-line assay, which lags behind the flotation process by 4 hours, an...

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): G01N21/84G01N33/00
Inventor 桂卫华阳春华周开军唐朝晖许灿辉程翠兰刘金平
Owner CENT SOUTH UNIV
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