Estimation of platinum flotation grades from froth image data

QR Code

Estimation of platinum flotation grades from froth image data

Features extracted online from froth images on flotation plants are potentially useful to the developmentof advanced control for flotation systems, provided that these features can be related to the key indicatorvariables of the plant, such as valuable metal loadings and recovery. Although such rela...

Full description

Bibliographic Details
Main Authors:	Marais, C., Aldrich, Chris
Format:	Journal Article
Published:	Elsevier 2011
Subjects:	- Online analysis - Modelling - Neural networks Froth flotation
Online Access:	http://hdl.handle.net/20.500.11937/5086

Similar Items

The estimation of platinum flotation grade from froth image features by using artificial neural networks
by: Marais, C., et al.
Published: (2011)

The Relationship between Froth Image Features and Platinum Flotation Grade
by: Marais, C., et al.
Published: (2010)

Automatic flotation froth bubble size distribution estimation using mean shift and watershed transforms.
by: Amankwah, A., et al.
Published: (2014)

Robust Block-Matching Motion Estimation of Flotation Froth Using Mutual Information
by: Amankwah, A., et al.
Published: (2012)

Online monitoring and control of froth flotation systems with machine vision:A review
by: Aldrich, Chris, et al.
Published: (2010)

Kernel-based fault diagnosis on mineral processing plants
by: Gorden, T., et al.
Published: (2006)

Process data visualisation with biplots
by: Gardner, S., et al.
Published: (2005)

Recent Advances in Flotation Froth Image Analysis
by: Aldrich, Chris, et al.
Published: (2022)

Detecting change in dynamic process systems with immunocomputing
by: Yang, X., et al.
Published: (2007)

Monitoring of mineral processing systems by using textural image analysis
by: Aldrich, Chris, et al.
Published: (2013)

Optimising control of coal flotation by neuro-immune algorithm
by: Aldrich, Chris, et al.
Published: (2013)

A comparison of 2D and 3D shape characterisations of free gold particles in gravity and flash flotation concentrates
by: McGrath, Teresa, et al.
Published: (2015)

Development of a laboratory test to characterise the behaviour of free gold for use in a combined flash flotation and gravity concentrator model
by: McGrath, Teresa, et al.
Published: (2013)

Relationship between solids flux and froth features in batch flotation of sulphide ore
by: Yang, X., et al.
Published: (2005)

Effect of Preconditioning on the Flotation of Coal
by: Feng, D., et al.
Published: (2005)

Probability density function of bubble size based reagent dosage predictive control for copper roughing flotation
by: Zhu, J., et al.
Published: (2014)

Grade estimation in realgar-orpiment batch flotation systems by froth image analysis and kernel methods
by: Aldrich, Chris, et al.
Published: (2014)

Motion estimation in flotation froth using the Kalman filter
by: Amankwah, A., et al.
Published: (2015)

Motion Estimation in Flotation Froth Images Based on Edge Detection and Mutual Information
by: Amankwah, Anthony, et al.
Published: (2012)

Visualization of the controller states of an autogenous mill from time series data
by: Aldrich, Chris, et al.
Published: (2014)

The relationships between the bubble–particle attachment time, collector dosage and the mineralogy of a copper sulfide ore
by: Albijanic, Boris, et al.
Published: (2012)

The behaviour of free gold particles in a simulated flash flotation environment
by: McGrath, Teresa, et al.
Published: (2015)

Automatic control of flotation process using computer vision
by: Saravani, Ali Jahed
Published: (2015)

Multivariate image analysis of realgar–orpiment flotation froths
by: Aldrich, Chris, et al.
Published: (2017)

Machine vision-based motion estimation of flotation froth using mutual information
by: Amankwah, A., et al.
Published: (2011)

Flotation kinetic models for fixed and variable pulp chemical conditions
by: Albijanic, Boris, et al.
Published: (2015)

Flotation Froth Image Analysis by Use of a Dynamic Feature Extraction Algorithm
by: Fu, Y., et al.
Published: (2016)

Laboratory Flash Flotation Trends for a Variety of Gold Particles
by: McGrath, T, et al.
Published: (2013)

Using Convolutional Neural Networks to Develop State-of-the-Art Flotation Froth Image Sensors
by: Fu, Y., et al.
Published: (2018)

Development of an efficient protein recovery system using liquid biphasic flotation
by: Sankaran, Revathy
Published: (2018)

The depression of sphalerite during carbon pre-flotation and lead flotation at the Century Mine concentrator
by: Healy, Daniel Francis
Published: (2005)

Multivariate image analysis of a realgar-orpiment batch froth flotation system
by: Aldrich, Chris, et al.
Published: (2014)

Automatic estimation of bubble size distributions in flotation froths by use of a mean shift algorithm and watershed transforms
by: Amankwah, A., et al.
Published: (2014)

Recognition of flotation froth conditions with k-shot learning and convolutional neural networks
by: Liu, Xiu, et al.
Published: (2023)

Increasing the grind size for effective liberation and flotation of a porphyry copper ore by microwave treatment
by: Batchelor, A.R., et al.
Published: (2016)

Detecting changes in the operational states of hydrocyclones
by: van Vuuren, J., et al.
Published: (2011)

Performance of Convolutional Neural Networks for Feature Extraction in Froth Flotation Sensing
by: Horn, Z., et al.
Published: (2017)

Influence of the propagation of three phase contact line on flotation recovery
by: Subasinghe, Nimal, et al.
Published: (2014)

Fundamental aspects of bubble–particle attachment mechanism in flotation separation
by: Albijanic, Boris, et al.
Published: (2014)

Modelling of large-scale brain network dynamics
by: Forrester, Michael J.
Published: (2021)

Cannot write session to /tmp/vufind_sessions/sess_6p6tnvir9dtamu4lv32kv8gh1h