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Abstract: In this paper, the use of different image analysis techniques is investigated for predicting alumina content of anode cover materials used in primary aluminum smelters. This approach is proposed in to order to allow on-line estimation of alumina content for feedback control purposes, which is not currently possible due to the long time delays and limited number of samples that can be analyzed in the laboratory. Both color and textural features of various anode cover materials are extracted from digital RGB images, and partial least squares (PLS) regression models are developed for predicting alumina content from these features. Most alumina content prediction errors are within of the X-ray fluorescence laboratory measurements, when larger variations are required by operators to make control decisions. Some challenges arising from the use of image analysis techniques for process control are also discussed. [Copyright &y& Elsevier]

Abstract: Variations in run-of-mine ore properties such as size, composition, and grindability strongly affect AG and SAG mills performance. In the past, most efforts to track and control these variations have focused on developing on-line size analysis using vision systems to reduce power consumption and avoid mill overload. To improve ore sorting/blending strategies and to account for variations in grindability, on-line run-of-mine composition analysis would be very helpful, but has received much less attention from the research community. This paper describes a general machine vision approach for on-line estimation of rock mixture composition, and is illustrated on a very challenging nickel mineral system: very heterogeneous minerals, similar coloration, and rock fragments can be dry or wet. The proposed mineral type recognition method involves: (1) dividing into sub-images; (2) extracting color and textural features using principal components analysis (PCA) and wavelet texture analysis (WTA), respectively; (3) reducing feature space dimensionality and removing dry/wet systematic variations using discriminant partial least squares (PLS-DA); and (4) establishing class boundaries using support vector machines (SVM). Through a pilot plant conveyor belt application, very good results were obtained for dry minerals. For wet rock mixtures, further investigation is required, but results are very promising. [Copyright &y& Elsevier]

Abstract: This paper summarizes research into the study of the control of flotation processes based on froth images. A review of the froth flotation operation background and the relevance and role of the froth phase are presented. The use of numerical image analysis techniques for the extraction of significant patterns from industrial flotation froths is discussed. First, the froth was analysed by the use of the Multivariate Image Analysis (MIA) method to extract the spectral variation contained in a RBG image. The Partial Least Squares (PLS) method was applied to develop an empirical model for the prediction of froth grade. The results of this application are illustrated using an industrial case study. Second, the froth was also analysed by Grey-Level Co-occurrence Matrix (GLCM) and Wavelet Transform Analysis (WTA) to extract features related more to morphological aspects. Since there is useful information hidden in froth texture, these methods are used as texture descriptor to classify different types of froths. They also provide qualitative information on the changes in the visual appearance of the froth. The pros and the cons of those methods are highlighted. Third, a control strategy based on a froth structure indicator was developed and implemented on an industrial zinc flotation circuit. The feedback controller uses the reagent flow-rate in order to maintain the froth structure at its set point. Process improvements obtained from the implemented control strategy are highlighted. Finally, the feasibility of implementing a hybrid control strategy consisting in a froth structure supervision controller based on the froth concentrate grade estimated by MIA and recovery inferred by image analysis is discussed. [Copyright &y& Elsevier]

This paper reports on the application of an acousto-ultrasonic (AU) scheme for the inspection of industrial-size carbon anode blocks used in the production of primary aluminium by the Hall-Héroult process. A frequency-modulated wave is used to excite the anode blocks at multiple points. The collected attenuated AU signals are decomposed using the Discrete Wavelet Transform (DTW) after which vectors of features are calculated. Principal Component Analysis (PCA) is utilized to cluster the AU responses of the anodes. The approach allows locating cracks in the blocks and the AU features were found sensitive to crack severity. The results are validated using images collected after cutting some anodes. [ABSTRACT FROM AUTHOR]

Reduction of pot draft in aluminum smelting cells is a promising approach for energy saving and waste heat recovery. The control of fugitive emissions (hazardous by-product gases escaping from cells to potroom) is investigated in a smelting cell with the reduced pot draft, down to half of the current level based on CFD simulations. Physical models with different length scales are created in order to directly resolve the very narrow escaping gaps on the pot shell in the physical model with smallest scale. A systematic analysis of the pot tightness is presented by considering various factors in the simulations, e.g., pot draft and hood placement. The results have shown that current pot structure, even within ideal operating conditions, fails to maintain 100% hooding efficiency under a 50% reduced pot draft. Two design modifications are proposed to enhance the pot tightness. An efficient sealing is observed when covering the lower half of the gaps between hoods. An estimation of the leaking hydrogen fluoride is made under different scenarios in order to quantitatively verify the modifications. [ABSTRACT FROM AUTHOR]

• Individual anode current signals used to detect anode incidents in real-time. • Detection systems built with principal component analysis and an industrial dataset. • Best detection performance was achieved with the simplest system configuration. • Model profit metric developed to evaluate economic potential of detection systems. • Detection systems appear to be economically superior to standard detection method. Anodic incidents occur when an aluminum electrolysis cell short circuits at an anode position. They reduce the current efficiency of the affected cell, which makes it economically advantageous to detect and remove them as early as possible. This study evaluates the performance of three anodic incident detection systems of varying complexity. Individual anode current signals from 6 different cells were monitored with a Principal Component Analysis (PCA) model to detect anodic incidents using the Squared Prediction Error (SPE) statistic. The results suggest that a simple detection system using a common PCA model and a common detection threshold for all cells may be preferable. A novel approach to estimating the economic benefit of a detection system was also developed and used to optimize the systems' detection threshold. The anodic incident detection systems were found to deliver positive profits relative to the standard detection technique. [ABSTRACT FROM AUTHOR]

Aluminium industry depends today on only the coal-tar-pitch as a binder to produce carbon anodes. However, it becomes difficult to secure a high-quality binder for the future needs of the aluminum industry as coal-tar-pitch is a non-renewable fossil binder. In this work bio-pitch, as a renewable and environmentally friendly binder, was produced by the heat treatment of a bio-oil. The range of heat treatment temperature and heating rate was selected to achieve the desired physical properties of the produced bio-pitch. This bio-pitch showed a softening point and a viscosity similar to that of the coal-tar-pitch. In addition, it was able to cover and spread over the coke particles and further, penetrate into their open pores. According to the results of this work, the bio-pitch is a promising candidate to replace the coal-tar-pitch to produce a homogenous and mechanically stable green carbon anode. [ABSTRACT FROM AUTHOR]