Off-line image analysis for froth flotation of coal

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Abstract

Froth flotation is an effective process for separating sulphur and fine minerals from coal. Such pre-cleaning of coal is necessary in order to reduce the environmental and operational problems in power plants. The separation depends very much on particle surface properties, and the selectivity can be improved by addition of a reagent. Image analysis can be used to determine the amount of reagent, by using the relation between surface properties and froth bubble sizes. This work reports some improvements in the efficiency of the image analysis, and in determination of bubble diameter distribution towards developing froth-based flotation models. Ultimate benefit of the technique would allow a pre-determined reagent addition profile to be identified for controlling the separation process.

Introduction

Studies show that the performance of froth flotation is affected by the froth structure, and has a strong relationship with visual information of the froth surface (Pryor, 1965, Glembotskii, 1972; Cutting, Barber, & Newton, 1986; McKee, 1990). The determination of the froth structure, therefore, plays a vital role for controlling the process (Sadr-Kazemi & Cilliers, 1997; Banford, Aktas, & Woodburn, 1998). Some progresses have been made in determining metallurgical parameters that influence surface froth appearance, and in image analysis of flotation froths (Banford, 1996, Holtham & Nguyen, 2002). However, looking at even the recent reports, there seems to be difficulties, such as computational complexity and incorrect edge detection, to overcome. This work intends to develop a pixel tracing technique for off-line image analysis to determine the size distribution of froth. Although image analysis has been previously reported as a simple and robust means of determining froth structure (Biland, 1987, Wiklund & Granlund, 1987), the present work provides some improvements in this perspective.

Section snippets

Image analysis technique

Images were recorded by a camera over the flotation cell, where Zonguldak bituminous coal was used. Each image as shown in exemplary Fig. 1 is, then considered to be a matrix of dimensions m×n. Each element or pixel of this matrix is the brightness intensity scaled from 0 to 255 (8 bits/pixel).

On high solids concentrations, the froth structure is sticky and the bubbles have large elliptical shapes (Moolman, Eksteen, Aldrich, & Van Deventer, 1996). To simplify the algorithm, froth shape is

Experimental

A Turkish bituminous coal from Zonguldak colliery was chosen for the investigation. The coal was first crushed to less than 5 mm diameter in a crusher. A ball mill was provided to achieve further particle size reduction. The milled sample was sieved and particles of less than 53 μm (for experiment 1) were collected and stored in sealed plastic bags. Some of the fraction of the feed coal (−53 μm) was re-milled in order to clarify the effects of finer particle size on froth structure, froth

Results and discussion

The tests were performed in the presence of Triton X-100 or its mixtures with MIBC at various ratios. A number of photographs taken at various time intervals during the experiment 1 (initial reagent loading: 0.9 mg/g coal) are shown in Fig. 9. As clearly shown from the images given in Fig. 9, the mean bubble diameters were smaller at the start of the experiments. However, the mean bubble diameter increased gradually towards the end of the tests. The results obtained from three tests were used in

Conclusion

The suggested image analysis method is coded and implemented in C language with a user interface, and consequently applied on the images taken in different times of froth flotation tests. The mean bubble diameters are calculated for each image. The cumulative grade, namely the purity of the final product is found experimentally for different times of the froth flotation. The relationship between the mean bubble diameter and the cumulative grade is represented by the fitted functions, hence for

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