In washability, the objective is to establish the set of maximum possible separation performance criteria for a given mineral feed. The method of choice for this has been the conventional sink– float analysis. Using traditional sink–float method it is not possible to sample and automatically measure. This fact, as well as time, cost and safety aspects, as well as required and manageable sample size of the sink–float method have prompted the search for a new approach for establishing separation performance criteria. This is especially important as performance levels of separator plants can be maximised if reliable information based on an analysis of washability in conjunction with particle size distribution, elemental constituency becomes available in time.
The new method to establish washability and associated performance information utilises at least two measurement technologies concurrently: single energy X-ray transmission and image processing. For porous or very inhomogeneous materials the results can be refined further by using dual energy X-ray transmission and image processing.
If used as a standard laboratory device the continuous build-up of the washability curve allows to evaluate the statistical significance of the sample size during measurement.
The measuring method can even be improved if it is combined with an automatic sampling system that feeds a continuous and representative particle stream to the analyser. Then the value of the collected data increases considerably since the washability data are additionally available in time to be considered in the control of the process plant. The washability curve can be derived and is continuously updated based on the particles measured during the past time interval. Older curves and results are stored in a database and can be retrieved for later reference. This technology now enables automated sampling and integrated automated measurement, which was previously not possible.
This incorporation of an automated washability monitor at a representative sample gives near real-time data that would impinge positively on the profitability of the plant operation. The method was extensively tested using a range of samples with different densities, varying from 1 g/cm3 (coal) to 5 g/cm3 (iron ore).
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Sampling and Blending , pp 213–218 (The Australasian Institute of Mining and Metallurgy: Melbourne).