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Horizontal vacuum belt filters are used for continuous solid–liquid separation in a wide variety of industrial processes. Despite the low pressure difference (usually Δp

The energy consumption of vacuum filtration operations in cake filtration depends on the properties of the cake, the filtration conditions applied, and the progress of the cake dewatering process. Operating a vacuum filter at a high pressure difference requires a high air flow rate and thus has high energy consumption. By taking the filtered solids content into consideration together with the power demand and energy consumed at a certain pressure difference level, it is possible to investigate the specific power demand and energy consumption relative to the filtered cake solids content. When the mother liquor in the void space of the filter cake is replaced by air, the flow rate of air through the cake increases, which has a dramatic influence on the specific energy consumption. In this study, dewatering of calcite mine tailings is investigated with respect to the specific power demand and energy consumption of vacuum generation calculated using the assumption of an ideal isentropic process. The results of this study demonstrate clearly that both the air flow rate and the specific energy consumption in dewatering increase sharply after a certain solid content of the cake is reached. The results suggest that pumping costs in vacuum filtration can be reduced substantially by allowing a slight increase in the residual moisture content of the filter cake.

The moisture content of filter cakes is probably the most important characteristic that should be kept at a desired level in industrial cake filtration applications to maintain consistent product quality and minimize energy consumption. Most of the currently applied methods for contactless real-time monitoring of the moisture content are based for example on x-ray or microwave techniques, and therefore, the equipment for the purpose is highly specialized. This paper introduces a novel soft sensor for filter cake moisture estimation that uses machine learning algorithms and data collected with basic process instrumentation. The method is primarily based on the cooling effect observed in the cake and air, caused by evaporation of liquid from the cake during the dewatering period, and it can be supported by other process data. The specific energy consumption of vacuum filtration and the subsequent thermal drying to zero moisture is also analyzed. The results of pilot-scale experiments with calcite slurry and a horizontal belt vacuum filter show that in order to minimize the specific energy consumption of vacuum filtration, it is crucial to find the right combination of slurry concentration, vacuum level, and mass of filter cake per unit area. The proposed method for estimating the filter cake moisture content is especially suitable for real-time monitoring and control, enabling also considerable reduction in the energy consumption of the overall process. When applying the proposed soft sensor method in a pilot-scale process, the mean absolute error of the estimated moisture content of the filter cake is ∼0.4 percentage points when the temperature of air at the vacuum pump inlet and the vacuum pump air flow rate are included in the input variables. Post-print / Final draft