A1 Journal article (refereed), original research

Real-time monitoring of the moisture content of filter cakes in vacuum filters by a novel soft sensor


Open Access publication

Publication Details
Authors: Huttunen Manu, Nygren Lauri, Kinnarinen Teemu, Ekberg Bjarne, Lindh Tuomo, Karvonen Vesa, Ahola Jero, Häkkinen Antti
Publisher: Elsevier
Publication year: 2019
Language: English
Related Journal or Series Information: Separation and Purification Technology
Volume number: 223
Start page: 282
End page: 291
Number of pages: 10
ISSN: 1383-5866
eISSN: 1873-3794
JUFO-Level of this publication: 2
Open Access: Open Access publication
Location of the parallel saved publication: http://urn.fi/URN:NBN:fi-fe2019110536726

Abstract

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.


Last updated on 2020-20-03 at 10:03