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Journal article · Conference paper

Software sensors based on the grey-box modelling approach

From

Department of Environmental Science and Engineering, Technical University of Denmark1

In recent years the grey-box modelling approach has been applied to wastewater transportation and treatment Grey-box models are characterized by the combination of deterministic and stochastic terms to form a model where all the parameters are statistically identifiable from the on-line measurements.

With respect to the development of software sensors, the grey-box models possess two important features. Firstly, the on-line measurements can be filtered according to the grey-box model in order to remove noise deriving from the measuring equipment and controlling devices. Secondly, the grey-box models may contain terms which can be estimated on-line by use of the models and measurements.

In this paper, it is demonstrated that many storage basins in sewer systems can be used as an on-line flow measurement provided that the basin is monitored on-line with a level transmitter and that a grey-box model for the specific dynamics is identified. Similarly, an on-line software sensor for detecting the occurrence of backwater phenomena can be developed by comparing the dynamics of a flow measurement with a nearby level measurement.

For treatment plants it is found that grey-box models applied to on-line ammonia measurements from the aeration tank of an alternating plant provide information on the incoming ammonia load It is also shown how measurements of the return sludge concentration from a secondary clarifier can be filtered to minimize the effect of the scraper.

Thus, important information can be derived from on-line measurements if the appropriate grey-box model for the specific system is identified. Copyright (C) 1996 IAWQ.

Language: English
Year: 1996
Pages: 117-126
Proceedings: Proceedings of the 1995 IAWQ Specialized Conference on Sensors in Wastewater Technology
ISSN: 19969732 and 02731223
Types: Journal article and Conference paper
DOI: 10.1016/0273-1223(96)00164-3
ORCIDs: 0000-0003-0016-6118

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