Jesús Zambrano
School of Business, Society and Engineering, Mälardalen University, Box 883, 72123 Västerås, Sweden
Oscar Samuelsson
IVL Swedish Environmental Research Institute, P.O. Box 210 60, 10031 Stockholm, Sweden / Department of Information Technology, Uppsala University, Box 337, 75105 Uppsala, Sweden
Bengt Carlsson
Department of Information Technology, Uppsala University, Box 337, 75105 Uppsala, Sweden
Ladda ner artikel
http://dx.doi.org/10.3384/ecp17142831Ingår i: Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016
Linköping Electronic Conference Proceedings 142:122, s. 831-835
Publicerad: 2018-12-19
ISBN: 978-91-7685-399-3
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
This paper presents a method for monitoring the sludge pro?les of a secondary settler using a Gaussian Mixture Model (GMM). A GMM is a parametric probability density function represented as a weighted sum of Gaussian components densities. To illustrate this method, the current approach is applied using real data from a sensor measuring the sludge concentration as a function of the settler level at a wastewater treatment plant (WWTP) in Bromma, Sweden. Results suggest that the GMM approach is a feasible method for monitoring and detecting possible disturbances of the process and fault situations such as sensor clogging. This approach can be a valuable tool for monitoring processes with a repetitive pro?le.
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