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Monitoring a Secondary Settler using Gaussian Mixture Models

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 artikelhttp://dx.doi.org/10.3384/ecp17142831

Ingår 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

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Publicerad: 2018-12-19

ISBN: 978-91-7685-399-3

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

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.

Nyckelord

signal monitoring, fault detection, clari?er, sludge pro?le

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