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Monitoring a Secondary Settler Using Gaussian Mixture Models
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-8034-4043
Uppsala University. (IVL Swedish Environmental Research Institute)
Uppsala University. (Division of Systems and Control, Department of Information Technology)
2016 (English)Conference paper, Abstract (Refereed)
Abstract [en]

This paper presents a method for monitoring the sludge profiles 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 methodfor 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 profile.

Place, publisher, year, edition, pages
Oulu, Finland, 2016.
Keyword [en]
signal monitoring, fault detection, clarifier, sludge profile
National Category
Remote Sensing
Research subject
Energy- and Environmental Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-32947OAI: oai:DiVA.org:mdh-32947DiVA: diva2:956099
Conference
9th Eurosim Congress on Modelling and Simulation
Funder
EU, FP7, Seventh Framework Programme, 315145
Available from: 2016-08-29 Created: 2016-08-29 Last updated: 2016-12-13Bibliographically approved

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