Sensor Data Fusion as an Alternative for Monitoring Chlorate in Electrochlorination Applications
Edwin Ross,
Martijn Wagterveld,
Mateo Mayer,
Hans Stigter,
Bo Højris,
Yang Li and
Karel Keesman
Additional contact information
Edwin Ross: Wetsus, European Centre of Excellence for Sustainable Water Technology, Oostergoweg 9, 8911 MA Leeuwarden, The Netherlands
Martijn Wagterveld: Wetsus, European Centre of Excellence for Sustainable Water Technology, Oostergoweg 9, 8911 MA Leeuwarden, The Netherlands
Mateo Mayer: EasyMeasure B.V., Breestraat 22, 3811 BJ Amersfoort, The Netherlands
Hans Stigter: Mathematical and Statistical Methods-Biometris, Wageningen University and Research, 6700 AA Wageningen, The Netherlands
Bo Højris: Grundfos Holding A/S, Poul Due Jensens Vej 7, 8850 Bjerringbro, Denmark
Yang Li: Mathematical and Statistical Methods-Biometris, Wageningen University and Research, 6700 AA Wageningen, The Netherlands
Karel Keesman: Wetsus, European Centre of Excellence for Sustainable Water Technology, Oostergoweg 9, 8911 MA Leeuwarden, The Netherlands
Sustainability, 2022, vol. 14, issue 10, 1-15
Abstract:
As chlorate concentrations have been found to be harmful to human and animal health, governments are increasingly demanding strict control of the chlorate concentration in drinking water. Since there are no chlorate sensors available, the current solution is sampling and laboratory analysis. This is costly and time consuming. The aim of this work was to investigate Sensor Data Fusion (SDF) as an alternative approach, with a focus on chlorate formation in the electrochlorination process, and design an observer for the real-time estimation of chlorate. The pH, temperature and UV-a absorption were measured in real time. A reduced-order nonlinear model was derived, and it was found to be detectable. An Extended Kalman Filter (EKF), based on this model, was then used to estimate the chlorate formation. The EKF algorithm was verified experimentally and was found to be capable of accurately estimating chlorate concentrations in real time. Electrochlorination is an emerging and efficient method of disinfecting drinking water. Soft sensing of chlorate concentrations, as proposed in this paper, may help to better control and manage the process of electrochlorination.
Keywords: sensor data fusion; electrochlorination; oxychlorides; chlorate; observer; Extended Kalman Filter; soft sensor; monitoring (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/2071-1050/14/10/6119/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/10/6119/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:10:p:6119-:d:818251
Access Statistics for this article
Sustainability is currently edited by Ms. Alexandra Wu
More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().