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Outlining Process Monitoring and Fault Detection in a Wastewater Treatment and Reuse System
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-3097-459x
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-3131-0285
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-3485-5440
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2020 (English)In: European Control Conference 2020, ECC 2020, Institute of Electrical and Electronics Engineers Inc. , 2020, p. 558-563Conference paper, Published paper (Refereed)
Abstract [en]

Process control is an important part of any industrial system. In a wastewater reuse system this remains true. Process monitoring and fault detection (FD) are important to ensure that the control system has access to reliable data which can be used in making decisions about the operation of the process. The reuse scenario being considered in this work is that of utilizing the nutrients from the wastewater as fertilizer to agricultural soil along with using the water for irrigation purposes. This paper identifies variables that are important to the control of the process and should be a focus of monitoring and FD. In wastewater treatment these variables include temperatures, pressures, liquid levels, flow rates, pH, conductivity, biomass content, suspended solids concentration, dissolved oxygen content, total organic carbon, and the concentrations of nitrate and ammonium. The variables of interest in the reuse of nutrients and water for agriculture include soil moisture, ambient conditions, plant height, biomass content, photosynthetic activity of the crop, leaf area and leaf water content, as well as the concentrations of several ions both in the soil and in the plant. Challenges associated with process monitoring and FD specific to the two processes are also discussed, examples of these are the high dimensionality of the problem, the harsh conditions that sensors must operate in and the non-linear relationships between variables. This information will be used in future work when comparing specific FD methods to ensure that methods chosen are capable of overcoming the commonly encountered problems.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2020. p. 558-563
Keywords [en]
Access control, Agricultural robots, Agriculture, Biochemical oxygen demand, Dissolved oxygen, Fault detection, Finite difference method, Nitrogen removal, Nutrients, Organic carbon, Process monitoring, Soil moisture, Wastewater reclamation, Wastewater treatment, Water conservation, Water content, Ambient conditions, Dissolved oxygen contents, High dimensionality, Non-linear relationships, Photosynthetic activity, Total Organic Carbon, Wastewater reuse system, Wastewater treatment and reuse, Process control
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-52658ISI: 000613138000098Scopus ID: 2-s2.0-85090125781ISBN: 9783907144015 (print)OAI: oai:DiVA.org:mdh-52658DiVA, id: diva2:1502325
Conference
18th European Control Conference, ECC 2020; Saint Petersburg; Russian Federation; 12 May 2020 through 15 May 2020; Category numberCFP1990U-USB; Code 161942
Available from: 2020-11-19 Created: 2020-11-19 Last updated: 2022-11-30Bibliographically approved
In thesis
1. Fault Detection in Wastewater Treatment: Process Supervision to Improve Wastewater Reuse
Open this publication in new window or tab >>Fault Detection in Wastewater Treatment: Process Supervision to Improve Wastewater Reuse
2023 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

As wastewater treatment plants transition to water resource recovery facilities, the need for improved control and consequently supervision increases. Despite the large volume of research that has been performed on this topic, the use in industry is scarce. Practical implementation is challenging due to the nature of the process, and a lack of standardisation in the research results in uncertainty as to the state of the art. This is one of the main challenges identified. 

Experimental work is performed using the Benchmark Simulation Model No. 1 to identify monitoring requirements and evaluate the performance of univariate fault detection methods. For the former, residual based process fault signatures are used to determine minimal sensor requirements based on detectability and isolability goals. Sensor faults are the focus of the latter issue, using the Shewhart, cumulative sum, and exponentially weighted moving average control charts to detect bias and drift faults in a controlled variable sensor. 

The use of a standard model and known fault detection methods is useful to establish a baseline for future work. Given the lack of standardised use in industry this is considered critical. Both proposed methods emphasise ease of visualisation which is beneficial for industrial implementation. 

Place, publisher, year, edition, pages
Västerås: Mälardalens universitet, 2023
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 332
Keywords
Wastewater treatment, Process supervision, Fault Detection
National Category
Environmental Engineering
Research subject
Energy- and Environmental Engineering
Identifiers
urn:nbn:se:mdh:diva-61078 (URN)978-91-7485-575-3 (ISBN)
Presentation
2023-01-27, Delta, Mälardalens universitet, Västerås, 09:30 (English)
Opponent
Supervisors
Available from: 2022-12-01 Created: 2022-11-30 Last updated: 2023-01-09Bibliographically approved

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Marais, Heidi L.Nordlander, EvaThorin, EvaDahlquist, ErikOdlare, Monica

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