Evaluation of Qualitative Trend Analysis as a Tool for Automation

Christian M. Thürlimann; David J. Dürrenmatt; Kris Villez

doi:10.1016/B978-0-444-63576-1.50116-3

Evaluation of Qualitative Trend Analysis as a Tool for Automation

Christian M. Thürlimann, David J. Dürrenmatt, Kris Villez

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

4 Scopus citations

Abstract

Ammonium (NH₄ ⁺) load based aeration control on biological wastewater treatment plants saves costs and enhances nitrogen removal. However, the need for maintenance intensive NH4+ sensors hamper the controls application in practice. Alternatives, in the form of soft-sensors are broadly discussed in academia. A soft-sensor recently described in literature exploits the pH effects induced by biological NH₄ ⁺ oxidation. This concept is now further developed by means of qualitative trend analysis (QTA). Previously, the qualitative path estimation (QPE) algorithms was proposed as a fast and reliable QTA algorithm for batch process data analysis. It does not allow online application in continuous flow systems however. In this work, a modification of QPE, call qualitative state estimation (QSE), is proposed as a suitable algorithm for continuous-flow systems. Initial tests indicate that the QSE algorithms is a robust technique for extraction of relevant information in a full-scale environment. At the WWTP Hard in Winterthur, this resulted in cost-saving automation of the aeration system. This contribution summarizes these first results.

Original language	English
Title of host publication	Computer Aided Chemical Engineering
Publisher	Elsevier B.V.
Pages	2531-2536
Number of pages	6
DOIs	https://doi.org/10.1016/B978-0-444-63576-1.50116-3
State	Published - 2015
Externally published	Yes

Publication series

Name	Computer Aided Chemical Engineering
Volume	37
ISSN (Print)	1570-7946

Funding

This work was supported by the Commission for Technology and Innovation (CTI) of the Swiss Federal Department of Economic Affairs Education and Research (EAER). (CTI project no. 14351. PFIW-IW). The authors thank the staff of the WWTP Hard in Winterthur for the opportunity and assistance with this study.

Funders	Funder number
EAER	14351
Swiss Federal Department of Economic Affairs Education and Research
Kommission für Technologie und Innovation

Keywords

Ammonia control
Biological wastewater treatment
Hidden Markov model
Kernel regression
Process monitoring

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/B978-0-444-63576-1.50116-3

Cite this

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title = "Evaluation of Qualitative Trend Analysis as a Tool for Automation",

abstract = "Ammonium (NH4 +) load based aeration control on biological wastewater treatment plants saves costs and enhances nitrogen removal. However, the need for maintenance intensive NH4+ sensors hamper the controls application in practice. Alternatives, in the form of soft-sensors are broadly discussed in academia. A soft-sensor recently described in literature exploits the pH effects induced by biological NH4 + oxidation. This concept is now further developed by means of qualitative trend analysis (QTA). Previously, the qualitative path estimation (QPE) algorithms was proposed as a fast and reliable QTA algorithm for batch process data analysis. It does not allow online application in continuous flow systems however. In this work, a modification of QPE, call qualitative state estimation (QSE), is proposed as a suitable algorithm for continuous-flow systems. Initial tests indicate that the QSE algorithms is a robust technique for extraction of relevant information in a full-scale environment. At the WWTP Hard in Winterthur, this resulted in cost-saving automation of the aeration system. This contribution summarizes these first results.",

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doi = "10.1016/B978-0-444-63576-1.50116-3",

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AU - Dürrenmatt, David J.

AU - Villez, Kris

PY - 2015

Y1 - 2015

N2 - Ammonium (NH4 +) load based aeration control on biological wastewater treatment plants saves costs and enhances nitrogen removal. However, the need for maintenance intensive NH4+ sensors hamper the controls application in practice. Alternatives, in the form of soft-sensors are broadly discussed in academia. A soft-sensor recently described in literature exploits the pH effects induced by biological NH4 + oxidation. This concept is now further developed by means of qualitative trend analysis (QTA). Previously, the qualitative path estimation (QPE) algorithms was proposed as a fast and reliable QTA algorithm for batch process data analysis. It does not allow online application in continuous flow systems however. In this work, a modification of QPE, call qualitative state estimation (QSE), is proposed as a suitable algorithm for continuous-flow systems. Initial tests indicate that the QSE algorithms is a robust technique for extraction of relevant information in a full-scale environment. At the WWTP Hard in Winterthur, this resulted in cost-saving automation of the aeration system. This contribution summarizes these first results.

AB - Ammonium (NH4 +) load based aeration control on biological wastewater treatment plants saves costs and enhances nitrogen removal. However, the need for maintenance intensive NH4+ sensors hamper the controls application in practice. Alternatives, in the form of soft-sensors are broadly discussed in academia. A soft-sensor recently described in literature exploits the pH effects induced by biological NH4 + oxidation. This concept is now further developed by means of qualitative trend analysis (QTA). Previously, the qualitative path estimation (QPE) algorithms was proposed as a fast and reliable QTA algorithm for batch process data analysis. It does not allow online application in continuous flow systems however. In this work, a modification of QPE, call qualitative state estimation (QSE), is proposed as a suitable algorithm for continuous-flow systems. Initial tests indicate that the QSE algorithms is a robust technique for extraction of relevant information in a full-scale environment. At the WWTP Hard in Winterthur, this resulted in cost-saving automation of the aeration system. This contribution summarizes these first results.

KW - Ammonia control

KW - Biological wastewater treatment

KW - Hidden Markov model

KW - Kernel regression

KW - Process monitoring

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M3 - Chapter

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SP - 2531

EP - 2536

BT - Computer Aided Chemical Engineering

PB - Elsevier B.V.

ER -

Evaluation of Qualitative Trend Analysis as a Tool for Automation

Abstract

Publication series

Funding

Keywords

UN SDGs

Access to Document

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