loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: David Tena ; Ignacio Peñarrocha-Alós ; Roberto Sanchis and Rubén Moliner-Heredia

Affiliation: Industrial Systems Engineering and Design Department, Universitat Jaume I, Castelló, Spain

Keyword(s): Fault Detection, Waste Treatment, Optimal Filtering, Trade-offs.

Abstract: We develop a fault detection strategy for the output ammonium sensor present in wastewater treatment plants. The only assumed measurements are the output ammonium concentration, the aeration of the reactor and the incoming volumetric flow to the plant. The incoming ammonium concentration is not measured, resulting in an important source of uncertainty. We use a IIR model based on Volterra series for predicting the ammonium measurement and we design a fault detector based on a filter applied on the prediction error and a threshold comparator to decide whether the sensor is faulty or not. The faults in the sensor are assumed to produce a slowly decreasing gain due to dirtiness in its surface. The fault detector design is based on the trade-off between fault detection sensitivity and disturbance rejection (due to measurement noise and model uncertainty). The design parameters are based in understandable fault indices: time needed to detect the fault, gain deviation at the time of detect ion, and poured volume of ammonium until the fault is detected. We use the benchmark BSM1 to validate the results as a common frame in the study of waste water treatment plants. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.219.253.199

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Tena, D.; Peñarrocha-Alós, I.; Sanchis, R. and Moliner-Heredia, R. (2020). Ammonium Sensor Fault Detection in Wastewater Treatment Plants. In Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics - ICINCO; ISBN 978-989-758-442-8; ISSN 2184-2809, SciTePress, pages 681-688. DOI: 10.5220/0009875406810688

@conference{icinco20,
author={David Tena. and Ignacio Peñarrocha{-}Alós. and Roberto Sanchis. and Rubén Moliner{-}Heredia.},
title={Ammonium Sensor Fault Detection in Wastewater Treatment Plants},
booktitle={Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics - ICINCO},
year={2020},
pages={681-688},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009875406810688},
isbn={978-989-758-442-8},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics - ICINCO
TI - Ammonium Sensor Fault Detection in Wastewater Treatment Plants
SN - 978-989-758-442-8
IS - 2184-2809
AU - Tena, D.
AU - Peñarrocha-Alós, I.
AU - Sanchis, R.
AU - Moliner-Heredia, R.
PY - 2020
SP - 681
EP - 688
DO - 10.5220/0009875406810688
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic