This page cannot be printed from here

Please use the dedicated print option from the 'view' drop down menu located in the blue ribbon in the top, right section of the publication.

screenshot of print menu option

Description: Soft-Sensor Application to Improve Ammonium Sensor Robustness in WRRFs
Soft-Sensor Application to Improve Ammonium Sensor Robustness in WRRFs
Abstract
Wastewater is a harsh environment for any instrumentation, however sensors implementation is fundamental in Water Resource Recovery Facilities. The study focuses on DO, pH, ORP, MLSS and ammonium sensors, with a specific attention on the last because of its promising application for ammonium-based aeration control. A software sensor is developed based on a Neural Network model with Principal Components Analysis as preprocessing of the raw data collected at a full-scale facility for a seasonal cycle. The soft-sensor predicts ammonium based on the other water quality data, to improve the hardware sensor robustness and enhance fault detection.
Wastewater is a harsh environment for any instrumentation, however sensors implementation is fundamental in Water Resource Recovery Facilities. The study focuses on DO, pH, ORP, MLSS and ammonium sensors, with a specific attention on the last because of its promising application for ammonium-based aeration control. A software sensor is developed based on a Neural Network model with Principal Components Analysis as preprocessing of the raw data collected at a full-scale facility for a seasonal cycle. The soft-sensor predicts ammonium based on the other water quality data, to improve the hardware sensor robustness and enhance fault detection.
SpeakerCecconi, Francesca
Presentation time
15:10:00
15:30:00
Session time
13:30:00
15:30:00
SessionNext Generation Data Analytics
Session number201
TopicFacility Operations and Maintenance, Intelligent Water, Municipal Wastewater Treatment Design, Research and Innovation
TopicFacility Operations and Maintenance, Intelligent Water, Municipal Wastewater Treatment Design, Research and Innovation
Author(s)
F. Cecconi,Y. ItoD. Rosso,
Author(s)F. Cecconi1; ,2; Y. Ito3; D. Rosso1; ,2;
Author affiliation(s)Department of Civil and Environmental Engineering, University of California, Irvine, CA1; Water-Energy Nexus Center, University of California2; Horiba Advanced Techno Co, Ltd.3
SourceProceedings of the Water Environment Federation
Document typeConference Paper
PublisherWater Environment Federation
Print publication date Oct 2020
DOI10.2175/193864718825157814
Volume / Issue
Content sourceWEFTEC
Copyright2020
Word count10

Purchase price $11.50

Get access