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Disturbance detection in wastewater treatment plants

Rosén, Christian LU and Olsson, Gustaf LU (1998) In Water Science and Technology 37(12). p.197-205
Abstract
The development in sensor technology has made many wastewater treatment systems data rich but not necessarily information rich. To extract the adequate information from several sensors is not trivial, and it is not sufficient to consider only the time series. Different tools for detecting unusual on-line measurement data and deviating process behaviour are discussed. In this paper various dimension reduction as well as advanced filtering methods are considered in order to extract adequate information for fault detection and diagnosis. Both the operator and the process engineer can take advantage of such methods for proper monitoring of the plant, in particular extreme events and their causes.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Data analysis, detection, diagnosis, monitoring, multivariate analysis, principal component analysis (PCA), projection to latent structures (PLS)
in
Water Science and Technology
volume
37
issue
12
pages
197 - 205
publisher
IWA Publishing
external identifiers
  • Scopus:0031757693
ISSN
0273-1223
DOI
10.1016/S0273-1223(98)00372-2
language
English
LU publication?
yes
id
ba42dd77-84c7-4bb0-9c26-6054e9cfb7d6 (old id 4358635)
alternative location
http://www.sciencedirect.com/science/article/pii/S0273122398003722
date added to LUP
2014-03-10 13:44:20
date last changed
2016-12-04 04:37:29
@misc{ba42dd77-84c7-4bb0-9c26-6054e9cfb7d6,
  abstract     = {The development in sensor technology has made many wastewater treatment systems data rich but not necessarily information rich. To extract the adequate information from several sensors is not trivial, and it is not sufficient to consider only the time series. Different tools for detecting unusual on-line measurement data and deviating process behaviour are discussed. In this paper various dimension reduction as well as advanced filtering methods are considered in order to extract adequate information for fault detection and diagnosis. Both the operator and the process engineer can take advantage of such methods for proper monitoring of the plant, in particular extreme events and their causes.},
  author       = {Rosén, Christian and Olsson, Gustaf},
  issn         = {0273-1223},
  keyword      = {Data analysis,detection,diagnosis,monitoring,multivariate analysis,principal component analysis (PCA),projection to latent structures (PLS)},
  language     = {eng},
  number       = {12},
  pages        = {197--205},
  publisher    = {ARRAY(0xb7d4c20)},
  series       = {Water Science and Technology},
  title        = {Disturbance detection in wastewater treatment plants},
  url          = {http://dx.doi.org/10.1016/S0273-1223(98)00372-2},
  volume       = {37},
  year         = {1998},
}