Data quality assurance in monitoring of wastewater quality: Univariate on-line and off-line methods

J. Alferes, P. Poirier, C. Lamaire-Chad, Anitha Kumari Sharma, Peter Steen Mikkelsen, P. A. Vanrolleghem

Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review

162 Downloads (Pure)

Abstract

To make water quality monitoring networks useful for practice, the automation of data collection and data validation still represents an important challenge. Efficient monitoring depends on careful quality control and quality assessment. With a practical orientation a data quality assurance procedure is presented that combines univariate off-line and on-line methods to assess water quality sensors and to detect and replace doubtful data. While the off-line concept uses control charts for
quality control, the on-line methods aim at outlier and fault detection by using autoregressive models. The proposed tools were successfully tested with data sets collected at the inlet of a primary clarifier,where probably the toughest measurement conditions are found in wastewater treatment plants.
Original languageEnglish
Publication date2013
Number of pages1
Publication statusPublished - 2013
Event11th IWA conference on instrumentation control and automation - Narbonne, France
Duration: 18 Sep 201320 Sep 2013
http://www1.montpellier.inra.fr/ica2013/

Conference

Conference11th IWA conference on instrumentation control and automation
CountryFrance
CityNarbonne
Period18/09/201320/09/2013
Internet address

Keywords

  • Data quality assessment
  • On-line wastewater monitoring
  • Univariate methods

Cite this

Alferes, J., Poirier, P., Lamaire-Chad, C., Sharma, A. K., Mikkelsen, P. S., & Vanrolleghem, P. A. (2013). Data quality assurance in monitoring of wastewater quality: Univariate on-line and off-line methods. Abstract from 11th IWA conference on instrumentation control and automation, Narbonne, France.