A statistical approach to multivariate measurement validation

  • Authors:
  • Andrew J. Fry

  • Affiliations:
  • Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK. Fax: +44 1865 273906/ E-mail: andrew.fry@eng.ox.ac.uk

  • Venue:
  • Intelligent Data Analysis
  • Year:
  • 2001

Quantified Score

Hi-index 0.00

Visualization

Abstract

The fusion of uncertain sensory information into multivariate measurement systems is explored from a classical measurement perspective. The issue of sensor validation in multivariate measurement systems using data-driven statistical uncertainty models is investigated. An online approach is motivated for the detection, isolation and rectification of measurement anomalies within a class of redundant process measurement systems. The procedure nominally allows for the control of validation false-positive alarms whilst detecting incipient sensor anomalies within redundant process sensor networks. Experimental results from a set of thermocouples are presented.