A statistical approach to multivariate measurement validation

Article type: Research Article

Authors: Fry, Andrew J.

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

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.

Keywords: sensor validation, uncertainties, fault detection, temperature measurement

DOI: 10.3233/IDA-2001-5206

Journal: Intelligent Data Analysis, vol. 5, no. 2, pp. 165-188, 2001