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A Comparison Of Two Methods For Stochastic Fault Detection: The Parity Space Approach And Principal Components Analysis

By Anna Hagenblad, Fredrik Gustafsson and Inger Klein

Abstract

This paper compares two methods for fault detection and isolation in a stochastic setting. We assume additive faults on input and output signals, and stochastic unmeasurable disturbances. The first method is the parity space approach, analyzed in a stochastic setting

Topics: Fault detection, fault isolation, diagnosis, Kalman filtering, adaptive filters, linear systems, parity space, principal components analysis
Year: 2003
OAI identifier: oai:CiteSeerX.psu:10.1.1.11.4847
Provided by: CiteSeerX
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