Fault Detection and Diagnosis Approach based on Observers and SVD-PCA

Authors

Abstract

In this paper, a new combined approach for fault
detection and diagnosis (FDD) of abrupt additive actuator and
sensor faults, based on Kalman observer (KFO), on sliding
mode observers (SMO), on singular values decomposition (SVD),
and on principal component analysis (PCA), is proposed. The
main contribution is the combined approach proposed for FDD
based on ratios between singular values of the adaptive slidingwindow
SVD-PCA model and on an improved SMO observer that
estimates the faults magnitude. In order to show the performance,
simulation results with a DTS-200 benchmark linear model are
presented.

Conference

2015 IEEE International Conference on Industrial Technology, March 2015

DOI