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PCA‐based fault diagnosis in the presence of control and dynamics
Author(s) -
Gertler Janos,
Cao Jin
Publication year - 2004
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.10035
Subject(s) - fault detection and isolation , redundancy (engineering) , control theory (sociology) , actuator , feedback control , system dynamics , engineering , control (management) , isolation (microbiology) , fault (geology) , control engineering , computer science , artificial intelligence , reliability engineering , microbiology and biotechnology , biology , seismology , geology
In PCA‐model‐based fault diagnosis, using the isolation enhancement approaches of analytical redundancy, mis‐isolation of some sensor and actuator faults may arise if the training data is collected under constant control. A detailed analysis is provided of how control actions affect PCA‐model‐based diagnosis. Ratio and feedback control in linear static and discrete dynamic systems, with full and partial PCA models is investigated. It is shown that all that it takes to eliminate the adverse effects is to vary the control set point (in feedback control) or the ratio coefficient (in ratio control) in the course of collecting the training data. © 2004 American Institute of Chemical Engineers AIChE J , 50: 388–402, 2004