In this section
@inproceedings{Boem:2015:10.1109/CDC.2015.7402918,
author = {Boem, F and Parisini, T},
doi = {10.1109/CDC.2015.7402918},
pages = {4474--4479},
publisher = {IEEE},
title = {Distributed model-based fault diagnosis with stochastic uncertainties},
url = {http://dx.doi.org/10.1109/CDC.2015.7402918},
year = {2015}
}
TY - CPAPER
AB - This paper proposes a novel distributed fault detection and isolation approach for the monitoring of non linear large-scale systems. The proposed architecture considers stochastic characterization of the measurement noises and modeling uncertainties, computing at each step stochastic time-varying thresholds with guaranteed false alarms probability levels. The convergence properties of the distributed estimation are demonstrated. A novel fault isolation method is proposed basing on a Generalized Observer Scheme, providing guaranteed error probabilities of the fault exclusion task. A consensus approach is used for the estimation of variables shared among more than one subsystem; a method is proposed to define the time-varying consensus weights in order to minimize at each step the variance of the uncertainty of the fault detection and isolation thresholds. Detectability and isolability conditions are provided.
AU - Boem,F
AU - Parisini,T
DO - 10.1109/CDC.2015.7402918
EP - 4479
PB - IEEE
PY - 2015///
SN - 0743-1546
SP - 4474
TI - Distributed model-based fault diagnosis with stochastic uncertainties
UR - http://dx.doi.org/10.1109/CDC.2015.7402918
UR - http://hdl.handle.net/10044/1/39118
ER -