Title
Fault diagnosis of a class of distributed parameter systems modeled by parabolic partial differential equations
Abstract
In this paper, a partial differential equation (PDE) representation of a system is directly utilized to construct a fault diagnosis observer for distributed parameter systems (DPS) in contrast with the traditional fault detection observers which are based on the approximated ordinary differential equation (ODE) representation of the system. A fault is detected by comparing the detection residual, which is the difference between measured and estimated outputs, with a predefined detection threshold. Once the fault is detected, an online approximator is activated to learn the fault function. The stability of the observer along with the online approximator is discussed analytically in the paper. Upon detecting a fault, the estimated fault parameters are compared with their failure thresholds to provide an estimate time to failure (TTF) of the system. The scheme is verified in simulations on a Lithium-ion battery which is described by parabolic PDEs.
Year
DOI
Venue
2014
10.1109/ACC.2014.6858836
American Control Conference
Keywords
Field
DocType
distributed parameter systems,failure analysis,fault diagnosis,observers,parabolic equations,partial differential equations,ODE representation,TTF,detection residual,distributed parameter systems,failure thresholds,fault detection,fault diagnosis observer,fault function,fault parameter estimation,lithium-ion battery,online approximator,ordinary differential equation,parabolic PDE,parabolic partial differential equations,predefined detection threshold,stability,time to failure estimate,Distributed parameter systems,Estimation,Fault detection/accommodation
Control theory,Computer science,Control engineering,Distributed parameter system,Partial differential equation,Parabola
Conference
ISSN
ISBN
Citations 
0743-1619
978-1-4799-3272-6
1
PageRank 
References 
Authors
0.45
5
2
Name
Order
Citations
PageRank
Hasan Ferdowsi1464.35
Sarangapani Jagannathan2113694.89