Fault Modeling for Monitoring and Diagnosis of Sensor-Rich Hybrid Systems
X. Koutsoukos, F. Zhao, H. Haussecker, J. Reich, and P. Cheung
Proceedings of the 40th IEEE Conference on Decision and Control,
pp. 793-801, Orlando, FL, December 2001.
Abstract -- This paper presents a framework for modeling
faults in hybrid systems
that leads to an efficient approach for monitoring and diagnosis of
real-time embedded systems. We describe a fault parameterization
based on hybrid automata models and consider both abrupt failures
and gradual degradation of system components.
%Recent advances in micro-machined
%sensors and electronics enable us to build sensor-rich environments
%consisting of a large number of sensors such as microphones scattered
%or embedded inside a system. Monitoring and diagnosis in a such a
%sensor-rich environment requires the collaborative processing of
%high-volume distributed sensor data in an efficient manner.
Our approach also addresses the computational problem of coping with
large amount of sensor data by using a discrete event model of the
system so as to focus distributed signal analysis on when and where
to look for signatures of interest. The approach has been demonstrated
for the on-line diagnosis of a hybrid system, the Xerox DC265 printer.