TY - GEN
T1 - Exploiting causal structure in the refined diagnosis of condition systems
AU - Ashley, Jeffrey
AU - Holloway, Lawrence E.
PY - 2006
Y1 - 2006
N2 - A condition system is a collection of Petri nets that interact with each other and the external environment through condition signals. Some of these condition signals may be unobservable. In previous work, fault diagnosis was defined in terms of observed behavior versus expected behavior of subsystem models, where the expected behavior is defined through condition system models, and approximate methods were presented for detection and diagnosis. We have also presented a method to determine a best possible diagnosis within the constraints of observability. However this method requires significant state space exploration. In this paper, we wish to exploit the causal structure imposed on the system by a partition of subsystem models in order to reduce (in certain situations) the amount of work required to perform a diagnosis.
AB - A condition system is a collection of Petri nets that interact with each other and the external environment through condition signals. Some of these condition signals may be unobservable. In previous work, fault diagnosis was defined in terms of observed behavior versus expected behavior of subsystem models, where the expected behavior is defined through condition system models, and approximate methods were presented for detection and diagnosis. We have also presented a method to determine a best possible diagnosis within the constraints of observability. However this method requires significant state space exploration. In this paper, we wish to exploit the causal structure imposed on the system by a partition of subsystem models in order to reduce (in certain situations) the amount of work required to perform a diagnosis.
UR - http://www.scopus.com/inward/record.url?scp=50149095628&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=50149095628&partnerID=8YFLogxK
U2 - 10.1109/ETFA.2006.355210
DO - 10.1109/ETFA.2006.355210
M3 - Conference contribution
AN - SCOPUS:50149095628
SN - 1424406811
SN - 9781424406814
T3 - IEEE International Conference on Emerging Technologies and Factory Automation, ETFA
SP - 364
EP - 371
BT - 2006 IEEE Conference on Emerging Technologies and Factory Automation, ETFA
T2 - 2006 IEEE Conference on Emerging Technologies and Factory Automation, ETFA
Y2 - 20 September 2006 through 22 September 2006
ER -