A Scalable Jointree Algorithm for Diagnosability

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A Scalable Jointree Algorithm for Diagnosability
Diagnosability is an essential property that determines how accurate any diagnostic reasoning can be on a system given any sequence of observations. An unobservable fault event in a discrete-event system is diagnosable iff its occurrence can always be deduced once sufficiently many subsequent observable events have occurred. A classical approach to diagnosability checking constructs a finite state machine known as a twin plant for the system, which has a critical path iff some fault event is not diagnosable. Recent work attempts to avoid the often impractical construction of the global twin plant by exploiting system structure. Specifically, local twin plants are constructed for components of the system, and synchronized with each other until diagnosability is decided. Unfortunately, synchronization of twin plants can remain a bottleneck for large systems; in the worst case, in particular, all local twin plants would be synchronized, again producing the global twin plant. We solve the...
Anika Schumann, Jinbo Huang
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2008
Where AAAI
Authors Anika Schumann, Jinbo Huang
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