Diagnosis and Importance Analysis Diagnosis and Importance Analysis
Figure 1. Graphical Model for Low Pressure Coolant Injection
System with no assertions.
To do this, we will look at a different view of the graphical model, the directed graph view, shown in Figure~1. This view hides all of the rules, we are just looking at the variables. Notice that all of the variable nodes are now colored according to their failure probability. Variables with high failure probability are red, those with low failure probability are blue. As this is a very reliable system, every component and subsystem variable is blue.
To the left of the model graph is a selection of "drop on tools." To perform an action on a variable, the analyst simply drags the tool icon and drops it over the appropriate variable. So to find out information about the system conditioned on system failure, we drag the "assert failure" tool over the "LPCI-Sys" variable node. Graphical-Belief recalculates the probability of each variable and displays Figure~2.
Assert System Failure Continue with this
example and see the effect of conditioning on system failure.
Return to
the main example page.
Back to overview of Graphical-Belief.
View a list
of Graphical-Belief in publications and downloadable technical
reports.
The Graphical-Belief user
interface is implemented in Garnet.
Get more
information about obtaining Graphical-Belief (and why
it is not generally available).
get
the home page for Russell Almond , author
of Graphical-Belief.
Click
here to get to the home page for Insightful (the company that StatSci
has eventually evolved into).