An Efficient Algorithm for Finding Minimal Over-constrained Sub-systems for Model-based Diagnosis
In model based diagnosis, the diagnostic system construction is based
on a model of the technical system to be diagnosed. To handle large
differential algebraic models and to achieve fault isolation, a
common strategy is to pick out small over-constrained parts of the
model and to test these separately against measured signals. A new
algorithm for computing all minimal over-constrained sub-systems in a
model is proposed. For complexity comparison, previous algorithms are
recalled. It is shown that the time complexity under certain
conditions is much better for the new algorithm. This is illustrated
using a truck engine model.
Mattias Krysander, Jan Åslund and Mattias Nyberg
IEEE Transactions on Systems, Man, and Cybernetics -- Part A: Systems and Humans,
2008
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