Dynamic Test Selection for Reconfigurable Diagnosis
Detecting and isolating multiple faults is a computationally intense
task which typically consists of computing a set of tests,
and then computing the diagnoses based on the test results. This paper
proposes a method to reduce the computational burden by only running
the tests that are currently needed, and dynamically starting new
tests when the need changes. A main contribution is a method to select
tests such that the computational burden is reduced while maintaining
the isolation performance of the diagnostic system. Key components in
the approach are the test selection algorithm, the test initialization
procedures, and a knowledge processing framework that supports the
functionality needed. The approach is exemplified on a relatively
small dynamical system, which still illustrates the complexity and
possible computational gain with the proposed approach.
Mattias Krysander, Fredrik Heintz, Jacob Roll and Erik Frisk
47th IEEE Conference on Decision and Control,
2008
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