Dynamic Bayesian Network Factors from Possible Conflicts for Continuous System Diagnosis

  title={Dynamic Bayesian Network Factors from Possible Conflicts for Continuous System Diagnosis},
  author={Carlos J. Alonso and Noemi Moya Alonso and Gautam Biswas},
This paper introduces a factoring method for Dynamic Bayesian Networks (DBNs) based on Possible Conflicts (PCs), which aim to reduce the computational burden of Particle Filter inference. Assuming single fault hypothesis and known fault modes, the method allows performing consistency based fault detection, isolation and identification of continuous dynamic systems, with the unifying formalism of DBNs. The three tank system benchmark has been used to illustrate the approach. Two fault scenarios… CONTINUE READING
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