Diagnosing Intermittent and Persistent Faults using Static Bayesian Networks



Brian W. Ricks Ole J. Mengshoel


Both intermittent and persistent faults may occur in a wide range of systems. We present in this paper the introduction of intermittent fault handling techniques into ProDiagnose, an algorithm that previously only handled persistent faults. We discuss novel algorithmic techniques as well as how our static Bayesian networks help diagnose, in an integrated manner, a range of intermittent and persistent faults. Through experiments with data from the ADAPT electrical power system test bed, generated as part of the Second International Diagnostic Competition (DXC-10), we show that this novel variant of ProDiagnose diagnoses intermittent faults accurately and quickly while maintaining strong performance on persistent faults.

How to Cite

W. Ricks, B., & J. Mengshoel, O. . (2010). Diagnosing Intermittent and Persistent Faults using Static Bayesian Networks. Annual Conference of the PHM Society, 2(2). https://doi.org/10.36001/phmconf.2010.v2i1.1952
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