Steam Turbine Vibration Fault Diagnosis Using Rough Sets and Bayesian Network
Pu Han · Turbine Technology · 2008
According to complementary strategy,a new turbine vibration fault diagnosis method based on rough sets(RS) theory and Bayesian network(BN) is presented for fault diagnosis containing redundancy and uncertain information.Through reduction approach of RS information table to simplify fault symptoms.The minimal diagnostic rules can be obtained.According to the minimal rules,complexity of BN structure are largely decreased.At the same time,the potential relationship between nodes can be discovered by BN,which can solve the uncertainty reasoning of fault diagnosis.Finally,the effectiveness of this method are validated by the result of practical fault diagnosis examples.