Abstract
Rotor of rotating machinery is the highly damaged part. Fault of 7 different types was confirmed as the main causes of rotor damage from the pump failure history data in domestic and U.S. nuclear. For each fault types, simulation testing was performed and fault signals were collected form the sensors. To calculate the statistical parameters of time-domain & frequency-domain, measured signals were analyzed by using the discrete wavelet transform, fast fourier transform, statistical analysis. Total 84 parameters were obtained. And Effectiveness factor were used to evaluate the discrimination capacity of each parameter. From the effectiveness factor, RAW-P4/RAW-P7/WT2-NNL/WT2-EE/WT1-P1 showed high ranking. Finally, these parameters were selected as the feature parameters of intelligent fault diagnostics for rotor.
