Amplitude envelope analysis for feature extraction of power plant blower bearing failure

Bearing vibrations of a power plant blower have random characteristics with stark noise, which make it difficult for fault feature extraction both by using vibration effective data of monitoring system and vibration analysis function of a portable measuring instrument. Made use of the vibration signals which were measured from a normal blower and a fault one, the vibration characteristics of fault impeller rotor support bearing were analyzed and studied. From time domain, frequency domain and cepstrum domain, the vibration signal characteristics were analyzed and compared between normal and fault units. Then narrowband envelope analysis had been made. The difference of envelope spectrum for vibration signals between normal and fault units was revealed. The results show that narrowband envelope analysis can effectively identify the bearing fault state.

[1]  A.K. Nandi,et al.  Detection and Classification of Rolling-Element Bearing Faults using Support Vector Machines , 2005, 2005 IEEE Workshop on Machine Learning for Signal Processing.

[2]  Wang Peng.  The Analysis of Reliability Indicators for Auxiliary Equipment of Coal-fired Power Generation Units (200 MW and above) in 2002 , 2004 .

[3]  Xu Xi-ren.  Diagnosis of Fan Vibration-caused Failures and Measures taken to Cope with Them , 2006 .

[4]  Yibing Liu,et al.  Amplitude envelope analysis for feature extraction of direct-driven wind turbine bearing failure , 2012, WCICA 2012.

[5]  J. Cusido,et al.  Broken Bearings Fault Detection for a Permanent Magnet Synchronous Motor under non-constant working conditions by means of a Joint Time Frequency Analysis , 2007, 2007 IEEE International Symposium on Industrial Electronics.

[6]  Shi Linsuo,et al.  Roller bearing fault detection using improved envelope spectrum analysis based on EMD and spectrum kurtosis , 2011 .

[7]  Yibing Liu,et al.  Bispectrum analysis for feature extraction of pitting fault in wind turbine gearbox , 2010, 2010 IEEE International Conference on Mechatronics and Automation.

[8]  Yu De-jie.  Application of the envelope order spectrum based on the generalized demodulation time-frequency analysis to the gear fault diagnosis , 2009 .

[9]  Zhang Yu,et al.  Fault diagnosis for large-scale wind turbine rolling bearing using stress wave and wavelet analysis , 2005, 2005 International Conference on Electrical Machines and Systems.