Title :
Fault Prognosis of Steam Turbine Generator Set by Trend Analysis of Frequency
Author :
Yan, Changfeng ; Zhang, Hao ; Wu, Lixiao
Author_Institution :
CIMS Res. Center, Tongji Univ., Shanghai, China
Abstract :
A new fault prognosis method based on trend analysis of frequency component is proposed. The vibration signal of bearing or shaft of the steam turbo-generator set is transformed into frequency signal by Fast Fourier Transform. The different frequency components are classified according to sohre´s chart. The amplitudes of different frequency components are ranked by time series. The trend of each frequency component is analyzed in terms of polynomial fitting and significant level 0.05. A set of diagnostic relations induced mainly from sohre´s charts can be used to predict the fault based on the trend analysis of the frequency components. And the model is validated and discussed by a simulation example and a case.
Keywords :
fast Fourier transforms; fault diagnosis; polynomials; steam turbines; fast Fourier transform; fault prognosis; frequency trend analysis; polynomial fitting; steam turbine generator Set; fault prognosis; significant test; sliding window and top-down algorithm; steam turbine generator set; trend analysis of frequency;
Conference_Titel :
Future Power and Energy Engineering (ICFPEE), 2010 International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-7378-6
Electronic_ISBN :
978-1-4244-7379-3
DOI :
10.1109/ICFPEE.2010.22
