A new online fault prognosis on steam turbine generator set by using frequency trend feature of vibration signal

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	A new online fault prognosis on steam turbine generator set by using frequency trend feature of vibration signal
	Yan, Changfeng1 ; Wu, Lixiao1 ; Zhang, Hao 2
	2011-12-01
发表期刊	Journal of Information and Computational Science
ISSN	15487741
卷号	8 期号:16 页码:4023-4043
摘要	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 extracted 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 by several simulation examples and cases. The ability of anti-noise and precision of fault prognosis are also discussed in detail. © 2009 by Binary Information Press.
关键词	Computer simulation Fast Fourier transforms Steam Steam turbines Time series Turbines Turbogenerators Fault prognosis Significant test Sliding Window Steam turbine generator set Trend analysis
收录类别	EI
语种	英语
出版者	Binary Information Press, Flat F 8th Floor, Block 3, Tanner Garden, 18 Tanner Road, Hong Kong
EI入藏号	20120214672846
EI主题词	Vibration analysis
EI分类号	617.2 Steam Turbines - 705.2 Electric Generators - 723.5 Computer Applications - 921.3 Mathematical Transformations - 922.2 Mathematical Statistics - 943.2 Mechanical Variables Measurements
来源库	Compendex
分类代码	617.2 Steam Turbines - 705.2 Electric Generators - 723.5 Computer Applications - 921.3 Mathematical Transformations - 922.2 Mathematical Statistics - 943.2 Mechanical Variables Measurements
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/111590
专题	机电工程学院
作者单位	1.School of Mechanical and Electronical Engineering, Lanzhou University of Technology, Lanzhou 730050, China; 2.CIMS Research Center, Tongji University, Shanghai 200092, China
第一作者单位	兰州理工大学
第一作者的第一单位	兰州理工大学
推荐引用方式 GB/T 7714	Yan, Changfeng,Wu, Lixiao,Zhang, Hao. A new online fault prognosis on steam turbine generator set by using frequency trend feature of vibration signal[J]. Journal of Information and Computational Science,2011,8(16):4023-4043.
APA	Yan, Changfeng,Wu, Lixiao,&Zhang, Hao.(2011).A new online fault prognosis on steam turbine generator set by using frequency trend feature of vibration signal.Journal of Information and Computational Science,8(16),4023-4043.
MLA	Yan, Changfeng,et al."A new online fault prognosis on steam turbine generator set by using frequency trend feature of vibration signal".Journal of Information and Computational Science 8.16(2011):4023-4043.