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	Application of RBF and SOFM neural networks on vibration fault diagnosis for aero-engines
	Li, Kai ; Jiang, Dongxiang ; Xiong, Kai ; Ding, Yongshan
	2010-05-10 ; 2010-05-10
会议名称	ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 3, PROCEEDINGS ; 3rd International Symposium on Neural Networks (ISNN 2006) ; Chengdu, PEOPLES R CHINA ; Web of Science ; INSPEC
关键词	ROTATING MACHINERY Computer Science, Theory & Methods
中文摘要	This paper applies two ANN methods-RBF and SOFM on fault diagnosis for two-shaft aero-engines. Two-shaft aero-engines are complex rotating machines which have many components and high rotating speed. First we presented both the principles and advantages of RBF and SOFM neural networks. Second we described the fundamentals of two-shaft aero-engines vibration fault diagnosis, and then obtained the standard fault samples (training samples) and simulation samples (testing samples). Third we applied the two ANN methods to perform diagnosing. The accurate diagnostic results have proved the effectiveness of the RBF and SOFM methods for vibration fault diagnosis of two-shaft aero-engines. Finally, the relative advantages and disadvantages of the two ANN methods are contrasted, and suggestions can be obtained on when one might use one of the two methods.
会议录出版者	SPRINGER-VERLAG BERLIN ; BERLIN ; HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
语种	英语 ; 英语
内容类型	会议论文
源URL	[http://hdl.handle.net/123456789/19629]
专题	清华大学
推荐引用方式 GB/T 7714	Li, Kai,Jiang, Dongxiang,Xiong, Kai,et al. Application of RBF and SOFM neural networks on vibration fault diagnosis for aero-engines[C]. 见:ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 3, PROCEEDINGS, 3rd International Symposium on Neural Networks (ISNN 2006), Chengdu, PEOPLES R CHINA, Web of Science, INSPEC.

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