QQ客服 官方微博 反馈留言

	Support vector machines-based fault diagnosis for turbo-pump rotor
	Yuan, SF ; Chu, FL
	2010-05-10 ; 2010-05-10
关键词	fault diagnosis support vector machines turbo pump rotor RECOGNITION CLASSIFICATION Engineering, Mechanical
中文摘要	Most artificial intelligence methods used in fault diagnosis are based on empirical risk minimisation principle and have poor generalisation when fault samples are few. Support vector machines (SVM) is a new general machine-learning tool based on structural risk minimisation principle that exhibits good generalisation even when fault samples are few. Fault diagnosis based on SVM is discussed. Since basic SVM is originally designed for two-class classification, while most of fault diagnosis problems are multi-class cases, a new multi-class classification of SVM named 'one to others' algorithm is presented to solve the multi-class recognition problems. It is a binary tree classifier composed of several two-class classifiers organised by fault priority, which is simple, and has little repeated training amount, and the rate of training and recognition is expedited. The effectiveness of the method is verified by the application to the fault diagnosis for turbo pump rotor. (c) 2005 Elsevier Ltd. All rights reserved.
语种	英语 ; 英语
出版者	ACADEMIC PRESS LTD ELSEVIER SCIENCE LTD ; LONDON ; 24-28 OVAL RD, LONDON NW1 7DX, ENGLAND
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/24758]
专题	清华大学
推荐引用方式 GB/T 7714	Yuan, SF,Chu, FL. Support vector machines-based fault diagnosis for turbo-pump rotor[J],2010, 2010.
APA	Yuan, SF,&Chu, FL.(2010).Support vector machines-based fault diagnosis for turbo-pump rotor..
MLA	Yuan, SF,et al."Support vector machines-based fault diagnosis for turbo-pump rotor".(2010).

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。