QQ客服 官方微博 反馈留言

	Rolling element bearing fault diagnosis based on multi-scale global fuzzy entropy, multiple class feature selection and support vector machine
	Zhu, Keheng; Chen, Liang; Hu, Xiong
刊名	TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
	2019
卷号	41页码:4013-4022
关键词	Multi-scale global fuzzy entropy multiple class feature selection rolling element bearing fault diagnosis
ISSN号	0142-3312
URL标识	查看原文
WOS记录号	[DB:DC_IDENTIFIER_WOSID]
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/3227619
专题	大连理工大学
作者单位	1.Shanghai Maritime Univ, Logist Engn Sch, Shanghai 201306, Peoples R China. 2.Dalian Univ Technol, Coll Energy & Power Engn, Dalian, Peoples R China.
推荐引用方式 GB/T 7714	Zhu, Keheng,Chen, Liang,Hu, Xiong. Rolling element bearing fault diagnosis based on multi-scale global fuzzy entropy, multiple class feature selection and support vector machine[J]. TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL,2019,41:4013-4022.
APA	Zhu, Keheng,Chen, Liang,&Hu, Xiong.(2019).Rolling element bearing fault diagnosis based on multi-scale global fuzzy entropy, multiple class feature selection and support vector machine.TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL,41,4013-4022.
MLA	Zhu, Keheng,et al."Rolling element bearing fault diagnosis based on multi-scale global fuzzy entropy, multiple class feature selection and support vector machine".TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 41(2019):4013-4022.

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。