基于小波包频带能量特征和BP神经网络的滚动轴承智能故障诊断
潘峥嵘; 刘雄; 谯自健
2015-05-25
Source Publication自动化与仪器仪表
ISSNISSN:1001-9227
Issue2015年05期Pages:82-84
Abstract对滚动轴承振动信号进行小波包分解,提取频带能量特征构成特征向量,并以此作为BP神经网络的输入,对神经网络进行训练,建立滚动轴承运行状态分类器,用以识别滚动轴承的运行状态。试验结果表明,通过小波包分解提取能量特征结合BP神经网络对滚动轴承进行故障诊断的方法是可靠的,可以准确识别轴承的故障类别。
Keyword小波包 能量特征 BP神经网络 滚动轴承 故障诊断
DOI10.14016/j.cnki.1001-9227.2015.05.082
URL查看原文
Indexed ByCNKI
Language中文
Document Type期刊论文
Identifierhttp://ir.lut.edu.cn/handle/2XXMBERH/7196
Collection电气工程与信息工程学院
Affiliation兰州理工大学电气工程与信息工程学院
First Author AffilicationColl Elect & Informat Engn
First Signature AffilicationColl Elect & Informat Engn
Recommended Citation
GB/T 7714
潘峥嵘,刘雄,谯自健. 基于小波包频带能量特征和BP神经网络的滚动轴承智能故障诊断[J]. 自动化与仪器仪表,2015(2015年05期):82-84.
APA 潘峥嵘,刘雄,&谯自健.(2015).基于小波包频带能量特征和BP神经网络的滚动轴承智能故障诊断.自动化与仪器仪表(2015年05期),82-84.
MLA 潘峥嵘,et al."基于小波包频带能量特征和BP神经网络的滚动轴承智能故障诊断".自动化与仪器仪表 .2015年05期(2015):82-84.
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