Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification | |
Lu, Chen; Wang, Zhen-Ya; Qin, Wei-Li; Ma, Jian | |
刊名 | SIGNAL PROCESSING
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2017 | |
卷号 | 130页码:377-388 |
关键词 | Fault diagnosis Stacked denoising autoencoder Health state identification Deep learning |
ISSN号 | 0165-1684 |
DOI | 10.1016/j.sigpro.2016.07.028 |
URL标识 | 查看原文 |
收录类别 | SCIE ; EI ; ESI高被引论文 |
WOS记录号 | WOS:000386410200038 |
内容类型 | 期刊论文 |
URI标识 | http://www.corc.org.cn/handle/1471x/5942537 |
专题 | 北京航空航天大学 |
推荐引用方式 GB/T 7714 | Lu, Chen,Wang, Zhen-Ya,Qin, Wei-Li,et al. Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification[J]. SIGNAL PROCESSING,2017,130:377-388. |
APA | Lu, Chen,Wang, Zhen-Ya,Qin, Wei-Li,&Ma, Jian.(2017).Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification.SIGNAL PROCESSING,130,377-388. |
MLA | Lu, Chen,et al."Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification".SIGNAL PROCESSING 130(2017):377-388. |
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