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Intelligent rotating machinery fault diagnosis based on deep learning using data augmentation

Crossref DOI link: https://doi.org/10.1007/s10845-018-1456-1

Published Online: 2018-11-30

Published Print: 2020-02

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Li, Xiang https://orcid.org/0000-0003-0569-2176
Zhang, Wei

Ding, Qian

Sun, Jian-Qiao
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (11172197)

National Natural Science Foundation of China (11332008)

National Natural Science Foundation of China (11572215)

Fundamental Research Funds for the Central Universities (N170503012)

Fundamental Research Funds for the Central Universities (N170308028)
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Text and Data Mining valid from 2018-11-30
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Article History

Received: 16 March 2018

Accepted: 26 November 2018

First Online: 30 November 2018