A novel data-driven method based on sample reliability assessment and improved CNN for machinery fault diagnosis with non-ideal data
Crossref DOI link: https://doi.org/10.1007/s10845-022-01944-x
Published Online: 2022-04-20
Published Print: 2023-06
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Zhang, Xin
Wang, Haifeng
Wu, Bo
Zhou, Quan
Hu, Youmin http://orcid.org/0000-0002-8813-0410
Funding for this research was provided by:
Key Technologies Research and Development Program (2017YFD0400405)
Text and Data Mining valid from 2022-04-20
Version of Record valid from 2022-04-20
Article History
Received: 19 October 2021
Accepted: 24 March 2022
First Online: 20 April 2022