Twin robust matrix machine for intelligent fault identification of outlier samples in roller bearing

作者：

Highlights：

• A twin robust matrix machine (TRMM) is proposed for classification with outliers.

• The truncated nuclear norm makes TRMM can capture strong correlated information.

• The ramp loss is introduced to make TRMM insensitive to outlier samples.

摘要

•A twin robust matrix machine (TRMM) is proposed for classification with outliers.•The truncated nuclear norm makes TRMM can capture strong correlated information.•The ramp loss is introduced to make TRMM insensitive to outlier samples.

论文关键词：Twin robust matrix machine (TRMM),Truncated nuclear norm,Ramp loss,Outlier sample,Fault diagnosis

论文评审过程：Received 7 May 2022, Revised 29 June 2022, Accepted 6 July 2022, Available online 11 July 2022, Version of Record 18 July 2022.

论文官网地址：https://doi.org/10.1016/j.knosys.2022.109391