Semi-supervised fault diagnosis of rolling bearing based on twin-representation contrastive learning

CHEN Renxiang1, ZHANG Xu1, YANG Lixia2, LIANG Dong1, SUN Shizheng1, DONG Shaojiang1

Journal of Vibration and Shock ›› 2025, Vol. 44 ›› Issue (15) : 209-216.

PDF(2482 KB)
PDF(2482 KB)
Journal of Vibration and Shock ›› 2025, Vol. 44 ›› Issue (15) : 209-216.
FAULT DIAGNOSIS ANALYSIS

Semi-supervised fault diagnosis of rolling bearing based on twin-representation contrastive learning

    {{javascript:window.custom_author_en_index=0;}}
  • {{article.zuoZhe_EN}}
Author information +
History +

HeighLight

{{article.keyPoints_en}}

Abstract

{{article.zhaiyao_en}}

Key words

QR code of this article

Cite this article

Download Citations
{{article.zuoZheEn_L}}. {{article.title_en}}[J]. {{journal.qiKanMingCheng_EN}}, 2025, 44(15): 209-216

References

References

{{article.reference}}

Funding

RIGHTS & PERMISSIONS

{{article.copyrightStatement_en}}
{{article.copyrightLicense_en}}
PDF(2482 KB)

Accesses

Citation

Detail

Sections
Recommended

/