Insights into modern machine learning approaches for bearing fault classification: A systematic literature review
Author:
Funder
Universiti Kebangsaan Malaysia
Universiti Teknologi PETRONAS
Publisher
Elsevier BV
Reference100 articles.
1. Aero-engine bearing fault detection: a clustering low-rank approach;Zhang;Mech. Syst. Signal Process.,2020
2. Fault detection of high-speed train axle bearings based on a hybridized physical and data-driven temperature model;Yang;Mech. Syst. Signal Process.,2024
3. Dynamics simulation-driven fault diagnosis of rolling bearings using security transfer support matrix machine;Li;Reliab. Eng. Syst. Saf.,2024
4. Integrated intelligent fault diagnosis approach of offshore wind turbine bearing based on information stream fusion and semi-supervised learning;Zhang;Expert Syst. Appl.,2023
5. A review on fault detection and diagnosis of industrial robots and multi-axis machines;Sabry;Results in Engineering,2024
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