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20192021
most citedMachine Learning and Deep Learning Algorithms for Bearing Fault Diagnostics -- A Comprehensive Review

900 citations · 1.1k across the 5 of their papers we have counts for

collaborators

5 papers

eess.SY2021★ 2 cited

Rotor Thermal Monitoring Scheme for Direct-Torque-Controlled Interior Permanent Magnet Synchronous Machines via High-Frequency Rotating Flux or Torque Injection

Shen Zhang, Sufei Li, Lijun He +2

Interior permanent magnet synchronous machine drives are widely employed in electric traction systems and various industrial processes. However, prolonged exposure to high temperat…

cs.LG2020★ 153 cited

Few-Shot Bearing Fault Diagnosis Based on Model-Agnostic Meta-Learning

Shen Zhang, Fei Ye, Bingnan Wang +1

The rapid development of artificial intelligence and deep learning has provided many opportunities to further enhance the safety, stability, and accuracy of industrial Cyber-Physic…

cs.LG2019★ 30 cited

Semi-Supervised Learning of Bearing Anomaly Detection via Deep Variational Autoencoders

Shen Zhang, Fei Ye, Bingnan Wang +1

Most of the data-driven approaches applied to bearing fault diagnosis up to date are established in the supervised learning paradigm, which usually requires a large set of labeled…

cs.LG2019★ 2 cited

Visualization of Multi-Objective Switched Reluctance Machine Optimization at Multiple Operating Conditions with t-SNE

Shen Zhang, Shibo Zhang, Sufei Li +2

The optimization of electric machines at multiple operating points is crucial for applications that require frequent changes on speeds and loads, such as the electric vehicles, to…

cs.LG2019★ 900 cited

Machine Learning and Deep Learning Algorithms for Bearing Fault Diagnostics -- A Comprehensive Review

Shen Zhang, Shibo Zhang, Bingnan Wang +1

In this survey paper, we systematically summarize existing literature on bearing fault diagnostics with machine learning (ML) and data mining techniques. While conventional ML meth…