Standout Papers

Toward Efficient and Interpretative Rolling Bearing Fault Diagnosis via Quadratic Neural Network With Bi-LSTM 2024 202662
  1. Toward Efficient and Interpretative Rolling Bearing Fault Diagnosis via Quadratic Neural Network With Bi-LSTM (2024)
    You Keshun, Yingkui Gu et al. IEEE Internet of Things Journal

Immediate Impact

18 standout
Sub-graph 1 of 7

Citing Papers

A zero-shot model for diagnosing unknown composite faults in train bearings based on label feature vector generated fault features
2025 Standout
Digital twin-inspired methods for rotating machinery intelligent fault diagnosis and remaining useful life prediction: A state-of-the-art review and future challenges
2025 Standout
2 intermediate papers

Works of You Keshun being referenced

Remaining useful life prediction of lithium-ion batteries using EM-PF-SSA-SVR with gamma stochastic process
2023
Optimizing prior distribution parameters for probabilistic prediction of remaining useful life using deep learning
2023

Author Peers

Author Last Decade Papers Cites
You Keshun 200 294 108 20 516
Xudong Li 148 221 67 23 462
Pengxin Wang 181 323 95 22 489
Sandeep S. Udmale 185 355 147 21 528
Xin Wang 197 299 99 20 463
Qinghua Zhang 220 383 123 16 548
Huimin Zhao 137 219 75 22 500
Zuqiang Su 282 415 131 34 610
Sijue Li 196 302 102 13 459
Fangyi Wan 206 289 115 37 569
Yang Hu 153 274 70 18 466

All Works

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2026