Standout Papers

Electric Locomotive Bearing Fault Diagnosis Using a Novel Convolutional Deep Belief Network 2017 2026 2020 2023 386
  1. Electric Locomotive Bearing Fault Diagnosis Using a Novel Convolutional Deep Belief Network (2017)
    Haidong Shao, Hongkai Jiang et al. IEEE Transactions on Industrial Electronics
  2. Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing (2017)
    Haidong Shao, Hongkai Jiang et al. Mechanical Systems and Signal Processing

Immediate Impact

50 standout
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Citing Papers

Data-driven machinery fault diagnosis: A comprehensive review
2025 Standout
A comprehensive literature review of the applications of AI techniques through the lifecycle of industrial equipment
2023 Standout
1 intermediate paper

Works of Tianchen Liang being referenced

Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing
2017 Standout
Electric Locomotive Bearing Fault Diagnosis Using a Novel Convolutional Deep Belief Network
2017 Standout

Author Peers

Author Last Decade Papers Cites
Tianchen Liang 52 737 69 481 257 14 960
Xiaoli Zhang 42 594 14 372 250 28 940
Zhiqiang Chen 65 470 10 314 207 11 740
Viktor Slavkovikj 19 714 43 510 333 7 1.1k
Lei Huang 59 347 44 203 109 27 903
Vilmar Æsøy 9 372 40 185 93 35 957
Zifei Xu 8 520 12 321 223 39 898
Yaoxiang Yu 17 453 6 378 174 44 775
Fei Shen 6 631 8 414 196 22 992
Zhe Cheng 24 586 5 497 210 47 949
Han Zhang 15 490 19 344 155 49 747

All Works

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2026