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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Multiscale Convolutional Neural Network With Feature Alignment for Bearing Fault Diagnosis
Junbin Chen, Ruyi Huang, Kun Zhao, et al.
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-10
Closed Access | Times Cited: 68

Showing 1-25 of 68 citing articles:

A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges
Weihua Li, Ruyi Huang, Jipu Li, et al.
Mechanical Systems and Signal Processing (2021) Vol. 167, pp. 108487-108487
Open Access | Times Cited: 523
A Multi-Source Weighted Deep Transfer Network for Open-Set Fault Diagnosis of Rotary Machinery
Zhuyun Chen, Yixiao Liao, Jipu Li, et al.
IEEE Transactions on Cybernetics (2022) Vol. 53, Iss. 3, pp. 1982-1993
Closed Access | Times Cited: 108
Federated Transfer Learning for Bearing Fault Diagnosis With Discrepancy-Based Weighted Federated Averaging
Junbin Chen, Jipu Li, Ruyi Huang, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-11
Closed Access | Times Cited: 80
Transfer learning based on improved stacked autoencoder for bearing fault diagnosis
Shuyang Luo, Xufeng Huang, Yanzhi Wang, et al.
Knowledge-Based Systems (2022) Vol. 256, pp. 109846-109846
Closed Access | Times Cited: 72
Fault diagnosis in rotating machines based on transfer learning: Literature review
Iqbal Misbah, C.K.M. Lee, K. L. Keung
Knowledge-Based Systems (2023) Vol. 283, pp. 111158-111158
Closed Access | Times Cited: 57
Deep continual transfer learning with dynamic weight aggregation for fault diagnosis of industrial streaming data under varying working conditions
Jipu Li, Ruyi Huang, Zhuyun Chen, et al.
Advanced Engineering Informatics (2023) Vol. 55, pp. 101883-101883
Closed Access | Times Cited: 46
Dconformer: A denoising convolutional transformer with joint learning strategy for intelligent diagnosis of bearing faults
Sheng Li, Jinchen Ji, Yadong Xu, et al.
Mechanical Systems and Signal Processing (2024) Vol. 210, pp. 111142-111142
Closed Access | Times Cited: 30
Deep Learning-Based Bearing Fault Diagnosis Using a Trusted Multiscale Quadratic Attention-Embedded Convolutional Neural Network
Yuheng Tang, Chaoyong Zhang, Jianzhao Wu, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-15
Closed Access | Times Cited: 19
Discriminative feature learning using a multiscale convolutional capsule network from attitude data for fault diagnosis of industrial robots
Jianyu Long, Yaoxin Qin, Zhe Yang, et al.
Mechanical Systems and Signal Processing (2022) Vol. 182, pp. 109569-109569
Open Access | Times Cited: 54
Multiscale Residual Attention Convolutional Neural Network for Bearing Fault Diagnosis
Linshan Jia, Tommy W. S. Chow, Yu Wang, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-13
Closed Access | Times Cited: 51
Full Attention Wasserstein GAN With Gradient Normalization for Fault Diagnosis Under Imbalanced Data
Jigang Fan, Xianfeng Yuan, Zhaoming Miao, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-16
Closed Access | Times Cited: 48
Lightweight Multiscale Convolutional Networks With Adaptive Pruning for Intelligent Fault Diagnosis of Train Bogie Bearings in Edge Computing Scenarios
Ao Ding, Yong Qin, Biao Wang, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 72, pp. 1-13
Closed Access | Times Cited: 39
A Novel Local Binary Temporal Convolutional Neural Network for Bearing Fault Diagnosis
Yihao Xue, Rui Yang, Xiaohan Chen, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-13
Closed Access | Times Cited: 29
In-situ fault diagnosis for the harmonic reducer of industrial robots via multi-scale mixed convolutional neural networks
Yiming He, Jihong Chen, Xing Zhou, et al.
Journal of Manufacturing Systems (2022) Vol. 66, pp. 233-247
Closed Access | Times Cited: 34
A novel unsupervised directed hierarchical graph network with clustering representation for intelligent fault diagnosis of machines
Bo Zhao, Xianmin Zhang, Qiqiang Wu, et al.
Mechanical Systems and Signal Processing (2022) Vol. 183, pp. 109615-109615
Closed Access | Times Cited: 32
The LST-SATM-net: A new deep feature learning framework for aero-engine hydraulic pipeline systems intelligent faults diagnosis
Tongguang Yang, Guanchen Li, Shenyou Yuan, et al.
Applied Acoustics (2023) Vol. 210, pp. 109436-109436
Closed Access | Times Cited: 20
Cross-Domain Compound Fault Diagnosis of Machine-Level Motors via Time–Frequency Self-Contrastive Learning
Yiming He, Chao Zhao, Weiming Shen
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 7, pp. 9692-9701
Closed Access | Times Cited: 5
Multiscale Dynamic Weight Based Mixed Convolutional Neural Network for Fault Diagnosis of Rotating Machinery
Wenliao Du, Lingkai Yang, Xiaoyun Gong, et al.
IEEE Transactions on Instrumentation and Measurement (2025) Vol. 74, pp. 1-11
Closed Access
A limited annotated sample fault diagnosis algorithm based on nonlinear coupling self-attention mechanism
Shuyang Luo, Dong Zhang, Jinhong Wu, et al.
Engineering Failure Analysis (2025), pp. 109474-109474
Closed Access
Rolling bearing fault diagnosis based on iDBO-VMD-LSSVM
Cheng Zhang, Li Cui, Feng Yan, et al.
Engineering Research Express (2025) Vol. 7, Iss. 1, pp. 015570-015570
Closed Access
MSRCN: A cross-machine diagnosis method for the CNC spindle motors with compound faults
Yiming He, Weiming Shen
Expert Systems with Applications (2023) Vol. 233, pp. 120957-120957
Closed Access | Times Cited: 15
Rotary Machinery Fault Diagnosis Based on Split Attention Mechanism and Graph Convolutional Domain Adaptive Adversarial Network
Haitao Wang, Mingjun Li, Zelin Liu, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 4, pp. 5399-5413
Closed Access | Times Cited: 4
Fault Diagnosis Method for Main Pump Motor Shielding Sleeve Based on Attention Mechanism and Multi-Source Data Fusion
Nengqing Liu, Xuewei Xiang, Hui Li, et al.
Sensors (2025) Vol. 25, Iss. 6, pp. 1775-1775
Open Access
Residual-Hypergraph Convolution Network: A Model-Based and Data-Driven Integrated Approach for Fault Diagnosis in Complex Equipment
Liqiao Xia, Yongshi Liang, Pai Zheng, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 72, pp. 1-11
Closed Access | Times Cited: 21
In-situ fault detection for the spindle motor of CNC machines via multi-stage residual fusion convolution neural networks
Yiming He, Hua Xiang, Hao Zhou, et al.
Computers in Industry (2022) Vol. 145, pp. 103810-103810
Closed Access | Times Cited: 20
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