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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:

End to end multi-task learning with attention for multi-objective fault diagnosis under small sample
Zongliang Xie, Jinglong Chen, Yong Feng, et al.
Journal of Manufacturing Systems (2021) Vol. 62, pp. 301-316
Closed Access | Times Cited: 81

Showing 1-25 of 81 citing articles:

Attention mechanism in intelligent fault diagnosis of machinery: A review of technique and application
Haixin Lv, Jinglong Chen, Tongyang Pan, et al.
Measurement (2022) Vol. 199, pp. 111594-111594
Closed Access | Times Cited: 148
A fault diagnosis method using improved prototypical network and weighting similarity-Manhattan distance with insufficient noisy data
Changdong Wang, Jingli Yang, Baoqin Zhang
Measurement (2024) Vol. 226, pp. 114171-114171
Closed Access | Times Cited: 33
Towards multi-scene learning: A novel cross-domain adaptation model based on sparse filter for traction motor bearing fault diagnosis in high-speed EMU
Feiyu Lu, Qingbin Tong, Jianjun Xu, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102536-102536
Closed Access | Times Cited: 18
On Paradigm of Industrial Big Data Analytics: From Evolution to Revolution
Zeyu Yang, Zhiqiang Ge
IEEE Transactions on Industrial Informatics (2022) Vol. 18, Iss. 12, pp. 8373-8388
Closed Access | Times Cited: 64
Semi-supervised multi-scale attention-aware graph convolution network for intelligent fault diagnosis of machine under extremely-limited labeled samples
Zongliang Xie, Jinglong Chen, Yong Feng, et al.
Journal of Manufacturing Systems (2022) Vol. 64, pp. 561-577
Closed Access | Times Cited: 62
End-to-end chiller fault diagnosis using fused attention mechanism and dynamic cross-entropy under imbalanced datasets
Song-Yu Han, Haidong Shao, Zhiqiang Huo, et al.
Building and Environment (2022) Vol. 212, pp. 108821-108821
Closed Access | Times Cited: 39
Auto-Embedding Transformer for Interpretable Few-Shot Fault Diagnosis of Rolling Bearings
Gang Wang, Dongdong Liu, Lingli Cui
IEEE Transactions on Reliability (2023) Vol. 73, Iss. 2, pp. 1270-1279
Closed Access | Times Cited: 24
Lightweight Convolutional Transformers Enhanced Meta-Learning for Compound Fault Diagnosis of Industrial Robot
Chong Chen, Tao Wang, Chao Liu, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-12
Open Access | Times Cited: 22
Multielement simultaneous quantitative analysis of trace elements in stainless steel via full spectrum laser-induced breakdown spectroscopy
Qing Ma, Ziyuan Liu, Tingsong Zhang, et al.
Talanta (2024) Vol. 272, pp. 125745-125745
Closed Access | Times Cited: 12
ISEANet: An interpretable subdomain enhanced adaptive network for unsupervised cross-domain fault diagnosis of rolling bearing
Bin Liu, Changfeng Yan, Yaofeng Liu, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102610-102610
Closed Access | Times Cited: 10
FW-UAV fault diagnosis based on knowledge complementary network under small sample
Yizong Zhang, Shaobo Li, Ansi Zhang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 215, pp. 111418-111418
Closed Access | Times Cited: 7
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
Improved spiking neural network for intershaft bearing fault diagnosis
Jun Wang, Tianfu Li, Chuang Sun, et al.
Journal of Manufacturing Systems (2022) Vol. 65, pp. 208-219
Closed Access | Times Cited: 30
M2FN: An end-to-end multi-task and multi-sensor fusion network for intelligent fault diagnosis
Jian Cui, Ping Xie, Xiao Wang, et al.
Measurement (2022) Vol. 204, pp. 112085-112085
Closed Access | Times Cited: 28
Paired ensemble and group knowledge measurement for health evaluation of wind turbine gearbox under compound fault scenarios
Weixiong Jiang, Jun Wu, Haiping Zhu, et al.
Journal of Manufacturing Systems (2023) Vol. 70, pp. 382-394
Closed Access | Times Cited: 18
An interpretable multiplication-convolution residual network for equipment fault diagnosis via time–frequency filtering
Rui Liu, Xiaoxi Ding, Yimin Shao, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102421-102421
Closed Access | Times Cited: 5
HeMTAN: Hybrid task-adapted experts-based multi-task attention network for unseen compound fault decoupling diagnosis of rotating machinery
Jimeng Li, Wei Wang, Sai Zhong, et al.
Expert Systems with Applications (2024) Vol. 252, pp. 124189-124189
Closed Access | Times Cited: 5
Data-driven machinery fault diagnosis: A comprehensive review
Dhiraj Neupane, Mohamed Reda Bouadjenek, Richard Dazeley, et al.
Neurocomputing (2025), pp. 129588-129588
Open Access
Collaborative monitoring method for cutter anomaly detection and RUL prediction based on multi-task learning
X. Y. Shao, Xiaoyin Nie, Hui Shi, et al.
Journal of Mechanical Science and Technology (2025)
Closed Access
Fault diagnosis based on gated recurrent unit network with attention mechanism and transfer learning under few samples in nuclear power plants
Gensheng Qian, Jingquan Liu
Progress in Nuclear Energy (2022) Vol. 155, pp. 104502-104502
Closed Access | Times Cited: 26
A novel framework based on adaptive Multi-Task learning for bearing fault diagnosis
Jierui Zhang, Jianjun Chen, Huiwen Deng, et al.
Energy Reports (2023) Vol. 9, pp. 522-531
Open Access | Times Cited: 13
A Balanced Deep Transfer Network for Bearing Fault Diagnosis
Shaopu Yang, Zhaoyang Cui, Xiaohui Gu
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-12
Closed Access | Times Cited: 13
Missing data imputation and classification of small sample missing time series data based on gradient penalized adversarial multi-task learning
Jingjing Liu, Jie-Peng Yao, Jin-Hang Liu, et al.
Applied Intelligence (2024) Vol. 54, Iss. 3, pp. 2528-2550
Closed Access | Times Cited: 4
Semi-supervised few-shot fault diagnosis driven by multi-head dynamic graph attention network under speed fluctuations
Li Jiang, Shuaiyu Wang, Tianao Zhang, et al.
Digital Signal Processing (2024) Vol. 151, pp. 104528-104528
Closed Access | Times Cited: 4
Multi-task Learning for Aero-engine Bearing Fault Diagnosis with Limited Data
Peixuan Ding, Yi Xu, Xi‐Ming Sun
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-11
Closed Access | Times Cited: 4
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