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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:

Deep multi-scale adversarial network with attention: A novel domain adaptation method for intelligent fault diagnosis
Bo Zhao, Xianmin Zhang, Zhenhui Zhan, et al.
Journal of Manufacturing Systems (2021) Vol. 59, pp. 565-576
Closed Access | Times Cited: 80

Showing 1-25 of 80 citing articles:

Novel Joint Transfer Network for Unsupervised Bearing Fault Diagnosis From Simulation Domain to Experimental Domain
Yiming Xiao, Haidong Shao, Song-Yu Han, et al.
IEEE/ASME Transactions on Mechatronics (2022) Vol. 27, Iss. 6, pp. 5254-5263
Closed Access | Times Cited: 224
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
Generative adversarial network in mechanical fault diagnosis under small sample: A systematic review on applications and future perspectives
Tongyang Pan, Jinglong Chen, Tianci Zhang, et al.
ISA Transactions (2021) Vol. 128, pp. 1-10
Closed Access | Times Cited: 133
Bayesian variational transformer: A generalizable model for rotating machinery fault diagnosis
Yiming Xiao, Haidong Shao, Jie Wang, et al.
Mechanical Systems and Signal Processing (2023) Vol. 207, pp. 110936-110936
Open Access | Times Cited: 103
Machinery Fault Diagnosis Based on Domain Adaptation to Bridge the Gap Between Simulation and Measured Signals
Yunxia Lou, Anil Kumar, Jiawei Xiang
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-9
Closed Access | Times Cited: 86
Maximum mean square discrepancy: A new discrepancy representation metric for mechanical fault transfer diagnosis
Quan Qian, Yi Wang, Taisheng Zhang, et al.
Knowledge-Based Systems (2023) Vol. 276, pp. 110748-110748
Closed Access | Times Cited: 82
Vibration signal-based early fault prognosis: Status quo and applications
Yaqiong Lv, Wenqin Zhao, Zhiyao Zhao, et al.
Advanced Engineering Informatics (2022) Vol. 52, pp. 101609-101609
Closed Access | Times Cited: 80
Deep Learning Techniques in Intelligent Fault Diagnosis and Prognosis for Industrial Systems: A Review
Shaohua Qiu, Xiaopeng Cui, Zuowei Ping, et al.
Sensors (2023) Vol. 23, Iss. 3, pp. 1305-1305
Open Access | Times Cited: 63
An Adaptive Domain Adaptation Method for Rolling Bearings’ Fault Diagnosis Fusing Deep Convolution and Self-Attention Networks
Xiao Yu, Youjie Wang, Zhongting Liang, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-14
Closed Access | Times Cited: 45
A Systematic Literature Review on Transfer Learning for Predictive Maintenance in Industry 4.0
Mehdi Saman Azari, Francesco Flammini, Stefania Santini, et al.
IEEE Access (2023) Vol. 11, pp. 12887-12910
Open Access | Times Cited: 42
Novel Domain-Adaptive Wasserstein Generative Adversarial Networks for Early Bearing Fault Diagnosis under Various Conditions
Z. K. Hei, Weifang Sun, Haiyang Yang, et al.
Reliability Engineering & System Safety (2025), pp. 110847-110847
Closed Access | Times Cited: 2
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
Deep multiple auto-encoder with attention mechanism network: A dynamic domain adaptation method for rotary machine fault diagnosis under different working conditions
Shengkang Yang, Xianguang Kong, Qibin Wang, et al.
Knowledge-Based Systems (2022) Vol. 249, pp. 108639-108639
Closed Access | Times Cited: 63
Intelligent fault diagnosis of rolling bearings under varying operating conditions based on domain-adversarial neural network and attention mechanism
Hao Wu, Jimeng Li, Qingyu Zhang, et al.
ISA Transactions (2022) Vol. 130, pp. 477-489
Closed Access | Times Cited: 62
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
A novel self-training semi-supervised deep learning approach for machinery fault diagnosis
Jianyu Long, Yibin Chen, Zhe Yang, et al.
International Journal of Production Research (2022) Vol. 61, Iss. 23, pp. 8238-8251
Closed Access | Times Cited: 61
Source-Free Adaptation Diagnosis for Rotating Machinery
Jinyang Jiao, Hao Li, Tian Zhang, et al.
IEEE Transactions on Industrial Informatics (2022) Vol. 19, Iss. 9, pp. 9586-9595
Closed Access | Times Cited: 52
Modified DSAN for unsupervised cross-domain fault diagnosis of bearing under speed fluctuation
Jingjie Luo, Haidong Shao, Hongru Cao, et al.
Journal of Manufacturing Systems (2022) Vol. 65, pp. 180-191
Open Access | Times Cited: 45
A novel adversarial domain adaptation transfer learning method for tool wear state prediction
Kai Li, Ming-Song Chen, Y.C. Lin, et al.
Knowledge-Based Systems (2022) Vol. 254, pp. 109537-109537
Closed Access | Times Cited: 37
Rolling bearing fault diagnosis based on information fusion and parallel lightweight convolutional network
Yang Guan, Zong Meng, Dengyun Sun, et al.
Journal of Manufacturing Systems (2022) Vol. 65, pp. 811-821
Closed Access | Times Cited: 37
A federated learning approach to mixed fault diagnosis in rotating machinery
Manan Mehta, Siyuan Chen, Haichuan Tang, et al.
Journal of Manufacturing Systems (2023) Vol. 68, pp. 687-694
Closed Access | Times Cited: 27
Tool wear condition monitoring across machining processes based on feature transfer by deep adversarial domain confusion network
Zhiwen Huang, Jiajie Shao, Jianmin Zhu, et al.
Journal of Intelligent Manufacturing (2023) Vol. 35, Iss. 3, pp. 1079-1105
Closed Access | Times Cited: 22
Multibranch and Multiscale Dynamic Convolutional Network for Small Sample Fault Diagnosis of Rotating Machinery
Haopeng Liang, Jie Cao, Xiaoqiang Zhao
IEEE Sensors Journal (2023) Vol. 23, Iss. 8, pp. 8973-8988
Closed Access | Times Cited: 22
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
Deep Unsupervised Domain Adaptation with Time Series Sensor Data: A Survey
Yongjie Shi, Xianghua Ying, Jinfa Yang
Sensors (2022) Vol. 22, Iss. 15, pp. 5507-5507
Open Access | Times Cited: 32
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