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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:

A two-stage domain alignment method for multi-source domain fault diagnosis
Wei Cao, Zong Meng, Dengyun Sun, et al.
Measurement (2023) Vol. 214, pp. 112818-112818
Closed Access | Times Cited: 22

Showing 22 citing articles:

A new multi-source information domain adaption network based on domain attributes and features transfer for cross-domain fault diagnosis
Yue Yu, Hamid Reza Karimi, Peiming Shi, et al.
Mechanical Systems and Signal Processing (2024) Vol. 211, pp. 111194-111194
Open Access | Times Cited: 20
A two-stage importance-aware subgraph convolutional network based on multi-source sensors for cross-domain fault diagnosis
Yue Yu, Youqian He, Hamid Reza Karimi, et al.
Neural Networks (2024) Vol. 179, pp. 106518-106518
Open Access | Times Cited: 18
Self-paced decentralized federated transfer framework for rotating machinery fault diagnosis with multiple domains
Ke Zhao, Zhenbao Liu, Jia Li, et al.
Mechanical Systems and Signal Processing (2024) Vol. 211, pp. 111258-111258
Closed Access | Times Cited: 17
Multi-source weighted source-free domain transfer method for rotating machinery fault diagnosis
Qinhe Gao, Tong Huang, Ke Zhao, et al.
Expert Systems with Applications (2023) Vol. 237, pp. 121585-121585
Closed Access | Times Cited: 31
Cross-Supervised multisource prototypical network: A novel domain adaptation method for multi-source few-shot fault diagnosis
Xiao Zhang, Weiguo Huang, Chuancang Ding, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102538-102538
Closed Access | Times Cited: 12
Multi-source partial domain adaptation method based on pseudo-balanced target domain for fault diagnosis
Guowei Zhang, Xianguang Kong, Qibin Wang, et al.
Knowledge-Based Systems (2023) Vol. 284, pp. 111255-111255
Closed Access | Times Cited: 16
A dynamic collaborative adversarial domain adaptation network for unsupervised rotating machinery fault diagnosis
Xin Wang, Hongkai Jiang, Mu Mingzhe, et al.
Reliability Engineering & System Safety (2024), pp. 110662-110662
Closed Access | Times Cited: 7
A Multi-Source Domain Feature-Decision Dual Fusion Adversarial Transfer Network for Cross-Domain Anti-Noise Mechanical Fault Diagnosis in Sustainable City
Changdong Wang, Huamin Jie, Jingli Yang, et al.
Information Fusion (2024) Vol. 115, pp. 102739-102739
Closed Access | Times Cited: 6
A novel sliding mixing graph contrastive domain adaptation method for fault diagnosis under time-varying speeds
Kai Chen, Zong Meng, Dengyun Sun, et al.
Expert Systems with Applications (2025), pp. 126576-126576
Closed Access
Joint distribution Bures–Wasserstein distance based multi-source student teacher network for rotating machinery fault diagnosis
Fucheng Yan, Liang Yu, Ran Wang, et al.
Mechanical Systems and Signal Processing (2025) Vol. 227, pp. 112366-112366
Closed Access
Research on prediction model of converter steelmaking process based on multi-scale feature extraction and self-attention mechanism for multi-source domain asynchronous data
Yan Hu, Jia Tang, Baoshan Huang, et al.
Measurement (2025), pp. 117060-117060
Closed Access
A Domain-Adaptive Segmentation Method Based on Segment Anything Model for Mechanical Assembly
Jinlei Wang, Chengjun Chen, Chenggang Dai, et al.
Measurement (2024) Vol. 235, pp. 114901-114901
Closed Access | Times Cited: 4
Multi-source domain self-supervised enhanced transfer fault diagnosis approach with source sample refinement strategy
Xinyu Ren, Wanli Zhao, Mengmeng Liu, et al.
Reliability Engineering & System Safety (2024) Vol. 251, pp. 110380-110380
Closed Access | Times Cited: 4
An Improved Cross-Machine Transfer Strategy Based on Multi-Source Domain Knowledge for Abnormal Sample Recognition
Zhenhao Yan, Bingqiang Zhou, Zenggui Gao, et al.
Reliability Engineering & System Safety (2025), pp. 110848-110848
Closed Access
A centroid contrastive multi-source domain adaptation method for fault diagnosis with category shift
Yufeng Li, Xinghan Xu, Lei Hu, et al.
Measurement (2025), pp. 116801-116801
Closed Access
Fault diagnosis of bearings using a two-stage transfer alignment approach with semantic consistency and entropy loss
Jichao Zhuang, Yudong Cao, Minping Jia, et al.
Expert Systems with Applications (2023) Vol. 226, pp. 120274-120274
Closed Access | Times Cited: 9
A semi-supervised learning method based on pseudo-label iterative purification for intelligent fault diagnosis of rolling bearing
Wenbo Yue, L. Zhang, Jianwei Yang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 066013-066013
Closed Access | Times Cited: 1
A multi-source unsupervised fault diagnosis network with residual enhancement attention module for rotating machinery cross-operating conditions
Hangbo Duan, Zongyan Cai, Qingtao Liu, et al.
Journal of Vibration and Control (2024)
Closed Access | Times Cited: 1
TSMDA: intelligent fault diagnosis of rolling bearing with two stage multi-source domain adaptation
Qianqian Zhang, Zhongwei Lv, Caiyun Hao, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 11, pp. 116112-116112
Closed Access
Domain adaptive segmentation method for mechanical assembly based on iterative loops
Jinlei Wang, Chengjun Chen, Chenggang Dai
Applied Intelligence (2024) Vol. 55, Iss. 1
Closed Access
Dual branch feature matching guided multi-source domain adaptive ensemble network for rotating machinery fault diagnosis
Bo Liu, Guofa Li, Jialong He, et al.
Advanced Engineering Informatics (2024) Vol. 64, pp. 103061-103061
Closed Access
Unsupervised Representation Learning for Fault Diagnosis in IT Infrastructure
Xin Hua
(2023), pp. 307-313
Closed Access
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