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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:

Subspace Network with Shared Representation learning for intelligent fault diagnosis of machine under speed transient conditions with few samples
Shen Liu, Jinglong Chen, Shuilong He, et al.
ISA Transactions (2021) Vol. 128, pp. 531-544
Closed Access | Times Cited: 82

Showing 1-25 of 82 citing articles:

Deep order-wavelet convolutional variational autoencoder for fault identification of rolling bearing under fluctuating speed conditions
Xiaoan Yan, Daoming She, Yadong Xu
Expert Systems with Applications (2022) Vol. 216, pp. 119479-119479
Closed Access | Times Cited: 69
Rotating Machinery Fault Diagnosis Under Time-Varying Speeds: A Review
Dongdong Liu, Lingli Cui, Huaqing Wang
IEEE Sensors Journal (2023) Vol. 23, Iss. 24, pp. 29969-29990
Open Access | Times Cited: 54
Prior knowledge-embedded meta-transfer learning for few-shot fault diagnosis under variable operating conditions
Zihao Lei, Ping Zhang, Yuejian Chen, et al.
Mechanical Systems and Signal Processing (2023) Vol. 200, pp. 110491-110491
Closed Access | Times Cited: 47
A pruned-optimized weighted graph convolutional network for axial flow pump fault diagnosis with hydrophone signals
Xin Zhang, Li Jiang, Lei Wang, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102365-102365
Closed Access | Times Cited: 18
Digital twin-assisted dual transfer: a novel information-model adaptation method for rolling bearing fault diagnosis
Zixian Li, Xiaoxi Ding, Zhenzhen Song, et al.
Information Fusion (2024), pp. 102271-102271
Closed Access | Times Cited: 17
Deep branch attention network and extreme multi-scale entropy based single vibration signal-driven variable speed fault diagnosis scheme for rolling bearing
Dongfang Zhao, Shulin Liu, Hongyi Du, et al.
Advanced Engineering Informatics (2022) Vol. 55, pp. 101844-101844
Closed Access | Times Cited: 61
Unsupervised fault diagnosis of wind turbine bearing via a deep residual deformable convolution network based on subdomain adaptation under time-varying speeds
Pengfei Liang, Bin Wang, Guoqian Jiang, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 118, pp. 105656-105656
Closed Access | Times Cited: 56
Multi-channel Calibrated Transformer with Shifted Windows for few-shot fault diagnosis under sharp speed variation
Zhuohang Chen, Jinglong Chen, Shen Liu, et al.
ISA Transactions (2022) Vol. 131, pp. 501-515
Closed Access | Times Cited: 46
Few-shot learning under domain shift: Attentional contrastive calibrated transformer of time series for fault diagnosis under sharp speed variation
Shen Liu, Jinglong Chen, Shuilong He, et al.
Mechanical Systems and Signal Processing (2022) Vol. 189, pp. 110071-110071
Closed Access | Times Cited: 39
Time-frequency supervised contrastive learning via pseudo-labeling: An unsupervised domain adaptation network for rolling bearing fault diagnosis under time-varying speeds
Bin Pang, Qiuhai Liu, Zhenduo Sun, et al.
Advanced Engineering Informatics (2023) Vol. 59, pp. 102304-102304
Closed Access | Times Cited: 39
Rolling bearing intelligent fault diagnosis towards variable speed and imbalanced samples using multiscale dynamic supervised contrast learning
Yutong Dong, Hongkai Jiang, Renhe Yao, et al.
Reliability Engineering & System Safety (2023) Vol. 243, pp. 109805-109805
Closed Access | Times Cited: 28
Transformer-based meta learning method for bearing fault identification under multiple small sample conditions
Xianze Li, Hao Su, Ling Xiang, et al.
Mechanical Systems and Signal Processing (2023) Vol. 208, pp. 110967-110967
Closed Access | Times Cited: 25
Multiattention-Based Feature Aggregation Convolutional Networks With Dual Focal Loss for Fault Diagnosis of Rotating Machinery Under Data Imbalance Conditions
Yadong Xu, Sheng Li, Xiaoan Yan, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-11
Closed Access | Times Cited: 8
Generative artificial intelligence and data augmentation for prognostic and health management: Taxonomy, progress, and prospects
Shen Liu, Jinglong Chen, Yong Feng, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124511-124511
Closed Access | Times Cited: 8
A reliable feature-assisted contrastive generalization net for intelligent fault diagnosis under unseen machines and working conditions
Zhen Shi, Jinglong Chen, Xinwei Zhang, et al.
Mechanical Systems and Signal Processing (2022) Vol. 188, pp. 110011-110011
Closed Access | Times Cited: 32
Global contextual feature aggregation networks with multiscale attention mechanism for mechanical fault diagnosis under non-stationary conditions
Yadong Xu, Yuejian Chen, Hengcheng Zhang, et al.
Mechanical Systems and Signal Processing (2023) Vol. 203, pp. 110724-110724
Closed Access | Times Cited: 17
Use of vibration signal to estimate instantaneous angular frequency under strong nonstationary regimes
Yifan Li, Changqing Geng, Ming J. Zuo, et al.
Mechanical Systems and Signal Processing (2023) Vol. 200, pp. 110571-110571
Closed Access | Times Cited: 16
Multi-expert Attention Network with Unsupervised Aggregation for long-tailed fault diagnosis under speed variation
Zhuohang Chen, Jinglong Chen, Zongliang Xie, et al.
Knowledge-Based Systems (2022) Vol. 252, pp. 109393-109393
Closed Access | Times Cited: 22
Multi-source information fusion meta-learning network with convolutional block attention module for bearing fault diagnosis under limited dataset
Shanshan Song, Shuqing Zhang, Wei Dong, et al.
Structural Health Monitoring (2023) Vol. 23, Iss. 2, pp. 818-835
Closed Access | Times Cited: 15
A meta-learning network with anti-interference for few-shot fault diagnosis
Zhiqian Zhao, Runchao Zhao, Xianglin Wu, et al.
Neurocomputing (2023) Vol. 552, pp. 126551-126551
Closed Access | Times Cited: 15
An information-induced fault diagnosis framework generalizing from stationary to unknown nonstationary working conditions
Jianing Liu, Hongrui Cao, Yang Luo
Reliability Engineering & System Safety (2023) Vol. 237, pp. 109380-109380
Closed Access | Times Cited: 14
Towards complex multi-component pulse signal with strong noise: Deconvolution and time–frequency assisted mode decomposition
Gang Shi, Chengjin Qin, Zhinan Zhang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 212, pp. 111274-111274
Closed Access | Times Cited: 5
An Interpretable Multiplication-Convolution Network for Equipment Intelligent Edge Diagnosis
Rui Liu, Xiaoxi Ding, Qihang Wu, et al.
IEEE Transactions on Systems Man and Cybernetics Systems (2024) Vol. 54, Iss. 6, pp. 3284-3295
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
CE-FFGAN: A feature fusion generative adversarial network with deep embedded category information for limited sample fault diagnosis of rotating machinery under speed variation
Chen Yang, Hongkun Li, Shunxin Cao, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102605-102605
Closed Access | Times Cited: 4
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