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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 combination of residual and long–short-term memory networks for bearing fault diagnosis based on time-series model analysis
Youming Wang, Lin Cheng
Measurement Science and Technology (2020) Vol. 32, Iss. 1, pp. 015904-015904
Closed Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Imbalanced fault diagnosis of rolling bearing using improved MsR-GAN and feature enhancement-driven CapsNet
Jie Liu, Changhe Zhang, Xingxing Jiang
Mechanical Systems and Signal Processing (2021) Vol. 168, pp. 108664-108664
Closed Access | Times Cited: 125
An efficient lightweight neural network using BiLSTM-SCN-CBAM with PCA-ICEEMDAN for diagnosing rolling bearing faults
You Keshun, Guangqi Qiu, Yingkui Gu
Measurement Science and Technology (2023) Vol. 34, Iss. 9, pp. 094001-094001
Closed Access | Times Cited: 41
Intelligent Fault Diagnosis of Rolling Bearing Based on Gramian Angular Difference Field and Improved Dual Attention Residual Network
Anshi Tong, Jun Zhang, Liyang Xie
Sensors (2024) Vol. 24, Iss. 7, pp. 2156-2156
Open Access | Times Cited: 14
Multi-perspective deep transfer learning model: A promising tool for bearing intelligent fault diagnosis under varying working conditions
Xue‐Gang Li, Xingxing Jiang, Qian Wang, et al.
Knowledge-Based Systems (2022) Vol. 243, pp. 108443-108443
Closed Access | Times Cited: 38
Rolling bearing fault diagnosis based on Gramian angular difference field and improved channel attention model
Lunpan Wei, Xiuyan Peng, Yunpeng Cao
PeerJ Computer Science (2024) Vol. 10, pp. e1807-e1807
Open Access | Times Cited: 11
Data augmentation for rolling bearing fault diagnosis using an enhanced few-shot Wasserstein auto-encoder with meta-learning
Zeyu Pei, Hongkai Jiang, Xingqiu Li, et al.
Measurement Science and Technology (2021) Vol. 32, Iss. 8, pp. 084007-084007
Closed Access | Times Cited: 42
A hybrid deep-learning model for fault diagnosis of rolling bearings in strong noise environments
Ke Zhang, Caizi Fan, Xiaochen Zhang, et al.
Measurement Science and Technology (2022) Vol. 33, Iss. 6, pp. 065103-065103
Closed Access | Times Cited: 30
Small sample gearbox fault diagnosis based on improved deep forest in noisy environments
Haidong Shao, Yuhang Ming, Yiyu Liu, et al.
Nondestructive Testing And Evaluation (2024), pp. 1-22
Closed Access | Times Cited: 5
Multi-scale dynamic adaptive residual network for fault diagnosis
Haopeng Liang, Jie Cao, Xiaoqiang Zhao
Measurement (2021) Vol. 188, pp. 110397-110397
Closed Access | Times Cited: 39
Rolling bearing fault diagnosis by Markov transition field and multi-dimension convolutional neural network
Chunli Lei, Linlin Xue, Mengxuan Jiao, et al.
Measurement Science and Technology (2022) Vol. 33, Iss. 11, pp. 114009-114009
Closed Access | Times Cited: 25
A novel convolutional neural network with multiscale cascade midpoint residual for fault diagnosis of rolling bearings
Zhiqiang Chao, Tian Han
Neurocomputing (2022) Vol. 506, pp. 213-227
Closed Access | Times Cited: 22
Adversarial training of multi-scale channel attention network for enhanced robustness in bearing fault diagnosis
Haotian Peng, Jinsong Du, Jie Gao, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 5, pp. 056204-056204
Closed Access | Times Cited: 3
Bearing fault diagnosis by combining a deep residual shrinkage network and bidirectional LSTM
Yizhi Tong, Ping Wu, Jiajun He, et al.
Measurement Science and Technology (2021) Vol. 33, Iss. 3, pp. 034001-034001
Closed Access | Times Cited: 25
Few-shot bearing fault diagnosis based on meta-learning with discriminant space optimization
Dengming Zhang, Kai Zheng, Yin Bai, et al.
Measurement Science and Technology (2022) Vol. 33, Iss. 11, pp. 115024-115024
Closed Access | Times Cited: 18
An intelligent diagnosis method of rolling bearing based on multi-scale residual shrinkage convolutional neural network
Xiaoqiang Zhao, Yazhou Zhang
Measurement Science and Technology (2022) Vol. 33, Iss. 8, pp. 085103-085103
Closed Access | Times Cited: 15
A Siamese CNN-BiLSTM-based method for unbalance few-shot fault diagnosis of rolling bearings
Xiyang Liu, Guo Chen, Hao Wang, et al.
Measurement and Control (2023)
Open Access | Times Cited: 8
Performance degradation prediction model of rolling bearing based on self-checking long short-term memory network
Xiaosheng Lan, Yunfeng Li, Yuanhao Su, et al.
Measurement Science and Technology (2022) Vol. 34, Iss. 1, pp. 015016-015016
Closed Access | Times Cited: 13
Drill Tools Sticking Prediction Based on Adaptive Long Short-Term Memory
Honglin Wu, Zhongbin Wang, Lei Si, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 8, pp. 086134-086134
Closed Access | Times Cited: 2
A multiscale convolution neural network for bearing fault diagnosis based on frequency division denoising under complex noise conditions
Youming Wang, Gongqing Cao
Complex & Intelligent Systems (2022) Vol. 9, Iss. 4, pp. 4263-4285
Open Access | Times Cited: 10
A combined deep learning model for damage size estimation of rolling bearing
Xiyang Liu, Guo Chen, Tengfei Hao, et al.
International Journal of Engine Research (2022) Vol. 24, Iss. 4, pp. 1362-1373
Closed Access | Times Cited: 9
Deep subclass alignment transfer network based on time–frequency features for intelligent fault diagnosis of planetary gearboxes under time-varying speeds
Songjun Han, Zhipeng Feng
Measurement Science and Technology (2022) Vol. 33, Iss. 10, pp. 105010-105010
Closed Access | Times Cited: 8
An improved semi-supervised prototype network for few-shot fault diagnosis
Zhenlian Lu, Jianglong Li, Jie Wu
Maintenance Reliability and Condition Monitoring (2024) Vol. 4, Iss. 1, pp. 18-31
Open Access | Times Cited: 1
An intelligent fault diagnosis method for an electromechanical actuator based on sparse feature and long short-term network
Jing Yang, Yingqing Guo, Wanli Zhao
Measurement Science and Technology (2021) Vol. 32, Iss. 9, pp. 095102-095102
Closed Access | Times Cited: 11
A Combination of Dilated Self-Attention Capsule Networks and Bidirectional Long- and Short-Term Memory Networks for Vibration Signal Denoising
Youming Wang, Gongqing Cao, Jiali Han
Machines (2022) Vol. 10, Iss. 10, pp. 840-840
Open Access | Times Cited: 7
A Rolling Bearing Fault Diagnosis Method Based on Enhanced Integrated Filter Network
Kang Wu, Jie Tao, Dalian Yang, et al.
Machines (2022) Vol. 10, Iss. 6, pp. 481-481
Open Access | Times Cited: 6
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