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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 novel intelligent diagnosis method of rolling bearing and rotor composite faults based on vibration signal-to-image mapping and CNN-SVM
Hongwei Fan, Ceyi Xue, Jiateng Ma, et al.
Measurement Science and Technology (2022) Vol. 34, Iss. 4, pp. 044008-044008
Closed Access | Times Cited: 43

Showing 1-25 of 43 citing articles:

Compound fault diagnosis of diesel engines by combining generative adversarial networks and transfer learning
Zhiquan Cui, Yanlin Lu, Yan Xu, et al.
Expert Systems with Applications (2024) Vol. 251, pp. 123969-123969
Closed Access | Times Cited: 10
Improved SE-ResNet Acoustic–Vibration Fusion for Rolling Bearing Composite Fault Diagnosis
Xiaojiao Gu, Yang Tian, Chi Li, et al.
Applied Sciences (2024) Vol. 14, Iss. 5, pp. 2182-2182
Open Access | Times Cited: 9
A gray texture image data-driven intelligent fault diagnosis method of induction motor rotor-bearing system under variable load conditions
Hongwei Fan, Zhongfu Ren, Xuhui Zhang, et al.
Measurement (2024) Vol. 233, pp. 114742-114742
Closed Access | Times Cited: 7
Deep learning based approaches for intelligent industrial machinery health management and fault diagnosis in resource-constrained environments
Ali Saeed, Muazzam A. Khan, Usman Akram, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Fast and stable fault diagnosis method for composite fault of subsea production system
Chao Yang, Baoping Cai, Xiangdi Kong, et al.
Mechanical Systems and Signal Processing (2025) Vol. 226, pp. 112373-112373
Closed Access
The research on fault diagnosis of rolling bearing based on current signal CNN-SVM
Xinghua Wang, Runxin Meng, Guangtao Wang, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 12, pp. 125021-125021
Closed Access | Times Cited: 14
Image deep learning in fault diagnosis of mechanical equipment
Chuanhao Wang, Yongjian Sun, Xiaohong Wang
Journal of Intelligent Manufacturing (2023) Vol. 35, Iss. 6, pp. 2475-2515
Closed Access | Times Cited: 13
Bearing fault diagnosis based on transfer learning with dual-flow manifold ResNet and improved CapsNet
L Yao, Hongwei Wang, Tao Lei, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 7, pp. 076123-076123
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
A Bearing Fault Diagnosis Model Based on a Simplified Wide Convolutional Neural Network and Random Forrest
Qikai Zhang, Yunan Yao, Yage Huang, et al.
Sensors (2025) Vol. 25, Iss. 3, pp. 752-752
Open Access
Intelligent fault diagnosis method for rotating machinery based on sample multirepresentation information fusion under limited labeled samples conditions
Xin Yang, Xinsheng Cao, Jiangbin Zhao, et al.
Measurement (2025), pp. 117164-117164
Closed Access
A small sample bearing fault diagnosis method based on novel Zernike moment feature attention convolutional neural network
Yunji Zhao, Xu Jun
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 066208-066208
Closed Access | Times Cited: 3
AI-Enabled Industrial Equipment Monitoring, Diagnosis and Health Management
Zhuyun Chen, Haidong Shao, Te Han, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 5, pp. 050102-050102
Closed Access | Times Cited: 2
A novel semi-supervised learning rolling bearing fault diagnosis method based on SNNGAN
Zhi Qiu, Shanfei Fan, Haibo Liang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 8, pp. 086135-086135
Closed Access | Times Cited: 2
Rolling Bearing Residual Useful Life Prediction Model Based on the Particle Swarm Optimization-Optimized Fusion of Convolutional Neural Network and Bidirectional Long–Short-Term Memory–Multihead Self-Attention
Jianzhong Yang, Xinggang Zhang, Song Liu, et al.
Electronics (2024) Vol. 13, Iss. 11, pp. 2120-2120
Open Access | Times Cited: 2
Fault diagnosis of gas turbine generator bearings using enhanced valuable sample strategy and convolutional neural network
Xiaozhuo Xu, Zhiyuan Li, Yunji Zhao, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 015021-015021
Closed Access | Times Cited: 6
Rolling bearing fault diagnosis model based on DSCB-NFAM
Xiaoqiang Zhao, Haike Guo
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 015029-015029
Closed Access | Times Cited: 5
A GTI&Ada-Act LMCNN Method for Intelligent Fault Diagnosis of Motor Rotor-Bearing Unit Under Variable Conditions
Hongwei Fan, Zhongfu Ren, Xiangang Cao, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-14
Closed Access | Times Cited: 1
Health indicator adaptive construction method of rotating machinery under variable working conditions based on spatiotemporal fusion autoencoder
Yong Duan, Xiangang Cao, Jiangbin Zhao, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102945-102945
Closed Access | Times Cited: 1
An intelligent multi-element fault diagnosis method of rolling bearings considering damage degrees and sensor abnormity under small samples
Hongwei Fan, Buran Chen, Xiangang Cao, et al.
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science (2024)
Closed Access | Times Cited: 1
An ensemble deep learning approach for untrained compound fault diagnosis in bearings under unstable conditions
Miao Jiang, Yang Xiang
Measurement Science and Technology (2023) Vol. 35, Iss. 2, pp. 025907-025907
Closed Access | Times Cited: 4
RS-SVM Machine Learning Approach Driven by Case Data for Selecting Urban Drainage Network Restoration Scheme
Jiang Li, Zheng Geng, Dongxiao Gu, et al.
Data Intelligence (2022) Vol. 5, Iss. 2, pp. 413-437
Open Access | Times Cited: 5
An Internal Detector Positioning Method in Oil Pipelines Using Vibration Signal
Senxiang Lu, Tianhong Zhou, Chenyang Wang, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 12, pp. 13411-13421
Closed Access | Times Cited: 2
Intelligent fault diagnosis for variable working conditions of rotor-bearing system based on vibration image and domain adaptation
Mengting Zhu, Xiaoyue Liu, Cong Peng, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 12, pp. 125105-125105
Closed Access | Times Cited: 2
Computational Intelligence for Detection of Bearing Faults in Permanent Magnet Synchronous Motor Using Current Signal
G Geetha, P. Geethanjali
(2024)
Closed Access
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