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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:

Multi-input CNN based vibro-acoustic fusion for accurate fault diagnosis of induction motor
Anurag Choudhary, Rismaya Kumar Mishra, Shahab Fatima, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 120, pp. 105872-105872
Closed Access | Times Cited: 90

Showing 1-25 of 90 citing articles:

A fault diagnosis method using improved prototypical network and weighting similarity-Manhattan distance with insufficient noisy data
Changdong Wang, Jingli Yang, Baoqin Zhang
Measurement (2024) Vol. 226, pp. 114171-114171
Closed Access | Times Cited: 33
Fault Detection in Induction Machines Using Learning Models and Fourier Spectrum Image Analysis
Kevin Barrera, Jordi Burriel-Valencia, Ángel Sapena-Bañó, et al.
Sensors (2025) Vol. 25, Iss. 2, pp. 471-471
Open Access | Times Cited: 2
Multiple-signal defect identification of hydraulic pump using an adaptive normalized model and S transform
Yong Zhu, Shengnan Tang, Shouqi Yuan
Engineering Applications of Artificial Intelligence (2023) Vol. 124, pp. 106548-106548
Closed Access | Times Cited: 38
LDD-Net: Lightweight printed circuit board defect detection network fusing multi-scale features
Longxin Zhang, Jingsheng Chen, Jianguo Chen, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 129, pp. 107628-107628
Closed Access | Times Cited: 26
CDTFAFN: A novel coarse-to-fine dual-scale time-frequency attention fusion network for machinery vibro-acoustic fault diagnosis
Xiaoan Yan, Dong Jiang, Ling Xiang, et al.
Information Fusion (2024) Vol. 112, pp. 102554-102554
Closed Access | Times Cited: 11
A Novel Fault Diagnosis Method Based on SWT and VGG-LSTM Model for Hydraulic Axial Piston Pump
Yong Zhu, Hong Su, Shengnan Tang, et al.
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 3, pp. 594-594
Open Access | Times Cited: 20
Review on prognostics and health management in smart factory: From conventional to deep learning perspectives
Prashant Kumar, Izaz Raouf, Heung Soo Kim
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107126-107126
Closed Access | Times Cited: 16
Research on feature extraction method for different levels of cracks and pitting in spur gear based on dynamic characteristic templates
Wenzheng Liu, Rupeng Zhu, Wenguang Zhou, et al.
Measurement (2024) Vol. 228, pp. 114335-114335
Closed Access | Times Cited: 6
A Novel Fault Diagnosis Method for a Power Transformer Based on Multi-Scale Approximate Entropy and Optimized Convolutional Networks
Haikun Shang, Zhidong Liu, Yanlei Wei, et al.
Entropy (2024) Vol. 26, Iss. 3, pp. 186-186
Open Access | Times Cited: 6
Multi-sensor signal fusion method for rolling bearing based on the standard relative mean–variance value and random weighting algorithm
Zuozhou Pan, Zhengyuan Zhang, Peng Zhao, et al.
Measurement (2024) Vol. 235, pp. 114823-114823
Closed Access | Times Cited: 6
A performance-interpretable intelligent fusion of sound and vibration signals for bearing fault diagnosis via dynamic CAME
You Keshun, Lian Zengwei, Yingkui Gu
Nonlinear Dynamics (2024) Vol. 112, Iss. 23, pp. 20903-20940
Closed Access | Times Cited: 6
Modified LinkNet and DenseNet-Based Hybrid Architecture for Combined Fault Detection in an Electromechanical System
Yogesh Andhale, Anand Parey
Journal of Vibration Engineering & Technologies (2025) Vol. 13, Iss. 1
Closed Access
A Bayesian computational technique for learning the airflow resistance of acoustical fibrous materials at high temperatures
Thamasha Samarasinghe, Sumudu Herath
Building Acoustics (2025)
Closed Access
Lightweight train image fault detection model based on location information enhancement
Longxin Zhang, Yang Hu, Runti Tan, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 143, pp. 109941-109941
Closed Access
Intelligent Monitoring Technology of Partial Discharge Based on an Integrated Sensing–Memory–Computation System
Zhao Yú, Jia‐Wei Zhang, Fouad Belhora, et al.
Langmuir (2025)
Closed Access
Fault Diagnosis of Dynamic Chemical Processes Based on Improved Residual Network Combined with a Gated Recurrent Unit
Shiqian Han, Pingping WANG, Cheng Zhang, et al.
ACS Omega (2025) Vol. 10, Iss. 9, pp. 8859-8869
Open Access
Application of Machine Learning Algorithms for Tool Condition Monitoring in Milling Chipboard Process
Agata Przybyś-Małaczek, Izabella Antoniuk, Karol Szymanowski, et al.
Sensors (2023) Vol. 23, Iss. 13, pp. 5850-5850
Open Access | Times Cited: 13
Harnessing attention mechanisms in a comprehensive deep learning approach for induction motor fault diagnosis using raw electrical signals
Thanh-Tung Vo, Meng‐Kun Liu, Minh‐Quang Tran
Engineering Applications of Artificial Intelligence (2023) Vol. 129, pp. 107643-107643
Closed Access | Times Cited: 13
Acoustic fault diagnosis of three-phase induction motors using smartphone and deep learning
Adam Głowacz, Maciej Sułowicz, Jason S. Zielonka, et al.
Expert Systems with Applications (2024) Vol. 262, pp. 125633-125633
Closed Access | Times Cited: 4
Learning the dynamical response of nonlinear non-autonomous dynamical systems with deep operator neural networks
Guang Lin, Christian Moya, Zecheng Zhang
Engineering Applications of Artificial Intelligence (2023) Vol. 125, pp. 106689-106689
Open Access | Times Cited: 11
An intelligent diagnosis method for oil-well pump leakage fault in oilfield production Internet of Things system based on convolutional attention residual learning
Zongchao Huang, Kewen Li, Cuihong Ke, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 106829-106829
Closed Access | Times Cited: 11
A Bayesian CNN-based fusion framework of sensor fault diagnosis
Beiyan He, Chunli Zhu, Zhongxiang Li, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 4, pp. 046110-046110
Closed Access | Times Cited: 3
Pipeline damage identification in nuclear industry using a particle swarm optimization-enhanced machine learning approach
Qi Jiang, Wenzhong Qu, Xiao Li
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108467-108467
Closed Access | Times Cited: 3
Adaptive Fusion Transfer Learning-based Digital Multitwin-assised Intelligent Fault Diagnosis
Sizhe Liu, Yongsheng Qi, Liqiang Liu, et al.
Knowledge-Based Systems (2024) Vol. 297, pp. 111923-111923
Closed Access | Times Cited: 3
STP-Model: A semi-supervised framework with self-supervised learning capabilities for downhole fault diagnosis in sucker rod pumping systems
Zongchao Huang, Kewen Li, Zhifeng Xu, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108802-108802
Closed Access | Times Cited: 3
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