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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:

Bearing Fault Classification Based on Convolutional Neural Network in Noise Environment
Qinyu Jiang, Faliang Chang, Bowen Sheng
IEEE Access (2019) Vol. 7, pp. 69795-69807
Open Access | Times Cited: 67

Showing 1-25 of 67 citing articles:

Multisensor data fusion for gearbox fault diagnosis using 2-D convolutional neural network and motor current signature analysis
Moslem Azamfar, Jaskaran Singh, Iñaki Bravo-Imaz, et al.
Mechanical Systems and Signal Processing (2020) Vol. 144, pp. 106861-106861
Closed Access | Times Cited: 260
Data Preprocessing Techniques in Convolutional Neural Network Based on Fault Diagnosis Towards Rotating Machinery
Shengnan Tang, Shouqi Yuan, Yong Zhu
IEEE Access (2020) Vol. 8, pp. 149487-149496
Open Access | Times Cited: 114
DTCNNMI: A deep twin convolutional neural networks with multi-domain inputs for strongly noisy diesel engine misfire detection
Chengjin Qin, Yanrui Jin, Jianfeng Tao, et al.
Measurement (2021) Vol. 180, pp. 109548-109548
Closed Access | Times Cited: 70
A physics-informed feature weighting method for bearing fault diagnostics
Hao Lü, Venkat Pavan Nemani, Vahid Barzegar, et al.
Mechanical Systems and Signal Processing (2023) Vol. 191, pp. 110171-110171
Open Access | Times Cited: 34
Rotating Machinery Fault Diagnosis Based on Typical Resonance Demodulation Methods: A Review
Hua Li, Xing Wu, Tao Liu, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 7, pp. 6439-6459
Closed Access | Times Cited: 24
A Lightweight Transformer With Strong Robustness Application in Portable Bearing Fault Diagnosis
Hairui Fang, Jialin An, Han Liu, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 9, pp. 9649-9657
Closed Access | Times Cited: 23
A New Convolutional Neural Network With Random Forest Method for Hydrogen Sensor Fault Diagnosis
Yongyi Sun, Hongquan Zhang, Tingting Zhao, et al.
IEEE Access (2020) Vol. 8, pp. 85421-85430
Open Access | Times Cited: 49
Parallel multi-fusion convolutional neural networks based fault diagnosis of rotating machinery under noisy environments
Guoqiang Li, Jun Wu, Chao Deng, et al.
ISA Transactions (2021) Vol. 128, pp. 545-555
Closed Access | Times Cited: 39
Feature Engineering and Artificial Intelligence-Supported Approaches Used for Electric Powertrain Fault Diagnosis: A Review
Xiaotian Zhang, Yihua Hu, Jiamei Deng, et al.
IEEE Access (2022) Vol. 10, pp. 29069-29088
Open Access | Times Cited: 26
Deep Learning in Industrial Machinery: A Critical Review of Bearing Fault Classification Methods
Attiq Ur Rehman, Weidong Jiao, Yonghua Jiang, et al.
Applied Soft Computing (2025), pp. 112785-112785
Closed Access
A Cost-Efficient MFCC-Based Fault Detection and Isolation Technology for Electromagnetic Pumps
Ugochukwu Ejike Akpudo, Jang-Wook Hur
Electronics (2021) Vol. 10, Iss. 4, pp. 439-439
Open Access | Times Cited: 30
Bearing Fault Detection in Adjustable Speed Drive-Powered Induction Machine by Using Motor Current Signature Analysis and Goodness-of-Fit Tests
Victor Aviña-Corral, Jose Rangel‐Magdaleno, Carlos Morales-Perez, et al.
IEEE Transactions on Industrial Informatics (2021) Vol. 17, Iss. 12, pp. 8265-8274
Closed Access | Times Cited: 29
Early and Intelligent Bearing Fault Detection Using Adaptive Superlets
S. K. Mitra, Chiranjib Koley
IEEE Sensors Journal (2023) Vol. 23, Iss. 7, pp. 7992-8000
Closed Access | Times Cited: 12
Improved Mel Frequency Cepstral Coefficients for Compressors and Pumps Fault Diagnosis with Deep Learning Models
Diego Cabrera, Rubén Medina, Mariela Cerrada, et al.
Applied Sciences (2024) Vol. 14, Iss. 5, pp. 1710-1710
Open Access | Times Cited: 4
MFCC based ensemble learning method for multiple fault diagnosis of roller bearing
Gangavva Choudakkanavar, J. Alamelu Mangai, Mohit Bansal
International Journal of Information Technology (2022) Vol. 14, Iss. 5, pp. 2741-2751
Closed Access | Times Cited: 16
Multi-mode non-Gaussian variational autoencoder network with missing sources for anomaly detection of complex electromechanical equipment
Qinyuan Luo, Jinglong Chen, Yanyang Zi, et al.
ISA Transactions (2022) Vol. 134, pp. 144-158
Closed Access | Times Cited: 16
An Intelligent Ball Bearing Fault Diagnosis System Using Enhanced Rotational Characteristics on Spectrogram
Gyujin Seong, Dongwan Kim
Sensors (2024) Vol. 24, Iss. 3, pp. 776-776
Open Access | Times Cited: 3
Mel frequency mapping for intelligent diagnosis of rolling element bearings across different working conditions
yubin yue, Hongjun Wang, Shenglun Zhang
Applied Acoustics (2024) Vol. 220, pp. 109944-109944
Closed Access | Times Cited: 3
Condition Monitoring and Fault Diagnosis of Rotating Machinery Towards Intelligent Manufacturing: Review and Prospect
Hui Zhang, W Che, Youren Cao, et al.
Iranian Journal of Science and Technology Transactions of Mechanical Engineering (2024)
Closed Access | Times Cited: 3
Research on a percussion-based bolt looseness identification method based on phase feature and convolutional neural network
Pengtao Liu, Xiaopeng Wang, Tianning Chen, et al.
Smart Materials and Structures (2023) Vol. 32, Iss. 3, pp. 035010-035010
Closed Access | Times Cited: 8
Research on SVM-Based Bearing Fault Diagnosis Modeling and Multiple Swarm Genetic Algorithm Parameter Identification Method
Changchun Mo, Huizi Han, Mei Liu, et al.
Mathematics (2023) Vol. 11, Iss. 13, pp. 2864-2864
Open Access | Times Cited: 8
Multi-head de-noising autoencoder-based multi-task model for fault diagnosis of rolling element bearings under various speed conditions
Jongmin Park, Jinoh Yoo, Tae-Hyung Kim, et al.
Journal of Computational Design and Engineering (2023) Vol. 10, Iss. 4, pp. 1804-1820
Open Access | Times Cited: 8
Bearing Fault Detection in ASD-Powered Induction Machine Using MODWT and Image Edge Detection
Victor Aviña-Corral, Jose Rangel‐Magdaleno, Hayde Peregrina‐Barreto, et al.
IEEE Access (2022) Vol. 10, pp. 24181-24193
Open Access | Times Cited: 13
A Multi-Input Convolutional Neural Network Model for Electric Motor Mechanical Fault Classification Using Multiple Image Transformation and Merging Methods
In-Su Bae, Suan Lee
Machines (2024) Vol. 12, Iss. 2, pp. 105-105
Open Access | Times Cited: 2
Innovative predictive maintenance for mining grinding mills: from LSTM-based vibration forecasting to pixel-based MFCC image and CNN
Ayoub Rihi, Salah Baïna, Fatima-Zahra Mhada, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 135, Iss. 3-4, pp. 1271-1289
Closed Access | Times Cited: 2
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