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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:

LSTM Based Bearing Fault Diagnosis of Electrical Machines using Motor Current Signal
Russell Sabir, Daniele Rosato, Sven Hartmann, et al.
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA) (2019), pp. 613-618
Closed Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

Fault detection and diagnosis for rotating machinery: A model based on convolutional LSTM, Fast Fourier and continuous wavelet transforms
Masoud Jalayer, Carlotta Orsenigo, Carlo Vercellis
Computers in Industry (2020) Vol. 125, pp. 103378-103378
Closed Access | Times Cited: 251
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
Artificial Intelligence-Based Technique for Fault Detection and Diagnosis of EV Motors: A Review
Wangjie Lang, Yihua Hu, Chao Gong, et al.
IEEE Transactions on Transportation Electrification (2021) Vol. 8, Iss. 1, pp. 384-406
Open Access | Times Cited: 100
Few-Shot Bearing Fault Diagnosis Based on Model-Agnostic Meta-Learning
Shen Zhang, Fei Ye, Bingnan Wang, et al.
IEEE Transactions on Industry Applications (2021) Vol. 57, Iss. 5, pp. 4754-4764
Open Access | Times Cited: 82
Wavelet LSTM for Fault Forecasting in Electrical Power Grids
Nathielle Waldrigues Branco, Mariana Santos Matos Cavalca, Stéfano Frizzo Stefenon, et al.
Sensors (2022) Vol. 22, Iss. 21, pp. 8323-8323
Open Access | Times Cited: 37
Data-Driven Intelligent Condition Adaptation of Feature Extraction for Bearing Fault Detection Using Deep Responsible Active Learning
T R Mahesh, Saravanan Chandrasekaran, Veerma Ram, et al.
IEEE Access (2024) Vol. 12, pp. 45381-45397
Open Access | Times Cited: 11
An efficient method for bearing fault diagnosis
G Geetha, P. Geethanjali
Systems Science & Control Engineering (2024) Vol. 12, Iss. 1
Open Access | Times Cited: 7
Hierarchical diagnosis of bearing faults using branch convolutional neural network considering noise interference and variable working conditions
Kaige Su, Jianhua Liu, Hui Xiong
Knowledge-Based Systems (2021) Vol. 230, pp. 107386-107386
Closed Access | Times Cited: 48
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
A Time Series Prediction-Based Method for Rotating Machinery Detection and Severity Assessment
Weirui Zhang, Zeru Sun, Dongxu Lv, et al.
Aerospace (2024) Vol. 11, Iss. 7, pp. 537-537
Open Access | Times Cited: 4
A hybrid LSTM random forest model with grey wolf optimization for enhanced detection of multiple bearing faults
Said Djaballah, Lotfi Saïdi, Kamel Meftah, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
Delamination Detection Framework for the Imbalanced Dataset in Laminated Composite Using Wasserstein Generative Adversarial Network-Based Data Augmentation
S. Kim, Muhammad Muzammil Azad, Jinwoo Song, et al.
Applied Sciences (2023) Vol. 13, Iss. 21, pp. 11837-11837
Open Access | Times Cited: 11
Advancing bearing fault diagnosis under variable working conditions: a CEEMDAN-SBS approach with vibro-electric signal integration
Abdel wahhab Lourari, Abdenour Soualhi, Tarak Benkedjouh
The International Journal of Advanced Manufacturing Technology (2024) Vol. 132, Iss. 5-6, pp. 2753-2772
Open Access | Times Cited: 3
Exploring real-time fault detection of high-speed train traction motor based on machine learning and wavelet analysis
Yanshu Li
Neural Computing and Applications (2021) Vol. 34, Iss. 12, pp. 9301-9314
Closed Access | Times Cited: 24
Wavelet Long Short-Term Memory to Fault Forecasting in Electrical Power Grids
Nathielle Waldrigues Branco, Mariana Santos Matos Cavalca, Stéfano Frizzo Stefenon, et al.
(2022)
Open Access | Times Cited: 17
Novel Data-Driven Approach Based on Capsule Network for Intelligent Multi-Fault Detection in Electric Motors
Jianjun Chen, Weihao Hu, Di Cao, et al.
IEEE Transactions on Energy Conversion (2020) Vol. 36, Iss. 3, pp. 2173-2184
Open Access | Times Cited: 25
Deep Residual Network Combined with Transfer Learning Based Fault Diagnosis for Rolling Bearing
Jianmin Zhou, Xiaotong Yang, Jiahui Li
Applied Sciences (2022) Vol. 12, Iss. 15, pp. 7810-7810
Open Access | Times Cited: 15
Fault classification of three phase induction motors using Bi-LSTM networks
Jeevesh Vanga, Durga Prabhu Ranimekhala, Swathi Jonnala, et al.
Journal of Electrical Systems and Information Technology (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 8
Multi-Channel LSTM-Capsule Autoencoder Network for Anomaly Detection on Multivariate Data
Ayman Elhalwagy, Tatiana Kalganova
Applied Sciences (2022) Vol. 12, Iss. 22, pp. 11393-11393
Open Access | Times Cited: 13
Unveiling the Black Box: A Unified XAI Framework for Signal-Based Deep Learning Models
Ardeshir Shojaeinasab, Masoud Jalayer, Amirali Baniasadi, et al.
Machines (2024) Vol. 12, Iss. 2, pp. 121-121
Open Access | Times Cited: 2
Signal Generation using 1d Deep Convolutional Generative Adversarial Networks for Fault Diagnosis of Electrical Machines
Russell Sabir, Daniele Rosato, Sven Hartmann, et al.
2022 26th International Conference on Pattern Recognition (ICPR) (2021)
Closed Access | Times Cited: 17
Adaptive weight-based capsule neural network for bearing fault diagnosis
Xiaoqiang Zhao, Jingxuan Chai
Measurement Science and Technology (2023) Vol. 34, Iss. 6, pp. 065008-065008
Closed Access | Times Cited: 6
Real-Time Neural Classifiers for Sensor Faults in Three Phase Induction Motors
Oscar D. Sánchez, Gabriel Martínez-Soltero, Jesús Gerardo Cruz Álvarez, et al.
IEEE Access (2023) Vol. 11, pp. 19657-19668
Open Access | Times Cited: 5
Bearing Fault Diagnosis via Incremental Learning Based on the Repeated Replay Using Memory Indexing (R-REMIND) Method
Junhui Zheng, Hui Xiong, Yuchang Zhang, et al.
Machines (2022) Vol. 10, Iss. 5, pp. 338-338
Open Access | Times Cited: 8
CNN Hardware Accelerator for Real-Time Bearing Fault Diagnosis
Ching-Che Chung, Yu-Pei Liang, Jiang HongJin
Sensors (2023) Vol. 23, Iss. 13, pp. 5897-5897
Open Access | Times Cited: 4
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