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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-fault classification based on wavelet SVM with PSO algorithm to analyze vibration signals from rolling element bearings
Zhiwen Liu, Hongrui Cao, Xuefeng Chen, et al.
Neurocomputing (2012) Vol. 99, pp. 399-410
Closed Access | Times Cited: 266

Showing 1-25 of 266 citing articles:

Artificial intelligence for fault diagnosis of rotating machinery: A review
Ruonan Liu, Boyuan Yang, Enrico Zio, et al.
Mechanical Systems and Signal Processing (2018) Vol. 108, pp. 33-47
Closed Access | Times Cited: 1729
Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals
Jaouher Ben Ali, Nader Fnaiech, Lotfi Saïdi, et al.
Applied Acoustics (2014) Vol. 89, pp. 16-27
Closed Access | Times Cited: 700
A novel bearing fault diagnosis model integrated permutation entropy, ensemble empirical mode decomposition and optimized SVM
Xiaoyuan Zhang, Yitao Liang, Jianzhong Zhou, et al.
Measurement (2015) Vol. 69, pp. 164-179
Closed Access | Times Cited: 524
A novel optimized SVM classification algorithm with multi-domain feature and its application to fault diagnosis of rolling bearing
Xiaoan Yan, Minping Jia
Neurocomputing (2018) Vol. 313, pp. 47-64
Closed Access | Times Cited: 433
Signal based condition monitoring techniques for fault detection and diagnosis of induction motors: A state-of-the-art review
Purushottam Gangsar, Rajiv Tiwari
Mechanical Systems and Signal Processing (2020) Vol. 144, pp. 106908-106908
Closed Access | Times Cited: 422
A summary of fault modelling and predictive health monitoring of rolling element bearings
Idriss El‐Thalji, Erkki Jantunen
Mechanical Systems and Signal Processing (2015) Vol. 60-61, pp. 252-272
Closed Access | Times Cited: 394
Recent advances on SVM based fault diagnosis and process monitoring in complicated industrial processes
Zuyu Yin, Jian Hou
Neurocomputing (2015) Vol. 174, pp. 643-650
Closed Access | Times Cited: 293
A new rolling bearing fault diagnosis method based on multiscale permutation entropy and improved support vector machine based binary tree
Yongbo Li, Minqiang Xu, Wei Yu, et al.
Measurement (2015) Vol. 77, pp. 80-94
Closed Access | Times Cited: 260
The concept and progress of intelligent spindles: A review
Hongrui Cao, Xingwu Zhang, Xuefeng Chen
International Journal of Machine Tools and Manufacture (2016) Vol. 112, pp. 21-52
Closed Access | Times Cited: 247
Challenges and Opportunities of Deep Learning Models for Machinery Fault Detection and Diagnosis: A Review
Mohd Syahril Ramadhan Mohd Saufi, Zair Asrar Ahmad, M. Salman Leong, et al.
IEEE Access (2019) Vol. 7, pp. 122644-122662
Open Access | Times Cited: 225
Knowledge Transfer for Rotary Machine Fault Diagnosis
Ruqiang Yan, Fei Shen, Chuang Sun, et al.
IEEE Sensors Journal (2019) Vol. 20, Iss. 15, pp. 8374-8393
Closed Access | Times Cited: 215
A Novel Method for Imbalanced Fault Diagnosis of Rotating Machinery Based on Generative Adversarial Networks
Zhenxiang Li, Taisheng Zheng, Yang Wang, et al.
IEEE Transactions on Instrumentation and Measurement (2020) Vol. 70, pp. 1-17
Closed Access | Times Cited: 139
Advances in materials and machine learning techniques for energy storage devices: A comprehensive review
Prit Thakkar, Sachi Khatri, Drashti Dobariya, et al.
Journal of Energy Storage (2024) Vol. 81, pp. 110452-110452
Closed Access | Times Cited: 20
A roller bearing fault diagnosis method based on hierarchical entropy and support vector machine with particle swarm optimization algorithm
Keheng Zhu, Song Xi-geng, Dongxin Xue
Measurement (2013) Vol. 47, pp. 669-675
Closed Access | Times Cited: 168
Adapted ensemble classification algorithm based on multiple classifier system and feature selection for classifying multi-class imbalanced data
Yijing Li, Haixiang Guo, Liu Xiao, et al.
Knowledge-Based Systems (2015) Vol. 94, pp. 88-104
Closed Access | Times Cited: 158
Basic research on machinery fault diagnostics: Past, present, and future trends
Xuefeng Chen, Shibin Wang, Baijie Qiao, et al.
Frontiers of Mechanical Engineering (2017) Vol. 13, Iss. 2, pp. 264-291
Open Access | Times Cited: 138
A comprehensive review of artificial intelligence-based approaches for rolling element bearing PHM: shallow and deep learning
Moussa Hamadache, Joon Ha Jung, Jung‐Ho Park, et al.
JMST Advances (2019) Vol. 1, Iss. 1-2, pp. 125-151
Open Access | Times Cited: 129
Recent progress on decoupling diagnosis of hybrid failures in gear transmission systems using vibration sensor signal: A review
Zhixiong Li, Yu Jiang, Chao Hu, et al.
Measurement (2016) Vol. 90, pp. 4-19
Closed Access | Times Cited: 128
Online automatic diagnosis of wind turbine bearings progressive degradations under real experimental conditions based on unsupervised machine learning
Jaouher Ben Ali, Lotfi Saïdi, Salma Harrath, et al.
Applied Acoustics (2017) Vol. 132, pp. 167-181
Closed Access | Times Cited: 128
Feature extraction and fault severity classification in ball bearings
Aditya Sharma, M. Amarnath, Pavan Kumar Kankar
Journal of Vibration and Control (2014) Vol. 22, Iss. 1, pp. 176-192
Closed Access | Times Cited: 126
Autocorrelation Aided Random Forest Classifier-Based Bearing Fault Detection Framework
Sayanjit Singha Roy, Sayantan Dey, Soumya Chatterjee
IEEE Sensors Journal (2020) Vol. 20, Iss. 18, pp. 10792-10800
Closed Access | Times Cited: 126
A novel intelligent method for mechanical fault diagnosis based on dual-tree complex wavelet packet transform and multiple classifier fusion
Jinxiu Qu, Zhousuo Zhang, Teng Gong
Neurocomputing (2015) Vol. 171, pp. 837-853
Closed Access | Times Cited: 126
Remaining useful life estimation using an inverse Gaussian degradation model
Donghui Pan, Jia‐Bao Liu, Jinde Cao
Neurocomputing (2015) Vol. 185, pp. 64-72
Open Access | Times Cited: 124
Multi-fault diagnosis for rotating machinery based on orthogonal supervised linear local tangent space alignment and least square support vector machine
Zuqiang Su, Baoping Tang, Ziran Liu, et al.
Neurocomputing (2015) Vol. 157, pp. 208-222
Closed Access | Times Cited: 116
A New Two-Level Hierarchical Diagnosis Network Based on Convolutional Neural Network
Long Wen, Xinyu Li, Liang Gao
IEEE Transactions on Instrumentation and Measurement (2019) Vol. 69, Iss. 2, pp. 330-338
Closed Access | Times Cited: 106
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