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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:

Initial center frequency-guided VMD for fault diagnosis of rotating machines
Xingxing Jiang, Changqing Shen, Juanjuan Shi, et al.
Journal of Sound and Vibration (2018) Vol. 435, pp. 36-55
Closed Access | Times Cited: 182

Showing 1-25 of 182 citing articles:

A systematic review of deep transfer learning for machinery fault diagnosis
Chuan Li, Shaohui Zhang, Qin Yi, et al.
Neurocomputing (2020) Vol. 407, pp. 121-135
Closed Access | Times Cited: 348
Machinery fault diagnosis with imbalanced data using deep generative adversarial networks
Zhang We, Xiang Li, Xiaodong Jia, et al.
Measurement (2019) Vol. 152, pp. 107377-107377
Closed Access | Times Cited: 299
The Entropy Algorithm and Its Variants in the Fault Diagnosis of Rotating Machinery: A Review
Yongbo Li, Xianzhi Wang, Zhenbao Liu, et al.
IEEE Access (2018) Vol. 6, pp. 66723-66741
Open Access | Times Cited: 254
Ensemble transfer CNNs driven by multi-channel signals for fault diagnosis of rotating machinery cross working conditions
Zhiyi He, Haidong Shao, Xiang Zhong, et al.
Knowledge-Based Systems (2020) Vol. 207, pp. 106396-106396
Closed Access | Times Cited: 206
Research on Remaining Useful Life Prediction of Rolling Element Bearings Based on Time-Varying Kalman Filter
Lingli Cui, Xin Wang, Huaqing Wang, et al.
IEEE Transactions on Instrumentation and Measurement (2019) Vol. 69, Iss. 6, pp. 2858-2867
Closed Access | Times Cited: 186
Bearing fault diagnosis method based on adaptive maximum cyclostationarity blind deconvolution
Zhijian Wang, Jie Zhou, Wenhua Du, et al.
Mechanical Systems and Signal Processing (2021) Vol. 162, pp. 108018-108018
Closed Access | Times Cited: 183
A fault information-guided variational mode decomposition (FIVMD) method for rolling element bearings diagnosis
Qing Ni, Jinchen Ji, Ke Feng, et al.
Mechanical Systems and Signal Processing (2021) Vol. 164, pp. 108216-108216
Closed Access | Times Cited: 181
A Hybrid Generalization Network for Intelligent Fault Diagnosis of Rotating Machinery Under Unseen Working Conditions
Te Han, Yan‐Fu Li, Min Qian
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-11
Closed Access | Times Cited: 179
Feature Mode Decomposition: New Decomposition Theory for Rotating Machinery Fault Diagnosis
Yonghao Miao, Boyao Zhang, Chenhui Li, et al.
IEEE Transactions on Industrial Electronics (2022) Vol. 70, Iss. 2, pp. 1949-1960
Closed Access | Times Cited: 174
FEM Simulation-Based Generative Adversarial Networks to Detect Bearing Faults
Yun Gao, Xiaoyang Liu, Jiawei Xiang
IEEE Transactions on Industrial Informatics (2020) Vol. 16, Iss. 7, pp. 4961-4971
Closed Access | Times Cited: 165
A review on the application of blind deconvolution in machinery fault diagnosis
Yonghao Miao, Boyao Zhang, Jing Lin, et al.
Mechanical Systems and Signal Processing (2021) Vol. 163, pp. 108202-108202
Closed Access | Times Cited: 162
Deep representation clustering-based fault diagnosis method with unsupervised data applied to rotating machinery
Xiang Li, Xu Li, Hui Ma
Mechanical Systems and Signal Processing (2020) Vol. 143, pp. 106825-106825
Closed Access | Times Cited: 137
Adversarial Domain-Invariant Generalization: A Generic Domain-Regressive Framework for Bearing Fault Diagnosis Under Unseen Conditions
Liang Chen, Qi Li, Changqing Shen, et al.
IEEE Transactions on Industrial Informatics (2021) Vol. 18, Iss. 3, pp. 1790-1800
Open Access | Times Cited: 137
Central frequency mode decomposition and its applications to the fault diagnosis of rotating machines
Xingxing Jiang, Qiuyu Song, Haien Wang, et al.
Mechanism and Machine Theory (2022) Vol. 174, pp. 104919-104919
Closed Access | Times Cited: 100
Smart multichannel mode extraction for enhanced bearing fault diagnosis
Qiuyu Song, Xingxing Jiang, Guifu Du, et al.
Mechanical Systems and Signal Processing (2023) Vol. 189, pp. 110107-110107
Closed Access | Times Cited: 49
Deep network-based maximum correlated kurtosis deconvolution: A novel deep deconvolution for bearing fault diagnosis
Yonghao Miao, Chenhui Li, Huifang Shi, et al.
Mechanical Systems and Signal Processing (2023) Vol. 189, pp. 110110-110110
Open Access | Times Cited: 48
Knowledge mapping-based adversarial domain adaptation: A novel fault diagnosis method with high generalizability under variable working conditions
Qi Li, Changqing Shen, Liang Chen, et al.
Mechanical Systems and Signal Processing (2020) Vol. 147, pp. 107095-107095
Closed Access | Times Cited: 128
Gear Fault Diagnosis Based on Genetic Mutation Particle Swarm Optimization VMD and Probabilistic Neural Network Algorithm
Jiakai Ding, Dongming Xiao, Xuejun Li
IEEE Access (2020) Vol. 8, pp. 18456-18474
Open Access | Times Cited: 99
An adaptive and efficient variational mode decomposition and its application for bearing fault diagnosis
Xingxing Jiang, Jun Wang, Changqing Shen, et al.
Structural Health Monitoring (2020) Vol. 20, Iss. 5, pp. 2708-2725
Closed Access | Times Cited: 99
Generalization of Deep Neural Networks for Imbalanced Fault Classification of Machinery Using Generative Adversarial Networks
Jinrui Wang, Shunming Li, Baokun Han, et al.
IEEE Access (2019) Vol. 7, pp. 111168-111180
Open Access | Times Cited: 76
Fast nonlinear blind deconvolution for rotating machinery fault diagnosis
Zongzhen Zhang, Jinrui Wang, Shunming Li, et al.
Mechanical Systems and Signal Processing (2022) Vol. 187, pp. 109918-109918
Closed Access | Times Cited: 64
Online chatter detection in milling process based on fast iterative VMD and energy ratio difference
Pengfei Zhang, Dong Gao, Yong Lü, et al.
Measurement (2022) Vol. 194, pp. 111060-111060
Closed Access | Times Cited: 46
Self-Adaptive Multivariate Variational Mode Decomposition and Its Application for Bearing Fault Diagnosis
Qiuyu Song, Xingxing Jiang, Shuang Wang, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-13
Closed Access | Times Cited: 40
Time series diffusion method: A denoising diffusion probabilistic model for vibration signal generation
Haiming Yi, Lei Hou, Yuhong Jin, et al.
Mechanical Systems and Signal Processing (2024) Vol. 216, pp. 111481-111481
Open Access | Times Cited: 10
An intelligent diagnosis framework for roller bearing fault under speed fluctuation condition
Baokun Han, Shanshan Ji, Jinrui Wang, et al.
Neurocomputing (2020) Vol. 420, pp. 171-180
Closed Access | Times Cited: 68
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