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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:

Intelligent Fault Diagnosis of Multichannel Motor–Rotor System Based on Multimanifold Deep Extreme Learning Machine
Xiaoli Zhao, Minping Jia, Peng Ding, et al.
IEEE/ASME Transactions on Mechatronics (2020) Vol. 25, Iss. 5, pp. 2177-2187
Closed Access | Times Cited: 69

Showing 1-25 of 69 citing articles:

Novel Joint Transfer Network for Unsupervised Bearing Fault Diagnosis From Simulation Domain to Experimental Domain
Yiming Xiao, Haidong Shao, Song-Yu Han, et al.
IEEE/ASME Transactions on Mechatronics (2022) Vol. 27, Iss. 6, pp. 5254-5263
Closed Access | Times Cited: 225
Modified Stacked Autoencoder Using Adaptive Morlet Wavelet for Intelligent Fault Diagnosis of Rotating Machinery
Haidong Shao, Min Xia, Jiafu Wan, et al.
IEEE/ASME Transactions on Mechatronics (2021) Vol. 27, Iss. 1, pp. 24-33
Open Access | Times Cited: 167
Semi-supervised meta-learning networks with squeeze-and-excitation attention for few-shot fault diagnosis
Yong Feng, Jinglong Chen, Tianci Zhang, et al.
ISA Transactions (2021) Vol. 120, pp. 383-401
Closed Access | Times Cited: 158
Semisupervised Graph Convolution Deep Belief Network for Fault Diagnosis of Electormechanical System With Limited Labeled Data
Xiaoli Zhao, Minping Jia, Zheng Liu
IEEE Transactions on Industrial Informatics (2020) Vol. 17, Iss. 8, pp. 5450-5460
Closed Access | Times Cited: 137
Feature Extraction Using Parameterized Multisynchrosqueezing Transform
Xinyan Li, Huimin Zhao, Ling Yu, et al.
IEEE Sensors Journal (2022) Vol. 22, Iss. 14, pp. 14263-14272
Closed Access | Times Cited: 96
A Systematic Review on Imbalanced Learning Methods in Intelligent Fault Diagnosis
Zhijun Ren, Tantao Lin, Ke Feng, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-35
Closed Access | Times Cited: 87
Multiscale Deep Graph Convolutional Networks for Intelligent Fault Diagnosis of Rotor-Bearing System Under Fluctuating Working Conditions
Xiaoli Zhao, Jianyong Yao, Wenxiang Deng, et al.
IEEE Transactions on Industrial Informatics (2022) Vol. 19, Iss. 1, pp. 166-176
Closed Access | Times Cited: 78
Supervised Contrastive Learning-Based Domain Adaptation Network for Intelligent Unsupervised Fault Diagnosis of Rolling Bearing
Yongchao Zhang, Zhaohui Ren, Shihua Zhou, et al.
IEEE/ASME Transactions on Mechatronics (2022) Vol. 27, Iss. 6, pp. 5371-5380
Closed Access | Times Cited: 76
Model-Assisted Multi-source Fusion Hypergraph Convolutional Neural Networks for intelligent few-shot fault diagnosis to Electro-Hydrostatic Actuator
Xiaoli Zhao, Xingjun Zhu, Jiahui Liu, et al.
Information Fusion (2023) Vol. 104, pp. 102186-102186
Closed Access | Times Cited: 43
Deep Adversarial Capsule Network for Compound Fault Diagnosis of Machinery Toward Multidomain Generalization Task
Ruyi Huang, Jipu Li, Yixiao Liao, et al.
IEEE Transactions on Instrumentation and Measurement (2020) Vol. 70, pp. 1-11
Closed Access | Times Cited: 123
Role of artificial intelligence in rotor fault diagnosis: a comprehensive review
Aneesh G. Nath, Sandeep S. Udmale, Sanjay Kumar Singh
Artificial Intelligence Review (2020) Vol. 54, Iss. 4, pp. 2609-2668
Closed Access | Times Cited: 112
Adversarial domain adaptation convolutional neural network for intelligent recognition of bearing faults
Yaochun Wu, Rongzhen Zhao, Hongru Ma, et al.
Measurement (2022) Vol. 195, pp. 111150-111150
Closed Access | Times Cited: 40
Semi-supervised fault diagnosis of machinery using LPS-DGAT under speed fluctuation and extremely low labeled rates
Shen Yan, Haidong Shao, Yiming Xiao, et al.
Advanced Engineering Informatics (2022) Vol. 53, pp. 101648-101648
Closed Access | Times Cited: 40
Deep hypergraph autoencoder embedding: An efficient intelligent approach for rotating machinery fault diagnosis
Mingkuan Shi, Chuancang Ding, Rui Wang, et al.
Knowledge-Based Systems (2022) Vol. 260, pp. 110172-110172
Closed Access | Times Cited: 40
Multi-sensor data fusion for rotating machinery fault detection using improved cyclic spectral covariance matrix and motor current signal analysis
Junchao Guo, Qingbo He, Dong Zhen, et al.
Reliability Engineering & System Safety (2022) Vol. 230, pp. 108969-108969
Open Access | Times Cited: 38
Semi-supervised learning for industrial fault detection and diagnosis: A systemic review
José Miguel Ramírez‐Sanz, Jose-Alberto Maestro-Prieto, Álvar Arnaiz‐González, et al.
ISA Transactions (2023) Vol. 143, pp. 255-270
Open Access | Times Cited: 36
Adaptive Multiscale Convolution Manifold Embedding Networks for Intelligent Fault Diagnosis of Servo Motor-Cylindrical Rolling Bearing Under Variable Working Conditions
Xingjun Zhu, Xiaoli Zhao, Jianyong Yao, et al.
IEEE/ASME Transactions on Mechatronics (2023) Vol. 29, Iss. 3, pp. 2230-2240
Closed Access | Times Cited: 34
Novel morphological scale difference filter with application in localization diagnosis of outer raceway defect in rolling bearings
Jinfeng Huang, Lingli Cui, Jianyu Zhang
Mechanism and Machine Theory (2023) Vol. 184, pp. 105288-105288
Closed Access | Times Cited: 31
Tensor Singular Spectrum Decomposition: Multisensor Denoising Algorithm and Application
Jinfeng Huang, Lingli Cui
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-15
Closed Access | Times Cited: 29
A collaborative central domain adaptation approach with multi-order graph embedding for bearing fault diagnosis under few-shot samples
Wengang Ma, Ruiqi Liu, Jin Guo, et al.
Applied Soft Computing (2023) Vol. 140, pp. 110243-110243
Closed Access | Times Cited: 22
Semisupervised Deep Sparse Auto-Encoder With Local and Nonlocal Information for Intelligent Fault Diagnosis of Rotating Machinery
Xiaoli Zhao, Minping Jia, Zheng Liu
IEEE Transactions on Instrumentation and Measurement (2020) Vol. 70, pp. 1-13
Closed Access | Times Cited: 61
Multiple-Order Graphical Deep Extreme Learning Machine for Unsupervised Fault Diagnosis of Rolling Bearing
Xiaoli Zhao, Minping Jia, Junchi Bin, et al.
IEEE Transactions on Instrumentation and Measurement (2020) Vol. 70, pp. 1-12
Closed Access | Times Cited: 49
A Fast Anomaly Diagnosis Approach Based on Modified CNN and Multisensor Data Fusion
Wenfeng Gong, Yuanzhe Wang, Meiling Zhang, et al.
IEEE Transactions on Industrial Electronics (2021) Vol. 69, Iss. 12, pp. 13636-13646
Closed Access | Times Cited: 48
A review: data driven-based fault diagnosis and RUL prediction of petroleum machinery and equipment
Daan Ji, Chuang Wang, Jiahui Li, et al.
Systems Science & Control Engineering (2021) Vol. 9, Iss. 1, pp. 724-747
Open Access | Times Cited: 47
A Light Weight Multisensory Fusion Model for Induction Motor Fault Diagnosis
Jinjiang Wang, Peilun Fu, Shuaihang Ji, et al.
IEEE/ASME Transactions on Mechatronics (2022) Vol. 27, Iss. 6, pp. 4932-4941
Closed Access | Times Cited: 29
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