Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

A deep feature enhanced reinforcement learning method for rolling bearing fault diagnosis
Ruixin Wang, Hongkai Jiang, Ke Zhu, et al.
Advanced Engineering Informatics (2022) Vol. 54, pp. 101750-101750
Closed Access | Times Cited: 91

Showing 1-25 of 91 citing articles:

Faulty rolling bearing digital twin model and its application in fault diagnosis with imbalanced samples
Yi Qin, Hongyu Liu, Yongfang Mao
Advanced Engineering Informatics (2024) Vol. 61, pp. 102513-102513
Closed Access | Times Cited: 29
Rolling bearing fault diagnosis method based on improved residual shrinkage network
Linjun Wang, Tengxiao Zou, Kanglin Cai, et al.
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2024) Vol. 46, Iss. 3
Closed Access | Times Cited: 25
A pruned-optimized weighted graph convolutional network for axial flow pump fault diagnosis with hydrophone signals
Xin Zhang, Li Jiang, Lei Wang, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102365-102365
Closed Access | Times Cited: 18
Single-domain incremental generation network for machinery intelligent fault diagnosis under unknown working speeds
Yuanyue Pu, Jian Tang, Xue‐Gang Li, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102400-102400
Closed Access | Times Cited: 15
Imbalanced domain generalization via Semantic-Discriminative augmentation for intelligent fault diagnosis
Chao Zhao, Weiming Shen
Advanced Engineering Informatics (2023) Vol. 59, pp. 102262-102262
Closed Access | Times Cited: 32
Multi-source information joint transfer diagnosis for rolling bearing with unknown faults via wavelet transform and an improved domain adaptation network
Pengfei Liang, Jiaye Tian, Suiyan Wang, et al.
Reliability Engineering & System Safety (2023) Vol. 242, pp. 109788-109788
Closed Access | Times Cited: 29
Semi-supervised fault diagnosis of gearbox based on feature pre-extraction mechanism and improved generative adversarial networks under limited labeled samples and noise environment
Lijie Zhang, Bin Wang, Pengfei Liang, et al.
Advanced Engineering Informatics (2023) Vol. 58, pp. 102211-102211
Closed Access | Times Cited: 27
Transformer-based meta learning method for bearing fault identification under multiple small sample conditions
Xianze Li, Hao Su, Ling Xiang, et al.
Mechanical Systems and Signal Processing (2023) Vol. 208, pp. 110967-110967
Closed Access | Times Cited: 25
Fault diagnosis of gearbox driven by vibration response mechanism and enhanced unsupervised domain adaptation
Fei Jiang, Weiqi Lin, Zhaoqian Wu, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102460-102460
Closed Access | Times Cited: 13
CBAM-CRLSGAN: A novel fault diagnosis method for planetary transmission systems under small samples scenarios
Jie Zhang, Yun Kong, Zhuyun Chen, et al.
Measurement (2024) Vol. 234, pp. 114795-114795
Closed Access | Times Cited: 13
Cross-Supervised multisource prototypical network: A novel domain adaptation method for multi-source few-shot fault diagnosis
Xiao Zhang, Weiguo Huang, Chuancang Ding, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102538-102538
Closed Access | Times Cited: 12
Wind turbines fault diagnosis method under variable working conditions based on AMVMD and deep discrimination transfer learning network
Peiming Shi, Linjie Jia, Siying Yi, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 4, pp. 046120-046120
Closed Access | Times Cited: 11
Physics-informed unsupervised domain adaptation framework for cross-machine bearing fault diagnosis
Ning Jia, Weiguo Huang, Chuancang Ding, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102774-102774
Closed Access | Times Cited: 10
Review of research on signal decomposition and fault diagnosis of rolling bearing based on vibration signal
Junning Li, Luo Wen-guang, Mengsha Bai
Measurement Science and Technology (2024) Vol. 35, Iss. 9, pp. 092001-092001
Closed Access | Times Cited: 9
Transfer learning rolling bearing fault diagnosis model based on deep feature decomposition and class-level alignment
Jingchuan Dong, Hongyu Jiang, Depeng Su, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 4, pp. 046006-046006
Closed Access | Times Cited: 8
A new fault feature extraction method of rolling bearings based on the improved self-selection ICEEMDAN-permutation entropy
Maohua Xiao, Zhenyu Wang, Yuanfang Zhao, et al.
ISA Transactions (2023) Vol. 143, pp. 536-547
Closed Access | Times Cited: 17
Structural discrepancy and domain adversarial fusion network for cross-domain fault diagnosis
Fuzheng Liu, Faye Zhang, Xiangyi Geng, et al.
Advanced Engineering Informatics (2023) Vol. 58, pp. 102217-102217
Closed Access | Times Cited: 17
A novel coupled array of multi-stable stochastic resonance under asymmetric trichotomous noise and its application in rolling bearing compound fault diagnosis
Zong Meng, Shuhan Quan, Jimeng Li, et al.
Applied Acoustics (2023) Vol. 209, pp. 109405-109405
Closed Access | Times Cited: 16
Systematic Review on Fault Diagnosis on Rolling-Element Bearing
M. Pandiyan, T. Narendiranath Babu
Journal of Vibration Engineering & Technologies (2024)
Closed Access | Times Cited: 6
Integrated decision-making with adaptive feature weighting adversarial network for multi-target domain compound fault diagnosis of machinery
Xuepeng Zhang, Jinrui Wang, Zongzhen Zhang, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102730-102730
Closed Access | Times Cited: 5
MCRCNet: A Bearing Fault Diagnosis Method for Unknown Faults Based on Transfer Learning
Guangyuan Xu, Ruifeng Guo, Zhenyu Yin, et al.
Applied Sciences (2025) Vol. 15, Iss. 2, pp. 921-921
Open Access
Residual shrinkage transformer relation network for intelligent fault detection of industrial robot with zero-fault samples
Zuoyi Chen, Ke Wu, Jun Wu, et al.
Knowledge-Based Systems (2023) Vol. 268, pp. 110452-110452
Closed Access | Times Cited: 15
Multi-source information fusion meta-learning network with convolutional block attention module for bearing fault diagnosis under limited dataset
Shanshan Song, Shuqing Zhang, Wei Dong, et al.
Structural Health Monitoring (2023) Vol. 23, Iss. 2, pp. 818-835
Closed Access | Times Cited: 15
A subtle defect recognition method for catenary fastener in high-speed railroad using destruction and reconstruction learning
Fanteng Meng, Yong Qin, Yunpeng Wu, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102393-102393
Closed Access | Times Cited: 4
Bearing fault diagnosis based on transfer learning with dual-flow manifold ResNet and improved CapsNet
L Yao, Hongwei Wang, Tao Lei, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 7, pp. 076123-076123
Closed Access | Times Cited: 4
Page 1 - Next Page

Scroll to top