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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:

Prior Knowledge-Augmented Self-Supervised Feature Learning for Few-Shot Intelligent Fault Diagnosis of Machines
Tianci Zhang, Jinglong Chen, Shuilong He, et al.
IEEE Transactions on Industrial Electronics (2022) Vol. 69, Iss. 10, pp. 10573-10584
Closed Access | Times Cited: 71

Showing 26-50 of 71 citing articles:

Bi-structural spatial–temporal network for few-shot fault diagnosis of rotating machinery
Zixu Chen, Jinchen Ji, Qing Ni, et al.
Mechanical Systems and Signal Processing (2025) Vol. 227, pp. 112378-112378
Closed Access
Cross-sensor contrastive learning-based pre-training for machinery fault diagnosis under sample-limited conditions
Hao Hu, Yue Ma, Ruoxue Li, et al.
Knowledge-Based Systems (2025), pp. 113075-113075
Closed Access
Unlocking the power of knowledge for few-shot fault diagnosis: A review from a knowledge perspective
Pei Ling Lai, Fan Zhang, Tianrui Li, et al.
Information Sciences (2025), pp. 121996-121996
Closed Access
Fault diagnosis method for chemical processes based on variable correlation‐guided convolutional neural networks
Zhe Zhou, Hongwei Yu, Yang Li, et al.
The Canadian Journal of Chemical Engineering (2025)
Closed Access
Integrating vibration signal analysis and image embedding for enhanced bearing fault diagnosis in manufacturing
Yongmin Kim, Hyunsoo Yoon
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Self-supervised Progressive Learning for Fault Diagnosis under Limited Labeled Data and Varying Conditions
Qiuyu Song, Lidong Yang, Xingxing Jiang, et al.
Neurocomputing (2025), pp. 130126-130126
Closed Access
Convolutional sparse filter with data and mechanism fusion: A few-shot fault diagnosis method for power transformer
Jia Qin, Dongsheng Yang, Nan Wang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 124, pp. 106606-106606
Closed Access | Times Cited: 9
Data-driven predictive maintenance framework considering the multi-source information fusion and uncertainty in remaining useful life prediction
Qifa Xu, Zhiwei Wang, Cuixia Jiang, et al.
Knowledge-Based Systems (2024) Vol. 303, pp. 112408-112408
Closed Access | Times Cited: 3
Robust Active Learning Multiple Fault Diagnosis of PMSM Drives With Sensorless Control Under Dynamic Operations and Imbalanced Datasets
Sveinung Attestog, Jagath Sri Lal Senanayaka, Huynh Van Khang, et al.
IEEE Transactions on Industrial Informatics (2022) Vol. 19, Iss. 9, pp. 9291-9301
Open Access | Times Cited: 14
Prior knowledge-based self-supervised learning for intelligent bearing fault diagnosis with few fault samples
Ke Wu, Yukang Nie, Jun Wu, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 10, pp. 105104-105104
Closed Access | Times Cited: 8
Robust Multiple-Fault Diagnosis of PMSM Drives Under Variant Operations and Noisy Conditions
Mahmoud S. Mahmoud, Huynh Van Khang, Jagath Sri Lal Senanyaka, et al.
IEEE Open Journal of the Industrial Electronics Society (2023) Vol. 4, pp. 762-772
Open Access | Times Cited: 8
Sparse Sample Train Axle Bearing Fault Diagnosis: A Semi-Supervised Model Based on Prior Knowledge Embedding
Yaxin Li, Suchao Xie, Jiacheng Wang, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-11
Closed Access | Times Cited: 7
Novel cross-domain fault diagnosis method based on model-agnostic meta-learning embedded in adaptive threshold network
Chenglong Ye, Jinxi Wang, Chang Peng, et al.
Measurement (2023) Vol. 222, pp. 113677-113677
Closed Access | Times Cited: 7
A zero-cost unsupervised transfer method based on non-vibration signals fusion for ball screw fault diagnosis
Fei Jiang, Qin Liang, Zhaoqian Wu, et al.
Knowledge-Based Systems (2024) Vol. 288, pp. 111475-111475
Closed Access | Times Cited: 2
Knowledge-driven domain adaptation strategy for rotating machinery fault diagnosis under varying working condition
Junyu Chang, Jiaqi Yao, Xu Chen, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 5, pp. 056110-056110
Open Access | Times Cited: 2
Multi-view contrastive learning framework for tool wear detection with insufficient annotated data
Rui Shu, Yadong Xu, Jianliang He, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102666-102666
Closed Access | Times Cited: 2
Structural prior-driven feature extraction with gradient-momentum combined optimization for convolutional neural network image classification
Yunyun Sun, Peng Li, He Xu, et al.
Neural Networks (2024) Vol. 179, pp. 106511-106511
Closed Access | Times Cited: 2
Designing a Hybrid Equipment-Failure Diagnosis Mechanism under Mixed-Type Data with Limited Failure Samples
Cheng-Hui Chen, Chen-Kun Tsung, Shyr-Shen Yu
Applied Sciences (2022) Vol. 12, Iss. 18, pp. 9286-9286
Open Access | Times Cited: 11
A Fault Diagnosis Method With Bitask-Based Time- and Frequency-Domain Feature Learning
Qiang Zhang, Ruiping Huo, Handong Zheng, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-11
Closed Access | Times Cited: 6
Sinc-Based Multiplication-Convolution Network for Small-Sample Fault Diagnosis and Edge Application
Rui Liu, Xiaoxi Ding, Shenglan Liu, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-12
Closed Access | Times Cited: 6
Maximizing model generalization for machine condition monitoring with Self-Supervised Learning and Federated Learning
Matthew Russell, Peng Wang
Journal of Manufacturing Systems (2023) Vol. 71, pp. 274-285
Open Access | Times Cited: 6
Dual prototypical contrastive network: a novel self-supervised method for cross-domain few-shot fault diagnosis
Xiao Zhang, Weiguo Huang, Rui Wang, et al.
Journal of Intelligent Manufacturing (2023)
Closed Access | Times Cited: 6
Prior-knowledge-guided mode filtering network for interpretable equipment intelligent diagnosis under varying speed conditions
Rui Liu, Xiaoxi Ding, Yimin Shao
Advanced Engineering Informatics (2024) Vol. 61, pp. 102493-102493
Closed Access | Times Cited: 1
Self-supervised fusion of deep soft assignments for multi-view diagnosis of machine faults
Chuan Li, Yifan Wu, Manjun Xiong, et al.
Journal of Intelligent Manufacturing (2024)
Closed Access | Times Cited: 1
Sequential Feature-Augmented Deep Multilabel Learning for Compound Fault Diagnosis of Rotating Machinery With Few Labeled and Imbalanced Data
Xinyue Wang, Gangyan Xu, Z. Y. Zhou, et al.
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 12, pp. 13947-13955
Closed Access | Times Cited: 1

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