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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:

A novel adaptive convolutional neural network for fault diagnosis of hydraulic piston pump with acoustic images
Shengnan Tang, Yong Zhu, Shouqi Yuan
Advanced Engineering Informatics (2022) Vol. 52, pp. 101554-101554
Closed Access | Times Cited: 118

Showing 1-25 of 118 citing articles:

A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
Laith Alzubaidi, Jinshuai Bai, Aiman Al-Sabaawi, et al.
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 320
Intelligent fault identification of hydraulic pump using deep adaptive normalized CNN and synchrosqueezed wavelet transform
Shengnan Tang, Yong Zhu, Shouqi Yuan
Reliability Engineering & System Safety (2022) Vol. 224, pp. 108560-108560
Closed Access | Times Cited: 110
Acoustic signal-based fault detection of hydraulic piston pump using a particle swarm optimization enhancement CNN
Yong Zhu, Guangpeng Li, Shengnan Tang, et al.
Applied Acoustics (2022) Vol. 192, pp. 108718-108718
Closed Access | Times Cited: 87
Fault diagnosis of hydro-turbine via the incorporation of bayesian algorithm optimized CNN-LSTM neural network
Fang Dao, Yun Zeng, Jing Qian
Energy (2024) Vol. 290, pp. 130326-130326
Closed Access | Times Cited: 78
An adaptive deep learning model towards fault diagnosis of hydraulic piston pump using pressure signal
Shengnan Tang, Yong Zhu, Shouqi Yuan
Engineering Failure Analysis (2022) Vol. 138, pp. 106300-106300
Closed Access | Times Cited: 76
You can get smaller: A lightweight self-activation convolution unit modified by transformer for fault diagnosis
Hairui Fang, Jin Deng, DongSheng Chen, et al.
Advanced Engineering Informatics (2023) Vol. 55, pp. 101890-101890
Closed Access | Times Cited: 49
A zero-shot fault semantics learning model for compound fault diagnosis
Juan Xu, Shaokang Liang, Xu Ding, et al.
Expert Systems with Applications (2023) Vol. 221, pp. 119642-119642
Closed Access | Times Cited: 49
Deep continual transfer learning with dynamic weight aggregation for fault diagnosis of industrial streaming data under varying working conditions
Jipu Li, Ruyi Huang, Zhuyun Chen, et al.
Advanced Engineering Informatics (2023) Vol. 55, pp. 101883-101883
Closed Access | Times Cited: 46
A parallel deep neural network for intelligent fault diagnosis of drilling pumps
Junyu Guo, Yulai Yang, He Li, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108071-108071
Open Access | Times Cited: 43
Fault detection and diagnosis of marine diesel engines: A systematic review
Yaqiong Lv, Xueting Yang, Yifan Li, et al.
Ocean Engineering (2024) Vol. 294, pp. 116798-116798
Closed Access | Times Cited: 22
Fault diagnosis study of hydraulic pump based on improved symplectic geometry reconstruction data enhancement method
Siyuan Liu, Jixiong Yin, Ming Hao, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102459-102459
Closed Access | Times Cited: 19
High imbalance fault diagnosis of aviation hydraulic pump based on data augmentation via local wavelet similarity fusion
Song Fu, Lin Lin, Yue Wang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 209, pp. 111115-111115
Closed Access | Times Cited: 18
A temporal-spatial multi-order weighted graph convolution network with refined feature topology graph for imbalance fault diagnosis of rotating machinery
Zhichao Jiang, Dongdong Liu, Lingli Cui
Reliability Engineering & System Safety (2025), pp. 110830-110830
Closed Access | Times Cited: 1
Tilting Pad Thrust Bearing Fault Diagnosis Based on Acoustic Emission Signal and Modified Multi-Feature Fusion Convolutional Neural Network
Meijiao Mao, Zhiwen Jiang, Zhifei Tan, et al.
Sensors (2025) Vol. 25, Iss. 3, pp. 904-904
Open Access | Times Cited: 1
Multiple-signal defect identification of hydraulic pump using an adaptive normalized model and S transform
Yong Zhu, Shengnan Tang, Shouqi Yuan
Engineering Applications of Artificial Intelligence (2023) Vol. 124, pp. 106548-106548
Closed Access | Times Cited: 39
Development of entropy measure for selecting highly sensitive WPT band to identify defective components of an axial piston pump
Yuqing Zhou, Anil Kumar, Chander Parkash, et al.
Applied Acoustics (2023) Vol. 203, pp. 109225-109225
Closed Access | Times Cited: 33
A hybrid intelligent rolling bearing fault diagnosis method combining WKN-BiLSTM and attention mechanism
Jiang Wang, Junyu Guo, Lin Wang, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 8, pp. 085106-085106
Closed Access | Times Cited: 29
Frequency-based leak signature investigation using acoustic sensors in urban water distribution networks
Konstantinos Sitaropoulos, Salvatore Salamone, Lina Sela
Advanced Engineering Informatics (2023) Vol. 55, pp. 101905-101905
Open Access | Times Cited: 26
A novel physics-informed neural network for modeling electromagnetism of a permanent magnet synchronous motor
Seho Son, Hyunseung Lee, Dayeon Jeong, et al.
Advanced Engineering Informatics (2023) Vol. 57, pp. 102035-102035
Closed Access | Times Cited: 25
Estimation of soil moisture in drip-irrigated citrus orchards using multi-modal UAV remote sensing
Zongjun Wu, Ningbo Cui, Wenjiang Zhang, et al.
Agricultural Water Management (2024) Vol. 302, pp. 108972-108972
Open Access | Times Cited: 9
A roadmap to fault diagnosis of industrial machines via machine learning: A brief review
Govind Vashishtha, Sumika Chauhan, Mert Sehri, et al.
Measurement (2024) Vol. 242, pp. 116216-116216
Closed Access | Times Cited: 9
M2FN: An end-to-end multi-task and multi-sensor fusion network for intelligent fault diagnosis
Jian Cui, Ping Xie, Xiao Wang, et al.
Measurement (2022) Vol. 204, pp. 112085-112085
Closed Access | Times Cited: 28
A Novel Fault Diagnosis Method Based on SWT and VGG-LSTM Model for Hydraulic Axial Piston Pump
Yong Zhu, Hong Su, Shengnan Tang, et al.
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 3, pp. 594-594
Open Access | Times Cited: 20
Knowledge addition for improving the transfer learning from the laboratory to identify defects of hydraulic machinery
Anil Kumar, Adam Głowacz, Hesheng Tang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 106756-106756
Closed Access | Times Cited: 20
A Novel Hierarchical Vision Transformer and Wavelet Time–Frequency Based on Multi-Source Information Fusion for Intelligent Fault Diagnosis
Changfen Gong, Rongrong Peng
Sensors (2024) Vol. 24, Iss. 6, pp. 1799-1799
Open Access | Times Cited: 6
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