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 Diagnosis of Rolling Bearings Fault Based on Multisignal Fusion and MTF-ResNet
Kecheng He, Yanwei Xu, Yun Wang, et al.
Sensors (2023) Vol. 23, Iss. 14, pp. 6281-6281
Open Access | Times Cited: 8
Kecheng He, Yanwei Xu, Yun Wang, et al.
Sensors (2023) Vol. 23, Iss. 14, pp. 6281-6281
Open Access | Times Cited: 8
Showing 8 citing articles:
Towards multi-scene learning: A novel cross-domain adaptation model based on sparse filter for traction motor bearing fault diagnosis in high-speed EMU
Feiyu Lu, Qingbin Tong, Jianjun Xu, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102536-102536
Closed Access | Times Cited: 18
Feiyu Lu, Qingbin Tong, Jianjun Xu, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102536-102536
Closed Access | Times Cited: 18
A Novel Method for Rolling Bearing Fault Diagnosis Based on Gramian Angular Field and CNN-ViT
Zijun Zhou, Qingsong Ai, Ping Lou, et al.
Sensors (2024) Vol. 24, Iss. 12, pp. 3967-3967
Open Access | Times Cited: 5
Zijun Zhou, Qingsong Ai, Ping Lou, et al.
Sensors (2024) Vol. 24, Iss. 12, pp. 3967-3967
Open Access | Times Cited: 5
An ensemble deep learning network based on 2D convolutional neural network and 1D LSTM with self-attention for bearing fault diagnosis
Liying Wang, Weiguo Zhao
Applied Soft Computing (2025), pp. 112889-112889
Closed Access
Liying Wang, Weiguo Zhao
Applied Soft Computing (2025), pp. 112889-112889
Closed Access
A rolling bearing fault diagnosis method based on Markov transition field and multi-scale Runge-Kutta residual network
Simin Ding, Zhiyuan Rui, Chunli Lei, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 12, pp. 125150-125150
Closed Access | Times Cited: 7
Simin Ding, Zhiyuan Rui, Chunli Lei, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 12, pp. 125150-125150
Closed Access | Times Cited: 7
Intelligent Fault Diagnosis of Rolling Bearings Based on Markov Transition Field and Mixed Attention Residual Network
Anshi Tong, Jun Zhang, Danfeng Wang, et al.
Applied Sciences (2024) Vol. 14, Iss. 12, pp. 5110-5110
Open Access | Times Cited: 2
Anshi Tong, Jun Zhang, Danfeng Wang, et al.
Applied Sciences (2024) Vol. 14, Iss. 12, pp. 5110-5110
Open Access | Times Cited: 2
Lightweight Ghost Enhanced Feature Attention Network: An Efficient Intelligent Fault Diagnosis Method under Various Working Conditions
Huaihao Dong, Kai Zheng, Siguo Wen, et al.
Sensors (2024) Vol. 24, Iss. 11, pp. 3691-3691
Open Access
Huaihao Dong, Kai Zheng, Siguo Wen, et al.
Sensors (2024) Vol. 24, Iss. 11, pp. 3691-3691
Open Access
Bearing Fault Diagnosis Based on the Markov Transition Field and SE-IShufflenetV2 Model
Chaozhi Cai, Tiexin Xu, Jianhua Ren, et al.
Structural durability & health monitoring (2024) Vol. 19, Iss. 1, pp. 125-144
Open Access
Chaozhi Cai, Tiexin Xu, Jianhua Ren, et al.
Structural durability & health monitoring (2024) Vol. 19, Iss. 1, pp. 125-144
Open Access
Detection and Feature Extraction in Acoustic Sensor Signals
Yuxing Li, Luca Fredianelli
Sensors (2023) Vol. 23, Iss. 19, pp. 8030-8030
Open Access | Times Cited: 1
Yuxing Li, Luca Fredianelli
Sensors (2023) Vol. 23, Iss. 19, pp. 8030-8030
Open Access | Times Cited: 1
