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 Siamese Vision Transformer for Bearings Fault Diagnosis
Qiuchen He, Shaobo Li, Qiang Bai, et al.
Micromachines (2022) Vol. 13, Iss. 10, pp. 1656-1656
Open Access | Times Cited: 13

Showing 13 citing articles:

A Novel Fault Diagnosis Method of Rolling Bearings Combining Convolutional Neural Network and Transformer
Wenkai Liu, Zhigang Zhang, Jiarui Zhang, et al.
Electronics (2023) Vol. 12, Iss. 8, pp. 1838-1838
Open Access | Times Cited: 20
Transformer-based intelligent fault diagnosis methods of mechanical equipment: A survey
Rongcai Wang, Enzhi Dong, Zhonghua Cheng, et al.
Open Physics (2024) Vol. 22, Iss. 1
Open Access | Times Cited: 5
Twins Transformer: Rolling Bearing Fault Diagnosis based on Cross-attention Fusion of Time and Frequency Domain Features
Zhikang Gao, Yanxue Wang, Xinming Li, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 9, pp. 096113-096113
Closed Access | Times Cited: 4
Deep Learning in Industrial Machinery: A Critical Review of Bearing Fault Classification Methods
Attiq Ur Rehman, Weidong Jiao, Yonghua Jiang, et al.
Applied Soft Computing (2025), pp. 112785-112785
Closed Access
A deep‐learning model based on MFE‐Transformer for chemical process fault detection
Ying Xie, Xiaotong Wu, Ying‐Jie Zhu, et al.
The Canadian Journal of Chemical Engineering (2025)
Closed Access
Deep transfer learning rolling bearing fault diagnosis method based on convolutional neural network feature fusion
Di Yu, H.C. Fu, Yanchen Song, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 015013-015013
Closed Access | Times Cited: 12
Detection and Classification of Surface Defects on Hot-Rolled Steel using Vision Transformers
Vinod Vasan, Naveen Venkatesh Sridharan, V. Sugumaran, et al.
Heliyon (2024) Vol. 10, Iss. 19, pp. e38498-e38498
Open Access | Times Cited: 1
TSViT: A Time Series Vision Transformer for Fault Diagnosis of Rotating Machinery
Shouhua Zhang, Jiehan Zhou, Xue Ma, et al.
Applied Sciences (2024) Vol. 14, Iss. 23, pp. 10781-10781
Open Access | Times Cited: 1
Instantaneous Square Current Signal Analysis for Motors Using Vision Transformer for the Fault Diagnosis of Rolling Bearings
Fei Chen, Xin Zhou, Binbin Xu, et al.
Applied Sciences (2023) Vol. 13, Iss. 16, pp. 9349-9349
Open Access | Times Cited: 3
Early anomaly detection of wind turbine gearbox based on SLFormer neural network
Zekun Wang, Xue Jiang, Zifei Xu, et al.
Ocean Engineering (2024) Vol. 311, pp. 118925-118925
Closed Access
Aileron fault detection with dynamic resampling based on fuzzy entropy and multi-branch neural network
Shize Qin, Ying Zhang, Kai Sun, et al.
Measurement (2024), pp. 115773-115773
Closed Access
A Fault Diagnosis Method for Bearings and Gears in Rotating Machinery Based on Data Fusion and Transfer Learning
Yi Zhang, Xiaoxiang Yan, Ping Xiao, et al.
Measurement Science and Technology (2024) Vol. 36, Iss. 1, pp. 016104-016104
Closed Access
Electric Vehicle Motor Fault Detection with Improved Recurrent 1D Convolutional Neural Network
Prashant Kumar, P Kumar, Ashish Kumar Sinha, et al.
Mathematics (2024) Vol. 12, Iss. 19, pp. 3012-3012
Open Access
Machine Learning Based Mechanical Fault Diagnosis and Detection Methods: A Systematic Review
Yuechuan Xin, Jianuo Zhu, Mingyang Cai, et al.
Measurement Science and Technology (2024) Vol. 36, Iss. 1, pp. 012004-012004
Closed Access
Page 1

Scroll to top