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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:

Tool wear state prediction based on feature-based transfer learning
Jianbo Li, Juan Lu, Chaoyi Chen, et al.
The International Journal of Advanced Manufacturing Technology (2021) Vol. 113, Iss. 11-12, pp. 3283-3301
Closed Access | Times Cited: 47

Showing 1-25 of 47 citing articles:

Tool Condition Monitoring for High-Performance Machining Systems—A Review
Ayman Mohamed, Mahmoud Hassan, Rachid M’Saoubi, et al.
Sensors (2022) Vol. 22, Iss. 6, pp. 2206-2206
Open Access | Times Cited: 88
Milling tool wear prediction using multi-sensor feature fusion based on stacked sparse autoencoders
Zhaopeng He, Tielin Shi, Jianping Xuan
Measurement (2022) Vol. 190, pp. 110719-110719
Closed Access | Times Cited: 68
State-of-art, challenges, and outlook on deep hole boring: chatter suppression, tool wear monitoring, and error measurement
Jiefu Sun, Chao Sun, Zheping Yan, et al.
The International Journal of Advanced Manufacturing Technology (2025)
Closed Access | Times Cited: 2
Accurate estimation of tool wear levels during milling, drilling and turning operations by designing novel hyperparameter tuned models based on LightGBM and stacking
Jawad Mahmood, Ghulam-e Mustafa, Muhammad Ali
Measurement (2022) Vol. 190, pp. 110722-110722
Closed Access | Times Cited: 40
Cutting tool wear state recognition based on a channel-space attention mechanism
Rongyi Li, Peining Wei, Xianli Liu, et al.
Journal of Manufacturing Systems (2023) Vol. 69, pp. 135-149
Closed Access | Times Cited: 32
Tool wear condition monitoring across machining processes based on feature transfer by deep adversarial domain confusion network
Zhiwen Huang, Jiajie Shao, Jianmin Zhu, et al.
Journal of Intelligent Manufacturing (2023) Vol. 35, Iss. 3, pp. 1079-1105
Closed Access | Times Cited: 22
Robust Tool Wear Prediction using Multi-Sensor Fusion and Time-Domain Features for the Milling Process using Instance-based Domain Adaptation
Vivek Warke, Satish Kumar, Arunkumar Bongale, et al.
Knowledge-Based Systems (2024) Vol. 288, pp. 111454-111454
Closed Access | Times Cited: 10
Adaptive weighted generative adversarial network with attention mechanism: A transfer data augmentation method for tool wear prediction
Jianliang He, Yadong Xu, Yi Pan, et al.
Mechanical Systems and Signal Processing (2024) Vol. 212, pp. 111288-111288
Closed Access | Times Cited: 10
Tool wear prediction based on domain adversarial adaptation and channel attention multiscale convolutional long short-term memory network
Wen Hou, Hong Guo, Lei Luo, et al.
Journal of Manufacturing Processes (2022) Vol. 84, pp. 1339-1361
Closed Access | Times Cited: 32
Cross-domain tool wear condition monitoring via residual attention hybrid adaptation network
Zhiwen Huang, Weidong Li, Jianmin Zhu, et al.
Journal of Manufacturing Systems (2023) Vol. 72, pp. 406-423
Closed Access | Times Cited: 17
Measurement of Micro Burr and Slot Widths through Image Processing: Comparison of Manual and Automated Measurements in Micro-Milling
Fatih Akkoyun, Ali Erçetin, Kubilay Aslantaş, et al.
Sensors (2021) Vol. 21, Iss. 13, pp. 4432-4432
Open Access | Times Cited: 40
Cross-domain adaptation network based on attention mechanism for tool wear prediction
Jianliang He, Yuxin Sun, Chen Yin, et al.
Journal of Intelligent Manufacturing (2022) Vol. 34, Iss. 8, pp. 3365-3387
Closed Access | Times Cited: 23
Similarity-based prediction method for machinery remaining useful life: A review
Bin Xue, Huangyang Xu, Xing Huang, et al.
The International Journal of Advanced Manufacturing Technology (2022) Vol. 121, Iss. 3-4, pp. 1501-1531
Closed Access | Times Cited: 22
Tool Condition Monitoring Methods Applicable in the Metalworking Process
Melvin Alexis Lara de León, Jakub Kolařík, Radek Byrtus, et al.
Archives of Computational Methods in Engineering (2023) Vol. 31, Iss. 1, pp. 221-242
Open Access | Times Cited: 14
A biomimetic micro-texture based on shark surface for tool wear reduction and wettability change
Yu Wang, Wenxin Peng, He Tong, et al.
Journal of Manufacturing Processes (2024) Vol. 129, pp. 202-214
Closed Access | Times Cited: 5
Deep Learning Tool Wear State Identification Method Based on Cutting Force Signal
Shuhang Li, Meiqiu Li, Yingning Gao
Sensors (2025) Vol. 25, Iss. 3, pp. 662-662
Open Access
A review of artificial intelligence application for machining surface quality prediction: from key factors to model development
Jeong Hoon Ko, Chen Yin
Journal of Intelligent Manufacturing (2025)
Open Access
Tool Wear State Identification Method with Variable Cutting Parameters Based on Multi-Source Unsupervised Domain Adaptation
Zhigang Cai, Wangyang Li, Jianxin Song, et al.
Sensors (2025) Vol. 25, Iss. 6, pp. 1742-1742
Open Access
An unsupervised dual-regression domain adversarial adaption network for tool wear prediction in multi-working conditions
Yumeng Zhu, Yanyang Zi, Jing Xu, et al.
Measurement (2022) Vol. 200, pp. 111644-111644
Closed Access | Times Cited: 21
Multi-condition wear prediction and assessment of milling cutters based on linear discriminant analysis and ensemble methods
Honggen Zhou, Shangshang Gao, Yang Xie, et al.
Measurement (2023) Vol. 216, pp. 112900-112900
Closed Access | Times Cited: 11
A domain adversarial graph convolutional network for intelligent monitoring of tool wear in machine tools
Kai Li, Zhou-Long Li, Xianshi Jia, et al.
Computers & Industrial Engineering (2023) Vol. 187, pp. 109795-109795
Closed Access | Times Cited: 11
Tool Wear Prediction Model Using Multi-Channel 1D Convolutional Neural Network and Temporal Convolutional Network
Min Huang, Xingang Xie, Weiwei Sun, et al.
Lubricants (2024) Vol. 12, Iss. 2, pp. 36-36
Open Access | Times Cited: 3
Efficient Tool Wear Prediction in Manufacturing: BiLPReS Hybrid Model with Performer Encoder
Zekai Si, Sumei Si, Deqiang Mu
Arabian Journal for Science and Engineering (2024) Vol. 49, Iss. 11, pp. 15193-15204
Closed Access | Times Cited: 3
Deep transfer learning for tool condition monitoring under different processing conditions
Yongqing Wang, Mengmeng Niu, Kuo Liu, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 133, Iss. 1-2, pp. 507-519
Closed Access | Times Cited: 3
Misalignment detection on linear feed axis using sensorless motor current signals
Mustafa Demetgul, Ma Zihan, Imanuel Heider, et al.
The International Journal of Advanced Manufacturing Technology (2023) Vol. 126, Iss. 5-6, pp. 2677-2691
Open Access | Times Cited: 8
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