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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:

Cutting tool wear monitoring based on a smart toolholder with embedded force and vibration sensors and an improved residual network
Pengfei Zhang, Dong Gao, Yong Lü, et al.
Measurement (2022) Vol. 199, pp. 111520-111520
Closed Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

A State-of-the-art Review on the Intelligent Tool Holders in Machining
Qinglong An, Jie Yang, Junli Li, et al.
Intelligent and sustainable manufacturing (2024) Vol. 1, Iss. 1, pp. 10002-10002
Open Access | Times Cited: 29
Improving generalisation and accuracy of on-line milling chatter detection via a novel hybrid deep convolutional neural network
Pengfei Zhang, Dong Gao, Dongbo Hong, et al.
Mechanical Systems and Signal Processing (2023) Vol. 193, pp. 110241-110241
Open Access | Times Cited: 30
Intelligent tool wear monitoring based on multi-channel hybrid information and deep transfer learning
Pengfei Zhang, Dong Gao, Dongbo Hong, et al.
Journal of Manufacturing Systems (2023) Vol. 69, pp. 31-47
Closed Access | Times Cited: 29
Position-dependent milling process monitoring and surface roughness prediction for complex thin-walled blade component
Zequan Yao, Jingyuan Shen, Ming Wu, et al.
Mechanical Systems and Signal Processing (2023) Vol. 198, pp. 110439-110439
Closed Access | Times Cited: 20
ACWGAN-GP for milling tool breakage monitoring with imbalanced data
Xuebing Li, Caixu Yue, Xianli Liu, et al.
Robotics and Computer-Integrated Manufacturing (2023) Vol. 85, pp. 102624-102624
Closed Access | Times Cited: 20
Use of machine learning models in condition monitoring of abrasive belt in robotic arm grinding process
Mochamad Denny Surindra, Gusti Ahmad Fanshuri Alfarisy, Wahyu Caesarendra, et al.
Journal of Intelligent Manufacturing (2024)
Open Access | Times Cited: 6
A tool wear condition monitoring method for non-specific sensing signals
Yezhen Peng, Qinghua Song, Runqiong Wang, et al.
International Journal of Mechanical Sciences (2023) Vol. 263, pp. 108769-108769
Closed Access | Times Cited: 16
Researches on tool wear progress in mill-grinding based on the cutting force and acceleration signal
Xian Wu, Chao Zhang, Yuan Li, et al.
Measurement (2023) Vol. 218, pp. 113234-113234
Closed Access | Times Cited: 13
A State-of-the-art Review on the Intelligent Tool Holders in Machining
Qinglong An, Jie Yang, Junli Li, et al.
Intelligent and sustainable manufacturing (2024) Vol. 1, Iss. 1, pp. 10002-10002
Open Access | Times Cited: 4
Tool wear status monitoring under laser-ultrasonic compound cutting based on acoustic emission and deep learning
Changjuan Zhang, Junhao Wang, Yongjing Cao, et al.
Journal of Mechanical Science and Technology (2024) Vol. 38, Iss. 5, pp. 2411-2421
Closed Access | Times Cited: 4
A hybrid deep learning-based approach for on-line chatter detection in milling using deep stem-inception networks and residual channel-spatial attention mechanisms
Khairul Jauhari, Achmad Zaki Rahman, Mahfudz Al Huda, et al.
Mechanical Systems and Signal Processing (2025) Vol. 226, pp. 112357-112357
Closed Access
Combining Sensor Fusion and a Machine Learning Framework for Accurate Tool Wear Prediction During Machining
Swathi Kotha Amarnath, Vamsi Inturi, Sabareesh Geetha Rajasekharan, et al.
Machines (2025) Vol. 13, Iss. 2, pp. 132-132
Open Access
Intelligent wireless tool wear monitoring system based on chucked tool condition monitoring ring and deep learning
Ni Chen, Zhan Liu, Zhongling Xue, et al.
Advanced Engineering Informatics (2025) Vol. 65, pp. 103176-103176
Closed Access
Analysis and Monitoring the Initial Tool Damage and Coating Failure when Hard Milling Vanadis 4E with TiAlN Coated PcBN
Оleksandr Gutnichenko, Sandra Gordon Pozuelo, L. Llanes, et al.
Procedia CIRP (2025) Vol. 133, pp. 322-327
Open Access
Tool design and wear control technology: progress and application
Jiashuai Huang, Guangjun Chen, Zhuang Chen, et al.
Machining Science and Technology (2025), pp. 1-44
Closed Access
Study on tool wear state recognition algorithm based on spindle vibration signals collected by homemade tool condition monitoring ring
Zhongling Xue, Liang Li, Youling Wu, et al.
Measurement (2023) Vol. 223, pp. 113787-113787
Closed Access | Times Cited: 8
Multi-sensor fusion and machine learning-driven sequence-to-sequence translation for interpretable process signature prediction in machining
Clayton Cooper, Jianjing Zhang, Ihab Ragai, et al.
Journal of Manufacturing Systems (2024) Vol. 75, pp. 288-298
Open Access | Times Cited: 2
Sensor-based intelligent tool online monitoring technology: applications and progress
Jiashuai Huang, Guangjun Chen, Hong Wei, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 11, pp. 112001-112001
Closed Access | Times Cited: 2
Tool breakage monitoring driven by the real-time predicted spindle cutting torque using spindle servo signals
Yinghao Cheng, Yingguang Li, Guangxu Li, et al.
Robotics and Computer-Integrated Manufacturing (2024) Vol. 92, pp. 102888-102888
Closed Access | Times Cited: 2
A novel pre-trained model based on graph-labeling graph neural networks for tool wear prediction under variable working conditions
Haitao Xu, Xu Yang, Wei Wang, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 12, pp. 125026-125026
Closed Access | Times Cited: 6
Tool wear classification based on minimalism in deep learning for VanillaNet and recurrence plot encoding technology
Shuqiang Wang, Jiawen Tian
Journal of Mechanical Science and Technology (2024) Vol. 38, Iss. 9, pp. 4793-4807
Closed Access | Times Cited: 1
Prediction of Machining Condition Using Time Series Imaging and Deep Learning in Slot Milling of Titanium Alloy
Faramarz Hojati, Bahman Azarhoushang, Amir Daneshi, et al.
Journal of Manufacturing and Materials Processing (2022) Vol. 6, Iss. 6, pp. 145-145
Open Access | Times Cited: 7
Direct Fabrication of a Copper RTD over a Ceramic-Coated Stainless-Steel Tube by Combination of Magnetron Sputtering and Sol–Gel Techniques
Aitor Bikarregi, Santiago Dominguez, Marta Brizuela, et al.
Sensors (2023) Vol. 23, Iss. 12, pp. 5442-5442
Open Access | Times Cited: 2
Development and testing of a wireless smart toolholder with multi-sensor fusion
Jin Zhang, Xinzhen Kang, Zhengmao Ye, et al.
Frontiers of Mechanical Engineering (2023) Vol. 18, Iss. 4
Closed Access | Times Cited: 2
Tool State Recognition Based on POGNN-GRU under Unbalanced Data
Weiming Tong, Jiaqi Shen, Zhongwei Li, et al.
Sensors (2024) Vol. 24, Iss. 16, pp. 5433-5433
Open Access
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