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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 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

Showing 1-25 of 32 citing articles:

Fault diagnosis of a CNC Hobbing Cutter through Machine Learning using three axis vibration data
Nagesh Tambake, Bhagyesh Deshmukh, Sujit S. Pardeshi, et al.
Heliyon (2025) Vol. 11, Iss. 2, pp. e41637-e41637
Open Access | Times Cited: 1
Tool wear state recognition study based on an MTF and a vision transformer with a Kolmogorov-Arnold network
Shengming Dong, Meng Yue, Shubin Yin, et al.
Mechanical Systems and Signal Processing (2025) Vol. 228, pp. 112473-112473
Closed Access | Times Cited: 1
Hierarchical temporal transformer network for tool wear state recognition
Zhongling Xue, Ni Chen, Youling Wu, et al.
Advanced Engineering Informatics (2023) Vol. 58, pp. 102218-102218
Closed Access | Times Cited: 14
An imbalanced data learning approach for tool wear monitoring based on data augmentation
Bowen Zhang, Xianli Liu, Caixu Yue, et al.
Journal of Intelligent Manufacturing (2023)
Closed Access | Times Cited: 14
A deep learning method based on multi-scale fusion for noise-resistant coal-gangue recognition
Qingjun Song, Shirong Sun, Qinghui Song, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Electricity terminal multi-label recognition with a “one-versus-all” rejection recognition algorithm based on adaptive distillation increment learning and attention MobileNetV2 network for non-invasive load monitoring
Linfei Yin, Nannan Wang, Jishen Li
Applied Energy (2025) Vol. 382, pp. 125307-125307
Closed Access
Toward high-performance machining of thin-walled parts: Fusion of parallel spatial–temporal information in high-speed milling for monitoring tool wear
Yezhen Peng, Qinghua Song, Runqiong Wang, et al.
Measurement (2025), pp. 116899-116899
Closed Access
Swin-fusion: An adaptive multi-source information fusion framework for enhanced tool wear monitoring
Kailin Hou, Rongyi Li, Xianli Liu, et al.
Journal of Manufacturing Systems (2025) Vol. 79, pp. 435-454
Closed Access
A novel algorithm for tool wear monitoring utilizing model and Knowledge-Guided Multi-Expert weighted adversarial deep transfer learning
Zhilie Gao, Ni Chen, Liang Li
Mechanical Systems and Signal Processing (2025) Vol. 228, pp. 112456-112456
Closed Access
A Model for Predicting 3D Wear Morphology of Ball-End Milling Tools: Development and Validation
Rongyi Li, Hengyang He, Caixu Yue, et al.
Coatings (2025) Vol. 15, Iss. 4, pp. 394-394
Open Access
Interpretable tool wear monitoring: Architecture with large-scale CNN and adaptive EMD
Yi Sun, Hong‐Liang Song, Hongli Gao, et al.
Journal of Manufacturing Systems (2024) Vol. 78, pp. 294-307
Closed Access | Times Cited: 3
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
Research on establishment of digital-twin system for intelligent control of cutting tools sintering process driven by data-model combination
Chao Niu, Rongyi Li, Mingqiu Dai, et al.
Journal of Manufacturing Systems (2024) Vol. 74, pp. 68-82
Closed Access | Times Cited: 2
An innovative Multisource Lightweight Adaptive Replayed Online Deep Transfer Learning algorithm for tool wear monitoring
Zhilie Gao, Ni Chen, Yinfei Yang, et al.
Journal of Manufacturing Processes (2024) Vol. 124, pp. 261-281
Closed Access | Times Cited: 2
Research on Wear State Identification of Ordered Grinding Wheel for C/SiC Composites Based on DBO-ELM
Ye Guo, Bing Chen, Hongyu Zeng, et al.
Wear (2024) Vol. 556-557, pp. 205529-205529
Closed Access | Times Cited: 2
Denoising Diffusion Probabilistic Model Enhanced Tool Condition Monitoring Method Under Imbalanced Conditions
Yu Fu, Meipeng Zhong, Junfeng Huang, et al.
Measurement Science and Technology (2024) Vol. 36, Iss. 1, pp. 015018-015018
Closed Access | Times Cited: 2
Recent Progress of Chatter Detection and Tool Wear Online Monitoring in Machining Process: A Review and Future Prospects
Feng-ze Qin, Huajun Cao, Guibao Tao, et al.
International Journal of Precision Engineering and Manufacturing-Green Technology (2024) Vol. 12, Iss. 2, pp. 719-748
Closed Access | Times Cited: 2
Online monitoring method of non-cylindrical wheel wear for gear grinding based on dynamic force model
Yuliang Xiao, Shilong Wang, Jianpeng Dong, et al.
Mechanical Systems and Signal Processing (2023) Vol. 206, pp. 110915-110915
Closed Access | Times Cited: 6
Tool Wear State Recognition Based on One-Dimensional Convolutional Channel Attention
Zhongling Xue, Liang Li, Ni Chen, et al.
Micromachines (2023) Vol. 14, Iss. 11, pp. 1983-1983
Open Access | Times Cited: 5
Tool wear prediction method based on dual-attention mechanism network
Yaonan Cheng, Shilong Zhou, Mengda Lu, et al.
International Journal of Computer Integrated Manufacturing (2024), pp. 1-16
Closed Access | Times Cited: 1
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
A deep learning approach for accurate assessment of conveyor belt wear state based on multispectral imaging
Mengran Zhou, Yue Chen, Feng Hu, et al.
Optics & Laser Technology (2024) Vol. 181, pp. 111782-111782
Closed Access | Times Cited: 1
BDTM-Net: A tool wear monitoring framework based on semantic segmentation module
Jiaqi Zhou, Caixu Yue, Jiaxu Qu, et al.
Journal of Manufacturing Systems (2024) Vol. 77, pp. 576-590
Closed Access | Times Cited: 1
Tool wear prediction based on hybrid feature selection
Wanzhen Wang, Sze Song Ngu, Miaomiao Xin, et al.
(2024), pp. 41-41
Closed Access
Comparative Study of Conventional Machine Learning versus Deep Learning-Based Approaches for Tool Condition Assessments in Milling Processes
Agata Przybyś-Małaczek, Izabella Antoniuk, Karol Szymanowski, et al.
Applied Sciences (2024) Vol. 14, Iss. 13, pp. 5913-5913
Open Access
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