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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 prediction method based on symmetrized dot pattern and multi-covariance Gaussian process regression
Chuandong Zhang, Wei Wang, Hai Li
Measurement (2021) Vol. 189, pp. 110466-110466
Closed Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

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
Integrating physics-informed recurrent Gaussian process regression into instance transfer for predicting tool wear in milling process
Biyao Qiang, Kaining Shi, Ning Liu, et al.
Journal of Manufacturing Systems (2023) Vol. 68, pp. 42-55
Closed Access | Times Cited: 32
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: 28
Intelligent milling tool wear estimation based on machine learning algorithms
Yunus Emre Karabacak
Journal of Mechanical Science and Technology (2024) Vol. 38, Iss. 2, pp. 835-850
Closed Access | Times Cited: 7
Bayesian-based uncertainty-aware tool-wear prediction model in end-milling process of titanium alloy
Gyeongho Kim, Sang Min Yang, Dong Min Kim, et al.
Applied Soft Computing (2023) Vol. 148, pp. 110922-110922
Open Access | Times Cited: 20
Tool Wear Prediction Based on Multi-Information Fusion and Genetic Algorithm-Optimized Gaussian Process Regression in Milling
Zhiwen Huang, Jiajie Shao, Weicheng Guo, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-16
Open Access | Times Cited: 18
Role of image feature enhancement in intelligent fault diagnosis for mechanical equipment: A review
Yongjian Sun, Wei Wang
Engineering Failure Analysis (2023) Vol. 156, pp. 107815-107815
Closed Access | Times Cited: 16
Auxiliary input-enhanced siamese neural network: A robust tool wear prediction framework with improved feature extraction and generalization ability
Chenghan Wang, Bin Shen
Mechanical Systems and Signal Processing (2024) Vol. 211, pp. 111243-111243
Closed Access | Times Cited: 5
A temporal-spatial encoder convolutional network model for multitasking prediction
Chengying Zhao, Huaitao Shi, Xianzhen Huang, et al.
Applied Intelligence (2025) Vol. 55, Iss. 5
Closed Access
Hybrid machine learning-enabled multi-information fusion for indirect measurement of tool flank wear in milling
Zhiwen Huang, Jiajie Shao, Weicheng Guo, et al.
Measurement (2022) Vol. 206, pp. 112255-112255
Closed Access | Times Cited: 22
Remaining useful life prediction using nonlinear multi-phase Wiener process and variational Bayesian approach
Wen‐Yi Lin, Yi Chai, Linchuan Fan, et al.
Reliability Engineering & System Safety (2023) Vol. 242, pp. 109800-109800
Closed Access | Times Cited: 15
Tool wear prediction based on parallel dual-channel adaptive feature fusion
Jinfei Yang, Jinxin Wu, Xianwang Li, et al.
The International Journal of Advanced Manufacturing Technology (2023) Vol. 128, Iss. 1-2, pp. 145-165
Closed Access | Times Cited: 13
Remaining useful life prediction of rolling bearing via composite multiscale permutation entropy and Elman neural network
Yongjian Sun, Zihan Wang
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108852-108852
Closed Access | Times Cited: 4
AI-Driven Wear Monitoring of PVD TiAlN Coated Carbide Insert in Sustainable Machining of Hastelloy C276: An Industry 4.0 Perspective
Binayak Sen, Subhankar Saha, Raman Kumar, et al.
Results in Engineering (2025), pp. 104457-104457
Open Access
Tool digital twin based on knowledge embedding for precision CNC machine tools: Wear prediction for collaborative multi-tool
Jiacheng Sun, Dong Wang, Zhenyu Liu, et al.
Journal of Manufacturing Systems (2025) Vol. 80, pp. 157-175
Closed Access
Image texture feature fusion enhancement for bearing fault diagnosis based on maximum gradient
Yongjian Sun, Gang Yu, Wei Wang
Reliability Engineering & System Safety (2025), pp. 111009-111009
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
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: 12
Intelligent Tool-Wear Prediction Based on Informer Encoder and Bi-Directional Long Short-Term Memory
Xingang Xie, Min Huang, Yue Liu, et al.
Machines (2023) Vol. 11, Iss. 1, pp. 94-94
Open Access | Times Cited: 11
Hybrid physics data-driven model-based fusion framework for machining tool wear prediction
Tianhong Gao, Haiping Zhu, Jun Wu, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 132, Iss. 3-4, pp. 1481-1496
Closed Access | Times Cited: 3
Deep transfer residual variational autoencoder with multi-sensors fusion for tool condition monitoring in impeller machining
Jiayu Ou, Hongkun Li, Bo Liu, et al.
Measurement (2022) Vol. 204, pp. 112028-112028
Closed Access | Times Cited: 16
Research on tool wear classification of milling 508III steel based on chip spectrum feature
Rui Guan, Yaonan Cheng, Shilong Zhou, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 133, Iss. 3-4, pp. 1531-1547
Closed Access | Times Cited: 3
A proposal for improving production efficiency of existing machining line through a hybrid monitoring and optimisation process
Jonny Herwan, Takashi Misaka, Yoshiyuki Furukawa, et al.
International Journal of Production Research (2022) Vol. 61, Iss. 16, pp. 5392-5410
Closed Access | Times Cited: 13
Multi-Source Information Fusion Fault Diagnosis for Gearboxes Based on SDP and VGG
Yuan Fu, Xiang Chen, Yu Liu, et al.
Applied Sciences (2022) Vol. 12, Iss. 13, pp. 6323-6323
Open Access | Times Cited: 10
Research on intelligent tool condition monitoring based on data-driven: a review
Yaonan Cheng, Rui Guan, Yingbo Jin, et al.
Journal of Mechanical Science and Technology (2023) Vol. 37, Iss. 7, pp. 3721-3738
Closed Access | Times Cited: 5
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