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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 identification and prediction method based on stack sparse self-coding network
Yiyuan Qin, Xianli Liu, Caixu Yue, et al.
Journal of Manufacturing Systems (2023) Vol. 68, pp. 72-84
Closed Access | Times Cited: 55

Showing 26-50 of 55 citing articles:

A dual knowledge embedded hybrid model based on augmented data and improved loss function for tool wear monitoring
Xuzhou Fang, Qinghua Song, Jing Qin, et al.
Robotics and Computer-Integrated Manufacturing (2024) Vol. 92, pp. 102901-102901
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 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
A Tcn-Bigru Network with Soft Thresholding and Attention Mechanism for the Tool Wear Prediction
Binglin Li, Jun Li, Xingsheng Wu, et al.
(2024)
Closed Access | Times Cited: 1
Tool wear monitoring strategy during micro-milling of TC4 alloy based on a fusion model of recursive feature elimination-bayesian optimization-extreme gradient boosting
Hongfei Wang, Qingshun Bai, Jianduo Zhang, et al.
Journal of Materials Research and Technology (2024) Vol. 31, pp. 398-411
Open Access | Times Cited: 1
Nondestructive evaluation of bonding quality of dual-layer coatings based on the multi-feature ultrasonic method
Shaorui Fan, Maodan Yuan, Jianlin Xu, et al.
Applied Acoustics (2024) Vol. 224, pp. 110151-110151
Closed Access | Times Cited: 1
A semi-supervised learning method combining tool wear laws for machining tool wear states monitoring
Mengmeng Niu, Kuo Liu, Yongqing Wang
Mechanical Systems and Signal Processing (2024) Vol. 224, pp. 112032-112032
Closed Access | Times Cited: 1
A deep transfer learning model for online monitoring of surface roughness in milling with variable parameters
Kai Zhou, Pingfa Feng, Feng Feng, et al.
Computers in Industry (2024) Vol. 164, pp. 104199-104199
Closed Access | Times Cited: 1
Physics-informed inhomogeneous wear identification of end mills by online monitoring data
Guochao Li, S. Xu, Ru Jiang, et al.
Journal of Manufacturing Processes (2024) Vol. 132, pp. 759-771
Closed Access | Times Cited: 1
Tool wear prediction method based on bidirectional long short-term memory neural network of single crystal silicon micro-grinding
Chengxi She, Kexin Li, Yinghui Ren, et al.
The International Journal of Advanced Manufacturing Technology (2023) Vol. 131, Iss. 5-6, pp. 2641-2651
Closed Access | Times Cited: 3
Knowledge Embedded Lightweight Vision Transformer for Machine Condition Monitoring
Yuekai Liu, Tianyang Wang, Fulei Chu
Measurement (2023) Vol. 221, pp. 113402-113402
Closed Access | Times Cited: 2
Physics-Informed Scaling Evolutionary Transformer for In-Situ Tool Condition Monitoring
Yuekai Liu, Tianyang Wang, Shilin Sun, et al.
IEEE/ASME Transactions on Mechatronics (2023) Vol. 29, Iss. 1, pp. 647-658
Closed Access | Times Cited: 2
Wear evaluation of hard disk drive head based on a converter-like neural network
Fan Zhang, Yu Wang, Mingquan Zhang, et al.
Tribology International (2024) Vol. 195, pp. 109664-109664
Closed Access
An Advanced Tool Wear Forecasting Technique with Uncertainty Quantification Using Bayesian Inference and Support Vector Regression
Zhiming Rong, Yuxiong Li, Li Wu, et al.
Sensors (2024) Vol. 24, Iss. 11, pp. 3394-3394
Open Access
An Augmented AutoEncoder With Multi-Head Attention for Tool Wear Prediction in Smart Manufacturing
Chunping Dong, Jiaqiang Zhao
IEEE Access (2024) Vol. 12, pp. 79128-79137
Open Access
Semi-supervised Prediction of Milling Cutter Wear Based on an Empirical Formula for Cutting Force and Wear
Wujun Yu, Hongfei Zhan, Junhe Yu, et al.
Research Square (Research Square) (2024)
Open Access
A variable modal decomposition and BiGRU-based tool wear monitoring method based on non-dominated sorting genetic algorithm II
Yiyuan Qin, Xianli Liu, Xudong Wei, et al.
International Journal of Computer Integrated Manufacturing (2024), pp. 1-17
Closed Access
Exploring the Processing Paradigm of Input Data for End-to-End Deep Learning in Tool Condition Monitoring
Chengguan Wang, Guangping Wang, Tao Wang, et al.
Sensors (2024) Vol. 24, Iss. 16, pp. 5300-5300
Open Access
Data-driven unsupervised anomaly detection of manufacturing processes with multi-scale prototype augmentation and multi-sensor data
Zongliang Xie, Zhipeng Zhang, Jinglong Chen, et al.
Journal of Manufacturing Systems (2024) Vol. 77, pp. 26-39
Closed Access
Machining Tool Wear Detection and Measurement Based on Edge Extraction and Sub-pixel Fitting
P. Chen, Jianbo Yu
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-11
Closed Access
Experimental prediction model for full life friction performance of wet clutch via attention-based LSTM network
Feng Yu-qing, Changsong Zheng, Liang Yu, et al.
Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering (2024)
Closed Access
Research on milling cutter wear monitoring based on self-learning feature boundary model
Xuchen Hou, Wei Xia, Xianli Liu, et al.
The International Journal of Advanced Manufacturing Technology (2024) Vol. 135, Iss. 3-4, pp. 1789-1807
Closed Access
Tool Wear Prediction Based on K-means and Adaboost Auto-Encoder
Lihua Shen, Fan He, Weiguo Lu, et al.
Measurement Science and Technology (2024) Vol. 36, Iss. 1, pp. 016119-016119
Closed Access
Machine remaining useful life prediction method based on global-local attention compensation network
Zhixiang Chen
Reliability Engineering & System Safety (2024) Vol. 255, pp. 110652-110652
Closed Access
Realizing on-machine tool wear monitoring through integration of vision-based system with CNC milling machine
Aitha Sudheer Kumar, Ankit Agarwal, Vinita Gangaram Jansari, et al.
Journal of Manufacturing Systems (2024) Vol. 78, pp. 283-293
Closed Access

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