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International Journal of Production Research Volume 46, 2008 - Issue 16
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Original Articles

Cutting force denoising in micro-milling tool condition monitoring

K. Zhu Department of Mechanical Engineering, National University of Singapore, Kent Ridge Crescent, Singapore 119260
,
G. S. Hong Department of Mechanical Engineering, National University of Singapore, Kent Ridge Crescent, Singapore 119260Correspondence[email protected]
,
Y. S. Wong Department of Mechanical Engineering, National University of Singapore, Kent Ridge Crescent, Singapore 119260
&
W. Wang Department of Mechanical Engineering, National University of Singapore, Kent Ridge Crescent, Singapore 119260
Pages 4391-4408 | Received 01 May 2005, Published online: 01 Jul 2008

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Read on this site (3)

Tamal Ghosh & Kristian Martinsen. (2019) CFNN-PSO: An Iterative Predictive Model for Generic Parametric Design of Machining Processes. Applied Artificial Intelligence 33:11, pages 951-978.
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Chun-Chin Hsu, Long-Sheng Chen & Cheng-Hsiang Liu. (2010) A process monitoring scheme based on independent component analysis and adjusted outliers. International Journal of Production Research 48:6, pages 1727-1743.
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K. P. Zhu, G. S. Hong & Y. S. Wong. (2008) A COMPARATIVE STUDY OF FEATURE SELECTION FOR HIDDEN MARKOV MODEL-BASED MICRO-MILLING TOOL WEAR MONITORING. Machining Science and Technology 12:3, pages 348-369.
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Articles from other publishers (27)

Christiand, Gandjar Kiswanto & Ario Sunar Baskoro. (2023) Towards the Digital Twin Based Tool Condition Monitoring System for Micro Milling Application: A Review. Towards the Digital Twin Based Tool Condition Monitoring System for Micro Milling Application: A Review.
Ci-Rong Huang & Ming-Chyuan Lu. (2023) Investigation of Cutting Path Effect on Spindle Vibration and AE Signal Features for Tool Wear Monitoring in Micro Milling. Applied Sciences 13:2, pages 1107.
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Kunpeng ZhuKunpeng Zhu. 2022. Smart Machining Systems. Smart Machining Systems 235 266 .
Kunpeng ZhuKunpeng Zhu. 2022. Smart Machining Systems. Smart Machining Systems 191 234 .
Sumant Bagri, Ashish Manwar, Alwin Varghese, Soham Mujumdar & Suhas S. Joshi. (2021) Tool wear and remaining useful life prediction in micro-milling along complex tool paths using neural networks. Journal of Manufacturing Processes 71, pages 679-698.
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Mustafa Kuntoğlu, Emin Salur, Munish Kumar Gupta, Murat Sarıkaya & Danil Yu. Pimenov. (2021) A state-of-the-art review on sensors and signal processing systems in mechanical machining processes. The International Journal of Advanced Manufacturing Technology 116:9-10, pages 2711-2735.
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Ming Li & Mihai Burzo. (2021) Tool Wear Monitoring Using Machine Learning. Tool Wear Monitoring Using Machine Learning.
Vinh Nguyen & Shreyes Melkote. (2021) Hybrid statistical modelling of the frequency response function of industrial robots. Robotics and Computer-Integrated Manufacturing 70, pages 102134.
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Vinh Nguyen & Shreyes N. Melkote. (2020) Identification of industrial robot frequency response function for robotic milling using operational modal analysis. Procedia Manufacturing 48, pages 154-158.
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Jay Lee, Jaskaran Singh, Moslem Azamfar & Vibhor Pandhare. 2020. Smart Manufacturing. Smart Manufacturing 213 244 .
Zhixiong Li, Rui Liu & Dazhong Wu. (2019) Data-driven smart manufacturing: Tool wear monitoring with audio signals and machine learning. Journal of Manufacturing Processes 48, pages 66-76.
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Tarak Benkedjouh, N. Zerhouni & S. Rechak. (2018) Tool wear condition monitoring based on continuous wavelet transform and blind source separation. The International Journal of Advanced Manufacturing Technology 97:9-12, pages 3311-3323.
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Qiushi Hao, Xin Zhang, Yan Wang, Yi Shen & Viliam Makis. (2018) A novel rail defect detection method based on undecimated lifting wavelet packet transform and Shannon entropy-improved adaptive line enhancer. Journal of Sound and Vibration 425, pages 208-220.
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Jialong He, Zhaojun Yang, Chuanhai Chen, Guofa Li, Zhen Li & Yuhui Jia. (2018) Improved multi-wavelet denoising with neighboring coefficients of cutting force for application in the load spectrum of computer numerical control lathe. Advances in Mechanical Engineering 10:2, pages 168781401875467.
Crossref
Brian Boswell, M. N. Islam & Ian J. Davies. (2017) A review of micro-mechanical cutting. The International Journal of Advanced Manufacturing Technology 94:1-4, pages 789-806.
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Kamil S. Kazimierski, Iwona Piotrowska-Kurczewski, Florian Böhmermann & Oltmann Riemer. (2016) A statistical filtering method for denoising of micro-force measurements. The International Journal of Advanced Manufacturing Technology 87:5-8, pages 1693-1704.
Crossref
Cunji Zhang, Xifan Yao, Jianming Zhang & Hong Jin. (2016) Tool Condition Monitoring and Remaining Useful Life Prognostic Based on a Wireless Sensor in Dry Milling Operations. Sensors 16:6, pages 795.
Crossref
Kunpeng Zhu & Birgit Vogel-Heuser. (2013) Sparse representation and its applications in micro-milling condition monitoring: noise separation and tool condition monitoring. The International Journal of Advanced Manufacturing Technology 70:1-4, pages 185-199.
Crossref
Emel Kuram & Babur Ozcelik. (2013) Multi-objective optimization using Taguchi based grey relational analysis for micro-milling of Al 7075 material with ball nose end mill. Measurement 46:6, pages 1849-1864.
Crossref
Chien-Wei Hung & Ming-Chyuan Lu. (2012) Model development for tool wear effect on AE signal generation in micromilling. The International Journal of Advanced Manufacturing Technology 66:9-12, pages 1845-1858.
Crossref
Yue Sun, Yongsheng Liu, Zhanjiang Yu, Huadong Yu & Jingkai Xu. (2012) Milling force mixed-signal denoising based on ICA in high speed micro-milling. Milling force mixed-signal denoising based on ICA in high speed micro-milling.
Zhu Kunpeng, Wong Yoke San & Hong Geok Soon. 2012. Mechatronics and Manufacturing Engineering. Mechatronics and Manufacturing Engineering 115 157 .
Zhu Kunpeng, Hong Geok Soon & Wong Yoke San. (2011) Multiscale Singularity Analysis of Cutting Forces for Micromilling Tool-Wear Monitoring. IEEE Transactions on Industrial Electronics 58:6, pages 2512-2521.
Crossref
Omid Geramifard, Jian-Xin Xu, Jun-Hong Zhou & Xiang Li. (2011) Continuous health condition monitoring: A single Hidden Semi-Markov Model approach. Continuous health condition monitoring: A single Hidden Semi-Markov Model approach.
Chun-Chin Hsu, Mu-Chen Chen & Long-Sheng Chen. (2010) A novel process monitoring approach with dynamic independent component analysis. Control Engineering Practice 18:3, pages 242-253.
Crossref
Kunpeng Zhu, Yoke San Wong & Geok Soon Hong. (2009) Wavelet analysis of sensor signals for tool condition monitoring: A review and some new results. International Journal of Machine Tools and Manufacture 49:7-8, pages 537-553.
Crossref
K. P. Zhu, Y. S. Wong & G. S. Hong. 2008. Soft Computing Applications in Industry. Soft Computing Applications in Industry 23 46 .

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