Real-time tool condition monitoring method based on in situ temperature measurement and artificial neural network in turning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Mechanical Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11465-021-0661-3.pdf
Reference26 articles.
1. Liu X, Wen D, Li Z, Xiao L, Yan F G. Cutting temperature and tool wear of hard turning hardened bearing steel. Journal of Materials Processing Technology, 2002, 129(1–3): 200–206
2. Dan L, Mathew J. Tool wear and failure monitoring techniques for turning—A review. International Journal of Machine Tools and Manufacture, 1990, 30(4): 579–598
3. Rizal M, Ghani J A, Nuawi M Z, Haron C H C. Online tool wear prediction system in the turning process using an adaptive neurofuzzy inference system. Applied Soft Computing, 2013, 13(4): 1960–1968
4. Zhou Y, Xue W. Review of tool condition monitoring methods in milling processes. International Journal of Advanced Manufacturing Technology, 2018, 96(5–8): 2509–2523
5. Visariya R, Ruparel R, Yadav R. Review of tool condition monitoring methods. International Journal of Computers and Applications, 2018, 179(37): 29–32
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