Segmentation and quantitative evaluation for tool wear condition via an improved SE-U-Net-Reference-Cited by-同舟云学术

Segmentation and quantitative evaluation for tool wear condition via an improved SE-U-Net

Published:2022-05-16 Issue: Volume: Page:
ISSN:0268-3768
Container-title:The International Journal of Advanced Manufacturing Technology
language:en
Short-container-title:Int J Adv Manuf Technol

Author:

Xia Linzhi,Shi Yizhu,Lin Hongjie,Zheng Houyuan,Cao Xincheng,Chen Binqiang,Zhou Yuqing,Sun Weifang^ORCID

Funder

Natural Science Foundation of Zhejiang Province

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00170-022-09338-2.pdf

Reference38 articles.

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4. Benkedjouh T, Zerhouni N, Rechak S et al (2018) Tool wear condition monitoring based on continuous wavelet transform and blind source separation. Int J Adv Manuf Technol 97:3311–3323

5. Wojciechowski S, Twardowski P, Pelic M et al (2014) Cutting forces and vibrations during ball end milling of inclined surfaces. Procedia CIRP 14:113–118

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