Online monitoring and prediction for surface roughness in rotational electro-magnetic finishing using acoustic emission and vision-based neural network
Author:
Funder
Korea Science and Technology Holdings
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/s00170-023-12654-w.pdf
Reference57 articles.
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2. Arora K, Singh AK (2021) Theoretical and experimental investigation on surface roughness of straight bevel gears using a novel magnetorheological finishing process. Wear 476:203693. https://doi.org/10.1016/j.wear.2021.203693
3. Medeossi F, Sorgato M, Bruschi S, Savio E (2018) Novel method for Burrs quantitative evaluation in micro-milling. Precis Eng 54:379–387. https://doi.org/10.1016/j.precisioneng.2018.07.007
4. Xing B, Zou Y (2020) Investigation of finishing aluminum alloy A5052 using the magnetic abrasive finishing combined with electrolytic process. Machines 8(4):78. https://doi.org/10.3390/machines8040078
5. Wei H, Gao H, Wang X (2019) Development of novel guar gum hydrogel based media for abrasive flow machining: shear-thickening behavior and finishing performance. Int J of Mech Sci 157:758–772. https://doi.org/10.1016/j.ijmecsci.2019.05.022
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