A novel approach for prediction of surface roughness in turning of EN353 steel by RVR-PSO using selected features of VMD along with cutting parameters-Reference-Cited by-同舟云学术

A novel approach for prediction of surface roughness in turning of EN353 steel by RVR-PSO using selected features of VMD along with cutting parameters

Published:2022-06 Issue:6 Volume:36 Page:2775-2785
ISSN:1738-494X
Container-title:Journal of Mechanical Science and Technology
language:en
Short-container-title:J Mech Sci Technol

Author:

Guleria Vikrant,Kumar Vivek,Singh Pradeep K.

Publisher

Springer Science and Business Media LLC

Subject

Mechanical Engineering,Mechanics of Materials

Link

https://link.springer.com/content/pdf/10.1007/s12206-022-0510-2.pdf

Reference47 articles.

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3. S. V. Prasad, B. V. R. R. Kumar and V. V. S. Rao, Prediction of surface roughness in turning of EN19 steel using acoustic emission, Recent Adv. Mater. Sci., Springer Singapore, Singapore (2019) 113–122.

4. C. Beggan et al., Using acoustic emission to predict surface quality, Int. J. Adv. Manuf. Technol., 15(10) (1999) 737–742.

5. D. R. Salgado et al., In-process surface roughness prediction system using cutting vibrations in turning, Int. J. Adv. Manuf. Technol., 43(1–2) (2009) 40–51.

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