Prediction of Tool Wear by Using RGB Techniques in Comparison with Experimental Analysis-Reference-Cited by-同舟云学术

Prediction of Tool Wear by Using RGB Techniques in Comparison with Experimental Analysis

Published:2022-12-08 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI)
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Author:

Dilli Ganesh V¹,Bommi R.M.²

Affiliation:

1. Saveetha Institute of Medical and Technical Science,Saveetha School of Engineering,Department of Mechanical Engineering,Chennai,India

2. Saveetha Institute of Medical and Technical Science,Saveetha School of Engineering,Department of Electronics and Communication Engineering,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10028778/10028782/10028899.pdf?arnumber=10028899

Reference15 articles.

1. Reliable tool wear monitoring by optimized image and illumination control in machine vision

2. Tool Wear Detection of Cutting Tool Using Matlab Software;patil;Int J Eng Tech Res,2014

3. Tool wear analysis during turning of hard material by simulink;kshetri;Int J Eng Adv Technol,2019

4. Use of image processing to monitor tool wear in micro milling

5. Investigation of signal behaviors for sensor fusion with tool condition monitoring system in turning;kunto?lu;Meas J Int Meas Confed,2021

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