A novel ensemble deep learning model for cutting tool wear monitoring using audio sensors-Reference-Cited by-同舟云学术

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A novel ensemble deep learning model for cutting tool wear monitoring using audio sensors

Published:2022-07 Issue: Volume:79 Page:233-249
ISSN:1526-6125
Container-title:Journal of Manufacturing Processes
language:en
Short-container-title:Journal of Manufacturing Processes

Author:

Li Zhixiong,Liu Xihao,Incecik Atilla,Gupta Munish Kumar,Królczyk Grzegorz M.,Gardoni Paolo

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Reference44 articles.

1. Investigation of microstructure, mechanical and machinability properties of mo-added steel produced by powder metallurgy method;Erden;Int J Adv Manuf Technol,2021

2. Investigation of signal behaviors for sensor fusion with tool condition monitoring system in turning;Kuntoğlu;Measurement,2021

3. Investigation on universal tool wear measurement technique using image-based cross-correlation analysis;Fong;Measurement,2021

4. Online tool condition monitoring for ultrasonic metal welding via sensor fusion and machine learning;Nazir;J Manuf Process,2021

5. Estimation of tool wear during CNC milling using neural network-based sensor fusion;Ghosh;Mech Syst Sign Process,2007

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