Application of metaheuristic optimization based support vector machine for milling cutter health monitoring-Reference-Cited by-同舟云学术

Application of metaheuristic optimization based support vector machine for milling cutter health monitoring

Published:2023-05 Issue: Volume:18 Page:200196
ISSN:2667-3053
Container-title:Intelligent Systems with Applications
language:en
Short-container-title:Intelligent Systems with Applications

Author:

Bajaj Naman S.,Patange Abhishek D.^ORCID,Jegadeeshwaran R.,Pardeshi Sujit S.,Kulkarni Kaushal A.,Ghatpande Rohan S.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,Computer Vision and Pattern Recognition,Signal Processing,Computer Science (miscellaneous)

Reference59 articles.

1. Heat generation and temperature prediction in metal cutting: A review and implications for high speed machining;Abukhshim;International Journal of Machine Tools and Manufacture,2006

2. Tool damage state condition monitoring in milling processes based on the mechanistic model goodness-of-fit metrics;Asadzadeh;Journal of Manufacturing Processes,2022

3. Multi-sensor heterogeneous data-based online tool health monitoring in milling of IN718 superalloy using OGM (1, N) model and SVM;Babu;Measurement,2022

4. Tool condition monitoring by SVM classification of machined surface images in turning;Bhat;The International Journal of Advanced Manufacturing Technology,2016

5. Tool condition monitoring (TCM) – the status of research and industrial application;Byrne;CIRP Annals,1995

Cited by 18 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A reduced-order machine-learning-based method for fault recognition in tool condition monitoring;Measurement;2024-01

2. An Accurate Metaheuristic Mountain Gazelle Optimizer for Parameter Estimation of Single- and Double-Diode Photovoltaic Cell Models;Mathematics;2023-11-07

3. Review on prognostics and health management in smart factory: From conventional to deep learning perspectives;Engineering Applications of Artificial Intelligence;2023-11

4. Knowledge Embedded Lightweight Vision Transformer for Machine Condition Monitoring;Measurement;2023-11

5. Review of resampling techniques for the treatment of imbalanced industrial data classification in equipment condition monitoring;Engineering Applications of Artificial Intelligence;2023-11