RETRACTED: An acoustic imaging recognition based cutting tools wear state prediction method

Author:

Hou Junjian1,Zhang Bingyu1,Zhong Yudong1,Zhao Dengfeng1,He Wenbin1,Zhou Fang1

Affiliation:

1. Henan Provincial Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Mechanical and Electrical Engineering Institute, Zhengzhou University of Light Industry, Zhengzhou, Henan, China

Abstract

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.

Publisher

IOS Press

Reference30 articles.

1. State-of-the-art methods and results in tool condition monitoring: a review;Rehorn;International Journal of Advanced Manufacturing Technology,2005

2. A review of flank wear prediction methods for tool condition monitoring in a turning process;Siddhpura;International Journal of Advanced Manufacturing Technology,2013

3. Deep learning;Heaton;Genetic Programing and Evolvable Machines,2018

4. Modeling and prediction of tool wera using LS-SVM in milling operation;Zhang;International Journal of Computer Integrated Manufacturing,2016

5. An in-process tool wear assessment using Bayesian optimized machine learning algorithm;Sarat;International Journal on Interactive Design and Manufacturing,2023

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