Multi-modal denoised data-driven milling chatter detection using an optimized hybrid neural network architecture

Multi-modal denoised data-driven milling chatter detection using an optimized hybrid neural network architecture

Abstract Chatter, a type of self-excited vibration, deteriorates surface quality and reduces tool life and machining efficiency. Chatter detection serves as an effective approach to achieve stable cutting. To address the low accuracy in chatter detection caused by the limitations of both one-dimensi...

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Bibliographic Details
Main Authors: Haining Gao, Haoyu Wang, Hongdan Shen, Shule Xing, Yong Yang, Yinlin Wang, Wenfu Liu, Lei Yu, Mazhar Ali, Imran Ali Khan
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Chatter detection
Multi-modal data
Optimized hybrid neural network
Data denoising
Online Access:https://doi.org/10.1038/s41598-025-88242-7
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