A Novel Unsupervised Machine Learning-Based Method for Chatter Detection in the Milling of Thin-Walled Parts

A Novel Unsupervised Machine Learning-Based Method for Chatter Detection in the Milling of Thin-Walled Parts

Data-driven chatter detection techniques avoid complex physical modeling and provide the basis for industrial applications of cutting process monitoring. Among them, feature extraction is the key step of chatter detection, which can compensate for the accuracy disadvantage of machine learning algori...

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Bibliographic Details
Main Authors: Runqiong Wang, Qinghua Song, Zhanqiang Liu, Haifeng Ma, Munish Kumar Gupta, Zhaojun Liu
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Sensors
Subjects:
chatter detection
thin-walled parts
unsupervised machine learning
feature extraction
fractal theory
Online Access:https://www.mdpi.com/1424-8220/21/17/5779

Internet

https://www.mdpi.com/1424-8220/21/17/5779

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