Feature extraction using dominant frequency bands and time-frequency image analysis for chatter detection in milling
Author:
Funder
Collaborative Innovation Center of High-End Equipment Manufacturing
International Postdocs Exchange Program
UNSW
Publisher
Elsevier BV
Subject
General Engineering
Reference31 articles.
1. Indicators for monitoring chatter in milling based on instantaneous angular speeds;Lamraoui;Mech Syst Signal Process,2014
2. Effect of different features to drill-wear prediction with back propagation neural network;Xu;Precis Eng,2014
3. Application of Hilbert–Huang transform for vibration signal analysis in end-milling;Susanto;Precis Eng,2018
4. A novel sound-based belt condition monitoring method for robotic grinding using optimally pruned extreme learning machine;Zhang;J Mater Process Technol,2018
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