Journal ArticleDOI
On-line chatter detection and identification based on wavelet and support vector machine
Zhehe Yao,Deqing Mei,Zichen Chen +2 more
TLDR
A intelligent recognition system, composed of the feature extraction and the SVM, has an accuracy rate of 95% for the identification of stable, transition and chatter state after being trained by the experiment data.About:
This article is published in Journal of Materials Processing Technology.The article was published on 2010-03-19. It has received 220 citations till now. The article focuses on the topics: Wavelet packet decomposition & Second-generation wavelet transform.read more
Citations
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Journal ArticleDOI
Chatter in machining processes: A review
Guillem Quintana,Joaquim Ciurana +1 more
TL;DR: A review of the state of research on the chatter problem and classifications the existing methods developed to ensure stable cutting into those that use the lobbing effect, out-of-process or in-process, and those that, passively or actively, modify the system behavior as mentioned in this paper.
Journal ArticleDOI
The concept and progress of intelligent spindles: A review
TL;DR: An in-depth review of the state-of-the-art of related technologies for intelligent spindles is provided, followed by descriptions of required characteristics, key enabling technologies and expected intelligent functions.
Journal ArticleDOI
Chatter identification in end milling process using wavelet packets and Hilbert–Huang transform
TL;DR: In this paper, the authors presented an effective chatter identification method for the end milling process based on the study of two advanced signal processing techniques, i.e., wavelet package transform (WPT) and Hilbert-Huang transform (HHT).
Journal ArticleDOI
Recent progress of chatter prediction, detection and suppression in milling
Lida Zhu,Changfu Liu +1 more
TL;DR: A critical review of chatter is presented, focusing on regenerative chatter and mode coupling chatter, and four directions for future research are presented, including integrating the chatter prediction, detection and suppression units into a smart machine tool or smart spindle.
Journal ArticleDOI
Chatter detection in milling process based on the energy entropy of VMD and WPD
TL;DR: A novel approach to detect the milling chatter based on energy entropy is presented, by using variational mode decomposition and wavelet packet decomposition, which can effectively detect the chatter at an early stage.
References
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Statistical learning theory
TL;DR: Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.
Journal ArticleDOI
Least Squares Support Vector Machine Classifiers
TL;DR: A least squares version for support vector machine (SVM) classifiers that follows from solving a set of linear equations, instead of quadratic programming for classical SVM's.
Journal ArticleDOI
Use of Audio Signals for Chatter Detection and Control
TL;DR: In this article, the authors compared various sensors and showed that a microphone is an excellent sensor to be used for chatter detection and control in industrial milling systems and concluded that the signal from the microphone provides a competitive, and in many instances a superior, signal tht can be utilized to identify chatter.
Journal ArticleDOI
Multisensor approaches for chatter detection in milling
TL;DR: In this article, the authors investigated the development of a chatter detection system for application in industrial conditions, in which the signal characteristics both in time and frequency domain were condensed into a set of chatter indicators, which were further elaborated by means of statistical basic concepts to obtain a chatter identification system.
Book
Wavelets and Signal Processing: An Application-Based Introduction
TL;DR: Wavelets and Signal Processing: An Application-Based ...