Cutting Chatter Monitoring Using Hidden Markov Models

被引：2
|
作者：
Zhang Chunliang [1 ]
Yue Xia [2 ]
Zhang Xuewen [2 ]
机构：
[1] GuangZhou Univ, Sch Mech & Elect Engn, Guangzhou, Guangdong, Peoples R China
[2] NanHua Univ, Sch Mech Engn, Hengyang, Peoples R China
来源：
2009 IITA INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS ENGINEERING, PROCEEDINGS | 2009年
基金：
中国国家自然科学基金;
关键词：
Cutting Chatter; Condition Monitoring; Hidden Markov Model (HMM); Fast Fourier Transform (FFT);
D O I：
10.1109/CASE.2009.63
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Monitoring of cutting chatter in metal cutting process is a very important economical consideration in automated manufacturing. However, the metal cutting process is a complicated process. The cutting chatter is still an unsolved problem in metal cutting process. In this paper, a new method for cutting chatter monitoring is developed. First, it uses fast Fourier transform (FFT) to process the monitoring signals of the cutting process and to extract the feature vectors. Then, it uses the Hidden Markov Model (HMM) as the classifiers to recognize the cutting chatter. The experimental results show that the proposed method is feasible and effective.
引用
收藏
页码：504 / +
页数：2
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