Hidden Markov model-based tool wear monitoring in turning

被引:117
作者
Wang, LT [1 ]
Mehrabi, MG [1 ]
Kannatey-Asibu, E [1 ]
机构
[1] Univ Michigan, Engn Res Ctr Reconfigurable Machining Syst, Dept Mech Engn, Ann Arbor, MI 48109 USA
来源
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME | 2002年 / 124卷 / 03期
关键词
D O I
10.1115/1.1475320
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents a new modeling framework for tool wear monitoring in machining processes using hidden Markov models (HMMs). Feature vectors are extracted from vibration signals measured during turning. A codebook is designed and used for vector quantization to convert the feature vectors into a symbol sequence for the hidden Markov model. A series of experiments are conducted to evaluate the effectiveness of the approach for different lengths of training data and observation sequence. Experimental results show approach.
引用
收藏
页码:651 / 658
页数:8
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