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DHMM+SVM在切削颤振中的应用
引用本文:蒋文凤,江涌涛,张春良,刘琼.DHMM+SVM在切削颤振中的应用[J].机电产品开发与创新,2009,22(3):179-181.
作者姓名:蒋文凤  江涌涛  张春良  刘琼
作者单位:南华大学机械工程学院,湖南,衡阳,421001
摘    要:根据切削颤振的特点,结合隐马尔可夫模型(Hidden Markov Model,HMM)和支持向量机(Support Vector Machine,SVM)的特点,提出了一种新的状态预测技术,同时也提出了一种新的特征提取方法。首先在等时间间隔内对切削信号实时进行小波包分解,然后通过SVM对各频带区间能量变化趋势进行回归预测,最后通过HMM对预测结果进行分类。结果表明,该方法取得了较好的预测结果。

关 键 词:切削颤振  小波包分解  HMM  SVR

Application of HMM and SVM in Cutting Chatter
JIANG Wen-Feng,JIANG Yong-Tao,ZHANG Chun-Liang,LIU Qiong.Application of HMM and SVM in Cutting Chatter[J].Development & Innovation of Machinery & Electrical Products,2009,22(3):179-181.
Authors:JIANG Wen-Feng  JIANG Yong-Tao  ZHANG Chun-Liang  LIU Qiong
Affiliation:School of Mechanical Engineering;University of South China;Hengyang Hunan 421001;China
Abstract:A new cutting chatter system has been developed according to Hidden Markov Model(HMM) and Support Vector Machine(SVM).This system uses HMM as the recognition method and SVM as the prediction method.Meanwhile,means like wavelet package decomposition are also employed to extract the cutting features.The basic idea and general steps are as follow.Firstly,bootstrapping analyzing the cutting signal in the same interval using wavelet packet decomposition.Secondly,we use SVR algorithm to predict the trend of energ...
Keywords:HMM  SVR
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