叶大鹏,刘震,张春良.小波包隐Markov模型刀具状态识别研究[J].南华大学学报(自然科学版),2007,21(3):13~15.[.Research on Cutting Status Recognition Based on Wavelet packets and Hidden Markov Model[J].Journal of University of South China(Science and Technology),2007,21(3):13~15.] |
小波包隐Markov模型刀具状态识别研究 |
Research on Cutting Status Recognition Based on Wavelet packets and Hidden Markov Model |
修订日期:2007-07-14 |
DOI: |
中文关键词: 小波 隐Markov模型 切削 状态识别 |
英文关键词:Wavelet Packets,Hidden Markov Model,Cutting,Status Recognition |
基金项目:福建省自然科学基金 |
叶大鹏 刘震 张春良 |
福建农林大学机电工程学院 南华大学机械工程学院 福建福州 福建福州 湖南衡阳 |
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中文摘要: |
针对切削过程中振动信号的特点,利用小波包得到信号能量分布,借助于隐Markov模型(HMM),并以信号的能量分布为特征进行分类,得到一种基于小波包和HMM的切削过程监测新方法.利用实测的钻削振动信号,对该方法进行验证.结果表明该方法能够较有效地识别切削过程刀具的工作状态. |
英文摘要: |
According to the character of vibration signal in the cutting process,a new cutting process monitoring method based on hidden Markov model(HMM) classification and wavelet packets feature extraction is proposed.The method is performed by using the data from drill experiment kit and the result shows that the tool status in the cutting process can be recognized effectively. |
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