| 基于EMD和SVM的刀具故障诊断方法 |
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| 引用本文： | 王涛,徐涛.基于EMD和SVM的刀具故障诊断方法[J].工具技术,2011,45(2):63-67. |
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| 作者姓名： | 王涛 徐涛 |
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| 作者单位： | 沈阳航空航天大学 |
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| 基金项目： | 沈阳市人才专项基金资助项目 |
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| 摘 要： | 为了解决刀具在切削过程中出现的故障,提出了基于经验模态分解(EMD)和支持向量机(SVM)的刀具故障诊断方法.该方法首先将经过标准化的声发射信号进行经验模态分解,将其分解为有限个固有模态函数(IMF)和残余量之和,然后对每个IMF分量通过一定的削减算法增强故障类型特征,计算每个IMF和残余项的能量以及整个信号的削减比作...
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| 关 键 词： | 刀具 声发射 EMD 支持向量机 故障诊断 |
Tool Wear Fault Diagnosis Based on Empirical Mode Decomposition and Support Vector Machines |
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| Wang Tao,Xu Tao.Tool Wear Fault Diagnosis Based on Empirical Mode Decomposition and Support Vector Machines[J].Tool Engineering(The Magazine for Cutting & Measuring Engineering),2011,45(2):63-67. |
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| Authors: | Wang Tao Xu Tao |
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| Affiliation: | Wang Tao,Xu Tao,Postgraduate,Automation Institute of Shenyang Aerospace University,Shenyang 110136,China |
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| Abstract: | To solve the fault diagnosis problem of cutting tool,a fault diagnosis approach based on empirical mode decomposition(EMD) method and support vector machines(SVM) is proposed.Firstly,the EMD method was used to decompose the standard AE signal into a number of intrinsic mode function(IMF) components and a residue component.Secondly,with a certain cutting algorithm,the IMFs with fault character were strengthened.After that,we can extract the energy of each IMF and calculate the average cutting ratio of all th... |
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| Keywords: | EMD |
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