| 支持向量机及其在机械故障诊断中的应用 |
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| 引用本文： | 袁胜发,褚福磊.支持向量机及其在机械故障诊断中的应用[J].振动与冲击,2007,26(11):29-35,58. |
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| 作者姓名： | 袁胜发 褚福磊 |
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| 作者单位： | 1. 清华大学精密仪器与机械学系,北京,100084;江西理工大学机电学院,江西,341000
2. 清华大学精密仪器与机械学系,北京,100084 |
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| 基金项目： | 国家自然科学基金;国家高技术研究发展计划(863计划) |
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| 摘 要： | 支持向量机（SVM）是一种基于统计学习理论的新型机器学习方法,对小样本决策具有较好的学习推广性。对近年来支持向量机的研究进展及其在故障诊断中的应用做了简要介绍,讨论了支持向量机的特点和存在的问题,展望了其在机械故障诊断的研究前景。
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| 关 键 词： | 支持向量机 机械故障诊断 机器学习 智能诊断 |
| 修稿时间： | 2007-01-082007-03-27 |
Support Vector Machines and Its Applications in Machine Fault Diagnosis |
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| Yuan Shengfa,Chu Fulei.Support Vector Machines and Its Applications in Machine Fault Diagnosis[J].Journal of Vibration and Shock,2007,26(11):29-35,58. |
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| Authors: | Yuan Shengfa Chu Fulei |
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| Abstract: | Support vector machines (SVM) is a new general machine-learning tool based on the structural risk minimization principle. It exhibits good generalization when fault samples are few. Research progress on support vector machines and its applications in machise fault diagnosis in recent years are introduced. Characteristics of the SVM and the unsolved problems are discussed. The prospect on the research of SVM in the field of machine fault diagnosis is presented. |
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| Keywords: | support vector machines machine fault diagnostics machine learning intelligent diagnosis |
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