| SVM模式识别技术及在机械故障诊断中的应用进展 |
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| 引用本文： | 王长林,陈鸿宝,林玮,秦启茂,宋宜梅.SVM模式识别技术及在机械故障诊断中的应用进展[J].桂林电子科技大学学报,2009,29(3):256-259. |
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| 作者姓名： | 王长林 陈鸿宝 林玮 秦启茂 宋宜梅 |
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| 作者单位： | 1. 桂林电子科技大学机电工程学院,广西桂林,541004
2. 广西右江矿务局,广西田东,531501 |
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| 基金项目： | 国家自然科学基金，广西自然科学青年基金 |
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| 摘 要： | 支持向量机(Support Vector Machines,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.为在机械故障诊断中更好地运用该方法,从基于支持向量机理论的模式识别技术和机械故障诊断中应用两方面,综述了近年来支持向量机国内外研究应用现状,分析了技术特点、存在问题、解决方案及其在机械工程领域应用前景.
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| 关 键 词： | 支持向量机 机器学习 模式识别 故障诊断 |
Pattern Recognition Based on Support Vector Machine and Its Application in Fault Diagnosis |
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| WANG Chang-lin,CHEN Hong-bao,LIN Wei,QING Qi-mao,SONG Yi-mei.Pattern Recognition Based on Support Vector Machine and Its Application in Fault Diagnosis[J].Journal of Guilin Institute of Electronic Technology,2009,29(3):256-259. |
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| Authors: | WANG Chang-lin CHEN Hong-bao LIN Wei QING Qi-mao SONG Yi-mei |
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| Affiliation: | 1.School of Mechanical and Electrical Engineering;Guilin University of Electronic Technology;Guilin 541004;China;2.Guangxi Youjiang Bureau of Mines;Tiandong 531501;China |
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| Abstract: | Support vector machine(SVM) is a new general machine learning method based on the Statistical Learning Theory.It exhibits good generalization characteristics when fault samples are few.The recent developments of support vector machine are reviewed and some new progresses in fault diagnosis are introduced.Some key techniques,unsolved problems,and the prospect of engineering applications are discussed in detail. |
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| Keywords: | support vector machine machine learning pattern recognition fault diagnosis |
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