| 基于RS和SVM的汽轮机组故障诊断方法 |
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| 引用本文： | 盛步云,周育洋.基于RS和SVM的汽轮机组故障诊断方法[J].武汉理工大学学报,2010(6). |
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| 作者姓名： | 盛步云 周育洋 |
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| 作者单位： | 武汉理工大学机电工程学院; |
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| 基金项目： | 国家自然科学基金重大国际合作项目(50620130441); 武汉市科技攻关项目(200810321153); 武汉市青年科技晨光计划项目(200750731289) |
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| 摘 要： | 为了提高汽轮机组故障诊断的效率,设计并实现了基于粗糙集和多类支持向量机的融合算法。把粗糙集作为数据的前处理器,对条件属性进行知识约简和去除冗余属性以达到降低数据维数的目的。然后构造多类支持向量机分类器并用约简后的新样本数据训练。测试结果表明,基于粗糙集和支持向量机融合算法的故障诊断方法诊断速度快,推广能力强。
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| 关 键 词： | 粗糙集 支持向量机 数据融合 汽轮机组 故障诊断 |
Fault Diagnosis of Steam Turbine Units Based on Rough Sets and Support Vector Machine |
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| SHENG Bu-yun,ZHOU Yu-yang.Fault Diagnosis of Steam Turbine Units Based on Rough Sets and Support Vector Machine[J].Journal of Wuhan University of Technology,2010(6). |
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| Authors: | SHENG Bu-yun ZHOU Yu-yang |
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| Affiliation: | SHENG Bu-yun,ZHOU Yu-yang(School of Mechanical , Electronic Engineering,Wuhan University of Technology,Wuhan 430070,China) |
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| Abstract: | In order to raise the efficiency of fault diagnosis of steam turbine units,a data fusion algorithm based on rough sets theory and support vector machine is developed and implemented.In this algorithm,the rough sets is used as data pre-processor,knowledge reduction of condition attribute and removal of redundant data attribute have reached the target of lowering the data dimension.Multi-class support vector machine classifier is constructed and trained with reduced sample data.Test results show that the faul... |
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| Keywords: | rough sets support vector machine data fusion steam turbine units fault diagnosis |
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