| 分级聚类支持向量机在汽轮机故障诊断中的应用 |
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| 引用本文： | 翟永杰,毛继珮,于丽敏,刘长良.分级聚类支持向量机在汽轮机故障诊断中的应用[J].华北电力大学学报,2003,30(6):25-29. |
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| 作者姓名： | 翟永杰 毛继珮 于丽敏 刘长良 |
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| 作者单位： | 1. 华北电力大学,动力工程系,河北,保定,071003
2. 西柏坡发电责任有限公司,河北平山,050400 |
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| 摘 要： | 在两类支持向量机的基础上,综合分级聚类和决策树的思想构造多类支持向量机,从而简化了分类器结构,减少了分类器数量,避免了拒绝分类区的出现,并加快了训练和识别速度。在小样本情况下对多类汽轮发电机组故障进行了诊断研究,结果表明该方法能够正确地对故障进行识别。
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| 关 键 词： | 支持向量机 分级聚类 决策树 故障诊断 汽轮发电机组 |
| 文章编号： | 1007-2691(2003)06-0025-05 |
| 修稿时间： | 2003年4月3日 |
Application of hierarchical clustering support vector machine in turbogenerator fault diagnosis |
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| ZHAI Yong-jie,MAO Ji-pei,YU Li-min,LIU Chang-liang.Application of hierarchical clustering support vector machine in turbogenerator fault diagnosis[J].Journal of North China Electric Power University,2003,30(6):25-29. |
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| Authors: | ZHAI Yong-jie MAO Ji-pei YU Li-min LIU Chang-liang |
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| Abstract: | The basic support vector machine is designed for two-class problem. A new support vector machine based on hierarchical clustering and decision tree is proposed to solve the multi-class recognition problems. The structure is simplified and the rate of tram and identify is expedited. The results indicate that the algorithm is efficient in the fault diagnosis of turbogenerator unit with small samples. |
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| Keywords: | support vector machines hierarchical clustering decision tree fault diagnosis turbogenerator unit |
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