| 基于粗糙集与K-均值聚类的故障知识挖掘 |
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| 引用本文： | 徐袭,祝力,范学鑫.基于粗糙集与K-均值聚类的故障知识挖掘[J].微计算机信息,2007,23(15):141-143. |
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| 作者姓名： | 徐袭 祝力 范学鑫 |
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| 作者单位： | 1. 430033,湖北武汉,海军工程大学电气与信息工程学院
2. 110000,辽宁大连,海军大连地区装备修理监修室 |
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| 摘 要： | 针对连续数据故障诊断知识挖掘,提出了一种将粗糙集理论与K-均值聚类算法相结合的故障诊断知识挖掘方法。该方法在提取设备状态参数数据的基础上,应用K-均值聚类算法将各状态参数下的连续数据离散化为有限类别,再应用粗糙集对所获得的离散数据表进行约简,获得由状态数据出发的故障诊断知识表格。应用于柴油机故障诊断数据知识挖掘,可以快速准确地获得故障诊断知识,方法简单易用。
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| 关 键 词： | 粗糙集 K-均值聚类 故障诊断 知识挖掘 |
| 文章编号： | 1008-0570（2007）05-3-0141-03 |
| 修稿时间： | 2007-03-03 |
Fault Knowledge Ming Based on Rough Set and K-Means Clustering |
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| XU XI,ZHU LI,FAN XUEXIN.Fault Knowledge Ming Based on Rough Set and K-Means Clustering[J].Control & Automation,2007,23(15):141-143. |
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| Authors: | XU XI ZHU LI FAN XUEXIN |
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| Affiliation: | 1 Coll.of Electrical and Information Eng.,Naval Univ. of Engineering,Wuhan 430033,China; 2 Monitor and management office for navy equipment repair in Dalian area,Dalian 110000,China |
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| Abstract: | Method for fault diagnosis knowledge mining of continuous data with rough set and K-means clustering is proposed. It disperses the continuous data of states parameters to some sorts with K-means clustering and then gets the reduction of the discrete data table by rough set. It can obtain the table of fault diagnosis knowledge through the state data. Applied to diesel engine fault diagnosis knowledge mining, it can get the diagnosis knowledge fast and true. It is simple and available. |
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| Keywords: | Rough set K-Means clustering Fault diagnosis Data mining |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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