铅锌密闭鼓风炉故障诊断知识获取的粗糙集方法  

Knowledge Acquisition Method Based on Rough Set for Fault Diagnosis for Imperial Pb-Zn Smelting Furnace

作　　者：唐朝晖[1] 桂卫华[1] 胡志坤[1] 刘晓颖[1] 

机构地区：[1]中南大学信息科学与工程学院,湖南长沙410083

出　　处：《小型微型计算机系统》2006年第12期2280-2285,共6页Journal of Chinese Computer Systems

基　　金：国家"九七三"计划(2002cb312200)资助.

摘　　要：从粗糙集等价类概念出发,提出从不完整数据集中获取故障诊断知识的密闭鼓风炉故障诊断方法.将不完整数据集的训练事例划分为下近似和上近似两类,首先假设属性的未知特征值为任意可能值,然后根据从训练事例中得到的上下近似进行提炼,最后从事例与近似互相作用以推导出确定的和可能的规则,得出规则概率,并估计出合适的属性的未知特征值.结合密闭鼓风炉悬料规则库的知识获取及其在故障诊断中的应用过程说明了该方法的有效性和实用性.A knowledge acquisition method for incomplete data sets knowledge acquisition is proposed for fault diagnosis of Imperial Pb-Zn Smelting Furnace （ISF） knowledge base based on the concept of equivalence classes of rough set theory. Two kinds of partitions are formed in the training examples of incomplete data sets ：lower approximations and upper approximations. Unknown characteristics are supposed at random,then lower approximations and upper approximations can be computed. At last ,certain rules and uncertain rules with rules probability can be deduced ,and appropriate estimate of unknown characteristics can also be obtained. The knowledge acquisition example of ISP shows its validity and practicability.

关 键 词：知识获取技术 不完整数据集 密闭鼓风炉 粗糙集 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]