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中文摘要：
借助粗糙集理论中的动态层次聚类的连续属性离散化算法和属性约简算法,对金属矿主通风机各类特征信息在线监测的数据进行融合,去除风机故障诊断决策表中的冗余和不一致信息,分析并推导出导致风机故障各因素的内在联系,找出关键因素和非关键因素,最终提取出故障诊断规则。研究结果表明：该故障故障方法能够对金属矿主通风机故障做出快速准确的诊断,并且在某矿山的实际应用中取得了良好的效果,达到了预期的目标。
英文摘要：
By virtue of discretization of continuous features and attribute reduction algorithm,online monitoring data were integrated for various feature information concerning the main ventilator of metal mine,and the redundant and inconsistent information in the ventilator fault decision table was deleted.The internal relationship among various factors leading to ventilator breakdown was analyzed.Key factors and non-key factors were distinguished from each other for the convenience of fault decision rules.The results show that the rules can be applied for quick and proper decision of main ventilator faults in metal mine.The application in a certain metal mine has produced satisfactory result,achieving intended target.
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