基于粗糙集的矿井风机故障规则提取  

Extraction Fault Rule of Fans of Coal Based on Rough Set

作　　者：李蒙[1] 柏杏丽[2] 

机构地区：[1]洛阳理工学院,河南洛阳471023 [2]河南工程学院,河南郑州451191

出　　处：《煤矿安全》2009年第9期6-9,共4页Safety in Coal Mines

基　　金：国家安监总局安全生产科技发展计划项目(07-153)

摘　　要：为了提高矿井风机故障诊断的准确率,使用UCI数据库的机械故障分析数据集进行分析。根据矿井风机的特点确定通频垂直振幅、基频垂直振动速率、振动频率是检测矿井风机故障的关键检测参数。因此,提出了采用粗糙集进行矿井风机故障数据挖掘的方法,通过对数据集中数据选择、离散、决策表的构建及约简方法的介绍,以期提取出矿井风机故障诊断的规则,实现矿井风机故障诊断专家系统规则库的建立。In order to improve the accuracy of rotation equipment fault diagnosis, aim at the mechanical failure in the UCI database analyses the characteristics of detection parameter t for the analysis of parameters of of data, of the vertical - frequency amplitude, the frequency rate of vertical vibration, the vibration frequency of rotating equipment failure detection is the key to testing parameters. As a result, the proposed use of rough set for rotation of equipment failure data mining method of data through the data to choose, discrete, decision - making table and build a reduction methods, in order to extract a rotating fault diagnosis rules, the realization of rotating equipment failure diagnosis expert system for the establishment of the rule base.

关 键 词：粗糙集 矿井风机 规则 

分 类 号：TD724.3[矿业工程—矿井通风与安全]