基于粗糙集的矿井风机故障规则提取

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。

Extraction Fault Rule of Fans of Coal Based on Rough Set

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 t...