基于粗糙集的柴油机故障数据特征提取
首发时间:2010-08-04
摘要:本文根据柴油机故障数据的特点,采用粗糙集理论对其进行特征提取研究。由于实际测量的参数大多为连续数据,而粗糙集只能处理离散数据,提出了一种适用于粗糙集的SOM网络离散化方法;接着给出一种基于简化差别矩阵的快速属性约简算法;最后以6135D型柴油机故障诊断数据为例进行特征提取,成功地将原始8个属性约简为3个,为后续研究工作打下了基础。
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Feature Extraction Of Diesel Engine Fault Data Based On Rough Set Theory
Abstract:In this paper, we use rough set theory to research how to extract features of diesel engine fault data because of its own character. Rough set can deal with discrete data only and most parameters are continuous, so we present a discretization method which uses SOM for rough set; then we give a quick attribute reduction algorithm based on simplified discernibility matrix; in the end, we extract features of 6135D diesel engine fault data, reduce its attributes from 8 to 3 successfully and lay the foundation of follow-up work.
Keywords: Rough Set SOM Attribute Reduction Feature Extraction
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