基于邻域粗糙集的转台故障诊断

针对转台的故障类型和特点,设计了基于邻域粗糙集的故障诊断系统。邻域粗糙集以邻域关系代替经典粗糙集的等价关系,通过邻域信息粒子逼近论域空间,可以直接处理数值型属性。提出了一种基于邻域等价关系的混合约简算法,通过计算条件属性的依赖度,对原始决策表进行约简,有效地剔除了系统的冗余属性。在约简决策表的基础提取分类规则,并最终生成分类机。通过对转台故障诊断的实验,验证了该方案的有效性和可行性。

Neighborhood rough set based fault diagnosis for turntable

In view of the charteristics and types of the turntable's fault, a fault diagnosis system based on neighborhood rough set is designed. The neighborhood rough set approximate the domain by neighborhood information granules and can treat the numerical attributes directly. A hybrid reduction algorithm is proposed based on the neighborhood granulation. By calculating the dependence of the condition attributes, the reduction of the raw fault information is obtained, and the inherent redundancy is effectively eliminated. On the base of the reduction, the classifying rules can be extracted and the classifier can be founded. The validity and feasibility of the scheme are demonstrated by the results of experiments based on the fault diagnosis of turntable.