模糊故障诊断中特征属性约简及其权重系数的确定

针对粗糙集模型在干扰属性约简方面的局限,采用一种基于最大一致性因子的改进模型对故障特征属性进一步约简。为了克服传统方法在确定权重系数的主观性的缺点,应用粗糙集理论对约简后的故障特征属性的重要程度进行判断和权值化处理,并将权值化处理的结果作为权重系数。最后论文通过一实例对相关方法进行了说明。

Characteristic Attribute Reduction and Weighting Coefficient Determination in Fuzzy Fault Diagnosis

The paper discusses the limitations of the existing rough set model for reducing superfluous attributes and uses a superfluous attribute reduction model which is based on the greatest consistency factor so as to reduce the characteristic attributes of faults. In order to overcome the shortcomings of subjectivity that comes from traditional methods, rough set theory is used for calculating the importance of the attributes after reduction and transforming weighted treatment results into weighting coefficients. An example is also used for explaining the validity of the method.