基于粗糙集理论与聚类算法的加工中心可靠性综合评价研究

Research on Comprehensive Reliability Evaluation of Machining Center Based on Rough Set Theory and Clustering Algorithm

针对数控机床可靠性综合评价中指标选取不一、需要大量先验知识等不足,提出一种粗糙集与K-means聚类算法相结合的评价方法。建立原始评价指标体系,通过K-means聚类算法与Silhouetta指标对各指标值进行离散化处理,并运用粗糙集理论约简冗余指标,构造动态评价指标体系。根据属性重要度定义对约简后的指标客观赋权,构建粗糙集聚类可靠性综合评价模型。结果表明:所提出的方法合理、有效。

Aiming at the different index selection and requiring a large amount of prior knowledge in the comprehensive reliability evaluation of CNC machine tools,an evaluation method combining rough set with K-means clustering algorithm was proposed.The original evaluation index system was established,each index was discretized through the K-means clustering algorithm and Silhouetta index,and the rough set theory was used to reduce the redundant index,to construct a dynamic evaluation index system.According to the definition of attribute importance,objective weight was given to the reduced index,a comprehensive reliability evaluation model of rough set-clustering was constructed.The results show that the proposed method is reasonable and effective.