聚类分析在缺陷分类中的应用

The application of cluster analysis in defect classification

为解决超声无损检测中未知类型缺陷的识别分类问题,提出了采用聚类分析的方法,使用ward规则,并根据R2统计量确定最佳聚类数,自动将缺陷数据分类。实验证明该方法能较准确地将实验数据分为适当数量的类。同时系统采用了VC++和MATLAB混合编程的方法,为实时数据采集和聚类分析打下了基础。

Method of cluster analysis is used to solve the identification of defects classification in ultrasonic nondestructive testing even if there is an unknown type of defect, using ward rules, and determine the optimal number of clusters accord- ing to the R2 statistic,in order to classify defect data automatically. Experimental results show that the method can be ac- curate divided experimental data are into appropriate number of classes. The system uses a mixed programming in VC＋ ＋ and MATLAB,and laid the foundation for real-time data acquisition and cluster analysis.