CAJ | 학술논문

轮廓监控中的变点识别问题是统计过程控制的重要研究内容。以非参数轮廓数据为研究对象，运用图像特征识别的豪斯多夫距离测量了样本轮廓之间的特征差异，设计了改进方法，提出了基于二维空间的改进豪斯多夫距离算法，以识别非参数轮廓变点。大量的仿真与论证表明，改进方法在识别变点位置和稳定性方面具有优异的性能。
륜곽감공중적변점식별문제시통계과정공제적중요연구내용。이비삼수륜곽수거위연구대상，운용도상특정식별적호사다부거리측량료양본륜곽지간적특정차이，설계료개진방법，제출료기우이유공간적개진호사다부거리산법，이식별비삼수륜곽변점。대량적방진여론증표명，개진방법재식별변점위치화은정성방면구유우이적성능。
Change point identification in profile monitoring is an important research topic in statis-tical process control.Herein,the profile had nonparametric characteristics.The proposed method was based on Hausdorff distance,and could be used to measure difference between profiles.A modified Hausdorff distance algorithm was proposed to identify nonparametric profile change point.The com-parison results of simulation study show that when there exists local changes in nonparametric pro-file,the modified algorithem has advantages in locating change points and performance stability.