基于改进豪斯多夫距离的非参数轮廓变点识别

摘要/Abstract

摘要：

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。

关键词: 非参数轮廓, 变点识别, 豪斯多夫距离, T2统计量

Abstract:

Change point identification in profile monitoring is an important research topic in statistical 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 comparison results of simulation study show that when there exists local changes in nonparametric profile, the modified algorithem has advantages in locating change points and performance stability.

Key words: nonparametric profile, change point identification, Hausdorff distance, T2 statistics

中图分类号:

TH165

聂斌, 孙会东, 李佩, 杜文超 . 基于改进豪斯多夫距离的非参数轮廓变点识别[J]. 中国机械工程, 2015, 26(8): 1029-1034.

Nie Bin, Sun Huidong, Li Pei, Du Wenchao. A Change Point Detection Method Based on Modified Hausdorff Distance in Nonparametric Profiles[J]. China Mechanical Engineering, 2015, 26(8): 1029-1034.

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http://www.cmemo.org.cn/CN/Y2015/V26/I8/1029

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