计算机应用 ›› 2012, Vol. 32 ›› Issue (10): 2940-2943.DOI: 10.3724/SP.J.1087.2012.02940

• 典型应用 • 上一篇    下一篇

基于Simulink仿真的质量控制图不确定异常模式识别

侯世旺1,2,朱慧明1,李荣1   

  1. 1. 湖南大学 工商管理学院,长沙 410082
    2. 中北大学 机械工程与自动化学院,太原 030051
  • 收稿日期:2012-04-09 修回日期:2012-05-22 发布日期:2012-10-23 出版日期:2012-10-01
  • 通讯作者: 侯世旺
  • 作者简介:侯世旺(1978-),男,山西太原人,讲师,博士,主要研究方向:工业工程、制造质量控制;朱慧明(1966-),男,湖南湘潭人,教授,博士,主要研究方向:金融工程与风险管理、管理统计与计量经济;李荣(1974-),男,湖南溆浦人,博士研究生,主要研究方向:统计管理。
  • 基金资助:
    中国博士后科学基金资助项目(20100481265)

Simulink-based uncertain abnormal pattern recognition of quality control chart

HOU Shi-wang1,2,ZHU Hui-ming1,LI Rong1   

  1. 1. College of Business Administration, Hunan University, Changsha Hunan 410082, China
    2. School of Mechanical Engineering and Automation, North University of China, Taiyuan Shanxi 030051, China
  • Received:2012-04-09 Revised:2012-05-22 Online:2012-10-23 Published:2012-10-01
  • Contact: HOU Shi-wang

摘要: 当控制图上出现点子临界、点子数接近判异规则规定的数目或多种异常模式并发时,控制图呈现不确定异常状态,常规的方法无法正确完成异常识别。针对趋势模式与周期模式并发的情况,提出了应用小波分解原始信号,选用相应系数重构不同频率的异常信号,并对重构信号进行拟合,以拟合度作为异常模式的特征数,作为模式发生度隶属函数的输入,获取控制图不确定异常模式的发生度,最后在Matlab/Simulink环境下,建立了上述方案的仿真模型,并以具体的应用实例验证了方案的可行性。

关键词: 质量控制图, 不确定异常, 模式识别, Simulink仿真

Abstract: The control chart is in uncertain abnormal state when the plotted-point is close to the critical value, or the number of points is close to the prescriptive target, or there is concurrence of many abnormities. The traditional methods are hard to complete the pattern recognition. Considering the concurrence of trend pattern and cycle pattern, the original control chart signal was decomposed by wavelets. The different abnormal signals were reconstructed with appropriate wavelet coefficients. By curve fitting, the goodness of fit to the reconstruction wavelets was taken as the characteristic number of abnormal pattern. Then the occurrence degrees of uncertain patterns were calculated by inputting the characteristic numbers into membership function of corresponding patterns. The simulation model of this approach was developed under Matlab/Simulik. Finally, an application example was given and the result shows the feasibility of this approach.

Key words: quality control chart, uncertain abnormity, pattern recognition, Simulink simulation

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