Recognition of control chart patterns using multi-resolution wavelets analysis and neural networks

被引:42
作者
Al-Assaf, Y [1 ]
机构
[1] Amer Univ Sharjah, Sharjah, U Arab Emirates
关键词
control charts; multi-resolution wavelet analysis; neural networks; statistical process control;
D O I
10.1016/j.cie.2004.02.007
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Control charts pattern recognition is one of the most important tools in statistical process control to identify process problems. Unnatural patterns exhibited by such charts can be associated with certain assignable causes affecting the process. In this paper, multi-resolution wavelets analysis (MRWA) is used to extract distinct features for unnatural patterns by providing distinct time-frequency coefficients. A reduced set of parameters is derived from these coefficients and used as input to an artificial neural network (ANN) classifier. Results show that the performance of the proposed technique in classifying shift, trend and cyclic patterns is superior to that of ANN classifier, which operated on coded observed data. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码:17 / 29
页数:13
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