Paper Title:

Simultaneous Process Mean and Variance Monitoring Using Wavelet Transform and Probabilistic Neural Network

Periodical Applied Mechanics and Materials (Volumes 157 - 158)
Main Theme Mechatronics and Applied Mechanics
Edited by Jing Guo
Pages 11-15
DOI 10.4028/www.scientific.net/AMM.157-158.11
Citation Shao Xiong Wu, 2012, Applied Mechanics and Materials, 157-158, 11
Online since February, 2012
Authors Shao Xiong Wu
Keywords Control Chart, Pattern Recognition, Probabilistic Neural Network, Statistical Process Control (SPC), Wavelet Transform (WT)
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Abstract

A real-time WPNN-based model was present for the simultaneous recognition of both mean and variance CCPs. In the modeling of structure for patterns recognition, the combined wavelet transform with probabilistic neural network (WPNN) was proposed. Input data was decomposed by wavelet transform into several detail coefficients and approximations. The approximation obtained and energy of every lever detail coefficients was for the input of PNN. The simulation results shows that it can recognize each pattern of the mean and variance CCPs accurately, which can be used in simultaneous process mean and variance monitoring.