Classifying textile faults with a back-propagation neural network using power spectra

被引：34

作者：

Chen, PW ^{[1
]}

Liang, TC

Yau, HF

Sun, WL

Wang, NC

Lin, HC

Lien, RC

机构：

[1] Natl Cent Univ, Inst Opt Sci, Chungli 320, Taiwan

[2] Natl Kaohsiung Inst Marine Technol, Dept Telecommun Engn, Kaohsiung 811, Taiwan

[3] China Text Inst, Dept Fabr Format, Tu Chen City, Taiwan

来源：

TEXTILE RESEARCH JOURNAL | 1998年 / 68卷 / 02期

关键词：

D O I：

10.1177/004051759806800207

中图分类号：

TB3 [工程材料学]; TS1 [纺织工业、染整工业];

学科分类号：

0805 ; 080502 ; 0821 ;

摘要：

A real-time system designed to detect and classify textile defects is presented. The system starts with an analysis of the optical Fourier transform of sample textiles. We also use a back-propagation neural network to help detect and classify defects. Experimental results show that the system is able to detect and classify nine out of the twelve kinds of defects in its data base.

引用

页码：121 / 126

页数：6

共 5 条

[1]

Freeman J., 1991, NEURAL NETWORKS ALGO, P89

[2]

*MATH WORKS INC, 1995, NEUR NETW TOOLB US M

[3] REAL-TIME FAULT-DETECTION ON TEXTILES USING OPTOELECTRONIC PROCESSING [J].