Fabric Defect Detection Technique Based on Two-double Neural Network

This paper introduces the identification of the defects on the fabric by using two-double neural network and wavelet analysis. The purpose is to fit for the automatic cloth inspection system and to avoid the disadvantages of traditional human inspection. Firstly, training the normal fabric to acquire its characteristics and then using the BP neural network to tell the normal fabric apart from the one with defects. Secondly, doing the two-dimeusional discrete wavelet transformation based on the image of the defects, then wiping off the proper characteristics of the fabric, and identifying the defects utilizing the trained BP neural network. It is proved that this method is of high speed and accuracy. It comes up to the requirement of automatic cloth inspection.     

竹节纱横截面应力的有限元分析

在建立竹节纱线横截面受力数学模型的基础上,根据内力平衡条件,对竹节纱轴向上任意截取的一个横截面的应力情况进行理论分析、计算,得到了极坐标下竹节纱弹性体内应力平衡微分方程以及纤维位移与应变微分方程组;以基纱号数48.6 tex、体积质量0.75 g/cm3精梳棉纱为讨论对象,通过有限元分析软件ANSYS10.0,模拟加捻时纤维转移所引起的应力变化情况,理论上解释竹节纱加捻时应力的变化规律;采用有限元法,并结合计算机模拟,从理论角度证明了纤维在不同层的位移产生的应变由外向内递减的结论.     

The Application of Neural Network in Recognition of Fabric Weave Parameters

IntroductionFabricweaveparametersaretheimportantcharactersoffabricweave.Todistinguishastructureoffabricweave,threeproblemshavetobesolved.Oneistofindthepositionofinterlacingpoint,anotheristodeterminethepropertyofinterlacingpoint,andthethirdistodistinguishthenameofinterlacingpoint.Inthisstudy,themethodofidentifyingfabricweaveparametersisbasedonthefollowingthreeassumptions:1)Thepositionofweftinfabricisdeterminedbypeakandvalebrightnessprojectioncurveinthedirectionofwarp;2)Thechangeinweftsbrightne…