Measurement of Nonwoven Surface Roughness With Machine Vision Method Presentation : D. Semnani ICSIP 2009, Amsterdam Isfahan University of Technology

Image Processing in Textile Engineering ICSIP 2009, Amsterdam Online Quality Control of Textiles Detection Of Yarn And Fabric Faults Classification of Products Measuring Uniformity of Fibrous Structures Determination of Woven And Nonwoven Fabrics Surface Roughness 1/13

Spunbond Nonwovens ICSIP 2009, Amsterdam Application & End Use Importance of Surface Friction 2/13

Measurement of Textile Surface Roughness ICSIP 2009, Amsterdam Conventional Measurement Advice K A W A B A T A E v a l u a t i o n S y s t e m Disadvantages 1/12 3/13

Our Method ICSIP 2009, Amsterdam First :Simulate An Ideal Surface Finite element model of human finger Complete and Regular Sine Roughnesses Minimum Sensible Amplitude and Wave Length 2 :Compare of Simulated Ideal Surface with Samples Surface Profile 3 :Surface Roughness Factor determination 4 :Compare Friction Coefficient With Evaluated Surface Roughness Factor 4/13

Simulating Ideal Surface ICSIP 2009, Amsterdam Mathematically Aspect of an Complete sine Surface Adjust the Confine of Amplitude between 0 to mm Rather Than to mm 5/13

Plotting The Simulated Ideal Surface ICSIP 2009, Amsterdam 6/13

Grayscale Image Sample Properties Image Acquisition of Sample Surfaces Conversion and Processing Image Processing of Sample Surfaces ICSIP 2009, Amsterdam Plotting the Surface Profile Of Samples RGB Image Histogram Equalization Gaussian and Wiener Filtering 7/13

Extracted Parameters From Preprocessed Sample Images and Simulated ideal Surface N : Number of picks in the surface T : Variance of distance between picks from point (0,0) in image matrices E : Volume of surface profile I d : Dispersion ratio (presented by Pourdeyhimi) V : Variance of gray scale values of image ICSIP 2009, Amsterdam 8/13

Definition of Normalized Factors For Compare of Ideal And Sample Surfaces ICSIP 2009, Amsterdam s : index of simulated surface r : index of generated profile from real surface 9/13

And Finally : Definition of Surface Roughness Factor ICSIP 2009, Amsterdam 10/13

Friction Standard Test ASTM D1894 ICSIP 2009, Amsterdam Determination The Surface Friction Coefficient of Samples 11/13

ICSIP 2009, Amsterdam Regression Between Surface Roughness Factor (R s ) and Surface Friction Coefficient of Samples 12/13 μ = R s – R ’ s = R s – New Roughness Factor with effect of friction

Final Conclusion Advantages of This Method Present an appropriate roughness factor which originally implies both elements of roughness : 1.Point by point consideration of surface roughness height compare with line by line height measurement in KES 2. Consideration of fabric surface friction in roughness factor determination ICSIP 2009, Amsterdam

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