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
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• Conventional Measurement Advice
KAWABATA Evaluation System• Disadvantages
1/123/13
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 Profile3 :Surface Roughness Factor determination4 :Compare Friction Coefficient With Evaluated Surface Roughness Factor
4/13
Simulating Ideal Surface
)/2sin(.)/2sin(0025.0 byaxz
mmA
mmba
0025.0
1
00125.0/2sin(.)/2sin(00125.0 byaxz
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• Mathematically Aspect of an Complete sine Surface
• Adjust the Confine of Amplitude between 0 to 0.0025 mm Rather Than -0.00125 to 0.00125 mm
5/13
Plotting The Simulated Ideal Surface
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6/13
Grayscale Image
•Sample Properties
• Image Acquisition of Sample Surfaces
•Conversion and Processing
Image Processing of Sample Surfaces
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• Plotting the Surface Profile Of Samples
RGB Image
Histogram Equalization Gaussian and Wiener Filtering7/13
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
Id : Dispersion ratio (presented by Pourdeyhimi)
V : Variance of gray scale values of image
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8/13
Definition of Normalized Factors For Compare of Ideal And Sample Surfaces
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s : index of simulated surface
r : index of generated profile from real surface
s
rst T
TTK
s
rse E
EEK
s
rsn N
NNK
s
rs
d
d
dd
I I
IIK
r
rsv V
VVK
9/13
vIetns KKKKKRd
5
1
And Finally : Definition of Surface Roughness Factor
ICSIP 2009, Amsterdam
10/13
Friction Standard Test ASTM D1894
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Determination The Surface Friction Coefficient of Samples
11/13
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Regression Between Surface Roughness Factor (Rs) and Surface Friction Coefficient of Samples
12/13
μ = 1.027 Rs – 0.023 R’
s = 1.027 Rs – 0.023
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
Thanks for your Attention
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