Adhesion, Roughness and Friction Characterization on Time-Dependant
Materials : Example with Fibrous Structures
Dr. Stéphane Fontaine, Cyril Marsiquet (PhD) and Pr. Marc Renner
Ecole Nationale Supérieure des Industries Textiles de Mulhouse, University of Mulhouse, France
Abstract
The surface states of fibrous structures have to be precisely characterized in order to answer to commercial
(softness of fabrics for example) and technical reasons (bio-compatibility of artery prosthesis that are polyester
made). This need induces the necessity to understand the tribologic phenomena that occur on these timedependant surfaces and then, to develop characterization methods that are able to identify special physical
parameters that quantify these phenomena. There is a wide range of fibrous structures. Their properties depend
on materials and process to made them. This study proposes an experimental approach to characterize adhesion,
roughness, compressibility of asperities on different kind of surfaces like traditional garment textiles and nonwoven surfaces. Classical textile methods have been used to estimate the previous parameters : Kawabata
Evaluation System for Fabrics (KES-F) ; and methods that have been developed in our lab : an optical pilemeter
and a multidirectional tribometer. The studied fibrous structures are made with cotton, polyester (traditional fibers
and micro-fibers), polypropylene, cashmere and wool. Moreover, some of these surfaces have been sanded
(abrasive process) in our lab. As this last process induces the apparition of fine hairiness on the fibrous structures,
the obtained fine modifications will be explained and quantified.
1. Background
In several technical applications, it is necessary to determine precisely the surface state of materials. In order to
do so, several methods can be used. These methods depend on the type of surfaces to be analysed. Surfaces
and products include different levels of structures issuing from various manufacturing processes. Further, they are
composed of different materials. This variety of surface types induces high complexity when wanting to
characterise and compare them.
The main problem is to be sensitive enough to measure very fine differences that influence the surface state. This
challenge induces the study of large zones on which a tribologic phenomenon like roughness can occur at very
different scales (from 1µm to several millimeters) in all directions. Then usual characterizations of surface state
are rapidly out of range.
Moreover, surface state depends on both roughness and friction properties which are interacting together.
Savkoor [1] relates the link between surface states, friction, roughness and topographies. Relating several studies
on adhesion and friction, the author reports that mechanical friction is strongly linked to micro-asperities whereas
adhesion depends on thin contaminant films that pollute surfaces. Moreover, it is very important to define the
scale of the asperities that are observed. Thus, when studying different kinds of surfaces, macro, meso and micro
scales of asperities have to be studied. Since these different scales are linked, measurements methods have to
be multi-scales sensitive.
Textiles are products issued from fibers that are natural or man-made ones. In one hand, fibers can be
transformed into yarns to give woven or knitted fabrics or, in other hand, fibers can be used directly to produce
non-woven fabrics. In the two cases, fabrics surfaces have to be considered in the three dimensions of the space
were transversal compressibility, roughness and adhesion behaviors are hardly linked. Then, textiles are very
complex time-dependant structure and are constituted of fibers that are very complex time-dependant,
heterogeneous and anisotropic materials.
The present study presents a measurement approach which provides solutions to the previous problems.
2. Measurement methods
The KES-F method [2] is a reference method for the textile industry. This method consists on measurements of
textiles responses under very small mechanical solicitations. Hence, the mechanical behaviors are evaluated
owing to 4 measurements apparatuses (KES-F1 to KES-F4). Then, tensile, shear, bending, transversal
compressibility, roughness and friction behaviors can be measured. During this study, only 3 parameters were
measured : Roughness (Ra), friction (µ) and transversal compressibility (C).
Roughness
measurement
Friction
measurement
Fig 2-1 : KES-FB4 tester - friction and roughness measurement
Fig 2-2 : KES-FB3 tester - transversal
compressibility measurements
0,01
0,008
0,006
Displacement (mm)
0,004
0,002
50
0
-0,002
-0,004
-0,006
Force (cN)
-0,008
-0,01
Time (s)
-0,012
0
5
10
15
20
0,35
Friction coeficient (µ)
0,3
0,25
0
0,2
Tm
0,15
Thickness (mm)
0,1
0,05
Time (s)
0
0
5
10
15
Fig 2-3 : KES-FB4 tester – measurement cycle
20
Fig 2-4 : KES-FB3 tester – measurement cycle
During a roughness test, the sample is stretched and a cylindrical probe (0.5 mm of diameter) measures the
roughness of the sample in both production wise and its perpendicular wise. An average is made between the Ra
measured in the both directions.
On the same sample and simultaneously, friction behavior is measured owing to the sensor showed on figure 2-1
under a normal load of 50 cN for a apparent contact area of 25 cm².
During a compressibility test, (fig 2-2 and 2-4), a 2cm² probe (planar contact) penetrates the surface until an
indentation force of 50 cN (ascending phase). Then, the probe comes back to a null indentation force (descending
phase). During this measurement, the compressibility of the sample is estimated as following :
C=
T −T
0
m
50cN − 0,5cN
Where
(mm/cN)
(1)
T0 is the thickness of the sample under a load of 0,5 cN (ascending phase of the test) and Tm is the
thickness of the sample under a load of 50 cN.
2.1 “ModalSens” Method [3,4]
During the measurement (fig 2-5 and 2-6), the sample is clamped on a rotating carrier and a pre-stressed blade
(50 µm thin) rubs on the tested surface. During the contact, the blade vibrates according to eigen values of
frequencies. Strain gauges are fixed on this blade and measure its vibrations (vibrating modes).
Clamp
Sensor - vibrating blade
Sample
Rotative carrier
Fig 2-5 : measurement principle
Fig 2-6 : photograph of a sensor
A Fourier analysis of the temporal signal from the sensor entails the computing of the power spectrum relative to
frequency with the help of a spectrum analyzer Bruël & Kjaër. The power spectrum is PS (f) :
PS ( f ) = X ( f )
2
(2)
+∞
Where
X(f ) =
∫ f (t ) exp(−2iπf ⋅ t )dt
(3)
−∞
Where f is the frequency (Hz) and X (f) is the Fourier transform of the temporal signal x(t), which corresponds to
the output signal of the sensor.
The power spectrum relative to frequency gives a spectrum as well as an average of several spectra, called
autospectrum. This autospectrum is computed during several revolutions of the sample carrier and show several
frequency peaks. These frequency peaks correspond to vibration modes of the sensor. The energy of these
peaks are extracted (equation 3) by integration of PS(f) between two frequencies f1 and f2 (gray zone on figure 27).
Energy[ f1 ; f 2 ] =
f2
∫ X(f )
f1
2
df
(4)
It is then clear that for a given mode, the higher is the excitation, the higher is the energy of the vibration in this
mode. The challenge is then to link data coming from the different vibration modes to the characteristics of the
tested surface.
In order to complete the signal analysis, the signal has been analysed in a “time – frequency” domain [3] where
the short-time Fourier transform (STFT) is used to observe the evolution of the spectra along the time. The STFT
of a signal is defined as following :
STFT (τ , w) = ∫ f (t ) ⋅ g (t − τ ) exp(−iwt )dt
(5)
Where g(t) is a window function that determines the time duration of the observation.
300
mode 1 (36 Hz)
150
100
50
0
mode 3 (260 Hz)
12
200
Magnitude (mV2/Hz)
Magnitude (mV2/Hz)
250
15
115
Frequency (Hz)
8
mode 4 (470 Hz)
4 mode 2
(128 Hz)
0
100 200 300 400 500
Frequency (Hz)
Fig 2-7: autospectrum analysis
3. Experimental
In order to separate the different phenomena (roughness, compressibility and adherence), different kinds of
surfaces such as nonwovens, woven and knitted fabrics and a sheet of paper have been studied. Their
description are available in the table 3– 1.
Name of the Surface
Plain weave fabric TJ
Nonwoven J1
Nonwoven NT-R
Nonwoven glass fibers
Velvet fabric
Twill cotton fabric
Plain cotton fabric
Structure
Material
Plain weave
Nonwoven
Nonwoven
Nonwoven
Velvet
Twill
Plain weave
unknown
PET
unknown
Glass
unknown
Cotton
Cotton
Name of the Surface
Structure
Twill µ-fibers PET
Twill
Sheet of paper
Cellulose
Plain cashmere fabric-1 Plain weave
Twill cashmere fabric-2
Twill
Twill cashmere fabric-3
Twill
Twill cashmere fabric-4
Twill
Twill cashmere fabric-5
Twill
Material
PET Micro
Cellulose
Cashmere
Cashmere
Cashmere
Cashmere
Cashmere
Table 3-1 : Surfaces characteristics
Parameters like friction (µ), roughness (Ra) and compressibility (C), have been estimated with the Kawabata
Evaluation’s System for fabrics (KES FB3,4). The samples have been also measured on the “blade – disk”
tribometer.
4. Experimental results
First, the results (fig 4-1 and 4-2) show that the surfaces can be easily discriminated and that classes of surfaces
naturally appear : ( classes 1,2,3 on fig 4-1). Second, we will show, during the communication, that some links can
be established between the informations given by the vibrational energies of the modes and the measured
parameters on KES apparels (µ, Ra, H). Moreover, we will point out that considering friction and roughness as
separated parameters on textiles cannot characterize those time-dependant surfaces in a good way.
30
Plain weave fabric TJ
2
Nonwoven PET fibers
80
Nonwoven glass fibers
20
Energy of Mode 3 (µV²)
Energy of Mode 3 (µV²)
Twill cotton fabric
3
Nonwoven NT-R
1
10
Velvet fabric
0
60
Plain weave - cotton
1000
2000
3000
4000
Plain weave cashmere 1
Twill PET
20
Twill cashmere fabrics
Paper
0
0
0
500
Energy of Mode 1 (µV²)
Fig 4-1 : Cross representation - mode 3 =f (mode 1)
Velvet fabric
40
1000
1500
2000
Energy of Mode 1 (µV²)
Fig 4-2 : Cross representation - mode 3 =f (mode 1) (Zoom)
5. Conclusions
Textiles are very complex time dependant structures and surface characterization need adapted approaches. This
paper present adhesion, roughness and compressibility behaviors on fibrous structures. These results have been
obtained owing to reference apparatuses (Kawabata Evaluation System for Fabrics) and owing to the
"ModalSens" method developed in our lab. This work purpose is to show how textile surfaces have to be
considered in terms of roughness and friction, linked with their compressibility.
6. References.
1. SAVKOOR R.A., “Advances in Polymer Science Friction and Wear”, Edition : Polymer Science and
Technology, Vol 5A, 1974.
2. Kawabata S., “The standardization and analysis of hand evaluation, 2
nd
ed., The Textile Machinery Society of
Japan, Osaka (Japan), 1980.
3. Bueno Marie-Ange, Fontaine Stéphane, Renner Marc (June 2000), Dispositif pour évaluer l’état de surface
d’un matériau et procédé de mise en œuvre du dit dispositif, French Patent Brevet N° BR 17695/FR, 2000.
US Patent N° 6,810,744, 2004, international extension continued.
4. FONTAINE S., MARSIQUET C., NICOLETTI N., RENNER M., BUENO M.A., "Development of a sensor for
surface state measurements using experimental and numerical analysis", Sensors and Actuators : A Physical,
120, 507-517, mars 2005.