# An Effective On-line Polymer Characterization Technique by Using SALS Image Processing Software and Wavelet Analysis

Authors: Guang-ming Xian; Jin-ping Qu; Bi-qing Zeng
Journal: Journal of Automated Methods and Management in Chemistry
 (2008)

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## Abstract

This paper describes an effective on-line polymer characterization technique by using small-angle light-scattering (SALS) image processing software and wavelet analysis. The phenomenon of small-angle light scattering has been applied to give information about transparent structures on morphology. Real-time visualization of various scattered light image and light intensity matrices is performed by the optical image real-time processing software for SALS. The software can measure the signal intensity of light scattering images, draw the frequency-intensity curves and the amplitude-intensity curves to indicate the variation of the intensity of scattered light in different processing conditions, and estimate the parameters. The current study utilizes a one-dimensional wavelet to delete noise from the original SALS signal and estimate the variation trend of maximum intensity area of the scattered light. So, the system brought the qualitative analysis of the structural information of transparent film success.


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## Body

## 1. Introduction

Small-angle light scattering (SALS)
techniques offer a number of advantages for the investigation of the nature and
behavior of polymer materials. Nonintrusive characterization of the
flow field of transparent film
is an essential step toward an implementation of a structural control system
that can regulate the structure development during processing.A combination of in situ
birefringence and depolarized light-scattering experiments was used to study
the formation of an ordered cylindrical microstructure in a
polystyrene-block-polyisoprene copolymer melt under a shear flow field [1]. A new multivariable measurement
approach [2] for
characterizing and correlating the nanoscale and microscale morphology of
crystal-amorphous polymer blends with melt-phase behavior is described. A
vertical small-angle light scattering
instrument optimized for examining the scattering and light transmitted
from structures ranging from 0.5 to 50μm, thereby spanning the size range
characteristic of the initial-to-late stages of thermal-phase transitions
(e.g., melt-phase separation and crystallization) in crystal-amorphous polymer
blends, was constructed. The present paper explores an
effective means of characterizing structural changes of
poly(vinyl chloride) (PVC) particles during gelation and fusion of PVC
plastisols with small-angle light scattering. The SALS method was shown to
provide an in situ observation of swelling of PVC particles as well as
quantitative information of average size of swollen particles while they are in
progress of gelation and fusion. In addition, the SALS method enabled one to
evaluate the relative solvent power of plasticizers from the manner of increase
in the correlation distances [3].Recently, there has been increasing interest in understanding
the complex processes that take place during the processing of polymer blends [4–6]. For this purpose, the small-angle
light scattering technique is a very efficient method [7–9]. One of the important
characteristics of light scattering is that it is a nondestructive test. This makes
it possible to
follow the time evolution of the phase separation process. The scattering pattern
is a direct reflection of
orientation, shape, and size of the structure. Another advantage is that with
an appropriate choice of instruments, one can follow extremely fast events having
a low optical contrast [10, 11].For optimum mechanical and optical
properties,  fine-structured
morphologies on a submicron scale are generally desired, as  fine dispersions or
cocontinuous morphologies with a low volume fraction of one component [12].The light
scattering method is valid for giving information about overall structures but
is difficult to use for extracting local information on morphology. Recently, a
digital image processing technique has shown its utility in analyzing the
pattern formation in polymer systems [13]. Small angle light scattering study provides information on changes
of morphology [14]. Various light scattering and optical techniques have been investigated as potential candidates for characterization of
multiphase polymeric materials [15]. SALS is one of the tools that can be used to
study a phase separation. It is shown that SALS can be used to discriminate
between nucleation and growth (NG) and spinodal decomposition (SD) even when
both give a pattern composed of a ring [16]. The gelation mode as a function of
time was analyzed
for polymers and polymer-carbon fiber composites by using polarized microscopy
and polarized light scattering in terms of the formation of polymer spherulites [17]. Endoh et al. [18] aimed at elucidating the influence of shear-induced
structures (shear-enhanced concentration fluctuations and/or shear-induced
phase separation), as observed by rheo-optical methods with small-angle light
scattering  under shear flow (shear-SALS) and shear-microscopy, on viscoelastic
properties in semidilute polystyrene (PS) solutions of 6.0 wt% concentration
using dioctyl phthalate (DOP) as a Θ solvent and tricresyl phosphate (TCP) as a
good solvent. Small-angle
light scattering was used to determine the binary interaction parameter in a
molten blend of linear polyethylene (LPE) (Mw  =  52 kg/mol, PDI  =  2.9) and linear
low-density polyethylenes (LLDPEs) based on homogeneous ethylene-1-butene
copolymers (LLDPE-1, 18.7 mol% butane branches, Mw  =  58.1 kg/mol, and LLDPE-2, 5.9 mol% butene branches, Mw  =  70 kg/mol). Our results
are significant because they show that the low optical contrast between
coexisting phases in polyolefin blends does not limit the determination of
phase boundaries by SALS as was previously assumed. The blends studied exhibit
upper critical solution temperature behavior [19].The quantitative analysis software system can be integrated
into the picture archiving and communication system [20]. The combination of advances in charge-coupled-device
(CCD) fabrication, camera design, digital interface technology, and software
development has enabled scientific imaging device manufacturers to overcome the
challenges created by the wide range of requirements [21]. The software kits, which include
PCI device driver and image processing package, are developed based on Windows
OS [22].In our study, the transparent film
is viewed through crossed polarizers to reveal the light scattering pattern. A
high-speed CCD camera is used to record the SALS signal in real time with different process conditions for
subsequent analysis. Modification algorithm has been proposed to eliminate the
noise of multiple scattering. An optical image real-time analysis software has
been developed for accurate modeling and simulation of the structural
information of the transparent film. Visualization is performed via a
high-performance analysis software which allows on-line data acquisition and
processing the SALS signal. The experiments yield information regarding the
trend of the maximum light intensity of the transparent film that can be compared under different processing
conditions.Wavelets have been used successfully in numerous applications ranging
from analysis of flotation froth to countertops [23, 24]. Lambert et al.  aims at
developing a more accurate measurement of the physical parameters of fractal
dimension, and the size distribution of large fractal aggregates by small-angle
light scattering. The theory of multiple scattering has been of particular
interest in the case of fractal [25]. Ismail et al. outline how the wavelet transform, a hierarchical
averaging scheme, can be used to perform both spatial and topological
coarse-graining n systems with multiscale physical behavior,
such as Ising lattices and polymer models [26].  A brief description is  given of
a methodology that exploits guided ultrasonic waves, lasers and  fiber optics, and
simultaneous time-frequency analysis to interrogate the state of a material,
component, or structure. The propagating ultrasound interrogates the host
material in a manner providing a wealth of information when coupled with
application of the Gabor wavelet transform to broadband dispersive waveforms. Recent
results are presented pertaining to delamination detection within layered
copper/polymer films [27].Wavelet analysis (WA) is typically
suited in applications where data contains both large and small scales of
variation, such as small-angle light signal. We presented
a new technique
that can be
used to analyze the
structural information of transparent film
on-line and nonintrusively while
the material is
processing. The technique is
based on SALS,
optical signal real-time analysis software,
and wavelet transform
method. It is shown that the
proposed technique is easy to implement and provides more flexibility, approximating the relation between the intensity signal and the corresponding
variation time. Applying this
method to analyze
structural information of transparent
film will be of
great interest, since it will
contribute information on optical prosperities that have been proven
to be useful
for obtaining deep insights into the molecular and structural
parameters of transparent
film. In our experiments, theSALS signal denoisedby wavelet analysis is
better than the signal denoised
by inducingKf factor. The variation trend of the SALS signal becomes clear, and
the exceptional SALS signal can be accurately detected by wavelet
decomposition [28].In this paper, the results from a measurement technique are investigated.
The method will be evaluated on the basis of light scattering measurements for
a small range of scattering angles. These measurements have been taken with a
fast CCD line scan camera and appropriate optics. An attempt is made to derive
information from these measurements only. With the continuous wavelet transform, SALS image
analysis methods are used to process the SALS signal.
The purpose of the
present work is to apply the optical image technique to characterize the structural
informal of transparent
film. In particular, we attempt
to on-line the analysis of
the light intensity signal.


## 2. Theoretical background for SALS

When  a light beam passes through a diffusion surface, the
variation of propagation direction of the beam cannot be determined by the
principle of geometrical optics because of scattering function of light beams
on diffusion surface [29].A transparent fluid is an optical phase object. In the
experimental set-up for measuring flow fields in fluid flows by using speckle
interferometry, the part of the arrangement for the object light beam is just
like a subjective photographic system. Therefore, in general, speckle
displacements are generated. The speckle displacements can change the intensity
distribution of spatial speckle fields. As a result, the intensity distribution
of a speckle interferogram is also changed. In this paper, the effect of
variation of the intensity is analyzed and discussed in detail. Experimental
results are shown. Methods for elimination of the multiple scattering effect
are provided. This is advantageous to improve the quality of the speckle
interferogram [30].In our experiments, device performs real-time image
analysis of the evolving light scattering signal. The experimental device
incorporates an He-Ne laser generator, optics, a CCD camera, and a personal
computer as its major hardware components. Software designed specifically for
this application performs real-time analysis of the light scattering pattern.
Intensities at various scattering and azimuthal angles are plotted at each time
[31].Figure1 shows an experimental set-up for small-angle light-scattering
measurement device. A laser light passes through polymer melts
in the visual slit dies. A polarizer and an analyzer are
placed before and after the polymer melts.  The laser light first passes the
polarizer, which removes one orthogonal component of the light [32]. The other component of light
passes through the polymer melts with resulting scattering due to the
orientation of molecular chain. The analyzer removes the second component since
it is placed 90° out of phase with respect to the analyzer.
Therefore, any light that comes out of the analyzer is entirely due to the
scattering within the polymer melts. The depolarized intensity of light that
passes through the polarizer, polymer melts, and analyzer is recorded and related to
the orientation of polymer melts. A CCD camera captures the image, and the total intensity
of the image is determined in every 5 seconds. The total intensity is assumed
proportional to orientation of molecular chain.Figure 1
Experimental device for SALS.We assume that each column of the following matrix represents
the intensities of one observed Raman spectrum at the selected wave shifts:(1)D=[d1,1d1,2⋯d1,nd2,1d2,2⋯d2,n⋯⋯⋯⋯dm,1dm,2⋯dm,n],D∈Rmxm.Therefore,  each spectrum is
represented by (m) number of spectral intensities, and a total of (n)
spectrum exists.
The dispersion matrix Z [32] that represents the variation in the
data is computed as (2)Z=DTD,Z∈Rmxm.The diagram of multiple scattering is shown in Figure2. According to the effect of the
sample on the incident light, the sample can be divided into a surface layer, a
first scattering layer, a second scattering layer, and so forth. The incident
light first impinges on the surface of the sample of the first scattering layer (random reflection)
of the medium. The second one comes from the first scattering layer (because of
the internal heterogeneity) and the third in turn [33].Figure 2
Diagram of multiple scattering.The sketch of incidence beam with litter angle is shown in Figure3. Here, α is the angle of incident light, and d is the thickness of the sample.Figure 3
The sketch of incidence beam with
litter angle.Because of multiple light scattering
caused by the thickness of the sample, the light scattering images will be dispersion and distortion
models. A distortion model is constructed, and a correcting factor is
introduced. Computer simulation is verified under some factual circumstance. Introducing the
correcting factor improves the precision and the reliability of the image.The measurable intensity of scattered
lightIs′ and the factual intensity of scattered light Is have the relationship  (3)Is=KfIs′,where Kf is the correcting factor that can be written
as  (4)Kf=e(τd/cosφ)τd(cos−1φ−1){e[τd(cos−1φ−1)−1]}−1,where φ is the scattering angle, and τ is the turbidity of the sample [34]. In a specific point, φ is a constant.Supposedτ (the turbidity of the sample) is the same, so
correcting factor Kf is only with relation to d (the thickness of the transparent film).


## 3. Wavelet analysis for multiple
scattering SALS signal

Spectral analysis and time series
methods are the most commonly used signal processing techniques. However, these
methods were reported to provide a good solution only in the frequency domain
and poor solution in the time domain. Like the Fourier transform (FT), the wavelet transform
(WT) can be used to measure the frequency content of a signal. However, the WT differs from
the FT in that it yields frequency
information in a time-localized fashion [35, 36]. This makes the WT far more effective
than FT in identifying time-based phenomena.Given a
time varying signalf(t), WTs
consist of computed coefficients of
inner products of the signal and a family of wavelets. In a continuous wavelet
transform (CWT), the wavelet corresponding to scale (a) and time
location (b) is (5)ψa,b=1|a|ψ(t−ba),a,b∈R,a≠0,   where (a)
and (b) are the dilation and translation parameters, respectively. The
CWT is defined as follows: (6)CWT{x(t);a,b}=∫x(t)ψa,b*(t)dt,   where * denotes the complex conjugation. In this
paper, Morlet
wavelet function [37] was used, which can be represented as (7)ψ(t)=e−t2/2ejw0t.Its CWT is(8)ψa,b=1ae−1/2((t−b)/a)2ejw0((t−b)/a).In (8), (a) and (w0) can be changed, each way yields
a different type
of WT. The sample frequency of the wavelet function and the signal is (fw) and (fs), respectively; the relationship
of the parameter a and w0 is (9)a=w0fs2πfwf0,   where (f0) is the frequency focused signal
energy.Whena=2j,b=k2j,j,k∈Z, the WT becomes (10)ψj,k=2−j/2ψ(2−jt−k).The discrete wavelet transform (DWT) is defined as(11)cj,k=∫f(t)ψj,k*(t),   where (cj,k) is a time frequency map of the original
signal f(t).A multiresolution analysis approach is used in this work, in which(12)ϕj,k=2−j/2ϕ(t−2jk2j),dj,k=∫f(t)ϕj,k*(t),   where (ϕj,k) is a discrete scaling function, and (dj,k) is a scaling coefficient.
When j=0,ϕj,k is the  sampled version of the original signal.
The DWT computes wavelet coefficients cj,k for j=1,…,J, and
scaling coefficients dj,k are given by (13)cj,k=∑nx[n]hj[n−2jk],dj,k=∑nx[n]gj[n−2jk],   where x[n] are discrete time signals, hj[n−2jk] are the discrete wavelets, the discrete equivalents
to 2−j/2ψ(2−j(t−2jk)),gj[n−2jk] are called scaling sequence.At each resolutionj>0, the
scaling coefficients and
the wavelet coefficients are (14)cj+1,k=∑ng[n−2k]dj,k,dj+1,k=∑nh[n−2k]dj,k.From a mathematical point of view, the structure of computations in a
DWT is exactly an octave-band  filter band [38].
The terms (g) and (h) are high-pass and low-pass filters derived
from the analysis wavelet ψ(t) and the scaling function ϕ(t). Hence, cj,k represents the high-frequency components of
the signal f(t) [39].


## 4. Experimental characterization for the flow field of polymer melts

### 4.1. Experimental Set-up

#### 4.1.1. Transparent Fluids Used

The results reported in this
study were obtained with polystyrene (PS) and high-density polyethylene (HDPE).
They are both transparent, which is necessary to perform visualization experiments.
As they are commercial polymers that melt at high temperatures, they enabled
the study to be performed under quasi-industrial conditions.


#### 4.1.2. Optics

An  He-Ne  laser is used as an incident light. Optical system
and the polarization analyzer are detected by a CCD connected to a computer. Figure4
shows the experimental set-up in our research.Figure 4
The experimental setup.


### 4.2. Experimental Procedures

Table1 shows the experimental conditions. We used two kinds of material (PS and HDPE),
three kinds of rotate speed (20 rpm, 24 rpm, and 32 rpm), five kinds of vibration
amplitude (0.04 mm, 0.08 mm, 0.12 mm, 0.16 mm, and 0.20 mm), and five kinds of
vibration frequency (5 Hz, 8 Hz 10 Hz, 12 Hz, and 15 Hz). In the experiments, first
the screw of the extruder rotated at constant speed. Second, we changed the amplitude and frequency of the
screw, respectively. At the same time, a CCD camera captured the light scattering image of each
processing condition. Finally, the optical image real-time analysis software characterized the flow field of polymer melts.Table 1
Experimental conditions.
MaterialRotate speedVibration amplitudeVibration frequencyPS HDPE0.04 mm5 Hz20 rpm0.08 mm8 Hz24 rpm0.12 mm10 Hz32 rpm0.16 mm12 Hz0.20 mm15 Hz


### 4.3. Optical Image Real-Time Analysis System for Sals

The optical image real-time processing software for SALS (see Figure5), which provides a user-friendly
interface already familiar to the users [40], is based on personal PC platform
running under MS Windows operating system. Hardware specifics of A/D and
digital I/O boards which are connected on PC motherboard impose some
constraints and partly determine real-time software structure, especially
disposition of its components at processors. The software is developed using
Delphi7.0.Figure 5
Optical image real-time processing software for SALS.Real-time
visualization of various scattered light image and light intensity matrices is
performed by the host application. Algorithm of visualization starts with the
selection of working parameters. The next step is setting parameters using
corresponding dialog-boxes provided by the host application. Some of these
parameters are vibration parameters (frequency, amplitude), display parameters
(sizing grid, display scale, image translation, and rotate angle), and other
parameters (rotate speed, material, sampling time). The light intensity matrix
can be saved on disk of main workstation for further analyses.The software
can measure the signal intensity of light scattering images, draw the
frequency-intensity curves and the amplitude-intensity curves to indicate the
variation of the intensity of scattered light in different processing
conditions, and estimate the hydrodynamic parameters. So, the system brought
the qualitative analysis of the structural information of transparent film
success [20].Figure6(a) shows a 3D light intensity image of HDPE at 24 rpm screw rotate speed
without vibration. Figure 6(b) shows light intensity image of HDPE at the same rotate
speed with vibration frequency of 10 Hz and vibration amplitude of 0.20 mm. In comparison
with 3D light intensity image without vibration, 3D light intensity image with
vibration has stronger light intensity. It is illustrated that the orientation
of molecular chain increases because light intensity is proportional
to orientation of molecular chain.3D light intensity compared images of HDPE
at 24 rpm screw rotate speed. (a) Without vibration, (b) with vibration
frequency of 10 Hz and vibration amplitude of 0.20 mm.
(a)
24 rpm-0-0(b)
24 rpm-10 Hz-0.20 mmFigure7
shows the variation trend of maximum intensity projection area with the
increase of vibration frequency of PS at 20 rpm rotate speed. As shown in Figure
8, with the increase of vibration frequency, the maximum intensity projection
area becomes larger. It is because with the increase of vibration frequency,
the molecular orientation of polymer melts also increases. As a consequence,
the light intensity becomes stronger.Figure 7
The relationship between maximum
intensity projection area and vibration frequency of PS (rotate speed: 20 rpm,
vibration amplitude: 0.16 mm, and different vibration frequency).Figure 8
The relationship between maximum intensity projection area and vibration
frequency of HDPE (rotate speed: 24 rpm, vibration frequency: 10 Hz, and
different vibration amplitude).Figure8
shows the relationship between maximum intensity projection area and vibration
amplitude of HDPE at 24 rpm screw rotate speed. From Figure 8, it is clear that with the increase
of vibration amplitude, the maximum intensity projection area becomes larger.
The molecular orientation of polymer melts increases is also the main reason of
this optical phenomenon.


### 4.4. Sals Signal Decomposition by Wavelet Analysis

A signal
including noise can be expressed as(15)s(i)=f(i)+σ⋅e(i),i=0,…,n−1,   where f(i) is the real signal, e(i) is the noise, σ is the coefficient of the noise, and s(i) is the signal including noise.The useful
signal is included in the part of low frequency, and the noise is included in
the part of high frequency. As shown in Figure9, we used one-dimensional wavelet
which decomposed
the original signal into three level: (16)S=Ca3+Cd1+Cd2+Cd3,   where S is the original signal, Ca1, Ca2, Ca3 are the approximation coefficients of levels 1, 2, and 3, and Cd1, Cd2, Cd3 are the detail coefficients of levels
1, 2, and 3.Figure 9
Sketch of multiresolution decomposition tree
at level 3.


#### 4.4.1. on-Line Sals Signal Denosing by Wavelet Transform

The performance of wavelet denoising is comparable to that of
inducingKf correcting factor. Figure 10(a) is the normal
SALS intensity signal. Figure 10(b) is the
SALS signal with multiple scattering
noise. Figure 10(c) shows
the SALS signal denoising
by Kf factor. After
being denoised by wavelet “sym6,"
the multiple scattering
noise is eliminated and the
signal (see Figure 10(e)) is
becoming more smooth.
From Figures 10(d) and 10(f), the
residuals by wavelet decomposition are smaller than the residuals by inducing Kf factor. Wavelet method is more successful in
removing multiple scattering noise than that of
inducing Kf correcting factor.On-line SALS signal denosing by wavelet analysis (wavelet “sym6,"level 3).
(a)(b)(c)(d)(e)(f)


#### 4.4.2. on-Line Wavelet Analysis for The Variation Trend of The Sals Signal

The  method  of  wavelet transform can reduce the ambiguities and accurately
analyze the variation trend of the SALS signal. As shown in Figure11(a),
the variation trend of the original
intensity signal (S)
is not clear. After multirevolution analysis by wavelet “sym6," the variation trend of the intensity is obvious as shown in Figure
11(f). As shown in Figures 11(b)–11(f), Caj(j=1,2,3,4,5) are
the wavelet approximation
coefficients of levels 1–5. It is illustrated that the orientation
of molecular chain increases because light intensity is proportional to
orientation of molecular chain.On-line
variation trend analysis of the
SALS signal by wavelet analysis (wavelet, “sym6,"level 5).
(a)(b)(c)(d)(e)(f)


#### 4.4.3. on-Line Wavelet Analysis for The Exceptional Sals Signal Detection

The wavelet transform
is used to
purify the original SALS signal and diagnose the
exceptional signal. Figure12(a) shows
the original exceptional maximum intensity
signal. Figure 12(b) is the approximation
coefficient of level
6. Figures 12(c)–12(h) are
the detail coefficients of levels
1–6. These
coefficients can be feature parameters of the inner structural information of
the transparent film for
further analysis. As shown in Figure 12(h), the exceptional signal takes place at 500–1000 seconds. The
result shows that this technique provides a new tool for diagnosis of exceptional SALS
signal.On-line wavelet analysis for the exceptional SALS signal (wavelet, “sym6,"
level 6).
(a)(b)(c)(d)(e)(f)(g)(h)


## 4.1. Experimental Set-up

### 4.1.1. Transparent Fluids Used

The results reported in this
study were obtained with polystyrene (PS) and high-density polyethylene (HDPE).
They are both transparent, which is necessary to perform visualization experiments.
As they are commercial polymers that melt at high temperatures, they enabled
the study to be performed under quasi-industrial conditions.


### 4.1.2. Optics

An  He-Ne  laser is used as an incident light. Optical system
and the polarization analyzer are detected by a CCD connected to a computer. Figure4
shows the experimental set-up in our research.Figure 4
The experimental setup.


## 4.1.1. Transparent Fluids Used

The results reported in this
study were obtained with polystyrene (PS) and high-density polyethylene (HDPE).
They are both transparent, which is necessary to perform visualization experiments.
As they are commercial polymers that melt at high temperatures, they enabled
the study to be performed under quasi-industrial conditions.


## 4.1.2. Optics

An  He-Ne  laser is used as an incident light. Optical system
and the polarization analyzer are detected by a CCD connected to a computer. Figure4
shows the experimental set-up in our research.Figure 4
The experimental setup.


## 4.2. Experimental Procedures

Table1 shows the experimental conditions. We used two kinds of material (PS and HDPE),
three kinds of rotate speed (20 rpm, 24 rpm, and 32 rpm), five kinds of vibration
amplitude (0.04 mm, 0.08 mm, 0.12 mm, 0.16 mm, and 0.20 mm), and five kinds of
vibration frequency (5 Hz, 8 Hz 10 Hz, 12 Hz, and 15 Hz). In the experiments, first
the screw of the extruder rotated at constant speed. Second, we changed the amplitude and frequency of the
screw, respectively. At the same time, a CCD camera captured the light scattering image of each
processing condition. Finally, the optical image real-time analysis software characterized the flow field of polymer melts.Table 1
Experimental conditions.
MaterialRotate speedVibration amplitudeVibration frequencyPS HDPE0.04 mm5 Hz20 rpm0.08 mm8 Hz24 rpm0.12 mm10 Hz32 rpm0.16 mm12 Hz0.20 mm15 Hz


## 4.3. Optical Image Real-Time Analysis System for Sals

The optical image real-time processing software for SALS (see Figure5), which provides a user-friendly
interface already familiar to the users [40], is based on personal PC platform
running under MS Windows operating system. Hardware specifics of A/D and
digital I/O boards which are connected on PC motherboard impose some
constraints and partly determine real-time software structure, especially
disposition of its components at processors. The software is developed using
Delphi7.0.Figure 5
Optical image real-time processing software for SALS.Real-time
visualization of various scattered light image and light intensity matrices is
performed by the host application. Algorithm of visualization starts with the
selection of working parameters. The next step is setting parameters using
corresponding dialog-boxes provided by the host application. Some of these
parameters are vibration parameters (frequency, amplitude), display parameters
(sizing grid, display scale, image translation, and rotate angle), and other
parameters (rotate speed, material, sampling time). The light intensity matrix
can be saved on disk of main workstation for further analyses.The software
can measure the signal intensity of light scattering images, draw the
frequency-intensity curves and the amplitude-intensity curves to indicate the
variation of the intensity of scattered light in different processing
conditions, and estimate the hydrodynamic parameters. So, the system brought
the qualitative analysis of the structural information of transparent film
success [20].Figure6(a) shows a 3D light intensity image of HDPE at 24 rpm screw rotate speed
without vibration. Figure 6(b) shows light intensity image of HDPE at the same rotate
speed with vibration frequency of 10 Hz and vibration amplitude of 0.20 mm. In comparison
with 3D light intensity image without vibration, 3D light intensity image with
vibration has stronger light intensity. It is illustrated that the orientation
of molecular chain increases because light intensity is proportional
to orientation of molecular chain.3D light intensity compared images of HDPE
at 24 rpm screw rotate speed. (a) Without vibration, (b) with vibration
frequency of 10 Hz and vibration amplitude of 0.20 mm.
(a)
24 rpm-0-0(b)
24 rpm-10 Hz-0.20 mmFigure7
shows the variation trend of maximum intensity projection area with the
increase of vibration frequency of PS at 20 rpm rotate speed. As shown in Figure
8, with the increase of vibration frequency, the maximum intensity projection
area becomes larger. It is because with the increase of vibration frequency,
the molecular orientation of polymer melts also increases. As a consequence,
the light intensity becomes stronger.Figure 7
The relationship between maximum
intensity projection area and vibration frequency of PS (rotate speed: 20 rpm,
vibration amplitude: 0.16 mm, and different vibration frequency).Figure 8
The relationship between maximum intensity projection area and vibration
frequency of HDPE (rotate speed: 24 rpm, vibration frequency: 10 Hz, and
different vibration amplitude).Figure8
shows the relationship between maximum intensity projection area and vibration
amplitude of HDPE at 24 rpm screw rotate speed. From Figure 8, it is clear that with the increase
of vibration amplitude, the maximum intensity projection area becomes larger.
The molecular orientation of polymer melts increases is also the main reason of
this optical phenomenon.


## 4.4. Sals Signal Decomposition by Wavelet Analysis

A signal
including noise can be expressed as(15)s(i)=f(i)+σ⋅e(i),i=0,…,n−1,   where f(i) is the real signal, e(i) is the noise, σ is the coefficient of the noise, and s(i) is the signal including noise.The useful
signal is included in the part of low frequency, and the noise is included in
the part of high frequency. As shown in Figure9, we used one-dimensional wavelet
which decomposed
the original signal into three level: (16)S=Ca3+Cd1+Cd2+Cd3,   where S is the original signal, Ca1, Ca2, Ca3 are the approximation coefficients of levels 1, 2, and 3, and Cd1, Cd2, Cd3 are the detail coefficients of levels
1, 2, and 3.Figure 9
Sketch of multiresolution decomposition tree
at level 3.


### 4.4.1. on-Line Sals Signal Denosing by Wavelet Transform

The performance of wavelet denoising is comparable to that of
inducingKf correcting factor. Figure 10(a) is the normal
SALS intensity signal. Figure 10(b) is the
SALS signal with multiple scattering
noise. Figure 10(c) shows
the SALS signal denoising
by Kf factor. After
being denoised by wavelet “sym6,"
the multiple scattering
noise is eliminated and the
signal (see Figure 10(e)) is
becoming more smooth.
From Figures 10(d) and 10(f), the
residuals by wavelet decomposition are smaller than the residuals by inducing Kf factor. Wavelet method is more successful in
removing multiple scattering noise than that of
inducing Kf correcting factor.On-line SALS signal denosing by wavelet analysis (wavelet “sym6,"level 3).
(a)(b)(c)(d)(e)(f)


### 4.4.2. on-Line Wavelet Analysis for The Variation Trend of The Sals Signal

The  method  of  wavelet transform can reduce the ambiguities and accurately
analyze the variation trend of the SALS signal. As shown in Figure11(a),
the variation trend of the original
intensity signal (S)
is not clear. After multirevolution analysis by wavelet “sym6," the variation trend of the intensity is obvious as shown in Figure
11(f). As shown in Figures 11(b)–11(f), Caj(j=1,2,3,4,5) are
the wavelet approximation
coefficients of levels 1–5. It is illustrated that the orientation
of molecular chain increases because light intensity is proportional to
orientation of molecular chain.On-line
variation trend analysis of the
SALS signal by wavelet analysis (wavelet, “sym6,"level 5).
(a)(b)(c)(d)(e)(f)


### 4.4.3. on-Line Wavelet Analysis for The Exceptional Sals Signal Detection

The wavelet transform
is used to
purify the original SALS signal and diagnose the
exceptional signal. Figure12(a) shows
the original exceptional maximum intensity
signal. Figure 12(b) is the approximation
coefficient of level
6. Figures 12(c)–12(h) are
the detail coefficients of levels
1–6. These
coefficients can be feature parameters of the inner structural information of
the transparent film for
further analysis. As shown in Figure 12(h), the exceptional signal takes place at 500–1000 seconds. The
result shows that this technique provides a new tool for diagnosis of exceptional SALS
signal.On-line wavelet analysis for the exceptional SALS signal (wavelet, “sym6,"
level 6).
(a)(b)(c)(d)(e)(f)(g)(h)


## 4.4.1. on-Line Sals Signal Denosing by Wavelet Transform

The performance of wavelet denoising is comparable to that of
inducingKf correcting factor. Figure 10(a) is the normal
SALS intensity signal. Figure 10(b) is the
SALS signal with multiple scattering
noise. Figure 10(c) shows
the SALS signal denoising
by Kf factor. After
being denoised by wavelet “sym6,"
the multiple scattering
noise is eliminated and the
signal (see Figure 10(e)) is
becoming more smooth.
From Figures 10(d) and 10(f), the
residuals by wavelet decomposition are smaller than the residuals by inducing Kf factor. Wavelet method is more successful in
removing multiple scattering noise than that of
inducing Kf correcting factor.On-line SALS signal denosing by wavelet analysis (wavelet “sym6,"level 3).
(a)(b)(c)(d)(e)(f)


## 4.4.2. on-Line Wavelet Analysis for The Variation Trend of The Sals Signal

The  method  of  wavelet transform can reduce the ambiguities and accurately
analyze the variation trend of the SALS signal. As shown in Figure11(a),
the variation trend of the original
intensity signal (S)
is not clear. After multirevolution analysis by wavelet “sym6," the variation trend of the intensity is obvious as shown in Figure
11(f). As shown in Figures 11(b)–11(f), Caj(j=1,2,3,4,5) are
the wavelet approximation
coefficients of levels 1–5. It is illustrated that the orientation
of molecular chain increases because light intensity is proportional to
orientation of molecular chain.On-line
variation trend analysis of the
SALS signal by wavelet analysis (wavelet, “sym6,"level 5).
(a)(b)(c)(d)(e)(f)


## 4.4.3. on-Line Wavelet Analysis for The Exceptional Sals Signal Detection

The wavelet transform
is used to
purify the original SALS signal and diagnose the
exceptional signal. Figure12(a) shows
the original exceptional maximum intensity
signal. Figure 12(b) is the approximation
coefficient of level
6. Figures 12(c)–12(h) are
the detail coefficients of levels
1–6. These
coefficients can be feature parameters of the inner structural information of
the transparent film for
further analysis. As shown in Figure 12(h), the exceptional signal takes place at 500–1000 seconds. The
result shows that this technique provides a new tool for diagnosis of exceptional SALS
signal.On-line wavelet analysis for the exceptional SALS signal (wavelet, “sym6,"
level 6).
(a)(b)(c)(d)(e)(f)(g)(h)


## 5. Conclusions

We
presented  a new technique that can be used to characterize the structural
information of transparent film on-line and nonintrusively while the material
is processing with different conditions. The technique is based on optical SALS
image real-time analysis software and wavelet analysis. Visualization is
performed via high-performance analysis software which allows real-time data
acquisition and processing the SALS signal.It is shown
that the proposed technique is easy to implement and provides more flexibility
approximating the nonlinear relation between the maximum intensity signal and
the corresponding vibration intensity (frequency or amplitude). Applying this
method to characterize
the flow field of polymer melts will be of great interest, since it will
contribute information on optical prosperities that have been proven to be
useful for obtaining deep insights into the molecular and structural parameters
of polymers. In our experiments with the increase of vibration intensity, the
light intensity matrix becomes stronger and the maximum intensity projection
area becomes larger. Because the light intensity is proportional to orientation
of molecular chain, it is illustrated that the orientation of molecular chain
increases.In conclusion, this technique is
believed to be important and promising to on-line characterize the structural
information of transparent film in the multiple-scattering regime.



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*Source: 838412-2009-02-15.xml*