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Real Time Surface Measurement Technique in a
Wide Range of Wavelengths Spectrum
Anzar Alam, Anatoliy Manuilskiy, Mattias O’Nils, and Jan Thim
Abstract— Real time surface topography measurement in the
paper and paperboard industries is a challenging research field.
The existing online techniques measure only a small area of
paper surface and estimate topographical irregularities in a
narrow scale as a single predictor. Considering the limitations
and complications in measuring the surface at high speed, a
laser line triangulation technique is explored to measure surface
topography in a wide scale. The developed technique is new for
the paper and paperboard application that scans a line onto
the paper-web surface up to 210 mm in length in the cross
machine direction. The combination of a narrow laser linewidth
imaging, a subpixel resolution, and the selection of a unique
measurement location has made it possible to measure roughness
and simultaneously characterize paper surface topography from
0.1 to 30 mm spatial wavelength. This spatial range covers
wide scale surface properties such as roughness, cockling, and
waviness. The technique clearly distinguishes and characterizes
the surface of newspaper, and lightweight coated, coated, and
uncoated paperboard in real time during the paper manufacturing process. The system temporal noise for the average roughness
is estimated as 37 dB. The signal to noise ratio found is from 5.4
to 8.1 in the short spatial wavelength up to 1 mm, whereas it is
more than 75 in the long spatial wavelength from 5 to 10 mm.
Index Terms— Optical online surface topography, narrow laser
linewidth imaging, laser line triangulation, surface measurements
techniques, paper and paperboard topography.
I. I NTRODUCTION
I
NCORPORATING automatic real time inspection and measurement of surface topography in the paper and paperboard
manufacturing process when the paper web is moving at high
velocities in a harsh industrial environment, is a challenging
research area [1]–[6].
The traditional surface quality measurement techniques used
in laboratories have obvious limitations, for example, these
techniques are slow and the surface dynamic properties change
during lab measurements. In addition, as only a few samples
at the end of the tambour are tested, leaving the rest of
the tambour un-measured. The laboratory measurement is not
sufficiently helpful to fix the problem if the surface quality
is not according to the set parameter. Hence, there is a
need to have an online measurement device that can monitor
Manuscript received August 27, 2013; accepted September 5, 2013. Date
of publication September 16, 2013; date of current version November 5,
2013. This work was supported by the Knowledge Foundation Sweden. The
associate editor coordinating the review of this paper and approving it for
publication was Dr. Richard T. Kouzes.
The authors are with the Department of Information Technology and
Media, Electronics Design Division, Mid Sweden University, Sundsvall
85170, Sweden (e-mail: [email protected]; [email protected];
[email protected]; [email protected]).
Color versions of one or more of the figures in this paper are available
online at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/JSEN.2013.2281913
record and characterize the entire tambour in order to achieve
smooth and uniform surface and to ensure that the quality
of the manufactured product can conform to its specified
standards. [5], [6]. Therefore, online measurements, during
the manufacturing process steps, will play an essential role
in enhancing the quality throughout the entire production and,
as a consequence, wastage will thus be reduced.
The paper surface complexity manifests itself in the form
of the perceived quality of the surface [7]–[14]. Based on a
number of reasons, online measurements on the paper surface
are critical and pose a challenge to researchers [2], [3], [8].
One reason is that paper is manufactured at very high speeds,
achieving up to 2000 m/min. During online measurements,
the paper web, at high velocities, induces components such as
machine waviness, form error, position error, vibrations, stress
on the surface, noise etc. These components can also embed
into the desired measurement, which could lead to a significant
error in the final measurement. This means that an online
technique should possess a high resolution and be sufficiently
fast to cope with speed problems and also be associated with
an intelligent algorithm, which has the ability to filtrate the
desired surface topography.
Although there is a great deal of sophisticated non-contact
laboratory equipment available. Contact based laboratory
equipment, for example, Stylus, Bendtsen, and Parker Print
Surf are widely used but, these are low resolution devices.
Many high resolution instruments are also available, for example, Atomic Force Microscope (AFM), and Scanning Electron
Microscope (SEM). The available laboratory instrument cannot be deployed for online measurements because they are
either contact based or are only designed to operate in a
laboratory environment.
Recently, a small number of online devices have been
developed but, with limited features, the majority of these
are only designed to detect surface defects [15]. Scientists
and researchers are endeavoring to develop new online techniques and are designing new sensors [16], [17] based on the
non-contact principle, for example, light scattering, diffractions, interferometric, confocal microscopy, and laser triangulation [5], [12], [18], [19].
The triangulation distance measurement technique is well
known for its simplicity, flexibility, reliability, economy, and
robustness [20], [21]. The triangulation technique has been
comprehensively described by Costa [21] together with its
applications in relation to surface inspections.
Surface measurement technique mainly depends on type of
light illumination and the geometry of the technique [22].
Illuminations are operated in either a continuous or pulse
mode, depending on the applications. The advantage of pulse
1530-437X © 2013 IEEE
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Light source
Imaging
sensor
Point
scanning
Line scanning
Area scanning
Fig. 1. Three basic principles to measure online surface roughness, point,
line and area measurement techniques.
laser source over continuous wave laser is its capability to
produce a powerful burst of light beam of short duration which
is usually employed for the applications where objects are
moving. In this work a pulsed laser source of one microsecond
exposure time is used which is essentially important to cope
with the paper web speed problem. The selection of the
measurement location on the moving paper web also plays
a unique role in making the technique reliable. The available
online instruments can be categorized into three basic groups,
namely points, line, and area measurements techniques as
shown in Fig. 1 [23]. In the majority of techniques, a light
source is projected onto the paper surface and the reflected
light from the sample is collected by the imaging sensor,
usually a CCD sensor(s). The point-scanned technique measure the surface roughness in the machine directions and
an example is the Scantron “Proscan Mastertrak1” online
profilometer. The majority of the point-scanned techniques
are used in laboratory, for example, Atomic force microscope
(AFM) and MicroProf (Fries Research & Technology GmbH),
which are high resolution devices designed for the laboratory
environment. In the line-scanning technique, a beam of laser
light is projected onto the paper surface and the reflected
line is collected by the sensor(s) [24]. Line-scanning provides
a whole length measurement as a vector, thus making the
computational algorithm fast in comparison to the point measurement technique. In the paper mill, line-scanning could be
advantageous to measure the paper web surface in the cross
direction (CD) which could be extended to measure across the
full width of the paper web. The area scanning measurement
technique is popular for measurements in the laboratories.
However, because of the speed limitation, it is not easy to
measure and analyze a large area of the paper surface in
real time. The “Precision FotoSurf” developed by Honeywell
claims to be capable of measuring surface up to a maximum
of 15 mm × 15 mm. However, the majority of instruments are
capable to scan an area in relation to the detection of a coarse
abnormality or fault on the paper surface by using multiple
sensors. An example of this is the Metso PQV developed by
the Metso Corporation which is designed to only detect online
paper surface defects.
Considering the importance of the online topography
measurement a prototype online profilometer was developed, which is based on a narrow laser linewidth imaging
technique, integration of existing optical techniques and fast
image processing algorithms. A general purpose computer,
with a windows operating system, has been chosen in order
to make experimental work simple and repeatable.
The prototype device projects a 210 mm line of light onto
the paper web, using two laser sources in the cross direction
(CD), and is able to take a measurement at almost every meter
in the machine direction (MD) thus in this way it is possible
to closely estimate the entire production surface quality. This
prototype has been successfully tested in a paperboard pilot
machine in Sweden. Paper web surface quality was estimated
in average roughness Ra, rms roughness Rq, and the surface
topography was characterized in a wide spatial range of
wavelength spectra from 0.09 to 10 mm for the different
qualities of paperboards and LWC papers, including newspaper
and fine paperboards.
II. OVERVIEW OF THE M EASUREMENT S ETUP
A. The Prototype Block Diagram
In this research work, a line of light measurement technique
was adopted in order to obtain fast, efficient online measurements in the cross machine direction on the paper web. The
basic trigonometric method used in order to determine the
surface height using the line of light technique, is described
in [25].
The fundamental hardware components of the prototype
consist of; pulse semiconductor laser sources, a pulse generator, pulse drivers, a pulse synchronized triggered system, dc
power sources, 3 CCD programmable digital sensors, personal
computer with labview and uEye embedded software. Two
40 mm focal length plano-convex cylindrical lenses were used
to project a focused thin line of light onto the paper surface.
The basic block diagram of the developed prototype device
is shown in Fig. 2, where one laser light source is shown
in order to maintain the simplicity. The real prototype is
constructed using two laser sources concatenated with each
other thus making a long stable line. The laser line images
were acquired by synchronizing a trigger pulse with the laser
sources. The laser line of light has pulse duration of about
1 μs, thus a tight synchronization technique was adopted.
The laser source, a multichannel semiconductor operating in
the near infrared region, has a wavelength of 900 nm and the
maximum power delivered in pulse mode is 100 watt, thus the
energy delivered is,
Energy = Power · Pulse duration = 100 μjoules.
A three terabyte USB mass storage device is integrated into
the system in order to save the images, online data and the
history of the measurements.
B. Measurement Location on the Moving Paper Web
The selection of the measurement location was one of the
most important parts of the entire measurement technique.
The aim was to place the prototype device after the coating
section so that the finished surface could be measured. Paper
manufacturers are interested in the measurement of the roughness rather than the long waviness, therefore, the measurement
ALAM et al.: REAL TIME SURFACE MEASUREMENT TECHNIQUE
Fig. 2.
287
The block diagram of the developed prototype based on optical line-of-light triangulation technique.
Fig. 3. The projected line of light shows measurement location is against
the metallic cylinder where paper web bends and routes for further process.
of the paper surface was chosen to be against the metallic
cylinder at the point at which the paper web bends and routes
for further processing. This location plays a unique role as
it is the most stable place on the entire web and it is where
the effect of long waviness and vibrations are minimized thus
enhancing the accuracy of the technique. An investigation has
shown that the accuracy will be enhanced if the roughness is
measured in the cross direction [26], therefore, a laser line is
projected against the paper surface in the cross direction as
shown in Fig. 3.
III. M EASUREMENT T ECHNIQUE
Fig. 4. The line of light ray tracing diagram using one laser source. The final
line of light is constructed using two laser sources which projects effectively
210 mm length of light on the paper surface.
A. The Construction of Line of Light
The second important part of this prototype was the formation of a narrow laser line that should be of sufficient
energy to maintain the output intensity within the range of
160 - 240 gray levels and which should be as uniform as
possible throughout the total length of the line. The advantage
of using a semiconductor laser diode is of its small size,
light weight, high power and very efficient. However, the
diverging nature of the semiconductor laser source does not
retain a uniform distribution of the light along the length of
the line. In order to maintain the line of light to be focused and
thin, cylindrical lenses have been utilized as shown in Fig. 4.
The combination of the two lens system focuses the laser line
onto the paper surface, which is at the focal length of the
secondary lens (f2 = 40 mm). The emission facet of the laser
beam is a rectangle. The two plano-convex cylindrical lenses,
each with a 40 mm focal length, shape the final line of light
to a narrow laser line. The laser diode has a divergence along
the length of laser facet (θ y) of 26° while along the width
(θ x) is 12°.
Fig. 4 shows one laser source but, in the actual prototype,
two laser sources are deployed, which are concatenated in
series in order to make the line uniform and stable. By concatenating the two laser lines, the effective length obtained
and monitored by the 3 sensors is 210 mm. The line of light
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Fig. 7.
Fig. 5. The intensity distribution along the whole line of 210 mm length.
Intensity is on vertical axis while the No. of pixels on horizontal axis.
Magnified pixilation image shows the width of a narrow laser line.
The optical axis is maintained at θ = 65° normal to
the paper surface. The actual height deviation on the paper
surface is “h” while the sensor captures this height equivalent
to h . The height deviation is monitored on the sensors as
a displacement “y”. Using trigonometric laws, the position
shift on the sensor “y” can be derived as
bSi nθ
∗h
(1)
y ≈
a
In the equation, “b” is the image to lens distance which was
found to be 27.78 mm using a 25 mm focal length of the
sensor lens and “a” is the paper surface to the lens distance.
The prototype is designed with a = 250 mm and θ = 65°.
By maintaining these constants values (1) can be reduced to,
y ≈ 0.101 ∗ h
(2)
As an example, if the actual height on the paper surface is
100 μm, the position shift on the imaging sensor would be
10.1 μm, which is about a 2.3 pixels shift.
C. Subpixel Resolution
Fig. 6.
The fundamental surface height measurement technique.
imaged by the sensors has a width in total, equivalent to
4 - 5 pixels but, the effective width consists of approximately 3 pixels, taking into account the effective intensity
levels.
Fig. 5 shows three line images, each of length 70 mm, captured by three individual CCD sensors thus making a total line
length of about 210 mm on the paper surface. Three typical
line intensity profile plots, along the cross direction, show the
intensity distribution at the beginning, middle and end of the
line. These figures show that the intensity distribution is not
uniform along the length of the line. The non-uniform energy
distribution of the laser is a source of noise in the system [27].
The measurement technique is based on the center of gravity
(COG) which is accountable for the changes in the surface
height rather than the change in the intensity level of line,
which thus reduces the effect of the non-uniform intensity
distribution in the overall measurement. Experimentally, it has
been found that the full width at a half maximum (FWHM)
Gaussian distribution of the line profile is about 3 - 4 pixels.
B. Surface Height Measurement
A fundamental surface height measurement technique [28]
is used in the development of the prototype as shown in Fig. 6.
The laser light source is projected perpendicularly onto the
paper surface and the reflected low specular light intensity is
measured by means of the CCD sensors.
The smallest physical element in a sensor is a pixel and
this is insufficient for high resolution applications, therefore,
a subpixel resolution is required, which enhances the Gage
Repeatability and Reproducibility (Gage R&R) in the machine
vision measurement [29]. The sensor used, has one pixel of
size 4.4 μm, which is equivalent to the physical spot of 44 μm
on the paper sample. This spatial resolution is certainly not
sufficient to measure the roughness on the paper surface. The
intention of the developed technique was to measure surface
irregularity in a sub-micrometer resolution, particularly in the
spatial wavelength from 0.1 - 0.5 mm. Different techniques
and algorithms have been in used to enhance the resolution of
the imaging sensor to the subpixel level. These include linear
interpolation, centroid and a Gauss curve fitting algorithm
being used in the machine vision system. The details regarding
the various algorithms are provided in [27]. In this work Center
of Gravity (COG) technique is adopted in order to achieve
subpixel resolution. COG is sensitive to the width of the line
and thus higher accuracy for the surface irregularities can be
achieved if the line width is short, consisting of a few pixels.
Using careful fine tuning of the optical systems, we achieved
a total width of about 4 - 5 pixels but, were able to achieve
an effective accountable line width of 3 pixels throughout
almost the entire length of the line and a part of the line
image is shown in Fig. 7. It should be noted that the post
image processing step, low level thresholding, also removes
low intensity pixels, making line narrower.
The line of light COG is calculated by the standard function,
y2 y=y1 I x,y ∗y
(3)
COG x = y2 y=y1 I x,y
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where x and y are the coordinates of the pixel (location of
the pixels) in the x and y axes of the image plane. “I” is the
gray level intensity of each individual pixel. y1 and y2 are the
upper and lower ends of the image area. Each image contains
1600 pixels in the x direction thus, (3) calculates the COG as
an array of 1600 values.
D. COG and Image Processing
The optical arrangements and acquisition of the images are
made in such a way that a narrow laser linewidth is focused
onto the paper surface and the low-specular light is imaged.
Each image sensor has a resolution of 1600 × 1200 but, the
primary images acquired are of size 1600 × 240. The images
are cropped because the width of interest is the width of the
laser line, which is spread over a small area. Before calculating
the COG, the images were further cropped widthwise in order
to achieve only the width of the laser line. The final width
of the frame was set to be between 30 - 50 pixels depending
on the paper roughness and tilt of the laser line due to form
and position error. For example, a laser line could occupy a
wider width on the rough LWC paper surface while, on the
fine coated paperboard it could occupy a narrower width. The
final cropped image achieved is of small size that utilizes less
space and performs the image processing task fast.
IV. T OPOGRAPHY AND S TATISTICAL DATA
Roughness is defined as the fine scaled out-of-plane surface
irregularities and is a high frequency phenomenon. Waviness
represents large scale irregularities on the paper surface and is
a low frequency phenomenon and is, often, characterized as
the surface homogeneity and by the machine ability [30]. Form
represents the shape, the curl of the spherical surfaces and is
embedded into the topography as one of the components. The
development of the position-error is either due to the misalignment of the measuring instrument or due to the incorrect
positioning of the sample surface. During the online setup
these errors are, primarily, minimized by means of a precise
optical tuning and by the fine alignment of the prototype with
the measuring surface. In addition to this, a standard algorithm
for a fit line and a fit curve was also applied after the COG
in order to remove part of the errors.
The statistical analysis of the surface profile is carried
out as a single predictor, average roughness Ra , or as root
mean square (rms) roughness Rq over the evaluation length L.
These are functions of the profile Zx , a variation from a
mean line Z̄ in the z-direction [23], [31] and calculate the
roughness on the paper using well known equations (4) and (5)
to estimate the roughness as a measure of surface quality
[31]–[34]. Equation (5) shows that the rms value is more
sensitive to the peaks and valleys of the profile [6].
Arithmetic Average Roughness =
1 L−1 Ra =
|Z x − Z̄ |
x=0
L
Root mean square Roughness (rms) =
1 L−1
Rq =
(Z x − Z̄ )2
x=0
L
(4)
(5)
where,
1 L−1
Zx
x=0
L
A Fourier analysis of the paper and paperboard surface is
often required. The advantages of a Fourier spectrum over a
simple Ra or Rq is that it facilitates the characterization of
the surface for a wide range of scales and separate small
scale variation from the large scale variation [9]. Online
measurements were taken by the prototype in a harsh industrial
environment and measurements on the moving paper web
could contain effect of machine vibrations, paper web tensions,
form and position error, etc. These additional effects could be
embedded into the profile and could change the roughness
data [23], [35] and, therefore, the provision of only single
roughness values Ra or Rq is insufficient for some cases. This
article contains online surface estimation as average roughness
and, in addition, provides characterizations in the Fourier
spectrum. The transformation of the spatial domain profile into
a Fourier power spectrum is described step by step in [23]
where the spectrum was plotted into the spatial wavelengths
bands in order to characterize the surface within the spatial
wavelength scale 0.09 to 10 mm.
Z̄ i s Mean li ne =
V. N OISE E STIMATION , DATA C ORRELATION
AND O NLINE M EASUREMENTS
Each imaging sensor, with a resolution of 1600 × 240
pixels, scans a 70 mm line of light (evaluation length). Thus
the line profile spatial resolution is 44 μm along the length
of the line or, alternatively, along the cross direction of the
paper web.
The non-uniform energy distribution and the coherent and
speckle nature of the laser light are sources of noise in the
measurement system. Additionally, optics, stray light, ambient
light, imaging sensor, and electronics [25] also contribute to a
deterioration of the accuracy of the online measurement [6].
An optical long-wave pass filter (λc = 850 nm) is used in the
imaging sensor to filter out the visible light in order to ensure
that ambient light effect is removed from the measurements.
Specular light could saturate the gray scale in the imaging
sensors, particularly if the paper surface is very smooth. The
prototype laser line incidents perpendicularly onto the paper
surface and the reflected light is collected at 65° normal to
the paper surface, thus a low specular line of light is imaged.
The laser speckle is the source of uncertainty in certain
triangulation methods [35]. It is stated that the criteria for
the uncertainty in the distance measurement by laser triangulation technique are: small temporal coherence, small spatial
coherence, small speckle contrast and a large observation
aperture [36]. We have used semiconductor laser diode with
reduced coherence length which results in less contribution of
speckle noise than would be in the case for a gaseous laser
source [35], [36].
Fig. 5 and 7 shows that the cross section intensity is
smooth which indicates less contribution of speckles intensity.
A chosen triangulation angle 65° and an observation aperture
10 mm contribute in the reduction of speckle noise [36], [37].
A sample of coated paperboard was 20 times repeatedly
line scanned in a fixed location and consequently array of line
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Fig. 9. Amplitude of the roughness, Ra and Rq vs. their respective temporal
noise levels. Twenty sequential measurements for the same location are plotted
on x-axis.
Fig. 8. A paper sample is measured repeatedly 20 times onto a fixed location
to determine series of roughness and rms roughness, per fixed line, in order
to estimate system temporal noise.
images of size 20 were obtained in order to estimate temporal
noise of the prototype device. These 20 measurements per
fixed line were acquired while keeping identical laboratory
conditions hence are just time variant repeat images that
could contain temporal noise. During the measurement, sample
was held securely in a fixed position to ensure that each
measurement be acquired for the same physical line onto
the sample surface. Each line images were transformed to
line profile using equation (3) COG and from each profile
roughness values were calculated. These steps are shown
in Fig. 8 and finally, arrays of roughness (Ra )n and rms
roughness (Rq )n were calculated using equations (4) and (5)
where n = 20. Ra and Rq were calculated when the surface
spatial long-wavelength cutoff, λc was 8.75 mm.
Temporal noise is calculated by subtracting neighbor values among the array of roughness with each other, as
under,
Ra Noise = (Ra )n − (Ra )n+1 Rq Noise = (Rq )n − (Rq )n+1 Fig. 9 is the plot of 20 individual Ra and Rq data along
with their corresponding temporal noise, Ra Noise and Rq Noise
values in μm. The low system noise indicates a low pulse-topulse intensity variation in the laser system or alternatively it
indicates almost identical illumination in each exposure time.
The σ is the standard deviation of the array of noise
Ra−Noise , μ is the mean value of the array Ra−Noise and n
is the size of the array which is 20. The SNR in decibel is
determined by (6).
1 n−1
{(Ra Noise ) i − μ}2
Noi seσ =
i=0
n−1
¯ of the array (Ra )n is,
The average roughness, Ra
n−1
¯ = 1
(Ra)i
Ra
i=0
n
¯
SNR in decibel = 20 log10 ( Ra)/Noise
σ
(6)
Table I shows the values of minimum, maximum, and
average roughness Ra and Rq along with the temporal noise
TABLE I
S YSTEM N OISE E STIMATION IN AVERAGE AND RMS ROUGHNESS
Fig. 10. Measured surface topography in wavelength bands for two sets of
measurements Spectrum1 and Spectrum2.
for the two samples; coated paperboard (Coated PB) and the
uncoated paperboard (Uncoated PB).
The signal to noise ratio (SNR) was determined as being
from 35.07 to 39.26 dB. It was noted that the noise is less for
the uncoated paperboard compared to the coated paperboard.
The noise level can vary depending on the sample quality and
the surface spatial long-wavelength cutoff λc.
Surface is also described in the spatial wavelengths in order
to estimate irregularities in a wide scale. Therefore, for any
measurement system, SNR in the entire range of measurement
should also be known. The SNR, in the developed prototype, was estimated in the spatial wavelength scales from
0.1 – 5 mm. A sample of coated paperboard was 20 times
repeatedly measured for a fixed location, as described earlier,
and the acquired 20 profiles were transformed into the spatial
wavelength spectra. Out of 20 spectra first 10 were averaged
and the resultant is termed as “Spectrum1” while the last 10
were also averaged and termed as “Spectrum2”. These Spectrum1 and Spectrum2 are plotted in Fig. 10. These spectral
ALAM et al.: REAL TIME SURFACE MEASUREMENT TECHNIQUE
Fig. 11.
291
The two raw line profiles obtained at a distance of 20 μm with each other on a coated paperboard sample.
Fig. 12. An specimen of step height 75 μm was measured by the prototype
and plot shows the line profile of the specimen which is compare able with
the measurement by manual Mahr digital caliper (figure reproduced [5]).
plots are representing the sample’s line topography height
in μm along the vertical axis corresponding to the wavelength
bands 0.1 to 5 mm. This wavelength range is important for
the perceive quality of the paper surface particularly for the
high quality graphic papers. The prototype system noise, in
the spatial wavelength scale, was estimated by subtracting
Spectrum2 from Spectrum1.
It is known that the SNR varies as the wavelength changes
and that generally the values are low in the shorter wavelengths
and it is high in the longer wavelengths. We have estimated
the SNR 5.36 to 8.08 in the short wavelength up to 1 mm
while, in the long wavelength, for example, beyond 5 mm, it
is more than 75, on average.
Two sequential profiles, acquired on a coated paperboard
surface at a gap of 20 μm with each other, are plotted in
Fig. 11. These two profiles show that how the surface is
changing in the neighbor hood of 20 μm and at the same
time the behavior of the two plots indirectly reveal that the
temporal noise is non-significant in the measurement system.
The surface height calibration of the prototype was verified
by means of a Mahr digital height caliper using a step height
specimen of 75 μm. Fig. 12 shows the profile plot obtained
by the prototype, which approximates the specimen height
difference to be 75 μm [5].
In a previous study, a total of 8 reels of newspaper and 8
reels of paperboard, each having different grades and surface
qualities, were measured online by the developed prototype
and the samples of these reels were also measured by using
a Sture-3, which is a commercial laboratory profilometer, by
MoRe research, Sweden [6]. Fig. 13(a) shows the correlation
plot between these two measurements for the 8 paperboards,
Fig. 13. Correlation between online and offline roughness data among 8
different grades of newspaper reels and 8 paperboard reels. Correlation plot
(a) for coated and uncoated paperboards and (b) for newspaper including top
and wire sides of reels (figure reproduced [6]).
which are comprised of different grades of coated and
uncoated reels while (b) shows the correlation plot for the
8 different grades of newspaper, including both topside and
wireside. Non-correlation in (b) could be due to the fact that
the online measurements are, actually, the average of a huge
amount of data and, in contrast, the offline measurements are
the averages of only a few samples. However, the reasonable
correlation achieved for the data with regards to both the
online and offline does validate the overall measurements of
the online prototype.
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the paper surface has been characterized by taking the average
of 20 consecutive measurements. All the measurements were
performed in the paperboard industry in Sweden.
Fig. 14 shows the plot of 20 successive online measurements for three grades of paper; coated paperboard, uncoated
paperboard and LWC. The rms roughness values Rq are plotted
in (a) and the standard deviations values are plotted in (b). The
standard deviations are also generally used to characterize the
surface quality. Each plot distinguishes the different qualities
of surface while the paper web was moving at 400 m/min.
The average value of the 20 measurements, inserted as text
in Fig. 14(a), is able to clearly distinguish between each
kind of surface. Fig. 15 shows the same online measurements
in the wavelength spectra. The spectral surface roughness
amplitudes of the LWC and uncoated paperboard are roughly
similar in the short wavelengths up to 0.8 mm but, differ
in the longer wavelengths. Characterization of topography
will be useful for paper manufacturer and researchers in
order to investigate differences of surface quality in various
wavelengths ranges. It would be worthwhile to mention, at this
point, that a detailed analysis of a number of different kinds
of papers and paperboards, including top-side and wire-side
newspaper, edge-side and middle-side of coated and uncoated
paperboards, have already been presented in [5], [6].
VI. C ONCLUSION
Fig. 14.
Online roughness measurements (a) and Standard deviation
(b) for three different grades of paper reels; Uncoated paperboard, Light
Weight Coated newspaper, and fine Coated paperboard.
Fig. 15. Online topography for three different grades of paper reels uncoated
paperboard, Light Weight Coated newspaper, and fine coated paperboard
plotted in the wavelength spectra from 0.09 to 10 mm.
A single measurement on a paper surface could also
describe the surface topography but, is possibly insufficient
to completely describe the surface topography because the
measurement on the paper surface changes when the measurement points are changed. Therefore, it is preferable for
the surface quality estimation to be conducted by taking the
average of multiple measurements. In this research work,
Currently available online surface measurement techniques
measure the paper and paperboard surface roughness as a
single predictor, average roughness Ra, or as a root mean
square (rms) roughness Rq over a short evaluation length L.
This article describes the online measurement technique to
characterize surface in a wide range of wavelengths, from
0.09 – 10 mm and is extendable up to 30 mm. This range
could explain many of the surface irregularities such as micro
and macro roughness, cockling, and waviness of paper and
paperboard. The developed technique measures and distinguishes between the various kinds of paper surface in real time,
including base paperboard, finished paperboard, and lightweight coated newspaper in a harsh industrial environment.
It measures at every meter of the web in the machine direction
and, thus, it is possible to obtain data for the entire production.
The high signal-to-noise ratio is encouraging the usefulness of
the technique in general for many other applications and, in
particular, for the paper and paperboard industries. It would be
possible for a paper manufacture to adopt this technique/device
to have a feedback control system in order to produce uniform, smooth, and efficient production. The available optics,
standard image processing algorithms, and the commercially
available hardware and software enables researchers to repeat
the experiment and could provide possible opportunities for
further improvements.
ACKNOWLEDGMENT
The authors gratefully acknowledge the assistance and
industrial support from Dr. J. Lindgren and J. Liden both
at Iggesund and Sundsvall Sweden. Thanks to our colleague,
F. Wait who has reviewed the manuscript.
ALAM et al.: REAL TIME SURFACE MEASUREMENT TECHNIQUE
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Anzar Alam received the B.E. degree in electrical
engineering from the NED University of Engineering and Technology, Karachi, Pakistan, in 1988. He
worked 18 years in the industry, including 14 years
in the oil and gas sector as a Senior Executive.
He is experienced in the control systems of twin
shaft gas turbines, gas driven electric generators,
centrifugal gas compressors, ESD, and plant fire and
gas protection systems.
He restarted education in 2007 and received the
M.S. degree in electronics design from Mid Sweden
University, Sundsvall, Sweden, in 2009, where he recieved the Licentiate
degree in 2012 and is currently pursuing the Ph.D. degree in the electronics
design. He has published three journal articles and his current research
interests include I & C, image processing, image computation and image
based measurement system, surface topography, and laser optics.
Anatoliy Manuilskiy received the Ph.D. degree in
optical systems for communication and information processing from the Post Graduate Department,
Ukrainian Institute of Physics, Kiev, Ukraine, 1971.
He is currently a Senior Research Assistant with
the Department of Electronic Design, Mid Sweden
University, Sundsvall, Sweden. His research interests include laser measurement systems, image and
information processing, and printed electronics.
294
Mattias O’Nils received the B.Sc. degree in electrical engineering from Mid Sweden University,
Sundsvall, Sweden, in 1993, and the Licentiate and
Ph.D. degrees in electronics system design from the
Royal Institute of Technology, Stockholm, Sweden,
in 1996 and 1999, respectively. In 2006, he became
a Full Professor and leads a research group in
embedded systems design with Mid Sweden University. His research interests include design methods
and implementation of embedded systems with a
specific interest in implementation of real-time video
processing systems and their application. In 2010, he became the Head of the
Department of Information Technology and Media, Mid Sweden University.
IEEE SENSORS JOURNAL, VOL. 14, NO. 1, JANUARY 2014
Jan Thim received the M.Sc. and Ph.D. degrees
in electronics design from Mid Sweden University,
Sundsvall, Sweden, in 2002 and 2007, respectively.
Currently, he is an Assistant Professor with the
Department of Electronics Design, Mid Sweden
University. His research interests include optical and
X-ray based measurement systems.
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