Electrical Field Simulation for Segmented Excitation of
Electrical Capacitance Tomography.
Shahrulnizahani Mohammad Din , Ruzairi Abdul Rahim and Leow Pei Ling
Faculty of Electrical Engineering, Universiti Teknologi Malaysia,
81310 UTM Johor Bahru, Johor.
hani-md@utm.my
Abstract—This paper presents verification of calculated
electrical field of Electrical Capacitance Tomography. The
electrical field was calculated mathematically along the paths of
the electrical field. The model was derived from linear (x-ray)
tomography. The modeling and simulation was done by using
COMSOL Multiphysics to reconstruct the electrical field. The
simulation was done for single and 4- electrode to analyses the
distribution of electrical field inside the pipe. In general, the
electrical field and electrical potential for segmented excitation
is greater than single excitation method; which may contribute
to better image reconstruction.
I.
INTRODUCTION
Tomography is defined as slice of a picture [1]. Initially,
Process tomography was applied for medical applications [2],
After twenty years of its development, tomography
application is not restricted to medical application only, the
concept of tomography had been applied for various field,
such as archaeology, biology, geophysics, oceanography,
material science, astrophysics and process applications. [3]
The benefits of tomography to industrial application are also
diverse. Tomography is one of the few feedback tools that
give information about what is actually happening inside that
industrial process. The significant contribution of tomography
in reducing production costs through enhancing efficiencies,
producing better yields and enhance process efficiently. It
also helps to simplify process and improve products. [4]
The selection type of sensor usually depends on the
properties or characteristic of the flow material such as
electrical conductivity and permittivity (liquid, gas or solid).
The selection also depends on the need or purpose of the
experiment and the size of the environment. [5]
II.
ELECTRICAL CAPACITANCE TOMOGRAPHY
The application in the industry is relevant and wide – from
medical purposes to understanding the flow of industry
pipelines. ECT is widely used in industrial multiphase
process validation and visualization, especially for petroleum
industry and electrical insulation materials application. From
the perspective point of view, it is possible to image vessels
or pipes of any cross section; most of the research to-date
more focuses on circular vessels. [6]
The principle of ECT is based on the capacitances
measurement placed outside the pipe and by measuring
variations in the dielectric permittivity of the material inside
the pipe.[1]. The capacitances are measured between single
pairs of electrodes where the first electrode is selected as the
transmitter electrode while others electrodes are all detector
(grounded) and the currents which flow into these detector
electrodes are measured. Then, the second electrode is
selected as the transmitter electrode and these sequences are
repeated until all possible pair of electrode capacitances has
been measured. The formula for independent measurement
values, M can be calculated by; where N is the number of
electrodes at the boundary of the pipe or vessel;
M 
N ( N  1)
2
(1)
ECT is suitable for imaging industrial multi-component
processes which involve non-conducting flow materials .An
ECT system consists of three main components; the sensors,
the data acquisition system and the image reconstruction
system [7]. The advantages of the ECT are it is non-invasive
[8] without disrupting the wall of the tested vessel and
disturbing the flow of the process. Electrodes are affordable
and high temperature and high pressure resistance. [9].
However, there are some disadvantages of ECT; it is limited
to non-conductive material and produces low resolution
images. [10]. The relationship between capacitance and
dielectric properties can be given:
C
 0 r A
(2)
dp
Where,
C = capacitance (F)
ε0 = permittivity of free space
εr = permittivity of the dielectric
A = area of the plate
dp = the distance between those plates
III.
EXPERIMENTAL METHOD
A. Segmented Excitations
This paper will focus on the ECT low resolution image
problem. To overcome the problem, the number of electrodes
needs to be increased. However, by doing so, the image
quality at the centre of the pipe will be decreased due to the
reduction of the electrode surface area. [11] [12]. To improve
the image quality, the number of electrodes excites at the
same time could be increase by implementing segmented
techniques. [13]. From the equation (1), the value of
capacitance ( c) will increase as the area (A) of the plate in
increased. Olmos et. al [14] reported the comparison between
single and 4-electrodes segmented excitation method. Better
image reconstruction produced when applying the segmented
sensor. This paper will concentrate for 4-electrode
segmentation excitation.
B. Fan Beam Projections
The arrangement of parallel and fan beam projection are
different. For parallel projection method, each transmitter and
receiver only corresponds to each other. While for the fan
beam projection method, the receiver’s may be more than one
depending to a single or multiple transmitter configurations.
In the switch-mode fan beam method, the transmitters and
receivers can be arranged alternately [15].
C. ECT Modelling
Zimam et al. demonstrated the simulation of fan-beam
projection using portable 16-electrodes ECT system to
compare between single excitation method with 4-electrodes
excitation at the same time [17]. The modelling was done by
using the COMSOL Multiphysics simulator as refer to the
ECT system design in the laboratory. The Electrical field and
potential field of 4-electrodes excitation is better than the
single excitation. COMSOL Multiphysics allows better
understanding of various segmented excitation configurations
and shows the distribution of electrical field and electrical
potential inside the pipe.
The COMSOL Multiphysics design process for ECT sensor
models can be divided into following approach:
(a) Choosing the mode in the electrostatics module
(b) Geometry modeling according to dimension to be
simulated
(c) Generating the mesh
(d) Set electrical properties in the domains
(e) Set the boundary conditions
Boundary conditions used are ground, port and distributed
capacitance. The equations used for the boundary and
subdomain conditions as follows;
, for ground
(3)
, for port (excitation electrode)
(
)
(
)
(4)
, for distributed permittivity (5)
where;
C is the capacitance value
Q is the charge of the two conductors
V is the voltage difference between the two conductors
D. Electrical Field
There is several researches conducted focus on electrical field
of ECT [18]. Loser et. al. [19] reported the development of the
electrical filed using mathematical modeling.
The sensor size and the sensor’s fixture size affected the
number of sensors used, the resolution increase along with
the number of sensors installed. [16]. The fan-beam
projection is better from the parallel projection because it
covers wider area of the pipe or vessel.
Identify applicable sponsor/s here. (sponsors)
Figure 1. Loser et.al test model with three droplets of water.
The FEM grid for the numerical calculation of the electrical
field inside the pipe was developed using the commercial
software package ANSYS 5.5. Three droplets of water were
used inside the pipe to represent the different permittivity as
shown in Figure 1. The calculated the electrical field inside the
pipeline by using the Poisson equation which is given by;
(
Where;
(
(
(
)
(
)
(
)
IV.
RESULT AND DISCUSSIONS
(6)
) = the electrical permittivity
) = the electrical potential
) = the charge distribution.
Figure 3. Single and segmented excitations for uniform permittivity (air)
The changes of electrical permittivity and changes of
electrical potential will gives the electrical charge
distribution. From figure 1, the line white line indicates the
electrical field generated. This paper will focus on the
development of electrical field using COMSOL Multiphysics.
The preliminarily result will use single excitation, later; the
multiple excitation will be introduced to compare the
electrical filed and electrical potential.
Figure 3 shows the simulation result of simulation test to
reconstruct the electrical field. Figure 3 (a) and (b) show the
single and segmented excitations for uniform permittivity
(air). The electrical potential is uniformly or linearly
distribute from the transmitter to the receivers’. However, the
electrical field in figure 3(b) is greater than figure 3(a). This
shows that the segmented excitation methods may contributes
to better image reconstruction at the center of the pipe.
D. Electrode indications
Figure 2 shows the indication of the electrodes for the
excitation purposes. The simulation considers single
excitation as to verify the calculated electrical field.
Segmented excitation will be done to compare with the single
Figure 4. Single and segmented excitations for multiple permittivity (air and
water)
The three droplets of water was introduced for figure 4 (a)
and (b). Figure 3(a) shows the same single excitation as Loser
test in figure 1, the distribution of distortion is likely the
same. The distortion of electrical field indicates that the ECT
system could detect the existence of the droplets of waters.
Extension to Loser et. al. test, the segmented switching is
introduced. The distortion of electrical field in figure 4 (b) is
more significant compared to figure a(a) as the electrode 1
until 4 are excited at the same time.
Figure 2. Indication of the
electrodes
The red color electrical potential in the figure 3and 4 shows
the highest potential while the blue color shows the lowest
electrical potential. Figure 3(a) shows the distribution of
electrical potential near the electrode; however, in figure 3(b)
the distribution of electrical potential is wider. It covers
almost up until the center of the pipe. The greater of electrical
field and electrical potential may contributes to better image
reconstruction in the pipeline.
[9]
[10]
V.
CONCLUSIONS
[11]
The electrical field was reconstructed using COMSOL
Multiphysics to verify the result of calculated electrical field.
Extended to the electrical field reconstruction for single
excitation, the multiple segmented switching is introduced.
The electrical field shows significant distortion to detect the
different permittivity inside the pipe. The electrical potential
also shows greater distribution inside the pipe for multiple
segmented switching. The electrical field degree will
increase when the permittivity increases. The greater
electrical field and electrical potential may contributes for
better image reconstruction.
[12]
[13]
[14]
[15]
ACKNOWLEDGMENT
The authors are grateful to the financial support from Research
University Grant of Universiti Teknologi Malaysia (Grant No.
Q.J130000.2823.00L03).
[16]
[17]
REFERENCES
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
E. Johana, F. R. M. Yunus, R. A. Rahim, and C. K. Seong,
"Hardware Development od Electrical Capacitance Tomography
for Imaging a Misture of Water and Oil," Jurnal Teknologi, vol.
54, pp. 425-442, 2011.
F. J. Dickin, B. S. Hoyle, A. Hunt, S. M. Huang, llyas, C. Lenn, et
al., "Tomographic imaging of industrial process equipment:
techniques and applications " IEE PROCEEDINGS-G, vol. 139,
pp. 72-82, 1999.
M. S. Becky and R. A. Williams, "Process tomography: a
European innovation and its applications," Meas. Sci. Technol.,
vol. 7, pp. 215–224, 1996.
Q.
Marashdeh,
"ADVANCES
IN
ELECTRICAL
CAPACITANCE TOMOGRAPHY," Graduate School, The Ohio
State University, 2006.
P. T. LTD, "ELECTRICAL CAPACITANCE TOMOGRAPHY
SYSTEM TYPE TFLR5000 OPERATING MANUAL,"
Wilmslow UK.2009.
W. Q. Yang and S. Liu, "Electrical Capacitance Tomography with
a Square Sensor," presented at the 1st World Congress on
Industrial Process Tomography, Buxton, Greater Manchester,
1999.
R. A. Rahim, Optical Tomography Pronciples, Techniques, and
Applications. Johor Bahru: Penerbit UTM, 2011.
Norberto Flores, J. C. Gamio, C. Ortiz-Alemán, and E. Damián,
"Sensor Modeling for an Electrical Capacitance Tomography
[18]
[19]
System Applied to Oil Industry," Excerpt from the Proceedings of
the COMSOL Multiphysics User's Conference 2005 Boston, 2005.
R. A. Williams and M. S. Becky, Process Tomography:
Principles, Tecniques and applications. Great Britain:
Butterwoth-Heinemann Ltd, 1995.
J. Lei, S. Liu, Z. H. Li, and M. Sun, "Image reconstruction
algorithm based on the extended regularised total least squares
method for electrical capacitance tomography," Science,
Measurement & Technology, IET, vol. 2, pp. 326-336, 2008.
A. S. Al-Afeef, "Image Reconstructing in Electrical Capacitance
Tomography of Manufacturing Processes Using Genetic
Programming," Master, Faculty of Graduate Studies, Al-Balqa
Applied University, Al-Salt, Jorda, 2010.
A. B. Plaskowski, C. G. Xie, and M. S. Beck, "CAPACITANCEBASED TOMOGRAPHlC FLOW
IMAGING SYSTEM,"
ELECTRONICS LETTERS, vol. 24, pp. 418 - 419, 1988.
E. J. Mohamad, R. A. Rahim, L. Leow Pei, M. H. F. Rahiman, O.
M. Faizan Bin Marwah, and N. M. N. Ayob, "Segmented
Capacitance Tomography Electrodes: A Design and Experimental
Verifications," Sensors Journal, IEEE, vol. 12, pp. 1589-1598,
2012.
A. M. Olmos, M. A. Carvajal, D. P. Morales, A. García, and A. J.
Palma, "Development of an Electrical Capacitance Tomography
system using four rotating electrodes," Sensors and Actuators A:
Physical, vol. 148, pp. 366-375, 2008.
R. Abdul Rahim, L. C. Leong, K. S. Chan, M. H. Rahiman, and J.
F. Pang, "Real time mass flow rate measurement using multiple
fan beam optical tomography," ISA Transactions, vol. 47, pp. 314, 2008.
R. A. Rahim, L. C. Leong, K. S. Chan, S. Sulaiman, and J. F.
Pang, "Tomographic imaging : Multiple fan beam projection
technique using optical fibre sensors," in Computers,
Communications, & Signal Processing with Special Track on
Biomedical Engineering, 2005. CCSP 2005. 1st International
Conference on, 2005, pp. 115-119.
M. A. Zimam, E. Johana, R. A. Rahim, and L. P. Ling, "Sensor
Modeling For An Electrical Capacitance Tomography System
Using COMSOL Multiphysics," Jurnal Teknologi, vol. 55, pp.
33-47, 2011.
W. Q. Yang and L. Peng, "Image reconstruction algorithms for
electrical capacitance tomography," Measurement Science And
Technology, vol. 14 (2003) R1–R1, pp. 1-13, 2003.
T. Loser, R. Wajman, and D. Mewes, "Electrical capacitance
tomography: image reconstruction along electrical field lines,"
MEASUREMENT SCIENCE AND TECHNOLOGY, vol. 2, pp.
1083–1091, 2001.