Design of Electromagnetic Tomography System based on Integrated Impedance Analyzer

Ze Liu1, Wuliang Yin2 , Xiufang Sun3 1School of Electronic Information and Engineering, Beijing Jiaotong University, Beijing, P.R.China, Zliu2005@gmail.com

2School of Electrical and Electronic Engineering, The University of Manchester, Manchester, UK 3School of Mechanical and Electronics Engineering, Beijing Union University, Beijing, P.R. China

Abstract — An Electromagnetic Tomography (EMT) prototype system based on integrated impedance analyzer is proposed and developed in this paper. In the prototype system the excitation signal generation and measurement signal demodulation are both realized by using an integrated impedance analyzer IC controlled by an embedded microcontroller. The sensor is constructed with a parallel excitation layer, which is realized with flexible circuit strips as current sources, and coil detector array. The sensor simulation and image reconstruction experimental results of the prototype EMT system are also introduced. The experimental image reconstructions show that the prototype system can locate the distributions of test objects. This work provides a solution that the EMT system can be developed as an embedded instrument to meet the requirement of industrial environment.

Keywords: Electromagnetic tomography; Signal demodulation; Impedance anaylize; Sensor array; Embedded Instrument

I. INTRODUCTION As one of electrical process tomography techniques,

Electromagnetic Tomography (EMT) has the unique advantage that it employs magnetic inductance measurements to extract tomographic data related to permeability and conductivity distributions [1]. So EMT techniques have the potential applications in the industrial process monitoring in situations where the object material contains high contrasts in conductivity and/or permeability. These applications include tracking of ferrite labeled powder in transport separation process, foreign body detection and location, food inspection and fault detection of metal components [2, 3]. Although the resolution of reconstruct images in EMT is not as high as X-ray Computerized Tomography (CT), it is accurate enough for some monitoring application systems which only require coarse image information. Recent years, EMT application system such as steel flow visualization system has been developed and brought obvious improvement for the inspection of steel production process [4, 5]. Nevertheless the ordinary EMT system is not convenient to install in many industrial environment because the size of frontend electronics chassis of EMT is too large and the connection between EMT sensor and signal process chassis is too complicated. The purpose of this paper is to develop a prototype EMT system which has the characteristic of small size, lesser and tidy cable connections. To realize this aim a kind of integrated impedance analyzer IC is used to replace the traditional analog multiplication demodulation circuit and Direct Digital Synthesis (DDS)

excitation signal generation circuit. To reduce the cable connection the data transmission between image reconstruct computer and front chassis is designed to use only a USB 2.0 link. A 32 bits ARM7 microcontroller with a full speed USB 2.0 controller integrated is used to undertake communication task and to control the process of the distribution of excitation signal and measurement multiplexer.

II. SYSTEM DESCRIPTION

A. System Structure The structure of the EMT system is shown as Fig. 1. The

prototype system is designed with three parts which are sensor, frontend electronics chassis and image reconstruction computer. The sensor is connected with electronics chassis by shielded cable including excitation and measurement signal. The electronics chassis is connected with image reconstruction computer by a USB 2.0 cable.

USB

2.0

Sens

or

Exci

tatio

n Si

ganl

Mea

sure

men

t

Figure 1. Structure of the EMT prototype system

The sensor array consists of 16 flexible circuit strips and 16 detection coils. The excitation strips are used to generate a rotatable parallel excitation field. The current excitation and detector signal measurement are controlled by a 32bits ARM7 (LPC2148) embedded microcontroller. The microcontroller’s General Purpose Input Output (GPIO) controls the current distribution of Voltage Controlled Current Source (VCCS) array to generate excitation magnetic field. The excitation signal generation and measurement signal demodulation are realized by using an integrated impedance analyzer IC (AD5933). The AD5933 integrates all basic elements circuit

The work is supported by The National 863 High-Tech R&D Program of China (Grant No. 2007AA11Z118) and NSFC (Grant No. 60776831).

I2MTC 2009 - International Instrumentation and Measurement Technology Conference Singapore, 5-7 May 2009

978-1-4244-3353-7/09/$25.00 ©2009 IEEE

used in the digital signal demodulation of an EMT system. These elements are DDS, Discrete Fourier Transform (DFT) processing core, ADC, DAC, Low Pass Filter (LPF), Programmable Gain Amplifier (PGA) and high speed digital communication interface. The integrated impedance analyzer is controlled by the LPC2148 via an I2C interface to exchange command word and demodulation result data. The sampling speed of the ADC integrated in AD5933 is 1 MSPS at precision of 12 bits. The 16 detector coils’ signal is amplified by 16 pre-amplifiers and switched by a multiplexer which connects to the AD5933’s PGA. The selected signal is then sampled by the in-chip ADC and demodulated by DFT algorithm which is processed by an in-chip DSP engine. The DFT algorithm returns Real (R) and Imaginary (I) data-word at each output frequency. The frequency of the impedance analyzing can get up to 100 kHz. [6]

The DFT algorithm in the AD5933 is as (1) 1023

0

( ) ( ( )(cos( ) sin( )))n

X f x n n j n=

= −∑ (1)

Where, X(f) is the power in the signal at the frequency point f. x(n) is the ADC’s output. cos(n) and sin(n) are the sampled test vectors provided by the DDS core at the frequency point f. The multiplication is accumulated over 1024 samples for each frequency point. The result is stored in two 16-bit registers representing the real and imaginary components of the result. According to a serial of instruction commands the integrated impedance analyzer can work in single frequency mode or frequency sweeping mode. So the signal of different frequency points can be demodulated by the sweeping function according to a sweeping step. The program of excitation and demodulation is running in the LPC2148 which runs at 60 MHz with 512K Bytes memory. The program of the ARM7 is written by C programming language and compiled in an ARM Development Studio (ADS) environment.

As shown in Fig.2, the EMT system’s sensor unit is connected with the electronics case by a DB25 connector with a shielded poly core cable for excitation and 16 shielded signal cables for measurement. The frontend electronics case is connected with an image reconstruction PC only by a USB cable. Also there is a process monitor LCD panel installed on the side of the electronics case, which enables the status of the measurement process to be indicated.

Figure 2. Photo of the prototype EMT system

As shown in Fig.2, there are an ATX (Advanced Technology Extended) sized analog Printed Circuit Board (PCB), a small digital PCB and a power module in the electronics case. To avoid the interference from the high frequency digital signal of embedded microcontroller the analog PCB is designed and installed separately with digital PCB. The image reconstruction computer can be a laptop or embedded high-end microprocessor system which has the ability of USB 2.0 connection and image reconstruction calculation.

B. Design of Sensor Array The sensor structure is shown in Fig.3. The sensor array

consists of three concentric pipe assemblies. From outside to inside there are an electromagnetically shielded pipe, an excitation pipe and a flow pipe [7]. The electromagnetic shielded pipe is made up of a plastic pipe covered with flexible high permeability polymer. The shielded layer can improve the system’s electromagnetic compatibility and reduce the disturbance from the environment. The excitation pipe is made up of plastic pipe covered with 16 flexible circuit strips on the outer surface. On the outside surface of the flow pipe there are 16 coil detectors installed. The connection cables of coil detectors and excitation strips are installed in the cable box and then connected to electronics case.

Figure 3. Sensor structure of the prototype EMT system

On the excitation layer the 16 flexible circuit strips are connected into 8 excitation coils. By controlling the current distribution on the excitation coils a parallel excitation field can be generated and rotated. The simulation of flux line distribution in the cross section of the pipe is shown in Fig. 4. The sensor can generate 8 excitation projections, the first 3 projections flux line distributions are as Fig. 4.

Direction 1 Direction 2 Direction 3

Flow pipe wall Excitation layer wall

Figure 4. Flux line distribution in cross section of the pipe

The excitation signal’s amplitude along the excitation wall is following the sine wave distribution. As the simulation result

shown in Fig. 4 the distribution of the excitation flux line is even and parallel in the center area of flow pipe in this kind of excitation method.

III. SENSITIVITY SIMULATION For calculating the sensor’s sensitivity, the Ansys

Parametric Design Language (APDL) was used to design an automatic geometry construction and filed simulation program. The program set 828 test poles in the pipe to calculate the 16 measurement data in 8 projections by turn automatically. So a sensitivity matrix of 828*16*8 data was generated. This sensitivity matrix was used in the sensitivity based linear back projection algorithm to reconstruct the images. The sensitivity of No.1 detector in the first projection is shown in Fig. 5.

Figure 5. Sensisivity distribution of No.1 detector in projection 1

IV. IMAGE RECONSTRUCTION EXPERIMENT Sensitivity based linear back projection Image

reconstruction algorithm is used in the prototype EMT system. The reconstruction program was developed by using Visual C++ 6.0. The tasks of the program include initialization of LPC2148 microcontroller, sending excitation commands, receiving measurement data and reconstructing images according to measurement data and sensitivity matrix. The program’s interface is shown as Fig. 6.

Figure 6. Image reconstruction software interface

The image reconstruction algorithm is as (2).

( ), ,

1 1

,1 1

( )

( )

P D

p d p dp d

P D

p dp d

ee

e

= =

= =

⋅=∑∑

∑∑

λ SG

S

(2)

, , , ,

, ,

( )( ) p d e p d emp

p d emp

ee

−=p,d

V VS

V (3)

, , ,,

, ,

( )p d p d empp d

p d emp

e −=

V Vλ

V (4)

Where e is the serial number of element meshed in cross section of the flow pipe. G(e) is the gray scale value of element e. There are totally 828 elements in the cross section of the flow pipe. p is the serial number of excitation projection. P is the total excitation projections, which is 8. d is the serial number of detectors, D is the total detectors, which is 16.

Sp,d(e) is the sensitivity value of detector d in projection p related element e . λp,d is the normalized measurement value of detector d in projection p when there are real objects in the flow pipe..

Vp,d,e(e) is measurement value of detector d in projection p when element e filled with the test material only. This value is acquired by simulation. It is the data from sensitivity matrix.

Vp,d,emp is the measurement value of detector d in projection p when the flow pipe is empty.

Vp,d(e) is the measurement value of detector d in projection p when there are real objects in the flow pipe.

The experimental reconstruction images are shown in Table I. Copper poles which radius is 5 mm are used as test samples to verify the performance of the system’s image reconstruction. The reconstruction result indicates that the test sample’s position can be recognized roughly. The resolution of the reconstruct image is not accurate. Nevertheless it still shows the potential application in some process which needs only approximately imaging.

To improve the resolution of reconstruction image in this system the image reconstruction algorithm improvement is the most important way. Linear back projection algorithm is the earliest and basic linear algorithm of process tomography system. In the future the regularization algorithm and iterative algorithm, even nonlinear algorithm of EMT will be developed and tested in this system [8].

TABLE I. EXPERIMENTAL RECONSTRUCTION RESULT

Num Position Mark (Test pole: Cu R=5 mm) Reconstruction Result

I

Num Position Mark (Test pole: Cu R=5 mm) Reconstruction Result

II

III

IV

V. CONCLUSION AND DISCUSSION A prototype EMT system is designed with an integrated

impedance analyzer and a high speed ARM7 microcontroller. This solution made the size of the EMT system reduced without sacrificing the system performance. Also because the link between image reconstruction computer and EMT electronics chassis is only a USB2.0 cable the image reconstruction computer can be designed by using a high performance embedded system with the ability of image reconstruction algorithm calculation. And also a laptop can be used as a test image reconstruction computer. We can anticipate that a more powerful embedded system can be added in the frontend chassis to undertaken the image reconstruction algorithm calculation and process information extraction. In this way the system electronics and the image reconstruction

computer can be merged into one small case to suit the space limited installation environment. And if process information extraction is realized in the frontend chassis, the data which is needed to be transmitted will be less enough to use wireless communicate to acquire by an upper level computer.

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