Toward an Automated Setup for Magnetic Induction ... - IEEE Xplore

IEEE TRANSACTIONS ON MAGNETICS, VOL. 51, NO. 1, JANUARY 2015

6500104

Toward an Automated Setup for Magnetic Induction Tomography Brendan J. Darrer1 , Joe C. Watson2 , Paul Bartlett1 , and Ferruccio Renzoni1 1 Department

of Physics and Astronomy, University College London, London WC1E 6BT, U.K. 2 Atomic Weapons Establishment, Reading RG7 4PR, U.K.

Magnetic induction tomography is a noncontact electromagnetic imaging technique that has potential applications in security, industry, and medicine. This paper describes an automated setup developed to image metallic objects. The instrument employs a pair of coils in the Helmholtz configuration for the driving field and a planar array of 400 sensor coils. The sample object is imaged via phase variation measurements between the driver and sensor coils’ potential difference, due to inductive coupling between the coils and sample object. The imaging system is automated via LabVIEW. A multiplexer with 400 channels automatically connects each sensor coil to a dual-phase lock-in amplifier, so that measurements of voltage phase-difference between the sensor and driver coils could be taken. These measurements were used to generate an image of the sample object. The planar geometry of the sensor coil array makes the system scalable to a full 3-D imaging system, by simply adding two more driver and sensor assemblies orthogonally to the existing one. However, this requires the ability to image objects at a finite distance from the array plane. An experiment was conducted to explore the imaging capability for various heights of sample-lift-off above the array. This proved that the system is scalable to a full 3-D imaging system. Index Terms— Eddy currents, imaging, magnetic induction tomography (MIT).

I. I NTRODUCTION

M

AGNETIC induction tomography (MIT) [1]–[6] is a noncontact and nondestructive electromagnetic imaging technique that has potential applications in security, industry, medicine, and geophysics. The term MIT is synonymous with electromagnetic induction tomography [1], [4]. Although much research has been undertaken in the biomedical MIT, the technique has not been well developed for imaging of metallic objects. In this paper, we report on an automated MIT system specifically designed to image metallic objects. We further discuss the potential for extending the system to a full 3-D imaging system, based on results of a disk-lift-off investigation. MIT principles rely on the establishment of eddy currents in a conductive object, and the detection of the magnetic field generated by these currents. In our instrument, an alternating current is passed through a Helmholtz coil assembly, providing a near-to-uniform sinusoidal driving field. This is the primary magnetic field B. The sensor-coil array and the sample object are placed in-between the Helmholtz coils. The primary field inductively couples with the sample object, generating a secondary opposing field B (Lenz’s Law) due to the eddy currents induced in the sample. This secondary field is dependent on the conductivity of the sample; and is indirectly detected by the sensor coils. The phase angle between the primary (B) and the total field B + B [1]–[3], is initially measured as phase-difference between the potential difference (p.d.) across the driver and the sensor coils. This measurement is made for each sensor coil of a 20 × 20 array in 2-D space. From the phase-difference data at each sensor position, an image can be constructed. Manuscript received June 12, 2014; revised August 25, 2014 and September 1, 2014; accepted September 2, 2014. Date of current version January 26, 2015. Corresponding author: B. J. Darrer (e-mail: [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/TMAG.2014.2355420

Fig. 1. Photograph of the Helmholtz coil assembly and the 20 × 20 sensorcoil array used to image metallic objects. In the center of the photo an aluminum disk is positioned for imaging at a lift-off height above the sensor coils.

The setup of our automated MIT system includes a Helmholtz driver-coil assembly and a sensor-coil array (Fig. 1), with sample object placed between them, on top of the array and separated by a sheet of graph paper. A 150 W ac amplifier supplies a signal of 27 V rms across the driver coil. At the level of the sensor coils this generates a 0.11 mT rms magnetic field at 500 Hz, and 0.42 mT rms at 200 Hz. A signal recovery 7230 DSP dual-phase lock-in amplifier reads the p.d. phase-difference between the driver and sensor coils. An Agilent multiplexer (34980A) switches between each of 400 sensors in the 20 × 20 planar array, in 500 ms intervals, with the phase data for each sensor being recorded to an output file. This whole process is automated by computer using LabVIEW via Ethernet connections, in a timed sequence loop. Once complete, the phase data are passed to a MATLAB script

0018-9464 © 2015 British Crown Copyright

6500104


to generate the image of the object. The magnetic image is therefore a 2-D surface plot in 3-D of sensor-coil position (x and y axes) versus p.d. phase-difference (z-axis). In the following sections, the different components of the system are described in detail, together with the results of an investigation of the system’s ability to image metallic objects at varying heights of lift-off above the sensor-coil array. II. S ENSOR A RRAY AND H ELMHOLTZ C OIL A. Driver Coils The Helmholtz coil assembly is constructed from wooden formers, a wooden support structure and nonmetallic fixtures. This is to magnetically isolate it from the electronic equipment and any other metallic objects in the vicinity. It consists of two identical coils separated by a distance, along their collinear axis, equal to the radius of the coils [7]. This is to obtain a near-to-uniform magnetic field in the central region of the Helmholtz coil system. The two Helmholtz coils were wound with 1 mm diameter enameled copper wire, with 300 turns in each coil. The external diameter was 28.8 cm and inner diameter 25 cm. The radius, measured from the horizontal center of the windings was 13.45 cm. Therefore, the perpendicular separation of the coils along their collinear axis, from the vertical center of their windings [7], [8], was adjusted to 13.45 cm, to be the same as the radius and to within ∼1 mm accuracy. The vertical thickness of each coil is 1.8 cm. The Helmholtz coils assembly has the following electrical and magnetic properties. First, it has resistance (11.5 ± 0.1) . The driving frequency depends on the specific applications. For calibrating the MIT system, in terms of vertical displacements (lift-off) of the sample above the array of sensors, the frequency of driving field was set to 500 Hz. At 500 Hz the inductance and impedance of the Helmholtz coil were measured as (100.17 ± 0.02) mH and (314.9 ± 0.1) , respectively. For applications requiring greater penetration depth, the instrument was operated at a frequency to 200 Hz. At 200 Hz the inductance and impedance of the Helmholtz coil was measured as (100.18 ± 0.01) mH and (126.40 ± 0.01) , respectively. The magnetic flux density generated by the Helmholtz coils, in its central region and level with the sensor array, was (0.107 ± 0.004) mT rms at 500 Hz and (0.42 ± 0.02) mT rms at 200 Hz. These measurements were made with a handheld magnetometer and (27 ± 1) V rms applied across the Helmholtz coil. The current through the Helmholtz coils was (86 ± 3) mA rms at 500 Hz and (215 ± 2) mA rms at 200 Hz. B. Planar Sensor-Coil Array The p.d. phase-difference measurements are between the driver and sensor coils, and these data are used to create the image of the sample. To make phase measurements efficiently the system was automated using an array of 20 × 20 sensor coils. The 400 sensor coils are commercially available inductors of (680 ± 10%) μH, with ferrite cores. The sensor coils are soldered to two veroboards connected together, with average

spacing of 12.74 mm between their centers in both x- and y-directions, in the plane of the array. The sensor coils cover an area of (242 × 242) mm. Ribbon cable connects the sensor coils to the multiplexer, so that each sensor can be selected in sequence via the multiplexer switching mechanism. The sensors are isolated on the veroboard with separate input and output terminals. The output signal of the sensors is sent to the dual-phase lock-in amplifier through the multiplexer. In the lock-in amplifier, the dynamic p.d. of the sensor coil is referenced with that of the driver coil, for phase measurements. The measured data consists of these relative phase values, one per sensor coil. In the final stage of the imaging process, cubic piecewise interpolation of the phase and position data enables an image of the object to be generated, as a 2-D surface plot. The sensor coils have resistance 1.4 and external diameter (6.90 ± 0.03) mm. The average current induced in the sensor coils was measured with no sample object present. This does not include sensors at the edges, outside of the uniform driving field. The current was calculated from the p.d. across the sensor coils and their impedances. These were measured from the output terminals with (27 ± 1) V rms applied across the driver coil. At 200 Hz the average current through a sensor coils was (0.044 ± 0.009) mA with average impedance of (205 ± 1) and average p.d. across the sensors of (9 ± 2) mV. The large impedance was due to 3 m of ribbon cable and the multiplexer that the current passes through before being measured. Similar values were measured at 500 Hz. III. P OWER S UPPLY, M EASUREMENT, AND C ONTROL I NSTRUMENTS The Helmholtz coil pair is driven by an amplifier, via the reference oscillator of the lock-in amplifier. A 150 W ac amplifier, with bandwidth of 20 Hz to 20 kHz, increases the oscillator signal amplitude from 2.6 to 27 V rms. This amplified signal is applied across the Helmholtz coil pair to provide the near-to-uniform driving field. The dual-phase lock-in amplifier measures the p.d. phasedifference between the driver and sensor coils, by measuring the p.d. induced across the sensor coil with respect to the reference p.d. applied across the driver coil. The Agilent 34980A multifunction switch/measure unit has six low-frequency multiplexer modules inserted (6 × Agilent 34924A) that make up the multiplexer used in the work described in this report. Each module is a 70-channel reed-switch multiplexer. IV. AUTOMATION OF THE I MAGING P ROCESS To automate the imaging process, a timed-sequence structure was set up in LabVIEW. First, the multiplexer is initiated and the first switch is closed, from within an array of 20 × 20 switches that connects to separate input and output for each sensor coil. Two for loops in LabVIEW enclose the time-sequence structure, and automatically select each sensor in the array, in turn. When a sensor coil is selected and its circuit closed, the timed-sequence structure waits 500 ms for the lock-in amplifier to settle. In the second part of the timedsequence structure, LabVIEW reads the phase value between

DARRER et al.: TOWARD AN AUTOMATED SETUP FOR MIT

6500104

Fig. 3. Calibration curves for copper (Cu) and aluminum (Al) disks, of varying diameters (Ø), 20 to 150 mm, and all 2 mm thickness. The plot shows edge-detected diameter against lift-off height above sensor-coil array. The measurements were made with a driving field of 500 Hz.

Fig. 2. Images of a copper rectangular cuboid: 99 mm × 45 mm × 2 mm, raised up (a) 0, (b) 20, and (c) 40 mm above planar sensor-coil array.

the driver and sensor coil, and sends it to an output array. The third part of the structure then opens the sensor-coil switch in the multiplexer, disconnecting its circuit. The LabVIEW nested for loops then select the next sensor in the array. This whole process is repeated 400 times, once for each sensor coil. An output array of phase values is then stored in an output file. The MATLAB script then generates a magnetic image of the sample object, by interpolation of the data with a cubic piecewise fit. V. I MAGING P OWER AT F INITE L IFT-O FF The planar geometry of the array makes it easily scalable to a full 3-D imaging system. This can be realized by adding two more 2-D imaging systems orthogonally to the existing one, and then combining the images in the three different directions. However, this requires the capability to image objects also

at a finite lift-off from the array plane. This is precisely investigated here. The ability of imaging objects at finite lift-off is qualitatively shown in Fig. 2, which also shows the distortion introduced by increasing lift-off. At a more quantitative level an experiment was conducted to determine the power of the system to image objects raised above the sensor-coil array, at 500 Hz driving frequency. Five disks of copper and five disks of aluminum, with diameter between 20 and 150 mm, and all with thickness 2 mm, were used. For each disk, MIT images were taken with our instrument for different lift-off heights. The diameter of the imaged disks was studied as a function of the lift-off distance. The diameter was determined from the images by applying a Canny edge detection algorithm [9]–[11] to each disk image and measuring the diameter traced out by the edge detection. The results of our measurements are shown in Fig. 3. First of all, we notice that copper and aluminum disks of the same size gave a similar result. This is not surprising as they have both large and comparable conductivities. We now analyze in detail the results. In the plane of the array, at a height of 0 mm lift-off, i.e., level with the top of the sensor coils, the system has a horizontal resolving power of about 30 mm. This is the minimum size disk resolvable in the array plane, for both copper and aluminum. For disk diameter larger than 50 mm, the edge-detected diameter is proportional to the true diameter. In particular, it is smaller than the true diameter by ∼18 mm, indicating a linear relationship with slope close to unity in the plane of the array, at 0 mm lift-off-height. For vertical resolution, described in the rest of this document, Fig. 3 also shows the changes in edge-detected diameter with disk-lift-off. This was up to a height of 40 mm, for the 20 mm diameter disks, and up to 80 mm height for the 150 mm diameter disks. The curves end after these heights, when edgedetection becomes too fragmented to measure a diameter from the image. Our imaging system can thus detect disks up to

6500104

Fig. 4. Calibration curve for two copper (Cu) disks of diameters 50 and 100 mm by 2 mm thickness. The plot shows edge-detected diameter against lift-off height above the sensor-coil array. The measurements were made with a driving field of 200 Hz, 500 Hz, 2 kHz, and 10 kHz.

80 mm lift-off-height for 100 and 150 mm diameter disks, and up to 40 mm for the 20 mm diameter disks. These images are poorer quality than the images at lower heights. As can be observed in Fig. 3, different size disks give a different response in the size of the images generated, with increasing disk-lift-off. For the small copper and aluminum disks with diameter equal to or smaller than 50 mm, there is a progressive increase in disk-image diameter with disk-lift-off. We attribute this behavior to the system operating near or below the limit of resolution. Our instrument is not suitable for imaging disks of this dimension. For the larger disks, with diameter equal to or larger than 100 mm diameter, the disk-image reduces in size whilst being raised up to 20–30 mm disk-lift-off, and then levels off with low gradients. This proves that our system is capable of imaging objects at a lift-off distance of up to 80 mm, provided that the object size is larger than the resolution limit. We also investigate how the performance of our instrument depends on the driving frequency. Fig. 4 shows the results of comparing disk-lift-off for 50 and 100 mm diameter copper disks at four different driving frequencies. For all the frequencies considered of the 50 mm diameter disk, the image shows an increasing dependence on the true diameter. This is in agreement with our previous statement that the system is operating near the resolution limit, and thus these images do not provide reliable information. A change in the driving frequency does not significantly change this. The 100 mm disk was included in Fig. 4, with uncertainties in the measurements of the edge-detected diameter shown as per frequency. VI. C ONCLUSION In this paper, we described a new automated MIT system based on a 20 × 20 planar sensor-coil array and Helmholtz coils for the driving field. Due to the planar geometry, our imaging system does not require a solution to the inverse-problem, often implemented in MIT systems.


This enables us to use a large number of sensor coils for imaging. This is at variance with MIT system using nonplanar geometries that, due to the large computational effort required to solve the inverse problem, are limited to approximately 16–32 exciter/receiver coils [12]. The planar geometry also makes the system suitable to be scaled up to a full 3-D imaging system. The 3-D system will comprise three imaging assemblies as the one described in this paper, oriented along three perpendicular axes. The 3-D image could then be generated by combining the images produced by the three individual assemblies. However, this approach requires the ability to image objects at finite lift-off from the array plane. The results presented in this paper for imaging of objects at different lift-off-heights, indicates a 3-D imaging system to be viable. It is interesting to compare our results with the planar MIT system in [13]. That setup can detect an aluminum rod, up to a depth of 30–40 mm beneath the planar array, using a 50 kHz driving frequency. Our imaging system can detect up to 80 mm depth (lift-off-height) for 150 mm diameter disks and up to 40 mm depth for the 20 mm diameter disks; although, these images are poorer quality. The driving frequency used was 500 Hz. ACKNOWLEDGMENT This work was supported in part by the Home Office and in part by the Ministry of Defence, and commissioned by AWE. The authors would like to thank N. Gaspar (AWE) for discussions. R EFERENCES [1] H. Griffiths, “Magnetic induction tomography,” Meas. Sci. Technol., vol. 12, no. 8, pp. 1126–1131, Jun. 2001. [2] H. Griffiths, W. Gough, S. Watson, and R. J. Williams, “Residual capacitive coupling and the measurement of permittivity in magnetic induction tomography,” Physiol. Meas., vol. 28, no. 7, pp. S301–S311, Jun. 2007. [3] A. Korjenevsky, V. Cherepenin, and S. Sapetsky, “Magnetic induction tomography: Experimental realization,” Physiol. Meas., vol. 21, no. 1, pp. 89–91, Feb. 2000. [4] A. J. Peyton et al., “An overview of electromagnetic inductance tomography: Description of three different systems,” Meas. Sci. Technol., vol. 7, no. 3, pp. 261–271, Mar. 1996. [5] H.-Y. Wei, L. Ma, and M. Soleimani, “Volumetric magnetic induction tomography,” Meas. Sci. Technol., vol. 23, no. 5, pp. 1–9, 2012. [6] M. Zolgharni, H. Griffiths, and P. D. Ledger, “Frequency-difference MIT imaging of cerebral haemorrhage with a hemispherical coil array: Numerical modelling,” Physiol. Meas., vol. 31, no. 8, pp. S111–S125, Jul. 2010. [7] E. L. Bronaugh, “Helmholtz coils for calibration of probes and sensors: Limits of magnetic field accuracy and uniformity,” in Proc. IEEE Int. Symp. Electromagn. Compat., Aug. 1995, pp. 73–76. [8] S. R. Trout, “Use of Helmholtz coils for magnetic measurements,” IEEE Trans. Magn., vol. 24, no. 4, pp. 2108–2111, Jul. 1988. [9] J. Canny, “A computational approach to edge detection,” IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-8, no. 6, pp. 679–698, Nov. 1986. [10] R. Deriche, “Using Canny’s criteria to derive a recursively implemented optimal edge detector,” Int. J. Comput. Vis., vol. 1, no. 2, pp. 167–187, Jun. 1987. [11] J. Canny, “Finding edges and lines in images,” M.S. thesis, Artif. Intell. Lab., Massachusetts Inst. Technol., Cambridge, MA, USA, 1983, pp. 81–83. [12] H.-Y. Wei and M. Soleimani, “A magnetic induction tomography system for prospective industrial processing applications,” Chinese J. Chem. Eng., vol. 20, no. 2, pp. 406–410, 2012. [13] L. Ma, H.-Y. Wei, and M. Soleimani, “Planar magnetic induction tomography for 3D near subsurface imaging,” Prog. Electromagn. Res., vol. 138, pp. 65–82, 2013.