Abstract
Demodulation is a crucial step in signal processing for electromagnetic tomography (EMT) systems. Impulse noise appears in EMT, in particular, when excitation current is switched from one coil to another. This is mainly a result of the fact that the discontinuity of current creates voltage spikes due to back electromotive force. This paper proposes a novel clustering-based method for reducing this impulsive noise on the basis of Kalman filter demodulation. The Kalman filter is capable of demodulating the multiplexing signal reclusively, but it introduces dynamic oscillations at the same time. The proposed clustering method is able to successfully separate the signal from the impulse noise and smoothen the dynamic oscillations after demodulation. Simulation and experimental results show that the proposed clustering method can improve the signal-to-noise ratio by more than 20 dB in both the real and imaginary parts of EMT measurements. This technique is also useful in multi-channel coil systems where coil switching is necessary.
Highlights
Electromagnetic tomography (EMT) is an imaging modality for industrial process monitoring and medical imaging, which has been intensively studied and developed due to its low-cost, non-destructive, non-invasion, and convenient nature.1–4 Generally, EMT has been widely used in the industrial processes such as imaging the conductive fluid,8,9 measuring the multi-phase flow,7,10,11 and for metallic object imaging.2,12,13 In addition, it is sensitive to all three passive electromagnetic properties: conductivity, permittivity, and permeability.5–7 An EMT system applies an alternating current in the sensor array, which produces a primary magnetic field B in the region of interest
The customized EMT system is based on a field programmable gate array (FPGA) and includes conditioning electronics for excitation, detection, multiplexing, and analogue-to-digital (AD) and digitalto-analogue (DA) conversion
An eight-coil sensor array is applied in the EMT system
Summary
Electromagnetic tomography (EMT) is an imaging modality for industrial process monitoring and medical imaging, which has been intensively studied and developed due to its low-cost, non-destructive, non-invasion, and convenient nature. Generally, EMT has been widely used in the industrial processes such as imaging the conductive fluid, measuring the multi-phase flow, and for metallic object imaging. In addition, it is sensitive to all three passive electromagnetic properties: conductivity, permittivity, and permeability. An EMT system applies an alternating current in the sensor array, which produces a primary magnetic field B in the region of interest. An EMT system applies an alternating current in the sensor array, which produces a primary magnetic field B in the region of interest. The resultant magnetic field B + ΔB is measured by a set of coils around the imaging area. The coils in the sensor array are excited in turn to generate the primary field, and a set of measurements can be obtained from the detection coils to form an EMT data frame. These signals at different coil pairs are used after the demodulation for the reconstruction of cross-sectional image in terms of the conductivity and/or permeability.
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