optimized-setup-protocol-for-magnetic-domain-imaging-with-situ

Optimized Setup and Protocol for Magnetic Domain Imaging with <em>In Situ</em> Hysteresis Measurement

This paper elaborates the sample preparation protocols required to obtain optimal domain patterns using the Bitter method, focusing on the extra steps ...

University of Manchester

Magnetic induction tomography (MIT) is a noninvasive modality for imaging the complex conductivity (kappa = sigma + jomegaepsilon) or the magnetic permeability (mu) of a target under investigation. Because MIT employs noncontact coils for excitation and detection, MIT may be suitable for imaging biological tissues. In medical applications where high resolutions are sought, image reconstruction is a time and memory consuming task because the associated inverse problem is nonlinear and ill-posed. The time and memory constraints are mainly imposed by the solution of the forward problem within the iterative image reconstruction procedure. This paper investigates the application of a weakly coupled approximation to the solution of the forward problem and examines the accuracy against the computation time and memory gained in adopting this approximation. Initially, an analytical solution for mutual impedance change of a coil pair due to a large planar conductive object is presented based on a full wave theory and used to demonstrate a 10 MHz frequency excitation as an acceptable upper frequency limit under which the approximation is valid. Subsequently, a numerical impedance method adopting the approximation is presented. Here the impedance method is used to solve the forward problem, which employs electrical circuit analogues to mesh the target into a network that can be solved using circuit analysis and sparse matrix technique. The error due to the approximation is further estimated numerically with the impedance method against a commercial finite-element package (commercial FE solver, COMSOL) and results show at 10 MHz excitation a 0.4% of tolerance is achieved for conductivities in the range <0.5 S/m. The results also show the method can be applied for low conductivity medical applications and is computationally efficient compared to equivalent finite-element methods.

A method to solve the forward problem in magnetic induction tomography based on the weakly coupled field approximation.

This paper presents a method which combines electromagnetic simulation and ultrasonic simulation to build EMAT array models. For a specific sensor configuration, Lorentz forces are calculated using the finite element method (FEM), which then can feed through to ultrasonic simulations. The propagation of ultrasound waves is numerically simulated using finite-difference time-domain (FDTD) method to describe their propagation within homogenous medium and their scattering phenomenon by cracks. Radiation pattern obtained with Hilbert transform on time domain waveforms is proposed to characterise the sensor in terms of its beam directivity and field distribution along the steering angle.

Simulation of ultrasonic and EMAT arrays using FEM and FDTD.

The detection of bubbles in liquid metals is important for many technical applications. The opaqueness and the high temperature of liquid metals set high demands on the measurement system. The high electrical conductivity of the liquid metal can be exploited for contactless methods based on electromagnetic induction. We will present a measurement system which consists of one excitation coil and a pickup coil system on the opposite sides of the pipe. With this sensor we were able to detect bubbles in a sodium flow inside a stainless steel pipe and bubbles in a column filled with a liquid Gallium alloy.

Article	Year
A method to solve the forward problem in magnetic induction tomography based on the weakly coupled field approximation. IEEE transactions on bio-medical engineering\| PubMed ID: 19932988	2010
Simulation of ultrasonic and EMAT arrays using FEM and FDTD. Ultrasonics\| PubMed ID: 26596420	2016
Contactless Inductive Bubble Detection in a Liquid Metal Flow. Sensors (Basel, Switzerland)\| PubMed ID: 26751444	2016

Anthony Peyton

Biography

JoVE Journal Publications

Other Publications