ABSTRACT
Recycling aluminium is essential for a circular economy, reducing the energy required and greenhouse gas emissions compared to extraction from virgin ore. A 'Twitch' waste stream is a mix of shredded wrought and cast aluminium. Wrought must be separated before recycling to prevent contamination from the impurities present in the cast. In this paper, we demonstrate magnetic induction spectroscopy (MIS) to classify wrought from cast aluminium. MIS measures the scattering of an oscillating magnetic field to characterise a material. The conductivity difference between cast and wrought makes it a promising choice for MIS. We first show how wrought can be classified on a laboratory system with 89.66% recovery and 94.96% purity. We then implement the first industrial MIS material recovery solution for sorting Twitch, combining our sensors with a commercial-scale separator system. The industrial system did not reflect the laboratory results. The analysis found three areas of reduced performance: (1) metal pieces correctly classified by one sensor were misclassified by adjacent sensors that only captured part of the metal; (2) the metal surface facing the sensor can produce different classification results; and (3) the choice of machine learning algorithm is significant with artificial neural networks producing the best results on unseen data.
ABSTRACT
This paper studies the use of electromagnetic induction in localization of wireless capsule endoscopes (WECs). There is still currently a need for an accurate localization system to enable localizing possible findings in the gastrointestinal tract, and to develop an active steering system for the capsule. Developing an optimal localization system requires the sensitivity of the system to be analyzed. In this paper, three different coil geometries are modelled with a computer simulation platform, and their sensitivities and target responses are compared. In order to do that, a formulation for the sensitivity based on the dipole model approximation is presented. The first coil array is based on literature and is used as a reference. The second array presents how having more transmit-receive channels in the array effects the sensitivity. The third coil array simulates the effect of increasing the field excitation intensity in different directions by using a three-axial Helmholtz array. In addition, both proposed coil arrays utilize larger coils than the reference. As a result, it seems that both increasing the coil size and the number of field projections interrogating the target increase the overall sensitivity in the region of interest and the target response. The findings suggest that an optimal coil array could utilize both large coils and multiple transmit-receive channels to increase the number of independent fields incident onto the target.
Subject(s)
Capsule Endoscopes , Magnetic Resonance Imaging , Computer Simulation , Equipment Design , Magnetic Resonance Imaging/methods , Radio WavesABSTRACT
Antennas are an important component in ground penetrating radar (GPR) systems. Although there has been much research reported on the design of individual antennas, there is less research reported on the design of the geometry of bi-static antennas. This paper considers the effects of key parameters in the setup of a GPR head consisting of a bi-static bow-tie pair to show the effect of these parameters on the GPR performance. The parameters investigated are the antenna separation, antenna height above the soil, and antenna input impedance. The investigation of the parameters was performed by simulation and measurements. It was found when the bi-static antennas were separated by 7 cm to 9 cm and were operated close to the soil (2 cm to 4 cm), the reflected signal from a near-surface object is relatively unaffected by height variation and object depth. An antenna input impedance of 250 Ω was chosen to feed the antennas to reduce the late-time ringing. Using these results, a new GPR system was designed and then evaluated at a test site near Benkovac, Croatia.
ABSTRACT
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.
