In the human brain, electrical activities are created due to the body functions. These electrical activities create potentials and magnetic fields which can be monitored elec- trically (Electroencephalography - EEG) or magnetically (Magnetoencephalography - MEG). Electrical activities in human brain are usually modeled by electrical dipoles. The purpose of Electro-magnetic source imaging (EMSI) is to determine the position, orientation and strength of dipoles. The first stage of EMSI is to model the human head numerically. In this study, The Finite Element Method (FEM) is chosen to han- dle anisotropy in the brain. The second stage of EMSI is to solve the potentials and magnetic fields for an assumed dipole configuration (forward problem). Realistic con- ductivity distribution of human head is required for more accurate forward problem solutions. However, to our knowledge, conductivity distribution for an individual has not been computed yet. The aim of this thesis study is to investigate the feasibility of a new approach to update the initially assumed conductivity distribution by using the evoked potentials and fields acquired during EMSI studies. This will increase the success of source localization problem, since more realistic conductivity distribution of the head will be used in the forward problem. This new method can also be used as a new imaging modality, especially for inhomogeneities where the conductivity value deviates. In this thesis study, to investigate the sensitivity of measurements to conductivity perturbations, a FEM based sensitivity matrix approach is used. The performance of the proposed method is tested using three different head models - homogeneous spherical, 4 layer concentric sphere and realistic head model. For spherical head models rectangular grids are preferred in the middle and curved elements are used nearby the head boundary. For realistic cases, head models are developed using uniform grids. Tissue boundary information is obtained by applying segmentation algorithms to the Magnetic Resonance (MR) images. A paralel computer cluster is employed to assess the feasibility of this new approach. PETSc library is used for forward problem calculations and linear system solutions. The performance of this novel approach depends on many factors such as the head model, number of dipoles and sensors used in the calculation, noise in the measure- ments, etc. In this thesis study, a number of simulations are performed to investigate the effects of each of these parameters. Increase in the number of elements in the head model leads to the increase in the number of unknows for linear system solu- tions. Then, accuracy of the solution is improved with increased number of dipoles or sensors. The performance of the adopted approach is investigated using noise-free measurements as well as noisy measurements. For EEG, measurement noise decreases the accuracy of the approach. For MEG, the effect of measurement noise is more pronounced and may lead to a larger error in tissue conductivity calculation.

In industrial drives market, speed and position estimation are one of the most important subjects for accurate motor drives. Vector controlled drives has the best dynamic performance among AC motor drives. Sensorless vector control is one of the most studied one. However, sensorless drive systems fail at low or zero speeds and may not have enough accuracy. For better accuracy and speed range speed sensors or position encoders are usually essential. However, coupling of sensor and sensor prices introduces extra cost on the drive. Thus in order to reduce the cost of the drive a cheap and easy to mount speed sensor is essential. Throughout this study, a speed and position sensor using an external search coil placed between cooling fins on the frame of an induction machine is proposed. The search coil utilizes the fringing flux outside the frame of induction motor. Using the induced voltage on the external search coil, a new method that estimates the flux and rotor position is proposed. In this study, the induced voltage on the search coils are investigated with different types of search coils placed on various positions. The frequency domain and time domain analysis are performed in order to build a model that can estimate machine flux, rotor speed and rotor position. As a result of this study, a low cost, easy to mount speed and position sensor is designed and implemented. Experiment results are presented.

The study involves the following stages: First, coupled-inductor and integrated magnetic structure used in Cuk converter circuit topologies are analyzed and the necessary information about these elements in circuit design is gathered. Also, benefits of using these magnetic elements are presented. Secondly / steady-state model, dynamic model and transfer functions of coupled-inductor Cuk converter topology are obtained via state-space averaging method. Third stage deals with determining the design criteria to be fulfilled by the implemented circuit. The selection of the circuit components and the design of the coupled-inductor providing ripple-free input current waveform are performed at this stage. Fourth stage introduces the experimental results of the implemented circuit operating in open loop mode. Besides, the controller design is carried out and the closed loop performance of the implemented circuit is presented in this stage.

Magnetic resonance imaging (MRI) is a high resolution medical imaging technique based on distinguishing tissues according to their nuclear magnetic properties. Magnetic resonance electrical impedance tomography (MREIT) is a conductivity imaging technique which reconstructs images of electrical properties, based on their effect on induced magnetic flux density due to externally applied current flow. Both of these techniques are of interest for novel research and development. Simulators help researchers observe the accuracy and the results of the study. In this study a user friendly complete MRI/MREIT simulator is designed. This simulator is the combination of improved version of MRI simulator (implemented by V. E. Arpinar, H. Yigitler), a forward solver, to observe the current injection effect, the improved version of user interface that is designed on LabVIEW graphical programming environment (designed by M. Ozsut), and equi-potential projection (EPP) reconstruction algorithm (proposed by M. S. Ozdemir, M. Eyuboglu, O. Ozbek). All of these individual parts are improved and gathered in LabVIEW environment in order to work in synchrony. In addition to that, regional image reconstruction technique (proposed by H. Altunel, M. Eyuboglu) is also included in the simulator. The simulator is run for various inputs and system specifications. It is observed that the simulation results are consistent with the expected results for MRI, MREIT and conventional/regional MREIT reconstruction. Four different models are designed and results are obtained using these models. The accuracy of the results usually differs with the input parameters and model geometry. Validating numerically the accuracy of the forward solution part using Biot-Savart and Ampere&#039 / s laws, the consistency of the forward problem solution part is obtained at a percentage of 95%. In the MREIT part, magnetic flux density distribution taken from forward solver part is added to the main magnetic flux density used in the MRI part. Consistency of the magnetic flux density distribution given to the simulator as input and the output taken from the MREIT part of the simulator is found as 99%. In addition to conventional EPP algorithm, regional MREIT reconstruction algorithm is applied for various noise levels. It is observed that, as the noise level increases, regional MREIT reconstruction algorithm gives relatively much better results compared to conventional MREIT reconstruction algorithm. Errors obtained by applying conventional reconstruction and regional reconstruction are compared for each inhomogeneity individually. Therefore, accuracies of the different current patterns depending on the inhomogeneities are observed as well.

A multi-frequency data acquisition system is realized for subsurface conductivity imaging of biological tissues. The measurement procedures of the system at different frequencies are same. The only difference between the single frequency experiments and the multi-frequency experiments is the hardware, i.e. the sensor and the power amplifier used in the single frequency experiments was different than that were used in the multi-frequency experiments. To avoid confusion the measurement system with which the single frequency experiments were performed is named as prototype system and the measurement system with which the multi-frequency experiments were performed is named as multi-frequency system. This system uses magnetic excitation (primary field) to induce eddy currents inside the conductive object and measures the resulting magnetic field due to eddy currents (secondary field). For this purpose, two differential-coil sensors are constructed / one is for the single frequency measurements and the other is for the multi-frequency measurements. Geometrically the coils are same, the only difference between them is the radius of the wires wound on them. The sensor consists of two differentially connected identical receiver coils employed to measure secondary field and in between the receiver coils is placed a transmitter coil, which creates the primary field. The coils are coaxial. In the prototype system the transmitter coil is driven by a sinusoidal current of 300 mA (peak) at 50 kHz. In the multi-frequency system the transmitter coil is driven by a sinusoidal current of 217 mA (peak), 318 mA (peak), 219 mA (peak) and 211 mA (peak) at 30 kHz, 50 kHz, 60 kHz and 90 kHz, respectively. A data acquisition card (DAcC) is designed and constructed on a printed circuit board (PCB) for phase sensitive detection (PSD). The equivalent input noise voltage of the card was found as $146.80 hspace{0.1 cm}nV$. User interface programs (UIP) are prepared to control the scanning experiments via PC (HP VEE based UIP, LabVIEW based UIP) and to analyze the acquired data (MATLAB based UIP). A novel sensitivity test method employing resistive ring phantoms is developed. A relation between the classical saline solution filled vessel (45mm radius, 10 mm depth) phantoms and the resistive ring phantoms is established. The sensitivity of the prototype system to saline solutions filled vessels is 13.2 $mV/(S/m)$ and to resistive rings is 155.02 mV/Mho while the linearity is 3.96$%$ of the full scale for the saline solution filled vessels and 0.12$%$ of the full scale for the resistive rings. Also the sensitivity of the multi-frequency system is determined at each operation frequency by using resistive ring phantoms. The results are in consistence with the theory stating that the measured signals are linearly proportional with the square of the frequency. The signal to noise ration (SNR) of the prototype system is calculated as 35.44 dB. Also the SNR of the multi-frequency system is calculated at each operation frequency. As expected, the SNR of the system increases as the frequency increases. The system performance is also tested with agar phantoms. Spatial resolution of the prototype system is found 9.36 mm in the point spread function (PSF) sense and 14.4 mm in the line spread function (LSF) sense. Spatial resolution of the multi-frequency system is also found at each operation frequency. The results show that the resolving power of the system to distinguish image details increases as the frequency increases, as expected. Conductivity distributions of the objects are reconstructed using Steepest-Descent algorithm. The geometries and the locations of the reconstructed images match with those of the real images. The image of a living tissue, a leech, is acquired for the first time in the literature. Magnetic conductivity spectroscopy of a biological tissue is shown for the first time in electrical conductivity imaging via contactless measurements. The results show the potential of the methodology for clinical applications.

Electrical and structural properties of Bismuth thin films were studied simultaneously. Electrical properties of the Bismuth thin films have been characterized by measuring temperature dependent conductivity and Hall effect. Structural analysis were carried out by X-ray diffraction technique and using a room temperature Atomic Force Microscope (RT-AFM).