Power electronics possess forms of non-ideality due to the nonlinearity present in physical switches. These switches are driven with pulse width modulation (PWM), which properly down-converts or up-converts based on converter topology. When these switches turn on or off, they introduce the main proponent of efficiency loss: harmonics. This becomes a nonlinear optimization problem with many converters. The solution proposed in this thesis is an analog/digital hybrid computer that utilizes the speed of analog computation and the accuracy of digital computing together. A Plexim RT Box provides the programmability needed for algorithms, while the analog circuit provides low-power, high-speed computation in order to provide the proper switching angle to minimize harmonics. This study explores optimization techniques for PWM harmonic elimination by implementing a hybrid computer that simulates harmonics and calculates solutions to the nonlinear optimization problem. Specifically, the analog computer handles the gradient flow dynamics of harmonic elimination by utilizing nonlinear programming and the KKT conditions. The analog computer is optimized by exploring higher-slew-rate operational amplifiers and observing their effects on convergence. All results are consistently compared to an LTSpice simulation to ensure the accuracy and stability of the physical analog computer.

The objective of this PhD research is to develop robust, and non-intrusive condition monitoring methods for induction motors fed by closed-loop inverters. The flexible energy forms synthesized by these connected power electronic converters greatly enhance the performance and expand the operating region of induction motors. They also significantly alter the fault behavior of these electric machines and complicate the fault detection and protection. The current state of the art in condition monitoring of power-converter-fed electric machines is underdeveloped as compared to the maturing condition monitoring techniques for grid-connected electric machines. This dissertation first investigates the stator turn-to-turn fault modelling for induction motors (IM) fed by a grid directly. A novel and more meaningful model of the motor itself was developed and a comprehensive study of the closed-loop inverter drives was conducted. A direct torque control (DTC) method was selected for controlling IM’s electromagnetic torque and stator flux-linkage amplitude in industrial applications. Additionally, a new driver based on DTC rules, predictive control theory and fuzzy logic inference system for the IM was developed. This novel controller improves the performance of the torque control on the IM as it reduces most of the disadvantages of the classical and predictive DTC drivers. An analytical investigation of the impacts of the stator inter-turn short-circuit of the machine in the controller and its reaction was performed. This research sets a based knowledge and clear foundations of the events happening inside the IM and internally in the DTC when the machine is damaged by a turn fault in the stator. This dissertation also develops a technique for the health monitoring of the induction machine under stator turn failure. The developed technique was based on the monitoring of the off-diagonal term of the sequence component impedance matrix. Its advantages are that it is independent of the IM parameters, it is immune to the sensors’ errors, it requires a small learning stage, compared with NN, and it is not intrusive, robust and online. The research developed in this dissertation represents a significant advance that can be utilized in fault detection and condition monitoring in industrial applications, transportation electrification as well as the utilization of renewable energy microgrids. To conclude, this PhD research focuses on the development of condition monitoring techniques, modelling, and insightful analyses of a specific type of electric machine system. The fundamental ideas behind the proposed condition monitoring technique, model and analysis are quite universal and appeals to a much wider variety of electric machines connected to power electronic converters or drivers. To sum up, this PhD research has a broad beneficial impact on a wide spectrum of power-converter-fed electric machines and is thus of practical importance.

Thesis (M. Soc. Sc.)--University of Hong Kong, 1990.

Thesis (M.Soc.Sc.)--University of Hong Kong, 1990. / Also available in print.

The determination of magnetohydrostatic equilibria usually requires that two of the equilibrium functions be given. as there is usually no a priori basis for specifying the form of these two functions, the functions and the equilibria they determine may be considered random.;In this dissertation, the author reviews a recent statistical method for determining the equilibrium of an axially symmetric cylindrical plasma which is most probable (in the maximum entropy sense) given four global constraints (i.e., energy, magnetic helicity, longitudinal magnetic flux, and longitudinal current flux). Previous results from this model have been limited to non-negative random equilibrium functions (B(,z), J(,z), where B is the magnetic field and J is the current density), and to analytically derived solutions of the determining equations in which one constraint (magnetic helicity) has been relaxed.;The present work extends these results to the fully constrained problem by presenting numerically computed solutions of the governing equations. Some of these solutions are specialized to values of the constraints appropriate to tokamaks. States which are approximately force-free (B = J x const.) are shown to exist as solutions to the most probable state equations.;A further extension of the model is attempted in order to alleviate the restriction to non-negative random equilibrium functions. The extended model is applied to the problem of finding most probable equilibria with reversed magnetic fields. An examination of solutions constrained to different values of energy and magnetic helicity shows a tendency toward low pressure equilibria when the energy-to-helicity ratio is lowered. This result is consistent with the Bessel function model of reverse-field equilibria in which dynamical relaxation of the energy with respect to a fixed magnetic helicity results in pressureless, Bellel function equilibria.;A study is made of the influence of the pinch ratio, an experimental parameter, on the degree of magnetic field reversal in the most probable state model. The dependence of solutions on this parameter is found to be consistent qualitatively with experiments.

No description available.

No description available.

Measurement of heat flux is required in many aerospace and heat treatment applications. Temperature data collected at embedded sites are noisy especially when measurements are taken in hostile environments. The predicted heat flux, when based on the rate of change of temperature, is more accurate than using temperature data as the latter data form is ill-posed. In the context of heat flux prediction, calculating the rate of change of temperature involves differentiation, which is the primary source of ill-posed effects. This work involves developing a universal voltage rate sensor interface that minimizes these effects and also improves the signal-to-noise ratio. This is based on the concept of amplitude modulating the temperature data and differentiating it at a higher frequency. The proposed concept of improvement in signal-to-noise ratio was verified by the Matlab and PSpice simulations. The experimental outputs matched the simulations results.

Thesis (D. Bus. Admin.)--Southern Cross University, 2007. / Title from PDF t.p. (viewed on Mar. 11, 2007). Includes bibliographical references (p. 178-194).

Thesis (M.S.)--Oregon State University, 2010. / Printout. Includes bibliographical references (leaves 49-50). Also available on the World Wide Web.