Submerged Arc Welding (SAW) for fillet joints is one of the major applications in the shipbuilding industry. Due to the requirement for the weld size, a sufficient amount of metal must be deposited. In conventional SAW process, the heat input is proportional to the amount of metal melted and is thus determined by the required weld size. To meet this requirement, an excessive amount of heat is applied causing large distortions on the welded structures whose follow-up straightening is highly costly. In order to reduce the needed heat input, Double-Electrode (DE) technology has been practiced creating the Double-Electrode SAW (DE-SAW) method for fillet joints. The reduction in the heat input, however, also reduces the penetration capability of the process, and the ability to produce required weld beads has to be compromised. To eliminate the unwanted side effect after using DE-SAW, a root opening between the panel and the tee has been proposed in this dissertation to form a modified fillet joint design. Experimental results verified that the use of root opening improves the ability of DE-SAW to produce the required weld beads at reduced heat input and penetration capability. Unfortunately, the use of root opening decreases the stability of the process significantly. To control the heat input at a minimally necessary level that guarantees the weld size and meanwhile the process stability, a feedback is needed to control the currents at their desired levels. To this end, the fillet DE-SAW process is modeled and a multivariable predictive control algorithm is developed based on the process model. Major parameters including the root opening size, travel speed and heat input level have been selected/optimized/minimized to produce required fillet weld beads with a minimized heat input based on qualitative and quantitative analyses. At the end of this dissertation, a series of experiments validated the feasibility and repeatability of the predictive control based DE-SAW process for fillet joints with root opening.

Combining human welder (with intelligence and sensing versatility) and automated welding robots (with precision and consistency) can lead to next generation intelligent welding systems. In this dissertation intelligent welding robots are developed by process modeling / control method and learning the human welder behavior. Weld penetration and 3D weld pool surface are first accurately controlled for an automated Gas Tungsten Arc Welding (GTAW) machine. Closed-form model predictive control (MPC) algorithm is derived for real-time welding applications. Skilled welder response to 3D weld pool surface by adjusting the welding current is then modeled using Adaptive Neuro-Fuzzy Inference System (ANFIS), and compared to the novice welder. Automated welding experiments confirm the effectiveness of the proposed human response model. A virtualized welding system is then developed that enables transferring the human knowledge into a welding robot. The learning of human welder movement (i.e., welding speed) is first realized with Virtual Reality (VR) enhancement using iterative K-means based local ANFIS modeling. As a separate effort, the learning is performed without VR enhancement utilizing a fuzzy classifier to rank the data and only preserve the high ranking “correct” response. The trained supervised ANFIS model is transferred to the welding robot and the performance of the controller is examined. A fuzzy weighting based data fusion approach to combine multiple machine and human intelligent models is proposed. The data fusion model can outperform individual machine-based control algorithm and welder intelligence-based models (with and without VR enhancement). Finally a data-driven approach is proposed to model human welder adjustments in 3D (including welding speed, arc length, and torch orientations). Teleoperated training experiments are conducted in which a human welder tries to adjust the torch movements in 3D based on his observation on the real-time weld pool image feedback. The data is off-line rated by the welder and a welder rating system is synthesized. ANFIS model is then proposed to correlate the 3D weld pool characteristic parameters and welder’s torch movements. A foundation is thus established to rapidly extract human intelligence and transfer such intelligence into welding robots.

Power electronic systems have been widely used in the electrical power processing for applications with power levels ranging from less than one watt in battery-operated portable devices to more than megawatts in the converters, inverters and rectifiers of the utility power systems. These systems typically involve the passive elements such as inductors, capacitors, and resistors, the switching electronic components such as IGBTs, MOSFETS, and diodes, and other electronic circuits. Multifrequency averaging is one of the widely used modeling and simulation techniques today for the analysis and design of power electronic systems. This technique is capable of providing the average behavior as well as the ripple behavior of power electronic systems. This work begins with the extension of multifrequency averaging to represent uniformly sampled PWM converters. A new multifrequency averaging method of solving an observed issue with model stability is proposed and validated. Multifrequency averaging can also be applied to study the instability phenomenon in power electronic systems. In particular, a reduced-order multifrequency averaging method, along with a genetic algorithm based procedure, is proposed in this work to estimate the regions of attraction of power electronic converters. The performance of this method is shown by comparing the accuracy and efficiency with the existing methods. Finally, a new continuous-time multifrequency averaging method of representing discrete-time systems is proposed. The proposed method is applied to model digitally controlled PWM converters. Simulation and hardware results show that the proposed method is capable of predicting the average behavior as well as the ripple behavior of the closed-loop systems. Future research in the area of multifrequency averaging is proposed.

The output power variability of intermittent renewable sources can cause significant fluctuations in distribution system voltages. A local linear controller that exploits the capability of a photovoltaic inverter to provide both real and reactive power is described. This controller substitutes reactive power for real power when fluctuations in the output of the photovoltaic source are experienced. In this way, the inverter can help mitigate distribution system voltage fluctuations. In order to provide real and reactive to the grid, a three-phase grid-connected single-stage photovoltaic system with maximum power point tracking and power control is described. A method of reducing the current harmonic caused by resonance of the LC filter and transformer is presented. The local linear controller is examined using an example distribution system, and it is found that the controller is effective at mitigating voltage violations. The photovoltaic control system is examined using three-phase single-stage PV inverter system. The power control and damping system show good performance and stability under rapid change of irradiance.

RFID has been characterized as a “disruptive technology” that has the potential to revolutionize numerous key sectors. A key advantage of passive RFID applications is the ability to wirelessly transmit automatic identification and related information using very little power. This paper presents an experimental investigation to inform the optimal configuration for programming passive ultra-high frequency (UHF) RFID media in dynamic applications. Dynamic programming solutions must be designed around the tag’s functionality, the physical programming configuration and environment. In this investigation, we present a methodology to determine an optimal configuration to maximize the systems programming efficiency for dynamic applications.

Humidity measurement has been increasingly important in many industries and process control applications. This thesis research focus mainly on humidity sensor calibration and characterization. The humidity sensor instrumentation is briefly described. The testing infrastructure was designed for sensor data acquisition, in order to compensate the humidity sensor’s temperature coefficient, temperature chambers using Peltier elements are used to achieve easy-controllable stable temperatures. The sensor characterization falls into a multivariate interpolation problem. Neuron networks is tried for non-linear data fitting, but in the circumstance of limited training data, an innovative algorithm was developed to utilize shape preserving polynomials in multiple planes in this kind of multivariate interpolation problems.

This dissertation examines probation for young people in Canada. Ninety percent of all young people sentenced in Canada receive a non-custodial or community sentence, with probation accounting for the majority (91%) of community supervision admissions (Munch, 2012). However, little is actually known about the judicial use of probation, the conditions that are imposed as a part of this sentence and, more importantly, what factors are associated with breaches of probation. Breaches of probation, have historically been and continue to be significant pathways back into the youth justice system, especially incarceration. Using informal social control theory (wider social processes – family, school and peers) and an integrated sites of oppression lens (an analysis of marginalized populations) this research explores the factors that influence the nature and extent of probation sentences and if there is disparity in the use of probation sentences for female and Aboriginal youth. This dissertation reports on a province-wide investigation of a sample of all Ontario youth sentenced to probation (N=6051) in 2005 and 2006, using data from the Ministry of Community Safety and Correctional Services and the Ministry of Children and Youth Services. This research also explores a sub-sample of youth on probation who were charged with breach of probation (N=255) during the period of study. It appears judges use probation conditions as a means to mitigate informal social controls that may cause delinquency (e.g. poor parenting, school failure, delinquent peers). Little support was found for the hypotheses that girls would receive particular conditions (curfews, residence orders, non-association orders) because of gender bias. Girls were more likely to receive shorter sentences of probation, which is interesting given that they are more likely to be given probation for violent offences. An examination into the impact of race on probation sentences revealed the need for further investigation into judicial decision making with non-custodial sentences. Results of the analysis of the breach of probation data indicate that regardless of the commission of a new offence (in addition to a breach or breaches of probation) non-compliance with previous dispositions, like probation, remains a significant pathway back into the youth justice system. Girls, younger youth and Aboriginal youth are all more likely to be charged with breach of probation. Breaching conditions of probation may be unrelated to the original offence (for which the young person received probation) and may be connected to wider concerns about protection and social control. Marginalized youth, in particular, who breach probation, are significantly more likely to be charged by police and receive custody. The aim of this dissertation is to provide a comprehensive understanding of probation and probation violations and broaden the scope of our knowledge of probation. This research adds both empirically and theoretically to the current body of research on youth sentencing in Canada.

This dissertation aims at developing techniques to achieve high power density in motor drives under the performance requirements for transportation system. Four main factors influencing the power density are the main objects of the dissertation: devices, passive components, pulse width modulation (PWM) methods and motor control methods. Firstly, the application of SiC devices could improve the power density of the motor drive. This dissertation developed a method of characterizing the SiC device performance in phase-leg with loss estimation, and claimed that with SiC Schottky Barrier Diode the advantage of SiC JFET could benefit the motor drive especially at high temperature. Then the design and improvement of the EMI filter in the active front-end rectifier of the motor drive was introduced in this dissertation. Besides the classical filter design method, the parasitic parameters in the passive filter could also influence the filtering performance. Random PWM could be applied to reduce the EMI noise peak value. The common-mode (CM) noise reduction by PWM methods is also studied in this dissertation. This dissertation compared the different PWM methods’ CM filtering performance. Considering the CM loop, the design of PWM methods and switching frequency should be together with the CM impedance. Variable switching frequency PWM (VSFPWM) methods are introduced in the dissertation for the motor drive’s EMI and loss improvement. The current ripple of the three-phase converter could be predicted. Then the switching frequency could be designed to adapt the current ripple requirements. Two VSFPWM methods are introduced to satisfy the ripple current peak and RMS value requirements. For motor control issue, this dissertation analyzed the principle of the start-up transient and proposed an improved start-up method. The transient was significantly reduced and the motor could push to high speed and high power with speed sensorless control. Next, the hardware development of modular motor drive was introduced. The development and modification of 10kW phase-legs and full power test of a typical 30kW modular converter is realized with modular design method. Finally, the techniques developed in this dissertation for high power density motor drive design and control are summarized and future works are proposed.

This thesis presents an analysis of the characteristics of malfunction flash incidents based on the Georgia Department of Transportation crash reporting database. Malfunction flash is an unintentional state of flash mode in intersection signal hardware. The flash mode is a signal indication of yellow/red or red/red flash. The flash mode can be due to many issues, such as hardware failure, damage, or storms. Crash reports are completed by police officers at the scene. After processing by the local jurisdiction reports are sent to GDOT for archiving and analysis. GDOT archives the reports in a PDF image format without editable text. This research will develop a procedure to convert the archived PDF reports to text files using optical character recognition (OCR) software. The developed procedure will extract the description paragraph of the incident from the PDF. The extracted descriptions may then be searched for useful information about the incident. The text files will be run through a filter for keywords, such as; "malfunction flash," "red/red flash," "yellow/red flash," and others. Incidents flagged by the keywords will be reexamined to determine if they are malfunction flash incidents. The 2006 GDOT incident data base will be used for this effort. From an original possible candidate list of 70,000 signalized intersection incidents malfunction incidents will be identified using this method. A statistical analysis will be completed seeking trends and important characteristics of malfunction incidents.

Thesis (M. Soc. Sc.)--University of Hong Kong, 1996. / Includes bibliographical references (leaf 119-126).