All-fiber multireflector spectral filters which have potential application in optical communications have been investigated experimentally. These multireflector etalons were produced by aligning equal-length fiber sections with TiO2/SiO2 dielectric mirrors deposited on the end in a silicon v-groove. Fiber sections 1.33mm in length were produced by polishing, with the fibers held in a silicon wafer polishing jig. The fibers were aligned inside the polishing jig using a precision micro positioner. Then four polishing steps with increasingly finer grit were applied to produce high-quality polished end surfaces on each fiber section. Finally, a dielectric mirror was deposited on one end of each fiber section by magnetron sputtering. After characterizing the optical loss, length, and mirror reflectance for each of the fiber sections, sections which were well-matched in length were chosen for assembly of the four-mirror etalon, which had nominal reflectance values of 10%, 50%, 50%, and 10% for the dielectric mirrors. Measured transmittance spectra for a mutireflector spectral filter were compared with calculated spectra. Thermal tuning of the multireflector etalon was also investigated. A 0.34 nm wavelength shift was observed for a 23° C temperature change, in agreement with prediction. increasingly finer grit were applied to produce high-quality polished end surfaces on each fiber section. Finally, a dielectric mirror was deposited on one end of each fiber section by magnetron sputtering. After characterizing the optical loss, length, and mirror reflectance for each of the fiber sections, sections which were well-matched in length were chosen for assembly of the four-mirror etalon, which had nominal reflectance values of 10%, 50%, 50%, and 10% for the dielectric mirrors. Measured transmittance spectra for a mutireflector spectral filter were compared with calculated spectra. Thermal tuning of the multireflector etalon was also investigated. A 0.34 nm wavelength shift was observed for a 23° C temperature change, in agreement with prediction.

In response to energy crisis and power quality concerns, three different methodologies to integrate the concept of active filtering into the alternators are proposed. Wind energy, due to its free availability and its clean and renewable character, ranks as the most promising renewable energy resource that could play a key role in solving the worldwide energy crisis. An Integrated Doubly-fed Electric Alternator/Active filter (IDEA) for wind energy conversion systems is proposed. The proposed IDEA is capable of simultaneous capturing maximum power of wind energy and improving power quality, which are achieved by canceling the most significant and troublesome harmonics of the utility grid and power factor correction and reactive power compensation in the grid. The back-to-back current regulated power converters are employed to excite the rotor of IDEA. The control strategy of rotor-side power converter is based on position sensoreless field oriented control method with higher power density. Analysis and experimental results are presented to demonstrate the effectiveness of the proposed IDEA. In next step, an integrated synchronous machine/active filter is discussed. The proposed technology is essentially a rotating synchronous machine with suitable modification to its field excitation circuit to allow dc and ac excitations. It is shown that by controlling the ac excitation, the 5th and 7th harmonics currents of the utility are compensated. The proposed method is cost effective because it can be applied to existing standby generators in commercial and industrial plants with minimal modification to the excitation circuits. To boost the gain of harmonic compensatory, an advanced electric machine is proposed. An Asymmetric Airgap Concentrated Winding Synchronous Machine (AACWSM) with ac and dc excitation was designed and employed. It is shown that the AACWSM with its unique design, in addition to power generation capability, could be used to compensate the most dominant current harmonics of the utility. The proposed AACWSM can compensate for the 5th and 7th harmonics currents in the grid by controlling the ac field excitation. In addition, the 11th and 13th harmonics currents are also significantly reduced. This system can be used at medium and low voltages for generation or motoring mode of operation.

Anionic surfactants are wildly used in many industrial and household applications. Because anionic surfactants are used so widely, significant attention has focused on the removal of these contaminants from wastewater. Among various treatment techniques, biofiltration, such as trickling filter technologies, has been employed in many wastewater treatment plants (WWPTs) to remove anionic surfactants. However, current knowledge of the efficacy of trickling filter to remove anionic surfactants from wastewaters is limited. The present study characterized the performance of a high rate (i.e. roughing) trickling filter to remove anionic surfactants both at lab-scale and pilot-scale. Lab-scale tests investigated the biodegradation of anionic surfactants under controllable conditions were compared with those from previous studies by others. Pilot-scale tests investigated the efficacy of a trickling filter at removing anionic surfactants from a wastewater over an extended period of time. The data from the pilot-scale tests were used to model the performance of trickling filter at removing anionic surfactants from the wastewater, using first order and modified Velz models. The lab-scale tests indicated that high molecular weight anionic surfactants degrade faster than the low molecular weight surfactants. The biodegradation rates observed in the present study were similar to those from pervious studies by others. The pilot-scale tests indicated that roughing trickling filter could remove 11% to 29% of anionic surfactants and 4% to 22% of COD from the wastewater. Higher molecular weight anionic surfactants were more degradable. The experimental data could be accurately modeled using the modified Velz model (R² value more than 0.9). The degradation rates of modified Velz model for total anionic surfactants, high molecular weight anionic surfactants and COD were 0.053±0.0057, 0.088±0.0048 and 0.119±0.0111 (mIs)0.5 respectively. The pilot-scale test results indicated that a high rate (i.e., roughing) trickling filter was not capable of effectively removing anionic surfactants in the primary effluent at Lions Gate WWTP because a relatively large trickling filter area would be required to achieve the required surfactant removal efficiency.

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Analysing migrating cells in microscopy time-lapse images has already helped the understanding of many biological processes and may be of importance in the development of new medical treatments. Today’s biological experiments tend to produce a huge amount of dynamic image data and tracking the individual cells by hand has become a bottleneck for the further analysis work. A number of cell tracking methods have therefore been developed over the past decades, but still many of the techniques have a limited performance. The aim of this Master Project is to develop a particle filter algorithm that automatically detects and tracks a large number of individual cells in an image sequence. The solution is based on a Rao-Blackwellized particle filter for multiple object tracking. The report also covers a review of existing automatic cell tracking techniques, a review of well-known filter techniques for single target tracking and how these techniques have been developed to handle multiple target tracking. The designed algorithm has been tested on real microscopy image data of neutrophils with 400 to 500 cells in each frame. The designed algorithm works well in areas of the images where no cells touch and can in these situations also correct for some segmentation mistakes. In areas where cells touch, the algorithm works well if the segmentation is correct, but often makes mistakes when it is not. A target effectiveness of 77 percent and a track purity of 80 percent are then achieved.

Estimation theory is a branch of statistics and probability that derives information about random variables based on known information. In process engineering, state estimation is used for a variety of purposes, such as: soft sensing, digital filter design, model predictive control and performance monitoring. In literature, there exist numerous estimation algorithms. In this study, we provide guidelines for choosing the appropriate estimator for a system under consideration. Various estimators are compared and their advantages and disadvantages are highlighted. This has been done through case studies which use examples from process engineering. We also address certain robustness issues of application of estimation techniques to chemical processes. Choice of estimator in case of high plant-model mismatch has also been discussed. The study is restricted to unconstrained nonlinear estimators. / Process Control

We introduce Simultaneous Localization and Tracking (SLAT), the problem of tracking a target in a sensor network while simultaneously localizing and calibrating the nodes of the network. Our proposed solution, LaSLAT, is a Bayesian filter providing on-line probabilistic estimates of sensor locations and target tracks. It does not require globally accessible beacon signals or accurate ranging between the nodes. When applied to a network of 27 sensor nodes, our algorithm can localize the nodes to within one or two centimeters.

Anionic surfactants are wildly used in many industrial and household applications. Because anionic surfactants are used so widely, significant attention has focused on the removal of these contaminants from wastewater. Among various treatment techniques, biofiltration, such as trickling filter technologies, has been employed in many wastewater treatment plants (WWPTs) to remove anionic surfactants. However, current knowledge of the efficacy of trickling filter to remove anionic surfactants from wastewaters is limited. The present study characterized the performance of a high rate (i.e. roughing) trickling filter to remove anionic surfactants both at lab-scale and pilot-scale. Lab-scale tests investigated the biodegradation of anionic surfactants under controllable conditions were compared with those from previous studies by others. Pilot-scale tests investigated the efficacy of a trickling filter at removing anionic surfactants from a wastewater over an extended period of time. The data from the pilot-scale tests were used to model the performance of trickling filter at removing anionic surfactants from the wastewater, using first order and modified Velz models. The lab-scale tests indicated that high molecular weight anionic surfactants degrade faster than the low molecular weight surfactants. The biodegradation rates observed in the present study were similar to those from pervious studies by others. The pilot-scale tests indicated that roughing trickling filter could remove 11% to 29% of anionic surfactants and 4% to 22% of COD from the wastewater. Higher molecular weight anionic surfactants were more degradable. The experimental data could be accurately modeled using the modified Velz model (R² value more than 0.9). The degradation rates of modified Velz model for total anionic surfactants, high molecular weight anionic surfactants and COD were 0.053±0.0057, 0.088±0.0048 and 0.119±0.0111 (mIs)0.5 respectively. The pilot-scale test results indicated that a high rate (i.e., roughing) trickling filter was not capable of effectively removing anionic surfactants in the primary effluent at Lions Gate WWTP because a relatively large trickling filter area would be required to achieve the required surfactant removal efficiency. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate

The major application of active noise control (ANC) has been focused on using a single reference signal; the work on multiple reference ANC is very scarce. Here, the behavior of multiple reference ANC is analyzed in both the frequency and time domain, and the coherence functions are provided to evaluate the effectiveness of multiple reference ANC. When there are multiple noise sources, multiple reference sensors are needed to generate complete reference signals. A simplified method combines those signals from multiple reference sensors into a single reference signal. Although this method could result in satisfactory noise control effects under special circumstances, the performance is generally compromised. A widely adopted method feeds each reference signal into a different control filter. This approach suffers from the problem of ill-conditioning when the reference signals are correlated. The problem of ill-conditioning results in slow convergence rate and high sensitivity to measurement error especially when the FXLMS algorithm is applied. To handle this particular problem, the decorrelated Filtered-X LMS (DFXLMS) algorithm is developed and studied in this thesis. Both simulations and experiments have been conducted to verify the DFXLMS algorithm and other issues associated with multiple reference ANC. The results presented herein are consistent with the theoretical analysis, and favorably indicate that the DFXLMS algorithm is effective in improving the convergence speed. To take the maximum advantage of the TMS320C30 DSP board used to implement the controller, several DSP programming issues are discussed, and assembly routines are given in the appendix. Furthermore, a graphical user interface (GUI) running under Windows' environment is introduced. The main purpose of the GUI is to facilitate parameters modification, real time data monitoring and DSP process control. / Master of Science

This dissertation describes the development of a method for simultaneous localization and mapping (SLAM)algorithm which is suitable for high dimensional vehicle and map states. The goal of SLAM is to be able to navigate autonomously without the use of external aiding sources for vehicles. SLAM's combination of the localization and mapping problems makes it especially difficult to solve accurately and efficiently, due to the shear size of the unknown state vector. The vehicle states are typically constant in number while the map states increase with time. The increasing number of unknowns in the map state makes it impossible to use traditional Kalman filters to solve the problem- the covariance matrix grows too large and the computational complexity becomes too overwhelming. Particle filters have proved beneficial for alleviating the complexity of the SLAM problem for low dimensional vehicle states, but there is little work done for higher dimensional states. This research provides an Gaussian Mixture Model based alternative to the particle filtering SLAM methods, and provides a further partition that alleviates the vehicle state dimensionality problem with the standard particle filter. A SLAM background and basic theory is provided in the early chapters. A description of the new algorithm is provided in detail. Simulations are run demonstrating the performance of the algorithm, and then an aerial SLAM platform is developed for further testing. The aerial SLAM system uses a RGBD camera as well as an inertial measurement unit to collect SLAM data, and the ground truth is captured using an indoor optical motion capture system. Details on image processing and specifics on the inertial integration are provided. The performance of the algorithm is compared to a state of the art particle filtering based SLAM algorithm, and the results are discussed. Further work performed while working in the industry is described, which involves SLAM for adding transponders onto long-baseline acoustic arrays and stereo-inertial SLAM for 3D reconstruction of deep-water sub-sea structures. Finally, a neatly packaged production line version of the stereo-inertial SLAM system presented.