Wireless video capsule endoscopy (VCE) plays an increasingly important role in assisting clinical diagnoses of gastrointestinal (GI) diseases. It provides a non-invasive way to examine the entire small intestine, where other conventional endoscopic instruments can barely reach. Existing examination systems for the VCE cannot track the location of a endoscopic capsule, which prevents the physician from identifying the exact location of the diseases. During the eight hour examination time, the video capsule continuously keeps taking images at a frame rate up to six frame per sec, so it is possible to extract the motion information from the content of the image sequence. Many attempts have been made to develop computer vision algorithms to detect the motion of the capsule based on the small changes in the consecutive video frames and then trace the location of the capsule. However, validation of those algorithms has become a challenging topic because conducting experiments on the human body is extremely difficult due to individual differences and legal issues. In this thesis, two validation approaches for motion tracking of the VCE are presented in detail respectively. One approach is to build a physical testbed with a plastic pipe and an endoscopy camera; the other is to build a virtual testbed by creating a three-dimensional virtual small intestine model and simulating the motion of the capsule. Based on the virtual testbed, a physiological factor, intestinal contraction, has been studied in terms of its influence on visual based localization algorithm and a geometric model for measuring the amount of contraction is proposed and validated via the virtual testbed. Empirical results have made contributions in support of the performance evaluation of other research on the visual based localization algorithm of VCE.

<p>The aim of this master's thesis is to implement and evaluate a method for estimating the indicated engine torque. The method is developed by IAV GmbH, Fraunhofer-Institut and Audi AG. The determination of the indicated torque is based on high resolution engine speed measurements. The engine speed is measured with a hall sensor, which receives the signal from the transmitterwheel mounted on the crankshaft. A transmitterwheel compensation is done to compensate for the partition defects that arises in the production and thus enable a more precise calculation of the angular velocity. The crankshaft angle, angular velocity and angular acceleration are estimated and the helpvariable effective torque is calculated using these signals as input. Through a relationship between effective torque and the indicated pressure the indicated pressure is extracted from a map. The indicated torque is then calculated from the pressure. </p><p>The method is validated with data from an engine test bed. Because of the low obtainable sample rate at the test bed, 4MHz, quantisation errors arises at engine speeds over 1000 rpm. Therefore the model is validated for low engine speeds and the result is promising.</p>

The aim of this master's thesis is to implement and evaluate a method for estimating the indicated engine torque. The method is developed by IAV GmbH, Fraunhofer-Institut and Audi AG. The determination of the indicated torque is based on high resolution engine speed measurements. The engine speed is measured with a hall sensor, which receives the signal from the transmitterwheel mounted on the crankshaft. A transmitterwheel compensation is done to compensate for the partition defects that arises in the production and thus enable a more precise calculation of the angular velocity. The crankshaft angle, angular velocity and angular acceleration are estimated and the helpvariable effective torque is calculated using these signals as input. Through a relationship between effective torque and the indicated pressure the indicated pressure is extracted from a map. The indicated torque is then calculated from the pressure. The method is validated with data from an engine test bed. Because of the low obtainable sample rate at the test bed, 4MHz, quantisation errors arises at engine speeds over 1000 rpm. Therefore the model is validated for low engine speeds and the result is promising.

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.

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Connected Vehicle research has emerged as one of the highest priorities in the transportation systems because connected vehicle technology has the potential to improve safety, mobility, and environment for the current transportation systems. Various connected vehicle based applications have been identified and evaluated through various measurements to assess the performance of connected vehicle applications. However, most of these previous studies have used hypothetical study areas with simple networks for connected vehicle environment. This study represents connected vehicle environment in TRANSIMS to assess the performance of V2V communication applications in the realistic urban network. The communication duration rate and spatial-temporal dispersion of equipped vehicles are investigated to evaluate the capability of V2V communication based on the market penetration rate of equipped vehicles and wireless communication coverage in the whole study area. The area coverage level is used to assess the spatial-temporal dispersion of equipped vehicles for two study areas. The distance of incident information propagation and speed estimation error are used to measure the performance of event-driven and periodic applications based on different market penetration rates of equipped vehicles and wireless communication coverage in both morning peak and non-peak times. The wireless communication coverage is the major factor for event-driven application and the market penetration rate of equipped vehicles has more impact on the performance of periodic application. The required minimum levels of deployment for each application are determined for each scenario. These study findings will be useful for making decisions about investments on deployment of connected vehicle applications to improve the current transportation systems. Notably, event-driven applications can be reliably deployed in the initial stage of deployment despite the low level of market penetration of equipped vehicles. / Ph. D.

Induction motors (IM) find widespread use in modern industry and for this reason they have been subject to a significant amount of research interest in recent times. One particular aspect of this research is the fault detection and diagnosis (FDD) of induction motors for use in a condition based maintenance (CBM) strategy; by effectively tracking the condition of the motor, maintenance action need only be carried out when necessary. This type of maintenance strategy minimises maintenance costs and unplanned downtime. The benefits of an effective FDD for IM is clear and there have been numerous studies in this area but few which consider the problem in a practical sense with the aim of developing a single system that can be used to monitor motor condition under a range of different conditions, with different motor specifications and loads. This thesis aims to address some of these problems by developing a general FDD system for induction motor. The solution of this problem involved the development and testing of a new approach; the adaptive mixed-residual approach (AMRA). The main aim of the AMRA system is to avoid the vast majority of unplanned failures of the machine and therefore as opposed to tackling a single induction motor fault, the system is developed to detect all four of the most statistically prevalent induction motor fault types; rotor fault, stator fault, air-gap fault and bearing fault. The mixed-residual fault detection algorithm is used to detect these fault types which includes a combination of spectral and model-based techniques coupled with particle swarm optimisation (PSO) for automatic identification of motor parameters. The AMRA residuals are analysed by a fuzzy-logic classifier and the system requires only current and voltage inputs to operate. Validation results indicate that the system performs well under a range of load torques and different coupling methods proving it to have significant potential for use in industrial applications. / The full-text was made available at the end of the embargo period on 29th Sept 2017.

ABSTRACT SENSORLESS DIRECT FIELD ORIENTED CONTROL OF INDUCTION MACHINE BY FLUX AND SPEED ESTIMATORS USING MODEL REFERENCE ADAPTIVE SYSTEM This work focuses on an observer design which will estimate flux-linkage and speed for induction motors in its entire speed control range. The theoretical base of the algorithm is explained in detail and its both open-loop, and closed-loop performance is tested with experiments, measuring only stator current and voltage. Theoretically, the field-oriented control for the induction motor drive can be mainly categorized into two types / indirect and direct field oriented. The field to be oriented may be rotor, stator, or airgap flux-linkage. In the indirect field-oriented control, the slip estimation based on the measured or estimated rotor speed is required in order to compute the synchronous speed. There is no need for the flux estimation in such a system. For the direct field oriented case the synchronous speed is computed with the aid of a flux estimator. In DFO, the synchronous speed is iv computed from the ratio of dq-axes fluxes. With the combination of a flux estimator and an open-loop speed estimator one can observe stator-rotor fluxes, rotor-flux angle and rotor speed. In this study, the direct (rotor) flux oriented control system with flux and-open-loop speed estimators is described and tested in real-time with the Evaluation Module named TMS320LF21407 and the Embedded Target software named Vissim from Visual Solutions Company.

In industrial drives market, requirements related to control quality and price of drives are important. In low cost drives, one of the aims is achieving speed estimation accuracy. Since motor parameters are required to estimate speed and sometimes it is impractical to do no-load and locked rotor tests, it is necessary to estimate motor parameters from motor label or by simple measurements. Throughout this study, some of parameter estimation and speed estimation methods found in literature are investigated and some new methods are proposed. These methods are applied to three induction motors and estimation results are compared with test results. Advantages and disadvantages of these methods are investigated. As a result of this study, the most suitable parameter and speed estimation methods amongst these methods are obtained for low cost motor drives.

Focus of this work is closed-loop speed control of an induction machine based on direct field-oriented control (DFOC) algorithm, using estimates of speed and flux observers which utilize only stator current and voltage. Theoretical bases of the algorithms are explained in detail and their performances are investigated with simulations and experiments. Field Orientated Control is based on projections which transform a threephase time and speed dependent system into a two co-ordinate time invariant system. These projections lead to a structure similar to that of a DC machine control. Transformations are done in synchronous frame alligned to d-axis of rotor flux. So rotor flux position must be known accurately to make these transformations. Degined flux observer, in which voltage model is assisted by current model via a closed-loop to compensate voltage model&rsquo / s disadvantages, estimates the position of the rotor flux. Obtaining adequate torque control via FOC, speed loop is closed using conventional PI regulators. Speed feedback is necessary to complete control loop. Model Reference Adaptive System is studied as a speed estimator. Reactive power scheme is applied to MRAS algorithm to estimate rotor speed. In this study, the direct (rotor) flux oriented control system with flux and speed estimators is described and tested in real-time with the starter kit named TMS320F2812 eZdsp DSK and the Embedded Target for the TI C2000 DSP tool of Matlab