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Automatic feature extraction still remains a relevant image and signal processing problem even tough both the field and technologies are developing rapidly. Images of low quality, where it is extremely difficult to reliably process image information automatically, are of special interest. To such images we can refer forensic fingerprints, which are left unintentionally on different surfaces andare contaminated by several of the most difficult noise types. For this reason, identification of fingerprints is mainly based on the visual skills of forensic examiners. We address the problem caused by low quality in fingerprints by connecting different sources of information together, yielding dense frequency and orientation maps in an iterative scheme. This scheme comprises smoothing ofthe original, but only along, ideally never across, the ridges. Reliable estimation of dense maps allows to introduce a continuous fingerprint ridge counting technique. In fingerprint scenario the collection of irrefutable tiny details, e.g. bifurcation of ridges, called minutiae, is used to tie the pattern of such points and their tangential directions to the finger producing the pattern. This limited feature set, location and direction of minutiae, is used in current AFIS systems, while fingerprint examiners use the extended set of features, including the image information between the points. With reasonably accurate estimationsof dense frequency and orientation maps at hand, we have been able to propose a novel compact feature descriptor of arbitrary points. We have used these descriptors to show that the image information between minutiae can be extracted automatically and be valuable for identity establishment of forensic images even if the underlying images are noisy. We collect and compress the image information in the neighborhoods of the fine details, such as minutiae, to vectors, one per minutia, and use the vectors to "color" the minutiae. When matching two patterns (of minutiae) even the color of the minutia must match to conclude that they come from the same identity. This feature development has been concentrated and tested on forensic fingerprint images. However, we have also studied an extension of its application area to other biometrics, periocular regions of faces. This allowed us to test the persistence of automatically extracted features across different types of imagesand image qualities, supporting its generalizability.

The two questions in science ``why" and ``how" are hereby answered in the context of statistical signal processing applied to vibration analysis and ultrasonic testing for fault detection and characterization in critical materials such as rolling bearings and thin layered media. Both materials are of interest in industrial processes. Therefore, assuring the best operating conditions on rolling bearings and product quality in thin layered materials is important. The methods defended in this thesis are for retrieval of the impulsive signals arising from such equipments and materials, representing either faults or responses to an excitation. As the measurements collected via sensors usually consist of signals masked by some unknown systems and noise, retrieving the information-rich portion is often challenging. By exploiting the statistical characteristics due to their natural structure, a linear system is designed to recover the signals of interest in different scenarios. Suppressing the undesired components while enhancing the impulsive events by iteratively adapting a filter is the primary approach here. Signal recovery is accomplished by optimizing objectives (skewness and $\ell_1$-norm) quantifying the presumed characteristics, rising the question of objective surface topology and probability of ill convergence. To attack these, mathematical proofs, experimental evidences and comprehensive discussions are presented in the contributions each aiming to answer a specific question. The aim in the theoretical study is to fill a gap in signal processing by providing analytical and numerical results especially on \emph{skewness} surface characteristics on a signal model (periodic impulses) build on harmonically related sinusoids. With understanding the inner workings and the conditions to suffice, the same approach is applied to different class of signals in ultrasonic testing, such as aperiodic finite energy signals (material impulse response) and a very short duration impulse as an excitation. A similar optimization approach aiming to enhance another attribute, \emph{sparseness}, is experimented numerically on the aforementioned signals as a case study. To summarize, two different objectives each quantifying a certain characteristic are optimized to recover signals carrying valuable information buried in noisy vibration and ultrasonic measurements. Considering the fact that a research is qualified as successful if it creates more questions than it answers and lets ideas flourish creating scientific value, the presented work aims to achieve this in statistical signal processing. Analytical derivations assisted with experiments form the basis for observations, discussions and further questions to be studied and directed on similar phenomena arising from different sources in nature.

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The conducting winding of an electrical machine is insulated in order to prevent any short circuits to occur within the machine. This insulation is during its lifetime exposed to several environmental stresses and therefore plays an important role in the life length of the machine. Accelerated stress tests are used to investigate what design and material is most suitable for a good endurance of a product. In this master thesis, new accelerated test methods for the insulation system in an electrical machine are developed and evaluated. The study resulted in four stress tests that simulate the thermal stress, the thermomechanical stress and the ambient stress from direct oil cooling. Three diagnosis tests and a material analysis were used in order to evaluate how these accelerated stress test methods affected the insulation. The diagnosis tests showed no clear sign of deterioration of the insulation in terms of change in electrical characteristics. However, the material analysis indicated deterioration of the insulation, such as cracks and oxidation of the material. These changes show that the test methods are capable to affect the insulation, but will need more time to cause a breakdown, since a stator of this kind is expected to have a very long life length. Therefore, in future work on this topic, these test methods should continue for a longer time and it would likely be interesting to look into other diagnosis tests.

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This project is about developing a complete amplifier that can integrate with three differentclass-D amplifier modules. With the thought so that the product can later be sold on themarket.Where the use of the product can be used for either home or cinema audio systems.We have designed and reused existing schematic solutions and the company has assisted indeveloping some of the schematics. The result of this report is the development and design ofcircuit boards with EMC guidelines.

As automation increases in train services, this project resulted in making a driver-less train. The main purpose was to see how security can be increased. By using sensors, today’s technologies and rebuild the stations with walls on the platforms, the safety can increase for the better. This project designs a railway system consisting of a train, boom barriers and a station. The mechanical parts were made from scratch to get the system to work beneficially. The use of Arduino as a micro controller where electrical components could be programmed, became the control of all subsystems. Ultrasonic- and IR-sensors were used to detect if obstructions were located on the rails and to detect the oncoming train at the railway crossing. To increase safety, a wall was built on the platform with doors to prevent people from tracing the tracks. The platform door opened and closed simultaneously with the door on the train. As a result, all subsystems worked well separately. When connecting them with each other, some problems occurred. For example, door operations did not match up to 100 percent, which still was considered approved. The major problem was that the train became too heavy for the motor to drive it properly. As there was no time to implement a larger motor, the solution was to increase the voltage with two 9V batteries connected in series. The project demonstrated that an automated train system is to prefer, given its safety benefits. This model can not be materialized into reality as more sensitive sensors are required and the train systems are built more advanced, both mechanically and electrically.

Electric vehicle chargers and batteries installed on the electrical grid have increased in the recent years. EV-chargers can increase the power needed in the grid while batteries give costumers new possibilities to control their own power consumption. This opens up a new situation where synergy between the utility and the costumers can be achieved. Less maximum power drawn from the grid allows the utility to use the power elsewhere while the costumers pay less for their electrical bill. This master thesis proves that the potential for synergy is good from a technical perspective, both with current electric vehicle charger technology and with future technology that will allow power also can to be fed into the grid and not just drawn from the grid. Although the technical potential is good the practical potential is still limited due to a number of reasons. Currently, the economic incentive for the costumers is too small to justify an investment in batteries so the cost for batteries needs to decrease. Furthermore, the legislative situation is far from optimal with a legal framework that does not encourage batteries in any part of the electrical grid. The legal and technical challenges create a situation that causes further problems with possible business models and all of these problems need solutions in order to stimulate the market for batteries on the electrical grid.