The Industrial Internet of Things (IIoT) is the result of the intersection between advancements in technology and the demand for more efficient and sustainable industry. Technology has provided a means for a large and heterogeneous collection of networks, devices, developers, owners, users and other stakeholders. From this there is a clear need for highly interoperable and independently developed systems. Interoperability is a communication challenge which affects all layers in a system. Communication protocols such as HTTP, CoAP, XMPP, OPC-UA and MQTT are above the network layer and below a semantic layer. This challenge includes overcoming interaction pattern differences, such as session and session-less protocols or publish/subscribe and request/response protocols. Common interoperability methods look at utilizing, a) middleware, such as in-system adapters and protocol gateways or b) restricting protocols to one or two possibilities. However, these solutions do not fit IIoT well as they are costly to adapt as the protocol landscape evolves, are intrusive to design or increase development costs. Service-Oriented Architecture (SOA) has been identified as having a great potential for integrating independent systems. When applied to industrial contexts, SOA late-binding and service composition offers opportunities for enhancing interoperability. However, SOA-based service contracts still require complete agreement between provider and consumer in order to exchange service. In this thesis an approach toward interoperability is proposed which leverages SOA principles and a multi-protocol translator. The proposed approach is first contextualized with a set of requirements pulled from existing literature and from application domain requirements. The thesis asks the question; how can late-binding and service composition be used to support a multi-protocol network of systems? The result, a new approach of a secure, on-demand and transparent protocol translator, is proposed. Conceptually satisfying the requirements defined, the design is backed up with empirical testing on usability and latency of the solution. The proposed solution differs from middleware in that, it is a participant (alongside the application system), it is on-demand (only used when needed), it is not intrusive (no design time dependencies) and it operates transparently (to application systems). A complete interoperability solution is deemed as future work, which could extend to full security, general encoding and semantic interoperability.

In this bachelor thesis the possibility of implementing a fully functioning Digital Signal Processing system based on the ARM-Cortex-m7 microcontroller from ST- microelectronics is investigated and implemented. The microcontroller is equipped with an Floating Point Unit, which resulted in the filter calculations being performed in floating-point arithmetic instead of fixed-point. The system is intended to be used in audio room correction with filter coefficients calculated by DLCT (Dirac Live Calibration Tool) which is a software distributed by the company Dirac Research. The main system components are a run-time where the audio is processed and a TCP/IP server for communication over ethernet between the system and DLCT. The system is also able to play stimuli sounds on a command from DLCT. The final system is capable of executing the filter calculations required for room correction with the filter topology used. The communication between DLCT and the subsystem was not fully established but the TCP/IP server was implemented and is a good foundation if the project is to be resumed in the future. The work showed that a modern microcontroller is able to perform real-time audio signal processing without the use of a digital signal processor which is more expensive and has a higher development cost.

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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.