107 resultados para sovellusten yhteenliittymä


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The objectives of this master’s thesis were to understand the importance of bubbling fluidized bed (BFB) conditions and to find out how digital image processing and acoustic emission technology can help in monitoring the bed quality. An acoustic emission (AE) measurement system and a bottom ash camera system were evaluated in acquiring information about the bed conditions. The theory part of the study describes the fundamentals of BFB boiler and evaluates the characteristics of bubbling bed. Causes and effects of bed material coarsening are explained. The ways and methods to monitor the behaviour of BFB are determined. The study introduces the operating principles of AE technology and digital image processing. The empirical part of the study describes an experimental arrangement and results of a case study at an industrial BFB boiler. Sand consumption of the boiler was reduced by optimization of bottom ash handling and sand feeding. Furthermore, data from the AE measurement system and the bottom ash camera system was collected. The feasibility of these two systems was evaluated. The particle size of bottom ash and the changes in particle size distribution were monitored during the test period. Neither of the systems evaluated was ready to serve in bed quality control accurately or fast enough. Particle size distributions according to the bottom ash camera did not correspond to the results of manual sieving. Comprehensive interpretation of the collected AE data requires much experience. Both technologies do have potential and with more research and development they may enable acquiring reliable and real-time information about the bed conditions. This information could help to maintain disturbance-free combustion process and to optimize bottom ash handling system.

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Augmented Reality (AR) is currently gaining popularity in multiple different fields. However, the technology for AR still requires development in both hardware and software when considering industrial use. In order to create immersive AR applications, more accurate pose estimation techniques to define virtual camera location are required. The algorithms for pose estimation often require a lot of processing power, which makes robust pose estimation a difficult task when using mobile devices or designated AR tools. The difficulties are even larger in outdoor scenarios where the environment can vary a lot and is often unprepared for AR. This thesis aims to research different possibilities for creating AR applications for outdoor environments. Both hardware and software solutions are considered, but the focus is more on software. The majority of the thesis focuses on different visual pose estimation and tracking techniques for natural features. During the thesis, multiple different solutions were tested for outdoor AR. One commercial AR SDK was tested, and three different custom software solutions were developed for an Android tablet. The custom software solutions were an algorithm for combining data from magnetometer and a gyroscope, a natural feature tracker and a tracker based on panorama images. The tracker based on panorama images was implemented based on an existing scientific publication, and the presented tracker was further developed by integrating it to Unity 3D and adding a possibility for augmenting content. This thesis concludes that AR is very close to becoming a usable tool for professional use. The commercial solutions currently available are not yet ready for creating tools for professional use, but especially for different visualization tasks some custom solutions are capable of achieving a required robustness. The panorama tracker implemented in this thesis seems like a promising tool for robust pose estimation in unprepared outdoor environments.