Verkkovaihtosuuntaajan vektorisäädön toteutus FPGA-piirillä

Verkkovaihtosuuntaajalla pystytään muuntamaan tasajännite vaihtojännitteeksi ja päinvastoin. Verkkovaihtosuuntaajan toiminta perustuu tehokytkinten ohjaukseen ja sopivan modulointimenetelmän käyttöön. Vektorisäädössä vaihtosuuntaajanvirrat ja jännitteet esitetään kompleksitasossa, jolloin virta- ja jännitekomponentit voidaan esittää vektoreina. Vektorisäädössä verkkovaihtosuuntaajan ohjaustoteutetaan laskemalla kompleksitasossa vektoreille arvot, jotka tuottavat vaihtosuuntaajan lähtöön halutun vektorin. Koska FPGA-piirit mahdollistavat nopean rinnakkaisen laskennan, soveltuvat ne hyvin vektorisäädön toteuttamiseen. FPGA-piirien rakenteesta johtuen on säätöjärjestelmän suunnittelussa huomioitava kiinteän pilkun lukujen riittävä bittileveys ja järjestelmän diskretointiaika. Työssä suunnitellaan verkkovaihtosuuntaajan vektorisäätö ja tutkitaan bittileveyden vaikutusta säädön toteuttamiseen FPGA-piirillä. Bittileveyden tarkasteluun esitetään käytettäväksi tilastollisia menetelmiä. Työssä tarkastellaan kiinteän pilkun järjestelmän ja liukulukujärjestelmän erosuureen tilastollisia tunnusmerkkejä sekä histogrammia. Tarkasteluissa huomattiin, että maksimivirhe itsessään ei tarjoa riittävästi tietoa erosuureen jakautumisesta. Näin ollen maksimivirhe ei ole kaikissa tilanteissa sovelias menetelmä riittävän bittitarkkuuden määrittämiseen. Työssä esitetään riittävän bittitarkkuuden määrittelemiseen käytettäväksi otossuureista otosvarianssia, keskipoikkeamaa ja vaihteluväliä.

Measuring irregularities and surface defects from printed patterns

Quality inspection and assurance is a veryimportant step when today's products are sold to markets. As products are produced in vast quantities, the interest to automate quality inspection tasks has increased correspondingly. Quality inspection tasks usuallyrequire the detection of deficiencies, defined as irregularities in this thesis. Objects containing regular patterns appear quite frequently on certain industries and science, e.g. half-tone raster patterns in the printing industry, crystal lattice structures in solid state physics and solder joints and components in the electronics industry. In this thesis, the problem of regular patterns and irregularities is described in analytical form and three different detection methods are proposed. All the methods are based on characteristics of Fourier transform to represent regular information compactly. Fourier transform enables the separation of regular and irregular parts of an image but the three methods presented are shown to differ in generality and computational complexity. Need to detect fine and sparse details is common in quality inspection tasks, e.g., locating smallfractures in components in the electronics industry or detecting tearing from paper samples in the printing industry. In this thesis, a general definition of such details is given by defining sufficient statistical properties in the histogram domain. The analytical definition allowsa quantitative comparison of methods designed for detail detection. Based on the definition, the utilisation of existing thresholding methodsis shown to be well motivated. Comparison of thresholding methods shows that minimum error thresholding outperforms other standard methods. The results are successfully applied to a paper printability and runnability inspection setup. Missing dots from a repeating raster pattern are detected from Heliotest strips and small surface defects from IGT picking papers.

Comparison of Local Feature Detectors and Descriptors for Visual Object Categorization

Local features are used in many computer vision tasks including visual object categorization, content-based image retrieval and object recognition to mention a few. Local features are points, blobs or regions in images that are extracted using a local feature detector. To make use of extracted local features the localized interest points are described using a local feature descriptor. A descriptor histogram vector is a compact representation of an image and can be used for searching and matching images in databases. In this thesis the performance of local feature detectors and descriptors is evaluated for object class detection task. Features are extracted from image samples belonging to several object classes. Matching features are then searched using random image pairs of a same class. The goal of this thesis is to find out what are the best detector and descriptor methods for such task in terms of detector repeatability and descriptor matching rate.

Automated, adaptive methods for forest inventory

Forest inventories are used to estimate forest characteristics and the condition of forest for many different applications: operational tree logging for forest industry, forest health state estimation, carbon balance estimation, land-cover and land use analysis in order to avoid forest degradation etc. Recent inventory methods are strongly based on remote sensing data combined with field sample measurements, which are used to define estimates covering the whole area of interest. Remote sensing data from satellites, aerial photographs or aerial laser scannings are used, depending on the scale of inventory. To be applicable in operational use, forest inventory methods need to be easily adjusted to local conditions of the study area at hand. All the data handling and parameter tuning should be objective and automated as much as possible. The methods also need to be robust when applied to different forest types. Since there generally are no extensive direct physical models connecting the remote sensing data from different sources to the forest parameters that are estimated, mathematical estimation models are of "black-box" type, connecting the independent auxiliary data to dependent response data with linear or nonlinear arbitrary models. To avoid redundant complexity and over-fitting of the model, which is based on up to hundreds of possibly collinear variables extracted from the auxiliary data, variable selection is needed. To connect the auxiliary data to the inventory parameters that are estimated, field work must be performed. In larger study areas with dense forests, field work is expensive, and should therefore be minimized. To get cost-efficient inventories, field work could partly be replaced with information from formerly measured sites, databases. The work in this thesis is devoted to the development of automated, adaptive computation methods for aerial forest inventory. The mathematical model parameter definition steps are automated, and the cost-efficiency is improved by setting up a procedure that utilizes databases in the estimation of new area characteristics.

Magnetic Resocance Imaging Methods in the Follow-up of Multiple Sclerosis and in Farby Disease

Multiple sclerosis (MS) is a chronic immune-mediated inflammatory disorder of the central nervous system. MS is the most common disabling central nervous system (CNS) disease of young adults in the Western world. In Finland, the prevalence of MS ranges between 1/1000 and 2/1000 in different areas. Fabry disease (FD) is a rare hereditary metabolic disease due to mutation in a single gene coding α-galactosidase A (alpha-gal A) enzyme. It leads to multi-organ pathology, including cerebrovascular disease. Currently there are 44 patients with diagnosed FD in Finland. Magnetic resonance imaging (MRI) is commonly used in the diagnostics and follow-up of these diseases. The disease activity can be demonstrated by occurrence of new or Gadolinium (Gd)-enhancing lesions in routine studies. Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are advanced MR sequences which can reveal pathologies in brain regions which appear normal on conventional MR images in several CNS diseases. The main focus in this study was to reveal whether whole brain apparent diffusion coefficient (ADC) analysis can be used to demonstrate MS disease activity. MS patients were investigated before and after delivery and before and after initiation of diseasemodifying treatment (DMT). In FD, DTI was used to reveal possible microstructural alterations at early timepoints when excessive signs of cerebrovascular disease are not yet visible in conventional MR sequences. Our clinical and MRI findings at 1.5T indicated that post-partum activation of the disease is an early and common phenomenon amongst mothers with MS. MRI seems to be a more sensitive method for assessing MS disease activity than the recording of relapses. However, whole brain ADC histogram analysis is of limited value in the follow-up of inflammatory conditions in a pregnancy-related setting because the pregnancy-related physiological effects on ADC overwhelm the alterations in ADC associated with MS pathology in brain tissue areas which appear normal on conventional MRI sequences. DTI reveals signs of microstructural damage in brain white matter of FD patients before excessive white matter lesion load can be observed on conventional MR scans. DTI could offer a valuable tool for monitoring the possible effects of enzyme replacement therapy in FD.

Persistent organic pollutants in sediments and fish from Lake Victoria, Uganda

This thesis describes the occurrence and sources of selected persistent organic pollutants (POPs) such as polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs) and hexachlorocyclohexanes (HCHs) in the northern watershed of Lake Victoria. Sediments and fish were collected from three highly polluted embayments (i.e. Murchison Bay, Napoleon Gulf and Thurston Bay) of the lake. The analysis for PCDD/Fs, PCBs and PBDEs was done using a high resolution mass spectrometer coupled to a gas chromatograph (GC), and a GC equipped with an electron capture detector was used for HCHs. Total (Σ) PCDD/Fs, PCBs and PBDEs in sediments ranged from 3.19 to 478, 313 to 4325 and 60.8 to 179 pg g-1 dry weight (dw), respectively. The highest concentrations of pollutants were found at sites close to industrial areas and wastewater discharge points. The maximum concentrations of PCDD/Fs, PCBs, PBDEs and HCHs in fish muscle homogenates were 49, 779, 495 and 45,900 pg g-1 wet weight (ww), respectively. The concentrations of the pollutants in Nile perch (Lates niloticus) were significantly greater than those in Nile tilapia (Oreochromis niloticus), possibly due to differences in trophic level and dietary feeding habits among fish species. World Health Organization-toxic equivalency quotient (WHO2005-TEQ) values in the sediments were up to 4.24 pg g-1 dw for PCDD/Fs and 0.55 pg TEQ g-1 dw for the 12 dioxin-like PCBs (dl-PCBs). 23.1% of the samples from the Napoleon Gulf were above the interim sediment quality guideline value of 0.85 pg WHO-TEQ g-1 dw set by the Canadian Council for Ministers of the Environment. The WHO2005-TEQs in fish were 0.001-0.16 pg g-1 for PCDD/Fs and 0.001-0.31 pg g-1 ww for dl- PCBs. The TEQ values were within a permissible level of 3.5 pg g−1 ww recommended by the European Commission. Based on the Commission set TEQs and minimum risk level criteria formulated by the Agency for Toxic Substances and Disease Registry, the consumption of fish from Lake Victoria gives no indication of health risks associated to PCDD/Fs and PCBs. Principal component analysis (PCA) indicated that anthropogenic activities such as agricultural straw open burning, medical waste incinerators and municipal solid waste combustors were the major sources of PCDD/Fs in the watershed of Lake Victoria. The ratios of α-/γ-HCH varied from 0.89 to 1.68 suggesting that the highest HCH residues mainly came from earlier usage and fresh γ-HCH (lindane). In the present study, the concentration of POPs in fish were not significantly related to those in sediments, and the biota sediment accumulation factor (BSAF) concept was found to be a poor predictor of the bioavailability and bioaccumulation of environmental pollutants.

Scaling analysis of small break experiments in PACTEL

The purpose of this thesis is to study the scalability of small break LOCA experiments. The study is performed on the experimental data, as well as on the results of thermal hydraulic computation performed on TRACE code. The SBLOCA experiments were performed on PACTEL facility situated at LUT. The temporal scaling of the results was done by relating the total coolant mass in the system with the initial break mass flow and using the quotient to scale the experiment time. The results showed many similarities in the behaviour of pressure and break mass flow between the experiments.