Genetic Basis and Diagnostics of Extended-Spectrum Beta-Lactamases among Enterobacteriaceae in Finland

Since the introduction of antibiotic agents, the amount and prevalence of Beta-lactam resistant enterobacteria has become an increasing problem. Many enterobacteria are opportunistic pathogens that easily acquire resistance mechanisms and genes, which make the situation menacing. These bacteria have acquired resistance and can hydrolyse extended spectrum cephalosporins and penicillins by producing enzymes called extended-spectrum Beta-lactamases (ESBLs). ESBL-producing bacteria are most commonly found in the gastro-intestinal tract of colonised patients. These resistant strains can be found in both health-care associated and community-acquired isolates. The detection and treatment of infections caused by bacteria producing ESBLs are problematic. This study investigated the genetic basis of extended-spectrum Beta-lactamases in Enterobacteriaceae, especially in Escherichia coli and Klebsiella pneumoniae isolates. A total of 994 Finnish Enterobacteriaceae strains, collected at 26 hospital laboratories, during 2000 and 2007 were analysed. For the genetic basis studies, PCR, sequencing and pyrosequencing methods were optimised. In addition, international standard methods, the agar dilution and disk diffusion methods were performed for the resistance studies, and the susceptibility of these strains was tested for antimicrobial agents that are used for treating patients. The genetic analysis showed that bla_CTX-M was the most prevalent gene among the E. coli isolates, while blaS_HV-12 was the most common Beta-lactamase gene in K. pneumoniae. The susceptibility testing results showed that about 60% of the strains were multidrug resistant. The prevalence of ESBL-producing isolates in Finland has been increasing since 2000. However, the situation in Finland is still much better than in many other European countries.

The influence of high cable penetration in distribution networks on earth fault currents and the operation of relay protection.

Recent Storms in Nordic countries were a reason of long power outages in huge territories. After these disasters distribution networks' operators faced with a problem how to provide adequate quality of supply in such situation. The decision of utilization cable lines rather than overhead lines were made, which brings new features to distribution networks. The main idea of this work is a complex analysis of medium voltage distribution networks with long cable lines. High value of cable’s specific capacitance and length of lines determine such problems as: high values of earth fault currents, excessive amount of reactive power flow from distribution to transmission network, possibility of a high voltage level at the receiving end of cable feeders. However the core tasks was to estimate functional ability of the earth fault protection and the possibility to utilize simplified formulas for operating setting calculations in this network. In order to provide justify solution or evaluation of mentioned above problems corresponding calculations were made and in order to analyze behavior of relay protection principles PSCAD model of the examined network have been created. Evaluation of the voltage rise in the end of a cable line have educed absence of a dangerous increase in a voltage level, while excessive value of reactive power can be a reason of final penalty according to the Finish regulations. It was proved and calculated that for this networks compensation of earth fault currents should be implemented. In PSCAD models of the electrical grid with isolated neutral, central compensation and hybrid compensation were created. For the network with hybrid compensation methodology which allows to select number and rated power of distributed arc suppression coils have been offered. Based on the obtained results from experiments it was determined that in order to guarantee selective and reliable operation of the relay protection should be utilized hybrid compensation with connection of high-ohmic resistor. Directional and admittance based relay protection were tested under these conditions and advantageous of the novel protection were revealed. However, for electrical grids with extensive cabling necessity of a complex approach to the relay protection were explained and illustrated. Thus, in order to organize reliable earth fault protection is recommended to utilize both intermittent and conventional relay protection with operational settings calculated by the use of simplified formulas.

Wind turbine indirect ice detection and operational analysis

Wind energy is one of the most promising and fast growing sector of energy production. Wind is ecologically friendly and relatively cheap energy resource available for development in practically all corners of the world (where only the wind blows). Today wind power gained broad development in the Scandinavian countries. Three important challenges concerning sustainable development, i.e. energy security, climate change and energy access make a compelling case for large-scale utilization of wind energy. In Finland, according to the climate and energy strategy, accepted in 2008, the total consumption of electricity generated by means of wind farms by 2020, should reach 6 - 7% of total consumption in the country [1]. The main challenges associated with wind energy production are harsh operational conditions that often accompany the turbine operation in the climatic conditions of the north and poor accessibility for maintenance and service. One of the major problems that require a solution is the icing of turbine structures. Icing reduces the performance of wind turbines, which in the conditions of a long cold period, can significantly affect the reliability of power supply. In order to predict and control power performance, the process of ice accretion has to be carefully tracked. There are two ways to detect icing – directly or indirectly. The first way applies to the special ice detection instruments. The second one is using indirect characteristics of turbine performance. One of such indirect methods for ice detection and power loss estimation has been proposed and used in this paper. The results were compared to the results directly gained from the ice sensors. The data used was measured in Muukko wind farm, southeast Finland during a project 'Wind power in cold climate and complex terrain'. The project was carried out in 9/2013 - 8/2015 with the partners Lappeenranta university of technology, Alstom renovables España S.L., TuuliMuukko, and TuuliSaimaa.

Free Prostate-specific Antigen Forms and Kallikrein-related Peptidase 2: Tools for Prostate Cancer Diagnostics

Prostate-specific antigen (PSA) is a marker that is commonly used in estimating prostate cancer risk. Prostate cancer is usually a slowly progressing disease, which might not cause any symptoms whatsoever. Nevertheless, some cases of cancer are aggressive and need to be treated before they become life-threatening. However, the blood PSA concentration may rise also in benign prostate diseases and using a single total PSA (tPSA) measurement to guide the decision on further examinations leads to many unnecessary biopsies, over-detection, and overtreatment of indolent cancers which would not require treatment. Therefore, there is a need for markers that would better separate cancer from benign disorders, and would also predict cancer aggressiveness. The aim of this study was to evaluate whether intact and nicked forms of free PSA (fPSA-I and fPSA-N) or human kallikrein-related peptidase 2 (hK2) could serve as new tools in estimating prostate cancer risk. First, the immunoassays for fPSA-I and free and total hK2 were optimized so that they would be less prone to assay interference caused by interfering factors present in some blood samples. The optimized assays were shown to work well and were used to study the marker concentrations in the clinical sample panels. The marker levels were measured from preoperative blood samples of prostate cancer patients scheduled for radical prostatectomy. The association of the markers with the cancer stage and grade was studied. It was found that among all tested markers and their combinations especially the ratio of fPSA-N to tPSA and ratio of free PSA (fPSA) to tPSA were associated with both cancer stage and grade. They might be useful in predicting the cancer aggressiveness, but further follow-up studies are necessary to fully evaluate the significance of the markers in this clinical setting. The markers tPSA, fPSA, fPSA-I and hK2 were combined in a statistical model which was previously shown to be able to reduce unnecessary biopsies when applied to large screening cohorts of men with elevated tPSA. The discriminative accuracy of this model was compared to models based on established clinical predictors in reference to biopsy outcome. The kallikrein model and the calculated fPSA-N concentrations (fPSA minus fPSA-I) correlated with the prostate volume and the model, when compared to the clinical models, predicted prostate cancer in biopsy equally well. Hence, the measurement of kallikreins in a blood sample could be used to replace the volume measurement which is time-consuming, needs instrumentation and skilled personnel and is an uncomfortable procedure. Overall, the model could simplify the estimation of prostate cancer risk. Finally, as the fPSA-N seems to be an interesting new marker, a direct immunoassay for measuring fPSA-N concentrations was developed. The analytical performance was acceptable, but the rather complicated assay protocol needs to be improved until it can be used for measuring large sample panels.

Supervised localimage feature detection

This thesis is about detection of local image features. The research topic belongs to the wider area of object detection, which is a machine vision and pattern recognition problem where an object must be detected (located) in an image. State-of-the-art object detection methods often divide the problem into separate interest point detection and local image description steps, but in this thesis a different technique is used, leading to higher quality image features which enable more precise localization. Instead of using interest point detection the landmark positions are marked manually. Therefore, the quality of the image features is not limited by the interest point detection phase and the learning of image features is simplified. The approach combines both interest point detection and local description into one phase for detection. Computational efficiency of the descriptor is therefore important, leaving out many of the commonly used descriptors as unsuitably heavy. Multiresolution Gabor features has been the main descriptor in this thesis and improving their efficiency is a significant part. Actual image features are formed from descriptors by using a classifierwhich can then recognize similar looking patches in new images. The main classifier is based on Gaussian mixture models. Classifiers are used in one-class classifier configuration where there are only positive training samples without explicit background class. The local image feature detection method has been tested with two freely available face detection databases and a proprietary license plate database. The localization performance was very good in these experiments. Other applications applying the same under-lying techniques are also presented, including object categorization and fault detection.

Real-Time Simulation of Mobile and Industrial Machines Using the Multibody Simulation Approach

This thesis introduces a real-time simulation environment based on the multibody simulation approach. The environment consists of components that are used in conventional product development, including computer aided drawing, visualization, dynamic simulation and finite element software architecture, data transfer and haptics. These components are combined to perform as a coupled system on one platform. The environment is used to simulate mobile and industrial machines at different stages of a product life time. Consequently, the demands of the simulated scenarios vary. In this thesis, a real-time simulation environment based on the multibody approach is used to study a reel mechanism of a paper machine and a gantry crane. These case systems are used to demonstrate the usability of the real-time simulation environment for fault detection purposes and in the context of a training simulator. In order to describe the dynamical performance of a mobile or industrial machine, the nonlinear equations of motion must be defined. In this thesis, the dynamical behaviour of machines is modelled using the multibody simulation approach. A multibody system may consist of rigid and flexible bodies which are joined using kinematic joint constraints while force components are used to describe the actuators. The strength of multibody dynamics relies upon its ability to describe nonlinearities arising from wearing of the components, friction, large rotations or contact forces in a systematic manner. For this reason, the interfaces between subsystems such as mechanics, hydraulics and control systems of the mechatronic machine can be defined and analyzed in a straightforward manner.

Early Detection of Alzheimer's Disease Beta-amyloid Pathology -Applicability of Positron Emission Tomography with the Amyloid Radioligand 11C-PIB

Early Detection of Alzheimer's Disease Beta-amyloid Pathology -Applicability of Positron Emission Tomography with the Amyloid Radioligand ¹¹C-PIB Accumulation of beta amyloid (Abeta) in the brain is characteristic for Alzheimer’s disease (AD). Carbon-11 labeled 2-(4’-methylaminophenyl)-6-hydroxybenzothiazole (¹¹C-PIB) is a novel positron emission tomography (PET) amyloid imaging agent that appears to be applicable for in vivo Abeta plaque detection and quantitation. The biodistribution and radiation dosimetry of ¹¹C-PIB were investigated in 16 healthy subjects. The reproducibility of a simplified ¹¹C-PIB quantitation method was evaluated with a test-retest study on 6 AD patients and 4 healthy control subjects. Brain ¹¹C-PIB uptake and its possible association with brain atrophy rates were studied over a two-year follow-up in 14 AD patients and 13 healthy controls. Nine monozygotic and 8 dizygotic twin pairs discordant for cognitive impairment and 9 unrelated controls were examined to determine whether brain Abeta accumulation could be detected with ¹¹C-PIB PET in cognitively intact persons who are at increased genetic risk for AD. The highest absorbed radiation dose was received by the gallbladder wall (41.5 mjuGy/MBq). About 20 % of the injected radioactivity was excreted into urine, and the effective whole-body radiation dose was 4.7 mjuSv/MBq. Such a dose allows repeated scans of individual subjects. The reproducibility of the simplified ¹¹C-PIB quantitation was good or excellent both at the regional level (VAR 0.9-5.5 %) and at the voxel level (VAR 4.2-6.4 %). ¹¹C-PIB uptake did not increase during 24 months’ follow-up of subjects with mild or moderate AD, even though brain atrophy and cognitive decline progressed. Baseline neocortical ¹¹C-PIB uptake predicted subsequent volumetric brain changes in healthy control subjects (r = 0.725, p = 0.005). Cognitively intact monozygotic co-twins – but not dizygotic co-twins – of memory-impaired subjects exhibited increased ¹¹C-PIB uptake (117-121 % of control mean) in their temporal and parietal cortices and the posterior cingulate (p<0.05), when compared with unrelated controls. This increased uptake may be representative of an early AD process, and genetic factors seem to play an important role in the development of AD-like Abeta plaque pathology. ¹¹C-PIB PET may be a useful method for patient selection and follow-up for early-phase intervention trials of novel therapeutic agents. AD might be detectable in high-risk individuals in its presymptomatic stage with ¹¹C-PIB PET, which would have important consequences both for future diagnostics and for research on disease-modifying treatments.

Determination of sugars and organic acids in pulp samples by capillary electrophoresis with UV detection

This MSc work was done in the project of BIOMECON financed by Tekes. The prime target of the research was, to develop methods for separation and determination of carbohydrates (sugars), sugar acids and alcohols, and some other organic acids in hydrolyzed pulp samples by capillary electrophoresis (CE) using UV detection. Aspen, spruce, and birch pulps are commonly used for production of papers in Finland. Feedstock components in pulp predominantly consist of carbohydrates, organic acids, lignin, extractives, and proteins. Here in this study, pulps have been hydrolyzed in analytical chemistry laboratories of UPM Company and Lappeenranta University in order to convert them into sugars, acids, alcohols, and organic acids. Foremost objective of this study was to quantify and identify the main and by-products in the pulp samples. For the method development and optimization, increased precision in capillary electrophoresis was accomplished by calculating calibration data of 16 analytes such as D-(-)-fructose, D(+)-xylose, D(+)-mannose, D(+)-cellobiose, D-(+)-glucose, D-(+)-raffinose, D(-)-mannitol, sorbitol, rhamnose, sucrose, xylitol, galactose, maltose, arabinose, ribose, and, α-lactose monohydratesugars and 16 organic acids such as D-glucuronic, oxalic, acetic, propionic, formic, glycolic, malonic, maleic, citric, L-glutamic, tartaric, succinic, adipic, ascorbic, galacturonic, and glyoxylic acid. In carbohydrate and polyalcohol analyses, the experiments with CE coupled to direct UV detection and positive separation polarity was performed in 36 mM disodium hydrogen phosphate electrolyte solution. For acid analyses, CE coupled indirect UV detection, using negative polarity, and electrolyte solution made of 2,3 pyridinedicarboxylic acid, Ca2+ salt, Mg2+ salts, and myristyltrimethylammonium hydroxide in water was used. Under optimized conditions, limits of detection, relative standard deviations and correlation coefficients of each compound were measured. The optimized conditions were used for the identification and quantification of carbohydrates and acids produced by hydrolyses of pulp. The concentrations of the analytes varied between 1 mg – 0.138 g in liter hydrolysate.

First-Line Chemotherapy with Anthracycline and Taxane Combination in Metastatic Breast Cancer. Detection of bone metastases with TRACP 5b

Background: In Finland, breast cancer (BC) is the most common cancer among women, and prostate cancer (PC) that among men. At the metastatic stage both cancers remain essentially incurable. The goals of therapy include palliation of symptoms, improvement or maintenance of quality of life (QoL), delay of disease progression, and prolongation of survival. Balancing between efficacy and toxicity is the major challenge. With increasing costs of new treatments, appropriate use of resources is paramount. When new treatment regimes are introduced into clinical practice a comprehensive assessment of clinical benefit, adverse effects and cost is necessary. Both BC and PC show a predilection to metastasize to bone. Bone metastases cause significant morbidity impairing the patients´ QoL. Diagnosis of bone metastases relies mainly on radiological methods, which however lack optimal sensitivity and specificity. New tools are needed for detection and follow-up of bone metastases. Aims: Anthracyclines and taxanes are effective chemotherapeutic agents in the treatment of metastatic breast cancer (MBC) with different mechanisms of action. Therefore, evaluation of the combination of anthracyclines with taxanes was a justifiable approach in the treatment of MBC patients. We assessed the efficacy, toxicity, cost of treatment and QoL of BC patients treated with first-line chemotherapy for metastatic disease with the combination epirubicin and docetaxel. We also evaluated the diagnostic potential of tartrate-resistant acid phosphatase 5b (TRACP 5b) and carboxyterminal telopeptides of type I collagen (ICTP) in the diagnosis of bone metastases in BC and TRACP 5b in PC patients. Results: The combination of epirubicin and docetaxel was effective in this phase II study, but required individual dose adjustment to avoid neutropenic infections, and the use of growth factors to maintain a feasible dose level. The response rate was 54 % (95 % CI 37-71) and the median overall survival (OS) was 26 months. Of the patients, 87 % were treated for infections. The treatment of adverse events required additional use of health resources mainly due to neutropenic infections, thereby raising direct treatment costs by 20 %. Despite adverse events, the global QoL was not significantly compromised during the treatment. Clinically evident acute cardiac toxicity was not observed. The combination of serum TRACP 5b and ICTP was at least equally sensitive and specific in detection of of bone metastases as commonly used total alkaline phosphatise (tALP) in BC patients. In contrast, TRACP 5b was less specific and sensitive than tALP as a marker of skeletal changes in PC patients. Conclusions: Treatment with epirubicin and docetaxel showed high efficacy in first-line chemotherapy of MBC. The relatively high incidence of neutropenic infections requiring hospitalization increased the treatment costs. Despite adverse events, the global QoL of the patients was not significantly compromised. The combination of TRACP 5b and ICTP showed similar activity as tALP in detecting bone metastases in MBC. In contrast, TRACP 5b was less specific and sensitive than tALP as a marker of skeletal changes in PC.

Capillary electrophoresis for monitoring of carboxylic, phenolic and amino acids in bioprocesses

Bioprocess technology is a multidisciplinary industry that combines knowledge of biology and chemistry with process engineering. It is a growing industry because its applications have an important role in the food, pharmaceutical, diagnostics and chemical industries. In addition, the current pressure to decrease our dependence on fossil fuels motivates new, innovative research in the replacement of petrochemical products. Bioprocesses are processes that utilize cells and/or their components in the production of desired products. Bioprocesses are already used to produce fuels and chemicals, especially ethanol and building-block chemicals such as carboxylic acids. In order to enable more efficient, sustainable and economically feasible bioprocesses, the raw materials must be cheap and the bioprocesses must be operated at optimal conditions. It is essential to measure different parameters that provide information about the process conditions and the main critical process parameters including cell density, substrate concentrations and products. In addition to offline analysis methods, online monitoring tools are becoming increasingly important in the optimization of bioprocesses. Capillary electrophoresis (CE) is a versatile analysis technique with no limitations concerning polar solvents, analytes or samples. Its resolution and efficiency are high in optimized methods creating a great potential for rapid detection and quantification. This work demonstrates the potential and possibilities of CE as a versatile bioprocess monitoring tool. As a part of this study a commercial CE device was modified for use as an online analysis tool for automated monitoring. The work describes three offline CE analysis methods for the determination of carboxylic, phenolic and amino acids that are present in bioprocesses, and an online CE analysis method for the monitoring of carboxylic acid production during bioprocesses. The detection methods were indirect and direct UV, and laser-induced frescence. The results of this work can be used for the optimization of bioprocess conditions, for the development of more robust and tolerant microorganisms, and to study the dynamics of bioprocesses.

Upconverting diagnostics: Multiplex assays utilizing upconversion luminescence technology

Conventional diagnostics tests and technologies typically allow only a single analysis and result per test. The aim of this study was to propose robust and multiplex array-inwell test platforms based on oligonucleotide and protein arrays combining the advantages of simple instrumentation and upconverting phosphor (UCP) reporter technology. The UCPs are luminescent lanthanide-doped crystals that have a unique capability to convert infrared radiation into visible light. No autofluorescence is produced from the sample under infrared excitation enabling the development of highly sensitive assays. In this study, an oligonucleotide array-in-well hybridization assay was developed for the detection and genotyping of human adenoviruses. The study provided a verification of the advantages and potential of the UCP-based reporter technology in multiplex assays as well as anti-Stokes photoluminescence detection with a new anti- Stokes photoluminescence imager. The developed assay was technically improved and used to detect and genotype adenovirus types from clinical specimens. Based on the results of the epidemiological study, an outbreak of adenovirus type B03 was observed in the autumn of 2010. A quantitative array-in-well immunoassay was developed for three target analytes (prostate specific antigen, thyroid stimulating hormone, and luteinizing hormone). In this study, quantitative results were obtained for each analyte and the analytical sensitivities in buffer were in clinically relevant range. Another protein-based array-inwell assay was developed for multiplex serodiagnostics. The developed assay was able to detect parvovirus B19 IgG and adenovirus IgG antibodies simultaneously from serum samples according to reference assays. The study demonstrated that the UCPtechnology is a robust detection method for diverse multiplex imaging-based array-inwell assays.

On the Condition Monitoring of Induction machines

The research of condition monitoring of electric motors has been wide for several decades. The research and development at universities and in industry has provided means for the predictive condition monitoring. Many different devices and systems are developed and are widely used in industry, transportation and in civil engineering. In addition, many methods are developed and reported in scientific arenas in order to improve existing methods for the automatic analysis of faults. The methods, however, are not widely used as a part of condition monitoring systems. The main reasons are, firstly, that many methods are presented in scientific papers but their performance in different conditions is not evaluated, secondly, the methods include parameters that are so case specific that the implementation of a systemusing such methods would be far from straightforward. In this thesis, some of these methods are evaluated theoretically and tested with simulations and with a drive in a laboratory. A new automatic analysis method for the bearing fault detection is introduced. In the first part of this work the generation of the bearing fault originating signal is explained and its influence into the stator current is concerned with qualitative and quantitative estimation. The verification of the feasibility of the stator current measurement as a bearing fault indicatoris experimentally tested with the running 15 kW induction motor. The second part of this work concentrates on the bearing fault analysis using the vibration measurement signal. The performance of the micromachined silicon accelerometer chip in conjunction with the envelope spectrum analysis of the cyclic bearing faultis experimentally tested. Furthermore, different methods for the creation of feature extractors for the bearing fault classification are researched and an automatic fault classifier using multivariate statistical discrimination and fuzzy logic is introduced. It is often important that the on-line condition monitoring system is integrated with the industrial communications infrastructure. Two types of a sensor solutions are tested in the thesis: the first one is a sensor withcalculation capacity for example for the production of the envelope spectra; the other one can collect the measurement data in memory and another device can read the data via field bus. The data communications requirements highly depend onthe type of the sensor solution selected. If the data is already analysed in the sensor the data communications are needed only for the results but in the other case, all measurement data need to be transferred. The complexity of the classification method can be great if the data is analysed at the management level computer, but if the analysis is made in sensor itself, the analyses must be simple due to the restricted calculation and memory capacity.

Ennakoiva vikojen havaitseminen liityntäverkosta

Tässä diplomityössä on tutkittu mahdollisuuksia ennakoida ja havaita kaapelivikoja mahdollisimman varhaisessa vaiheessa teleoperaattorin liityntäverkosta, joka käsittää optisen rajapinnan ja asiakkaan välisen parikaapeleilla toteutetun osan verkkoa. Liityntäverkon ikääntyessä kaapeleiden ja liitosten viat yleistyvät sekä niiden korjauskustannukset kasvavat. Mahdollisimmanvarhaisessa vaiheessa vikoja havaitsemalla ehkäistään vikojen laajentumista sekä asiakkaiden palveluiden katkeamista. Kannattavin tapa toteuttaa liityntäverkon vikoja ennakoiva järjestelmä Elisa Oyj:n tapauksessa on hyödyntää yrityksessä uudistettua DSL-tekniikkaa. DSLAM:eilla päivittäin suoritetuilla mittauksilla voidaan havaita liityntäverkon kaapeleiden kunnon heikkeneminen sekä vikaantumiset. Työssä on tutkittu vikatapausten aiheuttamia muutoksia linjojen sähköisiin ominaisuuksiin sekä niiden näkymistä mittaustuloksissa. Työssä löydettiin menetelmät toteuttaa liityntäverkon kuntoa mittaava ja tarkkaileva järjestelmä. Ennakoivalla toiminnalla voidaan aikaansaada merkittäviä kustannussäästöjä viankorjausprosessin eri vaiheissa sekä parantaa palveluiden laatua.

Development of the Acoustic Emission Based Diagnostics Concept for the Rotary Lime Kiln

Reaaliaikainen, ennakoiva kunnonvalvonta on erittäin tärkeä osa modernin tehtaan tai tuotantolinjan toimintaa. Diplomityön teettäjä haluaa edelleen kehittää akustiseen emissioon perustuvaa kunnonvalvonta järjestelmäänsä, jotta siitä olisi enemmän hyötyä asiakkaalle. Diplomityö sisältää johdannonakustiseen emissioon ja akustisiin emissio sensoreihin. Työn tavoitteena oli kehittää päätöksentekojärjestelmä, jota käytettäisiin työn teettäjän valmistamien sensoreiden antaman tiedon automatisoituun analysointiin. Työssä on vertailtu kolmea eri ohjelmistotoimittajaa ja heidän ohjelmiaan, ja tehty ehdotus hankittavasta ohjelmistosta. Lisäksi työssä on kehitetty ohjeita, joiden avulla ohjelmisto ohjelmoidaan tuottamaan reaaliaikaista tietoa ja huolto-ohjeita sen käyttäjille. Lisäksi työssä annetaan ehdotuksia kunnonvalvonta- ja päätöksentekojärjestelmän edelleen kehittämiseen.

Direct torque control of permanent magnet synchronous machines - analysis and implementation

Thedirect torque control (DTC) has become an accepted vector control method besidethe current vector control. The DTC was first applied to asynchronous machines,and has later been applied also to synchronous machines. This thesis analyses the application of the DTC to permanent magnet synchronous machines (PMSM). In order to take the full advantage of the DTC, the PMSM has to be properly dimensioned. Therefore the effect of the motor parameters is analysed taking the control principle into account. Based on the analysis, a parameter selection procedure is presented. The analysis and the selection procedure utilize nonlinear optimization methods. The key element of a direct torque controlled drive is the estimation of the stator flux linkage. Different estimation methods - a combination of current and voltage models and improved integration methods - are analysed. The effect of an incorrect measured rotor angle in the current model is analysed andan error detection and compensation method is presented. The dynamic performance of an earlier presented sensorless flux estimation method is made better by improving the dynamic performance of the low-pass filter used and by adapting the correction of the flux linkage to torque changes. A method for the estimation ofthe initial angle of the rotor is presented. The method is based on measuring the inductance of the machine in several directions and fitting the measurements into a model. The model is nonlinear with respect to the rotor angle and therefore a nonlinear least squares optimization method is needed in the procedure. A commonly used current vector control scheme is the minimum current control. In the DTC the stator flux linkage reference is usually kept constant. Achieving the minimum current requires the control of the reference. An on-line method to perform the minimization of the current by controlling the stator flux linkage reference is presented. Also, the control of the reference above the base speed is considered. A new estimation flux linkage is introduced for the estimation of the parameters of the machine model. In order to utilize the flux linkage estimates in off-line parameter estimation, the integration methods are improved. An adaptive correction is used in the same way as in the estimation of the controller stator flux linkage. The presented parameter estimation methods are then used in aself-commissioning scheme. The proposed methods are tested with a laboratory drive, which consists of a commercial inverter hardware with a modified software and several prototype PMSMs.