Nauhasuodatukseen vaikuttavien parametrien tutkiminen

Nauhasuodattimia käytetään teollisuuden aloilla, joissa suodatettavan suspension määrä vaihtelee laajalti ja suodinkakun peseytyminen on tärkeää. Oikean kangasrakenteen valinnalla voidaan kasvattaa suodatuskapasiteettia ja parantaa suodatustulosta. Tämän diplomityön tavoitteena oli tutkia metallisulfidisakan nauhasuodatukseen liittyviä parametreja suodatuksen parantamiseksi. Tavoitteena oli löytää sopiva kangas ja ajoparametrit kloridin pesemiseksi suodinkakusta mahdollisimman tarkasti ja samalla säilyttää hyvä suodospuhtaus. Suodatuskapasiteetin kasvattaminen oli myös toivottavaa. Kirjallisuusosassa keskityttiin kakkusuodatuksen teoriaan, nauhasuodatukseen ja tutustuttiin hieman nauhasuodatukseen liittyvään laskentaan. Uusia kehitteillä olevia suodatusta parantavia menetelmiä käsiteltiin myös kirjallisuusosassa. Kokeellisessa osassa tutkittiin koesuunnittelua hyväksi käyttäen metallisulfidisakan suodatukseen vaikuttavienparametrien vaikutusta. Testattavia parametreja olivat mm. alipaine, lietteen kiintoainepitoisuus, syötön ja pesuveden määrä. Kokeet osoittivat, että kankaan rakenteella ei ole suurta vaikutusta pesutulokseen. Pesuilla ei myöskään voida kokonaan poistaa suodinkakussa olevaa kloridia. Tulosten perusteella kokeissa käytetyillä kudotuilla kankailla päästiin yhtä hyviin kuin huopakankaalla. Suodattimen toiminnan kannalta paras tilanne on, jos suodattimelle tulevan lietteen kiintoainepitoisuus pysyy melko vakiona. Suodattimella käytettävän kankaan käyttöikää kasvattaa kankaan hyvä kulutuskestävyys, kakun irtoaminen helposti kankaan pinnalta ja kankaan pysyminen huokoisena kankaan pesujen ansiosta.

Practical applications of a systematic approach to the chemical abatement of pollutants in water and air

The present dissertation is devoted to the systematic approach to the development of organic toxic and refractory pollutants abatement by chemical decomposition methods in aqueous and gaseous phases. The systematic approach outlines the basic scenario of chemical decomposition process applications with a step-by-step approximation to the most effective result with a predictable outcome for the full-scale application, confirmed by successful experience. The strategy includes the following steps: chemistry studies, reaction kinetic studies in interaction with the mass transfer processes under conditions of different control parameters, contact equipment design and studies, mathematical description of the process for its modelling and simulation, processes integration into treatment technology and its optimisation, and the treatment plant design. The main idea of the systematic approach for oxidation process introduction consists of a search for the most effective combination between the chemical reaction and the treatment device, in which the reaction is supposed to take place. Under this strategy,a knowledge of the reaction pathways, its products, stoichiometry and kinetics is fundamental and, unfortunately, often unavailable from the preliminary knowledge. Therefore, research made in chemistry on novel treatment methods, comprisesnowadays a substantial part of the efforts. Chemical decomposition methods in the aqueous phase include oxidation by ozonation, ozone-associated methods (O3/H2O2, O3/UV, O3/TiO2), Fenton reagent (H2O2/Fe2+/3+) and photocatalytic oxidation (PCO). In the gaseous phase, PCO and catalytic hydrolysis over zero valent ironsare developed. The experimental studies within the described methodology involve aqueous phase oxidation of natural organic matter (NOM) of potable water, phenolic and aromatic amino compounds, ethylene glycol and its derivatives as de-icing agents, and oxygenated motor fuel additives ¿ methyl tert-butyl ether (MTBE) ¿ in leachates and polluted groundwater. Gas-phase chemical decomposition includes PCO of volatile organic compounds and dechlorination of chlorinated methane derivatives. The results of the research summarised here are presented in fifteenattachments (publications and papers submitted for publication and under preparation).

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.

Normaalijakaumaan perustuva mutaatio-operaatio differentiaalievoluutioalgoritmiin

Evoluutioalgoritmit ovat viime vuosina osoittautuneet tehokkaiksi menetelmiksi globaalien optimointitehtävien ratkaisuun. Niiden vahvuutena on etenkin yleiskäyttöisyys ja kyky löytää globaali ratkaisu juuttumatta optimoitavan tavoitefunktion paikallisiin optimikohtiin. Tässä työssä on tavoitteena kehittää uusi, normaalijakaumaan perustuva mutaatio-operaatio differentiaalievoluutioalgoritmiin, joka on eräs uusimmista evoluutiopohjaisista optimointialgoritmeista. Menetelmän oletetaan vähentävän entisestään sekä populaation ennenaikaisen suppenemisen, että algoritmin tilojen juuttumisen riskiä ja se on teoreettisesti osoitettavissa suppenevaksi. Tämä ei päde alkuperäisen differentiaalievoluution tapauksessa, koska on voitu osoittaa, että sen tilanmuutokset voivat pienellä todennäköisyydellä juuttua. Työssä uuden menetelmän toimintaa tarkastellaan kokeellisesti käyttäen testiongelmina monirajoiteongelmia. Rajoitefunktioiden käsittelyyn käytetään Jouni Lampisen kehittämää, Pareto-optimaalisuuden periaatteeseen perustuvaa menetelmää. Samalla saadaan kerättyä lisää kokeellista näyttöä myös tämän menetelmän toiminnasta. Kaikki käytetyt testiongelmat kyettiin ratkaisemaan sekä alkuperäisellä differentiaalievoluutiolla, että uutta mutaatio-operaatiota käyttävällä versiolla. Uusi menetelmä osoittautui kuitenkin luotettavammaksi sellaisissa tapauksissa, joissa alkuperäisellä algoritmilla oli vaikeuksia. Lisäksi useimmat ongelmat kyettiin ratkaisemaan luotettavasti pienemmällä populaation koolla kuin alkuperäistä differentiaalievoluutiota käytettäessä. Uuden menetelmän käyttö myös mahdollistaa paremmin sellaisten kontrolliparametrien käytön, joilla hausta saadaan rotaatioinvariantti. Laskennallisesti uusi menetelmä on hieman alkuperäistä differentiaalievoluutiota raskaampi ja se tarvitsee yhden kontrolliparametrin enemmän. Uusille kontrolliparametreille määritettiin kuitenkin mahdollisimman yleiskäyttöiset arvot, joita käyttämällä on mahdollista ratkaista suuri joukko erilaisia ongelmia.

Measurement of the air permeability profile on SC paper machine

Tämän diplomityön tarkoituksena oli asentaa ja kehittää UPM-Kymmene Rauman tehtaiden PK2:lle luotettava ja toimiva ilmanläpäisyprofiilin mittaus. Työn tarkoituksena oli myös kartoittaa tietoja ilmanläpäisyprofiiliin vaikuttavista seikoista sekä mahdollisuuksista säätää ilmanläpäisyprofiilia. Lisäksi työn tavoitteena oli löytää toimiva menetelmä verrata online mitattua ilmanläpäisyprofiilia laboratoriossa mitattuun ilmanläpäisyprofiiliin online mittauksen luotettavuuden näkökulmasta. Työn aikana selvitettiin myös ilmanläpäisyprofiilin mittauksen mahdollisuutta superkalanteroidusta SC paperista. Työn kirjallisessa osassa käsiteltiin paperin huokoisuutta ja ilmanläpäisyä, huokoisuustasoon ja huokoisuus profiiliin vaikuttavia tekijöitä, ilmanläpäisevyyden merkitystä SC paperin valmistukselle ja SC paperin painettavuudelle sekä ilmanläpäisevyyden laboratorio- sekä online mittausta. Kirjallisessa osassa käsiteltiin myös Honeywellin uutta Poros ilmanläpäisysensoria. Työn kokeellisessa osassa tutkittiin ilmanläpäisyprofiilimittauksen luotettavuutta CD ja MD suunnassa sekä laboratorio- ja online-mittausten välisiä eroavaisuuksia ennen PK2 uusintaa. PK2 uusinnan jälkeen kokeellisessa osassa keskityttiin luotettavuuden varmentamiseen CD ja MD suunnassa sekä kartoittamaan tekijöitä, jotka aiheuttivat pieniä tasoeroja mittausten välillä. Mittaukset todettiin luotettaviksi ja niiden pohjalta suoritettiin mitattujen online profiilien välisiä vertailuja. Ilmanläpäisyprofiililla todettiin olevan positiivinen korrelaatio neliömassaprofiilin ja kosteusprofiilin kanssa sekä negatiivinen korrelaatio tuhkaprofiilin kanssa. PK2 uusinnan yhteydessä tehtiin koeajoja, jotka liittyivät laadunoptimointiin viira- ja puristinosalla. Koeajoissa tutkittujen asioiden lisäksi tutkittiin muutettujen parametrien vaikutusta ilmanläpäisyprofiiliin. Höyrylaatikon vaikutusta ilmanläpäisyprofiiliin tutkittiin säätöjen virityksen yhteydessä.

Tuotannon- ja varastonohjausmallien kehittäminen sekä ylläpito kokoonpanotuotannossa

Asiakkaiden vaatimusten täyttäminen käytössä olevilla resursseilla edellyttää yrityksiltä usein varastojen pitämistä. Varastot aiheuttavat kuluja ja niihin sitoutuu pääomaa, joten niiden hallinta on yritysten mielenkiinnon kohde. Diplomityön tavoitteena on tutkia Peikko Finland Oy:n Teräsosatehtaan varastonohjausmallin toimivuutta sekä luoda ylläpitokelpoinen tapa tuotannonohjausmuodon ja varastoparametrien päivittämiseen. Yritysten käytössä olevien resurssien ollessa rajallisia tulee tärkeiden tuotteiden hallintaan keskittyä. Vähäpätöisempiä nimikkeitäkin on ohjattava, mutta yksinkertaisempien mallien avulla kuin tärkeitä tuotteita. Tuotannon- ja varastonohjauksen tavoitteena on löytää tasapaino pääoman sitoutumisen, asiakkaiden palvelun sekä kapasiteetin käytön väliltä. Niihin vaikuttavat tekijät tulee huomioida mahdollisimman kattavasti tuotannonohjausta ja varastonhallintaa suunniteltaessa, jolloin päästään koko yritystä hyödyttävään lopputulokseen. Yrityksen toimintaympäristö kehittyy jatkuvasti, joten kerran määritetyt tekijä eivät ole relevantteja loputtomiin vaan jatkuvan kehittämisen ja tietojen päivittämisen tulee olla osa yrityksen jokapäiväistä toimintaa. Työssä kehitettiin helposti päivitettävä malli, jonka avulla kohdeyritys pystyy päivittämään nimikkeiden tuotannonohjausmuodot ja varastonohjauksen parametrit.

Generalized Differential Evolution for Global Multi-Objective Optimization with Constraints

The objective of this thesis work is to develop and study the Differential Evolution Algorithm for multi-objective optimization with constraints. Differential Evolution is an evolutionary algorithm that has gained in popularity because of its simplicity and good observed performance. Multi-objective evolutionary algorithms have become popular since they are able to produce a set of compromise solutions during the search process to approximate the Pareto-optimal front. The starting point for this thesis was an idea how Differential Evolution, with simple changes, could be extended for optimization with multiple constraints and objectives. This approach is implemented, experimentally studied, and further developed in the work. Development and study concentrates on the multi-objective optimization aspect. The main outcomes of the work are versions of a method called Generalized Differential Evolution. The versions aim to improve the performance of the method in multi-objective optimization. A diversity preservation technique that is effective and efficient compared to previous diversity preservation techniques is developed. The thesis also studies the influence of control parameters of Differential Evolution in multi-objective optimization. Proposals for initial control parameter value selection are given. Overall, the work contributes to the diversity preservation of solutions in multi-objective optimization.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

The effects of real time control of welding parameters on weld quality in plasma arc keyhole welding

Joints intended for welding frequently show variations in geometry and position, for which it is unfortunately not possible to apply a single set of operating parameters to ensure constant quality. The cause of this difficulty lies in a number of factors, including inaccurate joint preparation and joint fit up, tack welds, as well as thermal distortion of the workpiece. In plasma arc keyhole welding of butt joints, deviations in the gap width may cause weld defects such as an incomplete weld bead, excessive penetration and burn through. Manual adjustment of welding parameters to compensate for variations in the gap width is very difficult, and unsatisfactory weld quality is often obtained. In this study a control system for plasma arc keyhole welding has been developed and used to study the effects of the real time control of welding parameters on gap tolerance during welding of austenitic stainless steel AISI 304L. The welding tests demonstrated the beneficial effect of real time control on weld quality. Compared with welding using constant parameters, the maximum tolerable gap width with an acceptable weld quality was 47% higher when using the real time controlled parameters for a plate thickness of 5 mm. In addition, burn through occurred with significantly larger gap widths when parameters were controlled in real time. Increased gap tolerance enables joints to be prepared and fit up less accurately, saving time and preparation costs for welding. In addition to the control system, a novel technique for back face monitoring is described in this study. The test results showed that the technique could be successfully applied for penetration monitoring when welding non magnetic materials. The results also imply that it is possible to measure the dimensions of the plasma efflux or weld root, and use this information in a feedback control system and, thus, maintain the required weld quality.

Repeatability ofthe recipe parameters of a corrugated board machine against warp

The warp of corrugated board is the most prevalent quality problem incorrugated board industry. Nowadays corrugators provide high quality board but there often occurs a warp problem within the production of some board grades. One of the main reasons for that are the humidity and the temperature levels of the raw materials. The goal of the research is to find out howthe adjusted corrugator recipe parameters required for appropriate running of the corrugated board are repeatable for the considered board grades, how the temperature and humidity imbalances of the raw material papers influence on the warpformation of the finished board. Furthermore, the solutions for preventing warpof corrugated board are presented in the thesis.

On Modelling, System Identification and Control of Servo-Systems with a Flexible Load

The present study was done with two different servo-systems. In the first system, a servo-hydraulic system was identified and then controlled by a fuzzy gainscheduling controller. The second servo-system, an electro-magnetic linear motor in suppressing the mechanical vibration and position tracking of a reference model are studied by using a neural network and an adaptive backstepping controller respectively. Followings are some descriptions of research methods. Electro Hydraulic Servo Systems (EHSS) are commonly used in industry. These kinds of systems are nonlinearin nature and their dynamic equations have several unknown parameters.System identification is a prerequisite to analysis of a dynamic system. One of the most promising novel evolutionary algorithms is the Differential Evolution (DE) for solving global optimization problems. In the study, the DE algorithm is proposed for handling nonlinear constraint functionswith boundary limits of variables to find the best parameters of a servo-hydraulic system with flexible load. The DE guarantees fast speed convergence and accurate solutions regardless the initial conditions of parameters. The control of hydraulic servo-systems has been the focus ofintense research over the past decades. These kinds of systems are nonlinear in nature and generally difficult to control. Since changing system parameters using the same gains will cause overshoot or even loss of system stability. The highly non-linear behaviour of these devices makes them ideal subjects for applying different types of sophisticated controllers. The study is concerned with a second order model reference to positioning control of a flexible load servo-hydraulic system using fuzzy gainscheduling. In the present research, to compensate the lack of dampingin a hydraulic system, an acceleration feedback was used. To compare the results, a pcontroller with feed-forward acceleration and different gains in extension and retraction is used. The design procedure for the controller and experimental results are discussed. The results suggest that using the fuzzy gain-scheduling controller decrease the error of position reference tracking. The second part of research was done on a PermanentMagnet Linear Synchronous Motor (PMLSM). In this study, a recurrent neural network compensator for suppressing mechanical vibration in PMLSM with a flexible load is studied. The linear motor is controlled by a conventional PI velocity controller, and the vibration of the flexible mechanism is suppressed by using a hybrid recurrent neural network. The differential evolution strategy and Kalman filter method are used to avoid the local minimum problem, and estimate the states of system respectively. The proposed control method is firstly designed by using non-linear simulation model built in Matlab Simulink and then implemented in practical test rig. The proposed method works satisfactorily and suppresses the vibration successfully. In the last part of research, a nonlinear load control method is developed and implemented for a PMLSM with a flexible load. The purpose of the controller is to track a flexible load to the desired position reference as fast as possible and without awkward oscillation. The control method is based on an adaptive backstepping algorithm whose stability is ensured by the Lyapunov stability theorem. The states of the system needed in the controller are estimated by using the Kalman filter. The proposed controller is implemented and tested in a linear motor test drive and responses are presented.

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.

The Control of the Edge Shrinkage in Board

Tämän diplomityön tavoitteena oli löytää prosessiparametrejä nestepakkauskartongin reuna-alueiden kuivatuskutistuman hallintaan ja saada tuotteen reuna-alueiden sileystaso paremmaksi. Tarkoituksena oli parantaa reuna-alueiden painettavuusominaisuuksia sekä saada koneen poikkisuunnassa laadultaan parempi tuote. Työn kirjallisuusosassa on tarkasteltu työn kannalta nestepakkauskartongin kriittisimpiä ominaisuuksia, sileyttä ja jäykkyyttä. Lisäksi kirjallisuusosassa on tarkasteltu kuitujen ominaisuuksia, sylinterikuivatusta ja kuivatuskutistumaa. Kokeellisessa osassa on etsitty esitutkimuksella prosessiparametrejä, jotka ovat aiheuttaneet poikkisuunnan sileyserojen kasvun kartonkikoneen investoinnin jälkeen. Suoria korrelaatioita prosessiparametrien ja kuivatuskutistuman välille ei löydetty. Kokeellisen osan tehdasmittakaavaisissa koeajoissa tutkittiin kahdeksan eri parametrin vaikutusta kuivatuskutistumaan, jotka perustuivat kirjallisuuteen. Tutkituista parametreistä huulisuihkun iskukulman muutoksella sekä konesuuntaisella kuivatusprofiililla ei ollut vaikutusta kuivatuskutistumaan. Runkokerroksen mäntysellun korvaaminen koivusellulla vähensi kuivatuskutistumaa ja lisäsi sileyttä, mutta tuotteen palstautumislujuus ei tällöin ollut riittävä. Retentiokemikaalien reseptimuutoksilla pinta- ja taustakerroksen välillä, kuivatusosan nollatason laskulla ja perälaatikkosakeuksien pienentämisellä oli vähän vaikutusta kuivatuskutistumaan. Vaikutus reuna-alueiden sileyteen oli kuitenkin vähemmän kuin 10 %. Diplomityön perusteella kuivatusosan nopeuseroilla ja kuivatusviirojen kireyksillä oli suurin vaikutusta kuivatuskutistumaan ja reuna-alueiden sileystasoon. Lisäämällä nopeuseroja ja kiristämällä kuivatusviiroja reuna-alueiden sileyttä pystyttiin parantamaan yli 20 %.

Energy efficiency parameters in variable speed drives

The main purpose of this thesis is to measure and evaluate how accurately the current energy saving calculation in ABB’s new variable speed drive ACS850 works. The main topic of this thesis is energy-efficiency parameters. At the beginning of this thesis centrifugal pump, squirrel cage motor and variable speed drive, including some equations related to them, are being introduced. Also methods of throttling control and variable speed drive control of centrifugal pumps are being introduced. These subjects are introduced because the energy saving calculation in ACS850 is related to the centrifugal pumps usually driven by squirrel cage motors. The theory also includes short section about specific energy of pumping. Before measurements the current energy saving calculation of ACS850 is being introduced and analyzed. The measurements part includes introduction of measuring equipment, measurement results, summary and analysis of the measurements. At the end of this thesis a proposal for an improvement to the current energy saving calculation is being introduced and few proposals are made for new energy-efficiency parameters, which could be added to variable speed drives. At the end are also thoughts

Position sensorless electrically excited synchronous motor drive for industrial use based on direct flux linkage and torque control

Synchronous machines with an AC converter are used mainly in large drives, for example in ship propulsion drives as well as in rolling mill drives in steel industry. These motors are used because of their high efficiency, high overload capacity and good performance in the field weakening area. Present day drives for electrically excited synchronous motors are equipped with position sensors. Most drives for electrically excited synchronous motors will be equipped with position sensors also in future. This kind of drives with good dynamics are mainly used in metal industry. Drives without a position sensor can be used e.g. in ship propulsion and in large pump and blower drives. Nowadays, these drives are equipped with a position sensor, too. The tendency is to avoid a position sensor if possible, since a sensor reduces the reliability of the drive and increases costs (latter is not very significant for large drives). A new control technique for a synchronous motor drive is a combination of the Direct Flux Linkage Control (DFLC) based on a voltage model and a supervising method (e.g. current model). This combination is called Direct Torque Control method (DTC). In the case of the position sensorless drive, the DTC can be implemented by using other supervising methods that keep the stator flux linkage origin centered. In this thesis, a method for the observation of the drift of the real stator flux linkage in the DTC drive is introduced. It is also shown how this method can be used as a supervising method that keeps the stator flux linkage origin centered in the case of the DTC. In the position sensorless case, a synchronous motor can be started up with the DTC control, when a method for the determination of the initial rotor position presented in this thesis is used. The load characteristics of such a drive are not very good at low rotational speeds. Furthermore, continuous operation at a zero speed and at a low rotational speed is not possible, which is partly due to the problems related to the flux linkage estimate. For operation in a low speed area, a stator current control method based on the DFLC modulator (DMCQ is presented. With the DMCC, it is possible to start up and operate a synchronous motor at a zero speed and at low rotational speeds in general. The DMCC is necessary in situations where high torque (e.g. nominal torque) is required at the starting moment, or if the motor runs several seconds at a zero speed or at a low speed range (up to 2 Hz). The behaviour of the described methods is shown with test results. The test results are presented for the direct flux linkage and torque controlled test drive system with a 14.5 kVA, four pole salient pole synchronous motor with a damper winding and electric excitation. The static accuracy of the drive is verified by measuring the torque in a static load operation, and the dynamics of the drive is proven in load transient tests. The performance of the drive concept presented in this work is sufficient e.g. for ship propulsion and for large pump drives. Furthermore, the developed methods are almost independent of the machine parameters.