Electric Motor and Frequency Converter Markets in Latin America and Especially in the Mining Industry of Chile

Latinalaisen Amerikan osuus maailmantaloudesta on pieni verrattuna sen maantieteelliseen kokoon, väkilukuun ja luonnonvaroihin. Aluetta pidetään kuitenkin yhtenä tulevaisuuden merkittävistä kasvumarkkinoista. Useissa Latinalaisen Amerikan maissa on teollisuutta, joka hyödyntää luonnonvaroja ja tuottaa raaka-aineita sekä kotimaan että ulkomaiden markkinoille. Tällaisia tyypillisiä teollisuudenaloja Latinalaisessa Amerikassa ovat kaivos- ja metsäteollisuus sekä öljyn ja maakaasun tuotanto. Näiden teollisuudenalojen tuotantolaitteiden ja koneiden valmistusta ei Latinalaisessa Amerikassa juurikaan ole. Ne tuodaan yleensä Pohjois-Amerikasta ja Euroopasta. Tässä diplomityössä tutkitaan sähkömoottorien ja taajuusmuuttajien markkinapotentiaalia Latinalaisessa Amerikassa. Tutkimuksessa perehdytään Latinalaisen Amerikan maiden kansantalouksien tilaan sekä arvioidaan sähkömoottorien ja taajuusmuuttajien markkinoiden kokoa tullitilastojen avulla. Chilen kaivosteollisuudessa arvioidaan olevan erityistä potentiaalia. Diplomityössä selvitetään ostoprosessin kulkua Chilen kaivosteollisuudessa ja eri asiakastyyppien roolia siinä sekä tärkeimpiä päätöskriteerejä toimittaja- ja teknologiavalinnoissa.

Impingement jet cooling of end windings in a high-speed electric machine

The rotational speed of high-speed electric machines is over 15 000 rpm. These machines are compact in size when compared to the power rate. As a consequence, the heat fluxes are at a high level and the adequacy of cooling becomes an important design criterion. In the high-speed machines, the air gap between the stator and rotor is a narrow flow channel. The cooling air is produced with a fan and the flow is then directed to the air gap. The flow in the gap does not provide sufficient cooling for the stator end windings, and therefore additional cooling is required. This study investigates the heat transfer and flow fields around the coil end windings when cooling jets are used. As a result, an innovative and new assembly is introduced for the cooling jets, with the benefits of a reduced amount of hot spots, a lower pressure drop, and hence a lower power need for the cooling fan. The gained information can also be applied to improve the cooling of electric machines through geometry modifications. The objective of the research is to determine the locations of the hot spots and to find out induced pressure losses with different jet alternatives. Several possibilities to arrange the extra cooling are considered. In the suggested approach cooling is provided by using a row of air jets. The air jets have three main tasks: to cool the coils effectively by direct impingement jets, to increase and cool down the flow that enters the coil end space through the air gap, and to ensure the correct distribution of the flow by forming an air curtain with additional jets. One important aim of this study is the arrangement of cooling jets in such manner that hot spots can be avoided to wide extent. This enables higher power density in high-speed motors. This cooling system can also be applied to the ordinary electric machines when efficient cooling is needed. The numerical calculations have been performed using a commercial Computational Fluid Dynamics software. Two geometries have been generated: cylindrical for the studied machine and Cartesian for the experimental model. The main parameters include the positions, arrangements and number of jets, the jet diameters, and the jet velocities. The investigated cases have been tested with two widely used turbulence models and using a computational grid of over 500 000 cells. The experimental tests have been made by using a simplified model for the end winding space with cooling jets. In the experiments, an emphasis has been given to flow visualisation. The computational analysis shows good agreement with the experimental results. Modelling of the cooling jet arrangement enables also a better understanding of the complex system of heat transfer at end winding space.

Cardiovascular effects of short term exposure to electric and magnetic fields of electricity power transmission

In the electrical industry the 50 Hz electric and magnetic fields are often higher than in the average working environment. The electric and magnetic fields can be studied by measuring or by calculatingthe fields in the environment. For example, the electric field under a 400 kV power line is 1 to 10 kV/m, and the magnetic flux density is 1 to 15 µT. Electricand magnetic fields of a power line induce a weak electric field and electric currents in the exposed body. The average current density in a human being standing under a 400 kV line is 1 to 2 mA/m2. The aim of this study is to find out thepossible effects of short term exposure to electric and magnetic fields of electricity power transmission on workers' health, in particular the cardiovascular effects. The study consists of two parts; Experiment I: influence on extrasystoles, and Experiment II: influence on heart rate. In Experiment I two groups, 26 voluntary men (Group 1) and 27 transmission-line workers (Group 2), were measured. Their electrocardiogram (ECG) was recorded with an ambulatory recorder both in and outside the field. In Group 1 the fields were 1.7 to 4.9 kV/m and 1.1 to 7.1 pT; in Group 2 they were 0.1 to 10.2 kV/m and 1.0 to 15.4 pT. In the ECG analysis the only significant observation was a decrease in the heart rate after field exposure (Group 1). The drop cannot be explained with the first measuring method. Therefore Experiment II was carried out. In Experiment II two groups were used; Group 1 (26 male volunteers) were measured in real field exposure, Group 2 (15 male volunteers) in "sham" fields. The subjects of Group 1 spent 1 h outside the field, then 1 h in the field under a 400 kV transmission line, and then again 1 h outside the field. Under the 400 kV linethe field strength varied from 3.5 to 4.3 kV/m, and from 1.4 to 6.6 pT. Group 2spent the entire test period (3 h) in a 33 kV outdoor testing station in a "sham" field. ECG, blood pressure, and electroencephalogram (EEG) were measured by ambulatory methods. Before and after the field exposure, the subjects performed some cardiovascular autonomic function tests. The analysis of the results (Experiments I and II) showed that extrasystoles or arrythmias were as frequent in the field (below 4 kV/m and 4 pT) as outside it. In Experiment II there was no decrease detected in the heart rate, and the systolic and diastolic blood pressure stayed nearly the same. No health effects were found in this study.

Numerical and ExperimentalModelling of Gas Flow and Heat Transfer in the Air Gap of An Electric Machine

This work deals with the cooling of high-speed electric machines, such as motors and generators, through an air gap. It consists of numerical and experimental modelling of gas flow and heat transfer in an annular channel. Velocity and temperature profiles are modelled in the air gap of a high-speed testmachine. Local and mean heat transfer coefficients and total friction coefficients are attained for a smooth rotor-stator combination at a large velocity range. The aim is to solve the heat transfer numerically and experimentally. The FINFLO software, developed at Helsinki University of Technology, has been used in the flow solution, and the commercial IGG and Field view programs for the grid generation and post processing. The annular channel is discretized as a sector mesh. Calculation is performed with constant mass flow rate on six rotational speeds. The effect of turbulence is calculated using three turbulence models. The friction coefficient and velocity factor are attained via total friction power. The first part of experimental section consists of finding the proper sensors and calibrating them in a straight pipe. After preliminary tests, a RdF-sensor is glued on the walls of stator and rotor surfaces. Telemetry is needed to be able to measure the heat transfer coefficients at the rotor. The mean heat transfer coefficients are measured in a test machine on four cooling air mass flow rates at a wide Couette Reynolds number range. The calculated values concerning the friction and heat transfer coefficients are compared with measured and semi-empirical data. Heat is transferred from the hotter stator and rotor surfaces to the coolerair flow in the air gap, not from the rotor to the stator via the air gap, althought the stator temperature is lower than the rotor temperature. The calculatedfriction coefficients fits well with the semi-empirical equations and precedingmeasurements. On constant mass flow rate the rotor heat transfer coefficient attains a saturation point at a higher rotational speed, while the heat transfer coefficient of the stator grows uniformly. The magnitudes of the heat transfer coefficients are almost constant with different turbulence models. The calibrationof sensors in a straight pipe is only an advisory step in the selection process. Telemetry is tested in the pipe conditions and compared to the same measurements with a plain sensor. The magnitudes of the measured data and the data from the semi-empirical equation are higher for the heat transfer coefficients than thenumerical data considered on the velocity range. Friction and heat transfer coefficients are presented in a large velocity range in the report. The goals are reached acceptably using numerical and experimental research. The next challenge is to achieve results for grooved stator-rotor combinations. The work contains also results for an air gap with a grooved stator with 36 slots. The velocity field by the numerical method does not match in every respect the estimated flow mode. The absence of secondary Taylor vortices is evident when using time averagednumerical simulation.

Analysis of torque and speed ripple producing non-idealities of frequency converters in electric drives

Electric motors driven by adjustable-frequency converters may produce periodic excitation forces that can cause torque and speed ripple. Interaction with the driven mechanical system may cause undesirable vibrations that affect the system performance and lifetime. Direct drives in sensitive applications, such as elevators or paper machines, emphasize the importance of smooth torque production. This thesis analyses the non-idealities of frequencyconverters that produce speed and torque ripple in electric drives. The origin of low order harmonics in speed and torque is examined. It is shown how different current measurement error types affect the torque. As the application environment, direct torque control (DTC) method is applied to permanent magnet synchronous machines (PMSM). A simulation model to analyse the effect of the frequency converter non-idealities on the performance of the electric drives is created. Themodel enables to identify potential problems causing torque vibrations and possibly damaging oscillations in electrically driven machine systems. The model is capable of coupling with separate simulation software of complex mechanical loads. Furthermore, the simulation model of the frequency converter's control algorithm can be applied to control a real frequency converter. A commercial frequencyconverter with standard software, a permanent magnet axial flux synchronous motor and a DC motor as the load are used to detect the effect of current measurement errors on load torque. A method to reduce the speed and torque ripple by compensating the current measurement errors is introduced. The method is based on analysing the amplitude of a selected harmonic component of speed as a function oftime and selecting a suitable compensation alternative for the current error. The speed can be either measured or estimated, so the compensation method is applicable also for speed sensorless drives. The proposed compensation method is tested with a laboratory drive, which consists of commercial frequency converter hardware with self-made software and a prototype PMSM. The speed and torque rippleof the test drive are reduced by applying the compensation method. In addition to the direct torque controlled PMSM drives, the compensation method can also beapplied to other motor types and control methods.

Market Study of Electric Drive Motion Control Business

Tämän diplomityön tavoitteena oli tutkia älykkäiden paikoituskäyttöjen markkinoita ja liiketoimintamalleja. Työn pääongelmina oli määritellä alalla käytössä olevaa terminologiaa, määrittää markkinoiden koko paikoitusominaisuudet omaaville kolmivaihetaajuusmuuttajille, tutkia viiden alalla toimivan paikoituskäyttötoimittajan liiketoimintarakenteita ja tuotteita teknisestä näkökulmasta sekä esitellä kaksi teollisuuden käyttökohdetta paikoituskäytölle. Työn sisältö voidaan jakaa neljään eri osioon. Terminologian määrittely- ja markkinatutkimusosiot perustuvat pääasiassa kirjallisuustutkimukseen. Paikoituskäyttöjen toimittajia sekä niiden tuotteita käsittelevä osuus perustuu kirjallisuustutkimukseen sekä teknisiin esitteisiin ja manuaaleihin. Paikoituskäyttöjen sovellusesimerkit on selvitetty haastatteluin. Työ painottuu paikoituskäyttötoimittajien tuotteiden, tuoteominaisuuksien ja tuotetarjonnan tarkasteluun. Työn tuloksena on määritelty paikoituskäyttöjen liiketoiminnan tärkeimmät termit, paikoituskäyttöjen markkinoiden koko sekä markkinoiden koko paikoitusominaisuudet omaavalle kolmivaihetaajuusmuuttajalle. Alalla toimivien paikoituskäyttötoimittajien liiketoimintarakenne on selvitetty, jonka mukaan toimittajat on profiloitu komponentti-, komponenttipaketti-, toimialakeskeisiksi tai automaatiotoimittajiksi. Toimittajien paikoituskäyttötuotteet on luokiteltu viiteen eri luokkaan niiden teknisten ominaisuuksien perusteella. Lisäksi paikoituskäyttöjen suorituskyvyt on selvitetty säätimien momentti-, nopeus-, ja paikoituslaskenta-aikatasojen sekä kenttäväyläliityntöjen suhteen. Työssä kuvatut vanerinsorvausprosessi sekä FMS -materiaalinkäsittelyprosessi esittävät paikoituskäyttöjen potentiaalisia sovelluskohteita.

Real-time Linux in electric drive systems

Reaaliaikaisten käyttöjärjestelmien käyttö sulautetuissa järjestelmissä on kasvamassa koko ajan. Sulautettuja tietokoneita käytetään yhä useammassa kohteessa kuten sähkökäyttöjen ohjauksessa. Sähkökäyttöjen ohjaus hoidetaan nykyisin yleensä nopealla digitaalisella signaaliprosessorilla (DSP), jolloin ohjelmointi ja päivittäminen on hidasta ja vaikeaa johtuen käytettävästä matalan tason Assembler-kielestä. Ratkaisuna yleiskäyttöisten prosessorien ja reaaliaikakäyttöjärjestelmien käyttö. Kaupalliset reaaliaikakäyttöjärjestelmät ovat kalliita ja lähdekoodin saaminen omaan käyttöön jopa mahdotonta. Linux on ei-kaupallinen avoimen lähdekoodin käyttöjärjestelmä, joten sen käyttö on ilmaista ja sitä voi muokata vapaasti. Linux:iin on saatavana useita laajennuksia, jotka tekevät siitä reaaliaikaisen käyttöjärjestelmän. Vaihtoehtoina joko kova (hard) tai pehmeä (soft) reaaliaikaisuus. Linux:iin on olemassa valmiita kehitysympäristöjä mutta ne kaipaavat parannusta ennen kuin niitä voidaan käyttää suuressa mittakaavassa teollisuudessa. Reaaliaika Linux ei sovellus nopeisiin ohjauslooppeihin (<100 ms) koska nopeus ei riitä vielä mutta nopeus kasvaa samalla kun prosessorit kehittyvät. Linux soveltuu hyvin rajapinnaksi nopean ohjauksen ja käyttäjän välille ja hitaampaan ohjaukseen.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

Electric energy recovery system for a hydraulic forklift

This thesis studies the possibilities to recover energy in a hydraulic forklift system. Controlling of the system is done directly with an electric servo motor drive and a hydraulic pump. A real system was built and tested and simulations of the system were made with Matlab. Results of the system and simulations were analysed and compared and according to them, energy can be recovered efficiently from the hydraulic forklift system. Also new ideas and directions of further research were obtained with the help of this research.

System Investigation for Hybrid Electric Vehicle

A hybrid electric vehicle is a fast-growing concept in the field of vehicle industry. Nowadays two global problems make manufactures to develop such systems. These problems are: the growing cost of a fuel and environmental pollution. Also development of controlled electric drive with high control accuracy and reliability allows improving of vehicle drive characteristics. The objective of this Diploma Thesis is to investigate the possibilities of electrical drive application for new principle of parallel hybrid vehicle system. Electric motor calculations, selection of most suitable control system and other calculations are needed. This work is not final work for such topic. Further investigation with more precise calculations, modeling, measurements and cost calculations are needed to answer the question if such system is efficient.

Active Damping and Energy Recovery in a Hydraulic Boom Controlled by an Electric Drive

The aim of the study is to obtain a mathematical description for an alternative variant of controlling a hydraulic circuit with an electrical drive. The electrical and hydraulic systems are described by basic mathematical equations. The flexibilities of the load and boom is modeled with assumed mode method. The model is achieved and proven with simulations. The controller is constructed and proven to decrease oscillations and improve the dynamic response of the system.

A Dependency Parsing Approach to Biomedical Text Mining

Biomedical research is currently facing a new type of challenge: an excess of information, both in terms of raw data from experiments and in the number of scientific publications describing their results. Mirroring the focus on data mining techniques to address the issues of structured data, there has recently been great interest in the development and application of text mining techniques to make more effective use of the knowledge contained in biomedical scientific publications, accessible only in the form of natural human language. This thesis describes research done in the broader scope of projects aiming to develop methods, tools and techniques for text mining tasks in general and for the biomedical domain in particular. The work described here involves more specifically the goal of extracting information from statements concerning relations of biomedical entities, such as protein-protein interactions. The approach taken is one using full parsing—syntactic analysis of the entire structure of sentences—and machine learning, aiming to develop reliable methods that can further be generalized to apply also to other domains. The five papers at the core of this thesis describe research on a number of distinct but related topics in text mining. In the first of these studies, we assessed the applicability of two popular general English parsers to biomedical text mining and, finding their performance limited, identified several specific challenges to accurate parsing of domain text. In a follow-up study focusing on parsing issues related to specialized domain terminology, we evaluated three lexical adaptation methods. We found that the accurate resolution of unknown words can considerably improve parsing performance and introduced a domain-adapted parser that reduced the error rate of theoriginal by 10% while also roughly halving parsing time. To establish the relative merits of parsers that differ in the applied formalisms and the representation given to their syntactic analyses, we have also developed evaluation methodology, considering different approaches to establishing comparable dependency-based evaluation results. We introduced a methodology for creating highly accurate conversions between different parse representations, demonstrating the feasibility of unification of idiverse syntactic schemes under a shared, application-oriented representation. In addition to allowing formalism-neutral evaluation, we argue that such unification can also increase the value of parsers for domain text mining. As a further step in this direction, we analysed the characteristics of publicly available biomedical corpora annotated for protein-protein interactions and created tools for converting them into a shared form, thus contributing also to the unification of text mining resources. The introduced unified corpora allowed us to perform a task-oriented comparative evaluation of biomedical text mining corpora. This evaluation established clear limits on the comparability of results for text mining methods evaluated on different resources, prompting further efforts toward standardization. To support this and other research, we have also designed and annotated BioInfer, the first domain corpus of its size combining annotation of syntax and biomedical entities with a detailed annotation of their relationships. The corpus represents a major design and development effort of the research group, with manual annotation that identifies over 6000 entities, 2500 relationships and 28,000 syntactic dependencies in 1100 sentences. In addition to combining these key annotations for a single set of sentences, BioInfer was also the first domain resource to introduce a representation of entity relations that is supported by ontologies and able to capture complex, structured relationships. Part I of this thesis presents a summary of this research in the broader context of a text mining system, and Part II contains reprints of the five included publications.

Opinion Mining

In this thesis we study the field of opinion mining by giving a comprehensive review of the available research that has been done in this topic. Also using this available knowledge we present a case study of a multilevel opinion mining system for a student organization's sales management system. We describe the field of opinion mining by discussing its historical roots, its motivations and applications as well as the different scientific approaches that have been used to solve this challenging problem of mining opinions. To deal with this huge subfield of natural language processing, we first give an abstraction of the problem of opinion mining and describe the theoretical frameworks that are available for dealing with appraisal language. Then we discuss the relation between opinion mining and computational linguistics which is a crucial pre-processing step for the accuracy of the subsequent steps of opinion mining. The second part of our thesis deals with the semantics of opinions where we describe the different ways used to collect lists of opinion words as well as the methods and techniques available for extracting knowledge from opinions present in unstructured textual data. In the part about collecting lists of opinion words we describe manual, semi manual and automatic ways to do so and give a review of the available lists that are used as gold standards in opinion mining research. For the methods and techniques of opinion mining we divide the task into three levels that are the document, sentence and feature level. The techniques that are presented in the document and sentence level are divided into supervised and unsupervised approaches that are used to determine the subjectivity and polarity of texts and sentences at these levels of analysis. At the feature level we give a description of the techniques available for finding the opinion targets, the polarity of the opinions about these opinion targets and the opinion holders. Also at the feature level we discuss the various ways to summarize and visualize the results of this level of analysis. In the third part of our thesis we present a case study of a sales management system that uses free form text and that can benefit from an opinion mining system. Using the knowledge gathered in the review of this field we provide a theoretical multi level opinion mining system (MLOM) that can perform most of the tasks needed from an opinion mining system. Based on the previous research we give some hints that many of the laborious market research tasks that are done by the sales force, which uses this sales management system, can improve their insight about their partners and by that increase the quality of their sales services and their overall results.