AMB system for high-speed motors using automatic commissioning

The general trend towards increasing e ciency and energy density drives the industry to high-speed technologies. Active Magnetic Bearings (AMBs) are one of the technologies that allow contactless support of a rotating body. Theoretically, there are no limitations on the rotational speed. The absence of friction, low maintenance cost, micrometer precision, and programmable sti ness have made AMBs a viable choice for highdemanding applications. Along with the advances in power electronics, such as signi cantly improved reliability and cost, AMB systems have gained a wide adoption in the industry. The AMB system is a complex, open-loop unstable system with multiple inputs and outputs. For normal operation, such a system requires a feedback control. To meet the high demands for performance and robustness, model-based control techniques should be applied. These techniques require an accurate plant model description and uncertainty estimations. The advanced control methods require more e ort at the commissioning stage. In this work, a methodology is developed for an automatic commissioning of a subcritical, rigid gas blower machine. The commissioning process includes open-loop tuning of separate parts such as sensors and actuators. The next step is to apply a system identi cation procedure to obtain a model for the controller synthesis. Finally, a robust model-based controller is synthesized and experimentally evaluated in the full operating range of the system. The commissioning procedure is developed by applying only the system components available and a priori knowledge without any additional hardware. Thus, the work provides an intelligent system with a self-diagnostics feature and an automatic commissioning.

Accuracy Analysis of Frequency Converter Estimates in Diagnostic Applications

Transportation of fluids is one of the most common and energy intensive processes in the industrial and HVAC sectors. Pumping systems are frequently subject to engineering malpractice when dimensioned, which can lead to poor operational efficiency. Moreover, pump monitoring requires dedicated measuring equipment, which imply costly investments. Inefficient pump operation and improper maintenance can increase energy costs substantially and even lead to pump failure. A centrifugal pump is commonly driven by an induction motor. Driving the induction motor with a frequency converter can diminish energy consumption in pump drives and provide better control of a process. In addition, induction machine signals can also be estimated by modern frequency converters, dispensing with the use of sensors. If the estimates are accurate enough, a pump can be modelled and integrated into the frequency converter control scheme. This can open the possibility of joint motor and pump monitoring and diagnostics, thereby allowing the detection of reliability-reducing operating states that can lead to additional maintenance costs. The goal of this work is to study the accuracy of rotational speed, torque and shaft power estimates calculated by a frequency converter. Laboratory tests were performed in order to observe estimate behaviour in both steady-state and transient operation. An induction machine driven by a vector-controlled frequency converter, coupled with another induction machine acting as load was used in the tests. The estimated quantities were obtained through the frequency converter’s Trend Recorder software. A high-precision, HBM T12 torque-speed transducer was used to measure the actual values of the aforementioned variables. The effect of the flux optimization energy saving feature on the estimate quality was also studied. A processing function was developed in MATLAB for comparison of the obtained data. The obtained results confirm the suitability of this particular converter to provide accurate enough estimates for pumping applications.

Design of an amplifier and an instrumentation setup for a harsh environment heat flux measurement application – case axial flux electric machine

Measurement is a tool for researching. Therefore, it is important that the measuring process is carried out correctly, without distorting the signal or the measured event. Researches of thermoelectric phenomena have been focused more on transverse thermoelectric phenomena during recent decades. Transverse Seebeck effect enables to produce thinner and faster heat flux sensor than before. Studies about transverse Seebeck effect have so far focused on materials, so in this Master’s Thesis instrumentation of transverse Seebeck effect based heat flux sensor is studied, This Master’s Thesis examines an equivalent circuit of transverse Seebeck effect heat flux sensors, their connectivity to electronics and choosing and design a right type amplifier. The research is carried out with a case study which is Gradient Heat Flux Sensors and an electrical motor. In this work, a general equivalent circuit was presented for the transverse Seebeck effect-based heat flux sensor. An amplifier was designed for the sensor of the case study, and the solution was produced for the measurement of the local heat flux of the electric motor to improve the electromagnetic compatibility.

Electrical Machine Product Development; Transmission to Lean Approach

The requirements set by the market for electrical machines become increasingly demanding requiring more sophisticated technological solutions. Companies producing electrical ma-chines are challenged to develop machines that provide competitive edge for the customer for example through increased efficiency, reliability or some customer specific special requirement. The objective of this thesis is to derive a proposal for the first steps to transform the electrical machine product development process of a manufacturing company towards lean product development. The current product development process in the company is presented together with the processes of four other companies interviewed for the thesis. On the basis of current processes of the electrical machine industry and the related literature, a generalized electrical machine product development process is derived. The management isms and –tools utilized by the companies are analyzed. Adoption of lean Pull-Event –reviews, Oobeya –management and Knowledge based product development are suggested as the initial steps of implementing lean product development paradigm in the manufacturing company. Proposals for refining the cur-rent product development process and increasing the stakeholder involvement in the development projects are made. Lean product development is finding its way to Finnish electrical machine industry, but the results will be available only after the methods have been implemented and adopted by the companies. There is some enthusiasm about the benefits of lean approach and if executed successfully it will provide competitive edge for the Finnish electrical machine industry.

Energy Efficiency of a Diesel-Electric MobileWorking Machine

The power demand of many mobile working machines such as mine loaders, straddle carriers and harvesters varies significantly during operation, and typically, the average power demand of a working machine is considerably lower than the demand for maximum power. Consequently, for most of the time, the diesel engine of a working machine operates at a poor efficiency far from its optimum efficiency range. However, the energy efficiency of dieseldriven working machines can be improved by electric hybridization. This way, the diesel engine can be dimensioned to operate within its optimum efficiency range, and the electric drive with its energy storages responds to changes in machine loading. A hybrid working machine can be implemented in many ways either as a parallel hybrid, a series hybrid or a combination of these two. The energy efficiency of hybrid working machines can be further enhanced by energy recovery and reuse. This doctoral thesis introduces the component models required in the simulation model of a working machine. Component efficiency maps are applied to the modelling; the efficiency maps for electrical machines are determined analytically in the whole torque–rotational speed plane based on the electricalmachine parameters. Furthermore, the thesis provides simulation models for parallel, series and parallel-series hybrid working machines. With these simulation models, the energy consumption of the working machine can be analysed. In addition, the hybridization process is introduced and described. The thesis provides a case example of the hybridization and dimensioning process of a working machine, starting from the work cycle of the machine. The selection and dimensioning of the hybrid system have a significant impact on the energy consumption of a hybrid working machine. The thesis compares the energy consumption of a working machine implemented by three different hybrid systems (parallel, series and parallel-series) and with different component dimensions. The payback time of a hybrid working machine and the energy storage lifetime are also estimated in the study.

Application of a Pid+fuzzy controller on the motion control system in machine tools

This work deals with an hybrid PID+fuzzy logic controller applied to control the machine tool biaxial table motions. The non-linear model includes backlash and the axis elasticity. Two PID controllers do the primary table control. A third PID+fuzzy controller has a cross coupled structure whose function is to minimise the trajectory contour errors. Once with the three PID controllers tuned, the system is simulated with and without the third controller. The responses results are plotted and compared to analyse the effectiveness of this hybrid controller over the system. They show that the proposed methodology reduces the contour error in a proportion of 70:1.

Tooth-Coil Permanent Magnet Synchronous Machine Design for Special Applications

This doctoral thesis presents a study on the design of tooth-coil permanent magnet synchronous machines. The electromagnetic properties of concentrated non-overlapping winding permanent magnet synchronous machines, or simply tooth-coil permanent magnet synchronous machines (TC-PMSMs), are studied in details. It is shown that current linkage harmonics play the deterministic role in the behavior of this type of machines. Important contributions are presented as regards of calculation of parameters of TC-PMSMs,particularly the estimation of inductances. The current linkage harmonics essentially define the air-gap harmonic leakage inductance, rotor losses and localized temporal inductance variation. It is proven by FEM analysis that inductance variation caused by the local temporal harmonic saturation results in considerable torque ripple, and can influence on sensorless control capabilities. Example case studies an integrated application of TC-IPMSMs in hybrid off-highway working vehicles. A methodology for increasing the efficiency of working vehicles is introduced. It comprises several approaches – hybridization, working operations optimization, component optimization and integration. As a result of component optimization and integration, a novel integrated electro-hydraulic energy converter (IEHEC) for off-highway working vehicles is designed. The IEHEC can considerably increase the operational efficiency of a hybrid working vehicle. The energy converter consists of an axial-piston hydraulic machine and an integrated TCIPMSM being built on the same shaft. The compact assembly of the electrical and hydraulic machines enhances the ability to find applications for such a device in the mobile environment of working vehicles.Usage of hydraulic fluid, typically used in working actuators, enables direct-immersion oil cooling of designed electrical machine, and further increases the torque- and power- densities of the whole device.

Analysis of open CNC architecture for machine tools

The evolution of digital circuit technology, leadind to higher speeds and more reliability allowed the development of machine controllers adapted to new production systems (e.g., Flexible Manufacturing Systems - FMS). Most of the controllers are developed in agreement with the CNC technology of the correspondent machine tool manufacturer. Any alterations or adaptation of their components are not easy to be implemented. The machine designers face up hardware and software restrictions such as lack of interaction among system's elements and impossibility of adding new function. This is due to hardware incompatibility and to software not allowing alterations in the source program. The introduction of open architecture philosophy propitiated the evolution of a new generation of numeric controllers. This brought the conventional CNC technology to the standard IBM - PC microcomputer. As a consequence, the characteristics of the CNC (positioning) and the microcomputer (easy of programming, system configuration, network communication etc) are combined. Some researchers have addressed a flexible structure of software and hardware allowing changes in the hardware basic configuration and all control software levels. In this work, the development of open architecture controllers in the OSACA, OMAC, HOAM-CNC and OSEC architectures is described.

Machine vision methods for process measurements in pulping

The papermaking industry has been continuously developing intelligent solutions to characterize the raw materials it uses, to control the manufacturing process in a robust way, and to guarantee the desired quality of the end product. Based on the much improved imaging techniques and image-based analysis methods, it has become possible to look inside the manufacturing pipeline and propose more effective alternatives to human expertise. This study is focused on the development of image analyses methods for the pulping process of papermaking. Pulping starts with wood disintegration and forming the fiber suspension that is subsequently bleached, mixed with additives and chemicals, and finally dried and shipped to the papermaking mills. At each stage of the process it is important to analyze the properties of the raw material to guarantee the product quality. In order to evaluate properties of fibers, the main component of the pulp suspension, a framework for fiber characterization based on microscopic images is proposed in this thesis as the first contribution. The framework allows computation of fiber length and curl index correlating well with the ground truth values. The bubble detection method, the second contribution, was developed in order to estimate the gas volume at the delignification stage of the pulping process based on high-resolution in-line imaging. The gas volume was estimated accurately and the solution enabled just-in-time process termination whereas the accurate estimation of bubble size categories still remained challenging. As the third contribution of the study, optical flow computation was studied and the methods were successfully applied to pulp flow velocity estimation based on double-exposed images. Finally, a framework for classifying dirt particles in dried pulp sheets, including the semisynthetic ground truth generation, feature selection, and performance comparison of the state-of-the-art classification techniques, was proposed as the fourth contribution. The framework was successfully tested on the semisynthetic and real-world pulp sheet images. These four contributions assist in developing an integrated factory-level vision-based process control.

Switchable lanthanide fluorescence probes in homogenous molecular diagnostics

The number of molecular diagnostic assays has increased tremendously in recent years.Nucleic acid diagnostic assays have been developed, especially for the detection of human pathogenic microbes and genetic markers predisposing to certain diseases. Closed-tube methods are preferred because they are usually faster and easier to perform than heterogenous methods and in addition, target nucleic acids are commonly amplified leading to risk of contamination of the following reactions by the amplification product if the reactions are opened. The present study introduces a new closed-tube switchable complementation probes based PCR assay concept where two non-fluorescent probes form a fluorescent lanthanide chelate complex in the presence of the target DNA. In this dual-probe PCR assay method one oligonucleotide probe carries a non-fluorescent lanthanide chelate and another probe a light absorbing antenna ligand. The fluorescent lanthanide chelate complex is formed only when the non-fluorescent probes are hybridized to adjacent positions into the target DNA bringing the reporter moieties in close proximity. The complex is formed by self-assembled lanthanide chelate complementation where the antenna ligand is coordinated to the lanthanide ion captured in the chelate. The complementation probes based assays with time-resolved fluorescence measurement showed low background signal level and hence, relatively high nucleic acid detection sensitivity (low picomolar target concentration). Different lanthanide chelate structures were explored and a new cyclic seven dentate lanthanide chelate was found suitable for complementation probe method. It was also found to resist relatively high PCR reaction temperatures, which was essential for the PCR assay applications. A seven-dentate chelate with two unoccupied coordination sites must be used instead of a more stable eight- or nine-dentate chelate because the antenna ligand needs to be coordinated to the free coordination sites of the lanthanide ion. The previously used linear seven-dentate lanthanide chelate was found to be unstable in PCR conditions and hence, the new cyclic chelate was needed. The complementation probe PCR assay method showed high signal-to-background ratio up to 300 due to a low background fluorescence level and the results (threshold cycles) in real-time PCR were reached approximately 6 amplification cycles earlier compared to the commonly used FRET-based closed-tube PCR method. The suitability of the complementation probe method for different nucleic acid assay applications was studied. 1) A duplex complementation probe C. trachomatis PCR assay with a simple 10-minute urine sample preparation was developed to study suitability of the method for clinical diagnostics. The performance of the C. trachomatis assay was equal to the commercial C. trachomatis nucleic acid amplification assay containing more complex sample preparation based on DNA extraction. 2) A PCR assay for the detection of HLA-DQA1*05 allele, that is used to predict the risk of type 1 diabetes, was developed to study the performance of the method in genotyping. A simple blood sample preparation was used where the nucleic acids were released from dried blood sample punches using high temperature and alkaline reaction conditions. The complementation probe HLA-DQA1*05 PCR assay showed good genotyping performance correlating 100% with the routinely used heterogenous reference assay. 3) To study the suitability of the complementation probe method for direct measurement of the target organism, e.g., in the culture media, the complementation probes were applied to amplificationfree closed-tube bacteriophage quantification by measuring M13 bacteriophage ssDNA. A low picomolar bacteriophage concentration was detected in a rapid 20- minute assay. The assay provides a quick and reliable alternative to the commonly used and relatively unreliable UV-photometry and time-consuming culture based bacteriophage detection methods and indicates that the method could also be used for direct measurement of other micro-organisms. The complementation probe PCR method has a low background signal level leading to a high signal-to-background ratio and relatively sensitive nucleic acid detection. The method is compatible with simple sample preparation and it was shown to tolerate residues of urine, blood, bacteria and bacterial culture media. The common trend in nucleic acid diagnostics is to create easy-to-use assays suitable for rapid near patient analysis. The complementation probe PCR assays with a brief sample preparation should be relatively easy to automate and hence, would allow the development of highperformance nucleic acid amplification assays with a short overall assay time.

Liminal Monster and the Conflict Between Human and Machine: The Shrike in Dan Simmons’ Hyperion and The Fall of Hyperion

Tarkastelen tutkielmassani Dan Simmonsin kaksiosaista tieteisfiktioteosta, joka koostuu romaaneista Hyperion ja The Fall of Hyperion. Keskityn teoksissa esiintyvään Shrike-hirviöön, joka edustaa ihmiskunnan pelkäämää potentiaalista konfliktia ihmisten ja koneiden välillä. Pelko ja konflikti ovat keskeisiä teemoja paitsi tieteisfiktiossa, myös hirviöteoksissa yleensä, ja näiden kahden käyttö samassa kertomuksessa luo otolliset edellytykset nyky-yhteiskunnan ahdistusten kuvaamiseen. Hirviöitä ja tieteisfiktiota on tätä nykyä tutkittu melko laajalti, mutta Shrike on aiemmin jäänyt vähälle huomiolle. Lähtökohtaisen teoreettisen viitekehyksen tutkimukselleni ovat luoneet Jeffrey Cohenin Monster Theory: Reading Culture, Stephen Asman On Monsters: An Unnatural History of Our Worst Fears sekä Holly Lynn Baumgartnerin ja Roger Davisin At the Interface: Hosting the Monster. Teoksista kokoamani hirviöteorian kautta tarkastelen sitä, miten Shriken puoliksi orgaaninen ja puoliksi keinotekoinen keho heijastaa niitä romaaneissa esiintyviä osa-alueita, joista tulevaisuudenpelko ja ihmisten ja koneiden väliseen konfliktin uhka koostuu. Koska Shrike on puoliksi orgaaninen ja puoliksi keinotekoinen, se on näiden ominaisuuksien kynnyksellä; tässä risteytyneessä kehossa yhdistyvät molemmat ääripäät, jolloin tämä keho myös symboloi osapuolten välistä konfliktia. Konfliktin lisäksi Shrike ilmentää niitä vastakkaisuuksia, joista ihmisten ja koneiden välisen konfliktin pelko rakentuu: itseyttä ja toiseutta, houkuttelevuutta ja luotaantyöntävyyttä, menneisyyttä ja tulevaisuutta sekä utopiaa ja dystopiaa.

Weed mapping using a machine vision system

Weed mapping is a useful tool for site-specific herbicide applications. The objectives of this study were (1) to determine the percentage of land area covered by weeds in no-till and conventionally tilled fields of common bean using digital image processing and geostatistics, and (2) to compare two types of cameras. Two digital cameras (color and infrared) and a differential GPS were affixed to a center pivot structure for image acquisition. Sample field images were acquired in a regular grid pattern, and the images were processed to estimate the percentage of weed cover. After calculating the georeferenced weed percentage values, maps were constructed using geostatistical techniques. Based on the results, color images are recommended for mapping the percentage of weed cover in no-till systems, while infrared images are recommended for weed mapping in conventional tillage systems.

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.

Flexible multibody dynamics and intelligent control of a hydraulically driven hybrid redundant robot machine

The assembly and maintenance of the International Thermonuclear Experimental Reactor (ITER) vacuum vessel (VV) is highly challenging since the tasks performed by the robot involve welding, material handling, and machine cutting from inside the VV. The VV is made of stainless steel, which has poor machinability and tends to work harden very rapidly, and all the machining operations need to be carried out from inside of the ITER VV. A general industrial robot cannot be used due to its poor stiffness in the heavy duty machining process, and this will cause many problems, such as poor surface quality, tool damage, low accuracy. Therefore, one of the most suitable options should be a light weight mobile robot which is able to move around inside of the VV and perform different machining tasks by replacing different cutting tools. Reducing the mass of the robot manipulators offers many advantages: reduced material costs, reduced power consumption, the possibility of using smaller actuators, and a higher payload-to-robot weight ratio. Offsetting these advantages, the lighter weight robot is more flexible, which makes it more difficult to control. To achieve good machining surface quality, the tracking of the end effector must be accurate, and an accurate model for a more flexible robot must be constructed. This thesis studies the dynamics and control of a 10 degree-of-freedom (DOF) redundant hybrid robot (4-DOF serial mechanism and 6-DOF 6-UPS hexapod parallel mechanisms) hydraulically driven with flexible rods under the influence of machining forces. Firstly, the flexibility of the bodies is described using the floating frame of reference method (FFRF). A finite element model (FEM) provided the Craig-Bampton (CB) modes needed for the FFRF. A dynamic model of the system of six closed loop mechanisms was assembled using the constrained Lagrange equations and the Lagrange multiplier method. Subsequently, the reaction forces between the parallel and serial parts were used to study the dynamics of the serial robot. A PID control based on position predictions was implemented independently to control the hydraulic cylinders of the robot. Secondly, in machining, to achieve greater end effector trajectory tracking accuracy for surface quality, a robust control of the actuators for the flexible link has to be deduced. This thesis investigates the intelligent control of a hydraulically driven parallel robot part based on the dynamic model and two schemes of intelligent control for a hydraulically driven parallel mechanism based on the dynamic model: (1) a fuzzy-PID self-tuning controller composed of the conventional PID control and with fuzzy logic, and (2) adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self-tuning of the gains of the PID controller, which are implemented independently to control each hydraulic cylinder of the parallel mechanism based on rod length predictions. The serial component of the hybrid robot can be analyzed using the equilibrium of reaction forces at the universal joint connections of the hexa-element. To achieve precise positional control of the end effector for maximum precision machining, the hydraulic cylinder should be controlled to hold the hexa-element. Thirdly, a finite element approach of multibody systems using the Special Euclidean group SE(3) framework is presented for a parallel mechanism with flexible piston rods under the influence of machining forces. The flexibility of the bodies is described using the nonlinear interpolation method with an exponential map. The equations of motion take the form of a differential algebraic equation on a Lie group, which is solved using a Lie group time integration scheme. The method relies on the local description of motions, so that it provides a singularity-free formulation, and no parameterization of the nodal variables needs to be introduced. The flexible slider constraint is formulated using a Lie group and used for modeling a flexible rod sliding inside a cylinder. The dynamic model of the system of six closed loop mechanisms was assembled using Hamilton’s principle and the Lagrange multiplier method. A linearized hydraulic control system based on rod length predictions was implemented independently to control the hydraulic cylinders. Consequently, the results of the simulations demonstrating the behavior of the robot machine are presented for each case study. In conclusion, this thesis studies the dynamic analysis of a special hybrid (serialparallel) robot for the above-mentioned special task involving the ITER and investigates different control algorithms that can significantly improve machining performance. These analyses and results provide valuable insight into the design and control of the parallel robot with flexible rods.

Biomedical Event Extraction with Machine Learning

Biomedical natural language processing (BioNLP) is a subfield of natural language processing, an area of computational linguistics concerned with developing programs that work with natural language: written texts and speech. Biomedical relation extraction concerns the detection of semantic relations such as protein-protein interactions (PPI) from scientific texts. The aim is to enhance information retrieval by detecting relations between concepts, not just individual concepts as with a keyword search. In recent years, events have been proposed as a more detailed alternative for simple pairwise PPI relations. Events provide a systematic, structural representation for annotating the content of natural language texts. Events are characterized by annotated trigger words, directed and typed arguments and the ability to nest other events. For example, the sentence “Protein A causes protein B to bind protein C” can be annotated with the nested event structure CAUSE(A, BIND(B, C)). Converted to such formal representations, the information of natural language texts can be used by computational applications. Biomedical event annotations were introduced by the BioInfer and GENIA corpora, and event extraction was popularized by the BioNLP'09 Shared Task on Event Extraction. In this thesis we present a method for automated event extraction, implemented as the Turku Event Extraction System (TEES). A unified graph format is defined for representing event annotations and the problem of extracting complex event structures is decomposed into a number of independent classification tasks. These classification tasks are solved using SVM and RLS classifiers, utilizing rich feature representations built from full dependency parsing. Building on earlier work on pairwise relation extraction and using a generalized graph representation, the resulting TEES system is capable of detecting binary relations as well as complex event structures. We show that this event extraction system has good performance, reaching the first place in the BioNLP'09 Shared Task on Event Extraction. Subsequently, TEES has achieved several first ranks in the BioNLP'11 and BioNLP'13 Shared Tasks, as well as shown competitive performance in the binary relation Drug-Drug Interaction Extraction 2011 and 2013 shared tasks. The Turku Event Extraction System is published as a freely available open-source project, documenting the research in detail as well as making the method available for practical applications. In particular, in this thesis we describe the application of the event extraction method to PubMed-scale text mining, showing how the developed approach not only shows good performance, but is generalizable and applicable to large-scale real-world text mining projects. Finally, we discuss related literature, summarize the contributions of the work and present some thoughts on future directions for biomedical event extraction. This thesis includes and builds on six original research publications. The first of these introduces the analysis of dependency parses that leads to development of TEES. The entries in the three BioNLP Shared Tasks, as well as in the DDIExtraction 2011 task are covered in four publications, and the sixth one demonstrates the application of the system to PubMed-scale text mining.