No description available.

Size measurement of iron ore pellets in industry is usually performed by manual sampling and sieving techniques. The manual sampling is performed infrequently and is inconsistent, invasive and time-consuming. Iron ore pellet's sizes are critical to the efficiency of the blast furnace process in the production of steel. Overly coarse pellets affect the blast furnace process negatively, however this affect can be minimized by operating the furnace with different parameters. An on-line system for measurement of pellet sizes would improve productivity through fast feedback and efficient control of the blast furnace. Also, fast feedback of pellet sizes would improve pellet quality in pellet production. Image analysis techniques promise a quick, inexpensive, consistent and non-contact solution to determining the size distribution of a pellet pile. Such techniques capture information of the surface of the pellet pile which is then used to infer the pile size distribution. However, there are a number of sources of error relevant to surface analysis techniques. The objective of this thesis is to address and overcome aspects of these sources of error relevant to surface analysis techniques. The research problem is stated as: How can the pellet pile size distribution be estimated with surface analysis techniques using image analysis? This problem is addressed by dividing the problem into sub-problems. The focus of the presented work is to develop techniques to overcome, or minimize, two of these sources of error; overlapped particle error and profile error. Overlapped particle error describes the fact that many pellets on the surface of a pile are only partially visible and a large bias results if they are sized as if they were smaller entirely visible pellets. No other researchers make this determination. Profile error describes the fact that only one side of an entirely visible pellet can be seen making it difficult to estimate pellets size. Statistical classification methods are used to overcome these sources of error. The thesis is divided into two parts. The first part contains an introduction to the research area together with a summary of the contributions, and the second part is a collection of four papers describing the research. / <p>Godkänd; 2007; 20071018 (ysko)</p>

Software Defined Radio (SDR), has become an increasingly popular alternative to traditional radio technology. In principle the incoming radio frequency signal is sampled as close to the antenna as possible to minimize noise, distortion and other hardware related effects which degrade the signal quality. Even though this sounds simple the trade-off is that the digital data rate is quite high and a significant amount of processing power is required to perform the same operation as a hardware radio. The biggest challenge for a software radio in a digital satellite navigation system is to replace the parallel hardware in the baseband processor, more commonly known as the correlator chip, with an equivalent software solution that preferably can work in real time. The front-end is usually the same regardless of the approach used in the baseband processor. The use of software radios in Global Navigation Satellite Systems (GNSS) is no exception and many applications can benefit from the unmatched flexibility of a software solution. GNSS receivers are being integrated into many traditional products such as cars and cell phones, where the latter now is beginning to contain sufficient processing power to enable true software radio capabilities. Modern production of cell phones is such that adding more hardware, no matter how inexpensive in itself, has a relatively large cost, therefore adding a software radio which requires a minimum of hardware, is likely to be the more cost-effective solution. However, the underlying hardware, in particular the data bridge for moving raw digital samples from the front-end to the processing element should not be forgotten. Depending on the spectral bandwidth and the dynamic range the data rate of the digital signal from the front-end can vary significantly. Typical transfer rates are on the order of 4-40 MB/s, which is about the same as the transfer rate over USB 2.0 when accessing a mass storage device. The focus of this thesis will be on the underlying technology which enables the use of software radio in the field of GNSS. / <p>Godkänd; 2007; 20070528 (ysko)</p>

There is an increasing utilization of modern Power Electronic (PE) devices in power systems, in for example, harmonic filters, reactive power compensation, and current limiting applications. The operational frequencies and switching rates of the PE devices now cover up to the megahertz range. As a consequence, an understanding of the functionality of static components like transformers, inductors (reactors), and capacitors in the presence of these high frequency signals are challenging issues. Present standards and legislation on EMC also put more constraints on the design of these power components. The focus of this work is the creation of high frequency electromagnetic models for power electronic components, with emphasis on air-core reactors. Attempts to model air-core reactors include lumped models, which typically consists of a series of mutually coupled lumped section, neglecting internal couplings within each section. This approach is limited to low frequencies where the voltage distribution along the turns in each section can be considered linear. For higher frequencies (several MHz), a more distributed model accounting for the electromagnetic couplings is inevitable. The Partial Element Equivalent Circuit (PEEC) modeling approach is suitable for mixed circuit and electromagnetic problems. It is based on the integral forms of Maxwell's equations upon which an equivalent circuit based model is developed. In this study, a broadband model for air-core reactors is created using the PEEC approach. Each reactor turn is represented by a finite number of interconnected bars or volume cells. From the volume cells equivalent circuit parameters, mainly the partial inductances, the coefficients of potential, and the resistances are evaluated using analytical routines. The electromagnetic coupling between the cells is represented by mutual partial inductances and the mutual coefficients of potential. The parameters are assembled into matrix equations, whose solution gives the current and voltage distribution in the model windings. The current distribution is post-processed to obtain the field distribution in the vicinity of the reactor. The PEEC reactor model was validated by comparing model results with measurements done on a laboratory air-core reactors and showed good agreement in both time and frequency domain. The time complexity for the PEEC simulation is greater compared to the corresponding lumped models, but the PEEC models give a better characterization at high frequencies. Using the frequency response from the PEEC model, smaller RLC resonance circuits replicating the same behaviour, can be synthesized. These reduced circuits can be easily included in system simulations as lumped components along side other power components. The PEEC model could also be helpful in design and diagnosis work for air-core reactors. Though the focus is on air-core reactors, the model could be enhanced to characterize other devices like power transformers. / <p>Godkänd; 2007; 20071107 (ysko)</p> / A New Method for Combined Electric and Electromagnetic Modeling of Power Distribution Systems -High frequency models for reactors

For the paper and pulp industry in Sweden and Finland to remain competitive against countries with lower overheads, they have to constantly strive to improve the quality and the efficiency of the manufacturing processes. One of the ways of doing this is to introduce sensors that will provide valuable online feedback on the characteristics of the pulp so that adjustments can be made to optimise the manufacturing process. The measurement method proposed in this thesis is based on ultrasound, since it is rapid, inexpensive, non-destructive and non-intrusive. Thus could be done online. Since ultrasound propagation and attenuation depends on the material properties through which is propagates, it has the potential to provide measurements of material properties such as pulp fibre density and elasticity. The aim of this thesis is to investigate the possibility of using ultrasound to measure pulp fibre material properties. The idea is to solve the inverse problem of estimating these properties from attenuation measurements and to establish the degree of accuracy to which this can be done. Firstly a model is developed and is tested with synthetic fibres to establish is validity. It is then used to solve the inverse problem of estimating material properties from attenuation measurements, again with synthetic fibres, to test the accuracy to which these properties can be estimated. Resonance peaks in the frequency response of the attenuation were found. On closer investigation it was established that the location of these peaks in the frequency domain is sensitive to the diameter of the fibres and their material properties. If the diameter is known, these peaks improve the accuracy of the estimation process. The results of the estimation process for synthetic fibre suspensions show values for the shear modulus are within known ranges but the estimation of Poisson's ratio and Young's modulus is poor. Improving the model or the estimation procedure may lead to better results. For the method as it is to have application in the paper and pulp industry there are certain conditions that need to be fulfilled. These are that we find peaks in the frequency response of the attenuation in pulp, know the diameter distribution of the fibres and the hollow nature of the fibres does not significantly alter the results. We can then, potentially, be able to establish the shear modulus of the pulp fibres. If the shear modulus is a factor in paper quality, we may be close to an online measurement of paper pulp quality using ultrasonic spectroscopy. Improving the model may allow us to estimate further properties and take into account the fibres being hollow. The thesis consists of two parts. The first part includes an overview of the pulp and paper industry and current testing methods, background theory on which the model is based and an overview of the model that is used in predicting ultrasound attenuation. There then follows a summary of the work done, some addition points are raised in the discussion before drawing conclusions. Finally we discuss what needs to be done to take this further. The second part contains a collection of four papers describing the research. / <p>Godkänd; 2006; 20061115 (ysko)</p>

In the manufacturing process of paper the mass fraction and material properties of the fibres in the pulp suspension are important for the strength and quality of the finished product. The properties of the fibres in the pulp suspension that enters the paper machine is not well understood and therefore an adequate prediction of the strength and quality of the finished paper is not possible. Also with the demand for a more environmentally friendly process the amount of recycled paper that enters the process has increased. The properties of the recycled fibre are unknown and also vary. Thus, the pulp suspension contains fibres of different sizes, mechanical properties and from fibres with different origin. The pulp and paper industry is a highly energy consuming industry. Therefore to be competitive on the world market the energy consumption needs to be reduced. Altogether, there is an increasing demand for methods of on-line characterisation of the pulp suspension as well as the fibres in the pulp suspension. If the knowledge of the pulp suspension is increased it will give potential to make an adequate prediction of the strength and quality of the finished paper. Also with the increased knowledge of the pulp suspension improvement of the process control will be feasible. Hence, a reduction of energy consumption is possible. The aim of this thesis is to describe and investigate a sensing strategy that consist of a combination of three existing measurement techniques, ultrasound, optical and photoacoustical. The combination of these techniques is believed to extract more information from the paper pulp suspension than a single technique by itself. The long-term goal is to find a measurement technique for the pulp and paper industry that are on-line, fast and increases the knowledge of the properties of the paper pulp suspension. And at the end the finished paper strength and quality. If the fibre properties are determined on-line it is believed that an improved process control is achievable. Three studies has been conducted, the first using only ultrasound technique, the second using a combination of ultrasound and optical technique and in the last study a combination of ultrasound and photoacoustical technique. Two studies were conducted on pulp suspensions. The mass fraction range corresponds to the ranges used in the paper forming process. In the third study properties of Nylon 66 suspended in water was investigated. The result shows that the sensing strategy of using a combination of existing measurement techniques gives additional information about the examined media. This shows that the sensing strategy have a potential in better process control within the pulp and paper industry. It is noted that the investigated measurement techniques do not require any special set-up. Thus, they can all be used together in the same measurement cell and in an on-line set-up. It is also observed that all investigated measurement techniques are fast compared to sampling and evaluation. However, the overall knowledge of the fibre in a pulp suspension has not increased to the extent that it can measure all needed requirements (physical, chemical and mechanical). Hence an optimisation of the process control in the preparation of a pulp suspension is not achievable in this state. The thesis also describes a parametric estimator for estimation of observable properties in an ultrasonic measurement system. It is shown that the proposed estimator enables accurate estimation of the observable properties with considerably lower variance compared to standard Fourier analysis methods. / <p>Godkänd; 2007; 20070320 (ysko)</p>

No description available.

In this thesis measurement systems for the purpose of characterization of radio frequency power amplifiers are studied. Methods to increase the speed, accuracy, bandwidth, as well as to reduce the sampling requirements and testing cost are presented. A method intended for signal shaping with respect to peak to-average ratio reduction and its effects-improvements on the radio frequency front-end performance is investigated. A time domain measurement system intended for fast and accurate measurements and characterization of radio frequency power amplifiers is discussed. An automated, fast and accurate technique for power and frequency sweep measurements is presented. Multidimensional representation of measured figure of merits is evaluated for its importance on the production-testing phase of power amplifiers. A technique to extend the digital bandwidth of a measurement system is discussed. It is based on the Zhu-Frank generalized sampling theorem which decreases the requirements on the sampling rate of the measurement system. Its application for power amplifiers behavioral modeling is discussed and evaluated experimentally. A general method for designing multitone for the purpose of out-of-band characterization of nonlinear radio frequency modules using harmonic sampling is presented. It has an application with the validation of power amplifiers behavioral models in their out-of-band frequency spectral support when extracted from undersampled data. A method for unfolding the frequency spectrum of undersampled wideband signals is presented. It is of high relevance to state-of-the-art radio frequency measurement systems which capture repetitive waveform based on a sampling rate that violates the Nyquist constraint. The method is presented in a compact form, it eliminates ambiguities caused by folded frequency spectra standing outside the Nyquist band, and is relevant for calibration matters. A convex optimization reduction-based method of peaks-to-average ratio of orthogonal frequency division multiplexing signals is presented and experimentally validated for a wireless local area network system. Improvements on the radio frequency power amplifier level are investigated with respect to power added efficiency, output power, in-band and out-of-band errors. The influence of the power distribution in the excitation signal on power amplifier performance was evaluated.

No description available.

A voltage dip is a short duration reduction in voltage magnitude due to a short duration increase in current magnitude. Causes of dips are, among others, electrical faults, large motor starting, transformer energizing and failure of power-electronic converters. Voltage dips are considered as a very important power quality issue because they lead to trip or malfunction of sensitive loads especially in industrial process installations and subsequently they lead to high costs. In this thesis the overall aim is extracting additional information from large voltage dip monitoring databases. An important step to this end is providing efficient characterization methods for voltage dips. Voltage dip characterization aids by describing voltage dip events (a set of voltage waveforms with high time resolution) as a limited number of values such that this set gives as much as possible information about the dip. This thesis contributes to the voltage dip characterization development through three different methods. The first method consists of a systematic way for comparison different sets of voltage dip characteristic. With this method, both real-measured and synthetic voltage dips are applied to generic models of sensitive loads. The best set of characteristics, for representing the voltage dip, is the one best enables the reproduction of the behaviour of equipment when exposed to real-measured voltage dips. The second method compares 12 different sets of characteristics for describing three-phase single-events.. The method determines the most efficient and feasible way that gives more realistic characteristics as well as comparable with existing standard methods. The proposed set of characteristics has been proposed for inclusion in international standard documents. The third method enables the extraction of dip characteristics based on machine learning approaches. It is applicable for characterization of multi-stage voltage dips in particular and for single-stage (normal) voltage dips as well. The proposed method uses the space-phasor model of three-phase voltages as an input data for k-means clustering algorithm. Then the calculated data are modeled as a general form of an ellipse by exploiting logistic regression algorithm. Finally the optimized obtained ellipse parameters are applied to calculate single-segment characteristics for each individual stage of a multi-stage voltage dip. Further, all proposed methods are implemented in an Matlab environment and validated by applying them to a large number of real-measured voltage dips in actual HV and MV power networks and some suitable synthetic voltage dips.