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EN
Accurate information on Induction Motor (IM) speed is essential for robust operation of vector controlled IM drives. Simultaneous estimation of speed provides redundancy in motor drives and enables their operation in case of a speed sensor failure. Furthermore, speed estimation can replace its direct measurement for low-cost IM drives or drives operated in difficult environmental conditions. During torque transients when slip frequency is not controlled within the set range of values, the rotor electromagnetic time constant varies due to the rotor deep-bar effect. The model-based schemes for IM speed estimation are inherently more or less sensitive to variability of IM electromagnetic parameters. This paper presents the study on robustness improvement of the Model Reference Adaptive System (MRAS) based speed estimator to variability of IM electromagnetic parameters resulting from the rotor deep-bar effect. The proposed modification of the MRAS-based speed estimator builds on the use of the rotor flux voltage-current model as the adjustable model. The verification of the analyzed configurations of the MRAS-based speed estimator was performed in the slip frequency range corresponding to the IM load adjustment range up to 1.30 of the stator rated current. This was done for a rigorous and reliable assessment of estimators’ robustness to rotor electromagnetic parameter variability resulting from the rotor deep-bar effect. The theoretical reasoning is supported by the results of experimental tests which confirm the improved operation accuracy and reliability of the proposed speed estimator configuration under the considered working conditions in comparison to the classical MRAS-based speed estimator.
PL
W pracy przedstawiono identyfikację charakterystyk energetycznych kotłów dla potrzeb diagnostyki i optymalizacji eksploatacji. Dla skorygowania nieuniknionych błędów pomiaru i uzyskania wymaganej dokładności predykcji zastosowano rachunek wyrównawczy. Estymację parametrów i dobór optymalnej struktury dokonano metodą regresji krokowej. W procedurze estymacyjnej wykorzystano pomiary eksploatacyjne i specjalne oraz wyniki obliczeń symulacyjnych z wykorzystaniem modeli matematycznych. Przedstawiono wyniki identyfikacji charakterystyk energetycznych kotła pyłowego elektrowni kondensacyjnej, kotła rusztowego ciepłowni i kotła wielopaliwowego w hutnictwie miedzi. Omówiono przydatność opracowanych modeli w systemach diagnostyki eksploatacji i w optymalizacji bieżącej w systemach sterowania.
EN
The paper presents mathematical modelling of steam boilers by the usage of regression modelling techniques for the purpose of thermal diagnostic systems and exploitation optimization. In order to correct unavoidable measurement errors and to achieve the satisfying prediction quality of developed models Advanced Data Validation and Reconciliation method has been used. The estimation procedure of model parameters and determination of optimal structure of developed model have been carried out with stepwise regression technique. Within estimation procedure, operational measurements as well as simulation calculation results (with usage of mathematical models) have been used. The results related to identification of coal dust fired boiler, stoker-fired boiler as well as multi fuel industrial boiler energy characteristics have been presented. The usage of developed models have been described from the thermal diagnostic systems as well as exploitation optimization point of view.
EN
The Ornstein-Uhlenbeck model is one of the most popular stochastic processes. It has found many interesting applications including physical phenomena. However, for many real data, the classical Ornstein-Uhlenbeck process cannot be applied. It is related to the fact that for many phenomena the vectors of observations exhibit the so-called heavy-tailed behaviour. In such cases, the modifications of the classical models need to be used. In this paper, we analyze the Ornstein-Uhlenbeck process based on stable distribution. This distribution is one of the most classical members of the heavy-tailed class of distributions. In the literature, one can find various applications of stable processes. However, the heavy-tailed property implies that the classical methods of estimation and statistical investigation cannot be applied. In this paper, we propose a new method of estimation of the stable Ornstein-Uhlenbeck process. This technique is based on the alternative measure of dependence, called fractional lower order covariance, which replaces the classical covariance for infinite-variance distribution. The proposed research is a continuation of the authors' previous studies, where the measure called covariation was proposed as the base for the estimation technique. We introduce the stable Ornstein-Uhlenbeck process and remind its main properties. In the main part, we define the new estymator of the parameters for discrete representation of the Ornstein-Uhlenbeck process. Its effectiveness is checked by Monte Carlo simulations.
PL
Proces Ornsteina-Uhlenbecka jest jednym z najbardziej popularnych procesów stochastycznych. Znalazł on wiele ciekawych praktycznych zastosowań. Należy jednak zwrócić uwagę, że klasyczny proces Ornsteina-Uhlenbecka nie może być zastosowany dla wielu danych rzeczywistych, ponieważ często pochodzą one z rozkładów ciężko- ogonwych, dla których nie istnieje drugi moment. W takich przypadkach niezbędna jest modyfikacja klasycznego modelu z wykorzystaniem rozkładu stabilnego. Z powodu zastosowania rozkładu stabilnego niezbędne jest użycie innej metody estymacji niż bazującej na autokowariancji. Zaproponowana została nowa metoda bazująca na ułamkowych momentach. Praca jest kontynuacją wcześniej otrzymanych rezultatów dla innej alternatywnej miary zależności, kowariacji. W pracy przypomniana została definicja stabilnego procesu Ornsteina-Uhlenbecka wraz z propozycją nowych estymatorów dla parametrów tego procesu.W celu sprawdzenia ich właściwości wykonane zostały symulacje Monte Carlo.
EN
The main aim of the research is to use the artificial neural network (ANN) model with the artificial bee colony (ABC) and teaching–learning-based optimization (TLBO) algorithms for estimating suspended sediment loading. The stream flow per month and SSL data obtained from two stations, İnanlı and Altınsu, in Çoruh River Basin of Turkey were taken as precedent. While stream flow and previous SSL were used as input parameters, only SSL data were used as output parameters for all models. The successes of the ANN-ABC and ANN-TLBO models that were developed in the research were contrasted with performance of conventional ANN model trained by BP (back-propagation). In addition to these algorithms, linear regression method was applied and compared with others. Root-mean-square and mean absolute error were used as success assessing criteria for model accuracy. When the overall situation is evaluated according to errors of the testing datasets, it was found that ANN-ABC and ANN-TLBO algorithms are more outstanding than conventional ANN model trained by BP.
PL
Efektywność sieci MANET uzależniona jest od funkcjonowania w niej mechanizmu routingu rozpoznającego topologię sieci, a następnie zestawiającego trasy do węzłów, często w warunkach dużej dynamiki zmian topologii. Prowadzi to do częstych przerw łączności, a w efekcie do opóźnień i strat danych. W artykule przedstawiona została koncepcja routingu z estymacją powiązań pomiędzy węzłami sieci. Rozwiązanie to pozwoli na wcześniejszą reakcję routingu na zmiany topologii oraz podjęcie działań utrzymania ciągłości tras. W artykule przedstawiono również wyniki testów symulacyjnych.
EN
The MANET network efficiency largely depends on the routing mechanism. This mechanism recognizes network topology, and than sets the routes to nodes, often under high topology changes. It leads to communication interruptions and consequently to delays and data loss. The article presents the concept of routing with nodes connection prediction. This solution allows for early response to topology changes and to take action to maintain routes continuity. In article also are presented the results of the connections time measurements’ simulation tests.
PL
Jednym z podstawowych składników ścieków komunalnych są zanieczyszczenia organiczne, których zawartość jest określana najczęściej na postawie ich biochemicznego zapotrzebowania na tlen (BZT5). W artykule opracowano prosty model regresyjny do szacowania wartości BZT5 ścieków komunalnych w celu zapewnienia bieżącej kontroli sprawności procesu biologicznego oczyszczania oraz możliwości optymalizacji warunków eksploatacji reaktorów biologicznych. Model opracowano na podstawie danych pochodzących z wieloletniego (1990–2000) monitoringu jakości ścieków w oczyszczalni Terrence J. O’Brien Water Reclamation Plant w Chicago (USA). Analizie statystycznej poddano wartości następujących wskaźników jakości ścieków dopływających do oczyszczalni: pH, BZT5, zawiesiny ogólne, azot amonowy, azot Kjeldahla oraz azotany. Wszystkie obliczenia wykonano w programie statystycznym R z nakładką R Studio w wersji 1.0.143. Do wyboru parametrów istotnych do budowy modelu zastosowano kryterium informacyjne Akaikego (AIC) oraz algorytm Leaps. Na podstawie wyników testowania sformułowano model regresyjny do szacowania wartości BZT5 ścieków komunalnych wykorzystujący zawartości zawiesin ogólnych oraz azotu Kjeldahla i azotanów w ściekach. Algorytm formułowania modelu regresyjnego, przydatnego do szybkiego uzyskiwania przybliżonych wartości BZT5 ścieków, może posłużyć do budowy podobnych modeli na potrzeby innych oczyszczalni ścieków, bez konieczności częstego wykonywania oznaczeń laboratoryjnych i długiego oczekiwania na ich wyniki.
EN
One of the primary components of municipal sewage is organic pollution, the content of which is determined most often on the basis of its biochemical oxygen demand (BOD5). In the paper, a simple regression model was developed to estimate BOD5 values of municipal sewage in order to ensure ongoing effi ciency control of the biological treatment process and possibilities for optimizing the operating conditions of biological reactors. The model was developed from the long-term monitoring data (1990–2000) on wastewater quality in the Terrence J. O’Brien Water Reclamation Plant in Chicago (USA). Statistical analysis covered the following quality indicators for the sewage material fl owing into the treatment plant: pH, BOD5, total suspended solids, ammonium nitrogen, Kjeldahl nitrogen and nitrates. All calculations were made using a statistical program R with R Studio patch, version 1.0.143. Akaiki Information Criterion (AIC) and the Leaps algorithm were employed to select parameters relevant to constructing the model. Based on the results of model testing, the regression model for BOD5 values estimation in municipal wastewaters was formulated. The model employed parameters such as total suspended solids, Kjeldahl nitrogen and nitrates wastewater content. The algorithm of formulating the regression model that allows for quick generation of approximate BOD5 values in wastewater can be applied to development of similar models for other treatment plants, with no need for frequent laboratory testing and long wait for the results.
PL
Biologiczna oczyszczalnia ścieków jest złożonym nieliniowym systemem przemysłowym. Jednym z istotnych i kosztownych procesów tam zachodzących jest napowietrzanie ścieków. Z procesem tym związana jest respiracja, czyli szybkość zużywania tlenu przez bakterie oczyszczające ścieki. Jest to jeden z najważniejszych parametrów, decydujący o efektywności oczyszczania ścieków. Niestety koszt zakupu urządzeń do pomiaru respiracji - respirometrów jest bardzo wysoki i w oczyszczalniach ścieków nie są one instalowane. W artykule dokonano estymacji respiracji, w oparciu o pomiar stężenia tlenu w biologicznej oczyszczalni typu wsadowego. W tym celu wykorzystano rozszerzony filtr Kalmana. W badaniach symulacyjnych przedstawiono wyniki estymacji respiracji dla biologicznej oczyszczalni ścieków typu SBR.
EN
Biological wastewater treatment plant is a complex, nonlinear, industrial system. One of the significant and costly process taking place there is aeration of wastewater. This process involves the respiration - the rate of oxygen consumption by the bacteria. It is one of the most important parameter deciding on the efficiency of wastewater treatment. Unfortunately, the cost of buying respiratory equipment - respirometers is very high and in wastewater treatment plants they are not installed. The paper presents estimation of respiration based on the measurement of dissolved oxygen. For this purpose, the extended Kalman filter is used. Simulation results for the biological wastewater treatment plant type SBR are presented.
EN
The article presents a method of a crossroad traffic load estimation based on the registered noise level. Data on the current noise level and the equivalent traffic intensity for the selected crossroad was recorded as part of the test installation of the road traffic impact assessment system for the acoustic climate. The measurement was carried out continuously over a fewmonth period. Based on the collected data, the analysis of variability of registered noise levels was carried out in relations to changes of equivalent traffic load and selected environmental parameters: temperature and relative air humidity. The use of artificial neural network has been proposed for estimating traffic load. On the basis of the equivalent noise level for the fifteen-minute interval and the values of environmental parameters averaged over the same period of time, the equivalent traffic load within the crossroad shall be determined.
9
Content available Optimal Control of Wind Power Generation
EN
Power system control is a complex task, which is strongly related to the number and kind of generating units as well as to the applied technologies, such as conventional coal fired power plants or wind and photovoltaic farms. Fast development of wind generation that is considered as unstable generation sets new strong requirements concerning remote control and data hubs cooperating with SCADA systems. Considering specific nature of the wind power generation, the authors analyze the problem of optimal control for wind power generation in farms located over a selected remote-controlled part of the Operator grid under advantageous wind conditions. This article presents an original stepwise method for tracing power flows that makes possible to eliminate current (power) overloading of power grid branches. Its core idea is to consider the discussed problem as an optimization task.
EN
In this paper, implementation of soft sensing technique for measurement of fluid flow rate is reported. The objective of the paper is to design an estimator to physically measure the flow in pipe by analysing the vibration on the walls of the pipe. Commonly used head type flow meter causes obstruction to the flow and measurement would depend on the placement of these sensors. In the proposed technique vibration sensor is bonded on the pipe of liquid flow. It is observed that vibration in the pipe varies with the control action of stem. Single axis accelerometer is used to acquire vibration signal from pipe, signal is passed from the sensor to the system for processing. Basic techniques like filtering, amplification, and Fourier transform are used to process the signal. The obtained transform is trained using neural network algorithm to estimate the fluid flow rate. Artificial neural network is designed using back propagation with artificial bee colony algorithm. Designed estimator after being incorporated in practical setup is subjected to test and the result obtained shows successful estimation of flow rate with the root mean square percentage error of 0.667.
11
EN
The estimation of position coordinates of a navigating ship is one of the navigational subprocesses. The methods used in this process are either deterministic (the case of a minimum number of navigational parameters measurements) or probabilistic (in cases where we have access to information redundancy). Naturally, due to the accuracy and reliability of the calculated coordinates, probabilistic methods should be primarily used. The article presents the use of the method of least squares and Kalman filtering in algorithms in integrated navigation for the estimation of position coordinates, taking into account ship movement parameters.
12
PL
W artykule przedstawiono metodę szybkiej estymacji początkowego położenia wału wirnika silnika z magnesami trwałymi IPMSM. Wykorzystano do tego celu efekt anizotropii magnetycznej obwodu wirnika, wynikającej z zainstalowania magnesów trwałych. Wymagany do prawidłowej pracy ciągły pomiar położenia i prędkości obrotowej wału silnika wykonywany jest za pomocą enkodera przyrostowego (ang. incremental encoder). Wyznaczone położenie początkowe wirnika jest uwzględniane w trakcie pierwszego obrotu wału silnika jako ustalone przesunięcie początkowe. Pozwala to na uzyskanie pełnego momentu elektromagnetycznego silnika już po jednym obrocie wału, w którego trakcie występuje pierwszy impuls indeksu z enkodera. Umożliwia to pewny start układu napędowego bez początkowego przypadkowego ruchu wstecznego silnika.
EN
The article presents the method and results of experimental research on an algorithm of the instant estimation of an initial position of the rotor of the permanent magnet motor. It is part of the design of highly dynamic controlled AC drive. Estimation and drive control algorithm has been implemented in the driver of the new generation signal microcontroller TMS320F28335 of Texas Instrument. It was written in C. The algorithm has proved itself in a model system of the drive. The estimation of the initial position of the shaft of the permanent magnet motor helped to reduce the cost and complexity of the drive system. Thanks to it, a cheaper and more convenient to use incremental encoder could be used. Without the estimation, however, it did not ensure the initial position of the rotor, required to proper start and work of the motor.
EN
This paper presents two approaches to determining estimates of an equivalence relation on the basis of pairwise comparisons with random errors. Obtaining such an estimate requires the solution of a discrete programming problem which minimizes the sum of the differences between the form of the relation and the comparisons. The problem is NP hard and can be solved with the use of exact algorithms for sets of moderate size, i.e. about 50 elements. In the case of larger sets, i.e. at least 200 comparisons for each element, it is necessary to apply heuristic algorithms. The paper presents results (a statistical preprocessing), which enable us to determine the optimal or a near-optimal solution with acceptable computational cost. They include: the development of a statistical procedure producing comparisons with low probabilities of errors and a heuristic algorithm based on such comparisons. The proposed approach guarantees the applicability of such estimators for any size of set.
EN
This article reports the results of experimental and numerical analysis of emissions of nitrogen oxides in exhaust gas to the environment from a turbocharged diesel engine of a tractor. The problem of identifying nitrogen oxides emissions from the exhaust gases was formulated and subsequently solved, based on data gained from measurements. The results of estimation of nitrogen oxides emissions were verified on the basis of research on a test object. The object of the study and a non-linear static model of nitrogen oxides emission were also described for two systems – with and without exhaust gas recirculation. The article demonstrates that the use of an adequately selected mathematical model can lead to the estimation of emissions of nitrogen oxides contained in the exhaust gas of diesel engines in an off-road vehicle. The created model can be used to control the valve of the exhaust gas of recirculation system and so reduce the emission of harmful substances to the environment. The presented research results show the comparison of estimated and measured nitrogen oxides concentration. The estimated value from the mathematical model concentration is about from 0.7 s to 1 s earlier than the value measured by the sensor, therefore the exhaust gas recirculation system could be controlled accordingly before nitrogen oxides are formed.
EN
MP estimation is a method which concerns estimating of the location parameters when the probabilistic models of observations differ from the normal distributions in the kurtosis or asymmetry. The system of Pearson’s distributions is the probabilistic basis for the method. So far, such a method was applied and analyzed mostly for leptokurtic or mesokurtic distributions (Pearson’s distributions of types IV or VII), which predominate practical cases. The analyses of geodetic or astronomical observations show that we may also deal with sets which have moderate asymmetry or small negative excess kurtosis. Asymmetry might result from the influence of many small systematic errors, which were not eliminated during preprocessing of data. The excess kurtosis can be related with bigger or smaller (in relations to the Hagen hypothesis) frequency of occurrence of the elementary errors which are close to zero. Considering that fact, this paper focuses on the estimation with application of the Pearson platykurtic distributions of types I or II. The paper presents the solution of the corresponding optimization problem and its basic properties. Although platykurtic distributions are rare in practice, it was an interesting issue to find out what results can be provided by MP estimation in the case of such observation distributions. The numerical tests which are presented in the paper are rather limited; however, they allow us to draw some general conclusions.
EN
One of the areas using the supply function of surface water ecosystems is agriculture. In the case of a lack of a sufficient amount of water for plants, it is necessary to supplement this amount through irrigation of agricultural land i.e. using the ecosystem service – water collection. The aim of this article is to determine the surface water ecosystem services connected to water collection for irrigation of agricultural land in the area of Podlaskie voivodship and to present a method for estimating the requirements for such services as a tool for water management within municipalities.
PL
W artykule przedstawiono przegląd istniejących metodyk szacowania miejsc postojowych w części parkingowej na obiektach MOP w różnych krajach (Polska, Wielka Brytania, USA, Niemcy). W jego wyniku zostały określone cechy jakie powinny być uwzględnione w analizach, co pozwoliło na opracowanie nowej metodyki, która może się sprawdzić w warunkach polskich. Najistotniejszą zmianą w stosunku do obowiązującej metodyki jest uwzględnienie zmienności sezonowej ruchu, kierunków ruchu oraz długości odcinka drogi dla której będzie wyznaczana ilość miejsc postojowych (w przyszłości można uwzględnić także atrakcyjność MOP). Metodyka ta ze względu na swoją prostotę i uniwersalność (bazuje na stabelaryzowanych wielkościach; umożliwia wyznaczenie potrzebnej liczby miejsc w odniesieniu do pojazdów lekkich i ciężkich) jest bardzo użyteczna. Prawidłowo zaprojektowane i rozmieszczone MOP-y wpłyną na poprawę bezpieczeństwa ruchu drogowego. Po przeprowadzeniu własnych pomiarów i badań ruchu na krajowych MOP-ach należy zweryfikować uzyskane wyniki.
EN
The article presents an overview of existing parking estimation methodologies in the parking area at SAs in various countries (Poland, United Kingdom, USA, Germany). As a result, the characteristics that should be included in the analyzes were determined, which allowed for the development of a new methodology that could be suitable in Polish conditions. The most important change to the current methodology is taking into account the seasonal variation in traffic, traffic directions and the length of the road section for which the number of parking spaces will be determined. This methodology is very useful due to its simplicity and universality (it is based on tabularized values, and allows for determining the required number of spaces for light and heavy vehicles). Properly designed and arranged SAs will improve road safety. After conducting own measurements and traffic studies at national SAs, the obtained results should be verified.
EN
In this paper, we introduce additional statistical tools for estimating the maximum regional earthquake magnitude, mmax, as complement to those already introduced by Kijko and Singh (Acta Geophys. 59(4):674– 700, 2011). Four new methods are introduced and investigated, with regard to their applicability and performance. We present an example of application and a comparison that includes the methods introduced earlier by the previous authors. A condition for the existence of the Tate– Pisarenko estimate and a proof of the asymptotic equivalence of the Tate–Pisarenko and Kijko–Sellevoll estimates are presented in the two appendices
EN
The article presents the general trends of application of artificial neural networks. It presents some examples of applications of artificial neural networks in the textile industry, including forecasts of selected mechanical properties of filament yarns spun from the melt, the classification of damage of card web, the control of regularity of linear mass of draw sliver, assessment the quality of yarn packages textured by false twist and predict the physical properties of unknot-ted spliced ends of wool worsted yarns.
EN
This article attempts to systematize some scientific problems of classification, recognition, prediction, estimation, optimization, control, approximation of research object via artificial neural networks. There were presented different methods of classifying artificial neural networks (due to the flow of information, types of tasks, way of learning networks, as well as the transition function and topology). Due to the types of tasks artificial neural networks are divided into networks intended to solve regression problems, classification tasks, clustering analysis and time series analysis. The article mentions the industrial fields of applications of artificial neural networks, with particular consideration on areas of the textile industry.
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