Iskanje po katalogu digitalne knjižnice

Opis: This paper presents a methodological framework for building a digital shadow of an induction motor based on standardised tests and a two‑axis (dq) simulation model. The tests were carried out according to IEEE Std 112 and IEC 60034‑2‑1. The parameters of the equivalent circuit were identified and entered into the model. Validation was performed by comparing the torque–speed and current–speed curves at 180 V and 220 V, while the nominal behaviour at 400 V was estimated using the model and voltage scaling. The model was then calibrated to reduce the discrepancy between the simulation and measurements, and the error was quantified using the root‑mean‑square error (RMSE) and mean absolute percentage error (MAPE). An automated load‑simulation setup that reproduces the torque test is also presented, enabling rapid evaluation of parameter influence. The results show a very good match in the current channel, with larger deviations in the prediction of characteristic torque points, indicating the limitations of linearised parameters and motivating nonlinear model extensions. The approach enables summarised reliable estimates at nominal voltage when direct measurements are not feasible.
Ključne besede: induction motor, digital shadow, standardised tests, dq model, torque test, automated load simulation, model calibration
Objavljeno v DKUM: 01.10.2025; Ogledov: 0; Prenosov: 3
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Opis: Measurements are of paramount importance in industry and other areas of importance to society. They are used to determine the characteristics of processes and products, to control and regulate processes, to decide on the acceptable quality of products, etc. To ensure the quality of measurements, we have to calibrate measuring devices regularly. In our laboratory – the holder of the national length standard, we mainly calibrate high-precision standards from accredited laboratories. As the demands on the accuracy of measurements are constantly increasing, we are also forced to continuously improve the accuracy of our calibration procedures. This article presents the development of methods for calibrating the diameter of ring gauges, which represent an important standard for calibrating measuring instruments for measuring internal dimensions. The main objective of this development is to reduce the measurement uncertainty based on a scientific investigation of all influencing parameters. The presented study focuses in particular on the control and reduction of the influence of geometric anomalies of the calibrated rings on the measurement uncertainty during calibration.
Ključne besede: measurement traceability, calibration, measurement uncertainty, error simulation
Objavljeno v DKUM: 11.03.2025; Ogledov: 0; Prenosov: 9
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Opis: This work deals with numerical simulation of the anaerobic digestion process. Special attention is focused on the inhibitions modeling. For this purpose, an existing complex BioModel is upgraded by adequate modeling of non-competitive, competitive, and uncompetitive inhibition types. The obtained results of sensitivity analysis shows that various inhibition constants are ranged within the most important model parameters. For each inhibition type, the upgraded model is calibrated and validated with respect to the measured anaerobic digestion performance in CSTR bioreactors of a full scale biogas plant in period of two years. The obtained statistical indicators differ up to 5% in model calibration and validation. The best values of relative index of agreement for CH4 and H2S flow rates were obtained when using competitive inhibition; their values were 0.9385 and 0.7903, respectively. For H2 flow rate and pH value, the best indices of 0.7945 and 0.6593 were obtained with uncompetitive inhibition. For biogas flow rate, the best index of 0.9518 was obtained when using non-competitive inhibition. Since no inhibition type delivers best results in all situations, further research is needed to model mixed inhibition type for various inhibitors.
Ključne besede: BioModel, inhibition modeling, model parameters calibration, active set optimization procedure, gadient-based optimization
Objavljeno v DKUM: 23.08.2024; Ogledov: 77; Prenosov: 20
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Ključne besede: urban traffic, microsimulation, calibration, neural networks, rundabouts, validation
Objavljeno v DKUM: 15.04.2024; Ogledov: 239; Prenosov: 19
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Opis: Walking, as a mode of transport, is becoming widespread, in a world, where urban conglomerates are broadening and becoming denser. Modern lifestyle trends on a side, and eco-friendly policies on the other, push people into walking habits, increasing the need for a suitable, attractive, accessible, connected and safe walking infrastructure. To reach such a result, it is necessary to understand, what are the needs of the users of this infrastructure, taking into consideration the behavioral specificities and the safety needs of pedestrians. In this process pedestrian microsimulation models, surrogate safety techniques, and technologies able to measure specific traits of pedestrian dynamics play a central role. The firsts allow to reproduce repeatedly in a virtual environment a specific infrastructure and to study the response of pedestrians. Nevertheless, to be accurate and efficient, they need to go through long and tedious calibration and validation processes, that are often seen as an important limitation by technicians. Surrogate safety techniques are methods, that are based on the concept, that it is possible to predict the safety level of a location, using near accidents. The main advantage of such techniques is that they are proactive. Till this moment, these techniques have been mainly applied to on-field measurements and are primarily centered on motorized road users. Less interest has been shown for vulnerable road users, especially for pedestrians, who have been less extensively studied. Finally, an element that could highly affect pedestrian safety is their reaction time. Nevertheless, its measurement has long been a big issue. Eye-tracking technology could be one of the solutions, allowing to analyze the directions and objects fixated by pedestrians. These listed issues are also the topics that are addressed by this research work. Focusing on the study of the action of pedestrians while crossing the road on an unsignalized crosswalk set on a roundabout entry leg, the dissertation thesis aims at studying the crossing time, reaction time and surrogate safety aspects typical of pedestrians at the recalled location. The main purpose of the research work is to develop a methodology to calibrate pedestrian Social Force Model at a selected location, using a specifically formulated neural network as a tool to fine-tune model's behavioral parameters. Eight parameters have been chosen to be fine-tuned, five of those are related to pedestrian behavior and three of them are related to car-following behavior. After the selection of input parameters, a feedforward network has been formulated. Its application in the framework of the whole calibration process has brought to considerably positive results, finding a combination of input parameters that improved the performance of the microsimulation model of 37 % in comparison to the default one. The outputs of the calibrated model have been used to calculate three measures of surrogate safety, and also in this case results demonstrated an improvement in the calculation of surrogate safety measures when using the calibrated outcomes in comparison to their calculation on the “default” model outputs. Finally, reaction time measurement and prediction have been addressed by the thesis, in order to be able to describe pedestrian crossing action in its completeness. Quantitative eye-tracking outputs have been the starting point for the calculation of pedestrian reaction time at different locations, and they allowed to create a database of behavioral, geometric, regulatory and flow characteristics, which was the foundation for the formulation of a new prediction model for pedestrian reaction time. The prediction model, which consists of a cascade-correlation neural network, gave a good response to the learning and generalization steps, turning a 74 % correlation between the measured reaction time values and the predicted ones, and being able to follow the variability of these values.
Ključne besede: pedestrian, microsimulation model, calibration, neural network, surrogate safety indicators, reaction time.
Objavljeno v DKUM: 03.10.2022; Ogledov: 873; Prenosov: 123
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