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Dynamic drawing analysis
Labounková, Ivana ; Čmiel, Vratislav (referee) ; Janoušek, Oto (advisor)
This thesis is focused on the dynamic drawing analysis. It deals with tracing drawing tests that can be applied for the analysis. It also deals with method for temporal segmentation of emerging drawings and also vectorization of resulted segments of drawings.
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Calibration and linearization of an RTD sensor
Hucl, Václav ; Šedivá, Soňa (referee) ; Beneš, Petr (advisor)
First part of this work is focused on the description exist method of analogue and digital calibration and linearization static parameters resistance sensors. Second part deal with concrete problem linearization thermistor NTC by multivibrator compound of two transistors same polarity and multivibrator, where active element is operational amplifier. Last part of bachelor work is devoted digital linearization based on curve fitting and linearization based on piecewise-linear interpolation, their using with thermistor NTC and comparison their attributes.
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Detection and Vizualization of Features in a Point Cloud
Kratochvíl, Jiří Jaroslav ; Mikeš, Josef (referee) ; Martišek, Dalibor (referee) ; Procházková, Jana (advisor)
The point cloud is an unorganized set of points with 3D coordinates (x, y, z) which represents a real object. These point clouds are acquired by the technology called 3D scanning. This scanning technique can be done by various methods, such as LIDAR (Light Detection And Ranging) or by utilizing recently developed 3D scanners. Point clouds can be therefore used in various applications, such as mechanical or reverse engineering, rapid prototyping, biology, nuclear physics or virtual reality. Therefore in this doctoral Ph.D. thesis, I focus on feature detection and visualization in a point cloud. These features represent parts of the object that can be described by the well--known mathematical model (lines, planes, helices etc.). The points on the sharp edges are especialy problematic for commonly used methods. Therefore, I focus on detection of these problematic points. This doctoral Ph.D. thesis presents a new algorithm for precise detection of these problematic points. Visualization of these points is done by a modified curve fitting algoritm with a new weight function that leads to better results. Each of the proposed methods were tested on real data sets and compared with contemporary published methods.
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Identification of tire model parameters
Olišar, Petr ; Zháňal, Lubor (referee) ; Porteš, Petr (advisor)
The main goal of this thesis is to obtain lateral parameters of the Magic Formula tire model of a tire commonly used in Formula Student competition. Both the author and the supervisor of the thesis know the tire name and its specification, but the research company that did the tire testing and provided me with the date prohibits sharing this of data publicly, so the tire designation is not mentioned in this thesis. The first chapter covers main theoretical facts related to a tire, briefly describes some of the tire models and shows possibilities how to determine tire characteristics that are used in a tire model. The thesis describes how to process raw tire data measured during a laboratory experiment using scripts created in Matlab software. The inputs variables are slip angle, lateral force, normal force and inclination angle. Raw data are splitted into parts, main coefficients of the Magic formula model (B, C, D, E, Sh, Sv) are calculated and subsequently the lateral parameters are obtained using least square method to fit parameters into the measured data. The works gives two main outcomes. The first output is a set of Matlab scripts that can be used to determine lateral parameters of any tire that has the same input data format as presented. A TIR file of the Formula Student tire in case of lateral slip is the second result of the work. This can be used for vehicle dynamics simulation of Formula Student racing car. The thesis also offers a comparison between parameters, which I calculated, and those gained thanks to Optimum Tire software by Calspan research company. Additionally the work shows the effect of load and inclination angle on lateral force.
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Identification of tire model parameters
Olišar, Petr ; Zháňal, Lubor (referee) ; Porteš, Petr (advisor)
The main goal of this thesis is to obtain lateral parameters of the Magic Formula tire model of a tire commonly used in Formula Student competition. Both the author and the supervisor of the thesis know the tire name and its specification, but the research company that did the tire testing and provided me with the date prohibits sharing this of data publicly, so the tire designation is not mentioned in this thesis. The first chapter covers main theoretical facts related to a tire, briefly describes some of the tire models and shows possibilities how to determine tire characteristics that are used in a tire model. The thesis describes how to process raw tire data measured during a laboratory experiment using scripts created in Matlab software. The inputs variables are slip angle, lateral force, normal force and inclination angle. Raw data are splitted into parts, main coefficients of the Magic formula model (B, C, D, E, Sh, Sv) are calculated and subsequently the lateral parameters are obtained using least square method to fit parameters into the measured data. The works gives two main outcomes. The first output is a set of Matlab scripts that can be used to determine lateral parameters of any tire that has the same input data format as presented. A TIR file of the Formula Student tire in case of lateral slip is the second result of the work. This can be used for vehicle dynamics simulation of Formula Student racing car. The thesis also offers a comparison between parameters, which I calculated, and those gained thanks to Optimum Tire software by Calspan research company. Additionally the work shows the effect of load and inclination angle on lateral force.
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Detection and Vizualization of Features in a Point Cloud
Kratochvíl, Jiří Jaroslav ; Mikeš, Josef (referee) ; Martišek, Dalibor (referee) ; Procházková, Jana (advisor)
The point cloud is an unorganized set of points with 3D coordinates (x, y, z) which represents a real object. These point clouds are acquired by the technology called 3D scanning. This scanning technique can be done by various methods, such as LIDAR (Light Detection And Ranging) or by utilizing recently developed 3D scanners. Point clouds can be therefore used in various applications, such as mechanical or reverse engineering, rapid prototyping, biology, nuclear physics or virtual reality. Therefore in this doctoral Ph.D. thesis, I focus on feature detection and visualization in a point cloud. These features represent parts of the object that can be described by the well--known mathematical model (lines, planes, helices etc.). The points on the sharp edges are especialy problematic for commonly used methods. Therefore, I focus on detection of these problematic points. This doctoral Ph.D. thesis presents a new algorithm for precise detection of these problematic points. Visualization of these points is done by a modified curve fitting algoritm with a new weight function that leads to better results. Each of the proposed methods were tested on real data sets and compared with contemporary published methods.
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Calibration and linearization of an RTD sensor
Hucl, Václav ; Šedivá, Soňa (referee) ; Beneš, Petr (advisor)
First part of this work is focused on the description exist method of analogue and digital calibration and linearization static parameters resistance sensors. Second part deal with concrete problem linearization thermistor NTC by multivibrator compound of two transistors same polarity and multivibrator, where active element is operational amplifier. Last part of bachelor work is devoted digital linearization based on curve fitting and linearization based on piecewise-linear interpolation, their using with thermistor NTC and comparison their attributes.
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