Jun 24, 2019   1:39 p.m. Ján
Academic information system

Summary of topics offered - Institute of Electrical Engineering (FEEIT)


Basic information

Type of work: Dissertation thesis
Topic: Štatistické a metrologické metódy kalibrácie a vyhodnocovania neistôt v meraní
Title of topic in English: Statistical and metrological methods for calibration and uncertainty evaluation in measurement
State of topic: approved (prof. Ing. Viktor Smieško, PhD. - Chairperson of Departmental Board)
Thesis supervisor: doc. RNDr. Viktor Witkovský, CSc.
Faculty: Faculty of Electrical Engineering and Information Technology
Supervising department: Institute of Electrical Engineering - FEEIT
Max. no. of students: 1
Academic year:2019/2020
Proposed by: doc. RNDr. Viktor Witkovský, CSc.
External educational institution: Institute of Measurement Science of the Slovak Academy of Science
Annotation: Kalibrácia meracích zariadení a analýza neistôt výsledkov merania patrí medzi základné úlohy metrológie a teórie merania. Vyhodnocovanie neistôt meraní podľa odporúčania ISO GUM (Evaluation of measurement data - Guide to the expression of uncertainty in measurement) a jeho dodatkov (Supplement 1 a 2, Propagation of distributions using a Monte Carlo method) vedie k problému určenia pravdepodobnostného rozdelenia funkcie nezávislých náhodných premenných. Hlavným cieľom dizertačnej práce je rozvoj nových metód a algoritmov vhodných pre vyjadrenie a výpočet neistôt v meraní, s dôrazom na metódy Monte Carlo a metódy založené na numerickom invertovaní charakteristickej funkcie príslušného pravdepodobnostného rozdelenia. Ďalším cieľom je aplikovať tieto pokročilé metódy a algoritmy na problémy komparatívnej kalibrácie meracích prístrojov a problémy analýzy dát a neistôt výsledkov meraní, v teórii spoľahlivosti resp. v metrológii. Predpokladom úspešného riešenia témy dizertačnej práce sú základné znalosti v oblasti metrológie, pravdepodobnosti a štatistiky a programovania v prostredí Matlab.
Annotation in English: Calibration of measurement devices and the analysis of uncertainty in measurement is a fundamental task of metrology and measurement science. Evaluating the uncertainties in measurements, as recommended by the ISO GUM (Evaluation of measurement data - Guide to the expression of uncertainty in measurement) and its amendments (Supplement 1 and 2, Propagation of distributions using a Monte Carlo method), leads to the problem of determining the probability distribution of function of independent random variables. The dissertation will be aimed at the development of new methods and algorithms suitable expression and calculation of uncertainties in measurement, with an emphasis on Monte Carlo methods and methods based on numerical inversion of the characteristic function of the associated probability distribution. Another objective is to apply these advanced methods and algorithms for comparative calibration of the measurement devices and uncertainty analysis of measurements, in the theory of reliability and in metrology. Precondition for a successful solution of the PhD thesis is basic knowledge of metrology, probability and statistics, and programming skills in Matlab.



Limitations of the topic

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Limit to study programme
The table shows limitations of study programme, field, track the student has to be enrolled in to be able to register for a given topic.

ProgrammeTrackTrack
D-MT Measurement Technology-- not entered -- -- not entered --