Report on the integrated software for data processing and uncertainty estimation of dynamic measurements, including related methods and algorithms
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00177016%3A_____%2F22%3AN0000108" target="_blank" >RIV/00177016:_____/22:N0000108 - isvavai.cz</a>
Výsledek na webu
<a href="https://zenodo.org/record/7090572" target="_blank" >https://zenodo.org/record/7090572</a>
DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Report on the integrated software for data processing and uncertainty estimation of dynamic measurements, including related methods and algorithms
Popis výsledku v původním jazyce
This document focuses on the errors and uncertainties of quantity estimation algorithms and propagation of uncertainties through algorithms. It provides description of basic problems, shows several examples and discussion on properties of selected algorithms. Basic theory on uncertainties is described in Guide to the Expression of Uncertainty in Measurement [1]. This approach is called GUF. Due to limitations, other approaches were studied. A Monte Carlo method (MCM) was summarized in [2], [3]. Methods presented in this document utilize both approaches. Chapter 2 describes errors and uncertainties of any quantity estimation algorithm. First, general theory is presented, next, application to an actual algorithm is discussed. Chapter 3 discuss existing software QWTB and TWM, and also describes a newly developed software QWTBvar including its interface, usage and presents two examples. Chapter 7 presents the results from uncertainty estimation and validation of algorithm for estimation of Spurious Free Dynamic Range (SFDR). Chapter 8 presents the results from uncertainty estimation and validation of algorithm for estimation of Integral and Differential non-linearity (INL-DNL). Chapter 3 describes the newly developed software with its inner structure, presented examples serves as a handbook of utilisation, and source code is presented in public repository [4].
Název v anglickém jazyce
Report on the integrated software for data processing and uncertainty estimation of dynamic measurements, including related methods and algorithms
Popis výsledku anglicky
This document focuses on the errors and uncertainties of quantity estimation algorithms and propagation of uncertainties through algorithms. It provides description of basic problems, shows several examples and discussion on properties of selected algorithms. Basic theory on uncertainties is described in Guide to the Expression of Uncertainty in Measurement [1]. This approach is called GUF. Due to limitations, other approaches were studied. A Monte Carlo method (MCM) was summarized in [2], [3]. Methods presented in this document utilize both approaches. Chapter 2 describes errors and uncertainties of any quantity estimation algorithm. First, general theory is presented, next, application to an actual algorithm is discussed. Chapter 3 discuss existing software QWTB and TWM, and also describes a newly developed software QWTBvar including its interface, usage and presents two examples. Chapter 7 presents the results from uncertainty estimation and validation of algorithm for estimation of Spurious Free Dynamic Range (SFDR). Chapter 8 presents the results from uncertainty estimation and validation of algorithm for estimation of Integral and Differential non-linearity (INL-DNL). Chapter 3 describes the newly developed software with its inner structure, presented examples serves as a handbook of utilisation, and source code is presented in public repository [4].
Klasifikace
Druh
O - Ostatní výsledky
CEP obor
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OECD FORD obor
20201 - Electrical and electronic engineering
Návaznosti výsledku
Projekt
<a href="/cs/project/8B18008" target="_blank" >8B18008: Quality assessment of electric vehicle Li-ion batteries for second use applications</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů