| Zugriffsnummer | 44584 |
| Dokumenttyp | Forschungsdaten |
| Peer Review | unbekannt |
| Sprache | Englisch |
| Titel | EMUE-D6-2 Calibration uncertainty GUM vs Bayesian : Calibration of a torque measuring system - GUM uncertainty evaluation for least-squares versus Bayesian inference |
| Autor(in); Institution |
Martens, Steffen; 8.4, Mathematische Modellierung und Datenanalyse, PTB-Berlin
Klauenberg, Katy; 8.4, Mathematische Modellierung und Datenanalyse, PTB-Berlin
Elster, Clemens; 8.4, Mathematische Modellierung und Datenanalyse, PTB-Berlin
|
| Quelle/Jahr | (2020) |
| Availability | [Dataset] |
| DOI | |
| URL | |
| Verlag | Zenodo |
| Freie Schlagworte | Measurement uncertainty ; Measurement model ; GUM ; Bayesian inference ; Calibration ; Straight-line regression ; Least-squares estimation ; Torque measuring device ; VDI/VDE - 2600 Blatt 2 |
| Zusammenfassung | Calibration of a torque measuring system - GUM uncertainty evaluation for least-squares versus Bayesian inference This example addresses the straight-line calibration of a torque measuring sensor against a reference system using measurements taken at different torque values. For each torque value, a single measurement result of the reference system is available, together with results of repeated measurements of sensor that shall be calibrated. The goal is to determine a linear relationship that relates results of the torque measuring sensor with those of the reference system. The data are analysed by applying (i) ordinary and weighted least-squares estimation in combination with an uncertainty evaluation following the GUM and (ii) Bayesian inference. Analytic expressions are given for the Bayesian uncertainty analysis which simplifies its application. The results obtained by the different approaches are discussed and recommendations given. Files contained in the dataset are: - Example_A242.pdf: Report “Calibration of a torque measuring system – GUM uncertainty evaluation for least-squares versus Bayesian inference”; - Example_A242.tex: LaTeX file to be compiled in order to produce Example_A242.pdf; - Compendium_A242.bib: bibliography file; - Fig1.pdf: PDF file needed to compile Example_A242.tex; - Fig2.pdf: PDF file needed to compile Example_A242.tex; - data_A242.csv: Date file containing the estimates and standard deviations of the measurements; - Example_A242.Rmd: R Markdown file for uncertainty evaluation following the GUM and Bayesian inference. As output an HTML file similar to Example_A242.pdf is created with results dynamically produced by underlying R code; - aps.csl: CSL file needed to cite the reference in Example_A242.Rmd according to the American Physical Society style. |
| Kostenfreier Zugang | Freier Zugang |
| Rechteinformation | CC BY 4.0 ; Creative Commons Attribution 4.0 License |
| Themenbereich der Metrologie | Mathematik und metrologische Informationstechnik |
| Forschungsprojekt | 17NRM05: EMUE: Advancing measurement uncertainty - comprehensive examples for key international standards |
| Förderinformationen (1) |
Förderername: European Commission (EC)
Förderer ID: 0000 0001 2242 8989 Förderer ID Typ: ISNI Förderprogramm: EMPIR 2017 Normative Titel der Förderung: 17NRM05: EMUE: Advancing measurement uncertainty - comprehensive examples for key international standards Förderungsnummer: 17NRM05 URI der Förderung: http://empir.npl.co.uk/emue/ |
Zitierung
Martens, S., Klauenberg, K., & Elster, C. (2020). EMUE-D6-2 Calibration uncertainty GUM vs Bayesian : Calibration of a torque measuring system - GUM uncertainty evaluation for least-squares versus Bayesian inference [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3858121