Uncertainty analysis of a non-automatic weighing instrument from calibration data on scales according to the SIM guide

Data in Brief

卷:33

José Daniel Hernández-Vásquez¹  Cristian Antonio Pedraza-Yepes²  Oscar Fabián Higuera-Cobos²  Germán Roca-Gómez²  Ulises Ospino-López² 

[1] Universidad Antonio Nariño, Faculty of Mechanical, Electronic and Biomedical Engineering (FIMEB), Research Group GIFOURIER, Mechanical Engineering Program, Puerto Colombia, Colombia;

[2] Universidad del Atlántico, Faculty of Engineering, Mechanical Engineering Program, Research Group CONFORMAT, Puerto Colombia, Colombia;

关键词: Calibration;    Measurement uncertainty;    Metrology;    SIM guide;   

DOI  :  

来源: DOAJ

【 摘 要 】

This research was motivated by technical-economic challenges imposed by mass metrology, specifically, in matters concerning calibration methods of non-automatic type weighing instruments (i.e.: digital scales). In order to contextualize the problem detected, in the industry there are different processes of mass measurement that are controlled by digital scales, such as: mass of liquids, chemicals, food, body mass of a person. In these processes, the scale is used in the following four conditions for mass measurement: (i) ascending and descending load, returned to zero; (ii) ascending and descending load, without the need to return to zero; (iii) only with ascending load and (iv) only with descending load. In this context and, maintaining the principles for the calibration of a measurement instrument in which it must be carried out under the same operating conditions as the instrument, metrology laboratories must knowing the metrological reliability (i.e.: errors and uncertainties) for each situation. This is exactly the main motivation for the development of the research. Thus, the experimental data obtained in a research laboratory under controlled environmental conditions allowed obtaining a minimum expanded uncertainty associated with the mass measurement of 0.0012 kg (k=2; confidence level: 95%).

【 授权许可】

Unknown