Industrial attachment with National Metrology Centre (NMC) A*STAR

• Main Author: Ong, Xiang Ren.
• Other Authors: Lin Zhiping
• Format: Industrial Attachment (IA)
• Language: English
• Published: 2011
• Subjects: DRNTU::Engineering::Electrical and electronic engineering
• Online Access: http://hdl.handle.net/10356/46526
• Institution: Nanyang Technological University

Metrology is the science of measurement which includes all theoretical and practical aspects of measurement. Metrological activities are fundamental for guaranteeing the quality of scientific and industrial activities. The Guide to the Expression of Uncertainty in measurement (GUM) has been an internationally accepted main reference for the evaluation and expression of measurement uncertainty. Recently, evaluation of measurement uncertainty has been proposed on the basis of a numerical method, Monte Carlo Method documented in GUM supplement 1 (S1), ‘Propagation of distributions using a Monte Carlo method’. For the programs that are used to simulate Monte Carlo, Excel macro and MATLAB are compared. Macro in Excel worksheet provides an interface to allow on screen values to be updated upon any form of calculation. A number of examples are tested with macro and shown to consistently produce a well-conditioned result that is documented in GUMS1. MATLAB provides an environment where the codes for Monte Carlo Method (MCM) are written based on matrix operations and integrated functions in this high level programming language. A number of examples are tested with MATLAB and has shown consistency in the results. In order to validate Monte Carlo Method, most of the examples are evaluated based on GUM and MCM. Adding on, both linear and non-linear model are evaluated. The purpose is to show the limitation that arises when GUM approach is applied. MCM is applied to practical applications such as finding the uncertainty of a calibration factor of the power sensor, where partial derivatives based on GUM are tedious to arrive at.