Application of Monte Carlo Method in the Measurement Process Design According to next Generation of GPS-Reference-Cited by-同舟云学术

Application of Monte Carlo Method in the Measurement Process Design According to next Generation of GPS

Published:2011-02 Issue: Volume:189-193 Page:96-101
ISSN:1662-8985
Container-title:Advanced Materials Research
language:
Short-container-title:AMR

Author:

Zhang Ya¹,Fu Jian Zhong¹,Chen Zi Chen¹

Affiliation:

1. Zhejiang University

Abstract

Measurement process has an important impact on the reliability of measurement. The reliability of measurement is weighed by measurement uncertainty. It is very difficult to estimate the uncertainty in the indirect measurements according to the transfer formula given by GUM (Guide to the Expression of Uncertainty in Measurement). Monte Carlo method was proposed to solve the problem of uncertainty estimation and seek suitable measurement process in the indirect measurements. The mathematical relation between the measurand and the direct measures is established firstly. Then Monte Carlo method was adopted to conduct the sampling and synthesis of measurement uncertainty contributors. At last, the measurement method was evaluated and improved according to Procedure for Uncertainty Management, which is given by next generation of GPS (Geometrical Product Specification). Experimental result shows that Monte Carlo Simulation method has a good application foreground in the uncertainty estimation and measurement process design.

Publisher

Trans Tech Publications, Ltd.

Subject

General Engineering

Link

https://www.scientific.net/AMR.189-193.96.pdf

Reference5 articles.

1. Liu Wenwen , Ge Leyi. Measurement Uncertainty Digital Evaluation for Virtual Instrument Based on Monte Carlo Method. Journal of Electronic Measurement and Instrument [J], Volume 21, Issues 3, (2007).

2. Defen Zhang, Paul G. Maropoulos, Martyn Hill. Random uncertainty propagation in estimates of ball parameters from coordinate measurements, international journal of machine tools &manufacture [J], Volume 46, Issues 12-13, October 2006, Pages 1362-1368.

3. Ding Zhenliang. Errors and data processing, [M], Harbin: Harbin Institute of Technology Press，2002, 5.

4. Dovmark J. New interesting concepts from ISO/TC 213. In: ACMC annual general meeting in Ottawa, Canada, December 3, (2001).

5. Wang Jinxing. Uncertainty theory and its application in the improved Geometrical Product Specifications (GPS) [D]. Huazhong University of Science and Technology, (2006).