By Topic

The evaluation of measurement uncertainty for laser tracker based on Monte Carlo method

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Jindong Wang ; State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China ; Junjie Guo ; Hao Wang ; Yufen Deng

The laser tracker is adopted the multi-station and time-sharing measurement principle to rapidly and accurately detect the precision of machine tool. In accordance with international standard, the measurement results should also give the corresponding measurement uncertainty. In the paper, the Monte Carlo method is used to evaluate the measurement uncertainty of laser tracker's multi-station and time-sharing measurement. The N pseudo-measured data are generated by the measured ranging data of laser tracker, and the N calculation results of base point will be determined by the algorithm for base point calibration. It can obtain the measurement uncertain of ase point by calculating standard deviation of the N calculation results, then it can calculate the measurement uncertainty of each measuring point. The measurement uncertainty for the base point and measuring point can be comparatively accurately evaluated based on Monte Carlo method through less measurement times, meanwhile, it does not need to determine the uncertainty propagation coefficient of each error source, which bring great convenience in the actual calculation. Results of simulation and experiment shows the Monte Carlo method is an effective evaluation method of measurement uncertainty.

Published in:

2011 IEEE International Conference on Mechatronics and Automation

Date of Conference:

7-10 Aug. 2011