It’s necessary to specify the uncertainty for the measuring results. It’s difficult to evaluate some uncertainties of large-scale measurement by conventional analysis method and standard comparison method

especially for special fitting task. For special large-scale measurement

we research its uncertainty based on Monte Carlo evaluation and denote this uncertainty as discrete point-clouds through computer visual. The measuring uncertainty is evaluated by off-line simulation for an optimum sampling strategy. The optimized measurement idea including point symmetry

equal distribution and radius constraint is given

taking the example of analyzing large-scale circular section part by laser tracker. This is applied to measuring practical tunnel components by laser tracker. It’s proved that the uncertainty of given measuring objects is evaluated accurately and intuitively by Monte Carlo evaluation and discrete point-clouds representation

which also build the optimum sampling strategy for better measuring precision.