Simulation of line scale contamination in calibration uncertainty model

Abstract

Precise calibration of quartz line scales is very important for assuring traceability of microscopic measurements. Very significant influence in calibration uncertainty budget is represented by uncertainty of line centre detection. Line centre is usually detected through video signal processing using different types of algorithms. This paper is presenting calibration procedure that was developed in the Laboratory for Production Measurement at the Faculty of Mechanical Engineering in Maribor. It is focused in uncertainty analysis and especially in the influence of line scale contamination on determination of line centre position. Different types of line scale contamination like dirt spots, scratches, line edge incorrectness, and line intensity were simulated in order to test the ability of the line centre detection algorithm to eliminate such influences from the measurement results.

Optimization of Calibrating HeNe Laser Interferometers by Sample-Period Simulation

“…From Edlén's equation it can be calculated that a change of 1 °C or 380 Pa would yield an error of approximately one part per million, while the humidity would have to change by almost 100 %. Similarly, the material of line scales and gauge blocks respond to temperature change with expansion: a 1 °C change in steel would introduce an error of approximately ten parts per million in the distance measured, while with precise temperature measurement (with a resolution of 0.01 K), this error can be reduced to the level 10 -7 [26][27][28][29][30]. By using air-conditioning to maintain smoke/dust free air under normal conditions (20 °C, 101.325 kPa and 50 % humidity), precise sensing of these air parameters, and by automatic wavelength-, dead path-and material-thermal compensation, the overall uncertainty less than 1 µm/m can be attained [25].…”

Comparison of pitch distance determination algorithms

“…The gradient vector points in the steepest direction and the magnitude at the (x,y) coordinates is defined as: (1) and the orientation denoted by f (x, y) is: (2) The major drawback of these algorithms is their high sensitivity to noise, as illustrated in the next picture. Even a low level of noise can completely hide the edge signal.…”

“…The edges of lines on a real scale are far from being straight; they contain bumps and dimples, and sometimes holes. The algorithm should be able to cope with them and find the best fit to the real edge [2].…”

Calibration machine for linear scales

“…A good overview is given in [12] of the various calibration methods and equipments used by the major national metrology laboratories. The paper by Druzuvec and his co-authors [3] discusses the effect of contamination in the calibration uncertainty model. Significant influence in calibration uncertainty budget is represented by the uncertainty of the line centre detection.…”