Method for approximate noise elimination in form and roughness measurements

摘要

In form and roughness measurements, often surfaces are measured which are approximately straight, round, or smooth. Measuring such surfaces often gives measurement results in which noise plays a role. This noise may give an offset in measurement parameter as the noise makes the parameter, e.g. the flatness deviation of the Ra-value, deviate away from zero. In this paper we propose a method to correct for this noise bias for the roughness parameter Rq which is equivalent to the standard deviation. By considering the decrease in Rq once an average over multiple measurements is made, an unbiased value for Rq is estimated by extrapolating the value to an infinite amount of measurements. It is shown that using this method for two profile measurements only, the true measurand is approached better than with averaging dozens of measurements. This principle is extended to obtain a complete 'noise-corrected' profile by considering the power spectrum and the change of each Fourier component with averaging. As for each Fourier component few estimations are available, the method only has advantages when many measurements are taken. Combining the two methods and considering the statistical significance of each Fourier component enables a further reduction. Simulation and measurement examples are shown for roughness and roundness measurments.