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Abstract

Obtaining discrete data is inseparably connected with losing information on surface properties. In contact measurements, the ball tip functions as a mechanical-geometrical filter. In coordinate measurements the coordinates of the measurement points of a discrete distribution on the measured surface are obtained. Surface geometric deviations are represented by a set of local deviations, i.e. deviations of measurement points from the nominal surface (the CAD model), determined in a direction normal to this surface. The results of measurements depend both on the ball tip diameter and the grid size of measurement points. This article presents findings on the influence of the ball tip diameter and the grid size on coordinate measurement results along with the experimental results of measurement of a free-form milled surface, in order to determine its local geometric deviations. One section of the surface under research was measured using different measurement parameters. The whole surface was also scanned with different parameters, observing the rule of selecting the tip diameter d and the sampling interval T in the ratio of 2:1.

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Authors and Affiliations

Małgorzata Poniatowska
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Abstract

Local geometric deviations of free-form surfaces are determined as normal deviations of measurement points from the nominal surface. Different sources of errors in the manufacturing process result in deviations of different character, deterministic and random. The different nature of geometric deviations may be the basis for decomposing the random and deterministic components in order to compute deterministic geometric deviations and further to introduce corrections to the processing program. Local geometric deviations constitute a spatial process. The article suggests applying the methods of spatial statistics to research on geometric deviations of free-form surfaces in order to test the existence of spatial autocorrelation. Identifying spatial correlation of measurement data proves the existence of a systematic, repetitive processing error. In such a case, the spatial modelling methods may be applied to fitting a surface regression model representing the deterministic deviations. The first step in model diagnosing is to examine the model residuals for the probability distribution and then the existence of spatial autocorrelation.

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Authors and Affiliations

Małgorzata Poniatowska
Andrzej Werner

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