Data sampling technique (DST) for measuring surface waving

Abstract

As the manufactured parts in aerospace and automotive industries tend to be larger and more complex, the inspection process becomes a difficult and timeconsuming one. To decrease inspection costs and time, the optimisation of the required Surface Sampling Points (SSP) is crucial. This paper describes a data sampling technique (DST) for the inspection of waving surfaces of parts. This technique provides the minimum number of SSP required to reconstruct accurately the waving surface. The developed DST comprises two steps: (1) trigonometric polynomial approximation of the curvilinear segments, at certain orthogonal sections on the waving surface, and (2) estimation of the critical frequency of the approximated waving sections, leading to the minimum number of SSP. The pilot implementation of the DST has been performed on a waving wing surface and has been tested using industrial data. The accuracy and the efficiency of the DST has been estimated through (1) the comparison of theoretical (CAD) profiles with the surface profiles measured using the current sampling method and with the ones derived using the developed sampling technique, and (2) the comparison of the sampling intervals extracted by DST and the ones extracted by analysing past measurements with Discrete Fourier Transform (DFT).