A Study of Natural Neighbour Interpolation and its application to automotive engine test data

R Tily, C J Brace

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Natural Neighbour interpolation (NNI) is a method of interpolation, used primarily with irregular spatial data, which has a number of attractive features. This paper discusses Natural Neighbour interpolation, its related Voronoi and Delaunay structures, and its suitability for processing automotive engine test data. Tests show that NNI can successfully interpolate randomly scattered engine test data without the need for an intermediate gridding operation. This allows data to be clustered tightly in some areas and sparsely scattered in others. NNI also shows itself to be a very accurate interpolation method, with better performance than commonly used techniques. Although NNI is available in a small number of specialized non-automotive software packages, there is currently no generally available implementation in mathematical software packages, such as MathWorks's MATLAB, that could be used in a wide number of applications, including automotive. A number of MATLAB functions and programs, that implement NNI, have been developed by the authors and are introduced here.
Original languageEnglish
Pages (from-to)1003
Number of pages1
JournalProceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
Volume220
Publication statusPublished - Mar 2006

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