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 NNI, 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 Math Works'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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
