An Algorithm to Recognize Shape and Position of Basic Functional Geometries Obtained by Manufacturing: An Optimization of Grid Increment

The development of automated measurement systems for monitoring basic functional geometries arises as a response to the increasing automation of manufacture. The paper describes the optimization of the grid increment to be used in the algorithm established by the authors to automatically recognize 3D geometries. Differential geometry was used to determine Gaussian and mean local curvatures of surfaces described by ordered cloud point representation, considered the fundamental conditions for the decision of geometric shapes automatic identification. A case study for spherical surfaces is shown, relating the grid increment with the values of the sphere attributes. The optimization of the increment appears to minimize the uncertainty of the algorithm. The results validated the suitability of the algorithm hereby proposed.