B-spline Surface Reconstruction Based on RBFNN Pre-fitting

The free-form surface reconstruction is one of the important skills of reverse en gineering. A novel method for B-spline surface reconstruction by artificial neu ral network was introduced. An effective radius-basis-function (RBF) network m odel was applied in pre-fitting of scattered data from an original surface. Usi ng a multi-step B-spline surface approximation algorithm,the mathematical mode l called as a RBFNN model,was transformed to a bicubic B-spline surface. This model can reconstruct original surfaces precisely and quickly, fitting to fairin g demand. The reconstructed surfaces have an available and standard format in CA D/CAM system, fitting to editable and exchangeable demand. Some key techni ques were analyzed in detail. The approach is feasible and valuable for practica l applications.