A contribution to curves network based ship hull form reverse engineering

Abstract

In reverse engineering (RE) there are several strategies, technologies and mathematical numerics involved from data acquisition system to surface fitting. This makes the reverse engineering methods always computationally expensive, time taking and more over error prone. Therefore, developing application specific RE method can offer the required quality with reasonable associated time and then cost. This paper presents a practical and efficient ship hull form reconstruction strategy which align the reverse engineering results into traditional hull form design procedures. The developed approach reads points from a set of unorganized noisy 3D point cloud and fits to cross-sectional curves network (transversal and waterline sections). It consists of several point cloud pre-processing functions, the curves fitting (interpolation and approximation) and presents different Non-Uniform Rational B-Spline (NURBS) surface fitting approaches from curves network. The point cloud pre-processing removes outliers and extracts transversal and waterline sections. It is also equipped with different functions to successfully filter and smooth point cloud so that it can be fitted to curves by interpolation or approximation. The suitability of different existing surface generations (lofting, patching and surface from curves network) are experimented based on cross-sectional curves. The developed approach is tested against two hull forms (scanned and manually generated) point cloud. The tests reveals that, the developed approach is time saving and suitable for hull form reconstruction.