An integrated fitting and fairing approach for object reconstruction using smooth NURBS curves and surfaces

Abstract This paper presents a new approach for object reconstruction by means of smooth NURBS curves and surfaces. Compared to the common object reconstruction algorithms that first, fit a curve or surface to a dataset and then, try to make it smooth in a post-processing fairing stage, this article proposes to apply the fitting and fairing procedures simultaneously to achieve desirable results. In the integrated fitting and fairing approach, the respective fitting and fairing objectives are met in a multi-objective optimization process. In the developed methodology, the structure of the reconstructed curves and surfaces (e.g. the arrangement of the knot vectors and location of control points) is optimized in such a way that the desired fairness will be locally achieved in every segment of the reconstructed object. The functionality of the developed method is investigated by some industrial case studies.

[1]  E. T. Y. Lee Energy, fairness, and a counterexample , 1990, Comput. Aided Des..

[2]  Weidong Zhu,et al.  Constrained fitting for 2D profile-based reverse modeling , 2006, Comput. Aided Des..

[3]  M. A. Ahmed,et al.  NURBS skinning surface for ship hull design based on new parameterization method , 2006 .

[4]  Robert Piessens,et al.  Quadpack: A Subroutine Package for Automatic Integration , 2011 .

[5]  F. Pérez-Arribas,et al.  Computer-aided design of horizontal axis turbine blades , 2012 .

[6]  Behnam Moetakef Imani,et al.  Innovative approach to computer-aided design of horizontal axis wind turbine blades , 2017, J. Comput. Des. Eng..

[7]  Gerald E. Farin,et al.  Fairing cubic B-spline curves , 1987, Comput. Aided Geom. Des..

[8]  Vipin Kumar,et al.  Multi-Objective Particle Swarm Optimization: An Introduction , 2014, Smart Comput. Rev..

[9]  Hyungjun Park,et al.  A method for approximate NURBS curve compatibility based on multiple curve refitting , 2000, Comput. Aided Des..

[10]  Weidong Zhu,et al.  Feature-based reverse modeling strategies , 2006, Comput. Aided Des..

[11]  Carlos A. Coello Coello,et al.  Improving PSO-Based Multi-objective Optimization Using Crowding, Mutation and epsilon-Dominance , 2005, EMO.

[12]  Yifan Chen,et al.  8. The Highlight Band, a Simplified Reflection Model for Interactive Smoothness Evaluation , 1994, Designing Fair Curves and Surfaces.

[13]  S. Nader Nabavi,et al.  Kinematically smoothing trajectories by NURBS reparameterization – an innovative approach , 2017, Adv. Robotics.

[14]  M Reyes Sierra,et al.  Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art , 2006 .

[15]  Ralph R. Martin,et al.  Constrained fitting in reverse engineering , 2002, Comput. Aided Geom. Des..

[16]  Yew Kee Wong,et al.  An automated curve fairing algorithm for cubic B -spline curves , 1999 .

[17]  Stefanie Hahmann,et al.  Knot-removal surface fairing using search strategies , 1998, Comput. Aided Des..

[18]  Russell C. Eberhart,et al.  Parameter Selection in Particle Swarm Optimization , 1998, Evolutionary Programming.

[19]  L. Fernández-Jambrina,et al.  Automatic surface modelling of a ship hull , 2006, Comput. Aided Des..

[20]  R. Piessens,et al.  A note on the optimal addition of abscissas to quadrature formulas of Gauss and Lobatto type , 1974 .

[21]  Behrooz Hassani,et al.  Pre-bent shape design of full free-form curved beams using isogeometric method and semi-analytical sensitivity analysis , 2018, Structural and Multidisciplinary Optimization.

[22]  Raúl Pérez-Fernández,et al.  A B-spline design model for propeller blades , 2018, Adv. Eng. Softw..

[23]  Liang Meng,et al.  A biarc-based shape optimization approach to reduce stress concentration effects , 2014 .

[24]  Ali Hashemian,et al.  Isogeometric analysis of free-form Timoshenko curved beams including the nonlinear effects of large deformations , 2018 .

[25]  Les A. Piegl,et al.  The NURBS Book , 1995, Monographs in Visual Communication.

[26]  Singiresu S. Rao Engineering Optimization : Theory and Practice , 2010 .

[27]  F. Pérez-Arribas,et al.  Automatic modelling of airfoil data points , 2016 .

[28]  Robert B. Fisher,et al.  Object reconstruction by incorporating geometric constraints in reverse engineering , 1999, Comput. Aided Des..

[29]  Yuping Wang,et al.  A new multi-objective particle swarm optimization algorithm based on decomposition , 2015, Inf. Sci..

[30]  P. Lan,et al.  Integration of non-uniform rational B-splines geometry and rational absolute nodal coordinates formulation finite element analysis , 2014 .

[31]  Nicholas S. Sapidis Designing Fair Curves and Surfaces: Shape Quality in Geometric Modeling and Computer-Aided Design , 1994, Designing Fair Curves and Surfaces.

[32]  Ali Hashemian,et al.  Surface fairness: a quality metric for aesthetic assessment of compliant automotive bodies , 2018 .

[33]  Behnam Moetakef Imani,et al.  A new quality appearance evaluation technique for automotive bodies including effect of flexible parts tolerances , 2018 .

[34]  Alessandro Reali,et al.  Finite element and NURBS approximations of eigenvalue, boundary-value, and initial-value problems , 2014 .

[35]  Gang Zhao,et al.  Target curvature driven fairing algorithm for planar cubic B-spline curves , 2004, Comput. Aided Geom. Des..

[36]  Seyed Farhad Hosseini,et al.  Improved B-Spline Skinning Approach for Design of Hawt Blade Mold Surfaces , 2017 .

[37]  Behnam Moetakef Imani,et al.  NURBS-BASED PROFILE RECONSTRUCTION USING CONSTRAINED FITTING TECHNIQUES , 2012 .

[38]  Gerald E. Farin,et al.  Curvature and the fairness of curves and surfaces , 1989, IEEE Computer Graphics and Applications.

[39]  Behrooz Hassani,et al.  The effect of parameterization on isogeometric analysis of free-form curved beams , 2016 .

[40]  Matthias Eck,et al.  Local Energy Fairing of B-spline Curves , 1993, Geometric Modelling.

[41]  Carlo H. Séquin,et al.  Functional optimization for fair surface design , 1992, SIGGRAPH.

[42]  Y. H. Peng,et al.  The algorithms for trimmed surfaces construction and tool path generation in reverse engineering , 2008, Comput. Ind. Eng..

[43]  Madjid Tavana,et al.  A new multi-objective particle swarm optimization method for solving reliability redundancy allocation problems , 2013, Reliab. Eng. Syst. Saf..