B-spline based corner smoothing method to decrease the maximum curvature of the transition curve

2021 ◽  
pp. 1-9
Author(s):  
Nuodi Huang ◽  
Li Hua ◽  
Xi Huang ◽  
Yang Zhang ◽  
Li-Min Zhu ◽  
...  
Keyword(s):  
External Factors ◽  
Error Tolerance ◽  
Transition Curve ◽  
Machining Efficiency ◽  
Control Points ◽  
Efficiency Improvement ◽  
B Spline ◽  
Maximum Curvature ◽  
Approximation Errors ◽  
The Given

Abstract Toolpath represented by linear segments leads to tangency discontinuity between blocks, which results in fluctuation of feedrate and reduction of machining efficiency and quality. To eliminate these unwanted external factors, optimal corner smoothing operation is essential for CNC systems to achieve a smooth toolpath. This work proposes a corner smoothing approach by generating a B-spline transition curve with 7 control points. By adjusting the position of the control points, the resulting transition curve is not limited to smooth the corner in the convex side of the corner, but shuttles back and forth between the convex and concave sides to decrease the maximum curvature, while respecting the given error tolerance. The approximation errors in convex and concave sides can be analytically calculated. Experimental results demonstrate the effectiveness of the proposed method on machining efficiency improvement.

scholarly journals Approximation of Vehicle Trajectory with B-Spline Curve

2016 ◽  
Vol 19 (1) ◽  
pp. 1-5
Author(s):  
Dušan Páleš ◽  
Veronika Váliková ◽  
Ján Antl ◽  
František Tóth
Keyword(s):  
Basis Function ◽  
Extreme Case ◽  
Bézier Curve ◽  
Control Points ◽  
B Spline ◽  
Spline Curve ◽  
Planar Curve ◽  
Vehicle Trajectory ◽  
The Given ◽  
Real Vehicle

In this contribution, we present the description of a B-spline curve. We deal with creation of its basis function as well as with creation of the curve itself from entered control points. Following the literature, we formed an algorithm for B-spline modelling and we used it for the planar and spatial curve. The planar curve is made of chosen points. The spatial curve approximates the trajectory of a real vehicle, which trajectory was obtained by the set of measured points. The modelled curve very exactly describes the polygon created from the linked control points. With the lowering degree of the curve, this one is more clamping to the given polygon and for the extreme case it is transformed to the polygon itself. The advantage of the B-spline curve use is, for example in comparison with a Bézier curve, high adaptability, which is expressed in its parameters - besides entered control points, these are knots generated on the curve and degree of the curve.

scholarly journals Approximating curve by a single segment of B-Spline or Bézier curve directly in CAD environment

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mariusz Sobolak ◽  
Piotr Połowniak ◽  
Adam Marciniec ◽  
Patrycja Ewa Jagiełowicz
Keyword(s):  
Simulated Annealing ◽  
Optimization Methods ◽  
Bézier Curve ◽  
Bezier Curve ◽  
Control Points ◽  
Curve Segment ◽  
B Spline ◽  
Single Segment ◽  
Original Procedure ◽  
The Given

AbstractThe paper presents the method of approximating curves with a single segment of the B-Spline and Bézier curves. The method for determining a single curve segment using the optimization methods in the CATIA environment is shown. The algorithms of simulated annealing and design of experiment are used for optimization. For the same purpose, a new original procedure for determining the distance between the given curves using explicit parameters in the CATIA environment was also used. This approximation of the cyclic curves results in the curve oscillation as shown in the examples. The results show that the approximation method with Bézier curve using control points as “free” points can be applied to obtain the best results of approximation.

Cubic TP B-Spline Curves with a Shape Parameter

2013 ◽  
Vol 11 ◽  
pp. 59-72 ◽  
Author(s):  
Mridula Dube ◽  
Reenu Sharma
Keyword(s):  
Tensor Product ◽  
Shape Parameter ◽  
Control Points ◽  
Shape Parameters ◽  
Special Shape ◽  
B Spline ◽  
Control Polygon ◽  
Spline Curves ◽  
Trigonometric Spline ◽  
The Given

In this paper a new kind of splines, called cubic trigonometric polynomial B-spline (cubic TP B-spline) curves with a shape parameter, are constructed over the space spanned by As each piece of the curve is generated by three consecutive control points, they posses many properties of the quadratic B-spline curves. These trigonometric curves with a non-uniform knot vector are C1 and G2 continuous. They are C2 continuous when choosing special shape parameter for non-uniform knot vector. These curves are closer to the control polygon than the quadratic B-spline curves when choosing special shape parameters. With the increase of the shape parameter, the trigonometric spline curves approximate to the control polygon. The given curves posses many properties of the quadratic B-spline curves. The generation of tensor product surfaces by these new splines is straightforward.

Realization of NURBS for Cranium in a Laser Sintering Machine

2011 ◽  
Vol 421 ◽  
pp. 570-573
Author(s):  
Jing Yu Zhuang ◽  
De Fu Liu ◽  
Cheng De Gao ◽  
Huan Long Hu ◽  
Li Wang ◽  
...  
Keyword(s):  
Boundary Condition ◽  
Selective Laser Sintering ◽  
Tangent Vector ◽  
Laser Sintering ◽  
Control Points ◽  
Characteristic Parameters ◽  
B Spline ◽  
Key Points ◽  
Nurbs Interpolation ◽  
The Given

It is an issue in the application of Non-Uniform Rational B-Spline (NURBS) how to achieve the characteristic parameters based on a given curve. In this work, the parameterization method of accumulated chord length is used to construct the knot vector. The tangent vector is chosen as the boundary condition. The characteristic parameters including the control points, the knot vector and the weights are calculated according to the key points and corresponding weights of a given curve. An example of NURBS interpolation for cranium is given based on a selective laser sintering (SLS) machine. The characteristic parameters are obtained with Rhino software. The NURBS interpolation for cranium is realized using these characteristic parameters in the SLS machine. The results show that the practical sintering curve is coincident with the given curve.

scholarly journals Complex Uncertainty of Surface Data Modeling via the Type-2 Fuzzy B-Spline Model

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1054
Author(s):  
Rozaimi Zakaria ◽  
Abd. Fatah Wahab ◽  
Isfarita Ismail ◽  
Mohammad Izat Emir Zulkifly
Keyword(s):  
Complex Surface ◽  
Complex Data ◽  
Fuzzy Data ◽  
Control Points ◽  
B Spline ◽  
Spline Surface ◽  
Data Control ◽  
Surface Data ◽  
Model Complex

This paper discusses the construction of a type-2 fuzzy B-spline model to model complex uncertainty of surface data. To construct this model, the type-2 fuzzy set theory, which includes type-2 fuzzy number concepts and type-2 fuzzy relation, is used to define the complex uncertainty of surface data in type-2 fuzzy data/control points. These type-2 fuzzy data/control points are blended with the B-spline surface function to produce the proposed model, which can be visualized and analyzed further. Various processes, namely fuzzification, type-reduction and defuzzification are defined to achieve a crisp, type-2 fuzzy B-spline surface, representing uncertainty complex surface data. This paper ends with a numerical example of terrain modeling, which shows the effectiveness of handling the uncertainty complex data.

scholarly journals On the BIC for determining the number of control points in B-spline surface approximation in case of correlated observations

2020 ◽  
Vol 10 (1) ◽  
pp. 110-123
Author(s):  
Gaël Kermarrec ◽  
Hamza Alkhatib
Keyword(s):  
Shape Control ◽  
Simple Procedure ◽  
Spline Approximation ◽  
Autoregressive Process ◽  
Optimal Number ◽  
Information Criteria ◽  
General Effect ◽  
Control Points ◽  
B Spline ◽  
Correlated Observations

Abstract B-spline curves are a linear combination of control points (CP) and B-spline basis functions. They satisfy the strong convex hull property and have a fine and local shape control as changing one CP affects the curve locally, whereas the total number of CP has a more general effect on the control polygon of the spline. Information criteria (IC), such as Akaike IC (AIC) and Bayesian IC (BIC), provide a way to determine an optimal number of CP so that the B-spline approximation fits optimally in a least-squares (LS) sense with scattered and noisy observations. These criteria are based on the log-likelihood of the models and assume often that the error term is independent and identically distributed. This assumption is strong and accounts neither for heteroscedasticity nor for correlations. Thus, such effects have to be considered to avoid under-or overfitting of the observations in the LS adjustment, i.e. bad approximation or noise approximation, respectively. In this contribution, we introduce generalized versions of the BIC derived using the concept of quasi- likelihood estimator (QLE). Our own extensions of the generalized BIC criteria account (i) explicitly for model misspecifications and complexity (ii) and additionally for the correlations of the residuals. To that aim, the correlation model of the residuals is assumed to correspond to a first order autoregressive process AR(1). We apply our general derivations to the specific case of B-spline approximations of curves and surfaces, and couple the information given by the different IC together. Consecutively, a didactical yet simple procedure to interpret the results given by the IC is provided in order to identify an optimal number of parameters to estimate in case of correlated observations. A concrete case study using observations from a bridge scanned with a Terrestrial Laser Scanner (TLS) highlights the proposed procedure.

Sequential B-Spline Surface Construction Using Multiresolution Data Clouds

2012 ◽  
Vol 12 (2) ◽  
Author(s):  
Yuan Yuan ◽  
Shiyu Zhou
Keyword(s):  
Control Points ◽  
Finite Sample ◽  
B Spline ◽  
Spline Surface ◽  
Spline Surfaces ◽  
Filtering Technique ◽  
Engineering Practices ◽  
Asymptotical Convergence ◽  
Surface Construction ◽  
Fitting Error

B-spline surfaces are widely used in engineering practices as a flexible and efficient mathematical model for product design, analysis, and assessment. In this paper, we propose a new sequential B-spline surface construction procedure using multiresolution measurements. At each iterative step of the proposed procedure, we first update knots vectors based on bias and variance decomposition of the fitting error and then incorporate new data into the current surface approximation to fit the control points using Kalman filtering technique. The asymptotical convergence property of the proposed procedure is proved under the framework of sieves method. Using numerical case studies, the effectiveness of the method under finite sample is tested and demonstrated.

A New Approach to G1 Biarc Approximations for Making Smooth, Accurate, and Non-Gouged Profile Features Using CNC Contouring

2006 ◽  
Author(s):  
Zezhong C. Chen ◽  
Xujing Yang
Keyword(s):  
Manufacturing Industry ◽  
Cutting Tool ◽  
Minimum Size ◽  
Free Form ◽  
New Approach ◽  
B Spline ◽  
Tool Paths ◽  
The Past ◽  
Approximation Errors ◽  
The Individual

Extensive research on G1 biarcs fitting to free-form curves (i.e., Bezier, B-spline, and NURBS curves) has been conducted in the past decades for various purposes, including CNC contouring to make smooth, accurate profile features such as pockets, islands, and sides. However, all the proposed approaches only focused on the approximation errors and the biarc number, not on the radius of the individual fitting arc; so it could be smaller than the cutting tool, which would cause gouging during machining. This work, based on the tool radius pre-determined by the minimum size of the concavities of the design profile, proposes a new approach to approximating the profile with a G1 biarc curve in order to make smooth, accurate, and non-gouged profile features using CNC contouring. The significant new contribution of this work is a new mechanism that ensures all the concave arcs of the fitting curve are larger than the pre-determined tool and the fitting errors meet the specified tolerance. This approach can promote the use of G1 biarc tool paths in the manufacturing industry to make high precision profile features.

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