Examinando por Materia "Curve fitting"
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Ítem Computational Geometry in Medical Applications(Universidad EAFIT, 2016) Cortés Acosta, Camilo Andrés; Ruíz Salguero, Óscar Eduardo; Flórez Esnal, JuliánÍtem Graphs of optimally fit features in assessment of geometric tolerances(2014) Ruíz, Óscar E.; Congote, John; Acosta, Diego A.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEThis article presents an industrial application case of geometric constraint graphs, whose nodes are statistically optimal instances of manufacturing or design features and whose edges are usual geometric relations used in tolerance applications -- The features might be virtual ones -- As a consequence, they may lie beyond the piece’s extents -- The geometric constraint graph may have cyclic topology -- Contrary to deterministic geometric constraint graphs, tolerance constraint graphs admit numerical slacks, due to their stochastic nature -- The methodology has been applied in industrial scenarios, showing superiority to traditional material features for the assessment of tolerancesÍtem High dynamic range imaging method for interferometry(ELSEVIER SCIENCE BV, 2011-01-01) Vargas, J.; Restrepo, R.; Quiroga, J.A.; Belenguer, T.; Universidad EAFIT. Departamento de Ciencias Básicas; Óptica AplicadaWe demonstrate a method to easily and quickly extend the dynamic range imaging capabilities of the camera in a typical interferometric approach. The camera dynamic range is usually low and limited to 256 gray levels. Also, it is well known that one may have over or under-exposed regions in the interferogram (due to non-uniform illumination) which makes these image regions not reliable. In our proposed method it is not necessary to obtain or use the non-linear camera response curve in order to extend the camera dynamic range. We obtain a sequence of differently exposed interferograms, typically five or six; after that, we compute the corresponding normalized fringe patterns and modulation maps using a typical normalization method. These normalized patterns are combined through a temporal weighted average using as weights the corresponding modulation maps. We show a set of experimental results that prove the effectiveness of the proposed method. © 2011 Elsevier B.V. All rights reserved.Ítem Parametric curve reconstruction from point clouds using minimization techniques(2013-01-01) Ruiz, O.E.; Cortés, C.; Aristizábal, M.; Acosta, D.A.; Vanegas, C.A.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAECurve reconstruction from noisy point samples is central to surface reconstruction and therefore to reverse engineering, medical imaging, etc. Although Piecewise Linear (PL) curve reconstruction plays an important role, smooth (C1-, C2-,?) curves are needed for many applications. In reconstruction of parametric curves from noisy point samples there remain unsolved issues such as (1) high computational expenses, (2) presence of artifacts and outlier curls, (3) erratic behavior of self-intersecting curves, and (4) erratic excursions at sharp corners. Some of these issues are related to non-Nyquist (i.e. sparse) samples. In response to these shortcomings, this article reports the minimization-based fitting of parametric curves for noisy point clouds. Our approach features: (a) Principal Component Analysis (PCA) pre-processing to obtain a topologically correct approximation of the sampled curve. (b) Numerical, instead of algebraic, calculation of roots in point-to-curve distances. (c) Penalties for curve excursions by using point cloud to - curve and curve to point cloud. (d) Objective functions which are economic to minimize. The implemented algorithms successfully deal with self - intersecting and / or non-Nyquist samples. Ongoing research includes self-tuning of the algorithms and decimation of the point cloud and the control polygon.Ítem Parametric curve reconstruction from point clouds using minimization techniques(2013-01-01) Ruiz, O.E.; Cortés, C.; Aristizábal, M.; Acosta, D.A.; Vanegas, C.A.; Universidad EAFIT. Departamento de Ingeniería de Procesos; Desarrollo y Diseño de ProcesosCurve reconstruction from noisy point samples is central to surface reconstruction and therefore to reverse engineering, medical imaging, etc. Although Piecewise Linear (PL) curve reconstruction plays an important role, smooth (C1-, C2-,?) curves are needed for many applications. In reconstruction of parametric curves from noisy point samples there remain unsolved issues such as (1) high computational expenses, (2) presence of artifacts and outlier curls, (3) erratic behavior of self-intersecting curves, and (4) erratic excursions at sharp corners. Some of these issues are related to non-Nyquist (i.e. sparse) samples. In response to these shortcomings, this article reports the minimization-based fitting of parametric curves for noisy point clouds. Our approach features: (a) Principal Component Analysis (PCA) pre-processing to obtain a topologically correct approximation of the sampled curve. (b) Numerical, instead of algebraic, calculation of roots in point-to-curve distances. (c) Penalties for curve excursions by using point cloud to - curve and curve to point cloud. (d) Objective functions which are economic to minimize. The implemented algorithms successfully deal with self - intersecting and / or non-Nyquist samples. Ongoing research includes self-tuning of the algorithms and decimation of the point cloud and the control polygon.Ítem Región de Inestabilidad y Optimización de las Condiciones de Producción de Metanol en un Reactor Lurgi(Centro de Informacion Tecnologica, 2016-01-01) Gómez, M.Á.; Dobrosz-Gómez, I.; Gilpavas, E.; Gómez, M.Á.; Dobrosz-Gómez, I.; Gilpavas, E.; Universidad EAFIT. Departamento de Ingeniería de Procesos; Procesos Ambientales (GIPAB)In the present work, the operational conditions for methanol synthesis in a Lurgi reactor are analyzed. The industrial data for a packed reactor (consisting of 1620 tubes of 7 m long) are the basis of this study. At first, the industrial reactor is simulated achieving excellent agreement with plant data. Then, the instability region is defined as a boundary in the conversion-temperature diagram and defines the conditions that must be avoided during reactor operation. The optimization of the operational conditions is performed based on the optimal temperature progression from the iso-reaction rate curves. Finally, it was found that the cooling fluid must be at 230 °C and that the heat transfer coefficient must guarantee a value of 118 J/(s.K.m2).Ítem Sensitivity analysis in optimized parametric curve fitting(EMERALD GROUP PUBLISHING LIMITED, 2015-03-02) Ruiz, Oscar E.; Cortes, Camilo; Acosta, Diego A.; Aristizabal, Mauricio; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEPurpose-Curve fitting from unordered noisy point samples is needed for surface reconstruction in many applications. In the literature, several approaches have been proposed to solve this problem. However, previous works lack formal characterization of the curve fitting problem and assessment on the effect of several parameters (i.e. scalars that remain constant in the optimization problem), such as control points number (m), curve degree (b), knot vector composition (U), norm degree (k ), and point sample size (r) on the optimized curve reconstruction measured by a penalty function ( f ). The paper aims to discuss these issues. Design/methodology/approach-A numerical sensitivity analysis of the effect of m, b, k and r on f and a characterization of the fitting procedure from the mathematical viewpoint are performed. Also, the spectral (frequency) analysis of the derivative of the angle of the fitted curve with respect to u as a means to detect spurious curls and peaks is explored. Findings-It is more effective to find optimum values for m than k or b in order to obtain good results because the topological faithfulness of the resulting curve strongly depends on m. Furthermore, when an exaggerate number of control points is used the resulting curve presents spurious curls and peaks. The authors were able to detect the presence of such spurious features with spectral analysis. Also, the authors found that the method for curve fitting is robust to significant decimation of the point sample. Research limitations/implications-The authors have addressed important voids of previous works in this field. The authors determined, among the curve fitting parameters m, b and k, which of them influenced the most the results and how. Also, the authors performed a characterization of the curve fitting problem from the optimization perspective. And finally, the authors devised a method to detect spurious features in the fitting curve. Practical implications-This paper provides a methodology to select the important tuning parameters in a formal manner. Originality/value-Up to the best of the knowledge, no previous work has been conducted in the formal mathematical evaluation of the sensitivity of the goodness of the curve fit with respect to different possible tuning parameters (curve degree, number of control points, norm degree, etc.). © Emerald Group Publishing Limited.Ítem Sensitivity analysis in optimized parametric curve fitting(EMERALD GROUP PUBLISHING LIMITED, 2015-03-02) Ruiz, Oscar E.; Cortes, Camilo; Acosta, Diego A.; Aristizabal, Mauricio; Universidad EAFIT. Departamento de Ingeniería de Procesos; Desarrollo y Diseño de ProcesosPurpose-Curve fitting from unordered noisy point samples is needed for surface reconstruction in many applications. In the literature, several approaches have been proposed to solve this problem. However, previous works lack formal characterization of the curve fitting problem and assessment on the effect of several parameters (i.e. scalars that remain constant in the optimization problem), such as control points number (m), curve degree (b), knot vector composition (U), norm degree (k ), and point sample size (r) on the optimized curve reconstruction measured by a penalty function ( f ). The paper aims to discuss these issues. Design/methodology/approach-A numerical sensitivity analysis of the effect of m, b, k and r on f and a characterization of the fitting procedure from the mathematical viewpoint are performed. Also, the spectral (frequency) analysis of the derivative of the angle of the fitted curve with respect to u as a means to detect spurious curls and peaks is explored. Findings-It is more effective to find optimum values for m than k or b in order to obtain good results because the topological faithfulness of the resulting curve strongly depends on m. Furthermore, when an exaggerate number of control points is used the resulting curve presents spurious curls and peaks. The authors were able to detect the presence of such spurious features with spectral analysis. Also, the authors found that the method for curve fitting is robust to significant decimation of the point sample. Research limitations/implications-The authors have addressed important voids of previous works in this field. The authors determined, among the curve fitting parameters m, b and k, which of them influenced the most the results and how. Also, the authors performed a characterization of the curve fitting problem from the optimization perspective. And finally, the authors devised a method to detect spurious features in the fitting curve. Practical implications-This paper provides a methodology to select the important tuning parameters in a formal manner. Originality/value-Up to the best of the knowledge, no previous work has been conducted in the formal mathematical evaluation of the sensitivity of the goodness of the curve fit with respect to different possible tuning parameters (curve degree, number of control points, norm degree, etc.). © Emerald Group Publishing Limited.Ítem Sensitivity analysis in optimized parametric curve fitting(Emerald Group Publishing, 2015) Ruíz, Óscar E.; Cortés, Camilo; Acosta, Diego A.; Aristizábal, Mauricio; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEPurpose – Curve fitting from unordered noisy point samples is needed for surface reconstruction in many applications -- In the literature, several approaches have been proposed to solve this problem -- However, previous works lack formal characterization of the curve fitting problem and assessment on the effect of several parameters (i.e. scalars that remain constant in the optimization problem), such as control points number (m), curve degree (b), knot vector composition (U), norm degree (k), and point sample size (r) on the optimized curve reconstruction measured by a penalty function (f) -- The paper aims to discuss these issues -- Design/methodology/approach - A numerical sensitivity analysis of the effect of m, b, k and r on f and a characterization of the fitting procedure from the mathematical viewpoint are performed -- Also, the spectral (frequency) analysis of the derivative of the angle of the fitted curve with respect to u as a means to detect spurious curls and peaks is explored -- Findings - It is more effective to find optimum values for m than k or b in order to obtain good results because the topological faithfulness of the resulting curve strongly depends on m -- Furthermore, when an exaggerate number of control points is used the resulting curve presents spurious curls and peaks -- The authors were able to detect the presence of such spurious features with spectral analysis -- Also, the authors found that the method for curve fitting is robust to significant decimation of the point sample -- Research limitations/implications - The authors have addressed important voids of previous works in this field -- The authors determined, among the curve fitting parameters m, b and k, which of them influenced the most the results and how -- Also, the authors performed a characterization of the curve fitting problem from the optimization perspective -- And finally, the authors devised a method to detect spurious features in the fitting curve -- Practical implications – This paper provides a methodology to select the important tuning parameters in a formal manner -- Originality/value - Up to the best of the knowledge, no previous work has been conducted in the formal mathematical evaluation of the sensitivity of the goodness of the curve fit with respect to different possible tuning parameters (curve degree, number of control points, norm degree, etc.)Ítem Sensitivity analysis of optimized curve fitting to uniform-noise point samples(2012-05) Ruíz, Óscar; Cortes, Camilo; Acosta, Diego; Aristizábal, Mauricio; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAECurve reconstruction from noisy point samples is needed for surface reconstruction in many applications (e.g. medical imaging, reverse engineering,etc.) -- Because of the sampling noise, curve reconstruction is conducted by minimizing the fitting error (f), for several degrees of continuity (usually C0, C1 and C2) -- Previous works involving smooth curves lack the formal assessment of the effect on optimized curve reconstruction of several inputs such as number of control points (m), degree of the parametric curve (p), composition of the knot vector (U), and degree of the norm (k) to calculate the penalty function (f) -- In response to these voids, this article presents a sensitivity analysis of the effect of mand k on f -- We found that the geometric goodness of the fitting (f) is much more sensitive to m than to k -- Likewise, the topological faithfulness on the curve fit is strongly dependent on m -- When an exaggerate number of control points is used, the resulting curve presents spurious loops, curls and peaks, not present in the input data -- We introduce in this article the spectral (frequency) analysis of the derivative of the curve fit as a means to reject fitted curves with spurious curls and peaks -- Large spikes in the derivative signal resemble Kronecker or Dirac Delta functions, which flatten the frequency content adinfinitum -- Ongoing work includes the assessment of the effect of curve degree p on f for non-Nyquist point samplesÍtem Statistical Assessment of Global and Local Cylinder Wear(IEEE, 2007-06) Ruíz, Óscar; Vanegas, Carlos; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEAssessment of cylindricity has been traditionally performed on the basis of cylindrical crowns containing a set of points that are supposed to belong to a controlled cylinder – As such, all sampled points must lie within a crown. In contrast, the present paper analyzes the cylindricity for wear applications, in which a statistical trend is assessed, rather than to assure that all points fall within a given tolerance -- Principal Component Analysis is used to identify the central axis of the sampled cylinder, allowing to find the actual (expected value of the) radius and axis of the cylinder -- Application of k-cluster and transitive closure algorithms allow to identify particular areas of the cylinder which are specially deformed -- For both, the local areas and the global cylinder, a quantile analysis allows to numerically grade the degree of deformation of the cylinder -- The algorithms implemented are part of the CYLWEAR system and used to assess local and global wear cylinders