Patch and curvature specific estimation of efficient sampling scheme for complex surface inspection

Abdulhameed, Osama; Mian, Syed Hammad; Al-Ahmari, Abdulrahman; Alkhalefah, Hisham

doi:10.1007/s00170-020-06063-6

Cited by 12 publications

(3 citation statements)

References 40 publications

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“…Using the best-fit alignment, the implant-cranium reconstruction model was positioned relative to the mirrored cranium model ( Figure 11 b). The best-fit alignment of the test and reference surfaces ensures that all components are placed in the same coordinate system [ 39 ]. It suggests that the test surface should overlay its idealized counterpart as close as feasible.…”

Section: Methodsmentioning

confidence: 99%

Design, Analysis, and 3D Printing of a Patient-Specific Polyetheretherketone Implant for the Reconstruction of Zygomatic Deformities

et al. 2023

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The reconstruction of craniomaxillofacial deformities, especially zygomatic bone repair, can be exigent due to the complex anatomical structure and the sensitivity of the crucial organs involved. The need to reconstruct the zygomatic bone in the most precise way is of crucial importance for enhancing the patient outcomes and health care-related quality of life (HRQL). Autogenous bone grafts, despite being the gold standard, do not match bone forms, have limited donor sites and bone volume, and can induce substantial surgical site morbidity, which may lead to adverse outcomes. The goal of this study is to provide an integrated approach that includes various processes, from patient scanning to implant manufacture, for the restoration of zygomatic bone abnormalities utilizing Polyetheretherketone (PEEK) material, while retaining adequate aesthetic and facial symmetry. This study takes an integrated approach, including computer-aided implant design using the mirror reconstruction technique, investigating the biomechanical behavior of the implant under loading conditions, and carrying out a fitting accuracy analysis of the PEEK implant fabricated using state-of-the-art additive manufacturing technology. The findings of the biomechanical analysis results reveal the largest stress of approximately 0.89 MPa, which is relatively low in contrast to the material’s yield strength and tensile strength. A high degree of sturdiness in the implant design is provided by the maximum value of strain and deformation, which is also relatively low at roughly 2.2 × 10−4 and 14 µm. This emphasizes the implant’s capability for load resistance and safety under heavy loading. The 3D-printed PEEK implant observed a maximum deviation of 0.4810 mm in the outside direction, suggesting that the aesthetic result or the fitting precision is adequate. The 3D-printed PEEK implant has the potential to supplant the zygoma bone in cases of severe zygomatic reconstructive deformities, while improving the fit, stability, and strength of the implant.

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Section: Methodsmentioning

confidence: 99%

Design, Analysis, and 3D Printing of a Patient-Specific Polyetheretherketone Implant for the Reconstruction of Zygomatic Deformities

et al. 2023

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“…Kim [13] et al compared the above four planning methods on a three-coordinate measuring machine, and found that the optimal sampling point planning is related to the priority coefficient and sample size. Syed [14] et al segmented and graded the surface according to the curvature, and respectively used Hammersley, Poisson point distribution method and UDM to plan the sampling points, and found that the UDM has the largest fitting error. The blind sampling method is simple to implement and has good versatility, but because the shape complexity of the surface is not considered, the sampling points cannot be adaptively distributed according to the complexity of the surface, and the sampling points may be redundant [15].…”

Section: A Blind Sampling Methodsmentioning

confidence: 99%

Sampling Point Planning for Complex Surface Inspection based on Feature Points under Area Division

Sun¹,

Xiang

Zhou³

et al. 2022

Preprint

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Traditional sampling point planning methods usually apply the same sampling strategy to all areas of the complex surface. It is very likely to miss the extreme points in areas with large curvature changes, which leads to low fitting accuracy. This paper proposes a new sampling method for complex surfaces based on feature points under area division. First, the curvature characteristics of the complex surface is analyzed, and the complex surface is divided into flat and sharply-edged areas. Then, for the flat areas the uniform distribution method is used, and for the sharply-edged areas, the feature points are defined and searched, and the curvature adaptive planning method based on the feature points is adopted. Finally, the repeated and redundant points are optimized and adjusted. The experimental verification results show that compared with four traditional sampling methods, the maximum and mean fitting errors of the proposed method are significantly reduced and the measuring accuracy is efficiently improved.

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“…The geometry-guided sampling methods usually analyze geometrical features, such as knot vectors, curvature, arclength, and inflection points, and combine multiple factors by conferring different weights. These methods enable the inspection points to reach the characteristic distribution [2,3,[7][8][9][10]. The error-guided sampling methods analyze the machine error, reconstruction error, reconstruction uncertainty, and other errors and utilize the error analysis results to determine critical points.…”

Section: Introductionmentioning

confidence: 99%

Efficient Adaptive Sampling Methods Based on Deviation Analysis of Piecewise Cubic Spline Interpolation

Cheng¹,

zeng²,

Jiang³

et al. 2021

Preprint

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The on-machine inspection technique requires a certain manufacturing time, so it is important for a sampling approach to achieve high precision for a fixed number of inspection points. This study designs an efficient adaptive sampling method for the non-uniform rational basis spline (NURBS) curves and surfaces based on deviation analysis. For the free-form curves, it is an iterative method that is used to remove points that are less significant to the reconstruction error from the dense points on the curve. That is, the points are ranked by their maximum deviation from the theoretical curves. Different from the existing methods, a closed-form is derived to approximate the maximum deviation by analyzing the curve reconstruction method, i.e., piecewise cubic spline interpolation. The proposed method is compared with recent curve sampling methods, and the comparison results have shown that, under the same number of inspection points, the reconstruction error of the proposed method is reduced by 82%. The proposed curve sampling algorithm is then further extended to surface sampling, where the global characteristics of a surface are extracted as a series of curves on the surface. Thus, surface sampling is simplified to curve sampling in two directions. The proposed surface sampling strategy is compared with classic surface sampling methods using three representative surfaces. The results show that by using the proposed surface sampling strategy, the reconstruction error is reduced significantly. By applying our sampling method to the on-machine inspection system, the inspection accuracy can be greatly improved.

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Patch and curvature specific estimation of efficient sampling scheme for complex surface inspection

Cited by 12 publications

References 40 publications

Design, Analysis, and 3D Printing of a Patient-Specific Polyetheretherketone Implant for the Reconstruction of Zygomatic Deformities

Design, Analysis, and 3D Printing of a Patient-Specific Polyetheretherketone Implant for the Reconstruction of Zygomatic Deformities

Sampling Point Planning for Complex Surface Inspection based on Feature Points under Area Division

Efficient Adaptive Sampling Methods Based on Deviation Analysis of Piecewise Cubic Spline Interpolation

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