Intelligent sampling for the measurement of structured surfaces

Wang, Jian; Jiang, Xiangqian; Blunt, Liam; Leach, Richard; Scott, Paul J.

doi:10.1088/0957-0233/23/8/085006

Cited by 49 publications

(38 citation statements)

References 36 publications

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“…The analysed adaptive sampling is the triangular patch sampling since it has achieved good reconstruction performances in Wang et al (2012) and Shih et al (2008). The reconstruction is performed through the piecewise cubic interpolation implemented in the fit function of MATLAB ® (2014).…”

Section: Reconstruction Resultsmentioning

confidence: 99%

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Curvature based sampling of curves and surfaces

Pagani

Scott

2018

Computer Aided Geometric Design

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Efficient sampling methods enable the reconstruction of a generic surface with a limited amount of points. The reconstructed surface can therefore be used for inspection purpose. In this paper a sampling method that enables the reconstruction of a curve or surface is proposed. The input of the proposed algorithm is the number of required samples. The method takes into account two factors: the regularity of the sampling and the complexity of the object. A higher density of samples is assigned where there are some significant features, described by the curvature. The analysed curves and surfaces are described through the B-splines spaces. The sampling of surfaces generated by two or more curves is also discussed.

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Section: Reconstruction Resultsmentioning

confidence: 99%

“…A review of intelligent sampling techniques can be found in Wang et al (2012). Among the reviewed techniques, two adaptive sampling methods have been analysed: triangle and rectangle patch adaptive subdivision.…”

Section: Introductionmentioning

confidence: 99%

Curvature based sampling of curves and surfaces

Pagani

Scott

2018

Computer Aided Geometric Design

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“…Moreover, many filtering and decomposition algorithms for freeform surfaces that are represented by triangular meshes were proposed. Those algorithms use different principles such as partial differential equations, lifting wavelets, mesh relaxation schemes, morphological operations and manifold harmonics, to filter any freeform surface or decompose it into its different scales and components [4][5][6][7][8][9][10]. The work carried out in this paper continues the previous work by investigating the two remaining blocks in figure 1, i.e., the texture representation and the parameter calculation.…”

Section: Introductionmentioning

confidence: 88%

“…Consequently, surface texture characterisation has witnessed important shifts in the last decade or two; from profile measurements to areal measurements and from simple surfaces to complex freeform surfaces [1][2][3]. These shifts have triggered the need for new algorithms and techniques that can better describe, represent, measure and characterise the newly evolved complex freeform surfaces [4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Freeform texture representation and characterisation based on triangular mesh projection techniques

et al. 2016

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Freeform texture representation and characterisation based on triangular mesh projection techniques, Measurement (2016), doi: http://dx. AbstractTexture characterisation for freeform non-Euclidean surfaces is becoming increasingly important due to the widespread of the use of such surfaces in different applications, e.g. the additive manufacturing. Four main steps are required to analyse and characterise those surfaces which include new surface representation, surface filtration and decomposition, texture representation methods and finally the calculation of the surface parameters. Recently, the representation, as well as the filtration and decomposition, of freeform surfaces have been investigated and some algorithms have been proposed. This paper, however, shed the light on how to represent the texture of freeform non-Euclidean surfaces before calculating the parameters. A novel model for freeform surface parameterisation is introduced; this new model proposes the use of a projection algorithm before the actual calculation of the parameters. Different projection algorithms have been adopted from the mesh projection techniques found in the field of computer graphics. The results of applying those algorithms to represent the texture of both simulated and bio-engineering surfaces are shown, also a comparison between those algorithms has been carried out. Furthermore, examples of calculating some of the surface parameters for freeform surfaces are given.

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“…Ref. [32] has made a summary about surface measurement, among which the probing points by uniform equidistant distribution in terms of the arc length is one of the most widely used method. Certainly, increasing the sample size can also reduce the uncertainty of an approximation model.…”

Section: 4mentioning

confidence: 99%

Efficient measurement of aero-engine blade considering uncertainties in adaptive machining

Zhang

Chen

Tao

2015

Int J Adv Manuf Technol

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Blade geometry plays an extremely important role in the aerodynamic performance of aero-engine. However, in the adaptive machining process of a near-net-shape blade, it is important for an application engineer to reconstruct an actual profile with high-precision measurement data in a short time. This paper presents an efficient measurement to meet the requirement for digital information in the adaptive machining, which is also intimately associated with the previous work in reconstruction (Zhang et al. in Int J Adv Manuf Technol 2015:1-16, 2015. Comparing with conventional measurement, the proposed method can not only improve the utilization of measurement data from multi-sensor system but also consider the uncertainties of measurement and localization in data merging. Concretely speaking, the low-precision data from non-contact measurement device is used for establishing possible substitute models. The modified Bayesian information (Modi_BIC) criterion based on Bayesian statistics is introduced as the principle to select the model structure. In order to reduce misalignment errors of the selected substitute model, the statistical analysis of Fisher information matrix is applied to determine registration points. Based on this, the uncertainties can be given in the form of variation boundaries. Comparisons with the specified tolerance band determine a set of re-measured points by using a contact measurement device. The high-precision data can be merged with the selected substitute model by means of free form deformation (FFD) technique. The final measurement data is provided in the form of skinning surface that is consistent to the reverse modeling methodology of aero-engine blade. Moreover, some practical examples are given to demonstrate the effectiveness and superiority of the proposed method.

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Intelligent sampling for the measurement of structured surfaces

Cited by 49 publications

References 36 publications

Curvature based sampling of curves and surfaces

Curvature based sampling of curves and surfaces

Freeform texture representation and characterisation based on triangular mesh projection techniques

Efficient measurement of aero-engine blade considering uncertainties in adaptive machining

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