Digital Twin of an Optical Measurement System

Vlaeyen, Michiel; Haitjema, Han; Dewulf, Wim

doi:10.3390/s21196638

Cited by 21 publications

(17 citation statements)

References 20 publications

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“…The considered uncertainty contributors in this virtual CMM are the geometrical error contributors, i.e. scale errors, misalignment and straightness errors of the guideways [14]. In total 21 geometric errors, i.e.…”

Section: Cmm Digital Twinmentioning

confidence: 99%

“…The random error is characterized by a normal distribution with zero mean and a standard deviation of 0.5 µm. The values for the parameters of the geometric errors can be found in [14]. By generating multiple measurements, with different random parameters for each measurement, the distribution of the measurement uncertainty on the tactile measurement of the reference object is determined.…”

Section: Cmm Digital Twinmentioning

confidence: 99%

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Geometric qualification for robot CT with flexible trajectories

Kang¹,

Probst²,

Vlaeyen³

et al. 2022

eJNDT

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Robot CT systems bring great flexibility to X-ray CT based inspection scans. The system geometry needs to be well calibrated in order to avoid serious artifacts in the reconstructed volume. However, conventional calibration methods are normally designed for circular paths, which may be insufficient for a robot CT system. This paper proposes a phantom based geometric qualification method which supports nearly any view points. This is achieved by automatically mapping 3D-2D features based on collinear markers. The position and orientation of the X-ray focal spot and the detector are determined for each image of the reference phantom. This can be used for the CT reconstructions of later scans with the same trajectory. It is also possible to use the acquired geometries parameters to calibrate the underlying robots. The approach is validated on experimentally acquired data and the uncertainty is estimated by a Monte-Carlo based method.

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Section: Cmm Digital Twinmentioning

confidence: 99%

Section: Cmm Digital Twinmentioning

confidence: 99%

Geometric qualification for robot CT with flexible trajectories

Kang¹,

Probst²,

Vlaeyen³

et al. 2022

eJNDT

View full text Add to dashboard Cite

show abstract

“…These technologies let organizations develop virtual representations of physical products, processes, or services using real-time data, mockups, algorithms, and AI. These technologies often cost less than physical prototypes, allowing companies to produce and test an infinite number of variations [25][26][27]. The qualitative difference between Virtual Instruments and Digital Twins is shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

Digital Avatar of Metrology

Rab

Wan

Sharma

et al. 2023

MAPAN

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In the present paper, the digital transformation in metrology is discussed, which is revolutionizing the world and is one of the most interesting developments in science & technology today. The study also discusses, how current technologies like Artificial Intelligence, the Internet of Things, Cloud computing, and more significantly digital twins would become synonymous with digital metrology, thus bolstering the future of manufacturing industries. The basic objective of any digital transformation initiative is to enhance the current processes, while each one will have its own unique set of objectives. As metrology is considered as the main pillar of Quality Infrastructure (QI), the digital transformation of metrology requires a holistic approach for all stakeholders working within the advanced QI of a country or economy.

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“…A virtual instrument (VI) can be part of this model or even comprise the model completely. In several publications [2][3][4][5], the concept of simulating the measurement instrument and using a Monte Carlo approach to calculate the uncertainty associated with an estimate of the measurand is proposed, and it continues to be a lively area of research [6][7][8]. In this process, all uncertain model parameters are randomly varied by sampling parameter values from appropriate probability distributions and, subsequently, the mathematical model is evaluated.…”

Section: Introductionmentioning

confidence: 99%

Impact of Imperfect Artefacts and the Modus Operandi on Uncertainty Quantification Using Virtual Instruments

2022

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The usage of virtual instruments (VIs) to analyze measurements and calculate uncertainties is increasing. Well-known examples are virtual coordinate measurement machines (VCMMs) which are often used and even commercially offered to assess measurement uncertainties of CMMs. A more recent usage of the VI concept is posed by the modeling of scatterometers. These VIs can be used to assess the measurement uncertainty after the measurement has been performed based on the real measurement data or prior to the measurement to predict the measurement uncertainty using a type of simulated measurement data. The research question addressed in this paper is to assess if this predicted uncertainty will be similar in magnitude to the calculated uncertainty based on the measurement data. It turns out that this is not necessarily the case. The main observation of this paper was that the uncertainty predicted by a VI can be highly sensitive to the chosen way of operating the VI. To amend this situation, a simple procedure was proposed that can be used prior to performing the real measurement and that is believed to produce a conservative prediction of the measurement uncertainty in most cases. This was verified in a case study involving the measurement of the asphericity of an imperfect sphere using a CMM, with the uncertainty calculated by means of a VCMM.

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Digital Twin of an Optical Measurement System

Cited by 21 publications

References 20 publications

Geometric qualification for robot CT with flexible trajectories

Geometric qualification for robot CT with flexible trajectories

Digital Avatar of Metrology

Impact of Imperfect Artefacts and the Modus Operandi on Uncertainty Quantification Using Virtual Instruments

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