Coordinate measurement uncertainty: Models and standards

Płowucha, Wojciech; Jakubiec, Władysław

doi:10.1515/teme-2014-0031

Cited by 6 publications

(3 citation statements)

References 4 publications

(5 reference statements)

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“…1) using gauge blocks and fixing holes in the CMM table. This minimizes errors due to the work piece orientation and location in the CMM measuring volume as shown in [12].…”

Section: Methods For Symmetry Checkmentioning

confidence: 99%

Methods for Checking the Symmetry of the Formula One Car Nose

Neamțu

Bere

2014

AMM

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Checking the symmetry of a Formula One (F1) car nose requires the measurement and inspection of complex surfaces and raises a number of challenges both in terms of the equipment used and the measurement strategy. Verifying the symmetry allows the identification of the asymmetrical areas regarding the critical aerodynamic elements of F1 car nose. This paper presents three methods to check the symmetry of a F1 car nose and to determine the deviation using symmetry points (by points measuring) in plane using 2D scanned profiles and 3D laser scanned surfaces. In order to acquire the symmetry points, and to scan the profiles and the surfaces, a state of the art multi-sensor CMM (Coordinated Measuring Machine) has been used and the data has been processed in CATIA V5.

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“…1) using gauge blocks and fixing holes in the CMM table. This minimizes errors due to the work piece orientation and location in the CMM measuring volume as shown in [12].…”

Section: Methods For Symmetry Checkmentioning

confidence: 99%

Methods for Checking the Symmetry of the Formula One Car Nose

Neamțu

Bere

2014

AMM

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“…Uncertainty estimation for measuring systems is still a challenging task [1][2][3][4]. Among the developed solutions, simulation methods show significant promise, since they are designed to shorten the length of the quality control process and enable automated evaluation of measurement uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Simulation model for uncertainty estimation of measurements performed on five-axis measuring systems

Gąska

Sładek

et al. 2019

Int J Adv Manuf Technol

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Five-axis measuring systems (i.e. coordinate measuring machines equipped with articulated probe heads capable of continuous indexation or five-axis machine tools with inspection probe mounted on a tilt and swivel head) are becoming more and more popular, especially in industrial applications, since their usage speeds up the measurement process without significant loss in accuracy. Widespread adoption of these systems necessitates development of viable and easy-to-use measurement uncertainty estimation methods. This paper describes the experiments required for identification of errors of five-axis measuring systems based on usage of LasrTracer system and measurements of ring standard. It also expounds the methodology for implementation of virtual CMM-based simulation model for these systems giving the explanation on all input quantities used in the model along with detailed mathematical explanations on uncertainty propagation procedure. Eventually, it presents the validation methodology and the results of validation measurements performed in order to prove the correct functioning of developed model. Basing on these results, the main conclusion drawn in the paper is that presented virtual model should be regarded as working properly and producing metrologically correct values of measurement uncertainty for common metrological tasks known from GD&T framework.

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“…Estimation of uncertainty of coordinate measurements is a very complex task due to the diversity of measured characteristics, strategies, and measurement methods. Therefore, the analytical estimation of uncertainty of coordinate measurements should be supported by specialist software [6].…”

Section: Introductionmentioning

confidence: 99%

Alternative Methods for Estimating Plane Parameters Based on a Point Cloud

Stryczek

2017

Measurement Science Review

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Non-contact measurement techniques carried out using triangulation optical sensors are increasingly popular in measurements with the use of industrial robots directly on production lines. The result of such measurements is often a cloud of measurement points that is characterized by considerable measuring noise, presence of a number of points that differ from the reference model, and excessive errors that must be eliminated from the analysis. To obtain vector information points contained in the cloud that describe reference models, the data obtained during a measurement should be subjected to appropriate processing operations. The present paperwork presents an analysis of suitability of methods known as RANdom Sample Consensus (RANSAC), Monte Carlo Method (MCM), and Particle Swarm Optimization (PSO) for the extraction of the reference model. The effectiveness of the tested methods is illustrated by examples of measurement of the height of an object and the angle of a plane, which were made on the basis of experiments carried out at workshop conditions.

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Coordinate measurement uncertainty: Models and standards

Cited by 6 publications

References 4 publications

Methods for Checking the Symmetry of the Formula One Car Nose

Methods for Checking the Symmetry of the Formula One Car Nose

Simulation model for uncertainty estimation of measurements performed on five-axis measuring systems

Alternative Methods for Estimating Plane Parameters Based on a Point Cloud

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