6533b851fe1ef96bd12a97a9
RESEARCH PRODUCT
Methodology for assessment of measuring uncertainties of articulated arm coordinates measuring machine
Richard CoquetMin GeJean François FontaineFrançois HennebelleFekria RomdhaniPatrick Juillionsubject
[ SPI.MECA.GEME ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]0209 industrial biotechnologyComputer scienceApplied MathematicsMonte Carlo methodWork (physics)Uncertainty[PHYS.MECA.GEME]Physics [physics]/Mechanics [physics]/Mechanical engineering [physics.class-ph]Monte Carlo SimulationControl engineering02 engineering and technologyCoordinate-measuring machineArticulated Arm Coordinate Measuring Machine01 natural sciencesExpression (mathematics)[SPI.MECA.GEME]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]010309 optics020901 industrial engineering & automation0103 physical sciences[ PHYS.MECA.GEME ] Physics [physics]/Mechanics [physics]/Mechanical engineering [physics.class-ph]CalibrationMeasurement uncertaintyPoint (geometry)InstrumentationEngineering (miscellaneous)description
International audience; The Articulated Arm Coordinate Measuring Machines (AACMM) have gradually evolved and are increasingly used in mechanic industry. At present, measurement uncertainties relating to the use of these devices are not yet well-quantified. The work carried out consists on determining the measurement uncertainties of a mechanical part by an Articulated Arm Coordinate Measuring Machine. The studies aiming to develop a model of measurement uncertainties are based on the Monte Carlo method developed in Supplement 1 of the Guide to Expression of Uncertainty in Measurement [1] but also identifying and characterizing the main sources of uncertainty. A Multi-level Monte Carlo approach principle has been developed which allows characterizing the possible evolution of the Articulated Arm CMM during the measurement and quantifying in a second level the uncertainty on the considered measurand. The first Monte Carlo level is the most complex and is thus divided into 3 sub-levels, namely characterization on positioning error of a point, estimation of calibration errors and evaluation of fluctuations of the “localization point”. The global method is thus presented and results of the first sub-level are particularly developed. The main sources of uncertainty, including AACMM deformations are exposed.
year | journal | country | edition | language |
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2014-11-14 |