6533b7d5fe1ef96bd12646d3
RESEARCH PRODUCT
Using of a uncertainty model of an polyarticulated coordinates measuring arm to validate the measurement in a manufacturing processsus
Patrick JuillionJean François FontaineFrançois HennebelleRichard CoquetFekria Romdhanisubject
[ SPI.MECA.GEME ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]0209 industrial biotechnologyEngineeringMonte Carlo method02 engineering and technologyMetrology01 natural sciences010309 opticsCMA Modelling020901 industrial engineering & automationOperator (computer programming)Control theory0103 physical sciencesCalibration[SPI.MECA.GEME] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]SimulationGeneral Environmental Sciencebusiness.industryProcess (computing)UncertaintyCovarianceMetrology[SPI.MECA.GEME]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]NoiseGeneral Earth and Planetary SciencesbusinessEncoderMonte Carlo Methoddescription
International audience; Coordinates Measuring Arms (CMA) are increasingly used to control industrial parts and are often an alternative to CMM controls that require conditions of laboratory measurement and involve significant costs. However, the control of uncertainties is often not guaranteed because the measurement process is complex and there is no standard for setting a framework qualification process of the measurement process.The proposed study, in this paper, is a first approach to model the measurement uncertainties of a CMA with contact sensor. The problem is complex because there are many sources of uncertainty, largely due to variability in the handling carried out by the operator.A model, based on Denavit-Hartenberg description, has been developed taking into account the measurement conditions (i.e.: the influence not only of the temperature, of the encoder error, of the deformation of different parts of the arm, of the noise of external vibrations, but also of the calibration parameters). The Monte Carlo method is used to estimate the uncertainties obtained. This method allows to take into account of the covariance when factors cannot be considered independent.The resulting model was validated for the measurement of the location of different points of the working space of an CMA Sigma 2025 (ROMER®), then for the measurement of an industrial part in comparison with a measurement carried using a CMM
year | journal | country | edition | language |
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2014-07-23 |