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Uncertainty Calculation of Roundness Assessment by Automatic Differentiation in Coordinate Metrology

Jia-chun LIN(林家春)1, Michael Krystek2, Zhao-yao SHI(石照耀)1

 

1. College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100124, China;2. Physikalisch-Technische Bundesanstalt, Braunschweig D-38116, Germany


 Abstract-Recently, Coordinate Measuring Machines (CMMs ) are widely used to measure roundness errors. Roundness is calculated from a la rge number of points collected from the profiles of the parts. According to the  Guide to the Expression of Uncertainty in Measurement (GUM), all measurement res ults must have a stated uncertainty associated the them. However, no CMMs give t he uncertainty value of the roundness, because no suitable measurement uncertain ty calculation procedure exists. In the case of roundness measurement in coordin ate metrology, this paper suggests the algorithms for the calculation of the mea surement uncertainty of the roundness deviation based on the two mainly used ass ociation criteria, LSC and MZC. The calculation of the sensitivity coefficients  for the uncertainty calculation can be done by automatic differentiation, in ord er to avoid introducing additional errors by the traditional difference quotient  approximations. The proposed methods are exact and need input data only as the  measured coordinates of the data points and their associated uncertainties.

 

 Key words-measurement uncertainty; roundness; automatic  diferentiation

 


Manuscript Number: 1674-8042(2010)03-0224-04

 


dio: 10.3969/j.issn.1674-8042.2010.03.05

 

 

References

 

[1]ISO 1101, 2004. Geometrical Product Specifications (GPS). Geometrica l tolerancing. Tolerances of form, orientation, location and run-out, ISO, Gene va.

[2]GB/T 7234-2004, 2004. Geometrical Product Specifications(GPS). Meas urement of roundness. Terms, definitions and parameters of roundness, SAC, Beiji ng.

[3]ISO 1993, 1993. Guide to the Expression of Uncertainty in Measuremen t, ISO, Geneva.

[4]Michael Krystek, Zhao-yao Shi, Jia-chun Lin, 2010. Least squares a ssociation of geometrical features by automatic differentiation. Key Engineering  Materials, 437, p. 222-226.

[5]T. J. Rivlin, 1979. Approximation by circles. Computing, 21, p. 93- 104.

[6]M. de Berg, M. van Kreveld, M. Overmars, O. Schwarzkopf, 1998. Comp utational Geometry. Springer, Berlin.

[7]L. B. Rall, 1981. Automatic Differentiation. Techniques and Applicat ions. Springer, Berlin.

[8]A. Griewank, 2000. Evaluating Derivatives. Principles and Techniques  of Algorithmic Differentiation. SIAM, Philadelphia.
 

 

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