Method and program for estimating uncertainty

Data processing: measuring – calibrating – or testing – Measurement system – Statistical measurement

Reexamination Certificate

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C702S180000, C702S181000, C702S182000, C702S183000, C702S184000, C702S185000, C702S186000, C702S187000, C702S188000, C702S189000, C702S196000

Reexamination Certificate

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11325135

ABSTRACT:
Measured values obtained in a measuring machine to be estimated are provided to estimate errors in the measured values. Based on the estimated errors in the measured values, a covariance matrix or correlation matrix of measured values is derived. The covariance matrix or correlation matrix is then subjected to eigenvalue decomposition to derive eigenvalues and eigenvectors. A normal random number with an expected value of 0 and a variance equal to an eigenvalue corresponding to the eigenvalue is generated as a coefficient of coupling for each eigenvector, and all eigenvectors are linearly coupled to generate pseudo-measured values of the measuring machine. The generated pseudo-measured values are subjected to statistic processing to estimate uncertainty of the measuring machine.

REFERENCES:
patent: 6829568 (2004-12-01), Julier et al.
patent: 198 46 597 (1999-04-01), None
“Traceability of Coordinate Measurements According to the Method of the Virtual Measuring Machine”, Part 2 of the Final Report Project MATI-CT94-0076, E. Trapet et al., PTB-F-35, Braunschweig, Mar. 1999.
“Reliability on calibration of CMM”, Abbe M et al., Measurement, Institute of Measurement and Control, London, GB, vol. 33, No. 4, Jun. 2003, pp. 359-368, XP004423860, ISSN: 0263-2241.
“Statistical verification of conformance to geometric tolerance”, Kurfess T R et al, Computer Aided Design, Elsevier Publishers BV., Barking, GB, vol. 27, No. 5, May 1995, pp. 353-361, XP004022789, ISSN: 00010-4485.

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