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Analytic Standard Uncertainty Evaluation (ASUE)


Analytical Standard Uncertainty Evaluation (ASUE) is systematic framework for the analytical standard measurement uncertainty evaluation of non-linear systems. This work is an extension of the Guide to the Expression of Uncertainty in Measurement (GUM) analytical method. The GUM provides systematic frameworks for analytic linear approximation and Monte Carlo simulation techniques, but does not present any framework for an analytic non-linear solution. The framework allows practitioners to arrive at an accurate analytic solution that describes the output uncertainties with respect to the input measurement uncertainties for most multivariate system. The ASUE framework provides the solution to some of the problems highlighted in latest GUM Anniversary Special Issue on 4th August 2014. This solution is shown to be valid and valuable for a wider community of engineers that rely on the GUM documentation to qualify their system or design. It is the first step towards simplifying and standardizing the GUM analytical method for non-linear systems. The figures below compares some of the results obtained from GUM uncertainty framework, Monte Carlo analysis and ASUE framework.


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The ASUE team therefore simplifies the standard measurement uncertainty evaluation by presenting the ASUE toolbox below. This toolbox is powered by Mathematica which is deployed using webMathematica.The framework for the ASUE toolbox has been published in Measurement, a journal by International Measurement Confederation (IMEKO). Hence the best citation for using ASUE toolbox is:

  • Y. C. Kuang, A. Rajan, M. P.-L. Ooi, and T. C. Ong, "Standard uncertainty evaluation of multivariate polynomial," Measurement, vol. 58, pp. 483-494, Dec. 2014

  • This ASUE webpage is supported by:

  • Monash University
  • Wolfram Mathematica and webMathematica
  • IEEE Instrumentation and Measurement Society, Technical Committee 32 - Fault Tolerance Measurement Systems

  • Please send any bug reports or questions by emailing us.



    ASUE Toolbox


    Note: The variables must be independent to each other and uncertainty is given in u^2[y]

    GUIDE
    VARIABLE SYMMETRY DISTRIBUTION LOCATION PARAMETER SCALE PARAMETER SHAPE PARAMETER
    x1 m1 s1
    x2 m2 s2
    ADD ROW DELETE ROW
    ENTER POLYNOMIAL (e.g. y = x1^2+x2^2): y =
    ASUE UNCERTAINTY u^2[y] GUM UNCERTAINTY u^2[y] 3RD ORDER MOMENT 4TH ORDER MOMENT

     
     

    Disclaimer

    Monash University School of Engineering provides the ASUE toolbox above "as is" and you use the software at your own risk. The ASUE webpage is a nonprofit webpage and solely for research purposes. Monash University make no warranties as to performance, merchantability, fitness for a particular purpose, or any other warranties whether expressed or implied. No oral or written communication from or information provided by Monash University shall create a warranty. Under no circumstances shall Monash University be liable for direct, indirect, special, incidental, or consequential damages resulting from the use, misuse, or inability to use this ASUE toolbox, even if Monash University has been advised of the possibility of such damages.


    ASUE Team


    Arvind Rajan

    Monash University Scholar
    Electrical and Computer Systems Engineering
    arvind.rajan@monash.edu

     

    Dr Kuang Ye Chow

    Associate Head of Research Training
    Electrical and Computer Systems Engineering
    Monash University
    kuang.ye.chow@monash.edu

    Dr Melanie Po-Leen Ooi

    OBE Coordinator
    Electrical and Computer Systems Engineering
    Monash University
    melanie.ooi@monash.edu
     

    Prof Serge Demidenko

    Associate Head
    School of Engineering & Advanced Technology
    Massey University
    s.demidenko@massey.ac.nz