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Improvement of Simulation Method in Validation of Software of the Coordinate Measuring Systems


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[1] Ratajczyk, E. (2005). Coordinate Measuring Technique. Warsaw University of Technology Publisher.Search in Google Scholar

[2] International Organization for Standardization. (2003). Measurement management systems - Requirements for measurement processes and measuring equipment. ISO 10012:2003.Search in Google Scholar

[3] International Organization for Standardization. (2002). Geometrical Product Specifications (GPS). Coordinate measuring machines (CMM): Acceptance test and reverification tests for coordinate measuring machines (CMM). Part 6: Estimation of errors in computing Gaussian associated features. PN-EN ISO 10360-6.Search in Google Scholar

[4] International Organization for Standardization. (2002). Software and System Engineering - Software Product Evaluation - Part 1: General overview. ISO/IEC 14598-1.Search in Google Scholar

[5] Jaworski, J.M., Morawski, R.Z., Olędzki, J.S. (1995). Measuring as the parametric identification of the mathematical model of the object being measured. Metrology and Measurement Systems, 2 (1).Search in Google Scholar

[6] IEEE. (1998). IEEE standard for a software quality metrics methodology. IEEE Std. 1061-1998.Search in Google Scholar

[7] Joint Committee for Guides in Metrology. (2008). International vocabulary of metrology - Basic and general concepts and associated terms (VIM 3rd edition). JCGM 200:2008.Search in Google Scholar

[8] Nieciąg, H. (2012). The assessment of the criterion in tests of acceptance type of the metrological software in coordinate measuring systems. In 10th International Scientific Conference „Coordinate Measuring Technique”, 23-25 April, 2012, Bielsko Biała, Poland.Search in Google Scholar

[9] Joint Committee for Guides in Metrology. (2008). Evaluation of measurement data -- Guide to the expression of uncertainty in measurement. JCGM 100:2008.Search in Google Scholar

[10] Joint Committee for Guides in Metrology. (2008). Evaluation of measurement data - Supplement 1 to the „Guide to the expression in measurement” - Propagation of distributions using a Monte Carlo method. JCGM 101:2008.Search in Google Scholar

[11] Joint Committee for Guides in Metrology. (2011). Evaluation of measurement data - Supplement 2 to the „Guide to the expression in measurement” - Extension to any number of output quantities. JCGM 102:2011.Search in Google Scholar

[12] International Organization for Standardization. (2008). Geometrical Product Specifications (GPS) -- Coordinate measuring machines (CMM): Technique for determining the uncertainty of measurement -- Part 4: Evaluating task-specific measurement uncertainty using simulation. ISO/TS 15530-4:2008.Search in Google Scholar

[13] Sładek, J. (2011). The Accuracy of Coordinate Measurements. Cracow University of Technology.Search in Google Scholar

[14] Nieciąg, H., Tabisz, R.A. (2011). Simulation of influence of systematic and random factors on measurement results of coordinate measuring machines. Measurement Automation and Monitoring, 57 (12), 1611-1616.Search in Google Scholar

[15] Weckenmann, A., Knauer, M. (1998). The influence of measurement strategy on the uncertainty of CMMmeasurements. Annals of the CIRP, 47 (7), 451-455.10.1016/S0007-8506(07)62872-8Search in Google Scholar

[16] Portman, V., Rubenchik, Y., Shuster, V. (2002). Statistical approach to assessments of geometrical accuracy. Annals of the CIRP, 51 (1), 463-466.10.1016/S0007-8506(07)61561-3Search in Google Scholar

[17] Cox, M.G., Siebert, B.R.L. (2006). The use of a Monte Carlo method for evaluating uncertainty and expanded uncertainty. Metrologia, 43, 178-188.10.1088/0026-1394/43/4/S03Search in Google Scholar

[18] McKey, M.D., Conover, W.J. (1979). Comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics, 21 (2), 239-24.Search in Google Scholar

[19] Helton, J.C., Davis, F.J. (2002). Latin Hypercube Sampling and the Propagation of Uncertainty in Analyses of Complex Systems. Sandia Report SAND2001-0417, Sandia National Laboratories Albuquerque, California.10.2172/806696Search in Google Scholar

[20] Stein, M. (1987). Large sample properties of simulations using latin hypercube sampling. Technometrics, 29 (2), 143-151.10.1080/00401706.1987.10488205Search in Google Scholar

[21] Owen, A.B. (1998). Latin supercube sampling for very high- dimensional simulations. ACM Transactions on Modeling and Computer Simulation, 8 (1), 71-102.10.1145/272991.273010Search in Google Scholar

[22] Tabisz, R.A., Nieciąg, H. (2012). Simulation of influence of systematic and random factors on measurement results of coordinate measuring machines. Measurement Automation and Monitoring, 58 (12), 1065-1067.Search in Google Scholar

[23] Adamczak, S., Janecki, D., Stępień, K. (2011). Testing of methods of measurement and evaluation of the spherical shape errors of machine parts. Mechanic, 12, 958-961.Search in Google Scholar

[24] Domański, Cz., Pruska, K. (2000). Non-classical Statistical Methods. Polish Economic Publishing House.Search in Google Scholar

[25] Adamczak, S. (2008). The geometric structure of the surface. Vol. 2. Comparative studies of the instruments. Correlation calculus method. Mechanic, 5-6, 514-518.Search in Google Scholar

[26] Wikipedia. Spearman's rank correlation coefficient. http://en.wikipedia.org/wiki/Spearman%27s_rank_correlation_coefficient. Search in Google Scholar

eISSN:
1335-8871
Language:
English
Publication timeframe:
6 times per year
Journal Subjects:
Engineering, Electrical Engineering, Control Engineering, Metrology and Testing