Abstract
According to JJF1509-1999, measurement uncertainty assessment of vertical metal tank becomes extreme difficult because it can not be measured for many times. This paper is aimed at finding out a way to calculate measurement uncertainty. In this paper, grey system theory is expounded to calculate the principle of degree of uncertainty. The mathematical model of the measurement uncertainty in vertical metal tank is constructed, and then calculation with examples is carried out.
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References
JJF1059 -1999. Measurement Uncertainty Assess and denotation. China Metrology Publishing House (1999)
Mingzhu, X., Chen, G.: Measurement uncertainty evaluation of imprecise data. Systems Engineering and Electronics 27, 929–930, 956 (2005)
Shaofeng, X., Xiaohuai, C., Yongbin, Z.: The Analysis of Uncertainty and Research of Dynamic Character on Measurement System. Journal of Acta Metrologica Sinica 23(3), 237–240 (2002)
JJG168 -87. Vertical metal Oilcan verification regulation. China Metrology Publishing House (1987)
Simeng, T.: Measurement Uncertainty Evaluation of Vertical Metal oilcan Capacity. J. Measurement Technology 8, 56–59 (2006)
Jianmin, Z., Hongzan, B., Zhongyu, W., Fuzhang, Z.: A Grey Evaluation Method of Measurement Result with Standard Uncertainty. J. Huazhong Univ. of Sci. and Tech. 28, 84–86 (2000)
Zhongyu, W., Ping, Q.: Grey Estimation of Measurement Uncertainty. J. Project Design 4, 89–91 (2000)
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© 2009 Springer-Verlag Berlin Heidelberg
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Tang, Dd., Yuan, Sz., Yan, Xp., Li, Pf. (2009). Measurement Uncertainty Assessment of Vertical Metal Tank Based on Grey System Theory. In: Cao, B., Li, TF., Zhang, CY. (eds) Fuzzy Information and Engineering Volume 2. Advances in Intelligent and Soft Computing, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03664-4_31
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DOI: https://doi.org/10.1007/978-3-642-03664-4_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03663-7
Online ISBN: 978-3-642-03664-4
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