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2013 Mathematical Model Based on BP Neural Network Algorithm for the Deflection Identification of Storage Tank and Calibration of Tank Capacity Chart
Caihong Li, Yali Yuan, Lulu Song, Yunjian Tan, Guochen Wang
Abstr. Appl. Anal. 2013(SI14): 1-13 (2013). DOI: 10.1155/2013/923036

Abstract

The tank capacity chart calibration problem of two oil tanks with deflection was studied, one of which is an elliptical cylinder storage tank with two truncated ends and another is a cylinder storage tank with two spherical crowns. Firstly, the function relation between oil reserve and oil height based on the integral method was precisely deduced, when the storage tank has longitudinal inclination but has no deflection. Secondly, the nonlinear optimization model which has both longitudinal inclination parameter α and lateral deflection parameter β was constructed, using cut-complement method and approximate treatment method. Then the deflection tank capacity chart calibration with a 10 cm oil level height interval was worked out. Lastly, the tank capacity chart was corrected by BP neural network algorithm and got proportional error of theoretical and experimental measurements ranges from 0% to 0.00015%. Experimental results demonstrated that the proposed method has better performance in terms of tank capacity chart calibration accuracy compared with other existing approaches and has a strongly practical significance.

Citation

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Caihong Li. Yali Yuan. Lulu Song. Yunjian Tan. Guochen Wang. "Mathematical Model Based on BP Neural Network Algorithm for the Deflection Identification of Storage Tank and Calibration of Tank Capacity Chart." Abstr. Appl. Anal. 2013 (SI14) 1 - 13, 2013. https://doi.org/10.1155/2013/923036

Information

Published: 2013
First available in Project Euclid: 26 February 2014

zbMATH: 07095493
Digital Object Identifier: 10.1155/2013/923036

Rights: Copyright © 2013 Hindawi

Vol.2013 • No. SI14 • 2013
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