Dislodgement recognition of oil tank with GA-BP networks

Abstract

Abstract: In view of tank capacity charts are distorted after oil tank dislodge, the integral model is established with micro-element method. The function relationship between oil volume, oil height, vertical angle and crosswise deflection angle is obtained. Dislodgement parameter is determined with least squares method and Matlab software. Also deflection angle is amended with genetic algorithms and BP networks to improve the accuracy. Then tank capacity charts are revised after oil tank dislodge. The model has certain promotion through sample data.

Key words: oil tank, dislodge, genetic algorithms, Back Propagation（BP） networks

摘要： 针对储油罐变位会导致罐容表读数失真的问题，采用微元法的思想建立积分模型，得到油的体积与油位高度及纵向倾斜角、横向偏转角的函数关系式；利用最小二乘法和Matlab软件确定出变位参数。为了提高精度，分别采用遗传算法和BP神经网络对变位角进行修订，同时给出了变位后的罐容表标定值；利用采样数据进行了检验，结果表明该模型具有一定的推广性。

关键词: 储油罐, 变位, 遗传算法, 反向传播（BP）网络

SUN Weiwei, SHENG Xingping, HUANG Yingxue. Dislodgement recognition of oil tank with GA-BP networks[J]. Computer Engineering and Applications, 2013, 49(14): 264-266.

孙娓娓，盛兴平，黄映雪. 基于遗传BP网络的变位储油罐识别模型[J]. 计算机工程与应用, 2013, 49(14): 264-266.

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Dislodgement recognition of oil tank with GA-BP networks

基于遗传BP网络的变位储油罐识别模型

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