求解超高压筒形容器爆破压力的神经网络方法
구해초고압통형용기폭파압력적신경망락방법
ANN-based prediction of bursting pressure under ultra-high pressure for cylindrical vessel
  • 万方数据
    兵器材料科学与工程 병기재료과학여공정
    Ordnance Material Science and Engineering
    2010年 2期 31-34 ,共4页

    袁格侠%刘宏昭%钱学梅%范彩霞%钱学军%秦丽柏

    원격협%류굉소%전학매%범채하%전학군%진려백

    超高压容器%爆破压力%BP神经网络%RBF神经网络%预测 超高壓容器%爆破壓力%BP神經網絡%RBF神經網絡%預測
    초고압용기%폭파압력%BP신경망락%RBF신경망락%예측
    ultra-high pressure vessel%bursting pressure%BP neural network%RBF neural network%prediction
    将BP和RBF神经网络的理论和算法应用于预测超高压容器爆破压力的研究中.选用MATLAB神经网络工具箱建立预测爆破压力的神经网络模型,研究模型中影响爆破压力的主要参数,内外径比值和材料的强度极限,屈服极限,屈服强度与强度极限的比值;选用Faupel、Crossland和Bones等文献中的爆破实验数据对神经网络模型进行训练,用训练好的神经网络模型对爆破压力进行预测.预测结果表明,用BP和RBF神经网络方法建立的模型能够对超高压筒形容器的爆破压力进行较为准确的预测.
    장BP화RBF신경망락적이론화산법응용우예측초고압용기폭파압력적연구중.선용MATLAB신경망락공구상건립예측폭파압력적신경망락모형,연구모형중영향폭파압력적주요삼수,내외경비치화재료적강도겁한,굴복겁한,굴복강도여강도겁한적비치;선용Faupel、Crossland화Bones등문헌중적폭파실험수거대신경망락모형진행훈련,용훈련호적신경망락모형대폭파압력진행예측.예측결과표명,용BP화RBF신경망락방법건립적모형능구대초고압통형용기적폭파압력진행교위준학적예측.
    The theory and the algorithm of BP and RBF neural network are applied in the research for predicting the bursting pressure of ultra-high pressure vessel.First.the neural network model has been established for predicting bumting pressure by using MATLAB Neural Network Tools in consideration of the main factors of influencing bursting pressure.The factors include ultimate strength,yield stress,ratio ofouter radius to inner radius ofthe pressure vessel cylinders and yield ratio.Then the established neural network model is trained by choosing a large amount of bursting experimental data from Faupel,Crossland and Bones,and some
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