CAJ | 학술논문

针对潜艇操纵性优化设计中水动力系数预报问题，在潜艇水动力预报中引入艇体肥瘦指数概念，确定了潜艇艇体几何描述的五参数模型。提出采用小波神经网络方法预报潜艇水动力，确定了神经网络的结构，利用均匀试验设计方法，设计了神经网络的学习样本。在验证CFD预报艇体水动力有效的基础上，完成了样本水动力系数的CFD计算；通过对样本进行学习，完成了潜艇艇体操纵性水动力系数小波神经网络预报。研究结果表明，只要确定适当的输入参数，选择适当的学习样本和网络结构，利用小波神经网络方法对潜艇水动力进行预报可以达到较高的精度。
침대잠정조종성우화설계중수동력계수예보문제，재잠정수동력예보중인입정체비수지수개념，학정료잠정정체궤하묘술적오삼수모형。제출채용소파신경망락방법예보잠정수동력，학정료신경망락적결구，이용균균시험설계방법，설계료신경망락적학습양본。재험증CFD예보정체수동력유효적기출상，완성료양본수동력계수적CFD계산；통과대양본진행학습，완성료잠정정체조종성수동력계수소파신경망락예보。연구결과표명，지요학정괄당적수입삼수，선택괄당적학습양본화망락결구，이용소파신경망락방법대잠정수동력진행예보가이체도교고적정도。
With respect to the prediction of hydrodynamic coefficients applied to maneuver performance optimization in submarine design, a fat-thin index of submarine hull is introduced, and a five parameters model is conformed. A method of predicting hydrodynamic coefficients is proposed by using wavelet neural networks. The structure of the network is confirmed, and by using uniform design method, a series of submarine hull model is designed as the sample for network to study. After checking the availability of CFD method in predicting hydrodynamic coefficients, hydrodynamic coefficients of the sample are calculated. Through the sample study the prediction of hydrodynamic coefficients of submarine hull is completed. The results indicate that hydrodynamic coefficients of submarine hull can be predicted well by using the wavelet neural network with suitable input parameters, study sample and net structure.