基于PSO-BP神经网络的Savonius型叶轮阵列消波性能优化  

Optimization of Wave Absorption Performance of Savonius Type Impeller Array Based on PSO-BP Neural Network

作　　者：盛勇 宋瑞银 杨状状 刘博宇 吴瑞明 任聪杰 SHENG Yong;SONG Ruiyin;YANG Zhuangzhuang;LIU Boy;WU Ruiming;REN Congjie(School of Mechanical and Energy Engineering,Zhejiang University of Science and Technology,Hangzhou 310023,China;School of Mechatronics and Energy Engineering,Ningbo Tech University,Ningbo 315100,Zhejiang,China;College of Mechanical Engineering,Zhejiang University,Hangzhou 310023,China;Zhejiang Engineering Research Center for Intelligent Marine Ranch Equipment,Ningbo 315100,Zhejiang,China)

机构地区：[1]浙江科技大学机械与能源工程学院,杭州1310023 [2]浙大宁波理工学院机电与能源工程学院,浙江宁波315100 [3]浙江大学机械工程学院,杭州310023 [4]智慧海洋牧场装备技术浙江省工程研究中心,浙江宁波315100

出　　处：《船舶工程》2024年第5期160-168,共9页Ship Engineering

基　　金：浙江省“领雁”重大专项计划(2023C03122);宁波市公益性科技计划项目(2022S095)。

摘　　要：为了提高Savonius型(S型)叶轮的消波性能,提出一种S型叶轮阵列装置。通过试验记录不同的叶轮间距和叶轮相对入水深度等5个参数下波浪经过叶轮阵列后的透射系数K_(t),建立基于粒子群优化(PSO)算法和反向传播(BP)神经网络的S型叶轮阵列消波性能预测模型。将采用该模型与采用BP网络模型和GA-BP网络模型得到的平均绝对误差、均方根误差和决定系数R^(2)指标进行对比,结果表明,采用PSO-BP神经网络模型优化能得到误差更小、更精准的预测结果。当相邻叶轮间距分别为0.62 m和0.41 m、各叶轮入水深度分别为0.15 m、0.18 m和0.19 m时,S型叶轮阵列具有相对最佳的消波性能。In order to improve the wave absorption performance of the Savonius-type(S-type)impeller,a S-type impeller array device is proposed.By conducting experiments and recording the transmission coefficient K_(t) of waves passing through the impeller array under five parameters,including diferent impeller spacing and relative submergence depth,a prediction model for the wave absorption performance of the S-type impeller array is established based on particle swarm optimization(PSO)algorithm and back-propagation(BP)neural network.The model is compared with the BP neural network model and the GA-BP neural network model using the average absolute error,root mean square error,and determination coefficient R^(2) as indicators.The results show that the PSO-BP neural network model optimization can achieve smaller and more accurate prediction errors.When the adjacent impeller spacing is 0.62 m and 0.41 m,and the submergence depths of each impeller are 0.15 m,0.18 m,and 0.19 m respectively,the S-type impeller array exhibits relatively optimal wave absorption performance.

关 键 词：Savonius型叶轮 消波性能 粒子群优化(PSO)算法 反向传播(BP)神经网络 

分 类 号：U656.2[交通运输工程—港口、海岸及近海工程]