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基于改进BP神经网络的复合叶轮离心泵性能预测

, PP. 77-80

Keywords: 复合叶轮,BP神经网络,性能预测

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Abstract:

应用Matlab建立了复合叶轮离心泵效率和扬程的BP神经网络预测模型。选取73组试验结果作为样本,采用Levenberg-Marquardt法则对构建的网络进行训练,并随机选取12组训练样本外的数据对训练好的网络进行测试。试验的主要参数为流量Q,叶片数z,叶片出口安放角β2,短叶片进口直径Di,叶片出口宽度b2,效率η以及扬程H。其中选取Q,z,β2,Di,b2作为网络的输入层,η和H作为输出层。预测结果的分析表明,预测值与试验值具有较好的一致性,利用BP神经网络对复合叶轮离心泵性能进行预测是可行的,可用来作复合叶轮的辅助设计,从而缩短试验时间,降低成本。

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