基于改进BP神经网络的离心泵性能预测

Performance Forecast of Centrifugal Pump by BP Neural Network

采用改进神经网络(贝叶斯正则化算法)对IB型单级离心泵水力模型的性能进行了预测,通过工程实践中得到的100组离心泵最优几何尺寸来训练网络,并用训练好的网络对需生产的水泵进行工况预测。结果显示,用改进神经网络来预测单级离心泵的性能,预测误差不超过6%。

The performance of centrifugal pump is forecasted by BP neural network, and the BP model is trained by 100 sets of example data es including 5 pumps' geometrical dimensions, then the pump performance data are obtained. Results show that BP neural network can well forecast centrifugal pump performance, and the relative error is less than 6%.