人工神经网络在水泵性能预测中的应用

Water pump performance prediction with artificial neural network

分析了影响水泵机组性能变化的主要因素;根据泵性能与各因素之间的关系,利用BP人工神经网络构建了水泵性能的预测模型;以某轴流泵试验数据为样本,BP人工神经网络为工具,对轴流泵模型进行了泵扬程及效率性能指标与流量、叶片角度等相关因素间的性能预测研究.预测结果表明,将该模型用于轴流泵性能参数预测,不仅可以提高预测精度,而且可以缩短试验时间,降低试验成本.

The main factors influencing the performance of pumping units were analyzed. Based on the relationships between the pump performance and each factor, a prediction model for pump performance was constructed by using artificial neural network, and the model was trained with the test data of an axial-flow pump. Then, the BP neural network was employed for prediction of the relationship of lift head and effficiency-performance index with the flow rate, the angle of blade installation, etc. of an axial-flow pump model. The results show that the BP neural network can improve the accuracy in performance prediction, and it can shorten the time and reduce the cost of experiments.