基于BP-ANN的贯流泵装置能量性能参数的预测及分析

为了分析和解决水泵转速变化超过20%时，通过水泵相似律换算的泵装置能量性能参数存在显著差异的问题，构建了基于水泵转速和泵装置扬程两个参数预测泵装置流量和水泵轴功率的曲面函数方程，并将不同转速贯流泵装置非线性特性的能量效率性能曲线转换为基于BP-ANN的不同转速贯流泵装置能量效率参数的预测模型，确定了效率参数预测模型的输入模式，给出了BP-ANN网络结构。BP神经网络预测模型经试验数据验证，预测的泵装置效率绝对偏差在1%以内，为泵装置的变速调节及性能换算提供了参考依据。

Experimental analysis and prediction of energy performance parameters of S-shaped tubular pumping system based on BP-ANN

When the rotating speed change of the pump exceeds 20% of the original speed, the calculated values of its performance parameters by the pump similarity law are greatly differentiated. In order to analyze and solve this problem, a surface function equation is constructed to predict the flow rate and axial power of the pump device based on the two parameters of the pump speed and the head of the pump device. The energy efficiency performance curve with nonlinear characteristics of the tubular pump device at different speeds is converted to a prediction model of the energy efficiency parameters of the tubular pump device at different speeds based on BP-ANN. Meanwhile, the input mode of the prediction model is determined to establish the network structure of BP-ANN. According to the verification by the experimental data, the absolute deviation of the predicted pump efficiency is less than 1 %, which meets the accuracy requirements of practical engineering applications. This model can provide a reference for variable speed regulation and performance conversion of pump devices.