基于BP神经网络的人工冰场低温冷水机组预测控制算法

Predictive control algorithm of low-temperature water chilling packages for artificial ice rink based on BP neural network

为精确控制人工冰场冰面温度,提出基于BP神经网络的人工冰场冰面温度预测及低温冷水机组控制方法。根据采集到的低温冷水机组供/回水温度、冰场环境温度以及冰面温度数据,利用BP神经网络进行网络模型训练,建立BP神经网络模型。利用测试样本对预测模型的仿真结果进行检验,证明BP神经网络用于人工冰场冰面温度预测的可行性。根据冰面温度预测值及目标值,调整低温冷水机组供/回水温度,能够满足不同冰上运动对冰面硬度(温度)的要求。

In order to accurately control of ice surface temperature in artificial ice rink,the prediction of ice surface temperature in artificial ice rink based on BP neural network and the control method of low-temperature water chilling packages are proposed.The BP neural network model is established,which uses the BP neural network to train the network model by extracting the data of the supply/return water temperatures of the low-temperature water chilling packages,the environmental temperature of the ice rink and the ice surface temperature.The test samples are used to test the simulation results of the prediction model,which proves the feasibility of BP neural network in predicting the ice surface temperature of artificial ice rink.Adjusting the water supply/return temperatures of low-temperature water chilling packages can meet the requirements of ice surface hardness(temperature)for different ice sports according to the predicted value and target value of ice surface temperature.