基于BP神经网络的露点蒸发冷却冷水机组性能预测

Performance Prediction of Dew-point Evaporative Cooling Chiller Based on BP Neural Network

本文针对传统蒸发冷却冷水机组的设计缺点,不能对机组实际运行情况全面考虑,量产前优化设计复杂、成本投入大等问题。通过借助神经网络对非线性动力学系统的预测能力,建立露点间接蒸发冷却器性能的预测模型,并对网络模型进行训练与仿真,以供参考。

This paper aims at the design shortcomings of the traditional evaporative cooling chillers,such as the failure to take the actual operation of the chillers into full consideration,the complexity of the optimization design before mass production and the large cost input.The prediction model of dew point indirect evaporative cooler was established by using neural network to predict the nonlinear dynamic system,and the network model was trained and simulated.