摘要
根据热力学性质建立了基于人工神经网络的分置式斯特林制冷机的热力模型 ,对室温腔、压缩腔、膨胀腔、连接管和回热器建立了动态仿真模型并进行数值计算。通过人工神经网络的输入、输出参数和优化网络结构实现对影响模型精度的一些关键参数进行调整 ,从而实现了人工神经网络与制冷机热力模型之间的融合 ,学习后的人工神经网络可直接用于制冷机的热力计算 ,减少了数据回归和预测计算过程。
According to the characteristics of thermodynamics,the thermodynamic model of split-stirling cryocooler was set up on the basic of artificial neural networks,and the dynamic simulative models of compression chamber,hot chamber,cold chamber,connecting hose and regenerator ware built and numerical calculated.The key parameters affecting the models'precision were adjusted by altering the input and output parameters of the artificial neural networks and by optimizing the structure of the networks,thus achieve the integration between the artificial neural networks and cryocooler thermodynamic model.The studied artifically neural networks can be used to thermodynamic calculation of cryocooler,and reduced the process of the data regression and predict computational.
出处
《流体机械》
CSCD
2004年第12期75-77,共3页
Fluid Machinery
关键词
斯特林制冷机
人工神经网络
热力模型
split-stirlin cryocooler
artificial neural networks
hermodynamic model