采用机理分析法建立了隔离型热管换热节能系统的稳态模型.对于机理方程中的未知关键参数,基于系统实际运行数据,采用粒子群优化算法和限定记忆的递推算法对未知参数进行了估计.针对模型参数的变化问题,采用RBF神经网络建立了系统输入变量与模型参数的定量关系,使用现场数据验证了方法的有效性.获得了换热节能系统比较精确的模型.为进一步的系统分析与实时优化打下了基础.
The steady state model of the heat pipe heat-exchange system is built using the mechanism analysis approach. For the unknown key parameter estimation in modeling, the particle swarm optimization algorithm and recursion algorithm with restricted memory are used based on the actual running data. Because of the change of model parameter, a RBF neural network is used to build a quantitative relationship between input variable and model parameter, and the validity of this method is verified using field data. Finally, a precise steady-state model is obtained. It lays a solid foundation for further system analysis and real time optimization.