远程对医院实验室温度优化监控仿真

摘要

This article proposes a method for remote supervision of temperature in hospital laboratory based on neural network.Firstly,a filter with first order type integrated with distribution diagram was designed and used to eliminate signal with high-frequency interference and initial state-transition matrix of automat in temperature system was provided.Then a neural network with radial basis function (RBF) was integrated with general PID to provide control strategy of remote supervision and used identifier of RBF neural network to carry out on-line identification for Jacobian matrix information of temperature control system.Finally,the remote supervision was completed.Experimental results show that the method has high supervision precision and can provide scientific gist for improving environmental quality in hospital laboratory.%远程对医院实验室温度进行监控,可有效的提升医院实验室的环境质量.对医院实验室温度的远程控制,需要计算出信号的截止频率,给出温度系统初始自动状态转移矩阵,完成远程温度控制.传统方法通过上位机监控单元和现场控制单元,采集现场的温度信息传至ARM进行数据的分析与处理,但无法得出温度状态转移矩阵,导致远程监控精度低.提出基于神经网络的医院实验室中温度的远程监控方法.融合于分布图理论设计一阶型滤波器,利用滤波器消除高频干扰信号,给出温度系统初始自动机状态转移矩阵,将径向基神经网络和常规PID相结合给出温度的远程监控控制策略,利用RBF神经网络辨识器对温度控制系统的Jacobian矩阵信息在线辨识,完成对医院实验室中温度的远程监控.仿真结果表明,所提方法监控精度高,可以为提升医院实验室内的环境质量给出科学的依据.