Fouling Prediction And Software Development Of Heat Exchanger Based On Typical Water Quality Parameters

In the process of industrial production,the problem of scaling in circulating cooling water has great influence on heat exchanger,and brings a series of technical and economic problems.The existence of fouling reduces the heat exchange efficiency of heat exchanger,and often fails to meet the operational requirements required by industrial production.And our country is vast,the circulating cooling water used in different places is different,the scale of heat transfer equipment is not the same,so it is necessary to design a heat exchanger to meet the requirement of circulating cooling water quality in different regions according to the different circulating cooling water quality in different places,so as to achieve the economic operation of the heat exchanger.Based on the dynamic monitoring device of analog heat exchanger,this paper experimentally studied the influence of the typical water quality parameters of the Songhua River water system and the Pearl River water system on the heat resistance of the heat exchanger,and developed a simple calculation software to to calculate the corresponding fouling resistance according to the water quality parameters,and then the total heat transfer coefficient and the redundant heat transfer area of the heat exchanger are calculated.The main contents of this paper are as follows:First,the dynamic monitoring device of simulated circulating cooling water was used to monitor the typical water quality parameters and fouling resistance of the Songhua River water system and the Pearl River system.The experimental data of the summer and winter seasons were obtained,and the influence of various water quality parameters and fouling resistance formation process of two water systems were analyzed.Secondly,on the basis of the experimental data of the Songhua River system and the Pearl River water system in summer and winter,a prediction model of fouling resistance based on BP neural network and generalized regression neural network(GRNN)was established,and the prediction results of the two models were compared.The results show that the generalized regression neural network prediction model is better than the BP neural network prediction model both in convergence speed and prediction accuracy.Finally,on the basis of the generalized regression neural network prediction model,using C# as the software development platform and MATLAB as the core design tool,a simple fouling thermal resistance prediction software is developed to meet the heat exchanger heat transfer coefficient and redundant heat transfer area,and provide a certain theoretical reference for the heat exchanger design.