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Study on the Methods of Predicting the Fouling Characteristics of Plate Heat Exchanger Based on Water Quality Parameters

机译:基于水质参数预测板式换热器污垢特性的方法研究

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Fouling characteristic of plate heat exchanger was studied through the experimental system, with the Songhua River water as working fluid. Several water quality parameters: pH value, conductivity, dissolved oxygen, turbidity, hardness, alkalinity, chloride ion, iron ion, chemical oxygen demand, total bacterial count, which had great influence on the formation of fouling, as well as running condition, fouling resistance and other parameters were measured through the experimental system built. A group of fouling data of the typical water quality was obtained. Two prediction models of fouling characteristics of the plate heat exchanger were built based on partial least squares algorithm (PLS) and support vector regression machine (SVR) with water quality parameters as independent variables and fouling resistance as dependent variable, and the impact of water quality parameter on predicting accuracy was analyzed. Research results showed that: the prediction accuracy of two methods could be controlled within 12.5% and meet the requirements of the project. Through the comparison of the prediction results, it was proved that the SVR method was better than the method of PLS. The impact of the water quality parameters on prediction model was discussed by the means of deleting the water quality parameters one by one.
机译:通过实验系统研究了板式换热器的污垢特征,并用松花江水作为工作流体。几种水质参数:pH值,电导率,溶解氧,浊度,硬度,碱度,氯离子,铁离子,化学需氧量,总细菌数量,这对污垢形成有很大的影响,以及运行条件,污垢通过建造的实验系统测量电阻和其他参数。获得了一组典型水质的污染数据。结垢板式热交换器的特征的两个预测模型建立了基于偏最小二乘算法(PLS)和支持向量回归机(SVR)与水质量参数作为独立变量和污垢热阻为因变量,和水的质量的影响分析了预测准确度的参数。研究结果表明:两种方法的预测准确性可以控制在12.5%以内并满足项目的要求。通过对预测结果的比较,证明SVR方法优于PLS的方法。通过逐一删除水质参数的方法讨论了水质参数对预测模型的影响。

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