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Chlorine modeling in water distribution networks using ARX and ARMAX model structures

机译：使用ARX和ARMAX模型结构对供水网络中的氯进行建模

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摘要

Chlorination is still the main method of disinfection worldwide. Utilization of chlorine modeling enhances the management of water supply systems toward the reduction of the risks of waterborne diseases and cancer from disinfection byproducts formation. In this paper, the results of chlorine modeling efforts were presented as an extension of a project for Konyaalti Water Distribution Network (KWDN) of Antalya City, in the south of Turkey, using autoregressive with exogenous input (ARX) and autoregressive moving average with exogenous input (ARMAX) model structures. The required data-sets were obtained from the existing online monitoring stations. The ARX and ARMAX model structures modified for time series applications were utilized to predict chlorine concentrations at the critical point of KWDN. Non-representative data-sets were initially identified and excluded from the database. Best fit and Akaike's Final Prediction Error techniques were used as model selection criteria. ARX4-5-3 and ARMAX2-3-3-4 were identified to be the best ARX and ARMAX model structures among several structures tested to predict chlorine concentrations at the critical point of KWDN. This study shows that ARX and ARMAX model structures can be considered as potential for managing chlorine levels in water distribution networks especially when the properties of the components and hydraulics of water distribution network are unknown.
机译：氯化仍是全世界消毒的主要方法。氯模型的使用增强了供水系统的管理，从而降低了由消毒副产物形成而导致的水传播疾病和癌症的风险。本文将氯模拟工作的结果作为土耳其南部安塔利亚市Konyaalti供水网络（KWDN）项目的扩展进行了介绍，该项目使用外生输入的自回归和外生自回归移动平均输入（ARMAX）模型结构。所需的数据集是从现有的在线监视站获得的。为时间序列应用而修改的ARX和ARMAX模型结构被用来预测KWDN临界点的氯浓度。最初确定了非代表性数据集，并将其从数据库中排除。最佳拟合和Akaike的最终预测误差技术用作模型选择标准。 ARX4-5-3和ARMAX2-3-3-4被确定为在KWDN临界点预测氯浓度的几种测试结构中最好的ARX和ARMAX模型结构。这项研究表明，ARX和ARMAX模型结构可以被认为是管理供水管网中氯含量的潜力，尤其是当供水管网的部件和水力特性未知时。

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