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The Analysis of Impact Factors for Dissolved Oxygen Concentration in Wastewater Treatment System Using an Adaptive Modeling Method

机译:自适应建模方法分析废水处理系统中溶解氧浓度的影响因素

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The dissolved oxygen concentration (DOC) in water is an important indicator of self-purification capacity of water in wastewater treatment system. In this study, the operating processes of wastewater treatment systems are modeled based on the mechanism model. Meanwhile, different factors that influence the DOC are analyzed. The adaptive dynamic model of DOC is established in the Matlab environment considering white noise in the model input. The effect of the input variables (e.g., aeration tank) and load variables (e.g., oxygen consumption) on the DOC is analyzed in detail when white noise is considered in the model input. The transform transient characteristics of DOC are obtained after leaving out outliers of the input variables. As an on-line outlier’s detection method, abnormal value detection is used to remove the inferior quality data in order to ensure the reliability of the efficiency of the developed model. Results demonstrate that the adaptive dynamic simulation model can be used to improve both the accuracy of modeling and the ability of modeling system dynamics.
机译:水中的溶解氧浓度(DOC)是废水处理系统中水自净能力的重要指标。在这项研究中,基于机理模型对废水处理系统的运行过程进行了建模。同时,分析了影响DOC的不同因素。在Matlab环境中,考虑模型输入中的白噪声,建立DOC的自适应动态模型。当在模型输入中考虑白噪声时,将详细分析输入变量(例如曝气池)和负载变量(例如氧气消耗)对DOC的影响。剔除输入变量的异常值后,即可获得DOC的变换暂态特性。作为在线异常值的检测方法,异常值检测用于删除质量较差的数据,以确保开发模型的效率可靠。结果表明,自适应动态仿真模型可用于提高建模的准确性和系统动力学建模的能力。

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