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Modelling effluent quality based on a real-time optical monitoring of the wastewater treatment process

机译:基于对废水处理过程的实时光学监控,对废水质量进行建模

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摘要

A novel optical monitoring device was used for imaging an activated sludge process in situ during a period of over one year. In this study, the dependencies between the results of image analysis and the process measurements were studied, and the optical monitoring results were utilized to predict the important quality parameters for the wastewater treatment process efficiency: suspended solids, biological oxygen demand, chemical oxygen demand, total nitrogen and total phosphorous in biologically treated wastewater. The optimal subsets of variables for each model were searched using five variable selection methods. It was shown that online optical analysis results have clear dependencies on some process variables and the purification result. The model based on optical monitoring and process variables from the early stage of the treatment process can be used to predict the levels of important quality parameters, and to show the quality of the biologically treated wastewater hours in advance. This study confirms that the optical monitoring method is a valuable tool for monitoring a wastewater treatment process and receiving new information in real time. Combined with predictive modelling, it has the potential to be used in process control, keeping the process in a stable operating condition and avoiding environmental risks.
机译:一种新型的光学监测设备用于在一年多的时间内对活性污泥过程进行现场成像。在这项研究中,研究了图像分析结果与过程测量之间的相关性,并利用光学监测结果预测了废水处理过程效率的重要质量参数:悬浮固体,生物需氧量,化学需氧量,生物处理废水中的总氮和总磷。使用五种变量选择方法来搜索每个模型的最优变量子集。结果表明,在线光学分析结果对某些工艺变量和纯化结果有明显的依赖性。基于光学监测和处理过程早期阶段的过程变量的模型可用于预测重要质量参数的水平,并提前显示经过生物处理的废水的质量。这项研究证实了光学监测方法是监测废水处理过程并实时接收新信息的有价值的工具。结合预测建模,它有可能用于过程控制中,从而使过程保持稳定的运行状态并避免环境风险。

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