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Researches of intelligent control system for the sludge activity in the aeration tank of wastewater treatment

机译:污水曝气池污泥活动智能控制系统的研究

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The level of the microbial activity of the activated sludge determined the efficiency of the activated sludge wastewater treatment essentially. An intelligent optimal control system in the nature of the best activity of the activated sludge is constituted in this paper. According to the influent water quality, constituted a MIMO-LSSVM soft measurement model to predict the sludge activity with a variety of physical and chemical parameters such as the influent conditions, and took the activity of the activated sludge as a feedback signal, and used fuzzy neural networks to optimize the dissolved oxygen and sludge density setting value. Finally, the inverse control system based on least squares support vector machine was used to decouple and track the setting value of dissolved oxygen density and sludge density. In this paper, Under the constraints of achieving the best activity of the activated sludge, this method not only ensuring the stability of water quality, but also reducing power consumption significantly and improving the energy efficiency of wastewater treatment effectively.
机译:活性污泥的微生物活性水平基本上决定了活性污泥废水处理的效率。本文构建了一种具有最佳活性污泥活性的智能最优控制系统。根据进水水质,构建了MIMO-LSSVM软测量模型,利用进水条件等多种理化参数预测污泥的活性,并以活性污泥的活性为反馈信号,并采用模糊神经网络来优化溶解氧和污泥密度设定值。最后,基于最小二乘支持向量机的逆控制系统被用来解耦和跟踪溶解氧浓度和污泥浓度的设定值。本文在实现活性污泥最佳活性的约束下,该方法不仅保证了水质的稳定性,而且还大大降低了能耗,有效地提高了废水处理的能效。

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