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

机译:废水处理曝气池污泥活动智能控制系统研究

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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确定了活性污泥废水基本处理的效率。本文构成了活性污泥最佳活性的智能最佳控制系统。根据水质的影响,构成了MIMO-LSSVM软测量模型,以预测污泥活性,具有各种物理和化学参数,如流入条件,并将活性污泥的活性作为反馈信号,并使用模糊神经网络优化溶解的氧气和污泥密度设定值。最后,基于最小二乘支持向量机的逆控制系统用于分离并跟踪溶解氧密度和污泥密度的设定值。本文在实现活性污泥的最佳活性的约束下,这种方法不仅能够确保水质的稳定性,而且显着降低功耗,从而有效地提高废水处理的能量效率。

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