Dongsheng Wang, Jiang Feng, Jiankun Xie, Xuzheng Xu, Chonghua Yao, Yunzhong Jiang
State Key Laboratory of Environmental Aquatic Chemistry, RCEES, Chinese Academy of Sciences, Beijing 100085, China.
Water Sci Technol. 2010;61(11):2699-706. doi: 10.2166/wst.2010.163.
Coagulation control plays a significant role in the final yield of sludge volume during water and wastewater treatment. The precise control of coagulant dosage, floc formation and aggregation behaviour becomes the important target for the coagulation process both in water and wastewater treatment. A critical review is presented first in this paper on the recent advances in coagulation control. In particular, the development of an in-situ image detecting system (IDS) based on characterization of floc properties, involving average diameter, fractal dimension and apparent strength is discussed. The results show that the data obtained from the IDS are generally in accordance with the outcome of common coagulation experiment, and have sensitivity for the slow stirring rate, raw water turbidity and coagulant dosage, in different degrees. The combination of IDS and ANN model is also discussed. This provides a possibility for applying the proposed IDS to control the coagulation process in water and wastewater treatment.
在水和废水处理过程中,混凝控制对污泥体积的最终产量起着重要作用。精确控制混凝剂用量、絮凝体形成和聚集行为成为水和废水处理中混凝过程的重要目标。本文首先对混凝控制的最新进展进行了批判性综述。特别讨论了基于絮凝体特性表征(包括平均直径、分形维数和表观强度)的原位图像检测系统(IDS)的发展。结果表明,从IDS获得的数据通常与常规混凝实验结果一致,并且对不同程度的慢速搅拌速率、原水浊度和混凝剂用量具有敏感性。还讨论了IDS与人工神经网络(ANN)模型的结合。这为将所提出的IDS应用于水和废水处理中的混凝过程控制提供了可能性。