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    • 1. 发明授权
    • System and method for controlling effluents in treatment systems
    • 控制污水处理系统的方法及系统
    • US06408227B1
    • 2002-06-18
    • US09414074
    • 1999-10-07
    • Sanjay S. SinghviJerald L. Schnoor
    • Sanjay S. SinghviJerald L. Schnoor
    • G01N3100
    • C02F1/5209C02F1/008C02F1/52C02F5/00G05B13/027
    • A system and method is provided that predicts operational parameters for all unit operations in water treatment plants or the like. Initial training with historical operations data, for example, allows the system and method to develop equations that can in turn predict the present and future performance of the plant in real time. In addition, the system and method can control operations of the plant in real time. The system improves the performance of the plant to meet predetermined subpoints of various parameters. For example, the predetermined subpoints can be used to enable the plant to meet regulatory needs while controlling for other parameters such as cost, chemical fees, flow rates and power consumption. The system and method include a non-linear predictive model for turbidity. The system considers the influent water quality and analyzes treatment options available to predict the dose of various chemicals required to get desired treatment. It will then predict plant performance resulting from intended operator changes in real time. The system preferably includes general regression neural networks with modeling modifications to learn if the works including learning patterns to make predictions and cost for operations control of unit operations and/or the system. The system includes virtual sensors for parameters that cannot be detected on-line. The system and method determine sufficient data to monitor and control all water quality parameters in the water treatment plant. The water treatment plant operations can be predicted and controlled as a plurality of coupled unit operations. In one embodiment, a unit operation block consist of a power mixer, a rapid mix basin, flocculation basin, and settling tank controlled as a coagulation control loop.
    • 提供了一种系统和方法,其预测水处理厂等中的所有单元操作的操作参数。 例如,具有历史操作数据的初步培训允许系统和方法开发方程式,从而实时地预测工厂的当前和未来的性能。 此外,该系统和方法可以实时控制设备的运行。 该系统提高了工厂的性能,以满足各种参数的预定子点。 例如,预定的子点可以用于使得工厂能够满足监管需求,同时控制诸如成本,化学费用,流量和功率消耗之类的其它参数。 该系统和方法包括用于浊度的非线性预测模型。 该系统考虑进水水质并分析可用于预测获得所需治疗所需的各种化学物质剂量的治疗方案。 然后,它将预期由操作人员实时改变而产生的工厂性能。 系统优选地包括具有建模修改的一般回归神经网络,以了解作品是否包括用于对单元操作和/或系统进行操作控制的预测和成本的学习模式。 该系统包括虚拟传感器,用于无法在线检测的参数。 该系统和方法确定足够的数据来监测和控制水处理厂的所有水质参数。 水处理厂的操作可以预测和控制为多个耦合单元操作。 在一个实施例中,单元操作块由功率混合器,快速混合盆,絮凝池和作为凝结控制回路控制的沉淀池组成。