초록 ▼

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 perform

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.

대표청구항 ▼

1. An apparatus for controlling a water treatment plant, comprising:a receiver unit that receives sensor information from the water treatment plant; a neural network; a monitoring unit coupled to the neural network and the receiver unit; a prediction unit coupled to the monitoring unit and the neura

1. An apparatus for controlling a water treatment plant, comprising:a receiver unit that receives sensor information from the water treatment plant; a neural network; a monitoring unit coupled to the neural network and the receiver unit; a prediction unit coupled to the monitoring unit and the neural network; a modeling unit coupled to the monitoring unit and the neural network; and an output unit that outputs water quality parameters to the water treatment plant, wherein the monitoring unit, the prediction unit and the modeling unit can process sufficient parameters of the sensor information to predict water treatment plant operations and control the water treatment plant operations, wherein the monitoring unit modifies water treatment plant operations to determine treated material dispensing and system control rates to reduce the quantity of the treated material used to meet prescribed intermediate set points, wherein the sensor information includes the prescribed intermediate set points, wherein the monitoring unit modifies water treatment plant operations to meet the prescribed intermediate set points, and wherein the prescribed intermediate set points are values for water quality parameters including each of turbidity, pH, alkalinity, hardness, flow, ferric sulfate dose, and total organic carbon.