Real-Time Sensor Control for DAF Water Treatment
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Solution Overview
Problem
Current water treatment systems, particularly those using dissolved air flotation (DAF) devices, face challenges in optimally treating industrial effluent due to its complex and fluctuating composition, leading to inefficient chemical dosing and sub-optimal water quality, which results in increased costs and potential non-compliance with regulatory standards.
Innovation Solution
A control and dosing system that utilizes real-time sensors to measure water quality metrics, a processor to adjust chemical treatments dynamically, and a method that involves systematic testing to generate a model for optimal chemical dosing, allowing for continuous optimization of water treatment processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If chemical dosage is increased to improve water quality, then water quality is improved, but chemical cost increases
Solution Approach 1:
The system dynamically changes chemical dosing parameters (dosage rates, timing, sequence) based on real-time water quality sensor data and predictive models to achieve optimal treatment effectiveness while minimizing chemical consumption. The controller continuously adjusts dosing parameters to match varying effluent conditions.
Solution Approach 2:
The system implements closed-loop feedback control where water quality sensors continuously monitor treated water quality, and the controller uses this feedback to adjust chemical dosing in real-time. The predictive model also provides forward-looking feedback about anticipated quality changes, allowing proactive dosing adjustments.
2Reliability
If chemical dosage is increased to ensure compliance, then compliance risk is reduced, but overall treatment cost increases
Solution Approach 1:
The system performs preliminary actions by using the predictive model to anticipate future water quality changes before they occur. The controller proactively adjusts chemical dosing in advance based on predicted effluent composition changes, ensuring compliance is maintained without needing to over-dose as a precaution.
Solution Approach 2:
The system dynamically changes dosing parameters based on predicted effluent characteristics and anticipated quality changes, achieving reliable compliance through precise, adaptive dosing rather than consistent over-dosing.
3Ease of manufacture
If traditional jar testing is used to determine chemical dosage, then initial treatment setup is achieved, but continuous optimization is lost due to time-consuming manual processes
Solution Approach 1:
The system replaces manual mechanical jar testing with an automated electronic control system that uses predictive modeling and real-time sensor data to determine optimal dosing parameters. The controller automatically executes dosing strategies without manual intervention, enabling continuous optimization at high speed.
Solution Approach 2:
The system performs self-service by automatically monitoring water quality, predicting changes, and adjusting chemical dosing without requiring continuous manual jar testing. The predictive model and controller work autonomously to maintain optimal treatment conditions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This system reduces chemical consumption and discharge costs, improves water quality consistency, and minimizes the risk of non-compliance by dynamically adjusting to changes in effluent composition, leading to cost savings and enhanced treatment efficiency.
Implementation Method 1
one or more feed water sensors to measure in substantially real-time a water quality metric of the feed water; one or more treated water sensors to measure in substantially real-time a water quality metric of the treated water
Implementation Method 2
Compressed air is also introduced into the effluent stream, typically in a recirculation loop, leading to the formation of dissolved air. When this stream is released at atmospheric pressure in the DAF, the bubbles formed by the air coming out of solution draw the suspended matter to the surface of the DAF system.
Implementation Method 3
Upon demobilization of these materials, flocculants are typically added to collect and aggregate these particles and other contaminants to make larger particles. This is done to improve the separation of the solids from the liquid phase of the waste water.
Implementation Method 4
The effluent or feed water is added at one end of a DAF system, as depicted in FIG. 1, and treated with chemicals such as coagulants, acids and bases which act to destabilize colloidal material, causing these to come out of suspension.
Data Source
AI summary
Disclosed herein is a water treatment system for connection to a water treatment plant (e.g. a dissolved air flotation device). The plant may have an inlet for the receipt of feed water (e.g. waste water) and an outlet for the discharge of treated water. The treatment system may comprise a first sensor disposed such that it is in fluidity communication with the feed water, and a second sensor disposed such that it is in fluidity communication with the treated water. The first and second sensors may be configured to sense parameters of the feed and treated water. The system may further comprise a first applicator (e.g. a pump) that is configured to discharge a treatment source (e.g. a chemical source) to the plant to treat the feed water. The disclosed system may be used to treat waste water (e.g. the treatment of effluent from oil refineries, petrochemical and chemical plants, natural gas processing plants, paper mills and general water treatment). The system has analogous applications in other processing methods that also use DAF, or very similar, systems, such as the processing of mineral ores and other such solid extraction processing methods.