Membrane Filtration Support Device Optimizing Flux and Cleaning
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Solution Overview
Problem
Conventional water treatment systems with membrane filtration devices face inefficiencies due to conservative control strategies that result in excessive energy usage and suboptimal operation, particularly when dealing with fluctuating water quality, leading to inefficient membrane cleaning and potential clogging.
Innovation Solution
A support device and method that acquires data on water quality, transmembrane pressure, and cleaning conditions to output optimized permeation flux and cleaning schedules using a learned determination model, enabling more efficient and adaptive operation of membrane filtration devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conservative control strategies are used to ensure stable water treatment operation, then system reliability is improved, but energy consumption increases and operational efficiency deteriorates
Solution Approach 1:
The patent implements dynamic control of the membrane filtration system by continuously monitoring water quality parameters (turbidity, pH, temperature, conductivity) and automatically adjusting operation modes (filtration, backwash, chemical cleaning) based on real-time conditions. This replaces static conservative control with adaptive dynamic control that optimizes energy consumption while maintaining reliability.
Solution Approach 2:
The system employs feedback control by monitoring water quality parameters and using this information to determine when to switch between operation modes. The controller receives feedback from sensors measuring turbidity, pH, temperature, and conductivity, then adjusts system operations accordingly to prevent membrane clogging while avoiding unnecessary energy-consuming operations during stable conditions.
2Duration of action of stationary object
If conservative control strategies are used to prevent membrane clogging, then membrane lifespan is improved, but operational efficiency deteriorates
Solution Approach 1:
The system performs preliminary backwashing operations when water quality parameters indicate approaching clogging thresholds, preventing severe membrane fouling before it occurs. This proactive approach extends membrane lifespan while avoiding the need for frequent intensive chemical cleanings, thereby improving operational efficiency.
Solution Approach 2:
The patent changes operational parameters dynamically based on water quality conditions. When water quality deteriorates (increased turbidity, pH, temperature, or conductivity), the system automatically adjusts to more frequent backwashing and chemical cleaning cycles. When water quality is stable, the system operates at higher productivity with reduced maintenance frequency, optimizing both membrane lifespan and operational efficiency.
3Device complexity
If fixed operation modes are used based on initial water quality conditions, then system simplicity is maintained, but adaptability to changing water quality deteriorates
Solution Approach 1:
The system performs self-service by automatically monitoring its own performance parameters (water quality, flux, pressure differential) and making self-adjustments without external intervention. The controller autonomously determines when to switch between filtration, backwash, and chemical cleaning modes based on real-time sensor data, providing adaptability while maintaining operational simplicity from the user perspective.
Solution Approach 2:
The patent implements a universal control system that handles multiple functions: monitoring water quality parameters, controlling filtration operation, managing backwashing cycles, and scheduling chemical cleaning. This multi-functional approach provides adaptability to various water quality conditions while presenting a simple unified interface for operation and maintenance.
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 approach allows for more efficient water treatment by optimizing permeation flux and cleaning schedules, reducing energy consumption and membrane clogging, and adapting to changing water quality conditions, thereby improving the overall operational efficiency and cost-effectiveness of the water treatment process.
Implementation Method 1
a membrane filtration device with a filtration membrane
Implementation Method 2
cleaning of the membrane is periodically performed
Data Source
AI summary
A support device includes an acquirer configured to acquire data indicating water quality information of water to be treated, a pressure to supply the water to be treated to a membrane filtration device, a transmembrane pressure at a filtration membrane, a permeation flux at the filtration membrane, a frequency and cleaning conditions for cleaning the filtration membrane with cleaning water, and an outputter configured to output an optimum value of a current permeation flux, and a frequency and cleaning conditions for cleaning the membrane filtration device with the cleaning water in the future based on the data indicating the water quality information of the water to be treated, the pressure to supply the water to be treated to the membrane filtration device, and the transmembrane pressure at the filtration membrane, that have been acquired by the acquirer, by using a learned determination model acquired by performing learning processing using the data acquired by the acquirer.