Automated Pump Shutdown via Clogging Risk Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for managing clogging in water supply systems for power generation plants, particularly nuclear power plants, rely on human operators to decide when to stop pumping devices due to excessive pressure drops, which can lead to equipment damage and inefficient shutdowns, lacking objective risk assessment and automation.
Innovation Solution
A method using a statistical model, such as the Parzen method, that incorporates hydrological, meteorological, and clogging parameters to predict clogging risks, enabling automated decision-making for pump device shutdown and providing objective risk assessment, including a warning system and automated deactivation of the pump device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human operators manually decide when to stop the pumping device, then operational flexibility is maintained, but decision objectivity and timeliness deteriorate due to lack of automated risk assessment
Solution Approach 1:
The patent replaces manual human decision-making with an automated computer-based system that processes hydrological, meteorological, and clogging parameters through statistical models (such as the Parzen method) to objectively determine when pump shutdown is necessary, eliminating subjectivity while maintaining operational control
Solution Approach 2:
The system enables self-monitoring and self decision-making capabilities by continuously collecting data from multiple sensors, analyzing clogging risks through statistical models, and automatically generating shutdown recommendations without requiring constant human intervention, allowing the system to manage itself based on objective criteria
2Productivity
If the pumping device operates continuously without automated shutdown, then productivity is maintained, but equipment damage risk increases due to excessive clogging
Solution Approach 1:
The system performs preliminary risk assessment by continuously analyzing hydrological parameters, meteorological conditions, and real-time clogging data to predict future clogging events before they cause equipment damage, enabling proactive shutdown decisions that prevent harmful outcomes while maintaining productivity during safe operating periods
Solution Approach 2:
The system establishes continuous feedback loops by monitoring pressure differentials across filter drums, collecting clogging event data, and using this information to refine statistical models and improve future shutdown recommendations, creating a self-improving system that reduces equipment damage risk while optimizing productivity
3Reliability
If filter drums are used to remove clogging elements, then water quality is improved, but system complexity increases due to additional filtering components
Solution Approach 1:
The patent makes the filter drums perform multiple functions: they not only filter clogging elements from water but also serve as sensors for measuring pressure differentials that indicate clogging levels, and their rotation mechanisms provide both cleaning functionality and data collection for the statistical model, reducing the need for separate monitoring systems
Solution Approach 2:
The statistical model acts as an intermediary that synthesizes data from multiple sources (hydrological parameters, meteorological conditions, pressure differentials across filters) to produce integrated shutdown recommendations, simplifying the complexity by providing a single decision output rather than requiring manual analysis of multiple separate systems
4Loss of energy
If pump shutdown is delayed until excessive clogging occurs, then energy loss is reduced, but equipment damage risk increases
Solution Approach 1:
The system performs preliminary risk assessment by continuously analyzing hydrological parameters, meteorological conditions, and real-time clogging data to predict future clogging events before they cause equipment damage, enabling proactive shutdown decisions that prevent harmful outcomes while maintaining productivity during safe operating periods
Solution Approach 2:
The system uses parameter changes in hydrological conditions (such as tidal coefficients, river flow rates, water heights) and meteorological factors to predict when clogging risk will increase, allowing shutdown decisions to be made at optimal moments that balance energy efficiency with equipment protection rather than relying on fixed thresholds
Data Source
Figure 1
Figure 2
Figure 3~5
AI summary
The invention relates to a method for assisting with the management of a pumping device capable of supplying an electricity production plant circuit with water taken from a natural watercourse, the water upstream of the circuit containing materials liable to clog one or more filters provided at the inlet of the circuit. In particular, at least parameters relating to the watercourse and that have an influence on the quantity of materials liable to clog the said filters is recorded, and: – during a previous step, a statistical model (S2) is produced based on historical data of said parameters relating to the watercourse in respect of which clogging of the filters has been observed,– During a current step, current parameters relating at least to the watercourse are recorded and the said statistical model is used in conjunction with the said current parameters to evaluate a risk of arrival of clogging materials (S6), and – According to the evaluated risk, an alert signal is generated to deactivate the pumping device at a chosen moment (S7).