Swimming pool water circulation filtration and energy consumption optimization control method and system

Abstract

The invention relates to a swimming pool water circulation filtration and energy consumption optimization control method and system, and belongs to the field of energy consumption control. The method comprises the following steps: acquiring swimming pool data, and constructing a three-dimensional water age field by establishing a water age field control equation; carrying out coupling transmission prediction based on the three-dimensional water age field, and outputting a pollutant concentration prediction map and a disinfectant concentration prediction map; a directional circulation strategy is generated based on the three-dimensional water age field, and optimized circulation system control parameters are obtained; on the basis of a directional circulation strategy, a pollutant concentration prediction map and a disinfectant concentration prediction map are combined, a disinfectant adding and water supplementing strategy is further optimized, and a comprehensive control instruction is output; and executing the comprehensive control instruction and carrying out real-time adaptive correction and learning optimization. According to the intelligent control method based on three-dimensional water age field modeling, coupling transmission prediction and multi-objective optimization, accurate, efficient and self-adaptive regulation and control of swimming pool water circulation and water quality management are achieved.

Description

A method and system for pool water circulation filtration and energy consumption optimization control Technical Field

[0001] This invention belongs to the field of energy consumption control technology, specifically relating to a method and system for pool water circulation filtration and energy consumption optimization control. Background Technology

[0002] Current swimming pool water circulation and water quality management technologies largely rely on fixed schedules or simple feedback control, such as timed start-stop of circulation pumps and targeted disinfectant addition based on residual chlorine sensors. While these methods can maintain basic water quality, they have significant shortcomings: First, the circulation system operates rigidly, unable to dynamically adjust according to the actual number of users, activity intensity, and water quality distribution, often leading to "circulation dead zones" in certain areas, resulting in water aging and contaminant accumulation. Second, disinfectant addition lacks spatial and temporal precision, often resulting in uneven distribution within the pool; excessive disinfectant in some areas may cause irritation, while insufficient disinfection in others poses hygiene risks. Third, energy consumption optimization is inadequate, with circulation pumps often operating at fixed power, leading to energy waste. Fourth, there is a lack of systematic modeling and control of "water age," a key indicator of water freshness, making it difficult to quantify and assess water renewal efficiency. Furthermore, existing systems mostly rely on localized point sensors, making it difficult to comprehensively perceive the three-dimensional water quality distribution and predict the dynamic processes of contaminant diffusion and disinfectant decay. Summary of the Invention

[0003] To address the aforementioned problems in the existing technology, this invention provides a method and system for pool water circulation filtration and energy consumption optimization control.

[0004] The objective of this invention can be achieved through the following technical solution: a swimming pool water circulation filtration and energy consumption optimization control method, the implementation of which includes the following steps: Step S1: Collecting pool data and constructing a three-dimensional water age field by establishing a water age field control equation; Step S2: Performing coupled transport prediction based on the three-dimensional water age field, and outputting a pollutant concentration prediction map and a disinfectant concentration prediction map; Step S3: Generating a directional circulation strategy based on the three-dimensional water age field, and obtaining optimized circulation system control parameters; Step S4: Based on the directional circulation strategy, and combining the pollutant concentration prediction map and the disinfectant concentration prediction map, further optimizing the disinfectant dosing and water replenishment strategy, and outputting a comprehensive control command; Step S5: Executing the comprehensive control command and performing real-time adaptive correction and learning optimization.

[0005] Preferably, the establishment of the water age field control equation in step S1 specifically involves: collecting pool data, including the pool's three-dimensional geometry, circulation system layout, current circulation pump operating status, and real-time monitoring data; discretizing the pool space to obtain multiple grid cells; and establishing the water age field control equation based on the pool data, mathematically described as follows: ,in, For grid cells At time t, For three-dimensional flow velocity, For the gradient of water age, The water age diffusion coefficient, The Laplace operator for water age is defined; boundary conditions are set; the governing equations of the water age field are discretized on each grid cell and solved iteratively to output the three-dimensional water age field.

[0006] Preferably, the coupled transport prediction in step S2 specifically involves: obtaining the current pollutant concentration distribution and the current disinfectant concentration distribution; obtaining a heat map of personnel activity; and establishing a water age-pollutant coupled transport equation, mathematically described as follows: ,in, For grid cells The pollutant concentration at time t, For three-dimensional flow velocity, For the gradient of pollutant concentrations, The pollutant diffusion coefficient, The Laplace operator for pollutant concentration, For the pollution source term, k is the basic rate constant of the disinfection reaction. For grid cells The disinfectant concentration at time t, The water age influence coefficient, The water age influence index, For reference water age, For grid cells Given a water age of time t, establish a water age-disinfectant coupled transport equation, mathematically described as follows: ,in, The diffusion coefficient of the disinfectant. To accelerate the dosing rate of disinfectant, This is the natural decay constant of the disinfectant. The coefficient representing the influence of water age on disinfectant consumption. The effect of water age on disinfectant consumption is defined as an index; by simultaneously solving the equations, the predicted pollutant concentration map and the predicted disinfectant concentration map are obtained, along with the updated three-dimensional water age field.

[0007] Preferably, the generation of the directional circulation strategy in step S3 specifically involves: obtaining the circulation dead zone risk index based on the three-dimensional water age field, mathematically described as follows: ,in, For grid cells The risk index of the cyclic dead zone at the location, For grid cells The age of the water at that location Steepness coefficient, The water age threshold is used; based on the aforementioned cycle dead zone risk index, an objective function is defined, mathematically described as follows: ,in, The objective function value, , and These are the weighting coefficients. The total volume of the swimming pool For the target water age gradient, The magnitude of the water age gradient, As a reference gradient, This represents the actual power of the water pump. The rated power of the water pump is given; based on the objective function, the optimized control parameters of the circulation system are obtained by combining the adjustable parameters of the current circulation system.

[0008] Preferably, the optimization of the disinfectant dosing and water replenishment strategy in step S4 specifically involves: acquiring current energy consumption data and adding equipment constraints; establishing a multi-objective optimization problem with the objectives of minimizing total energy consumption, minimizing maximum water age, and minimizing the volume of water exceeding standards; constraints including pollutant concentration not exceeding standards at all points, disinfectant concentration within a safe range, and the aforementioned equipment constraints; solving the multi-objective optimization problem using a multi-objective genetic algorithm to obtain a set of Pareto optimal solutions; and selecting the final execution scheme from the Pareto optimal solutions based on a comprehensive superiority index to obtain the comprehensive control command. The mathematical description of the comprehensive superiority index is... ,in, To assess the overall superiority index, , and These represent the minimum total energy consumption, minimum maximum water age, and minimum excess volume at the Pareto front. , and These are total energy consumption, maximum water age, and volume of water exceeding standards. , and These are the preference weights.

[0009] Preferably, step S5 specifically includes: real-time monitoring of sensor data, comparing the predicted pollutant concentration, disinfectant concentration, and water age distribution with the actual measured values, and calculating the error; correcting model parameters based on the error; and storing the current operating conditions and the final control strategy and its effects in the database.

[0010] A swimming pool water circulation filtration and energy consumption optimization control system, used to execute the swimming pool water circulation filtration and energy consumption optimization control method described above, includes a water age field construction module, a coupling transmission prediction module, a directional circulation module, a comprehensive control module, and an adaptive learning module. The water age field construction module collects swimming pool data and constructs a three-dimensional water age field by establishing water age field control equations. The coupling transmission prediction module performs coupling transmission prediction based on the three-dimensional water age field, outputting a pollutant concentration prediction map and a disinfectant concentration prediction map. The directional circulation module generates a directional circulation strategy based on the three-dimensional water age field, obtaining optimized circulation system control parameters. The comprehensive control module, based on the directional circulation strategy and combining the pollutant concentration prediction map and the disinfectant concentration prediction map, further optimizes the disinfectant dosing and water replenishment strategies, outputting comprehensive control commands. The adaptive learning module executes the comprehensive control commands and performs real-time adaptive correction and learning optimization.

[0011] The beneficial effects of the present invention are: (1) By establishing a water age field and a coupled transport model, the water quality distribution of the entire pool can be predicted and visualized in real time, the dead zone of circulation can be identified and optimized, and the water renewal efficiency and water quality uniformity can be significantly improved.

[0012] (2) Through the directional circulation strategy and intelligent dosing control, the multi-objective synergistic optimization of energy consumption and water quality is achieved. Under the premise of ensuring that the pollutant concentration does not exceed the standard and the disinfectant is within the safe range, the comprehensive energy consumption of the circulation pump, disinfection system and water replenishment treatment is effectively reduced, so as to achieve the purpose of energy saving and consumption reduction.

[0013] (3) By dynamically predicting the distribution of pollutants and disinfectants, we can provide early warning of water quality risk areas and achieve precise and on-demand addition of disinfectants to avoid excessively high or insufficient local concentrations and protect the health of swimmers. Attached Figure Description

[0014] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0015] Figure 1 is a flowchart of the steps of a swimming pool water circulation filtration and energy consumption optimization control method according to the present invention. Detailed Implementation

[0016] To better understand the invention, various aspects of the invention will be described in more detail with reference to the accompanying drawings. It should be understood that these detailed descriptions are merely illustrative of exemplary embodiments of the invention and are not intended to limit the scope of the invention in any way. Throughout the specification, the expression "and / or" includes any and all combinations of one or more of the associated listed items. As used herein, the terms "approximately," "about," and similar terms are used as expressions of approximation, not as expressions of degree, and are intended to describe inherent deviations in measured or calculated values ​​that will be recognized by those skilled in the art. Furthermore, the order in which the steps are described in this invention does not necessarily indicate the order in which these steps occur in actual operation, unless otherwise expressly defined or deduced from the context.

[0017] It should also be understood that expressions such as "comprising," "including," "having," "containing," and / or "comprising" are open-ended rather than closed-ended expressions in this specification, indicating the presence of the stated features, elements, and / or components, but not excluding the presence of one or more other features, elements, components, and / or combinations thereof. Furthermore, when expressions such as "at least one of..." appear after a list of listed features, they modify the entire list of features, not just individual elements in the list. Additionally, when describing embodiments of the invention, the word "may" is used to mean "one or more embodiments of the invention." And the term "exemplary" is intended to refer to examples or illustrations.

[0018] Unless otherwise specified, all terms used herein (including engineering and technical terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that, unless expressly stated herein, terms defined in common dictionaries shall be interpreted as having the meaning consistent with their meaning in the context of the relevant art, and not in an idealized or overly formalized sense.

[0019] It should be noted that, unless otherwise specified, the embodiments and features described in this invention can be combined with each other. The invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0020] Example 1: Please refer to Figure 1. A swimming pool water circulation filtration and energy consumption optimization control method includes: Step S1: Collecting pool data and constructing a three-dimensional water age field by establishing a water age field control equation; Step S2: Performing coupled transport prediction based on the three-dimensional water age field, and outputting a pollutant concentration prediction map and a disinfectant concentration prediction map; Step S3: Generating a directional circulation strategy based on the three-dimensional water age field, obtaining optimized circulation system control parameters, identifying circulation dead zones, and optimizing the operating parameters of the circulation system (such as pump speed and outlet direction) to improve water age distribution; Step S4: Based on the directional circulation strategy, combining the pollutant concentration prediction map and the disinfectant concentration prediction map, further optimizing the disinfectant dosing and water replenishment strategy to achieve a balance between the three objectives of energy consumption, maximum water age, and water quality exceeding the standard volume, and outputting a set of comprehensive control commands; Step S5: Executing the comprehensive control commands and performing real-time adaptive correction and learning optimization.

[0021] In this embodiment, the establishment of the water age field control equation is specifically as follows: S101: Collect the pool data, which includes the three-dimensional geometry of the pool, the layout of the circulation system (position, number, and size of the inlet and outlet), the current operating status of the circulation pump (pump speed or frequency, flow rate), and real-time monitoring data (water flow sensors are installed at multiple locations in the pool to measure flow velocity and direction; if no sensors are available, simulation calculations can be performed); S102: Discretize the pool space by dividing the pool into multiple cubes to obtain multiple grid cells; S103: Establish the water age field control equation based on the pool data, mathematically described as follows: ,in, For grid cells The water age at time t represents the time elapsed from when the water entered the pool to its current position. Three-dimensional flow velocity (e.g., meters per second) represents the speed at which water flows in the pool. The gradient of water age represents the rate of change of water age in space (e.g., hours / meter). The water age diffusion coefficient (e.g., in meters) 2 ( / second), indicating the degree of diffusion caused by turbulent mixing and other factors due to water age. Let be the Laplace operator for water age, and let represent the gradient of the water age gradient. S104: Set boundary conditions, setting the water age to 0 at the inlet; and setting the water age to not change through these boundaries at the pool walls, bottom, and surface. S105: Discretize the water age field control equations on each grid cell and solve them iteratively, outputting the three-dimensional water age field to display the water age of each area of ​​the pool. For example, the water age is smaller (fresher) in the area near the inlet, while the water age is larger (older) in the dead zone area far from the inlet.

[0022] In this embodiment, the coupled transport prediction specifically involves: S201: obtaining the current pollutant concentration distribution (e.g., total bacterial count, turbidity, etc.) and the current disinfectant concentration distribution (e.g., residual chlorine concentration) through multi-point water quality sensors; S202: identifying the number of people, their locations, and activity intensity in the pool using a camera to obtain a heat map of human activity and estimate the source of pollutant release; S203: establishing a water age-pollutant coupled transport equation, mathematically described as... ,in, For grid cells The concentration of pollutants (e.g., mg / L) at time t. For three-dimensional flow velocity, This represents the gradient of pollutant concentrations (e.g., mg / m·L). The pollutant diffusion coefficient (e.g., meter) 2 / Second), The Laplace operator for pollutant concentration, For pollution source terms (e.g., mg / L·s), it represents the increase in pollutant concentration per unit time and unit volume, which is proportional to population density and activity intensity. k is the basic rate constant for disinfection reaction (e.g., L / mg·s). For grid cells The concentration of disinfectant at time t (e.g., mg / L). The water age influence coefficient represents the strength of the effect of water age on disinfectant efficiency. The water age impact index represents the degree of non-linearity of the water age's influence. For reference water age, For grid cells At time t, the water age; S204: Establish the water age-disinfectant coupled transport equation, mathematically described as follows: ,in, Disinfectant diffusion coefficient (e.g., meter) 2 / Second), The dosing rate of disinfectant (e.g., mg / L·second). This is the natural decay constant of the disinfectant (e.g., 1 / second). The coefficient representing the influence of water age on disinfectant consumption. S205: Simultaneously solve the prediction to obtain the pollutant concentration prediction map and the disinfectant concentration prediction map, as well as the updated three-dimensional water age field (updated through simple time progression).

[0023] In this embodiment, the generation of the directional circulation strategy specifically involves: S301: obtaining the circulation dead zone risk index based on the three-dimensional water age field, mathematically described as follows: ,in, For grid cells The risk index of the cyclic dead zone at the location, For grid cells The age of the water at that location The steepness coefficient (e.g., 1 / hour). The water age threshold is defined; when the water age exceeds this value, the risk of dead zones increases significantly. S302: Based on the aforementioned dead zone risk index, an objective function is defined. By adjusting the control parameters of the circulation system (e.g., outlet direction angle, flow distribution ratio, main pump frequency), the total volume of the dead zone is minimized, the water age distribution is more uniform, and energy consumption is minimized. Mathematically, this is described as... ,in, The objective function value, , and These are the weighting coefficients. The total volume of the swimming pool For the target water age gradient, The magnitude of the water age gradient (indicating the degree of drastic change in water age; areas with large gradients are usually the boundary between active and stagnant water zones). As a reference gradient, This represents the actual power of the water pump. The rated power of the water pump; constraints include the pump's frequency range, valve opening range, etc.; S303: Based on the objective function, combined with the adjustable parameters of the current circulation system (such as the current frequency of the variable frequency pump, the current angle of the adjustable directional outlet, etc.), the optimized circulation system control parameters are obtained.

[0024] In this embodiment, the optimization of the disinfectant dosing and water replenishment strategy is specifically as follows: S401: Obtain current energy consumption data and add equipment constraints, such as the maximum and minimum dosing acceleration rate of the disinfectant dosing system, the opening range of the water replenishment valve, etc.; S402: Establish a multi-objective optimization problem, with the objectives being to minimize total energy consumption (including pump energy consumption, disinfection system energy consumption, and water replenishment treatment energy consumption), minimize the maximum water age (i.e., the maximum water age in the entire pool, reflecting the freshness of the worst area), and minimize the volume of water exceeding the standard (i.e., the volume of the area where the pollutant concentration exceeds the standard); the constraints are that the pollutant concentration does not exceed the standard at any point, the disinfectant concentration is within the safe range, and the equipment constraints; S403: Use a multi-objective genetic algorithm to solve the multi-objective optimization problem and obtain a set of Pareto optimal solutions, each solution being a set of control decisions; S404: Select the final execution scheme from the Pareto optimal solutions based on the comprehensive superiority index to obtain the comprehensive control instructions (dosing acceleration rate at each dosing point, opening of the water replenishment valve, and water replenishment time curve, etc.), the mathematical description of the comprehensive superiority index is... ,in, To assess the overall superiority index, , and These represent the minimum total energy consumption, minimum maximum water age, and minimum excess volume at the Pareto front. , and These are total energy consumption, maximum water age, and volume of water exceeding standards. , and The weights represent the preference weights, indicating the degree of importance that decision-makers attach to energy consumption, water age, and water quality, respectively.

[0025] In this embodiment, step S5 can be implemented through the following steps: S501: Monitor sensor data in real time, compare the predicted pollutant concentration, disinfectant concentration, and water age distribution with the actual measured values, and calculate the error; S502: Correct model parameters based on the error, and correct the water age diffusion coefficient, pollutant diffusion coefficient, disinfectant diffusion coefficient, and water age influence coefficient, etc.; S503: Store the current operating conditions (such as number of people, weather, season) and the final control strategy and its effects (energy consumption, water quality indicators) in the database. When similar operating conditions occur again, directly call the historical optimal strategy from the database as the initial value for optimization to accelerate the optimization process.

[0026] Example 2: A swimming pool water circulation filtration and energy consumption optimization control system, comprising a water age field construction module, a coupling transmission prediction module, a directional circulation module, a comprehensive control module, and an adaptive learning module; the water age field construction module is used to collect pool data and construct a three-dimensional water age field by establishing a water age field control equation; the coupling transmission prediction module is used to perform coupling transmission prediction based on the three-dimensional water age field, and output pollutant concentration prediction maps and disinfectant concentration prediction maps; the directional circulation module is used to generate a directional circulation strategy based on the three-dimensional water age field, obtain optimized circulation system control parameters, identify circulation dead zones, and optimize the operating parameters of the circulation system (such as pump speed and outlet direction) to improve water age distribution; the comprehensive control module is used to further optimize disinfectant dosing and water replenishment strategies based on the directional circulation strategy and in combination with the pollutant concentration prediction maps and the disinfectant concentration prediction maps, to achieve a balance between the three objectives of energy consumption, maximum water age, and water quality exceeding standards, and output a set of comprehensive control commands; the adaptive learning module is used to execute the comprehensive control commands and perform real-time adaptive correction and learning optimization.

[0027] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for pool water circulation filtration and energy consumption optimization control, characterized in that, The process includes the following steps: Step S1: Collect pool data and construct a three-dimensional water age field by establishing a water age field control equation; Step S2: Perform coupled transport prediction based on the three-dimensional water age field, and output a pollutant concentration prediction map and a disinfectant concentration prediction map; Step S3: Generate a directional circulation strategy based on the three-dimensional water age field to obtain optimized circulation system control parameters; Step S4: Based on the directional circulation strategy, combine the pollutant concentration prediction map and the disinfectant concentration prediction map to further optimize the disinfectant dosing and water replenishment strategy, and output a comprehensive control command; Step S5: Execute the comprehensive control command and perform real-time adaptive correction and learning optimization.

2. The swimming pool water circulation filtration and energy consumption optimization control method according to claim 1, characterized in that, The establishment of the water age field control equation in step S1 specifically involves: collecting pool data, including the pool's three-dimensional geometry, circulation system layout, current circulation pump operating status, and real-time monitoring data; discretizing the pool space to obtain multiple grid cells; and establishing the water age field control equation based on the pool data, mathematically described as follows: ,in, For grid cells At time t, For three-dimensional flow velocity, For the gradient of water age, The water age diffusion coefficient, The Laplace operator for water age is defined; boundary conditions are set; the governing equations of the water age field are discretized on each grid cell and solved iteratively to output the three-dimensional water age field.

3. The swimming pool water circulation filtration and energy consumption optimization control method according to claim 1, characterized in that, The coupled transport prediction in step S2 specifically involves: obtaining the current pollutant concentration distribution and the current disinfectant concentration distribution; obtaining a heat map of human activity; and establishing a water age-pollutant coupled transport equation, mathematically described as follows: ,in, For grid cells The pollutant concentration at time t, For three-dimensional flow velocity, For the gradient of pollutant concentrations, The pollutant diffusion coefficient, The Laplace operator for pollutant concentration, For the pollution source term, k is the basic rate constant of the disinfection reaction. For grid cells The disinfectant concentration at time t, The water age influence coefficient, The water age influence index, For reference water age, For grid cells Given a water age of time t, establish a water age-disinfectant coupled transport equation, mathematically described as follows: ,in, The diffusion coefficient of the disinfectant. To accelerate the dosing rate of disinfectant, This is the natural decay constant of the disinfectant. The coefficient representing the influence of water age on disinfectant consumption. The effect of water age on disinfectant consumption is defined as an index; by simultaneously solving the equations, the predicted pollutant concentration map and the predicted disinfectant concentration map are obtained, along with the updated three-dimensional water age field.

4. The swimming pool water circulation filtration and energy consumption optimization control method according to claim 1, characterized in that, The generation of the directional circulation strategy in step S3 specifically involves: obtaining the circulation dead zone risk index based on the three-dimensional water age field, mathematically described as follows: ,in, For grid cells The risk index of the cyclic dead zone at the location, For grid cells The age of the water at that location Steepness coefficient, The water age threshold is used; based on the aforementioned cycle dead zone risk index, an objective function is defined, mathematically described as follows: ,in, The objective function value, 、 and These are the weighting coefficients. The total volume of the swimming pool For the target water age gradient, The magnitude of the water age gradient, As a reference gradient, This represents the actual power of the water pump. The rated power of the water pump is given; based on the objective function, the optimized control parameters of the circulation system are obtained by combining the adjustable parameters of the current circulation system.

5. The swimming pool water circulation filtration and energy consumption optimization control method according to claim 1, characterized in that, The optimization of the disinfectant dosing and water replenishment strategy in step S4 specifically involves: acquiring current energy consumption data and adding equipment constraints; establishing a multi-objective optimization problem with the objectives of minimizing total energy consumption, minimizing maximum water age, and minimizing the volume of water exceeding the standard; and the constraints being that the pollutant concentration does not exceed the standard at any point, the disinfectant concentration is within a safe range, and the equipment constraints; and using a multi-objective genetic algorithm to solve the multi-objective optimization problem to obtain a set of Pareto optimal solutions. The final execution scheme is selected from the Pareto optimal solution based on the comprehensive superiority index, resulting in the comprehensive control command. The mathematical description of the comprehensive superiority index is... ,in, To assess the overall superiority index, 、 and These represent the minimum total energy consumption, minimum maximum water age, and minimum excess volume at the Pareto front. 、 and These are total energy consumption, maximum water age, and volume of water exceeding standards. 、 and These are the preference weights.

6. The swimming pool water circulation filtration and energy consumption optimization control method according to claim 1, characterized in that, Step S5 specifically includes: real-time monitoring of sensor data, comparing the predicted pollutant concentration, disinfectant concentration, and water age distribution with the actual measured values, and calculating the error; correcting model parameters based on the error; and storing the current operating conditions and the final control strategy and its effects in the database.

7. A swimming pool water circulation filtration and energy consumption optimization control system, characterized in that, The system is applied to the swimming pool water circulation filtration and energy consumption optimization control method as described in any one of claims 1-6, and includes a water age field construction module, a coupling transport prediction module, a directional circulation module, a comprehensive control module, and an adaptive learning module. The water age field construction module is used to collect swimming pool data and construct a three-dimensional water age field by establishing a water age field control equation. The coupling transport prediction module is used to perform coupling transport prediction based on the three-dimensional water age field and output a pollutant concentration prediction map and a disinfectant concentration prediction map. The directional circulation module is used to generate a directional circulation strategy based on the three-dimensional water age field and obtain optimized circulation system control parameters. The comprehensive control module is used to further optimize the disinfectant dosing and water replenishment strategies based on the directional circulation strategy and in combination with the pollutant concentration prediction map and the disinfectant concentration prediction map, and output a comprehensive control command. The adaptive learning module is used to execute the comprehensive control command and perform real-time adaptive correction and learning optimization.

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