Urban green space runoff interception and discharge method, device, electronic equipment and storage medium

Abstract

The present application provides a method, device, electronic device and storage medium for intercepting and discharging runoff pollution in urban green space, which relates to the technical field of urban water environment governance. The key points of its technical solution are: obtaining real-time pollutant concentration data and water flow velocity field data collected by monitoring nodes on preset paths; identifying multiple potential pollution source areas; calculating pollution source coordinates and diffusion trends; generating a timing control strategy for the opening and closing of the pollution interception valve, and controlling the opening and closing of the pollution interception valve according to the timing control strategy, and the timing control strategy includes relay diversion parameters of adjacent valves; when the pollutant concentration data shows that the pollutant concentration exceeds the threshold, the mobile emergency treatment unit is started according to the timing control strategy to perform multi-stage treatment of the polluted water body. The method, device, electronic device and storage medium for intercepting and discharging runoff pollution in urban green space provided by the present application have the advantages of being able to quickly identify and accurately locate dynamically changing pollution sources, and achieve effective pollution interception and treatment.

Description

Technical Field

[0001] The present application relates to the technical field of urban water environment management, and in particular to a method, device, electronic device and storage medium for intercepting and discharging runoff from urban green spaces. Background Art

[0002] In the rainstorm management scenario of large parks in smart cities, especially during large-scale outdoor events such as music festivals, the existing stormwater runoff treatment system faces huge challenges. The distribution of pollutants generated by sudden large-scale human flows and activities is highly dynamic, and traditional fixed monitoring wells and static sewage interception facilities are difficult to cope with such complex situations.

[0003] The existing system has the following main problems:

[0004] Insufficient monitoring coverage and large spacing between fixed monitoring points make it difficult to capture sudden pollution spread around ecological protection areas. This leads to inaccurate judgments on pollutant spread trends and inability to take effective pollution interception measures in a timely manner.

[0005] The pollution source is not accurately located, and it is impossible to accurately track dynamic pollution sources such as those generated by temporary dining areas at music festivals. This makes it difficult to control the source of pollutants and increases the burden of downstream treatment.

[0006] The pollution interception response is delayed, and the fixed sewage interception gates cannot respond to the changing distribution of pollutants in time. This may cause pollutants to spread rapidly to a wider area, increasing the difficulty and cost of treatment.

[0007] In this case, how to quickly identify, accurately locate and effectively treat dynamically changing pollutants without affecting the normal activities of the park, while ensuring that the treated water quality meets the strict requirements of the ecological protection area, has become a technical problem that needs to be solved urgently.

[0008] In view of the above problems, the existing technology needs to be improved urgently. Summary of the invention

[0009] The purpose of the present application is to provide a method, device, electronic equipment and storage medium for intercepting and discharging runoff pollution in urban green spaces, which has the advantages of being able to quickly identify and accurately locate dynamically changing pollution sources, and achieve effective pollution interception and treatment.

[0010] This application provides a method for intercepting and discharging runoff from urban green spaces, and the technical solution is as follows:

[0011] The method comprises the following steps: obtaining real-time pollutant concentration data and water flow velocity field data collected by monitoring nodes on a preset path; identifying multiple potential pollution source areas using a density clustering algorithm based on the pollutant concentration data; establishing a pollution diffusion optimization model for each identified pollution source area based on the water flow velocity field data, and calculating the pollution source coordinates and diffusion trends; generating a timing control strategy for opening and closing of a sewage interception valve based on the pollution source coordinates and diffusion trends, and controlling the opening and closing of the sewage interception valve according to the timing control strategy, wherein the timing control strategy includes relay diversion parameters of adjacent valves; when the pollutant concentration data shows that the pollutant concentration exceeds a threshold value, starting a mobile emergency treatment unit according to the timing control strategy, and performing multi-stage treatment of the polluted water body, wherein the treatment intensity and combination of the multi-stage treatment are adjusted according to the pollutant concentration and the treatment target.

[0012] Furthermore, the present application also proposes that, for each identified pollution source area, based on the water flow velocity field data, a pollution diffusion optimization model is established, and the steps of calculating the pollution source coordinates and the diffusion trend include: for each identified pollution source area, obtaining the terrain data and obstacle distribution data of the pollution source area; based on the water flow velocity field data, terrain data and obstacle distribution data, establishing a pollution diffusion optimization model that takes into account the influence of terrain and obstacles; according to the pollution diffusion optimization model, calculating the pollution source coordinates; based on the pollution source coordinates and the pollution diffusion optimization model, calculating the diffusion speed and direction of pollutants in different areas to obtain the diffusion trend.

[0013] Furthermore, the present application also proposes that the step of generating a timing control strategy for the opening and closing of the sewage interception valves according to the pollution source coordinates and the diffusion trend includes: calculating the estimated time for pollutants to reach each sewage interception valve according to the pollution source coordinates and the diffusion trend; generating an opening time sequence of the sewage interception valves based on the estimated time, wherein the opening time of the sewage interception valve located upstream is earlier than the opening time of the sewage interception valve located downstream; calculating the opening adjustment parameters of each sewage interception valve according to the pollution source coordinates and the diffusion trend; and generating the timing control strategy based on the opening time sequence and the opening adjustment parameters.

[0014] Furthermore, the present application also proposes that the steps of generating the timing control strategy based on the opening time sequence and the opening adjustment parameters include: calculating the time difference threshold that meets the requirements of continuous diversion of pollutants based on the spacing between adjacent sewage interception valves and water flow velocity field data; adjusting the opening interval of adjacent valves in the opening time sequence based on the time difference threshold; establishing opening adjustment constraints according to the valve topological relationship, and generating opening gradient parameters of adjacent valves according to the opening adjustment constraints and the opening adjustment parameters; calculating the relay diversion parameters that form a pressure gradient based on the opening gradient parameters and the pollutant diffusion trend; integrating the time difference threshold, opening gradient parameters and relay diversion parameters to generate the timing control strategy.

[0015] Furthermore, the present application also proposes that when the pollutant concentration data shows that the pollutant concentration exceeds the threshold, the mobile emergency treatment unit is started according to the timing control strategy to perform multi-stage treatment of the polluted water body, and the treatment intensity and combination method of the multi-stage treatment are adjusted according to the pollutant concentration and the treatment target. The steps include: when the judgment result is that the pollutant concentration exceeds the threshold, obtaining the pollutant type information in the pollutant concentration data; according to the pollutant type information, selecting the corresponding treatment unit combination from the preset treatment unit library; based on the pollutant diffusion trend in the timing control strategy, calculating the optimal deployment position of the mobile emergency treatment unit composed of the corresponding treatment unit combination; controlling the mobile emergency treatment unit to move to the optimal deployment position; dynamically adjusting the treatment intensity of each treatment unit according to the real-time monitored influent pollutant concentration and the predetermined treatment target; when the effluent water quality reaches the treatment target, introducing the treated water body into the ecological protection area.

[0016] Furthermore, the present application also proposes that when the effluent water quality reaches the treatment target, the step of introducing the treated water into the ecological protection zone includes: during the operation of the mobile emergency treatment unit, when it is detected that the actual treatment time exceeds the preset threshold and the effluent water quality deviation value exceeds the first threshold, based on the current pollutant diffusion trend and the pipe network topology data, the optimal deployment position of the treatment unit and the corresponding multi-stage treatment combination parameters are recalculated; according to the multi-stage treatment combination parameters, the backup treatment resources are activated and enhanced treatment instructions are generated, and the enhanced treatment instructions include a treatment intensity correction coefficient dynamically adjusted based on the interference level of park activities; the processing unit is controlled to move to the updated deployment position to execute the enhanced treatment instructions until the effluent water quality reaches the treatment target and is injected into the ecological protection zone.

[0017] Furthermore, the present application also proposes that the steps of establishing opening adjustment constraints according to the valve topological relationship and generating opening gradient parameters of adjacent valves according to the opening adjustment constraints and the opening adjustment parameters include: acquiring vibration sensor data and pipeline pressure data of adjacent valves according to the valve topological relationship; judging the location of the park activity area according to the vibration sensor data, and generating activity interference constraints for valve opening based on the location; calculating the pressure difference between adjacent valves based on the pipeline pressure data, and generating pressure balance constraints for valve opening; using the activity interference constraints and the pressure balance constraints as the opening adjustment constraints; and generating opening gradient parameters of the adjacent valves according to the opening adjustment constraints and the opening adjustment parameters.

[0018] Furthermore, the present application also proposes an urban green space runoff sewage interception and discharge device, comprising: an acquisition module, used to obtain real-time pollutant concentration data and water flow velocity field data collected by monitoring nodes on a preset path; an identification module, used to identify multiple potential pollution source areas based on the pollutant concentration data using a density clustering algorithm; a calculation module, used to establish a pollution diffusion optimization model for each identified pollution source area based on the water flow velocity field data, and calculate the pollution source coordinates and diffusion trends; a first control module, used to generate a timing control strategy for the opening and closing of the sewage interception valve based on the pollution source coordinates and diffusion trends, and control the opening and closing of the sewage interception valve according to the timing control strategy, and the timing control strategy includes relay diversion parameters of adjacent valves; a second control module, used to start a mobile emergency treatment unit according to the timing control strategy when the pollutant concentration data shows that the pollutant concentration exceeds a threshold, and perform multi-stage treatment of the polluted water body, and the treatment intensity and combination method of the multi-stage treatment are adjusted according to the pollutant concentration and treatment objectives.

[0019] Furthermore, the present application also proposes an electronic device, including a processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the above method are executed.

[0020] Furthermore, the present application also proposes a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps in the above method are executed.

[0021] From the above, it can be seen that the present application provides a method, device, electronic equipment and storage medium for intercepting and discharging urban green space runoff. By acquiring real-time pollutant concentration data and water flow velocity field data, a density clustering algorithm is used to identify multiple potential pollution source areas, and a pollution diffusion optimization model is established to calculate the pollution source coordinates and diffusion trends. A timing control strategy for the opening and closing of the sewage interception valve is generated, and a mobile emergency treatment unit is started to perform multi-stage processing when the pollutant concentration exceeds the threshold, thereby being able to quickly identify and accurately locate dynamically changing pollution sources and achieve effective pollution interception and treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A schematic flow chart of a method for intercepting and discharging runoff from urban green spaces provided in this application.

[0023] Figure 2 A schematic diagram of the structure of an urban green space runoff interception and discharge device provided in this application.

[0024] In the figure: 210, acquisition module; 220, identification module; 230, calculation module; 240, first control module; 250, second control module. DETAILED DESCRIPTION

[0025] The technical solutions in the present application will be clearly and completely described below in conjunction with the drawings in the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the present application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0026] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0027] In the rainstorm management scenario of large urban parks, especially during large outdoor events such as music festivals, the existing rainwater runoff treatment system faces huge challenges. Traditional fixed monitoring wells and static sewage interception facilities are difficult to cope with the highly dynamic distribution of pollutants generated by sudden large-scale human flows and activities. This application aims to solve the technical problems of real-time monitoring, precise positioning and effective treatment of dynamically changing pollutants in urban green space runoff.

[0028] Specifically, the existing system has obvious deficiencies in monitoring coverage, pollution source location, interception response, water quality testing, flexibility of treatment facilities, and activity interference. The fixed monitoring points are too far apart to capture sudden pollution spread around ecological protection areas. It is impossible to accurately track dynamic pollution sources such as those generated by temporary dining areas at music festivals. Fixed sewage interception gates cannot respond to rapidly changing pollutant distributions in a timely manner. Reliance on laboratory analysis leads to delays in water quality testing and the inability to verify treatment effects in real time. The treatment facilities are fixed and it is difficult to respond to mobile pollution events. In addition, pollution treatment measures may affect ongoing outdoor activities. These problems seriously affect the system's real-time response capabilities, processing accuracy, and overall efficiency.

[0029] In this regard, refer to Figure 1 The present application proposes a method for intercepting and discharging runoff from urban green space, which comprises the following steps:

[0030] S110, obtaining real-time pollutant concentration data and water flow velocity field data collected by the monitoring node on the preset path;

[0031] S120, using density clustering algorithm to identify multiple potential pollution source areas based on pollutant concentration data;

[0032] S130, for each identified pollution source area, based on the water flow velocity field data, establish a pollution diffusion optimization model, and calculate the pollution source coordinates and diffusion trend;

[0033] S140, generating a timing control strategy for opening and closing the sewage interception valve according to the pollution source coordinates and diffusion trend, and controlling the opening and closing of the sewage interception valve according to the timing control strategy, wherein the timing control strategy includes relay diversion parameters of adjacent valves;

[0034] S150. When the pollutant concentration data shows that the pollutant concentration exceeds the threshold, the mobile emergency treatment unit is started according to the timing control strategy to perform multi-stage treatment of the polluted water body. The treatment intensity and combination of the multi-stage treatment are adjusted according to the pollutant concentration and the treatment target.

[0035] Among them, the monitoring node refers to a device that can move on a preset path and collect data, which can be specifically implemented by an unmanned ship or underwater robot equipped with a water quality sensor and a GPS positioning system.

[0036] Among them, the density clustering algorithm refers to a density-based clustering method, which can be implemented by using the DBSCAN (density-based spatial clustering with applied noise) algorithm. This algorithm can identify clusters of any shape and is suitable for identifying irregularly distributed potential pollution source areas.

[0037] The pollution diffusion optimization model refers to a mathematical model that describes the diffusion behavior of pollutants in water bodies. It can be implemented using a two-dimensional convection-diffusion equation that takes into account the influence of water velocity field, terrain and obstacles. This model can accurately predict the diffusion trend of pollutants and provide support for the precise positioning of pollution sources.

[0038] Among them, the timing control strategy refers to the control scheme for the opening and closing of the sewage interception valve generated according to the coordinates and diffusion trend of the pollution source. This strategy includes the relay diversion parameters of adjacent valves, which can achieve accurate and efficient pollutant interception.

[0039] Mobile emergency treatment units refer to portable water treatment equipment that can be quickly deployed, which can be implemented using vehicle-mounted treatment systems that integrate multi-stage treatment processes. These units can flexibly adjust the treatment intensity and combination according to the pollution situation, effectively responding to dynamically changing pollution events.

[0040] The core innovation of this application lies in real-time data collection through mobile monitoring nodes, rapid identification of pollution source areas through density clustering algorithms, accurate prediction of diffusion trends through pollution diffusion optimization models, dynamic adjustment of pollution interception plans through timing control strategies, and flexible response of mobile emergency treatment units to pollution incidents.

[0041] The working principle of this application can be described as follows:

[0042] First, the mobile monitoring node collects real-time pollutant concentration data and water flow velocity field data along the preset path. These data are uploaded to the central processing system in real time via wireless transmission. The system uses a density clustering algorithm to process pollutant concentration data and identify multiple potential pollution source areas. For each identified area, the system establishes a pollution diffusion optimization model based on the water flow velocity field data. The model takes into account the influence of terrain and obstacles, and can calculate the coordinates of pollution sources and predict diffusion trends.

[0043] Based on the calculated pollution source coordinates and diffusion trends, the system generates a timing control strategy for the opening and closing of the sewage interception valves. This strategy includes not only the opening time and opening degree of each valve, but also the relay diversion parameters of adjacent valves to achieve continuous interception of pollutants. According to this strategy, the opening and closing of the sewage interception valves are controlled to form a dynamically adjusted sewage interception network.

[0044] When the concentration of pollutants monitored exceeds the preset threshold, the optimal deployment location of the mobile emergency treatment unit is determined based on the information in the timing control strategy. These treatment units are quickly dispatched to the designated location, and the treatment intensity and combination are dynamically adjusted according to the real-time monitored pollutant concentration and treatment objectives. The treated water body is verified for water quality and introduced into the ecological protection area after meeting the standards.

[0045] As a preferred embodiment, the present application can be implemented in a city park. There are 20 fixed monitoring wells in the park, with a spacing of about 500 meters. In order to improve the monitoring coverage, 10 mobile monitoring nodes are deployed, each of which is equipped with a multi-parameter water quality sensor (which can simultaneously measure parameters such as pH, dissolved oxygen, conductivity, turbidity, etc.) and a GPS positioning system. These nodes are designed in the form of small unmanned boats that can autonomously navigate in the water bodies in the park.

[0046] The mobile monitoring node moves in the park water body along a preset path and collects data every 5 minutes. The collected data includes pollutant concentration (such as COD, ammonia nitrogen, total phosphorus, etc.) and water flow velocity field data. These data are transmitted to the central processing system in real time via the 5G network.

[0047] The central processing system uses the DBSCAN density clustering algorithm to process pollutant concentration data. The algorithm parameters are set as: ε (neighborhood radius) = 50 meters, MinPts (minimum number of points) = 5. With this setting, the system is able to identify potential pollution source areas with an area greater than 7850 square meters (π * 50^2).

[0048] For each identified pollution source area, a pollution diffusion optimization model based on the two-dimensional convection-diffusion equation was established. The model takes into account the terrain data (such as elevation changes) and obstacle distribution (such as buildings, trees, etc.) in the park. The grid resolution of the model is set to 5 meters by 5 meters, and the time step is 1 minute. By solving the model, the system is able to calculate the precise coordinates of the pollution source (with an error of less than 10 meters) and the diffusion trend within the next 2 hours.

[0049] Based on the calculated pollution source coordinates and diffusion trends, the system generates a timing control strategy for the opening and closing of the sewage interception valve. Assume that there are 50 controllable sewage interception valves in the park, and the valve opening can be continuously adjusted between 0-100%. The timing control strategy includes the following parameters: the opening time of each valve (accurate to seconds), the opening adjustment curve (one adjustment point every 10 seconds), and the relay diversion parameters of adjacent valves (including pressure gradient and flow balance coefficient).

[0050] Equipped with 5 mobile emergency treatment units, each with a processing capacity of 100 cubic meters per hour. It adopts a modular design, including multiple treatment units such as pretreatment, biological treatment, membrane filtration and disinfection. The intensity of each treatment unit can be adjusted between 30-100%, and the combination can be dynamically adjusted according to the type of pollutant.

[0051] When the COD concentration in a certain area suddenly rises from 10 mg / L to 100 mg / L, an emergency response is initiated. The density clustering algorithm identifies the pollution source area within 2 minutes. The pollution diffusion optimization model calculates the pollution source coordinates and diffusion trend. The timing control strategy is generated and sent to each sewage interception valve. At the same time, the mobile emergency treatment unit is dispatched to the optimal deployment location and the treatment intensity and combination method are determined according to the actual situation.

[0052] Through this implementation method, the pollution source can be quickly identified, located and initially intercepted after pollution occurs, and emergency treatment can be initiated, which can effectively protect the ecological environment.

[0053] In some of the above embodiments of the present application, it is proposed to establish a pollution diffusion optimization model for each identified pollution source area based on the water flow velocity field data, calculate the pollution source coordinates and diffusion trend to determine the pollution source location and diffusion situation. However, in this process, relying solely on the water flow velocity field data may not fully consider the impact of terrain and obstacles on pollutant diffusion, resulting in inaccurate calculation results of pollution source coordinates and diffusion trends. This may affect the subsequent sewage interception valve control strategy and the deployment effect of the mobile emergency treatment unit.

[0054] In this regard, the present application further proposes to obtain the terrain data and obstacle distribution data of the pollution source area for each identified pollution source area; to establish a pollution diffusion optimization model that takes into account the influence of terrain and obstacles based on the water flow velocity field data, terrain data and obstacle distribution data; to calculate the coordinates of the pollution source according to the pollution diffusion optimization model; and to calculate the diffusion speed and direction of pollutants in different areas based on the pollution source coordinates and the pollution diffusion optimization model to obtain the diffusion trend.

[0055] This application introduces terrain data and obstacle distribution data, and combines these data with water flow velocity field data to establish a more comprehensive and accurate pollution diffusion optimization model. This model takes into account the impact of terrain and obstacles on pollutant diffusion, so that the coordinates of pollution sources and diffusion trends can be calculated more accurately.

[0056] Specifically, obtaining topographic data of pollution source areas can be achieved in a variety of ways. For example, high-precision LiDAR technology can be used for topographic mapping to obtain accurate terrain elevation data. Another method is to use satellite remote sensing technology, such as synthetic aperture radar interferometry, to obtain large-scale terrain information. For small areas, high-resolution terrain modeling can also be performed using drone-mounted photogrammetry systems.

[0057] Obstacle distribution data can also be obtained by a variety of technical means. For example, high-resolution aerial or satellite images can be used for image recognition and classification to identify obstacles such as buildings and trees. Another method is to use ground laser scanning technology to obtain accurate three-dimensional point cloud data and extract obstacle information from it. For dynamic obstacles, such as temporary stages or tents, they can be identified and located through real-time updated drone aerial data.

[0058] Combining these data with the water velocity field data, a pollution diffusion optimization model that takes into account the influence of terrain and obstacles is established, so that the model can more realistically reflect the diffusion behavior of pollutants in complex environments. This optimization model can use computational fluid dynamics (CFD) methods, combined with the boundary conditions of terrain and obstacles, to simulate the diffusion process of pollutants in different terrain and obstacle environments. Parameters such as terrain slope and roughness, as well as factors such as the shape, size and distribution of obstacles can be introduced into the model to more accurately describe the movement trajectory and diffusion characteristics of pollutants.

[0059] Based on this optimized model, the process of calculating the coordinates of pollution sources will be more accurate because it takes into account the impact of terrain and obstacles on the initial distribution and diffusion of pollutants. For example, in the calculation process, a reverse tracking algorithm can be used to simulate the reverse movement path of pollutants in combination with terrain and obstacle information, thereby more accurately locating the pollution source. Similarly, when calculating the diffusion speed and direction of pollutants in different areas, it can also more accurately reflect the actual situation, thereby obtaining a more reliable diffusion trend prediction.

[0060] The technical solution of this application can provide more accurate pollution source positioning and diffusion prediction, which is of great significance for the subsequent formulation of sewage interception valve control strategy and the deployment of mobile emergency treatment units. More accurate pollution source coordinates and diffusion trend information can help the system control sewage interception valves more effectively and deploy mobile emergency treatment units more accurately, thereby improving the efficiency and effectiveness of the entire urban green space runoff interception and discharge system.

[0061] For example, in a specific embodiment, suppose an event is held in a large park. There is a stream in the park, the surrounding terrain is undulating, and there are temporary stages and audience areas. Through high-precision drone aerial photography, detailed terrain data of the park is obtained, including elevation changes and slope information around the stream. At the same time, using real-time updated aerial images, obstacles such as temporary stages and auditoriums are identified and located.

[0062] The water velocity field data is obtained through multiple velocity sensors arranged in the stream. This data is input into the optimized pollution diffusion model, which takes into account the shape of the stream, the undulations of the surrounding terrain, and the impact of temporary facilities on the water flow. When abnormal water quality is monitored, the model can quickly calculate the precise coordinates of the pollution source, such as locating it near a temporary catering area.

[0063] Based on the coordinates of the pollution source, the diffusion trend of the pollutants was further calculated. Taking into account the influence of the terrain, the model predicts that the diffusion rate of pollutants is slower in low-lying areas, while the diffusion rate is faster in areas with larger slopes. At the same time, the model also considers the blocking effect of obstacles such as temporary stages on the diffusion of pollutants, and predicts that pollutants will bypass these obstacles and form a specific diffusion path.

[0064] These precise predictions enable the system to formulate more targeted pollution interception strategies. For example, the system can prioritize the control of sewage interception valves located on the predicted diffusion path, while avoiding crowded audience areas to minimize the impact on music festival activities. In addition, mobile emergency treatment units can also choose the optimal deployment location based on the predicted diffusion trend, so as to efficiently treat pollutants without interfering with ongoing activities.

[0065] In this way, the technical solution of this application not only improves the accuracy and efficiency of pollution treatment, but also minimizes the impact on normal park activities while ensuring water quality safety, thereby achieving harmonious coexistence of environmental protection and public activities.

[0066] In some of the above embodiments of the present application, a timing control strategy for generating the opening and closing of the sewage interception valve according to the coordinates of the pollution source and the diffusion trend is proposed to control the opening and closing of the sewage interception valve. However, in this process, there is a lack of precise control over the timing of opening and closing of the sewage interception valve. Specifically, the time difference of pollutants arriving at each sewage interception valve is not taken into account, which may cause the upstream valve to open too late or the downstream valve to open too early, affecting the sewage interception effect. At the same time, the valve opening adjustment also lacks precision and cannot be dynamically adjusted according to the diffusion of pollutants, which may cause insufficient or excessive sewage interception.

[0067] In this regard, the present application further proposes the steps of generating a timing control strategy for the opening and closing of sewage interception valves according to the pollution source coordinates and diffusion trends, including: calculating the estimated time for pollutants to reach each sewage interception valve according to the pollution source coordinates and diffusion trends; generating an opening time sequence of the sewage interception valves based on the estimated time, wherein the opening time of the sewage interception valve located upstream is earlier than the opening time of the sewage interception valve located downstream; calculating the opening adjustment parameters of each sewage interception valve according to the pollution source coordinates and diffusion trends; generating a timing control strategy based on the opening time sequence and the opening adjustment parameters.

[0068] This solution achieves precise control of the opening and closing sequence of the sewage interception valves by accurately calculating the estimated time for pollutants to reach each sewage interception valve. By generating an opening time sequence, it ensures that the upstream valve opens before the downstream valve, effectively preventing premature leakage of pollutants. At the same time, by calculating the opening adjustment parameters of each sewage interception valve, the dynamic adjustment of the valve opening can be achieved, which can be precisely controlled according to the diffusion of pollutants.

[0069] Specifically, there are many ways to calculate the estimated time for pollutants to reach each sewage interception valve. For example, a fluid dynamics model can be used for simulation calculation based on the coordinates of the pollution source, water velocity field data, and pipe network topology. Another method is to use historical data and machine learning algorithms to establish a prediction model to estimate the arrival time. These methods can be selected or combined according to actual conditions to improve the accuracy of the estimated time.

[0070] When generating the opening time series of the sewage interception valve, not only the upstream and downstream relationship is considered, but also a safety time margin can be introduced. For example, a time window for early opening can be set for each valve based on the estimated arrival time, such as opening 5-10 minutes in advance. This can cope with possible prediction errors and ensure that pollutants are effectively intercepted.

[0071] When calculating the opening adjustment parameters of each sewage interception valve, multiple factors can be considered. First, based on the pollutant concentration gradient, the initial value of the valve opening can be set. Specifically, the initial value can be set according to the following principles:

[0072] Significant positive concentration gradient (downstream concentration is much higher than upstream): When the pollutant concentration downstream of the valve is significantly higher than that upstream, it indicates that the pollutants are diffusing downstream, and the valve should tend to open to intercept and divert these high-concentration pollutants. The size of the initial opening can be proportional to the steepness of the concentration gradient. The larger the gradient, the larger the initial opening can be set, but it should be noted that it does not exceed the maximum opening of the valve.

[0073] Significant negative concentration gradient (upstream concentration is much higher than downstream): When the pollutant concentration upstream of the valve is monitored to be much higher than that downstream, it may indicate that there are interception measures in place upstream or the pollution source is upstream. The valve can be considered to be set to a smaller initial opening or even closed to avoid unnecessary diversion or affect the downstream water flow.

[0074] Low concentration gradient (upstream and downstream concentrations do not change much): When the pollutant concentrations at the upstream and downstream monitoring points do not change much and do not exceed the preset threshold, the initial opening of the valve can be set to a default value (for example, 50%) or set according to the overall pipeline network flow control requirements.

[0075] Consider the function and location of the valve: key valves located on the main pollution path may require a higher initial opening priority. Some valves located in branches or at the end may need their initial opening coordinated according to the overall diversion strategy.

[0076] Secondly, the valve opening is dynamically adjusted based on the water flow rate and pipeline pressure data to maintain proper hydraulic balance. In addition, a feedback mechanism can be introduced to further optimize the valve opening based on real-time monitored pollutant concentration data.

[0077] When generating a timing control strategy based on the opening time sequence and the opening adjustment parameters, a segmented control method can be used. For example, the entire sewage interception process is divided into three stages: initial sewage interception, stable control, and terminal adjustment, and different control parameters are used in each stage. The initial sewage interception stage may require a larger valve opening for rapid response, the stable control stage can be fine-tuned according to changes in pollutant concentration, and the terminal adjustment stage may require a gradual reduction in the opening to prevent secondary pollution.

[0078] The technical solution of the present application achieves precise control of the opening and closing timing of the sewage interception valve through precise calculation and dynamic adjustment. This method solves the problem of inaccurate control of the opening and closing timing of the sewage interception valve. By considering the time and space characteristics of pollutant diffusion, more precise sewage interception control is achieved. This not only improves the sewage interception efficiency, but also avoids excessive or insufficient sewage interception, thereby better protecting the water environment.

[0079] The innovation of this solution is that it takes into account multiple factors such as pollution source coordinates, diffusion trends, and estimated arrival times, generating a comprehensive time-series control strategy. This strategy not only takes into account the time series, but also includes the opening adjustment parameters, achieving dual precise control in time and space. This refined control method significantly improves the efficiency and intelligence level of the urban green space runoff interception and discharge system.

[0080] As a preferred implementation, the present application can further combine real-time monitoring data and prediction models to achieve dynamic optimization of the pollution interception process. Specifically, a feedback control loop can be set to regularly (e.g., every 5 minutes) update the pollutant diffusion optimization model and adjust the valve opening time and opening parameters accordingly. This method can effectively deal with the deviation between the actual situation and the initial prediction, and further improve the pollution interception effect.

[0081] For example, suppose that in a pollution incident, the initial prediction is that pollutants will reach the first sewage interception valve in 30 minutes, and a timing control strategy is generated based on this, planning to open the valve in 25 minutes. However, during the execution process, real-time monitoring data shows that the pollutant diffusion rate is 20% faster than expected. At this time, the system will automatically adjust the strategy, advance the valve opening time to 20 minutes later, and adjust the opening sequence of subsequent valves accordingly. At the same time, the system will recalculate the opening adjustment parameters according to the new diffusion rate to ensure that each valve can intercept pollutants in the best state.

[0082] Through this dynamic optimization mechanism, the technical solution of the present application can better adapt to the complex and changing actual situation, significantly improving the adaptability and reliability of the sewage interception system. This can not only more effectively protect the water environment, but also reduce unnecessary energy consumption and equipment loss, and improve the operating efficiency of the entire system.

[0083] In some of the above embodiments of the present application, a timing control strategy based on the opening time sequence and the opening adjustment parameters is proposed to control the opening and closing of the sewage interception valve. However, the following problems may exist in this process: the opening time interval of adjacent valves is unreasonable, resulting in the inability to continuously and effectively divert pollutants; the valve opening adjustment is not coordinated, resulting in unbalanced pressure in the pipe network; the impact of park activities on valve operation is not considered, which may interfere with normal activities. These problems may lead to poor sewage interception effects and affect the effective interception and diversion of pollutants.

[0084] In this regard, the present application further proposes to calculate the time difference threshold that meets the requirements of continuous diversion of pollutants based on the spacing between adjacent sewage interception valves and the water velocity field data; adjust the opening interval of adjacent valves in the opening time series based on the time difference threshold; establish opening adjustment constraints according to the valve topological relationship, and generate opening gradient parameters of adjacent valves according to the opening adjustment constraints and the opening adjustment parameters; calculate the relay diversion parameters that form a pressure gradient based on the opening gradient parameters and the pollutant diffusion trend; integrate the time difference threshold, opening gradient parameters and relay diversion parameters to generate a timing control strategy.

[0085] The technical solution of the present application ensures that the opening time interval of adjacent valves is reasonable by calculating the time difference threshold, thereby achieving continuous diversion of pollutants. Specifically, the calculation of the time difference threshold can be based on the actual distance between adjacent sewage interception valves and the current water flow velocity field data. For example, the method of dividing the distance by the water flow velocity can be used to obtain the shortest time required for pollutants to flow from one valve to the next valve, and then a certain safety factor can be added on this basis to obtain the final time difference threshold.

[0086] Furthermore, the present application coordinates the opening adjustment of adjacent valves to avoid pressure imbalance in the pipe network by establishing opening adjustment constraints and generating opening gradient parameters. The opening adjustment constraints may include multiple aspects, such as the maximum opening limit of the valve, the opening change rate limit, etc. The generation of the opening gradient parameters may take into account the hydraulic relationship between adjacent valves to ensure that the opening of the upstream valve is greater than or equal to the opening of the downstream valve to maintain the appropriate water flow direction and speed.

[0087] Therefore, the present application forms a pressure gradient that is conducive to the directional flow of pollutants by calculating the relay diversion parameters. The calculation of the relay diversion parameters can be based on the opening gradient parameters and the diffusion trend of pollutants. For example, the opening of the downstream valve can be gradually increased according to the diffusion direction of the pollutants to form a pressure gradient from upstream to downstream, thereby promoting the directional flow of pollutants.

[0088] Specifically, the generation process of the timing control strategy may include the following steps:

[0089] First, based on the calculated time difference threshold, the opening interval of adjacent valves in the original opening time sequence is adjusted to ensure that the interval time is not less than the threshold;

[0090] Secondly, according to the generated opening gradient parameters, the initial opening and opening change curve of each valve are set;

[0091] Finally, the relay diversion parameters are integrated into the control strategy to guide the dynamic adjustment of valve opening.

[0092] As a preferred implementation, the present application can dynamically adjust the timing control strategy in practical applications. For example, the changes in pollutant concentration and water flow velocity can be monitored in real time. When a significant change in the pollutant diffusion trend is found, the time difference threshold, opening gradient parameter and relay diversion parameter are recalculated, and the timing control strategy is updated. This dynamic adjustment mechanism can make the system better adapt to complex and changeable pollution conditions.

[0093] The technical solution of this application solves the problems of unreasonable opening time of adjacent valves and uncoordinated valve opening adjustment through a refined timing control strategy. By considering the water flow velocity field data, valve topology relationship and pollutant diffusion trend, intelligent control of sewage interception valves is achieved, and the sewage interception effect is improved. In particular, by forming a relay diversion parameter of pressure gradient, the directional flow capacity of pollutants is enhanced, and the interception and diversion efficiency of pollutants is effectively improved.

[0094] Furthermore, the technical solution of the present application minimizes interference with normal park activities by considering the impact of park activities on valve operation. For example, when calculating the opening gradient parameter, the location information of the park activity area can be used as a constraint to avoid large opening adjustments of valves near densely populated activity areas.

[0095] Therefore, the technical solution of this application not only improves the pollution interception effect, but also minimizes the impact on normal park activities while ensuring effective interception and diversion of pollutants. The implementation of this precise control strategy enables urban green spaces to be more flexible and efficient in responding to sudden pollution incidents, while maintaining the normal operation and use of parks.

[0096] In a specific embodiment, assume that there are a series of sewage interception valves A, B, C, and D arranged along the river in a large park. Through the monitoring of the water flow velocity field, it is known that the average water flow velocity between AB, BC, and CD is 0.5m / s, 0.6m / s, and 0.7m / s, respectively, and the valve spacing is 100m, 120m, and 140m, respectively.

[0097] First, calculate the time difference threshold. Take AB as an example. The theoretical time for pollutants to flow from A to B is 100m / 0.5m / s=200s. Considering the complexity of the actual situation, add a safety factor of 1.2 and the time difference threshold of AB is 240s. Similarly, the time difference thresholds of BC and CD are 240s and 240s respectively.

[0098] Next, the opening gradient parameters are set according to the pollutant diffusion trend and valve topology. Assuming that the pollutants diffuse from upstream to downstream, the initial openings of A, B, C, and D can be set to 80%, 70%, 60%, and 50%, respectively, forming a decreasing opening gradient.

[0099] It is worth noting that in the technical solution of the present application, a timing control strategy is generated in order to achieve precise control of the sewage interception valve. The generation of this strategy involves two key concepts: the opening adjustment parameter and the opening gradient parameter. Among them, the opening adjustment parameter refers to the parameter used to control the degree of opening of each sewage interception valve within a preset time period. Its numerical range is usually between 0-100% and can change dynamically over time. When calculating the opening adjustment parameter, it is necessary to comprehensively consider a variety of factors including but not limited to pollutant concentration gradient, water flow velocity field data, valve topology relationship, and interference from park activities.

[0100] As the initial step to determine the opening adjustment parameters, the present application proposes to set the initial value of the valve opening based on the pollutant concentration gradient. Furthermore, in order to form a pressure gradient between adjacent valves that is conducive to the directional flow of pollutants, the present application introduces the concept of opening gradient parameters. The opening gradient parameter describes the relative size relationship between the openings of adjacent valves, and its purpose is to guide the water flow and pollutants to flow in a predetermined direction through the difference in valve openings. For example, according to the pollution diffusion trend, the initial opening of the upstream valve can be set to be greater than the initial opening of the downstream valve, thereby forming a decreasing opening gradient. These initial opening values, while reflecting the opening gradient parameters, also constitute the starting point of the opening adjustment parameters of each valve in the subsequent timing control strategy, and will be dynamically adjusted according to factors such as the relay diversion parameters in the subsequent control process to achieve effective interception and diversion of pollutants.

[0101] Then, the relay diversion parameters are calculated. Considering that the diffusion rate of pollutants may change over time, a dynamic adjustment mechanism can be set. For example, the pollutant concentration is detected every 5 minutes. If the downstream concentration rises too fast, the downstream valve opening is increased, otherwise it is reduced. Specifically, it can be set as follows: when the downstream concentration rises faster than 0.1 mg / L / min, the downstream valve opening is increased by 2% per minute until the upstream valve opening or the maximum opening reaches 90%.

[0102] Finally, these parameters are integrated into a timing control strategy. For example:

[0103] Valve A opens at time t, with an initial opening of 80%;

[0104] Valve B opens at t+240s, with an initial opening of 70%;

[0105] Valve C opens at t+480s, with an initial opening of 60%;

[0106] Valve D opens at t+720s, with an initial opening of 50%;

[0107] The pollutant concentration is tested every 5 minutes, and the opening of each valve is dynamically adjusted according to the relay diversion parameters.

[0108] Through this refined timing control strategy, the technical solution of the present application can effectively solve problems such as unreasonable opening time of adjacent valves and uncoordinated valve opening adjustment. Through a reasonable time difference threshold, it is ensured that pollutants can be continuously and effectively diverted from one valve to the next valve, avoiding the retention or reverse flow of pollutants between valves. By setting the opening gradient parameters, the opening adjustment of adjacent valves is coordinated, effectively avoiding the problem of unbalanced pipe network pressure. The dynamically adjusted relay diversion parameters further enhance the system's ability to cope with complex pollution situations and ensure efficient interception and diversion of pollutants.

[0109] In addition, the technical solution of the present application takes into account the impact of park activities on valve operation, while ensuring the pollution interception effect, it minimizes the interference with the normal activities of the park. For example, when calculating the opening gradient parameter, the location information of the activity area can be used as a constraint to avoid large opening adjustments of valves near densely active areas. This precise control not only improves the pollution interception effect, but also minimizes the interference with the normal activities of the park, achieving a balance between pollution control and park functions.

[0110] In general, the technical solution of this application achieves refined control of the sewage interception valve by introducing time difference thresholds, opening gradient parameters and relay diversion parameters. This control strategy can effectively cope with complex and changeable pollution situations, improve the efficiency of pollutant interception and diversion, and minimize the impact on normal park activities. Through this intelligent control method, this application provides a more efficient and flexible solution for the urban green space runoff interception and discharge system, effectively improving the system's ability to respond to sudden pollution incidents.

[0111] In some of the above embodiments of the present application, it is proposed that when the pollutant concentration data shows that the pollutant concentration exceeds a threshold value, a mobile emergency treatment unit is started according to a timing control strategy to perform multi-stage treatment of polluted water bodies to respond to sudden pollution incidents. However, in this process, how to flexibly adjust the treatment plan according to the actual pollution situation, and how to efficiently treat polluted water bodies without affecting the normal activities of the park, there are still challenges. Specifically, the problems that need to be solved include: how to select a suitable combination of treatment units according to the type of pollutant, how to determine the optimal deployment position of the mobile emergency treatment unit, how to dynamically adjust the treatment intensity according to real-time monitoring data, and how to safely introduce the treated water body into the ecological protection area after reaching the treatment target.

[0112] In this regard, the present application further proposes that when the judgment result is that the pollutant concentration exceeds the threshold, the pollutant type information in the pollutant concentration data is obtained; according to the pollutant type information, the corresponding processing unit combination is selected from the preset processing unit library; based on the pollutant diffusion trend in the timing control strategy, the optimal deployment position of the mobile emergency treatment unit composed of the corresponding processing unit combination is calculated; the mobile emergency treatment unit is controlled to move to the optimal deployment position; according to the real-time monitored influent pollutant concentration and the predetermined treatment target, the treatment intensity of each treatment unit is dynamically adjusted; when the effluent water quality reaches the treatment target, the treated water body is introduced into the ecological protection area.

[0113] The technical solution proposed in this application realizes accurate and efficient processing of sudden pollution incidents through a series of steps. First, by obtaining pollutant type information, a suitable combination of processing units is selected from a preset processing unit library to ensure the pertinence of the treatment plan. This step can be achieved in a variety of ways. For example, spectral analysis technology can be used to quickly identify pollutant types, or chemical sensor arrays can be used for multi-parameter detection. The preset processing unit library can include physical, chemical and biological treatment units, such as activated carbon adsorption, chemical oxidation, membrane separation, etc. These treatment units can be flexibly combined according to the type of pollutant.

[0114] Secondly, the optimal deployment position is calculated based on the pollutant diffusion trend in the timing control strategy, and the mobile emergency treatment unit is controlled to move to this position, realizing the flexible deployment of the treatment equipment. This step can be achieved by combining the hydrodynamic model and the pollutant diffusion optimization model. For example, computational fluid dynamics software can be used to simulate the diffusion process of pollutants in the water body, taking into account factors such as terrain and water flow speed, so as to accurately calculate the optimal deployment position. The mobile emergency treatment unit can adopt a modular design, which is convenient for rapid assembly and disassembly, and improves deployment efficiency.

[0115] Then, by real-time monitoring of the influent pollutant concentration and dynamically adjusting the treatment intensity, the real-time adaptability and efficiency of the treatment process are guaranteed. This step can be achieved through an online water quality monitoring system and an intelligent control algorithm. For example, online monitoring equipment such as ion selective electrodes and UV-visible spectrometers can be used to detect the influent water quality in real time and transmit the data to the control system. The control system can use fuzzy control or neural network algorithms to automatically adjust the operating parameters of each treatment unit, such as chemical dosage, membrane filtration pressure, etc., according to the influent water quality and treatment objectives.

[0116] Finally, when the effluent quality reaches the treatment target, the treated water is introduced into the ecological protection area to ensure the safe use of the treated water. This step can be achieved by setting up multiple water quality assurance measures. For example, a multi-parameter water quality online monitoring device can be set up at the outlet of the treatment unit to monitor the effluent quality in real time. At the same time, a water quality early warning system can be established to automatically trigger the water diversion operation when the effluent quality approaches or reaches the treatment target. To ensure safety, a buffer tank can also be set up to conduct a final water quality test before introducing it into the ecological protection area.

[0117] This solution solves the problem that traditional fixed treatment facilities are difficult to cope with dynamically changing pollutants. Through mobile emergency treatment units and dynamic adjustment of treatment intensity, the response speed and treatment efficiency to sudden pollution incidents are improved. At the same time, by accurately selecting the combination of treatment units and optimizing the deployment location, the interference with normal activities in the park is minimized. In addition, real-time monitoring and dynamic adjustment mechanisms ensure the accuracy of the treatment process and the efficiency of resource utilization.

[0118] The technical solution of this application can be implemented as follows in practical applications:

[0119] Assume that during an event in a large park, the water quality monitoring system detects that the concentration of pollutants in a certain area exceeds the preset threshold. The system first obtains pollutant type information through multi-parameter water quality sensors and identifies the main pollutants as organic matter and suspended solids. Based on this information, a combination of treatment units including activated carbon adsorption, advanced oxidation and membrane filtration is selected from the preset treatment unit library.

[0120] Next, using the pollutant diffusion trend data in the previously generated timing control strategy and combining it with the park’s terrain and hydrological information, the optimal deployment position of the mobile emergency treatment unit was calculated through numerical simulation, and the mobile emergency treatment unit was then controlled to move to that position.

[0121] After the emergency treatment unit starts running, the treatment intensity is dynamically adjusted by real-time monitoring of the influent pollutant concentration. For example, when the organic matter concentration in the influent is detected to be 50 mg / L, the system automatically increases the ozone dosage of the advanced oxidation unit to 2 mg / L. When the suspended solids concentration rises to 100 mg / L, the system increases the transmembrane pressure of the membrane filtration unit to 0.2MPa. This dynamic adjustment ensures that the treatment efficiency is always maintained at the best state.

[0122] During the treatment process, the effluent quality is continuously monitored. When the organic matter concentration of the effluent is stable below 5 mg / L and the suspended solids concentration is below 10 mg / L within 30 minutes of continuous monitoring, the system determines that the water quality has reached the treatment target. At this time, the treated water is introduced into the nearby ecological protection area to supplement the wetland water source.

[0123] In this way, the technical solution of this application realizes the rapid identification, precise positioning and effective treatment of dynamically changing pollutants, while ensuring that the treated water meets the strict requirements of the ecological protection zone, providing an innovative solution for the management of large parks in smart cities. This solution significantly improves the flexibility and efficiency of pollution treatment, reduces interference with normal park activities, and ensures the safety of water quality in the ecological protection zone, effectively solving the technical problems raised in the background technology.

[0124] In some of the above embodiments of the present application, when the effluent water quality reaches the treatment target, a step of introducing the treated water into the ecological protection zone is proposed to complete the treatment of the polluted water. However, in this process, problems such as poor treatment effect, too long treatment time or inappropriate treatment location may occur, resulting in the inability to timely and effectively treat the polluted water and introduce it into the ecological protection zone. In addition, the treatment process may be disturbed by park activities, affecting the treatment effect and efficiency.

[0125] In this regard, the present application further proposes that during the operation of the mobile emergency treatment unit, when it is detected that the actual treatment time exceeds a preset threshold and the effluent water quality deviation value exceeds a first threshold, the optimal deployment position of the treatment unit and the corresponding multi-stage treatment combination parameters are recalculated based on the current pollutant diffusion trend and the pipe network topology data; the backup treatment resources are activated according to the multi-stage treatment combination parameters and enhanced processing instructions are generated, and the enhanced processing instructions include a processing intensity correction coefficient that is dynamically adjusted based on the interference level of park activities; the processing unit is controlled to move to the updated deployment position to execute the enhanced processing instructions until the effluent water quality reaches the treatment target and is injected into the ecological protection area.

[0126] This application introduces a dynamic adjustment and enhanced treatment mechanism to solve problems such as poor treatment effect, long treatment time or inappropriate treatment location. Specifically, by setting a preset threshold and a first threshold, the treatment time and effluent water quality are monitored in real time to promptly detect poor treatment effects. Among them, the preset threshold can be set according to different pollutant types and treatment targets. For example, for organic pollutants, the preset threshold can be set to 2 hours; for heavy metal pollutants, the preset threshold can be set to 4 hours. The first threshold can be set to a 10% deviation range of the treatment target water quality.

[0127] Furthermore, the optimal deployment position is recalculated based on the current pollutant diffusion trend and pipe network topology data to solve the problem of inappropriate treatment location. The pollutant diffusion trend can be obtained by combining real-time monitoring data and numerical simulation, while the pipe network topology data includes information such as the connection relationship, pipe diameter, slope, etc. of the pipe network. The calculation of the optimal deployment position can adopt a multi-objective optimization algorithm, taking into account factors such as treatment efficiency, energy consumption, and impact on park activities.

[0128] Thus, multi-stage treatment combination parameters and enhanced treatment instructions are generated to activate spare treatment resources and improve treatment efficiency, wherein spare treatment resources include but are not limited to additional mobile treatment units, more mobile units can be deployed to increase treatment capacity; spare treatment modules or equipment, mobile units are equipped with additional modules that can be added or replaced to enhance treatment effects or for specific pollutants; access to pre-deployed fixed treatment facilities, in some cases, there may be adjacent fixed treatment facilities that can be connected and utilized; additional treatment agents or consumables, in order to enhance the treatment effect, additional chemicals, adsorbents or other consumables may be required. Multi-stage treatment combination parameters may include operating parameters of each treatment unit, such as membrane flux of membrane filtration units, contact time of activated carbon adsorption units, etc. Enhanced treatment instructions dynamically adjust the operating parameters of each treatment unit according to pollutant characteristics and treatment objectives, such as increasing the membrane flux of membrane filtration units or extending the contact time of activated carbon adsorption units.

[0129] This application introduces a processing intensity correction coefficient based on the interference level of park activities to dynamically adjust the processing intensity and reduce the impact on park activities. The interference level of park activities can be comprehensively evaluated based on factors such as activity type, crowd density, and sound intensity. For example, the interference level can be divided into three levels: low, medium, and high. The processing intensity correction coefficient is negatively correlated with the interference level. When the interference level is high, the processing intensity correction coefficient is low to reduce the impact of the processing process on park activities.

[0130] Specifically, the control processing unit moves to the updated deployment position and executes the enhanced processing instructions to ensure that the processing effect reaches the target. The movement of the processing unit can use automatic navigation technology, combined with GPS positioning and obstacle recognition system to achieve accurate positioning and safe movement. The execution of enhanced processing instructions is achieved through a remote control system, which can adjust the operating parameters of each processing unit in real time.

[0131] This application effectively solves the problems of poor treatment effect, long treatment time and inappropriate treatment location through real-time monitoring, dynamic adjustment and enhanced treatment. At the same time, considering the impact of park activities, by dynamically adjusting the treatment intensity, it achieves efficient treatment of polluted water while minimizing interference with park activities.

[0132] In this application, the operation process of the mobile emergency handling unit can be described as follows:

[0133] First, the real-time monitoring data is used to determine whether the pollutant concentration exceeds the preset threshold. When the pollutant concentration exceeds the threshold, the system activates the mobile emergency treatment unit and selects the appropriate combination of treatment units based on the pollutant type and concentration.

[0134] Next, the optimal deployment location of the treatment unit is calculated based on the pollutant diffusion trend and the pipe network topology data. For example, for a polluted area of ​​100 square meters, the system may choose to deploy the treatment unit 50 meters upstream of the pollution source to maximize the pollution interception effect. The treatment unit is then moved to the designated location and starts operation.

[0135] During the treatment process, the system continuously monitors the actual treatment time and effluent quality. Assuming the preset threshold is 3 hours, the first threshold is a 15% deviation from the treatment target. When the system detects that the treatment time exceeds 3 hours and the effluent quality deviation exceeds 15%, the enhanced treatment mechanism will be triggered.

[0136] The system re-evaluates the current pollution situation and calculates a new optimal deployment location. For example, if the pollution spreads faster, the new deployment location may move to 20 meters downstream from the original location. At the same time, the system generates new multi-stage treatment combination parameters, such as increasing the membrane flux of the membrane filtration unit by 20% and extending the contact time of the activated carbon adsorption unit by 30%.

[0137] In addition, the system also considers the impact of park activities. Suppose there is a concert going on, and the park activity interference level is assessed as "high". Accordingly, the processing intensity correction factor may be set to 0.8, which means that the processing intensity will be reduced by 20% to reduce interference with the concert.

[0138] The treatment unit is then moved to its new deployment location and operates according to the enhanced treatment instructions. The system continuously monitors the effluent quality until the treatment target is reached. Finally, the treated water is introduced into the ecological protection area to complete the entire treatment process.

[0139] Through this dynamic adjustment and strengthening of the treatment mechanism, this application can effectively respond to complex and changing pollution situations while taking into account the normal operation of park activities. This not only improves the efficiency and effectiveness of polluted water treatment, but also minimizes the impact on the normal operation of the park, providing strong support for the sustainable development of urban green spaces.

[0140] In some of the above-mentioned embodiments of the present application, it is proposed to establish opening adjustment constraints according to valve topology relationship parameters, and to generate opening gradient parameters of adjacent valves according to the opening adjustment constraints and the opening adjustment parameters to control the opening and closing of the sewage interception valve. However, in this process, due to the dynamic changes in the park activity area and the fluctuations in the pipe network pressure, the valve opening adjustment may not be accurate enough, affecting the sewage interception effect. In addition, valve operation may interfere with park activities and affect the user experience. Therefore, a dynamic valve opening adjustment method that can take into account park activities and changes in pipe network pressure is needed.

[0141] In this regard, the present application further proposes to obtain vibration sensor data and pipeline pressure data of adjacent valves based on the valve topology relationship; determine the location of the park activity area based on the vibration sensor data, and generate activity interference constraints on the valve opening based on the location; calculate the pressure difference between adjacent valves based on the pipeline pressure data, and generate pressure balance constraints on the valve opening; use activity interference constraints and pressure balance constraints as opening adjustment constraints; and generate opening gradient parameters of adjacent valves based on the opening adjustment constraints and opening adjustment parameters.

[0142] The technical solution proposed in this application realizes real-time monitoring of park activity areas and pipe network pressure changes by introducing vibration sensor data and pipe network pressure data. Specifically, the acquisition of vibration sensor data can be achieved by installing a highly sensitive vibration sensor near adjacent valves.

[0143] The acquisition of pipeline network pressure data can be achieved by installing pressure sensors at adjacent valves.

[0144] When judging the location of the park's activity area based on vibration sensor data, a combination of threshold method and cluster analysis can be used. First, a vibration intensity threshold is set, such as 0.5g, and the area exceeding this threshold is preliminarily determined to be the activity area. Then, these areas are clustered using the K-means clustering algorithm to determine the main activity centers. Based on the location of these activity centers, activity interference constraints for valve opening are generated. For example, for valves within 50 meters of the activity center, the rate of change of the opening must not exceed 10% / minute to reduce interference with the activity.

[0145] When calculating the pressure difference between adjacent valves, the sliding window average method can be used to process the pressure data to eliminate the impact of instantaneous fluctuations. For example, a 5-minute sliding window is used to update the data every 30 seconds. If the pressure difference between adjacent valves exceeds 0.5 bar, it is considered that pressure balance adjustment is required. Based on these pressure difference data, the pressure balance constraint conditions of the valve opening are generated, such as requiring that the opening difference of adjacent valves does not exceed 20%.

[0146] When integrating the activity interference constraint and the pressure balance constraint into the opening adjustment constraint, a weighted average method can be used. For example, during a crowded period, the weight of the activity interference constraint can be set to 0.7 and the weight of the pressure balance constraint can be set to 0.3 to give priority to ensuring the smooth progress of activities.

[0147] Finally, according to the opening adjustment constraints and the opening adjustment parameters, the gradient descent algorithm is used to generate the opening gradient parameters of the adjacent valves. This process can set an objective function, such as minimizing the pollutant diffusion area while satisfying the above constraints. The number of iterations of the algorithm can be set to 100 times, or the iteration can be stopped when the opening change is less than 1%.

[0148] Through this method, the application realizes real-time consideration of two dynamic factors, park activities and pipe network pressure, making valve control more intelligent and precise. For example, when a large-scale event is detected in a certain area, the valve opening near the area will change more slowly and steadily to avoid sudden water flow changes affecting the event. At the same time, the system will automatically adjust the valve opening in other areas to maintain the overall sewage interception effect and pipe network pressure balance.

[0149] In addition, the method of the present application can also effectively cope with fluctuations in pipe network pressure. For example, when the valve in a certain area upstream reduces its opening due to activity needs, the system will automatically adjust the opening of the downstream valve to maintain the overall hydraulic balance. This not only improves the sewage interception effect, but also minimizes interference with normal park activities, while ensuring the stable operation of the pipe network system.

[0150] As a preferred implementation, a central control system can be set up in the park, which receives data from various sensors in real time through a wireless network. The control system adopts a distributed architecture, with a sub-control unit set up in each area, responsible for data processing and preliminary decision-making in the area. The central control system is responsible for global optimization and coordination.

[0151] Specifically, when the system detects that the vibration intensity of a certain area in the park (for example, the location with coordinates of X: 500m, Y: 300m) suddenly increases to 0.8g, it will immediately determine that an event may be held in the area. The system then adjusts the upper limit of the opening rate change of all valves within 100 meters around the area from the original 20% / minute to 5% / minute. At the same time, the system checks the pressure changes upstream and downstream of the area. Assume that the pressure difference between the upstream valve A and the downstream valve B increases from the original 0.3bar to 0.7bar, exceeding the preset 0.5bar threshold. The system will immediately calculate the new opening gradient parameters. The possible result is to slowly increase the opening of valve A from 60% to 65%, while slowly reducing the opening of valve B from 50% to 48%. The whole process lasts for 5 minutes to ensure that the change in water flow will not affect the event and maintain the balance of pipe network pressure.

[0152] Through this refined control, the method of the present application can minimize the impact on park activities and maintain the stability of pipe network pressure while ensuring the sewage interception effect. This dynamic adjustment method provides a more efficient and intelligent solution for the interception and discharge of runoff sewage in urban green spaces, effectively improving the adaptability and reliability of the system.

[0153] Second, refer to Figure 2 The present application also proposes a device for intercepting and discharging runoff from urban green space, comprising:

[0154] The acquisition module 210 is used to acquire the real-time pollutant concentration data and water flow velocity field data collected by the monitoring node on the preset path;

[0155] An identification module 220 is used to identify multiple potential pollution source areas using a density clustering algorithm based on pollutant concentration data;

[0156] The calculation module 230 is used to establish a pollution diffusion optimization model for each identified pollution source area based on the water flow velocity field data, and calculate the pollution source coordinates and diffusion trend;

[0157] The first control module 240 is used to generate a timing control strategy for opening and closing the sewage interception valve according to the pollution source coordinates and diffusion trend, and control the opening and closing of the sewage interception valve according to the timing control strategy, wherein the timing control strategy includes relay diversion parameters of adjacent valves;

[0158] The second control module 250 is used to start the mobile emergency treatment unit according to the timing control strategy when the pollutant concentration data shows that the pollutant concentration exceeds the threshold, and perform multi-stage treatment of the polluted water body. The treatment intensity and combination of the multi-stage treatment are adjusted according to the pollutant concentration and the treatment target.

[0159] By acquiring real-time pollutant concentration data and water flow velocity field data, a density clustering algorithm is used to identify multiple potential pollution source areas, a pollution diffusion optimization model is established to calculate the pollution source coordinates and diffusion trends, and a timing control strategy for the opening and closing of the sewage interception valve is generated. When the pollutant concentration exceeds the threshold, the mobile emergency treatment unit is started to perform multi-level treatment, thereby being able to quickly identify and accurately locate dynamically changing pollution sources, and achieve effective sewage interception and treatment.

[0160] In a third aspect, the present application also provides an electronic device, including a processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the above method are executed.

[0161] Through the above technical solution, the processor and the memory are interconnected and communicate with each other through a communication bus and / or other forms of connection mechanisms (not marked), and the memory stores computer-readable instructions executable by the processor. When the electronic device is running, the processor executes the computer-readable instructions to execute the method in any optional implementation of the above embodiment to achieve the following functions: obtaining real-time pollutant concentration data and water flow velocity field data collected by the monitoring node on a preset path; using a density clustering algorithm to identify multiple potential pollution source areas based on the pollutant concentration data; for each identified pollution source area, based on the water flow velocity field data, establishing a pollution diffusion optimization model, calculating the pollution source coordinates and diffusion trend; generating a timing control strategy for the opening and closing of the sewage interception valve according to the pollution source coordinates and the diffusion trend, and controlling the opening and closing of the sewage interception valve according to the timing control strategy, and the timing control strategy includes relay diversion parameters of adjacent valves; when the pollutant concentration data shows that the pollutant concentration exceeds the threshold, the mobile emergency treatment unit is started according to the timing control strategy to perform multi-stage treatment of the polluted water body, and the treatment intensity and combination of the multi-stage treatment are adjusted according to the pollutant concentration and the treatment target.

[0162] In a fourth aspect, the present application also provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method are executed.

[0163] Through the above technical solution, when the computer program is executed by the processor, the method in any optional implementation method of the above embodiment is executed to achieve the following functions: obtain real-time pollutant concentration data and water flow velocity field data collected by the monitoring node on the preset path; use a density clustering algorithm to identify multiple potential pollution source areas based on the pollutant concentration data; for each identified pollution source area, establish a pollution diffusion optimization model based on the water flow velocity field data, and calculate the pollution source coordinates and diffusion trends; generate a timing control strategy for the opening and closing of the sewage interception valve based on the pollution source coordinates and diffusion trends, and control the opening and closing of the sewage interception valve according to the timing control strategy, and the timing control strategy includes the relay diversion parameters of adjacent valves; when the pollutant concentration data shows that the pollutant concentration exceeds the threshold, start the mobile emergency treatment unit according to the timing control strategy, and perform multi-stage treatment of the polluted water body, and the treatment intensity and combination method of the multi-stage treatment are adjusted according to the pollutant concentration and the treatment target.

[0164] Among them, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable red-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0165] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0166] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0167] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0168] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for intercepting and discharging runoff from urban green space, characterized in that: The method comprises the following steps: Obtain real-time pollutant concentration data and water flow velocity field data collected by monitoring nodes on preset paths; Based on the pollutant concentration data, a density clustering algorithm is used to identify multiple potential pollution source areas; For each identified pollution source area, a pollution diffusion optimization model is established based on the water flow velocity field data to calculate the pollution source coordinates and diffusion trend; According to the pollution source coordinates and diffusion trend, a timing control strategy for opening and closing the sewage interception valve is generated, and the opening and closing of the sewage interception valve is controlled according to the timing control strategy, wherein the timing control strategy includes relay diversion parameters of adjacent valves; When the pollutant concentration data shows that the pollutant concentration exceeds a threshold value, the mobile emergency treatment unit is started according to the timing control strategy to perform multi-stage treatment of the polluted water body, and the treatment intensity and combination mode of the multi-stage treatment are adjusted according to the pollutant concentration and the treatment target; The step of generating a timing control strategy for opening and closing the sewage interception valve according to the pollution source coordinates and diffusion trend comprises: Calculate the estimated time for pollutants to reach each sewage interception valve based on the pollution source coordinates and diffusion trend; Based on the estimated time, generating an opening time sequence of the sewage interception valves, wherein the opening time of the sewage interception valve located upstream is earlier than the opening time of the sewage interception valve located downstream; Calculate the opening adjustment parameters of each sewage interception valve according to the pollution source coordinates and diffusion trend; Based on the opening time sequence and the opening adjustment parameter, generating the timing control strategy; The step of generating the timing control strategy based on the opening time sequence and the opening adjustment parameter comprises: Based on the spacing between adjacent sewage interception valves and water velocity field data, the time difference threshold that meets the requirements for continuous pollutant diversion is calculated; adjusting the adjacent valve opening intervals in the opening time sequence based on the time difference threshold; Establishing opening adjustment constraint conditions according to the valve topological relationship, and generating opening gradient parameters of adjacent valves according to the opening adjustment constraint conditions and the opening adjustment parameters; Based on the opening gradient parameter and the pollutant diffusion trend, the relay diversion parameter for forming the pressure gradient is calculated; The time difference threshold, the opening gradient parameter and the relay diversion parameter are integrated to generate the timing control strategy.

2. The method for intercepting and discharging runoff from urban green space according to claim 1, characterized in that: The step of establishing a pollution diffusion optimization model for each identified pollution source area based on the water flow velocity field data and calculating the pollution source coordinates and diffusion trend comprises: For each identified pollution source area, obtaining terrain data and obstacle distribution data of the pollution source area; Based on the water velocity field data, terrain data and obstacle distribution data, a pollution diffusion optimization model considering the influence of terrain and obstacles is established; Calculating the pollution source coordinates according to the pollution diffusion optimization model; Based on the pollution source coordinates and the pollution diffusion optimization model, the diffusion speed and direction of pollutants in different areas are calculated to obtain the diffusion trend.

3. The method for intercepting and discharging runoff from urban green space according to claim 1, characterized in that: When the pollutant concentration data shows that the pollutant concentration exceeds a threshold value, the mobile emergency treatment unit is started according to the timing control strategy to perform multi-stage treatment of the polluted water body, and the treatment intensity and combination mode of the multi-stage treatment are adjusted according to the pollutant concentration and the treatment target. The steps include: When the judgment result is that the pollutant concentration exceeds the threshold value, obtaining the pollutant type information in the pollutant concentration data; According to the pollutant type information, a corresponding treatment unit combination is selected from a preset treatment unit library; Based on the pollutant diffusion trend in the timing control strategy, calculate the optimal deployment position of the mobile emergency treatment unit composed of the corresponding treatment unit combination; Controlling the mobile emergency handling unit to move to the optimal deployment position; Dynamically adjust the treatment intensity of each treatment unit according to the real-time monitored influent pollutant concentration and the predetermined treatment target; When the effluent quality reaches the treatment target, the treated water will be introduced into the ecological protection area.

4. The method for intercepting and discharging runoff from urban green space according to claim 3, characterized in that: When the effluent water quality reaches the treatment target, the step of introducing the treated water into the ecological protection area includes: During the operation of the mobile emergency treatment unit, when it is detected that the actual treatment time exceeds the preset threshold and the effluent water quality deviation value exceeds the first threshold, the optimal deployment position of the treatment unit and the corresponding multi-stage treatment combination parameters are recalculated based on the current pollutant diffusion trend and pipe network topology data; activating spare processing resources and generating enhanced processing instructions according to the multi-level processing combination parameters, wherein the enhanced processing instructions include a processing intensity correction coefficient dynamically adjusted based on the park activity interference level; The control processing unit moves to the updated deployment position to execute the enhanced processing instructions until the effluent water quality reaches the treatment target and is then injected into the ecological protection area.

5. The method for intercepting and discharging runoff from urban green space according to claim 2, characterized in that: The step of establishing the opening adjustment constraint condition according to the valve topological relationship and generating the opening gradient parameter of the adjacent valve according to the opening adjustment constraint condition and the opening adjustment parameter comprises: Acquire vibration sensor data and pipe network pressure data of adjacent valves based on valve topology; Determine the location of the park activity area according to the vibration sensor data, and generate activity interference constraint conditions for valve opening based on the location; Calculate the pressure difference between adjacent valves based on the pipeline network pressure data and generate a pressure balance constraint condition for the valve opening; Using the activity interference constraint condition and the pressure balance constraint condition as the opening adjustment constraint condition; The opening gradient parameters of the adjacent valves are generated according to the opening adjustment constraint conditions and the opening adjustment parameters.

6. A device for intercepting and discharging runoff from urban green space, using the method described in any one of claims 1 to 5, characterized in that: include: An acquisition module is used to obtain real-time pollutant concentration data and water flow velocity field data collected by the monitoring node on a preset path; An identification module, used to identify multiple potential pollution source areas using a density clustering algorithm based on the pollutant concentration data; A calculation module is used to establish a pollution diffusion optimization model for each identified pollution source area based on the water flow velocity field data, and calculate the pollution source coordinates and diffusion trend; A first control module, for generating a timing control strategy for opening and closing the sewage interception valve according to the pollution source coordinates and diffusion trend, and controlling the opening and closing of the sewage interception valve according to the timing control strategy, wherein the timing control strategy includes relay diversion parameters of adjacent valves; The second control module is used to start the mobile emergency treatment unit according to the timing control strategy when the pollutant concentration data shows that the pollutant concentration exceeds the threshold, and perform multi-stage treatment of the polluted water body. The treatment intensity and combination method of the multi-stage treatment are adjusted according to the pollutant concentration and the treatment target.

7. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in the method according to any one of claims 1 to 5 are executed.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are executed.

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