Irrigation area project management method, device and equipment based on digital twinning and medium

Abstract

The invention provides an irrigation district engineering management method, device and equipment based on digital twinning and a medium, and belongs to the technical field of irrigation district engineering management.The method comprises the steps that irrigation district information data are collected and preprocessed; the method comprises the following steps: carrying out oblique photography on an irrigation area to collect image data of the irrigation area, constructing an irrigation area basic base map in combination with geographic information data of the irrigation area, introducing key elements of the irrigation area, carrying out three-dimensional digital modeling on the irrigation area, and introducing a BIM model of a hydraulic structure to obtain a digital twin irrigation area system; monitoring an irrigation district project through a digital twinborn irrigation district system; and according to the real-time irrigation district information data and the engineering management model, matching an irrigation district management scheduling instruction, sending the irrigation district management scheduling instruction to execution equipment of the hydraulic structure, and displaying the operation state of the corresponding hydraulic structure. According to the invention, by introducing digital twinning, refined and intelligent management of irrigation district engineering is realized, and the problems of insufficient water resource scheduling monitoring, low scheduling efficiency and high error rate in traditional irrigation district management are solved.

Description

Technical Field

[0001] The present application belongs to the technical field of irrigation project management, and specifically relates to an irrigation project management method, device, equipment and medium based on digital twins. Background Art

[0002] Irrigation areas, as important infrastructure for agricultural production, play a very important role in agricultural development. Through irrigation area project management, we can rationally manage irrigation area water resources, improve irrigation efficiency and reduce water waste.

[0003] With the development of informatization, especially the widespread application of the Internet of Things, big data, cloud computing, and artificial intelligence, irrigation project management has entered the information-based management stage. Existing irrigation district monitoring and management systems have achieved remote monitoring and control of irrigation to a certain extent, but they still face the following problems: First, they lack effective monitoring of irrigation district water resource scheduling. Existing irrigation district monitoring and management systems primarily focus on monitoring and controlling the irrigation process, while relatively lacking in monitoring methods for irrigation district water resource scheduling. This makes it difficult to ensure that the control modules execute commands correctly and accurately during the irrigation district water resource scheduling process, and it is also difficult to promptly identify any anomalies in the control modules or irrigation district systems. Second, scheduling is inefficient and prone to errors. Irrigation districts primarily rely on manual inspections of hydraulic structures. Staff must regularly visit sluices and pumping stations to check the operating status of equipment, record water levels, flow rates, and other data, and then manually summarize and analyze this data as the basis for water resource scheduling. This approach not only consumes a large amount of manpower but is also prone to delayed or irrational scheduling decisions due to errors in manual recording and untimely information transmission. For example, during the peak irrigation season, a certain area may be in urgent need of water, but due to the inability to obtain the real-time status of each channel and hydraulic structure in a timely and accurate manner, accurate water allocation decisions cannot be made quickly, affecting agricultural irrigation efficiency. Summary of the Invention

[0004] In a first aspect, an embodiment of the present application provides an irrigation project management method based on digital twins, comprising the following steps: S1. Collect irrigation information data from sensors, monitoring equipment and external data sources within the irrigation area and pre-process it; the monitoring equipment includes a video surveillance system; S2. Oblique photography is used to collect image data of the irrigation district. This data is combined with geographic information to construct a base map of the irrigation district. Key elements of the irrigation district are introduced based on this base map. Three-dimensional digital modeling of the irrigation district is then performed. BIM models of hydraulic structures are then incorporated to create a digital twin irrigation district system. This system is then incorporated into the irrigation district project management model and irrigation district management and dispatching instructions. S3. Monitoring irrigation projects through the digital twin irrigation system: Map irrigation district information data to the digital twin irrigation district system for monitoring, monitor the irrigation district site video collected by the video surveillance system, and manage the inspection of irrigation district projects; S4. Match irrigation district management and dispatching instructions based on real-time irrigation district information data and engineering management models, send the matched irrigation district management and dispatching instructions to the execution equipment of hydraulic structures through the digital twin irrigation district system, and display the operating status of the corresponding hydraulic structures.

[0005] Furthermore, the sensors in the irrigation area in step S1 include a water level meter, a flow meter, and a soil moisture sensor; The external data source is the weather station database; Irrigation area information data includes water level, flow, soil moisture, and meteorological data; the meteorological data includes rainfall, temperature, humidity, wind speed and direction; Video surveillance systems are deployed at key nodes such as sluice gates, pumping stations, and channels; Preprocessing of irrigation district information data includes data cleaning, conversion and standardization.

[0006] Furthermore, the specific steps of step S2 are as follows: S21. Use a drone equipped with a camera to photograph the entire irrigation area from vertical and four oblique angles. S22. Obtain the geographical coordinates and elevation of the irrigation area through geographic information measurement equipment to obtain geographic information data of the irrigation area; S23. Fusing the irrigation district information data with the irrigation district geographic information data to generate a basic base map of the entire irrigation district; S24. Identify the water source elements and hydraulic structures that are key elements of the irrigation district. Based on the irrigation district's geographic information data and detailed information on the water source elements and hydraulic structures, use 3D modeling software to construct a 3D digital model of the irrigation district. S25. Enter detailed information about the irrigation district, which serves as the digital twin data base, into the three-dimensional digital model of the irrigation district and overlay it with the BIM model of the hydraulic structure to create a digital twin irrigation district system. S26. Input the irrigation district project management model, historical irrigation data, and irrigation district management and scheduling instructions into the digital twin irrigation district system.

[0007] Furthermore, the specific steps of step S3 are as follows: S31. Map the irrigation district information data to the front-end interface of the digital twin irrigation district system, and issue an alarm by marking when the irrigation district information data exceeds the preset normal range; S32. A video surveillance system interface for the irrigation district site is established on the front-end interface of the digital twin irrigation district system. This interface accesses live video from key nodes and uses intelligent video analysis algorithms to analyze and process the live video in real time. This automatically identifies risk factors such as abnormal behavior, intrusion, and equipment failure, and issues early warnings to management personnel. S33. Manage inspections of irrigation projects and map inspection results to the front-end interface of the digital twin irrigation system. S34. Conduct real-time monitoring of the operating status of hydraulic structures in irrigation projects.

[0008] Furthermore, the specific steps of step S4 are as follows: S41. Input real-time irrigation district information data and historical irrigation district data into the LSTM neural network to predict the water demand of each area in the irrigation district during the future set period, and output the water demand forecast value and confidence interval; S42. Initialize the water distribution plan using the water balance model, minimize water transmission loss and water demand deviation, and construct a genetic algorithm optimization model to optimize the water distribution plan to obtain the optimal water distribution plan; S43. Use the water flow scheduling model to match irrigation district management scheduling instructions based on the water distribution plan. Simulate the execution effect of the matched irrigation district management scheduling instructions in the digital twin irrigation district system. If the deviation between the simulated execution effect and the expected execution effect exceeds a threshold, return to step S42 to regenerate the water distribution plan until the expected execution effect is met, thereby obtaining the final irrigation district management scheduling instructions. S44. Send the final irrigation district management dispatch instruction to the corresponding hydraulic structure execution device and display the operating status of the corresponding hydraulic structure; S45. Record the execution effect of the final irrigation district management scheduling instructions, and regularly optimize the LSTM neural network based on the execution effect.

[0009] Furthermore, the specific steps of step S42 are as follows: S421. Divide the irrigation area into n areas, and the water demand of each area i is Q 需水,i Predicted by LSTM neural network; S422. Calculate the initial water distribution plan Q based on the water balance model 初始,i ,satisfy: ∑Q 初始,i =Total available water - estimated water transmission loss; Among them, the water transmission loss estimate is calculated based on the channel length, material coefficient and historical loss rate; S423. Construct a genetic algorithm optimization model with the objective function: minZ=α·(∑|Q 分配,i -Q 需水,i |)+β·(actual water transmission loss); Among them, Q 分配,i is the optimized water distribution of the i-th area, α is the water demand deviation weight coefficient, β is the water transmission loss weight coefficient, and β=1-α; Actual water transmission loss =∑(k j ·L j Q 分配,j ), k j is the loss coefficient of the j-th channel, L j is the channel length; S424. Set the genetic algorithm parameters, including population size, crossover probability, mutation probability and maximum number of iterations; S425. Output the water distribution plan Q that minimizes Z through genetic algorithm 最优,i As the best water distribution solution.

[0010] Furthermore, the specific formula of the water balance model is as follows: Q 初始,i =A i ·E i ·(1-η i )+B i Among them: A i is the crop planting area in the i-th area, E i is the crop water demand intensity, η i is the irrigation efficiency coefficient, B i The amount of water required to compensate for environmental needs.

[0011] In a second aspect, this embodiment provides an irrigation project management device based on digital twins, including: A data acquisition and preprocessing module is used to collect irrigation area information data from sensors, monitoring equipment and external data sources within the irrigation area and perform preprocessing; the monitoring equipment includes a video monitoring system; The digital twin irrigation district system construction module is used to collect irrigation district image data through oblique photography, build a basic base map of the irrigation district based on the irrigation district geographic information data, introduce key elements of the irrigation district based on the basic base map, and conduct 3D digital modeling of the irrigation district. The BIM model of the hydraulic structure is then introduced to obtain the digital twin irrigation district system, and the irrigation district project management model and irrigation district management and dispatch instructions are input; Irrigation project monitoring module, used to monitor irrigation projects through the digital twin irrigation system: Map irrigation district information data to the digital twin irrigation district system for monitoring, monitor the irrigation district site video collected by the video surveillance system, and manage the inspection of irrigation district projects; The irrigation district scheduling module is used to match irrigation district management scheduling instructions based on real-time irrigation district information data and engineering management models, send the matched irrigation district management scheduling instructions to the execution equipment of hydraulic structures through the digital twin irrigation district system, and display the operating status of the corresponding hydraulic structures.

[0012] In a third aspect, an embodiment of the present application further provides an electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of the irrigation project management method based on digital twins as described in the first aspect are implemented.

[0013] In a fourth aspect, an embodiment of the present application further provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the irrigation project management method based on digital twins as described in the first aspect are implemented.

[0014] It can be seen from the above technical solutions that this application has the following advantages: The irrigation district project management method, device, equipment and medium based on digital twin provided in this application collect irrigation district information data through sensors, monitoring equipment and external data sources, and improve data quality through preprocessing, so as to realize real-time and accurate monitoring of irrigation district water resources, make up for the shortcomings of traditional monitoring means in water resource scheduling and monitoring, and provide data support for the management of irrigation district water resources; based on the digital twin irrigation district system, by predicting water demand, optimizing water distribution plan, simulating the execution effect of scheduling instructions, the optimal irrigation district management scheduling instructions are generated, the allocation efficiency of irrigation district water resources is improved, and the water demand of each area of ​​the irrigation district can be met in a timely and accurate manner, avoiding the problem of low irrigation efficiency caused by delayed or unreasonable manual decision-making; by integrating LSTM neural network and genetic algorithm , water balance model, based on real-time irrigation district information data and historical data, provides a basis for the generation and optimization of irrigation district management scheduling instructions, makes scheduling decisions reasonable and intelligent, and reduces the interference of human factors in decision-making; maps irrigation district information data to the front-end interface of the digital twin irrigation district system, and intuitively displays the operation status of the irrigation district project, so that management personnel can fully and in real time understand the irrigation district situation, discover problems in time and make solutions, and also provide a visualization platform for inspection management, thereby improving the efficiency of irrigation district management; by recording the execution effect of irrigation district management scheduling instructions and optimizing models such as LSTM neural networks accordingly, self-learning and continuous improvement of irrigation district project management can be achieved, and the accuracy and efficiency of irrigation district management can be continuously improved to adapt to the ever-changing actual situation and management needs of the irrigation district. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for the description. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0016] Figure 1 It is a flow chart of the irrigation project management method based on digital twin of the present invention.

[0017] Figure 2 This is a schematic diagram of the irrigation project management device based on digital twins of the present invention. DETAILED DESCRIPTION

[0018] The various embodiments of the present disclosure will be described more fully below in detail in the specific steps of the digital twin-based irrigation project management method. The present disclosure can have various embodiments, and adjustments and changes can be made therein. However, it should be understood that there is no intention to limit the various embodiments of the present disclosure to the specific embodiments disclosed herein, and that the present disclosure should be construed to encompass all adjustments, equivalents, and / or alternatives falling within the spirit and scope of the various embodiments of the present disclosure.

[0019] For example, irrigation districts play an important role in promoting agricultural development. Through irrigation district project management, water resources can be rationally allocated, irrigation efficiency can be improved, and water waste can be reduced.

[0020] In the wave of informatization, the widespread application of technologies such as the Internet of Things, big data, cloud computing, and artificial intelligence has propelled irrigation project management into the era of information-based management. While current irrigation district monitoring and management systems have made remote monitoring and control of irrigation feasible to a certain extent, they have exposed the following shortcomings: First, there is a lack of effective monitoring of irrigation district water resource scheduling. Existing systems primarily focus on monitoring and controlling the irrigation process, while monitoring capabilities for irrigation district water resource scheduling are relatively weak. This makes it difficult to ensure the accurate execution of control module instructions during irrigation district water resource scheduling, and it is also difficult to promptly detect abnormal conditions in the control modules or irrigation district systems. Second, scheduling is inefficient and prone to errors. Irrigation district management still relies on manual inspections of hydraulic structures. Staff must regularly visit sluice gates, pumping stations, and other locations to check equipment operation, manually record key data such as water levels and flow rates, and then summarize and analyze this data for reference in water resource scheduling. This traditional model is not only time-consuming and labor-intensive, but also prone to problems such as manual recording errors and information transmission delays, resulting in delayed or irrational scheduling decisions. During the peak irrigation season, if a region urgently needs irrigation water but cannot quickly obtain the real-time status of channels and hydraulic structures, it will be difficult to formulate accurate water allocation plans in a timely manner, thus affecting agricultural irrigation efficiency. To address the above issues, this embodiment provides an irrigation project management method based on digital twins. Through digital twin technology, it realizes the refined and intelligent management of irrigation projects, and solves the problems existing in traditional irrigation district management, such as insufficient water resource scheduling and monitoring, low scheduling efficiency and easy errors.

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0022] See also Figure 1 FIG. 1 is a flowchart of a method for managing an irrigation project based on digital twins in a specific embodiment, the method comprising the following steps: S1. Collect irrigation information data from sensors, monitoring equipment and external data sources within the irrigation area and pre-process it; the monitoring equipment includes a video surveillance system; It should be noted that irrigation district information data is collected from sensors, monitoring equipment, and external data sources within the irrigation district, thereby obtaining key information on irrigation district water resources, providing a data foundation for irrigation district project management, and ensuring the rationality and accuracy of subsequent management decisions; pre-processing the collected data improves the quality and consistency of the data, provides reliable data input for subsequent monitoring, analysis, and scheduling, and reduces the impact of data quality issues on irrigation district management; S2. Oblique photography is used to collect image data of the irrigation district. This data is combined with geographic information to construct a base map of the irrigation district. Key elements of the irrigation district are introduced based on this base map. Three-dimensional digital modeling of the irrigation district is then performed. BIM models of hydraulic structures are then incorporated to create a digital twin irrigation district system. This system is then incorporated into the irrigation district project management model and irrigation district management and dispatching instructions. It should be noted that by collecting irrigation area image data through oblique photography of the irrigation area and combining it with the irrigation area geographic information data to construct the irrigation area base map, the topography and geospatial information of the irrigation area can be truly and accurately reflected, providing high-quality basic data for three-dimensional digital modeling, and ensuring the accuracy and reliability of the model; based on the basic base map, the key elements of the irrigation area are introduced, the irrigation area is three-dimensionally modeled, and the BIM model of the hydraulic structure is introduced to obtain the digital twin irrigation area system, creating a virtual digital platform corresponding to the physical irrigation area, realizing the digital mapping of the physical entity of the irrigation area, and providing a basis for virtual simulation, real-time monitoring and intelligent management of the irrigation area project; the irrigation area project management model and irrigation area management scheduling instructions are entered into the digital twin irrigation area system, so that the digital twin system not only contains the physical information of the irrigation area, but also integrates the business logic and operation instructions of the engineering management, providing digital support for the operation management and scheduling decision-making of the irrigation area, and realizing the informatization of irrigation area management; S3. Monitoring irrigation projects through the digital twin irrigation system: Map irrigation district information data to the digital twin irrigation district system for monitoring, monitor the irrigation district site video collected by the video surveillance system, and manage the inspection of irrigation district projects; It should be noted that the irrigation district information data is mapped to the digital twin irrigation district system for monitoring, and the irrigation district on-site video collected by the video surveillance system is monitored; the inspection of the irrigation district project is managed, and the inspection situation is mapped to the front-end interface of the digital twin irrigation district system, which realizes real-time tracking and management of the inspection work, improves the quality and efficiency of the inspection work, and ensures the stable operation of the irrigation district project.

[0023] S4. Match irrigation district management and dispatch instructions based on real-time irrigation district information data and engineering management models. Send these instructions to the actuators of hydraulic structures through the digital twin irrigation district system, and display the operating status of the corresponding hydraulic structures. It should be noted that matching irrigation district management and dispatching instructions according to real-time irrigation district information data and engineering management models provides reasonable and accurate decision-making support for the generation of irrigation district management and dispatching instructions, thereby improving the rationality of dispatching decisions; through the digital twin irrigation district system, the matched irrigation district management and dispatching instructions are sent to the execution equipment of the hydraulic structure, and the operating status of the corresponding hydraulic structure is displayed, thereby realizing the precise allocation and efficient management of irrigation district water resources, and improving the utilization efficiency of irrigation district water resources and the operating benefits of the project.

[0024] Furthermore, as a refinement and expansion of the specific implementation of the above embodiment, in order to fully illustrate the specific implementation process of this embodiment, as shown below: Figure 2 As shown in FIG, another irrigation project management method based on digital twin is provided, which includes the following steps: S1. Collect irrigation information data from sensors, monitoring equipment and external data sources within the irrigation area and pre-process it; the monitoring equipment includes a video surveillance system; In step S1, the sensors in the irrigation area include a water level meter, a flow meter, and a soil moisture sensor; The external data source is the weather station database; Irrigation area information data includes water level, flow, soil moisture, and meteorological data; the meteorological data includes rainfall, temperature, humidity, wind speed and direction; Video surveillance systems are deployed at key nodes such as sluice gates, pumping stations, and channels; Pre-processing of irrigation district information data includes data cleaning, conversion and standardization; For example, the water level and flow data are normalized to the interval [0,1] by removing abnormal fluctuation data points and performing linear interpolation on missing values; Remove negative values ​​or data points outside the reasonable range from the soil moisture data, fill missing values ​​with the average of the data from adjacent time points, and keep the original unit of the soil moisture data (such as percentage) for subsequent analysis; The processing of meteorological data is as follows: For rainfall data, negative or extreme values ​​are removed, and missing values ​​are filled with moving averages. For temperature data, abnormally high or low values ​​are removed, and missing values ​​are linearly interpolated. Humidity data is processed in the same way as temperature data; For wind speed and direction data, unify the wind direction representation method (using angles or text descriptions), and fill in missing values ​​with data from adjacent time points; For example, water level, flow, and soil moisture data are collected through radar water level meters, ultrasonic flow meters, and soil moisture sensors, with a sampling frequency of ≥ 1 time / minute. Sensor data is aggregated through a 5G edge gateway, and the Kalman filter algorithm is used to eliminate noise. S2. Oblique photography is used to collect image data of the irrigation district. This data is combined with geographic information to construct a base map of the irrigation district. Key elements of the irrigation district are introduced based on this base map. Three-dimensional digital modeling of the irrigation district is then performed. BIM models of hydraulic structures are then incorporated to create a digital twin irrigation district system. This system is then incorporated into the irrigation district project management model and irrigation district management and dispatching instructions. The specific steps of step S2 are as follows: S21. Use a drone equipped with a camera to photograph the entire irrigation area from vertical and four oblique angles. For example, the vertical angle can be that the drone camera directly shoots vertically downward, at a 90-degree angle to the ground; obtaining basic data on the overall layout and geographic information of the irrigation area; It should be noted that in order to fully obtain high-resolution textures of the top and side views of the irrigation area buildings, the drone camera needs to shoot from four different tilt angles; these four tilt angles can be specifically defined as the deflection angle relative to the vertical direction, and the angle combination that can evenly cover the four sides of the irrigation area is usually selected; Assuming the drone is moving forward, we can set the four tilt angles as follows: Front tilt angle: The camera is tilted forward and downward, at an angle of approximately 30 to 45 degrees from the vertical direction (the specific angle can be adjusted according to actual needs, and 45 degrees is used as an example here); the 45-degree angle facilitates capturing elevation information in front of the irrigation area and the side texture of buildings; Rear tilt angle: The camera is tilted downward and rearward, also at an angle of approximately 45 degrees from the vertical; this angle is used to capture information about the area behind the irrigation area.

[0025] Left tilt angle: The camera is tilted to the lower left, at an angle of about 45 degrees to the vertical direction; this angle is convenient for capturing the elevation information of the left side of the irrigation area and the side texture of the building; Right tilt angle: The camera is tilted to the lower right, at an angle of approximately 45 degrees from the vertical. This angle is used to capture information on the right side of the irrigation area. For example, a five-lens oblique camera is used to photograph the irrigation area at an altitude of 100 meters to generate a real-world 3D model with a resolution of 2 cm; S22. Obtain the geographical coordinates and elevation of the irrigation area through geographic information measurement equipment to obtain geographic information data of the irrigation area; S23. Fusing the irrigation district information data with the irrigation district geographic information data to generate a basic base map of the entire irrigation district; S24. Identify the water source elements and hydraulic structures that are key elements of the irrigation district. Based on the irrigation district's geographic information data and detailed information on the water source elements and hydraulic structures, use 3D modeling software to construct a 3D digital model of the irrigation district. For example, hydraulic structures include large sluice gates on main channels, small regulating gates on branch channels, and pumping stations; water source elements include rivers, reservoirs, and channels in irrigation areas; The 3D digital model not only shows the 3D appearance of irrigation area elements such as rivers, reservoirs, and channels, but also accurately reflects the location, scale, and structural details of each hydraulic structure. It achieves a precise mapping of the physical irrigation area in virtual space. For example, the model allows for intuitive visualization of the connection between a particular sluice and upstream and downstream channels, as well as the gate height and width parameters. S25. Enter detailed information about the irrigation district, which serves as the digital twin data base, into the three-dimensional digital model of the irrigation district and overlay it with the BIM model of the hydraulic structure to create a digital twin irrigation district system. For example, detailed information about an irrigation district includes the total length of the district, the specific location and scale of each hydraulic structure (e.g., the installed capacity and lift of a pumping station), the number and location of water level monitoring stations (located at key nodes in the irrigation district, such as near reservoir dams and important water diversion points in channels), and the layout of flow monitoring stations. For example, the BIM model is aligned with the oblique photography model using the seven-parameter method with an error of ≤0.1 m; S26. Input the irrigation district project management model, historical irrigation data, and irrigation district management and scheduling instructions into the digital twin irrigation district system; Specifically, the irrigation project model includes water balance model and water flow scheduling model; S3. Monitoring irrigation projects through the digital twin irrigation system: Map irrigation district information data to the digital twin irrigation district system for monitoring, monitor the irrigation district site video collected by the video surveillance system, and manage the inspection of irrigation district projects; The specific steps of step S3 are as follows: S31. Map the irrigation district information data to the front-end interface of the digital twin irrigation district system, and issue an alarm by marking when the irrigation district information data exceeds the preset normal range; For example, the real-time status of gate opening and pump station power is dynamically rendered; S32. A video surveillance system interface for the irrigation district site is established on the front-end interface of the digital twin irrigation district system. This interface accesses live video from key nodes and uses intelligent video analysis algorithms to analyze and process the live video in real time. This automatically identifies risk factors such as abnormal behavior, intrusion, and equipment failure, and issues early warnings to management personnel. The specific video intelligent analysis algorithm is as follows: First, preprocess the video frames of the video surveillance system: Gaussian filtering is used to reduce the noise of the video frame. The filter kernel function is:

[0026] Among them, σ = 1.5, kernel size 5×5; Then, the following target detection model is built based on the improved YOLOv5: Input layer: normalize the 640×480 resolution video frame to the [0,1] interval; Backbone network: uses the CSPDarknet53 structure, including the basic convolutional layer, CSP module and detection head; The basic convolutional layer Conv (k=6, s=2, p=2); the CSP module consists of three residual blocks, each of which contains two 1×1 and one 3×3 convolutions; the detection head outputs detection results at three scales (80×80, 40×40, 20×20); For example, the target detection model is used to perform special detection for foreign objects on gates: A dual-channel detection model was constructed, where channel 1 detected conventional foreign objects (confidence threshold 0.7); Conventional foreign objects include floating objects such as water plants and plastic bags, and hard objects such as stones. Water plants and plastic bags are segmented using HSV color space (H∈[35,77],S∈[43,255]), while hard objects such as stones are detected based on edge density (edge ​​pixel ratio>15%). Channel 2 detects structural anomalies (confidence threshold 0.85); Structural anomalies include gate programming and gate jamming. Gate deformation is detected by SIFT feature point matching, and an alarm is triggered when the offset of the matching point is greater than 5 pixels. Gate jamming is triggered by combining the opening sensor data and when the difference between the command and the measured opening is greater than 5% for 30 seconds. The final alarm judgment conditions are: Alarm Level = { Level 0 (normal): No abnormality is detected in channel 1 and channel 2 Level 1 (early warning): An abnormality is detected in any channel and lasts for less than 10 seconds Level 2 (Emergency): Abnormality is detected simultaneously in both channels or in a single channel for ≥ 10 seconds } S33. Manage inspections of irrigation projects and map inspection results to the front-end interface of the digital twin irrigation system. Specifically, an inspection plan is developed, with clear inspection cycles, routes, and content, and tasks assigned to inspectors. Inspectors conduct on-site inspections of irrigation projects according to the plan, recording inspection details, including equipment appearance, operating sounds, and surrounding environment information, and uploading them to the digital twin irrigation system in real time via mobile terminals. The system tracks the execution of inspection tasks, reminds inspectors to complete tasks on time, and promptly addresses any problems found, ensuring the standardization and effectiveness of inspection work. S34. Real-time monitoring of the operating status of hydraulic structures in irrigation projects; Specifically, sensors are used to obtain key operating parameters of hydraulic structures in real time, such as gate opening, water level change rate, flow rate, equipment vibration, temperature, etc. These parameters are monitored and analyzed in real time to determine whether the equipment is operating normally. Once an abnormal situation is found, such as abnormal changes in gate opening, sudden increase or decrease in flow rate, an alarm is issued in time to remind management personnel to take action and ensure the safe and stable operation of hydraulic structures. S4. Match irrigation district management and dispatch instructions based on real-time irrigation district information data and engineering management models. Send these instructions to the actuators of hydraulic structures through the digital twin irrigation district system, and display the operating status of the corresponding hydraulic structures. The specific steps of step S4 are as follows: S41. Input real-time irrigation district information data and historical irrigation district data into the LSTM neural network to predict the water demand of each area in the irrigation district during the future set period, and output the water demand forecast value and confidence interval; For example, based on real-time soil moisture, meteorological data, and historical irrigation data, the water demand of each area in the next 24 hours is predicted through an LSTM neural network; S42. Initialize the water distribution plan using the water balance model. Minimize water transmission loss and water demand deviation. Optimize the water distribution plan using a genetic algorithm optimization model to obtain the optimal water distribution plan. The specific steps of step S42 are as follows: S421. Divide the irrigation area into n areas, and the water demand of each area i is Q 需水,i Predicted by LSTM neural network; S422. Calculate the initial water distribution plan Q based on the water balance model 初始,i ,satisfy: ∑Q 初始,i =Total available water - estimated water transmission loss; Among them, the water transmission loss estimate is calculated based on the channel length, material coefficient and historical loss rate; The specific formula of the water balance model is as follows: Q 初始,i =A i ·E i ·(1-η i )+B i Among them: A i is the crop planting area in the i-th area, E i is the crop water demand intensity, η i is the irrigation efficiency coefficient, B i Compensation for environmental water demand; S423. Construct a genetic algorithm optimization model with the objective function: minZ=α·(∑|Q 分配,i -Q需水,i |)+β·(actual water transmission loss); Among them, Q 分配,i is the optimized water distribution of the i-th area, α is the water demand deviation weight coefficient, β is the water transmission loss weight coefficient, and β=1-α; Actual water transmission loss =∑(k j ·L j Q 分配,j ), k j is the loss coefficient of the j-th channel, L j is the channel length; Exemplarily, 0.6≤α≤0.9; S424. Set the genetic algorithm parameters, including population size, crossover probability, mutation probability and maximum number of iterations; S425. Output the water distribution plan Q that minimizes Z through genetic algorithm 最优,i As the best water distribution solution; S43. Use the water flow scheduling model to match irrigation district management scheduling instructions based on the water distribution plan. Simulate the execution effect of the matched irrigation district management scheduling instructions in the digital twin irrigation district system. If the deviation between the simulated execution effect and the expected execution effect exceeds a threshold, return to step S42 to regenerate the water distribution plan until the expected execution effect is met, thereby obtaining the final irrigation district management scheduling instructions. S44. Send the final irrigation district management dispatch instruction to the corresponding hydraulic structure execution device and display the operating status of the corresponding hydraulic structure; For example, the final irrigation district management dispatch instruction is sent to the PLC controller of the execution equipment of the hydraulic structure via the Modbus TCP protocol; S45. Record the execution effect of the final irrigation district management scheduling instructions, and regularly optimize the LSTM neural network based on the execution effect.

[0027] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0028] like Figure 2 As shown, the following is an embodiment of the irrigation project management device based on digital twin provided by the embodiment of the present disclosure. The device and the irrigation project management method based on digital twin of the above embodiments belong to the same inventive concept. For details not fully described in the embodiment of the irrigation project management device based on digital twin, please refer to the embodiment of the irrigation project management method based on digital twin.

[0029] The device includes: A data acquisition and preprocessing module is used to collect irrigation area information data from sensors, monitoring equipment and external data sources within the irrigation area and perform preprocessing; the monitoring equipment includes a video monitoring system; The digital twin irrigation district system construction module is used to collect irrigation district image data through oblique photography, build a basic base map of the irrigation district based on the irrigation district geographic information data, introduce key elements of the irrigation district based on the basic base map, and conduct 3D digital modeling of the irrigation district. The BIM model of the hydraulic structure is then introduced to obtain the digital twin irrigation district system, and the irrigation district project management model and irrigation district management and dispatch instructions are input; Irrigation project monitoring module, used to monitor irrigation projects through the digital twin irrigation system: Map irrigation district information data to the digital twin irrigation district system for monitoring, monitor the irrigation district site video collected by the video surveillance system, and manage the inspection of irrigation district projects; The irrigation district scheduling module is used to match irrigation district management scheduling instructions based on real-time irrigation district information data and engineering management models, send the matched irrigation district management scheduling instructions to the execution equipment of hydraulic structures through the digital twin irrigation district system, and display the operating status of the corresponding hydraulic structures.

[0030] The irrigation project management method based on digital twins provided in the embodiments of the present application can be applied to electronic devices. Those skilled in the art will understand that the electronic device structure involved in the embodiments of the present invention does not constitute a limitation on the electronic device, and the electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. In the embodiments of the present invention, electronic devices include but are not limited to laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the embodiments of the present application described and / or required herein.

[0031] The electronic device may include a processor, an external memory interface, an internal memory, a universal serial bus (USB) interface, a charging management module, a power management module, a battery, a wireless communication module, an audio module, a speaker, a microphone, a sensor module, a button, a camera, a display, and a SIM card interface, etc.

[0032] It is understood that the structures illustrated in the embodiments of the present application do not constitute specific limitations on the electronic device. In other embodiments of the present application, the electronic device may include more or fewer components than shown, or combine or separate certain components, or arrange the components differently. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0033] A processor may include one or more processing units, such as a central processing unit (CPU), an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU). Different processing units may be independent devices or integrated into one or more processors.

[0034] The processor can be the nerve center and command center of the electronic device. The controller can generate operation control signals based on the instruction opcode and timing signal to complete the control of instruction fetching and execution.

[0035] The processor may also include a memory for storing instructions and data. In some embodiments, the memory in the processor is a cache memory. This memory can store instructions or data that the processor has just used or is reusing. If the processor needs to use the instruction or data again, it can directly call it from the memory. This avoids repeated accesses, reduces processor latency, and thus improves system efficiency.

[0036] The above-mentioned electronic equipment realizes the irrigation area project management method based on digital twin of the present application, which collects irrigation area information data from sensors, monitoring equipment and external data sources in the irrigation area and pre-processes it; the monitoring equipment includes a video monitoring system; oblique photography of the irrigation area is performed to collect irrigation area image data, and a basic base map of the irrigation area is constructed in combination with the irrigation area geographic information data. Based on the basic base map of the irrigation area, the key elements of the irrigation area are introduced, and three-dimensional digital modeling of the irrigation area is performed. Then, the BIM model of the hydraulic structure is introduced to obtain a digital twin irrigation area system, and the irrigation area project management model and irrigation area management scheduling instructions are entered; the irrigation area project is monitored by the digital twin irrigation area system: the irrigation area The district information data is mapped to the digital twin irrigation district system for monitoring, the irrigation district on-site video collected by the video surveillance system is monitored, and the inspection of the irrigation district project is managed; the irrigation district management scheduling instructions are matched according to the real-time irrigation district information data and the project management model, and the matched irrigation district management scheduling instructions are sent to the execution equipment of the hydraulic structure through the digital twin irrigation district system, and the technical solution of the operating status of the corresponding hydraulic structure is displayed. By introducing digital twins, the beneficial effect of realizing the refined and intelligent management of the irrigation district project and solving the problems of insufficient water resource scheduling and monitoring, low scheduling efficiency and easy errors in traditional irrigation district management is achieved.

[0037] The storage medium provided in this application stores a program product that can implement an irrigation project management method based on digital twins.

[0038] The irrigation district project management method based on digital twins includes: collecting irrigation district information data from sensors, monitoring equipment and external data sources within the irrigation district and preprocessing it; the monitoring equipment includes a video monitoring system; performing oblique photography on the irrigation district to collect irrigation district image data, constructing an irrigation district basic base map in combination with the irrigation district geographic information data, introducing key elements of the irrigation district based on the irrigation district basic base map, performing three-dimensional digital modeling of the irrigation district, and then introducing the BIM model of the hydraulic structure to obtain a digital twin irrigation district system, and entering the irrigation district project management model and irrigation district management scheduling instructions; monitoring the irrigation district project through the digital twin irrigation district system: mapping the irrigation district information data to the digital twin irrigation district system for monitoring, monitoring the irrigation district on-site video collected by the video monitoring system, and managing the inspection of the irrigation district project; matching the irrigation district management scheduling instructions according to the real-time irrigation district information data and the project management model, sending the matched irrigation district management scheduling instructions to the execution equipment of the hydraulic structure through the digital twin irrigation district system, and displaying the operating status of the corresponding hydraulic structure.

[0039] In some possible implementations, the digital twin-based irrigation project management method disclosed herein can be implemented in the form of a program product, which includes program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps of various exemplary implementations of the present disclosure described in the above "Exemplary Method" section of this specification.

[0040] The storage medium of the present disclosure can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, a system, device or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0041] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for irrigation project management based on digital twins, characterized in that: The steps include: S1. Collect irrigation information data from sensors, monitoring equipment and external data sources within the irrigation area and pre-process it; the monitoring equipment includes a video surveillance system; S2. Oblique photography is used to collect image data of the irrigation district. This data is combined with geographic information to construct a base map of the irrigation district. Key elements of the irrigation district are introduced based on this base map. Three-dimensional digital modeling of the irrigation district is then performed. BIM models of hydraulic structures are then incorporated to create a digital twin irrigation district system. This system is then incorporated into the irrigation district project management model and irrigation district management and dispatching instructions. S3. Monitoring irrigation projects through the digital twin irrigation system: Map irrigation district information data to the digital twin irrigation district system for monitoring, monitor the irrigation district site video collected by the video surveillance system, and manage the inspection of irrigation district projects; S4. Match irrigation district management and dispatching instructions based on real-time irrigation district information data and engineering management models, send the matched irrigation district management and dispatching instructions to the execution equipment of hydraulic structures through the digital twin irrigation district system, and display the operating status of the corresponding hydraulic structures.

2. The irrigation project management method based on digital twin according to claim 1 is characterized in that: In step S1, the sensors in the irrigation area include a water level meter, a flow meter, and a soil moisture sensor; The external data source is the weather station database; Irrigation area information data includes water level, flow, soil moisture, and meteorological data; the meteorological data includes rainfall, temperature, humidity, wind speed and direction; Video surveillance systems are deployed at key nodes such as sluice gates, pumping stations, and channels; Preprocessing of irrigation district information data includes data cleaning, conversion and standardization.

3. The irrigation project management method based on digital twin according to claim 2 is characterized in that: The specific steps of step S2 are as follows: S21. Use a drone equipped with a camera to photograph the entire irrigation area from vertical and four oblique angles. S22. Obtain the geographical coordinates and elevation of the irrigation area through geographic information measurement equipment to obtain geographic information data of the irrigation area; S23. Fusing the irrigation district information data with the irrigation district geographic information data to generate a basic base map of the entire irrigation district; S24. Identify the water source elements and hydraulic structures that are key elements of the irrigation district. Based on the irrigation district's geographic information data and detailed information on the water source elements and hydraulic structures, use 3D modeling software to construct a 3D digital model of the irrigation district. S25. Enter detailed information about the irrigation district, which serves as the digital twin data base, into the three-dimensional digital model of the irrigation district and overlay it with the BIM model of the hydraulic structure to create a digital twin irrigation district system. S26. Input the irrigation district project management model, historical irrigation data, and irrigation district management and scheduling instructions into the digital twin irrigation district system.

4. The irrigation project management method based on digital twin according to claim 3 is characterized in that: The specific steps of step S3 are as follows: S31. Map the irrigation district information data to the front-end interface of the digital twin irrigation district system, and issue an alarm by marking when the irrigation district information data exceeds the preset normal range; S32. A video surveillance system interface for the irrigation district site is established on the front-end interface of the digital twin irrigation district system. This interface accesses live video from key nodes and uses intelligent video analysis algorithms to analyze and process the live video in real time. This automatically identifies risk factors such as abnormal behavior, intrusion, and equipment failure, and issues early warnings to management personnel. S33. Manage inspections of irrigation projects and map inspection results to the front-end interface of the digital twin irrigation system. S34. Conduct real-time monitoring of the operating status of hydraulic structures in irrigation projects.

5. The irrigation project management method based on digital twin according to claim 4 is characterized in that: The specific steps of step S4 are as follows: S41. Input real-time irrigation district information data and historical irrigation district data into the LSTM neural network to predict the water demand of each area in the irrigation district during the future set period, and output the water demand forecast value and confidence interval; S42. Initialize the water distribution plan using the water balance model, minimize water transmission loss and water demand deviation, and construct a genetic algorithm optimization model to optimize the water distribution plan to obtain the optimal water distribution plan; S43. Use the water flow scheduling model to match irrigation district management scheduling instructions based on the water distribution plan. Simulate the execution effect of the matched irrigation district management scheduling instructions in the digital twin irrigation district system. If the deviation between the simulated execution effect and the expected execution effect exceeds a threshold, return to step S42 to regenerate the water distribution plan until the expected execution effect is met, thereby obtaining the final irrigation district management scheduling instructions. S44. Send the final irrigation district management dispatch instruction to the corresponding hydraulic structure execution device and display the operating status of the corresponding hydraulic structure; S45. Record the execution effect of the final irrigation district management scheduling instructions, and regularly optimize the LSTM neural network based on the execution effect.

6. The irrigation project management method based on digital twin according to claim 5 is characterized in that: The specific steps of step S42 are as follows: S421. Divide the irrigation area into n areas, and the water demand of each area i is Q 需水,i Predicted by LSTM neural network; S422. Calculate the initial water distribution plan Q based on the water balance model 初始,i ,satisfy: ∑Q 初始,i =Total available water - estimated water transmission loss; Among them, the water transmission loss estimate is calculated based on the channel length, material coefficient and historical loss rate; S423. Construct a genetic algorithm optimization model with the objective function: minZ=α·(∑|Q 分配,i -Q 需水,i |)+β·(actual water transmission loss); Among them, Q 分配,i is the optimized water distribution of the i-th area, α is the water demand deviation weight coefficient, β is the water transmission loss weight coefficient, and β=1-α; Actual water transmission loss =∑(k j ·L j Q 分配,j ), k j is the loss coefficient of the j-th channel, L j is the channel length; S424. Set the genetic algorithm parameters, including population size, crossover probability, mutation probability and maximum number of iterations; S425. Output the water distribution plan Q that minimizes Z through genetic algorithm 最优,i As the best water distribution solution.

7. The irrigation project management method based on digital twin according to claim 6 is characterized in that: The specific formula of the water balance model is as follows: Q 初始,i =A i ·E i ·(1-th i )+B i Among them: A i is the crop planting area in the i-th area, E i is the crop water demand intensity, η i is the irrigation efficiency coefficient, B i The amount of water required to compensate for environmental needs.

8. An irrigation project management device based on digital twin, characterized in that: include: A data acquisition and preprocessing module is used to collect irrigation area information data from sensors, monitoring equipment and external data sources within the irrigation area and perform preprocessing; the monitoring equipment includes a video monitoring system; The digital twin irrigation district system construction module is used to collect irrigation district image data through oblique photography, build a basic base map of the irrigation district based on the irrigation district geographic information data, introduce key elements of the irrigation district based on the basic base map, and conduct 3D digital modeling of the irrigation district. The BIM model of the hydraulic structure is then introduced to obtain the digital twin irrigation district system, and the irrigation district project management model and irrigation district management and dispatch instructions are input; Irrigation project monitoring module, used to monitor irrigation projects through the digital twin irrigation system: Map irrigation district information data to the digital twin irrigation district system for monitoring, monitor the irrigation district site video collected by the video surveillance system, and manage the inspection of irrigation district projects; The irrigation district scheduling module is used to match irrigation district management scheduling instructions based on real-time irrigation district information data and engineering management models, send the matched irrigation district management scheduling instructions to the execution equipment of hydraulic structures through the digital twin irrigation district system, and display the operating status of the corresponding hydraulic structures.

9. An electronic device, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the irrigation project management method based on digital twins as claimed in any one of claims 1 to 7 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the irrigation project management method based on digital twins as described in any one of claims 1 to 7 are implemented.

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