A water conservancy information management system based on a digital twin model

Abstract

This invention discloses a water conservancy information management system based on a digital twin model, belonging to the field of water conservancy management technology. The system includes a block-based management module. Based on equipment, topography, and hydrological information data of water conservancy facilities, management blocks are divided according to the characteristics of these data. Each management block has locally deployed computing devices, and management computing tasks are allocated according to the load of these local computing devices. This block-based management module divides the equipment, topography, and hydrological environment of water conservancy facilities into multiple gridded node units. Through independent monitoring and management of each management block, each block independently undertakes data storage and computing tasks, reducing the data load pressure on a single central server and avoiding response delays and failure risks caused by central server overload, thus ensuring the stable operation of the water conservancy information management system.

Description

Technical Field

[0001] This invention relates to the field of water conservancy management technology, specifically to a water conservancy information management system based on a digital twin model. Background Technology

[0002] Water conservancy management refers to the systematic work of utilizing, protecting, and managing water sources, water areas, and water conservancy facilities. Its core objectives are to ensure water security, eliminate water hazards, rationally allocate water resources, and verify the correctness of water conservancy facilities. It involves water allocation, engineering operation and maintenance, and water ecological protection.

[0003] The existing water conservancy information management system relies on the central server of the control center for the processing and management of water conservancy facilities and hydrological information. The central server of the control center needs to undertake the collection, storage and data analysis of water conservancy information. The central server needs to bear a lot of data pressure, which makes the central server work under high load. This makes the water conservancy information management system risk system response delay and system failure due to the overload of the central server, thus restricting the operation stability and management efficiency of the water conservancy information management system. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a water conservancy information management system based on a digital twin model, which solves the problems mentioned in the background section.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a water conservancy information management system based on a digital twin model, the water conservancy information management system comprising: a block management module, a digital twin module, a blockchain network module, and a health management module;

[0006] The block-based management module divides the water conservancy facilities into management blocks based on the equipment, terrain, and hydrological information data of the water conservancy facilities. Each management block has a locally deployed computing device, and the local computing device of the management block is used to allocate management computing tasks according to the load.

[0007] The digital twin module is used to simulate the entire life cycle of water conservancy facilities and hydrological environment. It establishes a digital twin model based on the acquired equipment, regional topography and hydrological information data of the water conservancy facilities and the corresponding historical data. The digital twin model outputs the entire life cycle data simulating the equipment, topography and hydrological information status of the water conservancy facilities. The digital twin module is deployed in the computing device of the block management module.

[0008] The blockchain network module uses each management block as an independent management point. Each management point is equipped with a distributed ledger. The distributed ledger is used for the storage and management of the full life cycle data. The full life cycle data is written into the distributed ledger in encrypted form. At the same time, cross-regional data sharing is realized according to the allocation and management of the block-based management module, and the full life cycle data is transmitted to the water conservancy control center through the blockchain network module.

[0009] The health management module, based on the full life cycle data generated by the digital twin module, and the analysis results of the full life cycle data for each management block, determines the status of the water conservancy facilities and hydrological environment, assesses the overall health level, and generates management early warning information.

[0010] The block management module includes: a block partitioning submodule, a load balancing submodule, and a cross-chain collaboration submodule;

[0011] The block division submodule imports the equipment, topography, and hydrological information data of the water conservancy facilities. The block division submodule analyzes the equipment, topography, and hydrological information data of the water conservancy facilities through the computing device, aligns the geometric coordinates of the equipment, topography, and hydrological information data of the water conservancy facilities, and divides the water conservancy facilities into management blocks according to the grid-based division rules after the geometric coordinates are aligned.

[0012] The load balancing submodule classifies the computing load of the computing devices in the management block and sets corresponding load thresholds according to the classification. When the management computing task of the management block exceeds the preset load threshold, the management computing task is sent to the computing devices of the surrounding low-load management blocks, and the calculation result is returned to the computing device of the corresponding management block after the calculation is completed.

[0013] The cross-chain collaboration submodule supports data sharing and collaborative decision-making among the management blocks. It establishes an encrypted channel through the blockchain network module, verifies data requests sent according to permissions, transmits shared data in a standardized format, and triggers a joint decision-making process when an event occurs that crosses the management blocks. The management blocks synchronize data and collaboratively generate a scheduling scheme.

[0014] Preferably, the method for dividing management blocks according to the equipment, topography, and hydrological information data characteristics of the water conservancy facilities includes:

[0015] The process involves acquiring three types of basic data related to the water conservancy facilities: equipment, topography, and hydrological information. The equipment data includes information on the type, quantity, distribution location, functional parameters, and management unit of the equipment. The topography data includes spatial data on watershed elevation, slope, landform type, and administrative boundaries. The hydrological information includes hydrological data on watershed river system distribution, river course, flow direction, water level fluctuations, flow characteristics, and watershed extent.

[0016] Features of the three types of basic data of the water conservancy facilities—equipment, topography, and hydrological information—are extracted. Weights are set according to the importance of the equipment, functional relevance, and management distance of the water conservancy facilities. Weights are also set based on the continuity of the topography, elevation difference, and geographical barriers. Finally, weights are set according to the water flow connectivity, watershed catchment relationship, and water level influence range of the hydrological information.

[0017] Using the weight of the device as a base point, the features of the associated terrain and hydrological information are divided by extending the distance outward from the characteristics of the device, thereby determining the scope of the management block and completing the gridded division of the management block.

[0018] Preferably, the allocation logic for allocating management computing tasks to the local computing device of the management block according to the load is as follows:

[0019] First, the computational workload and importance of the management blocks are classified. According to the importance of the operation of the equipment in the management blocks, the complexity of the terrain, and the frequency of change of the hydrological information, the load areas are divided into three levels: heavy load area, medium load area, and low load area.

[0020] The three-level load area uses a hybrid approach of proof-of-work and proof-of-weight to allocate computing tasks. The proof-of-work is evaluated based on a combination of equipment, topographic and hydrological information data of the water conservancy facilities in the management block and the corresponding historical data. The proof-of-weight is determined based on the load classification and hardware resource configuration of the management block.

[0021] When the computational load of the heavy-load region exceeds the set load threshold, the heavy-load region assigns management computing tasks to the medium-load region and the low-load region, and returns the calculation results to the computing device of the heavy-load region after the calculation is completed. When allocating the management computing tasks, priority is given to allocating them to the low-load region.

[0022] Preferably, the blockchain network module includes: a distributed ledger submodule, a cross-chain communication submodule, and a node management submodule;

[0023] The distributed ledger submodule: After the digital twin module simulates and generates the full lifecycle data, the distributed ledger submodule encrypts and stores the full lifecycle data to ensure that the full lifecycle data cannot be changed;

[0024] The cross-chain communication submodule is used to transmit the full lifecycle data stored in the distributed ledger submodule to the water conservancy control center, and the transmission process adopts an encrypted transmission method, and provides cross-chain data communication for data sharing between the management blocks;

[0025] The node management submodule is used to generate a unique block identification code for different management blocks. When the distributed ledger submodule stores the full lifecycle data, it synchronously performs encoding matching on the full lifecycle data and then encrypts and stores it. When the cross-chain communication submodule transmits the full lifecycle data and shares data between the management blocks, the node management submodule verifies the corresponding block identification code. After successful verification, the transmission of the full lifecycle data and the sharing of data between the management blocks can be carried out.

[0026] Preferably, the health management module includes: a status monitoring submodule, a health assessment submodule, and an early warning response submodule;

[0027] The status monitoring submodule: The blockchain network module uploads the full life cycle data to the water conservancy control center. The status monitoring submodule identifies the uploaded full life cycle data and judges the results of the full life cycle data. When there are abnormal values ​​in the full life cycle data, it is determined that the corresponding management block has a risk and is marked as a risk management block.

[0028] The health assessment submodule further analyzes the full lifecycle data of the risk management block to identify specific anomalies in the equipment, topography, and hydrological information data of the water conservancy facilities. The health assessment submodule assesses and predicts the anomalies, evaluates their risk level, predicts potential risk items in other equipment, topography, and hydrological information within the risk management block, and generates an assessment report.

[0029] The early warning response submodule: when the health score in the assessment report is lower than a preset threshold, it triggers an early warning for the corresponding item, generates early warning information and sends it to the staff's smart device or the server of the water conservancy control center, and at the same time generates an adjustment plan corresponding to the early warning information.

[0030] Preferably, the water conservancy information management system further includes: a data acquisition module, a data processing module, and a management interaction module;

[0031] The data acquisition module is used to collect equipment operating parameters of the water conservancy facility, hydrological information on water quality, water quantity and flow of the water conservancy facility, and three-dimensional topographic images of the water conservancy facility environment.

[0032] The data processing module is used to process the operating parameters, three-dimensional terrain images and hydrological information collected by the data acquisition module, and output the processed equipment, terrain and hydrological information data of the water conservancy facility, which is deployed in the computing device.

[0033] The management interaction module is used to support staff in managing the water conservancy information management system and viewing its status.

[0034] Preferably, the management interaction module includes: a user interaction submodule and an AR visualization submodule;

[0035] The user interaction submodule provides a graphical user interface to support staff in operating and managing the water conservancy information management system.

[0036] The AR visualization submodule overlays the simulation results of the digital twin module with the physical scene to display the information management status of water conservancy facilities.

[0037] Preferably, the data acquisition module includes:

[0038] Water level sensors, flow sensors, water quality sensors, equipment vibration sensors, and meteorological sensors are used to collect data on the equipment and hydrological information of the water conservancy facilities and are deployed in the equipment and aquatic environment of the water conservancy facilities.

[0039] A mapping drone, equipped with a high-definition camera and lidar, is used to collect topographic data of the water conservancy facilities.

[0040] This invention provides a water resources information management system based on a digital twin model. It has the following beneficial effects:

[0041] (1) By dividing the equipment, terrain and hydrological environment of water conservancy facilities into management blocks through the block management module, the entire water conservancy facilities and environment are divided into multiple gridded node units. Through separate monitoring and management of each management block, it independently undertakes data storage and computing tasks, reduces the data load pressure of a single central server, and achieves a balanced operation of the water conservancy information management system. It avoids response delay and failure risk caused by overload of the central server, ensures the stable operation of the water conservancy information management system, and improves the continuity of management processes.

[0042] (2) By distributing water conservancy information management to each block node through the blockchain network module, the decentralized characteristics of blockchain are utilized to transform the management mode of a single central server into the independent operation of each node. The information management of each block is aggregated by the blockchain network, replacing the traditional centralized processing mode of the central server. The management pressure of each node is lower, thereby achieving a more stable and efficient water conservancy management effect.

[0043] (3) The digital twin module constructs a full life cycle digital twin model based on the collected water conservancy data and historical data. Combined with the block management module, it divides the management blocks according to the characteristics of the basin and facilities, realizes the accurate mapping and zoned control of water conservancy information, makes the water conservancy information management more refined and the management more targeted, provides dynamic visualization support for the full life cycle management of water conservancy facilities, and improves the accuracy of management decisions. Attached Figure Description

[0044] Figure 1 This is a system block diagram of a water conservancy information management system based on a digital twin model according to the present invention;

[0045] Figure 2 This is a management flowchart of a water conservancy information management system based on a digital twin model, according to the present invention. Detailed Implementation

[0046] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] Example 1

[0048] Please see Figure 1-2 This invention provides a water conservancy information management system based on a digital twin model. To achieve the above objectives, this invention is implemented through the following technical solution: The water conservancy information management system includes: a block management module, a digital twin module, a blockchain network module, and a health management module;

[0049] The block-based management module divides management blocks according to the characteristics of equipment, terrain and hydrological information data of water conservancy facilities. Each management block has a local computing device, and the management computing tasks are allocated according to the load using the local computing device of the management block.

[0050] The digital twin module is used to simulate the entire life cycle of water conservancy facilities and hydrological environment. It establishes a digital twin model based on the acquired equipment, regional topography and hydrological information data of water conservancy facilities and corresponding historical data. The digital twin model outputs full life cycle data simulating the equipment, topography and hydrological information status of water conservancy facilities. The digital twin module is deployed in the computing device of the block-based management module.

[0051] The blockchain network module uses each management block as an independent management point. Each management point is equipped with a distributed ledger, which is used for the storage and management of full lifecycle data. The full lifecycle data is written to the distributed ledger in encrypted form. At the same time, cross-regional data sharing is realized according to the allocation and management of the block-based management module, and the full lifecycle data is transmitted to the water conservancy control center through the blockchain network module.

[0052] The health management module, based on the full life cycle data generated by the digital twin module, analyzes the full life cycle data of each management block to determine the status of water conservancy facilities and hydrological environment, assess the overall health level, and generate management early warning information.

[0053] The block management module includes: a block partitioning submodule, a load balancing submodule, and a cross-chain collaboration submodule;

[0054] Block partitioning submodule: Import equipment, topography and hydrological information data of water conservancy facilities. The block partitioning submodule analyzes the equipment, topography and hydrological information data of water conservancy facilities through computing equipment, aligns the geometric coordinates of the equipment, topography and hydrological information data of water conservancy facilities, and divides the water conservancy facilities into management blocks according to the grid partitioning rules after the geometric coordinates are aligned.

[0055] Load balancing submodule: classifies the computing load of the computing devices in the management block and sets corresponding load thresholds according to the classification. When the management computing task of the management block exceeds the preset load threshold, it sends the management computing task to the computing devices of the surrounding low-load management blocks and returns the computing result to the computing device of the corresponding management block after the calculation is completed.

[0056] Cross-chain collaboration sub-module: Supports data sharing and collaborative decision-making among management blocks. It establishes an encrypted channel through the blockchain network module, verifies data requests sent according to permissions, and transmits shared data in a standardized format. When an event occurs that crosses management blocks, it triggers a joint decision-making process, and each management block synchronizes data and collaboratively generates a scheduling plan.

[0057] In this embodiment, the corresponding water conservancy facility area is specifically divided into multiple management blocks using a grid-based approach based on equipment, terrain, and hydrological information. Then, various monitoring sensors are deployed in a distributed manner according to these management blocks, forming a sensing network covering the entire water area and all facilities. A mapping drone is then used to capture and scan from the air, constructing a 3D image of the water environment and facilities. This image is updated regularly to promptly detect changes in the terrain and hydrological information of the water environment. The operational data of these water conservancy facilities, the water area status, and the 3D images are transmitted to locally deployed computing devices for data processing. The processed data generates standardized data, which is then imported into a digital twin model. Simultaneously, the digital twin model calls upon corresponding historical water conservancy data. Using these two sets of data, the digital twin model simulates the entire lifecycle of water conservancy information, thereby generating full lifecycle data for the corresponding management blocks. At this point, the corresponding management block transmits the generated full lifecycle data to the control center via a blockchain network. At this time, water conservancy staff can view and manage water conservancy information in each management block through the management interaction module. During user management operations, they can monitor, issue warnings, or issue commands to one or more management blocks individually. Through the decentralized design of the blockchain network, each management block operates and manages independently. When the corresponding management block receives command information, the local computing device can execute the command. During the operation of the water conservancy information management system, the health management module monitors water conservancy facilities, water levels, water flow velocity, and water volume in real time. If the operating parameters of the equipment in the water conservancy facility change, the health analysis is initiated. When the health score of the equipment is lower than the set threshold, a health risk warning information for the corresponding facility is generated and sent to the smart terminal or control center of the water conservancy staff through the blockchain network. This enables timely feedback for maintenance and timely awareness of water conservancy equipment and water risks, allowing for timely equipment maintenance or flood control operations.

[0058] Example 2

[0059] Specifically, the methods for dividing management zones based on the equipment, topography, and hydrological information data characteristics of water conservancy facilities include:

[0060] The basic data to be acquired includes three categories: equipment, topography, and hydrological information of water conservancy facilities. Equipment data includes the type, quantity, distribution location, functional parameters, and management unit of water conservancy facilities. Topographic data includes spatial data of watershed elevation, slope, landform type, and administrative boundaries. Hydrological information includes hydrological data of watershed river system distribution, river course, flow direction, water level variation, flow characteristics, and watershed extent.

[0061] Features of three types of basic data of water conservancy facilities—equipment, topography, and hydrological information—are extracted. Weights are set according to the importance of equipment, functional relevance, and management distance of water conservancy facilities. Weights are also set based on the continuity of topography, elevation difference, and geographical barriers. Finally, weights are set according to the water flow connectivity, watershed catchment relationship, and water level influence range of hydrological information.

[0062] Using the weight of the equipment as a base point, the characteristics of the equipment are extended outward to divide the associated terrain and hydrological information features, thereby determining the scope of the management block and completing the gridded management block division.

[0063] The specific logic for allocating management computing tasks to the local computing devices of the management block based on load is as follows:

[0064] First, the computational workload and importance of the management blocks are classified according to the importance of the equipment operation within the management blocks, the complexity of the corresponding terrain, and the frequency of changes in the corresponding hydrological information. The blocks are divided into three load areas: heavy load area, medium load area, and low load area.

[0065] The three-level load area adopts a hybrid approach of proof-of-work and proof-of-weight to allocate computing tasks. The proof-of-work is evaluated based on the combination of equipment, topography and hydrological information data of water conservancy facilities in the management block and corresponding historical data. The proof-of-weight is determined based on the load classification and hardware resource configuration of the management block.

[0066] When the computational load in the heavy-load area exceeds the set load threshold, the heavy-load area manages the computational tasks to the medium-load and low-load areas, and returns the computation results to the computing device in the heavy-load area after the computation is completed. When allocating and managing computational tasks, priority is given to allocating them to the low-load area.

[0067] The blockchain network module includes: a distributed ledger submodule, a cross-chain communication submodule, and a node management submodule;

[0068] Distributed Ledger Submodule: After the digital twin module simulates and generates full lifecycle data, the distributed ledger submodule encrypts and stores the full lifecycle data to ensure that the full lifecycle data cannot be changed.

[0069] Cross-chain communication submodule: Used to transmit the full lifecycle data stored in the distributed ledger submodule to the water conservancy control center, and the transmission process adopts encrypted transmission method, and provides cross-chain data communication for data sharing between management blocks;

[0070] Node Management Submodule: Used to generate a unique block identification code for different management blocks. When the distributed ledger submodule stores full lifecycle data, it synchronously performs encoding matching on the full lifecycle data and then encrypts and stores it. When the cross-chain communication submodule transmits full lifecycle data and shares data between management blocks, it verifies the corresponding block identification code through the node management submodule. After verification, the transmission of full lifecycle data and data sharing between management blocks can be carried out.

[0071] The health management module includes: a status monitoring submodule, a health assessment submodule, and an early warning response submodule;

[0072] Status monitoring submodule: The blockchain network module uploads the full life cycle data to the water conservancy control center. The status monitoring submodule identifies the uploaded full life cycle data and judges the results of the full life cycle data. When there are abnormal values ​​in the full life cycle data, it judges that the corresponding management block has a risk and marks it as a risk management block.

[0073] Health Assessment Submodule: Based on the full lifecycle data of the risk management block, further analysis is performed to identify specific anomalies in the equipment, topography, and hydrological information data of water conservancy facilities. The health assessment submodule assesses and predicts the anomalies, evaluates their risk level, predicts potential risk items in other equipment, topography, and hydrological information within the risk management block, and generates an assessment report.

[0074] Early warning response submodule: When the health score in the assessment report is lower than the preset threshold, an early warning for the corresponding item is triggered, and an early warning message is generated and sent to the staff's smart device or the server of the water conservancy control center. At the same time, an adjustment plan for the corresponding early warning message is generated.

[0075] In this embodiment, the weight setting adopts the analytic hierarchy process to ensure that the influence of various features on the block division matches the actual management needs. Specifically, the weight ratio of equipment, terrain, and hydrological information is 4:3:3. After confirming the weights, the equipment core area is radiated outward to include closely related terrain and hydrological areas into the same block, ensuring the management synergy of facilities and environment within the block. The heavy load area is the core hub facility or the area with frequent hydrological dynamics, the medium load area is the conventional facility and the stable hydrological area, and the low load area is the auxiliary facility or the low dynamic area. The workload proof reflects the actual processing capacity of the node, and the weight proof reflects the task priority and hardware foundation. The combination of the two achieves the reasonable allocation of tasks.

[0076] The distributed ledger submodule adopts a chain storage structure and hash encryption technology. Each data block is associated with the feature value of the previous block. Any tampering will cause the chain verification to fail, ensuring data integrity, preventing data errors, and ensuring the accuracy of water conservancy management. At the same time, through end-to-end encryption and blockchain-style transmission technology with data sharding, it improves transmission efficiency while ensuring security, supports stable transmission of large-scale data, and prevents server load paralysis caused by a large amount of data being transmitted to the central server at the same time.

[0077] The digital twin module establishes a digital twin model for simulation. It utilizes Building Information Modeling (BIM) to construct a 3D structural model of the water conservancy facility, accurately reproducing details such as the facility's geometry, component connections, and material properties. Geographic Information System (GIS) provides a macroscopic geospatial framework, embedding the facility model into the real topography and water system distribution, achieving integrated modeling of the facility and its surrounding environment. Parametric design methods are used during model construction to associate key performance parameters of the facility with model components. For example, the gate opening parameter is associated with the gate's geometric position in the model, and the pump power parameter is associated with the pump's operating status in the model, enabling the model to realistically reflect the facility's physical characteristics. The digital twin model has a built-in parameter update unit that automatically matches the corresponding model parameters based on the data type. For example, water level data updates the water height parameter, and equipment vibration data updates the equipment operating status parameters in the model. The parameter update adopts an incremental update strategy, adjusting only the changing parameters to reduce computational resource consumption and ensure the efficiency of model updates. During the update process, the parameter change history is recorded simultaneously, forming parameter evolution curves to provide data support for trend analysis.

[0078] The status monitoring submodule synchronizes various data output from the digital twin module, including facility operation parameters, environmental monitoring data, and simulation results from the digital twin module. It establishes a data monitoring catalog, clarifies the monitoring frequency, threshold range, and anomaly judgment criteria for various types of data, and promptly detects abnormal data fluctuations by comparing data with the standard range in real time. This provides basic data support for health assessment and records data change trends to form long-term monitoring curves that reflect the evolution of facility status.

[0079] The health assessment submodule constructs multi-dimensional assessment indicators. Equipment health assessment includes indicators such as the operational stability of water conservancy facilities, the degree of performance degradation, and the frequency of failures. Environmental health assessment includes indicators such as water quality compliance rate, ecological indicator compliance, and disaster risk level. Each indicator is quantitatively scored, and an overall health score is obtained. An assessment report is generated based on the scoring results. The report includes analysis of the health status of equipment and water areas, diagnosis of potential problems, and improvement suggestions, providing a basis for management decisions.

[0080] The early warning response submodule has preset multiple early warning thresholds, corresponding to different risk levels, such as general early warning, important early warning, and emergency early warning. When the health score is lower than the corresponding threshold, the corresponding level of early warning process is activated, including sending early warning information to staff, displaying early warning icons on the system interface, and triggering audible and visual alarm devices. At the same time, it automatically associates with emergency plans according to the early warning level, provides guidance on handling procedures and resource scheduling suggestions, and assists staff in responding quickly to early warning events and reducing the impact of risks.

[0081] Example 3

[0082] Specifically, the water conservancy information management system also includes: a data acquisition module, a data processing module, and a management interaction module;

[0083] The data acquisition module is used to collect equipment operating parameters of water conservancy facilities, hydrological information on water quality, water quantity and flow of water conservancy facilities, and three-dimensional topographic images of the environment of water conservancy facilities.

[0084] The data processing module is used to process the operating parameters, 3D topographic images, and hydrological information collected by the data acquisition module, and output the processed equipment, topographic, and hydrological information data of the water conservancy facilities, which is then deployed in the computing device.

[0085] The management interaction module is used to support staff in managing and operating the water conservancy information management system and viewing its status.

[0086] The management interaction module includes: a user interaction submodule and an AR visualization submodule;

[0087] The user interaction submodule provides a graphical user interface to support staff in operating and managing the water conservancy information management system.

[0088] AR visualization sub-module: Overlays the simulation results of the digital twin module with the physical scene to display the status of water conservancy facilities through information management.

[0089] The data acquisition module includes:

[0090] Water level sensors, flow sensors, water quality sensors, equipment vibration sensors, and meteorological sensors are used to collect data on equipment and hydrological information of water conservancy facilities and are deployed in the equipment and aquatic environment of water conservancy facilities.

[0091] Mapping drones, equipped with high-definition cameras and lidar, are used to collect topographic data of water conservancy facilities;

[0092] In this embodiment, the AR visualization submodule uses spatial positioning to obtain the user's current physical location and viewing direction, and overlays information such as virtual facilities and data indicators in the digital twin model onto the user's real-time field of vision according to the actual spatial location. During the maintenance of water conservancy facilities, the part to be maintained is directly displayed in front of the staff, which makes it easier for the staff to quickly locate the maintenance location. Similarly, for some risk warning management of water areas, this technology can also be used to allow the staff to intuitively see the location of water area risks and problems. The AR visualization submodule supports multi-dimensional information display, and the staff can switch the displayed content through gestures or voice commands, such as switching from facility operation parameters to hydrological trend prediction, to achieve intuitive and efficient information acquisition.

[0093] The mapping drone emits laser pulses and receives reflected signals through lidar. It obtains the three-dimensional coordinates of the target by calculating the signal propagation time and generates high-precision point cloud data. The drone flies along a preset route to collect data. During the flight, it performs positioning and attitude control to ensure the continuity and accuracy of data collection. After the data collection is completed, it is automatically transmitted to ground computing equipment for processing, providing raw spatial data for 3D modeling.

[0094] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A water conservancy information management system based on a digital twin model, characterized in that, The water conservancy information management system includes: a block-based management module, a digital twin module, a blockchain network module, and a health management module; The block-based management module divides management blocks according to the characteristics of the equipment, terrain and hydrological information data of the water conservancy facilities. Each management block has a local computing device, and the local computing device of the management block is used to allocate management computing tasks according to the load. The digital twin module is used to simulate the entire life cycle of water conservancy facilities and hydrological environment. It establishes a digital twin model based on the acquired equipment, regional topography and hydrological information data of the water conservancy facilities and the corresponding historical data. The digital twin model outputs the entire life cycle data simulating the equipment, topography and hydrological information status of the water conservancy facilities. The digital twin module is deployed in the computing device of the block management module. The blockchain network module uses each management block as an independent management point. Each management point is equipped with a distributed ledger. The distributed ledger is used for the storage and management of the full life cycle data. The full life cycle data is written into the distributed ledger in encrypted form. At the same time, cross-regional data sharing is realized according to the allocation and management of the block-based management module, and the full life cycle data is transmitted to the water conservancy control center through the blockchain network module. The health management module, based on the full life cycle data generated by the digital twin module, and the analysis results of the full life cycle data for each management block, determines the status of the water conservancy facilities and hydrological environment, assesses the overall health level, and generates management early warning information. The block management module includes: a block partitioning submodule, a load balancing submodule, and a cross-chain collaboration submodule; The block division submodule imports the equipment, topography, and hydrological information data of the water conservancy facilities. The block division submodule analyzes the equipment, topography, and hydrological information data of the water conservancy facilities through the computing device, aligns the geometric coordinates of the equipment, topography, and hydrological information data of the water conservancy facilities, and divides the water conservancy facilities into management blocks according to the grid-based division rules after the geometric coordinates are aligned. The load balancing submodule classifies the computing load of the computing devices in the management block and sets corresponding load thresholds according to the classification. When the management computing task of the management block exceeds the preset load threshold, the management computing task is sent to the computing devices of the surrounding low-load management blocks, and the calculation result is returned to the computing device of the corresponding management block after the calculation is completed. The cross-chain collaboration submodule supports data sharing and collaborative decision-making among the management blocks. It establishes an encrypted channel through the blockchain network module, verifies data requests sent according to permissions, transmits shared data in a standardized format, and triggers a joint decision-making process when an event occurs that crosses the management blocks. The management blocks synchronize data and collaboratively generate a scheduling scheme.

2. The water conservancy information management system based on a digital twin model according to claim 1, characterized in that, The methods for dividing management blocks based on the equipment, topography, and hydrological information data characteristics of the aforementioned water conservancy facilities include: The process involves acquiring three types of basic data for the water conservancy facilities: equipment, topography, and hydrological information. The equipment data includes the type, quantity, distribution location, functional parameters, and management unit data of the water conservancy facilities. The topography data includes spatial data on watershed elevation, slope, landform type, and administrative boundaries. The hydrological information includes hydrological data on watershed river system distribution, river course, flow direction, water level fluctuation, flow characteristics, and watershed extent. Features of the three types of basic data of the water conservancy facilities—equipment, topography, and hydrological information—are extracted. Weights are set according to the importance of the equipment, functional relevance, and management distance of the water conservancy facilities. Weights are also set based on the continuity of the topography, elevation difference, and geographical barriers. Finally, weights are set according to the water flow connectivity, watershed catchment relationship, and water level influence range of the hydrological information. Using the weight of the device as a base point, the features of the associated terrain and hydrological information are divided by extending the distance outward from the characteristics of the device, thereby determining the scope of the management block and completing the gridded division of the management block.

3. A water conservancy information management system based on a digital twin model according to claim 1, characterized in that, The specific allocation logic for the local computing devices in the management block to allocate management computing tasks based on load is as follows: First, the computational workload and importance of the management blocks are classified. According to the importance of the operation of the equipment in the management blocks, the complexity of the terrain, and the frequency of change of the hydrological information, the load areas are divided into three levels: heavy load area, medium load area, and low load area. The three-level load area uses a hybrid approach of proof-of-work and proof-of-weight to allocate computing tasks. The proof-of-work is evaluated based on a combination of equipment, topographic and hydrological information data of the water conservancy facilities in the management block and the corresponding historical data. The proof-of-weight is determined based on the load classification and hardware resource configuration of the management block. When the computational load of the heavy-load region exceeds the set load threshold, the heavy-load region allocates the management computing tasks to the medium-load region and the low-load region, and returns the computation results to the computing device of the heavy-load region after the computation is completed. When allocating the management computing tasks, priority is given to allocating them to the low-load region.

4. A water conservancy information management system based on a digital twin model according to claim 1, characterized in that, The blockchain network module includes: a distributed ledger submodule, a cross-chain communication submodule, and a node management submodule; The distributed ledger submodule: After the digital twin module simulates and generates the full lifecycle data, the distributed ledger submodule encrypts and stores the full lifecycle data to ensure that the full lifecycle data cannot be changed; The cross-chain communication submodule is used to transmit the full lifecycle data stored in the distributed ledger submodule to the water conservancy control center, and the transmission process adopts an encrypted transmission method, and provides cross-chain data communication for data sharing between the management blocks; The node management submodule is used to generate a unique block identification code for different management blocks. When the distributed ledger submodule stores the full lifecycle data, it synchronously performs encoding matching on the full lifecycle data and then encrypts and stores it. When the cross-chain communication submodule transmits the full lifecycle data and shares data between the management blocks, the node management submodule verifies the corresponding block identification code. After successful verification, the transmission of the full lifecycle data and the sharing of data between the management blocks can be carried out.

5. A water conservancy information management system based on a digital twin model according to claim 1, characterized in that, The health management module includes: a status monitoring submodule, a health assessment submodule, and an early warning response submodule; The status monitoring submodule: The blockchain network module uploads the full life cycle data to the water conservancy control center. The status monitoring submodule identifies the uploaded full life cycle data and judges the results of the full life cycle data. When there are abnormal values ​​in the full life cycle data, it is determined that the corresponding management block has a risk and is marked as a risk management block. The health assessment submodule further analyzes the full lifecycle data of the risk management block to identify specific anomalies in the equipment, topography, and hydrological information data of the water conservancy facilities. The health assessment submodule assesses and predicts the anomalies, evaluates their risk level, predicts potential risk items in other equipment, topography, and hydrological information within the risk management block, and generates an assessment report. The early warning response submodule: when the health score in the assessment report is lower than a preset threshold, it triggers an early warning for the corresponding item, generates early warning information and sends it to the staff's smart device or the server of the water conservancy control center, and at the same time generates an adjustment plan corresponding to the early warning information.

6. A water conservancy information management system based on a digital twin model according to claim 1, characterized in that, The water conservancy information management system also includes: a data acquisition module, a data processing module, and a management interaction module; The data acquisition module is used to collect equipment operating parameters of the water conservancy facility, hydrological information on water quality, water quantity and flow of the water conservancy facility, and three-dimensional topographic images of the water conservancy facility environment. The data processing module is used to process the operating parameters, three-dimensional terrain images and hydrological information collected by the data acquisition module, and output the processed equipment, terrain and hydrological information data of the water conservancy facility, which is deployed in the computing device. The management interaction module is used to support staff in managing the water conservancy information management system and viewing its status.

7. A water conservancy information management system based on a digital twin model according to claim 6, characterized in that, The management interaction module includes: a user interaction submodule and an AR visualization submodule; The user interaction submodule provides a graphical user interface to support staff in operating and managing the water conservancy information management system. The AR visualization submodule overlays the simulation results of the digital twin module with the physical scene to display the information management status of water conservancy facilities.

8. A water conservancy information management system based on a digital twin model according to claim 7, characterized in that, The data acquisition module includes: Water level sensors, flow sensors, water quality sensors, equipment vibration sensors, and meteorological sensors are used to collect equipment and hydrological information data of the water conservancy facilities and are deployed in the equipment and aquatic environment of the water conservancy facilities; A mapping drone, equipped with a high-definition camera and lidar, is used to collect topographic data of the water conservancy facilities.

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