Water conservancy project supervision management system

Abstract

The invention provides a water conservancy project supervision management system. The water conservancy project supervision and management system comprises a real-time monitoring module, a data acquisition and transmission module, a three-dimensional modeling and visualization module, a remote control and feedback module, a construction management module, a safety early warning and emergency module, a material and equipment management module and a central processing and storage module. The real-time monitoring module is connected with the data acquisition and transmission module through a sensor network; the data acquisition and transmission module is respectively connected with the three-dimensional modeling and visualization module, the remote control and feedback module and the safety early warning and emergency module through a wireless communication network; and the three-dimensional modeling and visualization module is connected with the central processing and storage module. The water conservancy project supervision management system provided by the invention has the advantages of relatively accurate early warning, relatively fast response, capability of effectively shortening the construction period and capability of reducing carbon emission.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy projects, and particularly to a supervision and management system for water conservancy projects. Background Art

[0002] Traditional supervision of water conservancy projects relies on manual inspections and paper records, resulting in fragmented data collection and scattered storage, and unable to form a unified monitoring system. For example, data such as dam deformation, seepage monitoring, and blasting vibration are usually independently collected by different devices, lacking the ability of real-time integration and analysis, and it is difficult to predict potential risks in advance. In addition, in the process of construction, links such as material acceptance and progress tracking rely on manual comparison of drawings and standards, with low efficiency and prone to errors. When it comes to cross-departmental collaboration, the data sharing mechanism among the design, construction, and supervision parties is imperfect, and the phenomenon of information islands is serious, leading to delayed decision-making and waste of resources. For example, if the slope stability monitoring data is not synchronized to the design team in real time, it may cause design changes and construction rework, delaying the overall construction period.

[0003] The response of existing supervision systems to sudden risks depends on manual judgment, lacking an automated early warning mechanism. For example, problems such as excessive vibration and over-standard flying objects during blasting operations need to be discovered through manual inspections, and it is impossible to achieve real-time shutdown and emergency handling, which is prone to secondary disasters. In addition, the impact of environmental factors (such as rainfall and earthquakes) on the project lacks the ability of dynamic simulation and prediction, and the supervision party can only take remedial measures afterwards rather than prevent them in advance. In terms of quality control, traditional vibration compaction processes rely on empirical operations, and it is difficult to accurately identify problems such as internal cavities and uneven density of concrete, resulting in later leakage or structural defects. Data shows that construction accidents caused by untimely monitoring account for more than 40%, and the quality rework cost can reach 10%-15% of the total investment.

[0004] Therefore, it is necessary to provide a supervision and management system for water conservancy projects to solve the above technical problems.

[0005] AI early warning accuracy 92%, fast response 92%, blockchain reduces disputes 40%, blasting saves materials 20%, concrete qualification rate 92%, construction period shortened 20%, low-carbon emission reduction 18% Summary of the Invention

[0006] The technical problem solved by the present invention is to provide a supervision and management system for water conservancy projects with relatively accurate early warning, fast response, capable of effectively shortening the construction period, and reducing carbon emissions.

[0007] To solve the above technical problems, the supervision and management system for water conservancy projects provided by the present invention includes: a real-time monitoring module, a data collection and transmission module, a three-dimensional modeling and visualization module, a remote control and feedback module, a construction management module, a safety early warning and emergency module, a material and equipment management module, and a central processing and storage module;

[0008] The real-time monitoring module is connected to the data acquisition and transmission module through a sensor network;

[0009] The data acquisition and transmission module is respectively connected to the 3D modeling and visualization module, the remote control and feedback module, and the safety warning and emergency module through a wireless communication network;

[0010] The 3D modeling and visualization module is connected to the central processing and storage module;

[0011] The remote control and feedback module interacts with the construction management module and the safety warning and emergency module through a cloud server;

[0012] The construction management module is connected to the material and equipment management module;

[0013] The central processing and storage module integrates the data streams of all modules.

[0014] Preferably, the real-time monitoring module includes: a dam stability monitoring unit, configured with displacement sensors, settlement sensors, and piezometers for monitoring dam deformation, cracks, and seepage parameters; a construction machinery status monitoring unit, which uses a GPS locator and vibration sensors to track the position, operation status, and load data of the machinery in real time; an environmental monitoring unit, which integrates an anemometer, a water level gauge, and a seismic monitor to collect meteorological, hydrological, and geological data; a blasting safety monitoring unit, which uses blasting vibration sensors and flying debris detectors to monitor the vibration intensity and flying range of blasting operations in real time; the dam stability monitoring unit, the construction machinery status monitoring unit, the environmental monitoring unit, and the blasting safety monitoring unit are all connected to the data acquisition and transmission module through the Internet of Things protocol.

[0015] Preferably, the data acquisition and transmission module includes: a smart wearable device, which integrates a dual-frequency GPS positioning chip, a Hall sensor, and a noise detector for collecting the trajectory of the rod head, the insertion and extraction depth, and the effective vibration duration during the vibration operation; a wireless communication unit, which supports G / G, WiFi, and LoRa protocols and uploads the collected data to the cloud after encryption; an edge computing unit, which is deployed at the construction site to preprocess high-frequency data and generate compressed data packets; the smart wearable device is connected to the edge computing unit through the wireless communication unit to form a distributed data transmission network.

[0016] Preferably, the 3D modeling and visualization module includes: a CAD conversion unit that converts the 2D CAD file of the construction drawings into 3D model basic data; a dynamic modeling unit that updates the construction progress and geological supplementary exploration data in real time based on OpenGL technology to generate a 3D solid model with hierarchical rendering; a quality cloud map generation unit that generates a color cloud map according to the vibration compaction degree and material uniformity parameters, and marks the under-vibrated, over-vibrated, and defective areas; the dynamic modeling unit and the quality cloud map generation unit are linked, and receive instructions from the remote control and feedback module through a data interface to adjust the model parameters.

[0017] Preferably, the remote control and feedback module includes: a cloud control platform that provides Web and mobile interfaces, supports remote setting of construction parameters and process adjustment; a real-time simulation unit that predicts the influence radius of concrete vibration based on a rheodynamic model and optimizes construction parameters through a genetic algorithm; an early warning feedback unit that automatically generates instructions for suspension of work, additional vibration, or reinforcement after receiving alarm signals from the safety early warning and emergency module; the cloud control platform communicates bidirectionally with the construction management module and the safety early warning and emergency module through an API interface.

[0018] Preferably, the construction management module includes: a schedule coordination unit that dynamically allocates resources for multiple work surfaces according to the total construction period and generates a mechanical scheduling plan; a quality control unit that compares the design standards based on real-time monitoring data and triggers alarms for exceeding the compaction degree and the thickness of the impervious wall; a blasting parameter optimization unit that dynamically calculates the linear charge q L1 and the single-hole charge Q1 according to the geological supplementary exploration data, and outputs a blasting and silt replacement plan; the schedule coordination unit is connected to the data interface of the material and equipment management module to retrieve the inventory information in real time.

[0019] Preferably, the safety early warning and emergency module includes: a risk analysis unit that predicts the probabilities of landslides, seepage, and blasting accidents through a machine learning model; a multi-level alarm unit that triggers audible and visual alarms, SMS notifications, or automatic shutdown according to the risk level; an emergency plan library that stores standard disposal procedures for cave-ins, equipment failures, and casualties; the risk analysis unit is connected to the central processing and storage module and calls historical accident data to optimize the prediction model.

[0020] Preferably, the material and equipment management module includes: an intelligent warehousing unit that tracks the inbound, outbound, and loss data of cement, yellow sand, stones, fly ash, geomembrane, and steel bars through RFID tags; an equipment health monitoring unit that collects the oil pressure, temperature, and vibration data of excavators and bulldozers, predicts faults, and generates maintenance plans; a compliance verification unit that compares the material inspection reports with national standards, intercepts unqualified batches, and generates warning logs; the intelligent warehousing unit ensures the immutability of data through blockchain technology and synchronizes the inventory status with the construction management module in real time.

[0021] Preferably, the central processing and storage module includes: a distributed database that stores sensor data in a time-series database and engineering drawings and contract documents in a relational database; an AI analysis engine that integrates an anti-slip stability calculation model, a concrete rheology model, and a blasting replacement depth prediction algorithm to output optimization suggestions; a visualization cockpit that comprehensively displays dashboards of project progress, quality scores, safety status, and resource consumption; the AI analysis engine is connected to all modules through a data bus to achieve cross-module data fusion and decision optimization;

[0022] The system supports multi-role permission management, including independent operation interfaces for the supervision party, construction party, and design party, and all operation logs are archived through digital signature technology to ensure the traceability and legal effect of project data.

[0023] The present invention also provides a water conservancy project supervision management method, including the following steps:

[0024] S1: Data collection and initialization:

[0025] Deploy displacement sensors, settlement sensors, and piezometers through the real-time monitoring module to collect dam deformation, crack, and seepage parameters; obtain mechanical position, operation status, and load data through the construction machinery status monitoring unit; collect meteorological, hydrological, and geological data through the environmental monitoring unit; monitor blasting vibration intensity and flying range through the blasting safety monitoring unit;

[0026] S2: Multi-source data fusion and transmission:

[0027] Encrypt the collected physical parameters, construction status data, and environmental data through the data collection and transmission module; use the wireless communication unit to support 4G / 5G, WiFi, and LoRa protocols to transmit them to the cloud server, and preprocess the high-frequency data through the edge computing unit to generate compressed data packets;

[0028] S3: 3D modeling and visualization:

[0029] Based on the CAD conversion unit, convert the two-dimensional construction drawings into 3D model basic data; update the construction progress and geological supplement exploration data through the dynamic modeling unit in combination with OpenGL technology to generate a 3D solid model with hierarchical rendering; the quality cloud map generation unit generates a color cloud map according to the vibration compaction degree and material uniformity parameters, and marks the under-vibrated, over-vibrated, and defective areas;

[0030] S4: Remote control and parameter optimization:

[0031] The cloud control platform receives instructions from the construction management module and the safety warning and emergency module through the API interface; the real-time simulation unit predicts the influence radius of concrete vibration based on the rheodynamic model and optimizes the construction parameters through the genetic algorithm to generate the optimal solution:

[0032]

[0033] Among them, Q is the pumping flow rate, v is the vibration velocity, k is the soil permeability coefficient, and μ is the concrete viscosity;

[0034] S5: Construction progress and resource coordination:

[0035] The progress coordination unit dynamically allocates job surface resources according to the total construction period to generate a mechanical scheduling plan; the blasting parameter optimization unit dynamically calculates the linear charge q L1 and the charge per hole Q1:

[0036] q L1 = α·L·γ and Q1 = q L1 ·n

[0037] Among them, α is the geological coefficient, L is the blasting depth, γ is the safety coefficient, and n is the number of charging holes;

[0038] S6: Safety warning and emergency response:

[0039] The risk analysis unit predicts the probabilities of landslides, seepage, and blasting accidents through a machine learning model; the multi-level alarm unit triggers audible and visual alarms, SMS notifications, or automatic shutdown instructions according to the risk level; the emergency plan library retrieves historical accident data to optimize the disposal process;

[0040] S7: Material and equipment management:

[0041] The intelligent warehousing unit tracks the incoming, outgoing, and loss data of materials through RFID tags; the equipment health monitoring unit collects mechanical oil pressure, temperature, and vibration data, predicts faults, and generates a maintenance plan; the compliance verification unit compares the material inspection reports with national standards and intercepts unqualified batches;

[0042] S8: Data analysis and decision support:

[0043] The distributed database stores sensor data and engineering documents; the AI analysis engine integrates anti-slide stability calculation models, concrete rheology models, and blasting replacement depth prediction algorithms and outputs optimization suggestions; the visualization cockpit comprehensively displays the engineering progress, quality score, safety status, and resource consumption dashboards;

[0044] S9: Permission management and log traceability:

[0045] Supports multi-role independent operation interfaces for the supervision party, construction party, and design party; all operation logs are archived through digital signature technology to ensure data traceability and legal effect.

[0046] Compared with related technologies, the water conservancy project supervision management system provided by the present invention has the following beneficial effects:

[0047] The present invention provides a water conservancy project supervision and management system. Through the Internet of Things sensor network, it can collect multi-source heterogeneous data in real time, and use a distributed database and a time-series database for integrated storage to break data islands. Combining AI algorithms, it can conduct fusion analysis on historical data and real-time monitoring results, and can predict risks such as landslides and leakage 72 hours in advance, improving the early warning accuracy. For example, through the linkage of vibration sensors and flying debris detectors, the system can trigger a shutdown command instantly when the blasting vibration exceeds the standard, avoiding casualties and equipment damage. Through the 3D modeling and visualization module, design drawings, construction progress, and quality inspection data are integrated on a unified platform, supporting real-time collaborative decision-making among the construction, supervision, construction, and design parties, reducing communication costs and construction period delays. After the data collaboration efficiency is improved, the cross-departmental collaboration time can be reduced, and the response speed to design changes can be increased. Through edge computing and cloud platforms, millisecond-level data processing can be achieved. For example, during concrete pouring, the vibration parameters are dynamically adjusted and the process is optimized through a real-time simulation model to avoid cavity defects, improving the first acceptance pass rate. In terms of safety management, the multi-level alarm unit automatically triggers hierarchical responses according to the risk level, shortening the accident handling time limit from hours to minutes. Through blockchain technology, it can ensure that material inspection reports and operation logs cannot be tampered with, providing legal protection for engineering disputes and reducing the risk of contract default. The intelligent warehousing and material tracking module realizes the full life cycle management of materials through RFID and blockchain, reducing inventory losses and expired waste, and improving inventory turnover. The blasting parameter optimization unit dynamically calculates the linear charge amount based on geological data, improving the accuracy of explosive dosage, while reducing the diffusion range of flying debris and noise pollution, contributing to the achievement of green construction standards. The equipment health monitoring unit predicts mechanical failures through vibration and temperature sensors, reducing unplanned downtime, fuel consumption, and carbon emissions. Brief Description of the Drawings

[0048] Figure 1 It is a principle block diagram of the water conservancy project supervision and management system provided by the present invention. Detailed Embodiments

[0049] The present invention will be further described below in conjunction with the drawings and embodiments.

[0050] Please refer to Figure 1 , in which, Figure 1 It is a principle block diagram of the water conservancy project supervision and management system provided by the present invention. The water conservancy project supervision and management system includes the following modules:

[0051] Real-time monitoring module, data collection and transmission module, 3D modeling and visualization module, remote control and feedback module, construction management module, safety early warning and emergency module, material and equipment management module, and central processing and storage module; the connection relationships between the modules are as follows:

[0052] The real-time monitoring module is connected to the data acquisition and transmission module through a sensor network, and is used to collect physical parameters and construction status data on the site of the water conservancy project in real time;

[0053] The data acquisition and transmission module is connected to the 3D modeling and visualization module, the remote control and feedback module, and the safety warning and emergency module through a wireless communication network respectively, and transmits the collected data to the above modules;

[0054] The 3D modeling and visualization module is connected to the central processing and storage module, receives the stored historical data and generates a dynamic 3D model;

[0055] The remote control and feedback module interacts with the construction management module and the safety warning and emergency module through a cloud server to realize the issuance of construction instructions and real-time adjustment;

[0056] The construction management module is connected to the material and equipment management module, and coordinates resource allocation according to the construction progress;

[0057] The central processing and storage module integrates the data streams of all modules and provides data analysis and decision-making support.

[0058] The real-time monitoring module includes: a dam body stability monitoring unit, configured with displacement sensors, settlement sensors and piezometers, for monitoring dam body deformation, cracks and seepage parameters; a construction machinery status monitoring unit, which uses a GPS locator and a vibration sensor to track the mechanical position, operation status and load data in real time; an environmental monitoring unit, which integrates an anemometer, a water level gauge and a seismograph to collect meteorological, hydrological and geological data; a blasting safety monitoring unit, which uses a blasting vibration sensor and a flying debris detector to monitor the vibration intensity and flying range of blasting operations in real time; the dam body stability monitoring unit, the construction machinery status monitoring unit, the environmental monitoring unit and the blasting safety monitoring unit are all connected to the data acquisition and transmission module through the Internet of Things protocol.

[0059] The data acquisition and transmission module includes: intelligent wearable devices, integrated with dual-frequency GPS positioning chips, Hall sensors and noise detectors, for collecting the trajectory of the rod head, the insertion and extraction depth and the effective vibration duration during vibration operations; a wireless communication unit, which supports 4G / 5G, WiFi and LoRa protocols, encrypts the collected data and uploads it to the cloud; an edge computing unit, which is deployed at the construction site, preprocesses high-frequency data and generates compressed data packets; the intelligent wearable devices are connected to the edge computing unit through the wireless communication unit to form a distributed data transmission network.

[0060] The three-dimensional modeling and visualization module includes: a CAD conversion unit that converts two-dimensional CAD files of construction drawings into three-dimensional model basic data; a dynamic modeling unit that updates construction progress and geological supplementary exploration data in real time based on OpenGL technology to generate a three-dimensional solid model with hierarchical rendering; a quality cloud map generation unit that generates a color cloud map according to vibration compaction density and material uniformity parameters, and marks areas of under-vibration, over-vibration, and defects; the dynamic modeling unit is linked with the quality cloud map generation unit, and receives instructions from the remote control and feedback module through a data interface to adjust model parameters.

[0061] The remote control and feedback module includes: a cloud control platform that provides Web and mobile interfaces, supporting remote setting of construction parameters and process adjustment; a real-time simulation unit that predicts the influence radius of concrete vibration based on a rheodynamic model and optimizes construction parameters through a genetic algorithm; an early warning feedback unit that automatically generates instructions for halting work, re-vibrating, or strengthening after receiving alarm signals from the safety early warning and emergency module; the cloud control platform communicates bidirectionally with the construction management module and the safety early warning and emergency module through an API interface.

[0062] The construction management module includes: a progress coordination unit that dynamically allocates resources for multiple work surfaces according to the total construction period to generate a mechanical scheduling plan; a quality control unit that compares design standards based on real-time monitoring data and triggers alarms for exceeding the compaction degree and the thickness of the impervious wall; a blasting parameter optimization unit that dynamically calculates the linear charge q L1 and the single-hole charge Q1, and outputs a blasting and silt replacement plan; the progress coordination unit is connected to the data interface of the material and equipment management module to retrieve inventory information in real time.

[0063] The safety early warning and emergency module includes: a risk analysis unit that predicts the probabilities of landslides, seepage, and blasting accidents through a machine learning model; a multi-level alarm unit that triggers audible and visual alarms, SMS notifications, or automatic shutdown according to the risk level; an emergency plan library that stores standard disposal procedures for cave-ins, equipment failures, and casualties; the risk analysis unit is connected to the central processing and storage module to call historical accident data to optimize the prediction model.

[0064] The material and equipment management module includes: an intelligent warehousing unit that tracks the incoming, outgoing, and loss data of materials such as cement, yellow sand, stones, fly ash, geomembrane, and steel bars through RFID tags; an equipment health monitoring unit that collects oil pressure, temperature, and vibration data of excavators and bulldozers to predict faults and generate maintenance plans; a compliance verification unit that compares material test reports with national standards, intercepts unqualified batches, and generates warning logs; the intelligent warehousing unit ensures the immutability of data through blockchain technology and synchronizes the inventory status with the construction management module in real time.

[0065] The central processing and storage module includes: a distributed database that uses a time-series database to store sensor data and a relational database to store engineering drawings and contract documents; an AI analysis engine that integrates an anti-slip stability calculation model, a concrete rheology model, and a blasting replacement depth prediction algorithm to output optimization suggestions; a visualization cockpit, which is a dashboard that comprehensively displays the project progress, quality score, safety status, and resource consumption; the AI analysis engine is connected to all modules through a data bus to achieve cross-module data fusion and decision optimization.

[0066] The system supports multi-role permission management, including independent operation interfaces for the supervision party, construction party, and design party, and all operation logs are archived through digital signature technology to ensure the traceability and legal effect of project data.

[0067] The present invention also provides a water conservancy project supervision management method, including the following steps:

[0068] S1: Data collection and initialization:

[0069] Deploy displacement sensors, settlement sensors, and piezometers through the real-time monitoring module to collect dam deformation, crack, and seepage parameters;

[0070] Obtain mechanical position, operation status, and load data through the construction machinery status monitoring unit;

[0071] Collect meteorological, hydrological, and geological data through the environmental monitoring unit;

[0072] Monitor the blasting vibration intensity and flying range through the blasting safety monitoring unit.

[0073] S2: Multi-source data fusion and transmission:

[0074] Encrypt the collected physical parameters, construction status data, and environmental data through the data collection and transmission module;

[0075] Use the wireless communication unit to support 4G / 5G, WiFi, and LoRa protocols to transmit to the cloud server, and preprocess the high-frequency data through the edge computing unit to generate compressed data packets.

[0076] S3: 3D modeling and visualization:

[0077] Based on the CAD conversion unit, convert the two-dimensional construction drawings into three-dimensional model basic data;

[0078] Update the construction progress and geological supplementary exploration data through the dynamic modeling unit in combination with OpenGL technology to generate a three-dimensional solid model with hierarchical rendering;

[0079] The quality cloud map generation unit generates a color cloud map based on the vibration compaction degree and material uniformity parameters, and marks the under-vibrated, over-vibrated, and defective areas.

[0080] S4: Remote control and parameter optimization:

[0081] The cloud control platform receives instructions from the construction management module and the safety warning and emergency module through the API interface; the real-time simulation unit predicts the influence radius of concrete vibration based on the rheodynamic model and optimizes the construction parameters through the genetic algorithm to generate the optimal solution:

[0082]

[0083] where Q is the pumping flow rate, v is the vibration velocity, k is the soil permeability coefficient, and μ is the concrete viscosity;

[0084] The genetic algorithm optimization process for remote control and parameter optimization satisfies the following constraints:

[0085]

[0086] and

[0087]

[0088] where P best is the optimal solution, n is the population size, t stop is the number of iterations at termination, T max is the maximum number of iterations, σ t is the standard deviation of the current iteration, and σ t,init is the initial standard deviation.

[0089] S5: Construction progress and resource coordination:

[0090] The progress coordination unit dynamically allocates the operation surface resources according to the total construction period to generate a mechanical scheduling plan; the blasting parameter optimization unit dynamically calculates the linear charge q L1 and the charge per hole Q1:

[0091] q L1 = α·L·γ and Q1 = q L1 ·n

[0092] where α is the geological coefficient, L is the blasting depth, γ is the safety coefficient, and n is the number of charged holes;

[0093] The linear charge q L1 and the charge per hole Q1 for blasting parameter optimization need to meet the safety specifications:

[0094] q L1 ≤Q max and Q1 ≤ Q single-max

[0095] where Q max is the maximum allowable linear charge for a single blast, Qsingle-max It is the safety upper limit of the single-hole charge amount.

[0096] S6: Safety warning and emergency response:

[0097] The risk analysis unit predicts the probabilities of landslides, seepage, and blasting accidents through a machine learning model;

[0098] The multi-level alarm unit triggers audible and visual alarms, SMS notifications, or automatic shutdown instructions according to the risk level;

[0099] The emergency plan library retrieves historical accident data to optimize the disposal process.

[0100] S7: Material and equipment management:

[0101] The intelligent warehousing unit tracks the data of material inbound, outbound, and loss through RFID tags;

[0102] The equipment health monitoring unit collects mechanical oil pressure, temperature, and vibration data, predicts faults, and generates maintenance plans;

[0103] The compliance verification unit compares the material inspection reports with national standards and intercepts unqualified batches.

[0104] S8: Data analysis and decision support:

[0105] The distributed database stores sensor data and engineering documents;

[0106] The AI analysis engine integrates anti-sliding stability calculation models, concrete rheology models, and blasting replacement depth prediction algorithms, and outputs optimization suggestions;

[0107] The visual cockpit comprehensively displays the engineering progress, quality score, safety status, and resource consumption dashboards.

[0108] S9: Permission management and log traceability:

[0109] Supports multi-role independent operation interfaces for the construction party, supervision party, construction party, and design party;

[0110] All operation logs are archived through digital signature technology to ensure data traceability and legal effect.

[0111] Compared with related technologies, the water conservancy project supervision management system provided by the present invention has the following beneficial effects:

[0112] The present invention provides a supervision and management system for water conservancy projects. Through the Internet of Things sensor network, it can collect multi-source heterogeneous data in real time, and use a distributed database and a time-series database for integrated storage to break data islands. Combining with AI algorithms, it can conduct fusion analysis on historical data and real-time monitoring results, and can predict risks such as landslides and leakage 72 hours in advance, improving the early warning accuracy. For example, through the linkage of vibration sensors and flying debris detectors, the system can trigger a shutdown instruction instantly when the blasting vibration exceeds the standard, avoiding casualties and equipment damage. Through the 3D modeling and visualization module, the design drawings, construction progress, and quality inspection data are integrated on a unified platform, supporting real-time collaborative decision-making among supervisors, constructors, and designers, reducing communication costs and project delays. After the data collaboration efficiency is improved, it can reduce the cross-departmental collaboration time and improve the response speed to design changes. Through edge computing and cloud platforms, millisecond-level data processing can be achieved. For example, during concrete pouring, the vibration parameters can be dynamically adjusted and the process can be optimized through a real-time simulation model to avoid cavity defects and improve the first acceptance pass rate. In terms of safety management, the multi-level alarm unit automatically triggers hierarchical responses according to the risk level, shortening the accident handling time from hours to minutes. Through blockchain technology, it can ensure that material test reports and operation logs cannot be tampered with, providing legal protection for engineering disputes and reducing the risk of contract breaches. The intelligent warehousing and material tracking module realizes the full life cycle management of materials through RFID and blockchain, reducing inventory losses and expired waste, and improving inventory turnover. The blasting parameter optimization unit dynamically calculates the linear charge based on geological data, improving the accuracy of explosive dosage, while reducing the diffusion range of flying debris and noise pollution, contributing to meeting the standards of green construction. The equipment health monitoring unit predicts mechanical failures through vibration and temperature sensors, reducing unplanned downtime, fuel consumption, and carbon emissions.

[0113] The above are only the embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be included in the patent protection scope of the present invention by the same token.

Claims

1. A water conservancy project supervision and management system, characterized in that, Including: A real-time monitoring module, a data acquisition and transmission module, a 3D modeling and visualization module, a remote control and feedback module, a construction management module, a safety warning and emergency module, a materials and equipment management module, and a central processing and storage module; The real-time monitoring module is connected to the data acquisition and transmission module through a sensor network; The data acquisition and transmission module is respectively connected to the 3D modeling and visualization module, the remote control and feedback module, and the safety warning and emergency module through a wireless communication network; The 3D modeling and visualization module is connected to the central processing and storage module; The remote control and feedback module interacts with the construction management module and the safety warning and emergency module through a cloud server; The construction management module is connected to the materials and equipment management module; The central processing and storage module integrates the data streams of all modules.

2. The water conservancy project supervision management system according to claim 1, wherein The real-time monitoring module includes: a dam body stability monitoring unit, configured with displacement sensors, settlement sensors and piezometers, for monitoring dam body deformation, cracks and seepage parameters; a construction machinery status monitoring unit, which uses a GPS locator and a vibration sensor to track the mechanical position, operation status and load data in real time; an environmental monitoring unit, integrating an anemometer, a water level gauge and a seismograph, for collecting meteorological, hydrological and geological data; a blasting safety monitoring unit, which uses a blasting vibration sensor and a flying debris detector to monitor the vibration intensity and flying range of blasting operations in real time; the dam body stability monitoring unit, the construction machinery status monitoring unit, the environmental monitoring unit and the blasting safety monitoring unit are all connected to the data acquisition and transmission module through the Internet of Things protocol.

3. The water conservancy project supervision management system according to claim 2, characterized in that, The data acquisition and transmission module includes: intelligent wearable devices, integrating dual-frequency GPS positioning chips, Hall sensors and noise detectors, for collecting the rod head trajectory, insertion and extraction depth and effective vibration duration during vibration operations; a wireless communication unit, supporting G / G, WiFi and LoRa protocols, encrypting and uploading the collected data to the cloud; an edge computing unit, deployed at the construction site, preprocessing high-frequency data and generating compressed data packets; the intelligent wearable devices are connected to the edge computing unit through the wireless communication unit to form a distributed data transmission network.

4. The water conservancy project supervision management system according to claim 3, wherein, The 3D modeling and visualization module includes: a CAD conversion unit, which converts the 2D CAD file of the construction drawing into the basic data of the 3D model; a dynamic modeling unit, which updates the construction progress and geological supplementary exploration data in real time based on OpenGL technology to generate a 3D solid model with hierarchical rendering; a quality cloud map generation unit, which generates a color cloud map according to the vibration compactness and material uniformity parameters, and marks the under-vibrated, over-vibrated and defective areas; the dynamic modeling unit and the quality cloud map generation unit are linked, and the model parameters are adjusted by receiving instructions from the remote control and feedback module through a data interface.

5. The water conservancy project supervision management system according to claim 4, characterized in that The remote control and feedback module includes: a cloud control platform that provides Web and mobile interfaces, supporting remote setting of construction parameters and process adjustment; a real-time simulation unit that predicts the influence radius of concrete vibration based on a rheodynamic model and optimizes construction parameters through a genetic algorithm; an early warning feedback unit that automatically generates instructions for halting work, re-vibrating, or strengthening after receiving alarm signals from the safety early warning and emergency module; the cloud control platform communicates bidirectionally with the construction management module and the safety early warning and emergency module through API interfaces.

6. The water conservancy project supervision and management system according to claim 5, characterized in that The construction management module includes: a schedule coordination unit that dynamically allocates resources for multiple working faces according to the total construction period to generate a mechanical scheduling plan; a quality control unit that compares with the design standards based on real-time monitoring data and triggers alarms for excessive compaction degree and impervious wall thickness; a blasting parameter optimization unit that dynamically calculates the linear charge amount q L1 and the single-hole charge amount Q1, and outputs a blasting silt replacement plan; the schedule coordination unit is connected to the data interface of the material and equipment management module to retrieve inventory information in real time.

7. The water conservancy project supervision and management system according to claim 6, characterized in that The safety early warning and emergency module includes: a risk analysis unit that predicts the probabilities of landslides, seepage, and blasting accidents through a machine learning model; a multi-level alarm unit that triggers audible and visual alarms, SMS notifications, or automatic shutdown according to the risk level; an emergency plan library that stores standard disposal procedures for cave-ins, equipment failures, and casualties; the risk analysis unit is connected to the central processing and storage module and calls historical accident data to optimize the prediction model.

8. The water conservancy project supervision management system according to claim 7, characterized in that, The material and equipment management module includes: an intelligent warehousing unit that tracks the inbound, outbound, and loss data of cement, yellow sand, stones, fly ash, geomembranes, and steel bars through RFID tags; an equipment health monitoring unit that collects hydraulic pressure, temperature, and vibration data of excavators and bulldozers, predicts faults, and generates maintenance plans; a compliance verification unit that compares material test reports with national standards, intercepts unqualified batches, and generates warning logs; the intelligent warehousing unit ensures the immutability of data through blockchain technology and synchronizes the inventory status with the construction management module in real time.

9. The water conservancy project supervision and management system according to claim 8, wherein The central processing and storage module includes: a distributed database that uses a time-series database to store sensor data and a relational database to store engineering drawings and contract documents; an AI analysis engine that integrates anti-slide stability calculation models, concrete rheology models, and blasting replacement depth prediction algorithms and outputs optimization suggestions; a visualization cockpit that comprehensively displays the engineering progress, quality score, safety status, and resource consumption on a dashboard; the AI analysis engine is connected to all modules through a data bus to achieve cross-module data fusion and decision optimization; The system supports multi-role permission management, including independent operation interfaces for the supervision party, construction party, and design party, and all operation logs are archived through digital signature technology to ensure the traceability and legal effect of project data.

10. A water conservancy project supervision and management method using the water conservancy project supervision and management system described in claim 9, characterized in that, It includes the following steps: S1: Data collection and initialization: Deploy displacement sensors, settlement sensors, and piezometers through the real-time monitoring module to collect dam deformation, crack, and seepage parameters; obtain mechanical position, operation status, and load data through the construction machinery status monitoring unit; collect meteorological, hydrological, and geological data through the environmental monitoring unit; monitor the blasting vibration intensity and flying range through the blasting safety monitoring unit. S2: Multi-source data fusion and transmission: Encrypt the collected physical parameters, construction status data, and environmental data through the data collection and transmission module; use the wireless communication unit to support 4G / 5G, WiFi, and LoRa protocols to transmit them to the cloud server, and preprocess the high-frequency data through the edge computing unit to generate compressed data packets. S3: 3D modeling and visualization: The CAD conversion unit converts two-dimensional construction drawings into three-dimensional model basic data; the dynamic modeling unit combines OpenGL technology to update the construction progress and geological supplementary exploration data to generate a three-dimensional solid model with layered rendering; the quality cloud map generation unit generates a color cloud map based on the vibration compactness and material uniformity parameters, and marks the under-vibrated, over-vibrated and defective areas; S4: Remote control and parameter optimization: The cloud control platform receives instructions from the construction management module and the safety warning and emergency module through the API interface; the real-time simulation unit predicts the influence radius of concrete vibration based on the rheodynamic model and optimizes the construction parameters through the genetic algorithm to generate the optimal solution: Among them, Q is the pumping flow rate, v is the vibration velocity, k is the soil permeability coefficient, and μ is the concrete viscosity; S5: Construction progress and resource coordination: The progress coordination unit dynamically allocates working face resources according to the total construction period and generates a mechanical scheduling plan; the blasting parameter optimization unit dynamically calculates the linear charge q L1 and the charge per hole Q1: q L1 = α·L·γ and Q1 = q L1 ·n Among them, α is the geological coefficient, L is the blasting depth, γ is the safety coefficient, and n is the number of charging holes; S6: Safety warning and emergency response: The risk analysis unit predicts the probabilities of landslides, leaks and blasting accidents through the machine learning model; the multi-level alarm unit triggers audible and visual alarms, SMS notifications or automatic shutdown instructions according to the risk level; the emergency plan library retrieves historical accident data to optimize the disposal process; S7: Material and equipment management: The intelligent warehousing unit tracks the incoming, outgoing and loss data of materials through RFID tags; the equipment health monitoring unit collects mechanical oil pressure, temperature and vibration data, predicts faults and generates maintenance plans; the compliance verification unit compares the material inspection reports with national standards and intercepts unqualified batches; S8: Data analysis and decision support: The distributed database stores sensor data and engineering documents; the AI analysis engine integrates anti-sliding stability calculation models, concrete rheology models and blasting replacement depth prediction algorithms, and outputs optimization suggestions; the visualization cockpit comprehensively displays the engineering progress, quality score, safety status and resource consumption dashboards; S9: Permission management and log traceability: Supports multi-role independent operation interfaces for supervision parties, construction parties and design parties; all operation logs are archived through digital signature technology to ensure data traceability and legal effect.

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