Real-time operation monitoring system based on risk factor dynamic assessment

Abstract

The invention discloses an operation real-time monitoring system based on risk factor dynamic assessment, and relates to the technical field of desilting operation risk assessment, the system can comprehensively assess various potential risks in the desilting operation process through multi-dimensional environmental data acquisition and real-time monitoring, and the risk factor dynamic assessment is realized. Comprise dam instability, water flow shearing force, sediment disturbance, soft foundation stability and the like. The system calculates comprehensive risk factors according to the data, timely identifies risks and triggers early warning, and ensures the safety of an operation area. The system can dynamically evaluate the soil liquefaction risk by monitoring the soil liquefaction factor and the volume change of the workboat in real time, and prevents the workboat from inclining or sinking. In addition, the system generates and implements specific emergency strategies according to different early warning instructions, and takes effective protective measures to deal with sudden risks. The safety and efficiency of the dredging operation are improved, the potential accident risk is reduced, and the sustainability of the dredging operation is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of risk assessment for dredging operations, and in particular to a real-time operation monitoring system based on dynamic assessment of risk factors. Background Art

[0002] Traditional hydropower plant desilting operations rely primarily on static data from water level fluctuations and the operation area to assess soil conditions and operational safety. This static data includes indicators such as water level, sediment thickness, and reservoir dam structural integrity. While these data can reflect certain basic operational conditions, they overlook the impact of dynamic changes in soil and water during operations. Consequently, in actual operations, it is impossible to fully grasp the real-time changes in complex risks such as soil liquefaction, reservoir dam instability, and sediment disturbance.

[0003] During the daily operations of hydropower plants, the soil in the waters surrounding reservoirs and dams may experience varying degrees of sediment accumulation and soil disturbance due to natural factors such as water erosion and sediment accumulation. Traditional dredging monitoring often focuses on static monitoring of infrastructure such as water levels and reservoir dams, while neglecting the more detailed monitoring of dynamic soil changes and water flow. For example, factors such as water shear stress, sediment disturbance, and soil liquefaction cannot be directly reflected in static monitoring, resulting in potential bias in assessment results and a lack of comprehensive identification of potential risks in the operation area. Summary of the Invention

[0004] In view of the deficiencies of the prior art, the present invention provides a real-time operation monitoring system based on dynamic evaluation of risk factors to solve the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a real-time operation monitoring system based on dynamic assessment of risk factors, comprising:

[0006] The 3D model building module is used to collect 3D point cloud data of the reservoir operation area to be desilted, build a 3D model, divide the reservoir operation area to be desilted into several operation areas, mark them, and set monitoring points in each operation area;

[0007] The data acquisition module is used to install IoT sensor groups at monitoring points to collect environmental data of each operating area and establish an environmental data set;

[0008] The first risk area identification module is used to calculate the dam instability factor Dsw of the i-th operation area based on the environmental data set i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjwi , and associate to obtain the comprehensive risk factor Zh of the i-th operation area i , and preset the total risk threshold X, if the comprehensive risk factor Zh of the i-th operation area i If the total risk threshold X is exceeded, the first warning information is triggered. If the comprehensive risk factor Zh of the i-th operation area i If the total risk threshold X is not exceeded, a qualified operation area group is generated;

[0009] After receiving the first warning information, the dam instability factor Dsw of the operation area is calculated. i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i Evaluate them respectively and generate corresponding first instability graded warning instructions, second impact force graded warning instructions, third sediment disturbance graded warning instructions and fourth soft foundation graded warning instructions;

[0010] The construction operation monitoring module is used to prioritize qualified operation area groups and then perform dredging operations. It collects the total volume of the operation boat in the i-th operation area in real time, establishes an operation data set, and constructs the soil liquefaction factor Slf of the i-th operation area. i , analyze the disturbance pressure and soil liquefaction changes during the dredging operation, and preset the soil liquefaction threshold T. If the soil liquefaction factor Slf in the i-th operation area i If the soil liquefaction threshold T is exceeded, the corresponding fifth-level warning instruction is triggered;

[0011] The strategy module is used to generate and implement corresponding strategies after receiving the first instability graded warning instruction, the second impact force graded warning instruction, the third sediment disturbance graded warning instruction, the fourth soft foundation graded warning instruction and the fifth operation graded warning instruction.

[0012] Preferably, the three-dimensional model building module includes a three-dimensional terrain acquisition unit and a region division unit;

[0013] A 3D terrain acquisition unit, which uses a drone-mounted camera and image matching technology to generate a 3D model of the reservoir area to be desilted;

[0014] LiDAR is used to scan the reservoir area to be desilted to obtain ground 3D point cloud data, which includes elevation and slope information of the reservoir dam, embankment, and surrounding environment. Underwater laser scanning equipment is also used to scan the underwater area of ​​the reservoir area to be desilted to obtain underwater 3D point cloud data. The underwater 3D point cloud data includes 3D data of the underwater reservoir dam, spillway, and sediment accumulation layer structure. The ground 3D point cloud data and underwater 3D point cloud data are then fused into a 3D stereo model.

[0015] The regional division unit is used to divide the reservoir operation area to be desilted into several operation areas, set up monitoring points in each operation area, and mark several operation areas in the three-dimensional model as: Q1, Q2, Q3, ..., Q n , n represents the total number of operating areas.

[0016] Preferably, the data acquisition module is used to install an Internet of Things sensor group in the monitoring point. The Internet of Things sensor group includes: a water level sensor, a soil moisture sensor, a stress sensor, a density sensor, an angle sensor, a pressure sensor, a flow rate sensor and a sonar device. The environmental data set includes: the current water level H of the i-th operating area water,i , slope S i , soil friction angle μ i , soil compressive strength σ soil,i , soil moisture SM i , density ρ i , water flow velocity V flow,i , the angle θ between the water flow and the bottom of the reservoir dam i , the adhesion force between particles F adhesion,i , average soil particle diameter D i , sediment disturbance constant C sed,i , the average diameter of sediment particles D sediment,i and soil stress y soil,i .

[0017] Preferably, the first risk area identification module includes a prediction model building unit and an analysis unit;

[0018] A prediction model building unit is used to build a regional risk prediction model based on the environmental data set and the dredging equipment status data set;

[0019] The steps for establishing the regional risk prediction model are as follows: using a convolutional neural network to construct an initial convolutional neural network model, and using the environmental data set and the dredging equipment status data set to train and test the initial convolutional neural network model, and using the trained initial convolutional neural network model as the regional risk prediction model. At the same time, the intermediate layer output of the regional risk prediction model is used as a feature vector to identify feature information, and the regional risk prediction model is trained and tested based on the obtained feature information, and the trained regional risk prediction model is used as data for running predictions;

[0020] The analysis unit is used to analyze the environmental data set through the regional risk prediction model to calculate the dam instability factor Dsw of the i-th operation area. i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i .

[0021] Preferably, the analysis unit is used to calculate and obtain the dam instability factor Dsw of the i-th operation area i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i , the specific steps are:

[0022] S11. Extract the current water level H of the i-th operating area in the environmental data set water,i , slope S i , soil friction angle μ i , soil compressive strength σ soil,i and soil moisture SM i After dimensionless processing, the dam instability factor Dsw of the i-th operation area is calculated by the following formula: i :

[0023]

[0024] Where H water,i represents the current water level of the i-th operating area, H critical Indicates the critical water level, S i represents the slope of the i-th operating area, μ i represents the soil friction angle of the i-th operating area, σ soil,i represents the soil compressive strength of the i-th operating area, SM i represents the soil moisture of the i-th operating area; It represents the ratio of the water level to the critical water level. The higher the water level, the greater the risk of reservoir dam instability. Highly humid soil may cause reservoir dam to slip.

[0025] S12. Extract the water density ρ of the i-th operating area in the environmental data set i , water flow velocity V flow,i , the angle θ between the water flow and the bottom of the reservoir dam i and slope S i After dimensionless processing, the water flow shear force factor Jql is calculated using the following formula: i :

[0026]

[0027] Where, ρ i represents the water density in the i-th operating area, V flow,i represents the water flow velocity in the i-th operating area, θ i represents the angle between the water flow in the i-th operation area and the bottom of the reservoir dam, S i represents the slope of the i-th operating area; Represents the kinetic energy of water flow, which affects the scouring intensity of reservoir dams; sin(θ i ) takes into account the angle between the water flow and the bottom of the reservoir dam. The more consistent the slope of the water flow, the stronger the scouring effect. The term takes into account the additive effect of the slope on the water velocity; the relationship between the kinetic energy of water and the square of the water velocity is because the calculation of the kinetic energy of water is based on the kinetic energy formula in physics, so in The kinetic energy of the water flow is squared;

[0028] S13, extracting the adhesion force F between particles in the i-th operating area in the environmental data set adhesion,i and the average soil particle diameter D i , after dimensionless processing, first calculate the adhesion factor μ of the soil in the i-th operation area soil,i :

[0029]

[0030] Where, represents the contact area of ​​the particles;

[0031] S131, based on the adhesion factor μ of the soil in the i-th operation area soil,i , combined with the sediment disturbance constant C of the i-th operating area sed,i , the average diameter of sediment particles D sediment,i , water flow velocity V flow,i 、Current water level H water,i and the angle θ between the water flow and the bottom of the reservoir dam i After dimensionless processing, the sediment disturbance factor Crd of the i-th operating area is calculated by the following formula:i :

[0032]

[0033] Where, when the water flow velocity is greater than the critical flow velocity, the sediment will begin to be disturbed; H critical represents the critical water level. When the critical water depth is exceeded, the disturbance of the water flow on the sediment may become more severe; the soil adhesion factor μ soil,i , reflects the degree of adhesion between soil and water flow; the greater the adhesion, the less likely the sediment is to be disturbed; μ critical represents the critical adhesion factor;

[0034] S14. Extract the soil stress y of the i-th operation area in the environmental data set soil,i , slope S i and soil moisture SM i After dimensionless processing, the soft foundation stability factor Rjw is calculated by the following formula i :

[0035]

[0036] Where y critical represents the critical stress of soft foundation, y soil,i represents the soil stress in the i-th operating area, which is acquired through stress sensors. It represents the influencing factor of soil moisture. The higher the moisture, the worse the soil stability. Therefore, this item is used to correct the effect of moist soil on stability. It indicates that the slope has a positive relationship with the stability of the soft foundation. The greater the slope, the worse the stability. Therefore, areas with larger slopes require higher stability. Soft foundation refers to geological layers in soil or rock with lower bearing capacity, higher compressibility and poorer stability.

[0037] Preferably, the first risk area identification module further includes an association unit, an overall assessment unit and a hierarchical assessment unit;

[0038] The associated unit is used to extract the dam instability factor Dsw of the i-th operation area i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i After dimensionless processing, the comprehensive risk factor Zh of the i-th operation area is calculated by the following related formula i :

[0039] Zh i =a1×Dsw i +a2×Jql i +a3×Crdi -a4×Rjw i ;

[0040] Where a1, a2, a3 and a4 are the dam instability factors Dsw of the i-th operation area respectively. i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i The weight coefficient of the soft foundation stability factor Rjw i It is an anti-correlation factor, the lower the value, the greater the risk;

[0041] The total assessment unit is used to preset the total risk threshold X and calculate the comprehensive risk factor Zh of the i-th operation area. i Compare with the total risk threshold X to obtain the first judgment result, including:

[0042] When the comprehensive risk factor Zh of the i-th operation area i >Total risk threshold X, indicating that there is a potential risk in the operation area, generating the first warning information, and requiring classification and determination of the potential risk type;

[0043] When the comprehensive risk factor Zh of the i-th operation area i ≤ the total risk threshold X, indicating that there is no potential risk in the operation area and everything is normal. A qualified mark is generated in the 3D model, and the operation areas with qualified marks are counted to generate a qualified operation area group, indicating that dredging operations can be carried out sustainably;

[0044] The hierarchical evaluation unit is used to preset the first threshold value X1, the second threshold value X2, the third threshold value X3 and the fourth threshold value X4 after receiving the first warning information, and to calculate the dam instability factor Dsw of the i-th operation area. i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i Compare with the corresponding threshold to obtain the graded assessment results, including:

[0045] When the dam instability factor Dsw of the i-th operation area i > the first threshold X1, indicating that the reservoir dam in the operation area has an instability risk, and the first instability graded warning instruction is generated; when the dam instability factor Dsw of the i-th operation area i < the first threshold X1, indicating that there is no risk of instability of the reservoir dam in the operation area;

[0046] When the water shear force factor Jql in the i-th operating area i> the second threshold X2, indicating that there is a sharp change in water flow in the reservoir dam in the operation area, and the impact force will cause the risk of disturbance of the reservoir dam, soil or sediment, and a second impact force graded warning instruction will be generated; when the water flow shear force factor Jql in the i-th operation area i ≤ the second threshold X2, indicating that there is no risk of rapid changes in water flow and impact force on the reservoir dam in the operation area;

[0047] When the sediment disturbance factor Crd in the i-th operation area i > the third threshold value X3, indicating that the sediment accumulation in the operation area is abnormal and the disturbance exceeds the controllable range, and a third sediment disturbance graded warning instruction is generated; when the sediment disturbance factor Crd of the i-th operation area i ≤ the third threshold X3, indicating that the sediment disturbance is within the controllable range and continuous monitoring is required;

[0048] When the soft foundation stability factor Rjw of the i-th operation area i ≥ the fourth threshold X4, indicating that the soil stability of the operation area is qualified and continuous monitoring is required; when the soft foundation stability factor Rjw of the i-th operation area is i < the fourth threshold value X4, indicating that the soil stability of the operation area is unqualified, and a fourth soft foundation classification warning instruction is generated.

[0049] Preferably, the construction operation monitoring module includes a sequencing unit and a second monitoring unit;

[0050] The construction operation monitoring module is used to group qualified operation areas according to the comprehensive risk factor Zh of the i-th operation area. i Sort from small to large to obtain a priority list, and perform dredging operations on the priority list in order;

[0051] The second monitoring unit is used to collect the total volume of the operating vessels in the i-th operating area and establish an operating data set.

[0052] Preferably, the construction operation monitoring module further includes a dynamic analysis unit and an operation evaluation unit. The dynamic analysis unit is used to analyze and calculate the soil liquefaction factor Slf of the i-th operation area based on the operation data set. i , the specific steps are as follows:

[0053] S21. The workboat is subject to buoyancy in the water. Buoyancy is equal to the pressure exerted by water on the bottom of the hull. Extract the total volume of the workboat in the i-th work area from the work data set and calculate the buoyancy F of the workboat in the i-th work area. ship,i :

[0054] F ship,i =ρ i ×V ship,j ×g;

[0055] Where V ship represents the volume of the workboat, g represents the acceleration due to gravity, which is 1000kg / m 3 ρ i represents the water density of the i-th operating area;

[0056] S22. The buoyancy of the workboat directly affects the distribution of water pressure on the soil, which in turn affects the probability of soil liquefaction. The greater the buoyancy, the greater the pressure the workboat exerts on the water and soil, increasing the risk of soil liquefaction.

[0057] Soil liquefaction is mainly composed of static pressure, dynamic pressure and liquefaction stress. Liquefaction occurs in loose saturated soil. When external disturbance causes the soil to lose its solid state, liquefaction stress is used to measure whether the soil will liquefy. Combined with the buoyancy F of the operation vessel in the i-th operation area obtained by S21, ship,i After dimensionless processing, the soil liquefaction factor Slf of the i-th operation area is calculated by the following formula i :

[0058]

[0059] σ static,i =γ i ×h i ;

[0060] Where, σ static,i represents the static pressure caused by the soil's own weight; σ dynamic,i represents the dynamic pressure caused by water flow disturbance, σ max It represents the maximum stress that the soil can withstand before liquefaction occurs; γ i represents the unit weight of the soil in the i-th operation area, h i represents the buried depth of the soil in the i-th operation area;

[0061] Among them, ΔP represents the maximum value of water pressure change, P critical It represents the critical water pressure that causes soil liquefaction. When this water pressure is exceeded, the pore water pressure of the soil will cause the consolidation force of the soil to decrease, and liquefaction will occur.

[0062] Preferably, the operation evaluation unit is used to preset the soil liquefaction threshold T and set the soil liquefaction factor Slf of the i-th operation area i Compare this with the soil liquefaction threshold T to determine whether there is a risk of soil liquefaction causing the dredging vessel to tilt or sink during the dredging operation, including:

[0063] If the soil liquefaction factor Slf in the i-th operation area i> soil liquefaction threshold T, indicating that there is soil liquefaction in the reservoir dam in the operation area, which may cause the dredging vessel to tilt or sink, and the fifth operation level warning instruction is generated; if the soil liquefaction factor Slf of the i-th operation area i ≤Soil liquefaction threshold T, indicating that there is no risk of soil liquefaction on the reservoir embankment in the operation area causing the dredging vessel to tilt or sink, and continuous monitoring is carried out.

[0064] Preferably, the strategy module is configured to generate corresponding strategies upon receiving the first instability graded warning instruction, the second impact force graded warning instruction, the third sediment disturbance graded warning instruction, the fourth soft foundation graded warning instruction, and the fifth operation graded warning instruction, including:

[0065] The first strategy is generated according to the first instability graded warning instruction, including: installing a 20% coverage reservoir dam protection device in the operation area, and installing 3-6 anchor rods at the base of the reservoir dam for support, until the dam instability factor Dsw of the i-th operation area is i When the water level drops below the first threshold value X1, desilting operations are resumed. The reservoir dam protection device includes a waterproof membrane and a geonet. The waterproof membrane is required to be made of PVC with a thickness of 0.5 mm. The geonet has a strength of 200 kN / m to ensure resistance to water erosion on the reservoir dam.

[0066] The second strategy is generated based on the second impact force graded warning instruction, including: arranging floating isolation walls in the operation area, covering an area of ​​30% of the operation area to reduce the impact of water flow impact on the reservoir dam and sediment; the floating isolation wall is made of high-density polyethylene with a thickness of 2m, and the water flow velocity in the operation area is adjusted between 0.3-1.5m / s until the water shear force factor Jql in the i-th operation area is reached. i ≤ the second threshold value X2, and then resume the dredging operation;

[0067] The third strategy is generated based on the third sediment disturbance graded warning instruction, including: arranging sediment disturbance protection nets in the operation area, covering an area of ​​40% of the operation area; using geotextile fiber nets with a mesh size of 3mm; until the sediment disturbance factor Crd of the i-th operation area is i ≤ the third threshold value X3, and then resume the dredging operation;

[0068] The fourth strategy is generated based on the fourth soft foundation grade warning instruction, including: grouting reinforcement in the operation area, injecting 20-30% of 10-15% stability enhancer, including gypsum powder or cement slurry; the grouting volume per square meter is 1-2L; and a reinforced wall is set on the soft foundation of the operation area, with a wall height of 2-3m and a width of 1.5m; until the soft foundation stability factor Rjw of the i-th operation area is i ≥ the fourth threshold value X4, and then resume the dredging operation;

[0069] The fifth strategy is generated according to the fifth operation grade warning instruction, including: installing 4-6 adjustable buoyancy platforms on the bottom of the operation vessel to prevent the hull from tilting or sinking due to soil liquefaction; the buoyancy design of each adjustable buoyancy platform can support a weight of 10-15 tons; once the soil liquefaction factor Slf of the i-th operation area is detected i >Soil liquefaction threshold T×150%, the emergency mechanism is activated, the work vessel immediately stops operations and evacuates to a safe area, and the emergency response time does not exceed 15 minutes.

[0070] The present invention provides a real-time operation monitoring system based on dynamic risk factor assessment. It has the following beneficial effects:

[0071] (1) This is a real-time operation monitoring system based on dynamic risk factor assessment. This system combines environmental data collection with real-time monitoring point setting to comprehensively collect environmental information of the operation area (such as dam instability, water shear force, sediment disturbance, soft foundation stability, etc.) and calculates comprehensive risk factors based on this data. During the operation process, the system can dynamically assess the risk status of each operation area, promptly identify and respond to potential risks, and effectively prevent safety accidents caused by environmental changes.

[0072] (2) This is a real-time operation monitoring system based on dynamic risk factor assessment. By establishing multiple risk assessment indicators such as dam instability factor, water shear force factor, sediment disturbance factor and soft foundation stability factor, the system can achieve refined risk classification management. Once the comprehensive risk factor of the operation area exceeds the preset threshold, the system will trigger the corresponding early warning instruction and carry out specific graded response. This graded management can adopt different emergency strategies according to different risk levels, ensuring that risks are managed and responded to scientifically and reasonably, thereby improving the safety of dredging operations.

[0073] (3) This is a real-time operation monitoring system based on dynamic assessment of risk factors. The construction operation monitoring module dynamically monitors the volume changes of the operation vessel based on the real-time collected operation data, calculates the soil liquefaction factor, and evaluates the disturbance pressure of the dredging operation on the soil in real time. This real-time monitoring and dynamic analysis mechanism enables timely detection of soil liquefaction risks during the operation process and triggers corresponding operation classification warning instructions based on whether the soil liquefaction factor exceeds the set threshold T. By adjusting the operation strategy in real time and dynamically, the tilting or sinking of the hull due to problems such as soil liquefaction can be avoided, thereby enhancing the safety of the operation.

[0074] (4) This is a real-time operation monitoring system based on dynamic assessment of risk factors. The strategy module generates a series of specific emergency strategies according to different early warning instructions and implements them in a timely manner. These strategies include effective response measures to problems such as dam instability, impact force, sediment disturbance, soft foundation stability and soil liquefaction. The implementation of the strategy not only ensures that the operation area can quickly take protective measures when encountering sudden risks, avoiding operation interruptions or accidents, but also improves the emergency response speed, ensures the smooth progress of the operation process, and greatly improves the safety and efficiency of the operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 The figure is a flow chart of a real-time operation monitoring system based on dynamic assessment of risk factors according to the present invention. DETAILED DESCRIPTION

[0076] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0077] Example 1

[0078] See also Figure 1 The present invention provides a real-time operation monitoring system based on dynamic risk factor assessment, comprising:

[0079] The 3D model building module is used to collect 3D point cloud data of the reservoir operation area to be desilted, build a 3D model, divide the reservoir operation area to be desilted into several operation areas, mark them, and set monitoring points in each operation area;

[0080] The data acquisition module is used to install IoT sensor groups at monitoring points to collect environmental data of each operating area and establish an environmental data set;

[0081] The first risk area identification module is used to calculate the dam instability factor Dsw of the i-th operation area based on the environmental data set i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i , and associate to obtain the comprehensive risk factor Zh of the i-th operation area i , and preset the total risk threshold X, if the comprehensive risk factor Zh of the i-th operation area i If the total risk threshold X is exceeded, the first warning information is triggered. If the comprehensive risk factor Zh of the i-th operation areai If the total risk threshold X is not exceeded, a qualified operation area group is generated;

[0082] After receiving the first warning information, the dam instability factor Dsw of the operation area is calculated. i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i Evaluate them respectively and generate corresponding first instability graded warning instructions, second impact force graded warning instructions, third sediment disturbance graded warning instructions and fourth soft foundation graded warning instructions;

[0083] The construction operation monitoring module is used to prioritize qualified operation area groups and then perform dredging operations. It collects the total volume of the operation boat in the i-th operation area in real time, establishes an operation data set, and constructs the soil liquefaction factor Slf of the i-th operation area. i , analyze the disturbance pressure and soil liquefaction changes during the dredging operation, and preset the soil liquefaction threshold T. If the soil liquefaction factor Slf in the i-th operation area i If the soil liquefaction threshold T is exceeded, the corresponding fifth-level warning instruction is triggered;

[0084] The strategy module is used to generate and implement corresponding strategies after receiving the first instability graded warning instruction, the second impact force graded warning instruction, the third sediment disturbance graded warning instruction, the fourth soft foundation graded warning instruction and the fifth operation graded warning instruction.

[0085] In this embodiment, traditional dredging operations usually rely only on basic data such as static water level, sediment thickness and reservoir dam structural integrity, while ignoring dynamic risk factors such as water shear force, soil liquefaction, and sediment disturbance during the dredging process. Through the three-dimensional model building module and data acquisition module in the present invention, the system collects and analyzes various environmental data in real time, and combines the dam instability factor Dsw i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i The system uses a comprehensive risk factor analysis to generate dynamic risk factors for each operation area. This allows the system to monitor and assess changes in soil, reservoir embankments, and water bodies in real time during the desilting process, providing a more comprehensive risk assessment.

[0086] Traditional dredging operations often fail to identify potential risks before they occur due to the lack of real-time monitoring and early warning mechanisms. The first risk area identification module of the present invention can quickly calculate the risk factor for each operating area after receiving environmental data and compare it with a preset overall risk threshold. Once the comprehensive risk factor of a particular operating area exceeds the threshold, the system immediately triggers a first early warning message. This early warning mechanism based on real-time data helps identify potential risk areas early in dredging operations and avoid operational accidents caused by sudden risks.

[0087] After receiving different early warning information, the strategy module in the present invention can generate corresponding operation strategies according to the specific situation and implement them immediately. For example, if the soil liquefaction factor exceeds the preset threshold, the system will trigger the soil liquefaction early warning instruction and adjust the operation plan according to the risk situation. This dynamic adjustment strategy not only improves the flexibility of the operation, but also optimizes the dredging process according to the changes in different risk factors to ensure safe and efficient operations. Through the construction operation monitoring module to collect the total volume data and disturbance pressure of the operation vessel in real time, the system can accurately construct the soil liquefaction factor and analyze the impact of soil disturbance on soil liquefaction during the operation. This soil liquefaction assessment based on real-time data can effectively avoid the shortcomings of traditional methods that cannot reflect risk changes in the operation in a timely manner, improve the accuracy and safety of the operation, and prevent accidents such as soil liquefaction and reservoir dam instability.

[0088] Example 2

[0089] This embodiment is explained in Example 1, please refer to Figure 1 ,The 3D model building module includes a 3D terrain acquisition unit and a ,region division unit;

[0090] A 3D terrain acquisition unit, which uses a drone-mounted camera and image matching technology to generate a 3D model of the reservoir area to be desilted;

[0091] LiDAR is used to scan the reservoir area to be desilted to obtain ground 3D point cloud data, which includes elevation and slope information of the reservoir dam, embankment, and surrounding environment. Underwater laser scanning equipment is also used to scan the underwater area of ​​the reservoir area to be desilted to obtain underwater 3D point cloud data. The underwater 3D point cloud data includes 3D data of the underwater reservoir dam, spillway, and sediment accumulation layer structure. The ground 3D point cloud data and underwater 3D point cloud data are then fused into a 3D stereo model.

[0092] The regional division unit is used to divide the reservoir operation area to be desilted into several operation areas, set up monitoring points in each operation area, and mark several operation areas in the three-dimensional model as: Q1, Q2, Q3, ..., Q n, n represents the total number of operating areas.

[0093] In this embodiment, traditional dredging operations often rely on two-dimensional drawings or simple topographic data, which cannot fully capture the complex topography and underwater structures of the reservoir operation area. By utilizing drone-mounted cameras and LiDAR technology, the present invention can generate a high-precision three-dimensional model of the reservoir operation area to be desilted. This 3D model not only displays detailed information such as ground elevation and slope, but also uses underwater laser scanning technology to obtain 3D data of key underwater structures such as reservoir embankments, spillways, and sediment accumulation layers, providing more accurate operational data than traditional methods. Traditional dredging operations may rely solely on limited ground measurements and water level data, failing to fully account for changes in the reservoir embankment, levees, surrounding environment, and underwater areas. However, using a 3D terrain acquisition unit, combined with drone image matching technology, LiDAR, and underwater laser scanning equipment, it is possible to comprehensively capture detailed data such as ground and underwater elevation, slope, and sediment accumulation. The integration of this data creates a high-precision, three-dimensional model, providing a solid foundation for subsequent dredging risk assessment, early warning, and operational strategies.

[0094] Example 3

[0095] This embodiment is explained in Example 1, please refer to Figure 1 ,The data acquisition module is used to install the IoT sensor group in the monitoring point. The IoT sensor group includes: water level sensor, soil moisture sensor, stress sensor, density sensor, angle sensor, pressure sensor, flow rate sensor and sonar device. The environmental data set includes: the current water level H of the i-th operation area water,i , slope S i , soil friction angle μ i , soil compressive strength σ soil,i , soil moisture SM i , density ρ i , water flow velocity V flow,i , the angle θ between the water flow and the bottom of the reservoir dam i , the adhesion force between particles F adhesion,i , average soil particle diameter D i , sediment disturbance constant C sed,i , the average diameter of sediment particles D sediment,i and soil stress y so il , i.

[0096] In this embodiment, the IoT sensor group enables real-time data collection and continuously tracks the dynamic changes of various environmental factors within the operation area. For example, changes in soil moisture, density, and water flow velocity may directly affect soil stability, while data such as the angle between the water flow and the bottom of the reservoir dam and the average diameter of sediment particles can effectively reflect the potential scour risk of the reservoir dam. This real-time data provides an accurate basis for dynamic analysis of dredging operations, allowing timely adjustments to operational strategies to avoid operational risks caused by environmental changes and ensure operational safety and efficiency. Key data provided by sensors such as soil stress, sediment disturbance constant, and inter-particle adhesion can effectively assess soil mechanical behavior during operations, thereby helping to predict potential risks such as soil liquefaction and reservoir dam instability. For example, by monitoring changes in soil stress in real time, signs of reservoir dam or soil instability can be promptly identified, providing early warning to operators. By combining parameters such as water flow velocity, soil compressive strength, and sediment disturbance, the system can comprehensively assess the risk status of the entire operation area and adjust the operation plan based on the assessment results, greatly improving operational safety. By meticulously collecting multiple environmental data points, the IoT sensor cluster generates an environmental dataset that provides a precise basis for subsequent analysis and decision-making. This data not only supports the calculation and comprehensive assessment of risk factors but also provides detailed parameter inputs for the policy module, enabling the generation of scientific and precise response strategies. For example, based on data such as soil moisture, density, and friction angle, the system can assess soil stability, the impact of flow velocity on reservoir embankments, and the scale of sediment disturbance. These analyses enable effective adjustments to operational plans, avoiding interruptions and unnecessary waste of resources. Through the data collection module, all environmental data is centrally integrated into the environmental dataset, facilitating further processing and analysis by the system. This dataset not only supports real-time monitoring but also provides a basis for historical data comparison and trend analysis. For example, by accumulating historical data on water levels, sediment disturbance, and soil stress, long-term trend analysis can be performed, helping the system identify long-term trends in reservoir conditions and providing a scientific basis for subsequent operational adjustments, maintenance, and planning.

[0097] Example 3

[0098] This embodiment is explained in Example 1, please refer to Figure 1 ,The first risk area identification module includes a prediction model building unit and an ,analysis unit;

[0099] A prediction model building unit is used to build a regional risk prediction model based on the environmental data set and the dredging equipment status data set;

[0100] The steps for establishing the regional risk prediction model are as follows: using a convolutional neural network to construct an initial convolutional neural network model, and using the environmental data set and the dredging equipment status data set to train and test the initial convolutional neural network model, and using the trained initial convolutional neural network model as the regional risk prediction model. At the same time, the intermediate layer output of the regional risk prediction model is used as a feature vector to identify feature information, and the regional risk prediction model is trained and tested based on the obtained feature information, and the trained regional risk prediction model is used as data for running predictions;

[0101] The analysis unit is used to analyze the environmental data set through the regional risk prediction model to calculate the dam instability factor Dsw of the i-th operation area. i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i .

[0102] Analysis unit, used to calculate the dam instability factor Dsw of the i-th operation area i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i , the specific steps are:

[0103] S11. Extract the current water level H of the i-th operating area in the environmental data set water,i , slope S i , soil friction angle μ i , soil compressive strength σ soil,i and soil moisture SM i After dimensionless processing, the dam instability factor Dsw of the i-th operation area is calculated by the following formula: i :

[0104]

[0105] Where H water,i represents the current water level of the i-th operating area, H critical Indicates the critical water level, S i represents the slope of the i-th operating area, μ i represents the soil friction angle of the i-th operating area, σ soil,i represents the soil compressive strength of the i-th operating area, SM i represents the soil moisture of the i-th operating area; It represents the ratio of the water level to the critical water level. The higher the water level, the greater the risk of reservoir dam instability. Highly humid soil may cause reservoir dam to slip.

[0106] S12. Extract the water density ρ of the i-th operating area in the environmental data set i , water flow velocity V flow,i , the angle θ between the water flow and the bottom of the reservoir dam i and slope S i After dimensionless processing, the water flow shear force factor Jql is calculated using the following formula: i :

[0107]

[0108] Where, ρ i represents the water density in the i-th operating area, V flow,i represents the water flow velocity in the i-th operating area, θ i represents the angle between the water flow in the i-th operation area and the bottom of the reservoir dam, S i represents the slope of the i-th operating area; Represents the kinetic energy of water flow, which affects the scouring intensity of reservoir dams; sin(θ i ) takes into account the angle between the water flow and the bottom of the reservoir dam. The more consistent the slope of the water flow, the stronger the scouring effect. The term takes into account the additive effect of the slope on the water velocity; the relationship between the kinetic energy of water and the square of the water velocity is because the calculation of the kinetic energy of water is based on the kinetic energy formula in physics, so in The kinetic energy of the water flow is squared;

[0109] S13, extracting the adhesion force F between particles in the i-th operating area in the environmental data set adhesion,i and the average soil particle diameter D i , after dimensionless processing, first calculate the adhesion factor μ of the soil in the i-th operation area soil,i :

[0110]

[0111] Where, represents the contact area of ​​the particles;

[0112] The following refers to the adhesion force F between particles in the i-th working area. adhesion,i An example chart:

[0113] Soil type <![CDATA[The adhesion force F between particles adhesion,i > sandy soil 0.1-0.3 fine sand 0.2-0.4 silt 0.3-0.5 clay 0.5-0.8 organic soil 0.4-0.7

[0114] Sand: The particles are larger and the gaps are larger, so water can flow through easily, so the adhesion is weaker (0.1-0.3).

[0115] Fine sand: Relatively small particles with slightly stronger adhesion (0.2-0.4).

[0116] Silt: It has finer particles and is more likely to adhere to water flow than sand and fine sand (0.3-0.5).

[0117] Clay: It has fine particles and strong viscosity, and usually has a high adhesion force (0.5-0.8), so it is not easily disturbed.

[0118] Organic soil: Because it contains humus, it has strong adsorption capacity (0.4-0.7).

[0119] S131, based on the adhesion factor μ of the soil in the i-th operation area soil,i , combined with the sediment disturbance constant C of the i-th operating area sed,i , the average diameter of sediment particles D sediment,i , water flow velocity V flow,i 、Current water level H water,i and the angle θ between the water flow and the bottom of the reservoir dam i After dimensionless processing, the sediment disturbance factor Crd of the i-th operating area is calculated by the following formula: i :

[0120]

[0121] Where, when the water flow velocity is greater than the critical flow velocity, the sediment will begin to be disturbed; H critical represents the critical water level. When the critical water depth is exceeded, the disturbance of the water flow on the sediment may become more severe; the soil adhesion factor μ soil,i , reflects the degree of adhesion between soil and water flow; the greater the adhesion, the less likely the sediment is to be disturbed; μ critical represents the critical adhesion factor;

[0122] The following refers to the sediment disturbance constant C of the i-th operating area. sed,i An example chart:

[0123] Sediment type <![CDATA[Sediment disturbance constant C sed,i > sandy soil 0.1-0.3 fine sand 0.2-0.4 silt 0.4-0.6 organic sediments 0.3-0.5 clay 0.5-0.7

[0124] S14. Extract the soil stress y of the i-th operation area in the environmental data set soil,i , slope S i and soil moisture SM i After dimensionless processing, the soft foundation stability factor Rjw is calculated by the following formula i :

[0125]

[0126] Where y critical represents the critical stress of soft foundation, y soil,irepresents the soil stress in the i-th operating area, which is acquired through stress sensors. It represents the influencing factor of soil moisture. The higher the moisture, the worse the soil stability. Therefore, this item is used to correct the effect of moist soil on stability. It indicates that the slope has a positive relationship with the stability of the soft foundation. The greater the slope, the worse the stability. Therefore, areas with larger slopes require higher stability. Soft foundation refers to geological layers in soil or rock with lower bearing capacity, higher compressibility and poorer stability.

[0127] In this example, a regional risk prediction model built using a convolutional neural network (CNN) can effectively analyze the complex relationships between multiple environmental factors and identify potential risks within the desilting operation area. This technology enables a shift from static data to dynamic, real-time assessments.

[0128] The first risk area identification module analyzes multiple influencing factors, such as the dam instability factor Dsw of the i-th operation area. i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i , which can assess the risk status of the operating area in multiple dimensions. Specifically:

[0129] The dam instability factor is calculated through factors such as the ratio of water level to critical water level, soil friction angle, and soil moisture to accurately evaluate the stability of the dam.

[0130] The water shear force factor combines water flow density, water flow velocity, slope and other data to evaluate the scouring intensity of water flow on the bottom of the dam.

[0131] The sediment disturbance factor predicts the risk of sediment disturbance by factors such as soil adhesion, sediment particle diameter, and water flow velocity.

[0132] The soft foundation stability factor evaluates the stability of soft foundation areas based on factors such as soil stress, soil moisture, and slope.

[0133] Example 4

[0134] This embodiment is explained in Example 5, please refer to Figure 1 , the first risk area identification module further includes an association unit, a total assessment unit and a hierarchical assessment unit;

[0135] The associated unit is used to extract the dam instability factor Dsw of the i-th operation area i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw iAfter dimensionless processing, the comprehensive risk factor Zh of the i-th operation area is calculated by the following related formula i :

[0136] Zh i =a1×Dsw i +a2×Jql i +a3×Crd i -a4×Rjw i ;

[0137] Where a1, a2, a3 and a4 are the dam instability factors Dsw of the i-th operation area respectively. i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i The weight coefficient of the soft foundation stability factor Rjw i It is an anti-correlation factor. The lower the value, the greater the risk. And 0<a1<1, 0<a2<1, 0<a3<1, 0<a4<1, and a1+a2+a3+a4=1;

[0138] The total assessment unit is used to preset the total risk threshold X and calculate the comprehensive risk factor Zh of the i-th operation area. i Compare with the total risk threshold X to obtain the first judgment result, including:

[0139] When the comprehensive risk factor Zh of the i-th operation area i >Total risk threshold X, indicating that there is a potential risk in the operation area, generating the first warning information, and requiring classification and determination of the potential risk type;

[0140] When the comprehensive risk factor Zh of the i-th operation area i ≤ the total risk threshold X, indicating that there is no potential risk in the operation area and everything is normal. A qualified mark is generated in the 3D model, and the operation areas with qualified marks are counted to generate a qualified operation area group, indicating that dredging operations can be carried out sustainably;

[0141] The hierarchical evaluation unit is used to preset the first threshold value X1, the second threshold value X2, the third threshold value X3 and the fourth threshold value X4 after receiving the first warning information, and to calculate the dam instability factor Dsw of the i-th operation area. i , water flow shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i Compare with the corresponding threshold to obtain the graded assessment results, including:

[0142] When the dam instability factor Dsw of the i-th operation area i> the first threshold X1, indicating that the reservoir dam in the operation area has an instability risk, and the first instability graded warning instruction is generated; when the dam instability factor Dsw of the i-th operation area i < the first threshold X1, indicating that there is no risk of instability of the reservoir dam in the operation area;

[0143] When the water shear force factor Jql in the i-th operating area i > the second threshold X2, indicating that there is a sharp change in water flow in the reservoir dam in the operation area, and the impact force will cause the risk of disturbance of the reservoir dam, soil or sediment, and a second impact force graded warning instruction will be generated; when the water flow shear force factor Jql in the i-th operation area i ≤ the second threshold X2, indicating that there is no risk of rapid changes in water flow and impact force on the reservoir dam in the operation area;

[0144] When the sediment disturbance factor Crd in the i-th operation area i > the third threshold value X3, indicating that the sediment accumulation in the operation area is abnormal and the disturbance exceeds the controllable range, and a third sediment disturbance graded warning instruction is generated; when the sediment disturbance factor Crd of the i-th operation area i ≤ the third threshold X3, indicating that the sediment disturbance is within the controllable range and continuous monitoring is required;

[0145] When the soft foundation stability factor Rjw of the i-th operation area i ≥ the fourth threshold X4, indicating that the soil stability of the operation area is qualified and continuous monitoring is required; when the soft foundation stability factor Rjw of the i-th operation area is i < the fourth threshold value X4, indicating that the soil stability of the operation area is unqualified, and a fourth soft foundation classification warning instruction is generated.

[0146] In this embodiment, the first risk area identification module calculates a comprehensive risk factor by comprehensively considering the dam instability factor, water shear force factor, sediment disturbance factor, and soft foundation stability factor, and assigns different weight coefficients to each factor. By setting the overall assessment unit, the comprehensive risk factor is compared with the preset total risk threshold, and it is possible to promptly determine whether there is a potential risk in the operation area. When the comprehensive risk factor is greater than the set risk threshold, the system generates a first warning message, prompting relevant personnel to further analyze the risk type and ensure that appropriate measures are taken in areas with higher risks. For example, if the risk of dam instability is high, the system will automatically issue an instability warning instruction to attract the attention of staff and adjust the operation strategy.

[0147] After receiving the first warning information from the overall assessment unit, the hierarchical assessment unit further refines the risk assessment, combines the specific data of the four key factors, and makes a hierarchical judgment according to the preset thresholds. This hierarchical assessment system provides more refined risk management: through the comprehensive assessment and classification of multiple risk factors, the present invention provides more accurate decision-making support for dredging operations. Operators can take more targeted and flexible response measures based on different levels of warning information. For example, if the dam instability factor is high, the reinforcement measures of the reservoir dam will be strengthened; if the water shear force factor is high, it may be necessary to accelerate soil reinforcement or change the operation path to avoid scouring and sediment disturbance.

[0148] The system's automated workflow not only significantly improves assessment efficiency but also reduces errors and delays associated with manual judgment. By acquiring real-time environmental and equipment status data and integrating it with predictive models, the system automatically conducts comprehensive risk assessments and grading, effectively improving the management of dredging operations. Operators only need to make precise operational adjustments based on the system's early warning information and risk assessment results, significantly reducing operational complexity.

[0149] Example 5

[0150] This embodiment is explained in Example 4. Please refer to Figure 1 ,The construction operation monitoring module includes a sorting unit and a second monitoring unit;

[0151] The construction operation monitoring module is used to group qualified operation areas according to the comprehensive risk factor Zh of the i-th operation area. i Sort from small to large to obtain a priority list, and perform dredging operations on the priority list in order;

[0152] The second monitoring unit is used to collect the total volume of the operating vessels in the i-th operating area and establish an operating data set.

[0153] The construction operation monitoring module also includes a dynamic analysis unit and an operation evaluation unit. The dynamic analysis unit is used to analyze and calculate the soil liquefaction factor Slf of the i-th operation area based on the operation data set. i , the specific steps are as follows:

[0154] S21. The workboat is subject to buoyancy in the water. Buoyancy is equal to the pressure exerted by water on the bottom of the hull. Extract the total volume of the workboat in the i-th work area from the work data set and calculate the buoyancy F of the workboat in the i-th work area. ship,i :

[0155] F ship,i =ρ i ×V ship,j ×g;

[0156] Where V ship represents the volume of the workboat, g represents the acceleration due to gravity, which is 1000kg / m 3 ρ i represents the water density of the i-th operating area;

[0157] S22. The buoyancy of the workboat directly affects the distribution of water pressure on the soil, which in turn affects the probability of soil liquefaction. The greater the buoyancy, the greater the pressure the workboat exerts on the water and soil, increasing the risk of soil liquefaction.

[0158] Soil liquefaction is mainly composed of static pressure, dynamic pressure and liquefaction stress. Liquefaction occurs in loose saturated soil. When external disturbance causes the soil to lose its solid state, liquefaction stress is used to measure whether the soil will liquefy. Combined with the buoyancy F of the operation vessel in the i-th operation area obtained by S21, ship,i After dimensionless processing, the soil liquefaction factor Slf of the i-th operation area is calculated by the following formula i :

[0159]

[0160] σ static,i =γ i ×h i ;

[0161] Where, σ static,i represents the static pressure caused by the soil's own weight; σ dynamic,i represents the dynamic pressure caused by water flow disturbance, σ max It represents the maximum stress that the soil can withstand before liquefaction occurs; γ i represents the unit weight of the soil in the i-th operation area, h i represents the buried depth of the soil in the i-th operation area;

[0162] Among them, ΔP represents the maximum value of water pressure change, P critical It represents the critical water pressure that causes soil liquefaction. When this water pressure is exceeded, the pore water pressure of the soil will cause the consolidation force of the soil to decrease, and liquefaction will occur.

[0163] In this embodiment, the construction operation monitoring module prioritizes qualified work areas based on comprehensive risk factors, ensuring that operations are prioritized in areas with the lowest risk. This prioritization method significantly reduces potential threats in high-risk areas and ensures that workers begin dredging operations in safer areas, thereby reducing risk and improving operational efficiency. By monitoring the total volume of the work vessel through the second monitoring unit and combining it with the operational data set, the system can obtain real-time status data on the work vessel. This real-time data collection not only provides detailed information on the work vessel's load during construction operations but also provides essential basic data for dynamic analysis of soil liquefaction risk, thereby improving monitoring accuracy. The dynamic analysis unit calculates and analyzes the soil liquefaction factor based on the work vessel's buoyancy and other environmental data, providing a quantitative indicator of soil liquefaction risk. The calculation of the liquefaction factor takes into account the pressure exerted by the work vessel on the water and soil, analyzing the impact of the work vessel's buoyancy on soil pressure, ensuring accurate prediction of soil liquefaction risk during operations. Key factors affecting liquefaction, such as static pressure, dynamic pressure, and liquefaction stress, are calculated by this system, helping to predict soil liquefaction, allowing for proactive countermeasures and mitigating potential risks.

[0164] Example 6

[0165] This embodiment is explained in Example 1, please refer to Figure 1 The operation evaluation unit is used to preset the soil liquefaction threshold T and calculate the soil liquefaction factor Slf of the i-th operation area. i Compare this with the soil liquefaction threshold T to determine whether there is a risk of soil liquefaction causing the dredging vessel to tilt or sink during the dredging operation, including:

[0166] If the soil liquefaction factor Slf in the i-th operation area i > soil liquefaction threshold T, indicating that there is soil liquefaction in the reservoir dam in the operation area, which may cause the dredging vessel to tilt or sink, and the fifth operation level warning instruction is generated; if the soil liquefaction factor Slf of the i-th operation area i ≤Soil liquefaction threshold T, indicating that there is no risk of soil liquefaction on the reservoir embankment in the operation area causing the dredging vessel to tilt or sink, and continuous monitoring is carried out.

[0167] In this embodiment, the operation assessment unit, by presetting a soil liquefaction threshold T and monitoring the soil liquefaction factor in the operation area in real time, can accurately determine whether there is a risk of soil liquefaction causing the dredging vessel to tilt or sink during the dredging operation. By comparing this with the threshold T, the system can promptly detect potential liquefaction risks and provide early warning instructions to operators to avoid major accidents. When the soil liquefaction factor in the operation area exceeds the preset liquefaction threshold T, the system can automatically generate a fifth-level operation warning instruction, alerting operators to the risk of soil liquefaction in the area causing the dredging vessel to tilt or sink. This dynamic early warning mechanism can promptly remind relevant personnel to take emergency measures and reduce the probability of risk events.

[0168] Example 7

[0169] This embodiment is explained in Example 1, please refer to Figure 1 The strategy module is used to generate corresponding strategies upon receiving the first instability graded warning instruction, the second impact force graded warning instruction, the third sediment disturbance graded warning instruction, the fourth soft foundation graded warning instruction, and the fifth operation graded warning instruction, including:

[0170] The first strategy is generated according to the first instability graded warning instruction, including: installing a 20% coverage reservoir dam protection device in the operation area, and installing 3-6 anchor rods at the base of the reservoir dam for support, until the dam instability factor Dsw of the i-th operation area is i When the water level drops below the first threshold, X1, desilting operations resume. Reservoir dam protection devices include waterproof membranes and geonets. The waterproof membranes must be made of PVC with a thickness of 0.5 mm. The geonets must have a strength of 200 kN / m to ensure resistance to water erosion. To address the risk of dam instability, the strategy module effectively enhances dam stability by installing protective devices (such as waterproof membranes and geonets) and adding anchor supports, reducing safety incidents caused by dam instability. Furthermore, the design materials and technical specifications of the reservoir dam protection devices ensure they can effectively resist water erosion, enhancing their effectiveness.

[0171] The second strategy is generated based on the second impact force graded warning instruction, including: arranging floating isolation walls in the operation area, covering an area of ​​30% of the operation area to reduce the impact of water flow impact on the reservoir dam and sediment; the floating isolation wall is made of high-density polyethylene with a thickness of 2m, and the water flow velocity in the operation area is adjusted between 0.3-1.5m / s until the water shear force factor Jql in the i-th operation area is reached. iDesilting operations resume when the water level reaches ≤ the second threshold X2. In the event of sudden changes in water flow and impact forces, the strategy module deploys floating isolation walls to mitigate the impact, reducing the impact of water flow on the reservoir embankment and sediment. The deployment of floating isolation walls and the regulation of water flow rates ensure water flow stability and effectively reduce sediment disturbance. This measure protects the safety of the embankment while avoiding excessive sediment disturbance, ensuring a stable operating environment.

[0172] The third strategy is generated based on the third sediment disturbance graded warning instruction, including: arranging sediment disturbance protection nets in the operation area, covering an area of ​​40% of the operation area; using geotextile fiber nets with a mesh size of 3mm; until the sediment disturbance factor Crd of the i-th operation area is i When sediment disturbance exceeds the controllable range, the strategy module deploys a sediment disturbance protection net to prevent further disturbance. This strategy effectively reduces abnormal sediment accumulation and disturbance, ensuring that sediment in the operation area is properly managed and preventing excessive disturbance from affecting operational effectiveness.

[0173] The fourth strategy is generated based on the fourth soft foundation grade warning instruction, including: grouting reinforcement in the operation area, injecting 20-30% of 10-15% stability enhancer, including gypsum powder or cement slurry; the grouting volume per square meter is 1-2L; and a reinforced wall is set on the soft foundation of the operation area, with a wall height of 2-3m and a width of 1.5m; until the soft foundation stability factor Rjw of the i-th operation area is i When the water level reaches ≥ the fourth threshold x4, desilting operations resume. To address the risk of unstable soft foundations, the strategy module effectively improves soil stability in the operation area through grouting and the installation of reinforcement walls. Precise control of grouting volume and the design of reinforcement walls ensure long-term soil stability in the operation area, providing a solid foundation for subsequent desilting operations.

[0174] The fifth strategy is generated according to the fifth operation grade warning instruction, including: installing 4-6 adjustable buoyancy platforms on the bottom of the operation vessel to prevent the hull from tilting or sinking due to soil liquefaction; the buoyancy design of each adjustable buoyancy platform can support a weight of 10-15 tons; once the soil liquefaction factor Slf of the i-th operation area is detected iIf the soil liquefaction threshold exceeds T × 150%, the emergency mechanism is activated, and the work vessel immediately ceases operations and evacuates to a safe area. The emergency response time is no more than 15 minutes. To address the risk of soil liquefaction, the strategy module has designed an adjustable buoyancy platform to prevent the dredging vessel from tilting or sinking due to soil liquefaction. The buoyancy platform ensures that the dredging vessel can cope with different liquefaction risks and ensures the stability of the work vessel in dangerous situations. In addition, if the liquefaction factor exceeds a preset threshold, the system automatically activates the emergency mechanism and quickly evacuates the work vessel to a safe area, avoiding major accidents.

[0175] In this embodiment, the strategy module can automatically generate corresponding response strategies based on different early warning instructions (such as dam instability, impact force, sediment disturbance, soft foundation stability, soil liquefaction, etc.), forming a multi-level, comprehensive risk management framework. This mechanism can accurately prevent and control each different type of risk, ensuring that various uncertainties encountered during the operation process can be responded to and handled in a timely manner. All strategies are aimed at enhancing the safety of the operation area and ensuring that corresponding protective measures can be taken or the operation process can be adjusted when facing various adverse conditions. This comprehensive strategy makes the safety of the operation process more stringent and can cope with various risk types, thereby ensuring the smooth progress of the operation and avoiding accidents. Through the preset strategy, the impact of different risk factors is effectively controlled within a reasonable range, reducing the possibility of operation interruption or shutdown. This not only improves the operation efficiency, but also enhances the sustainability of the operation. Through reasonable risk management and real-time response, the smooth progress of dredging operations is ensured.

[0176] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each set of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0177] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The factors in the formula are set by those skilled in the art according to actual conditions. The above is only a preferred specific implementation method of the present invention, but the protection scope of the present invention is not limited to this. Any technician familiar with this technical field, within the technical scope disclosed by the present invention, can make equivalent replacements or changes based on the technical solution and inventive concept of the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A real-time operation monitoring system based on dynamic assessment of risk factors, characterized by: include: The 3D model building module is used to collect 3D point cloud data of the reservoir operation area to be desilted, build a 3D model, divide the reservoir operation area to be desilted into several operation areas, mark them, and set monitoring points in each operation area; The data acquisition module is used to install IoT sensor groups at monitoring points to collect environmental data of each operating area and establish an environmental data set; The first risk area identification module is used to calculate the dam instability factor Dsw of the i-th operation area based on the environmental data set i , water shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i , and associate to obtain the comprehensive risk factor Zh of the i-th operation area i , and preset the total risk threshold X, if the comprehensive risk factor Zh of the i-th operation area i If the total risk threshold X is exceeded, the first warning information is triggered. If the comprehensive risk factor Zh of the i-th operation area i If the total risk threshold X is not exceeded, a qualified operation area group is generated; After receiving the first warning information, the dam instability factor Dsw of the operation area is calculated. i , water shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i Evaluate them respectively and generate corresponding first instability graded warning instructions, second impact force graded warning instructions, third sediment disturbance graded warning instructions and fourth soft foundation graded warning instructions; The construction operation monitoring module is used to prioritize qualified operation area groups and then perform dredging operations. It collects the total volume of the operation boat in the i-th operation area in real time, establishes an operation data set, and constructs the soil liquefaction factor Slf of the i-th operation area. i , analyze the disturbance pressure and soil liquefaction changes during the dredging operation, and preset the soil liquefaction threshold T. If the soil liquefaction factor Slf in the i-th operation area i If the soil liquefaction threshold T is exceeded, the corresponding fifth-level warning instruction is triggered; The strategy module is used to generate and implement corresponding strategies after receiving the first instability graded warning instruction, the second impact force graded warning instruction, the third sediment disturbance graded warning instruction, the fourth soft foundation graded warning instruction and the fifth operation graded warning instruction.

2. A real-time operation monitoring system based on dynamic risk factor assessment according to claim 1, characterized in that: The three-dimensional model building module includes a three-dimensional terrain acquisition unit and a region division unit; The three-dimensional terrain acquisition unit is used to use a camera mounted on a drone to generate a three-dimensional model of the reservoir operation area to be desilted using image matching technology; A laser radar is used to scan the reservoir area to be desilted to obtain ground 3D point cloud data, which includes elevation and slope information of the reservoir dam, embankment, and surrounding environment. An underwater laser scanning device is used to scan the underwater area of ​​the reservoir area to be desilted to obtain underwater 3D point cloud data, which includes 3D data of the underwater reservoir dam, spillway, and sediment accumulation layer structure. The ground 3D point cloud data and the underwater 3D point cloud data are then fused into a 3D stereo model. The area division unit is used to divide the reservoir operation area to be desilted into several operation areas, set monitoring points in each operation area, and mark the several operation areas in the three-dimensional model as: Q1, Q2, Q3, ..., Q n , n represents the total number of operating areas.

3. A real-time operation monitoring system based on dynamic risk factor assessment according to claim 1, characterized in that: The data acquisition module is used to install an IoT sensor group in the monitoring point. The IoT sensor group includes: water level sensor, soil moisture sensor, stress sensor, density sensor, angle sensor, pressure sensor, flow rate sensor and sonar device. The environmental data set includes: the current water level H of the i-th operation area water,i , slope S i , soil friction angle μ i , soil compressive strength σ soil,i , soil moisture SM i , density ρ i , water flow velocity V flow,i , the angle θ between the water flow and the bottom of the reservoir dam i , the adhesion force between particles F adhesion,i , average soil particle diameter D i , sediment disturbance constant C sed,i , the average diameter of sediment particles D sediment,i and soil stress y soil,i .

4. A real-time operation monitoring system based on dynamic risk factor assessment according to claim 1, characterized in that: The first risk area identification module includes a prediction model building unit and an analysis unit; The prediction model establishment unit is used to establish a regional risk prediction model based on the environmental data set and the dredging equipment status data set; The steps for establishing the regional risk prediction model are as follows: using a convolutional neural network to construct an initial convolutional neural network model, and using the environmental data set and the dredging equipment status data set to train and test the initial convolutional neural network model, and using the trained initial convolutional neural network model as the regional risk prediction model. At the same time, the intermediate layer output of the regional risk prediction model is used as a feature vector to identify feature information, and the regional risk prediction model is trained and tested based on the obtained feature information, and the trained regional risk prediction model is used as data for running predictions; The analysis unit is used to analyze the environmental data set through the regional risk prediction model to calculate the dam instability factor Dsw of the i-th operation area. i , water shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i .

5. A real-time operation monitoring system based on dynamic risk factor assessment according to claim 4, characterized in that: The analysis unit is used to calculate the dam instability factor Dsw of the i-th operation area i , water shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i , the specific steps are: S11. Extract the current water level H of the i-th operating area in the environmental data set water,i , slope S i , soil friction angle μ i , soil compressive strength σ soil,i and soil moisture SM i After dimensionless processing, the dam instability factor Dsw of the i-th operation area is calculated by the following formula: i : Where H water,i represents the current water level of the i-th operating area, H critical Indicates the critical water level, S i represents the slope of the i-th operating area, μ i represents the soil friction angle of the i-th operating area, σ soil,i represents the soil compressive strength of the i-th operating area, SM i represents the soil moisture of the i-th operating area; S12. Extract the water density ρ of the i-th operating area in the environmental data set i , water flow velocity V flow,i , the angle θ between the water flow and the bottom of the reservoir dam i and slope S i After dimensionless processing, the water flow shear force factor Jql is calculated using the following formula: i : Where, ρ i represents the water density in the i-th operating area, V flow,i represents the water flow velocity in the i-th operating area, θ i represents the angle between the water flow in the i-th operation area and the bottom of the reservoir dam, S i represents the slope of the i-th operating area; Represents the kinetic energy of water flow, which affects the scouring intensity of reservoir dams; sin(θ i ) takes into account the angle between the water flow and the bottom of the reservoir dam. The more consistent the slope of the water flow, the stronger the scouring effect. The term takes into account the additive effect of slope on water velocity; S13, extracting the adhesion force F between particles in the i-th operating area in the environmental data set adhesion,i and the average soil particle diameter D i , after dimensionless processing, first calculate the adhesion factor μ of the soil in the i-th operation area soil,i : Where, represents the contact area of ​​the particles; S131, based on the adhesion factor μ of the soil in the i-th operation area soil,i , combined with the sediment disturbance constant C of the i-th operating area sed,i , the average diameter of sediment particles D sediment,i , water flow velocity V flow,i 、Current water level H water,i and the angle θ between the water flow and the bottom of the reservoir dam i After dimensionless processing, the sediment disturbance factor Crd of the i-th operating area is calculated by the following formula: i : Where H critical Indicates the critical water level; μ critical represents the critical adhesion factor; S14. Extract the soil stress y of the i-th operation area in the environmental data set soil,i , slope S i and soil moisture SM i After dimensionless processing, the soft foundation stability factor Rjw is calculated by the following formula i : Where y critical represents the critical stress of soft foundation, y soil,i Represents the soil stress in the i-th operating area, which is acquired through the stress sensor.

6. A real-time operation monitoring system based on dynamic risk factor assessment according to claim 1, characterized in that: The first risk area identification module further includes an association unit, an overall assessment unit, and a hierarchical assessment unit; The associated unit is used to extract the dam instability factor Dsw of the i-th operation area i , water shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i After dimensionless processing, the comprehensive risk factor Zh of the i-th operation area is calculated by the following related formula i : Zh i =a1×Dsw i +a2×Jql i +a3×Crd i -a4×Rjw i ; Where a1, a2, a3 and a4 are the dam instability factors Dsw of the i-th operation area respectively. i , water shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i The weight coefficient of the soft foundation stability factor Rjw i It is an anti-correlation factor, the lower the value, the greater the risk; The overall assessment unit is used to preset the overall risk threshold X and calculate the comprehensive risk factor Zh of the i-th operation area. i Compare with the total risk threshold X to obtain the first judgment result, including: When the comprehensive risk factor Zh of the i-th operation area i >Total risk threshold X, indicating that there is a potential risk in the operation area, generating the first warning information, and requiring classification and determination of the potential risk type; When the comprehensive risk factor Zh of the i-th operation area i ≤ the total risk threshold X, indicating that there is no potential risk in the operation area and everything is normal. A qualified mark is generated in the 3D model, and the operation areas with qualified marks are counted to generate a qualified operation area group, indicating that dredging operations can be carried out sustainably; The hierarchical evaluation unit is used to preset a first threshold value X1, a second threshold value X2, a third threshold value X3 and a fourth threshold value X4 after receiving the first warning information, and to calculate the dam instability factor Dsw of the i-th operation area. i , water shear force factor Jql i , sediment disturbance factor Crd i and soft foundation stability factor Rjw i Compare with the corresponding threshold to obtain the graded assessment results, including: When the dam instability factor Dsw of the i-th operation area i > the first threshold X1, indicating that the reservoir dam in the operation area has an instability risk, and the first instability graded warning instruction is generated; when the dam instability factor Dsw of the i-th operation area i < the first threshold X1, indicating that there is no risk of instability of the reservoir dam in the operation area; When the water shear force factor Jql in the i-th operating area i > the second threshold X2, indicating that there is a sharp change in water flow in the reservoir dam in the operation area, and the impact force will cause the risk of disturbance of the reservoir dam, soil or sediment, and a second impact force graded warning instruction will be generated; when the water flow shear force factor Jql in the i-th operation area i ≤ the second threshold X2, indicating that there is no risk of rapid changes in water flow and impact force on the reservoir dam in the operation area; When the sediment disturbance factor Crd in the i-th operation area i > the third threshold value X3, indicating that the sediment accumulation in the operation area is abnormal and the disturbance exceeds the controllable range, and a third sediment disturbance graded warning instruction is generated; when the sediment disturbance factor Crd of the i-th operation area i ≤ the third threshold X3, indicating that the sediment disturbance is within the controllable range and continuous monitoring is required; When the soft foundation stability factor Rjw of the i-th operation area i ≥ the fourth threshold X4, indicating that the soil stability of the operation area is qualified and continuous monitoring is required; when the soft foundation stability factor Rjw of the i-th operation area is i < the fourth threshold value X4, indicating that the soil stability of the operation area is unqualified, and a fourth soft foundation classification warning instruction is generated.

7. The real-time operation monitoring system based on dynamic risk factor assessment according to claim 1 is characterized in that: The construction operation monitoring module includes a sorting unit and a second monitoring unit; The construction operation monitoring module is used to group qualified operation areas according to the comprehensive risk factor Zh of the i-th operation area. i Sort from small to large to obtain a priority list, and perform dredging operations on the priority list in order; The second monitoring unit is used to collect the total volume of the operating vessels in the i-th operating area and establish an operating data set.

8. The real-time operation monitoring system based on dynamic risk factor assessment according to claim 1 is characterized in that: The construction operation monitoring module also includes a dynamic analysis unit and an operation evaluation unit. The dynamic analysis unit is used to analyze and calculate the soil liquefaction factor Slf of the i-th operation area based on the operation data set. i , the specific steps are as follows: S21. The workboat is subject to buoyancy in the water. Buoyancy is equal to the pressure exerted by water on the bottom of the hull. Extract the total volume of the workboat in the i-th work area from the work data set and calculate the buoyancy F of the workboat in the i-th work area. ship,i : F ship,i =ρ i ×V ship,j ×g; Where V ship represents the volume of the workboat, g represents the acceleration due to gravity, which is 1000kg / m 3 ; ρ i represents the water density of the i-th operating area; S22: The buoyancy of the workboat directly affects the pressure distribution of the water on the soil, and thus affects the probability of soil liquefaction. The greater the buoyancy, the greater the pressure of the workboat on the water and soil, increasing the risk of soil liquefaction. Combined with the buoyancy of the workboat F in the i-th work area obtained in S21, ship,i After dimensionless processing, the soil liquefaction factor Slf of the i-th operation area is calculated by the following formula i : s static,i =c i ×h i ; Where, σ static,i represents the static pressure caused by the soil's own weight; σ dynamic,i represents the dynamic pressure caused by water flow disturbance, σ max It represents the maximum stress that the soil can withstand before liquefaction occurs; γ i represents the unit weight of the soil in the i-th operation area, h i represents the soil burial depth of the i-th operation area; Among them, ΔP represents the maximum value of water pressure change, P critical It represents the critical water pressure that causes soil liquefaction. When this water pressure is exceeded, the pore water pressure of the soil will cause the consolidation force of the soil to decrease, and liquefaction will occur.

9. A real-time operation monitoring system based on dynamic risk factor assessment according to claim 8, characterized in that: The operation evaluation unit is used to preset the soil liquefaction threshold T and calculate the soil liquefaction factor Slf of the i-th operation area. i Compare this with the soil liquefaction threshold T to determine whether there is a risk of soil liquefaction causing the dredging vessel to tilt or sink during the dredging operation, including: If the soil liquefaction factor Slf in the i-th operation area i > soil liquefaction threshold T, indicating that there is soil liquefaction in the reservoir dam in the operation area, which may cause the dredging vessel to tilt or sink, and the fifth operation level warning instruction is generated; if the soil liquefaction factor Slf of the i-th operation area i ≤Soil liquefaction threshold T, indicating that there is no risk of soil liquefaction on the reservoir embankment in the operation area causing the dredging vessel to tilt or sink, and continuous monitoring is required.

10. A real-time operation monitoring system based on dynamic risk factor assessment according to claim 9, characterized in that: The strategy module is configured to generate corresponding strategies upon receiving the first instability graded warning instruction, the second impact force graded warning instruction, the third sediment disturbance graded warning instruction, the fourth soft foundation graded warning instruction, and the fifth operation graded warning instruction, including: The first strategy is generated according to the first instability graded warning instruction, including: installing a 20% coverage reservoir dam protection device in the operation area, and installing 3-6 anchor rods at the base of the reservoir dam for support, until the dam instability factor Dsw of the i-th operation area is i < the first threshold value X1, and then resume desilting operations; the reservoir dam protection device includes: waterproof membrane and geonet; The second strategy is generated according to the second impact force graded warning instruction, including: arranging floating isolation walls in the operation area, covering an area of ​​30% of the operation area, adjusting the water flow velocity in the operation area between 0.3-1.5m / s, until the water flow shear force factor Jql in the i-th operation area is i ≤ the second threshold value X2, and then resume the dredging operation; The third strategy is generated according to the third sediment disturbance graded warning instruction, including: arranging sediment disturbance protection nets in the operation area, covering an area of ​​40% of the operation area, until the sediment disturbance factor Crd of the i-th operation area is i ≤ the third threshold value X3, and then resume the dredging operation; The fourth strategy is generated according to the fourth soft foundation grade warning instruction, including: grouting reinforcement in the operation area, injecting 20-30% of 10-15% stability enhancer, and setting up a reinforcement wall on the soft foundation of the operation area, with a wall height of 2-3m and a width of 1.5m; until the soft foundation stability factor Rjw of the i-th operation area is i ≥ the fourth threshold value X4, and then resume the dredging operation; The fifth strategy is generated according to the fifth operation grade warning instruction, including: installing 4-6 adjustable buoyancy platforms on the bottom of the operation ship; once the soil liquefaction factor Slf of the i-th operation area is detected i >Soil liquefaction threshold T×150%, the emergency mechanism is activated, the work vessel immediately stops operations and evacuates to a safe area, and the emergency response time does not exceed 15 minutes.

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