A multi-data processing and analysis method and system for river engineering models

Abstract

The present invention discloses a multi-data processing and analysis method and system for a river engineering model, and relates to the technical field of water conservancy engineering. The method generates a standard river engineering motion data set by extracting motion feature vectors in a digital twin model and performing preprocessing. The method calculates the spatial distribution concentration Nsc(x, y, z, t) of sediment in a three-dimensional coordinate grid through a standardized data set, and evaluates its changing trend over time. When the spatial distribution concentration Nsc(x, y, z, t) of sediment is greater than 0, the abnormal area is highlighted using a visualization interface; when the spatial distribution concentration Nsc(x, y, z, t) of sediment is less than or equal to 0, it indicates that the sediment concentration is normal. For abnormal areas, the method further calculates the sediment transport volume Qs and the deposition rate S, accurately predicts the movement path, deposition area and speed of sediment, and dynamically analyzes the movement of river sediment. The method can track the sediment change trend in real time under a complex dynamic environment.

Description

Technical Field

[0001] The invention relates to the technical field of water conservancy engineering, and in particular to a multi-data processing and analysis method and system for a river engineering model. Background Art

[0002] River regulation and water resources management belong to the broad field of water conservancy engineering and environmental science. In this field, the study of river sediment movement and deposition is a key topic, which is directly related to specific issues such as river dredging, flood prevention and control, and water ecological protection. Sediment movement in rivers involves complex processes of sediment transport, diffusion, and deposition. Controlling and optimizing these processes helps to ensure the smooth flow of rivers, protect the water ecological environment, and improve the efficiency of water resource utilization. As an important tool in this subject, river sediment movement and deposition simulation can provide a scientific basis for river regulation through data analysis and model prediction.

[0003] At present, traditional sediment monitoring methods rely on manual sampling and offline analysis, with low data acquisition efficiency and poor real-time performance. Secondly, existing sediment deposition prediction models are mostly based on static data or simplified conditions, which are difficult to fully reflect the complex dynamic characteristics of rivers. Finally, for the abnormal distribution of sediment concentration in different river areas, existing methods often lack the ability to accurately evaluate and visualize the results, resulting in low efficiency in sediment management decisions. These shortcomings limit the widespread application of river sediment movement and deposition simulation in modern water conservancy projects.

[0004] The above status quo and shortcomings are mainly attributed to the following points: First, traditional monitoring technology is difficult to support large-scale, long-term high-precision data collection; second, the limitation of model computing capacity fails to integrate multi-source data and fully capture the dynamic characteristics of sediment movement and deposition; third, river sediment movement has strong nonlinear and regional characteristics, which are difficult to effectively describe by conventional methods. Under the influence of this, when the abnormal distribution of sediment concentration is not discovered and resolved in time, it may lead to increased river sedimentation, frequent floods and waterlogging, imbalance of water ecosystems, and even affect the economic development of riverside areas. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a multi-data processing and analysis method and system for a river engineering model, which solves the problems mentioned in the background technology.

[0006] To achieve the above objectives, the present invention is implemented by the following technical scheme: comprising the following steps:

[0007] S1. Deploy river engineering monitoring equipment in actual rivers, collect river data in real time, build a river engineering server, transmit the collected river data to the river engineering server, and access the river management system through the API application program interface to extract the actual river engineering data of the current river and transmit it to the river engineering server. In the river engineering server, build a digital twin model of river engineering based on the river engineering data and river data;

[0008] S2, by extracting the motion feature vector of the river dynamic simulation in the digital twin model and preprocessing the motion feature vector, a standard river engineering motion data set is obtained;

[0009] S3. Extract the standard river movement data set to calculate the sediment spatial distribution concentration Nsc of the sediment in the water flow, and based on the output results of the sediment spatial distribution concentration Nsc, preliminarily evaluate the temporal trend of the sediment spatial distribution concentration Nsc in different areas of the river in the river engineering digital twin model;

[0010] S4. If the sediment concentration in the current area is abnormal after preliminary assessment, the standard river movement data set is extracted to calculate and output the sediment transport volume Qs and sedimentation rate S of the river, and predict the sediment distribution and movement path of the river as well as the sediment deposition area and deposition rate;

[0011] S5. The sediment transport volume Qs and the deposition rate S are then comprehensively calculated to output the comprehensive sediment deposition index Zns. Based on the output result of the comprehensive sediment deposition index Zns, a secondary comparative evaluation is performed to comprehensively analyze the movement of river sediment under abnormal sediment concentration in the river, and based on the secondary comparative evaluation results, optimization tips are generated.

[0012] Preferably, said S1 includes S11 and S12;

[0013] S11. Deploy river monitoring equipment at the same intervals in actual rivers to collect river data of riverbeds in different river basins in real time;

[0014] The river monitoring equipment includes a sliding friction meter, a laser particle size analyzer, a viscometer, a water level meter, a flow meter, a particle concentration sensor and an underwater sonar;

[0015] The river data includes sediment movement data, river movement data and water body data;

[0016] S12, setting up a wireless transmission network NB-loT to integrate the river engineering monitoring equipment with the river engineering server, transmitting the river data to the river engineering server, and using 3DMax software to construct a river engineering three-dimensional model based on the actual river data obtained and the river engineering data of the actual river;

[0017] The river engineering data include riverbed depth, water surface width and slope;

[0018] The acquired three-dimensional model of river engineering is used by Unity and fluid mechanics CFD model to dynamically simulate the three-dimensional model of river engineering based on river data. At the same time, a three-dimensional coordinate grid is set for the three-dimensional model of river engineering, and the three-dimensional coordinates (x, y, z) are marked at each cross point of the three-dimensional coordinate grid, where x represents the horizontal axis coordinate, y represents the vertical axis coordinate, and z represents the vertical axis coordinate. Then a visualization interface is constructed, and the three-dimensional model of river engineering after dynamic simulation is loaded into the visualization interface for integration to obtain the digital twin model of the river engineering.

[0019] Preferably, S2 includes S21 and S22;

[0020] S21. After constructing the digital twin model, extracting features of the digital twin model to obtain motion feature vectors of river dynamic simulation;

[0021] The motion characteristic vector includes the friction coefficient Mc, sediment morphology factor Fs, sediment diffusion coefficient Dm, particle density Pp, water viscosity Nx, particle settling velocity Vs, water shear stress Jq and riverbed roughness coefficient Kb;

[0022] The friction coefficient Mc is collected in real time by a sliding friction meter and then integrated into the digital twin model for extraction;

[0023] The sediment morphology factor Fs is collected in real time by a laser particle size analyzer and then integrated into the digital twin model for extraction;

[0024] The particle density Pp is collected in real time by a particle concentration sensor and then integrated into the digital twin model for extraction and acquisition;

[0025] The water viscosity Nx is collected in real time by a viscometer and then integrated into the digital twin model for extraction and acquisition;

[0026] The riverbed roughness coefficient Kb is collected in real time by underwater sonar and then integrated into the digital twin model for extraction;

[0027] The sediment diffusion coefficient Dm is extracted by inversion calculation based on the flow field and sediment characteristics using the fluid mechanics CFD model through the turbulence intensity of the water flow and the particle characteristics. The specific calculation formula is: ; Where Vt represents the turbulent viscosity, Ks represents the sediment diffusion Prandtl value;

[0028] The particle settling velocity Vs is calculated and extracted based on the particle density Pp and the water viscosity Nx. The specific algorithm formula is: , where Pf represents the river water density and g represents the gravitational acceleration;

[0029] The water flow shear stress Jq is calculated and extracted by combining the river velocity and river depth. The specific algorithm formula is: , where h represents the water depth, obtained by the water level gauge, and Sf represents the water flow slope;

[0030] S22. Preprocessing the extracted motion feature vectors, wherein the preprocessing method includes data cleaning and denoising. After the preprocessing, the motion feature vectors are scaled to the same interval using a normalization method to eliminate the dimensional influence of the motion feature vectors and obtain a standard river engineering motion data set.

[0031] Preferably, said S3 includes S31 and S32;

[0032] S31. Start the digital twin model, extract the constantly changing standard river movement data set in real time, and calculate the sediment spatial distribution concentration Nsc in the three-dimensional coordinate grid in different time periods in real time;

[0033] The sediment spatial distribution concentration Nsc is calculated and outputted by the following algorithm formula;

[0034] ;

[0035] Where Nsc(x, y, z, t) represents the change in the spatial distribution concentration of sediment in the three-dimensional coordinate (x, y, z) space with time t, Dm(t) represents the sediment diffusion coefficient at time t, Ms represents the mass of sediment, V represents the volume of the water sample, represents the sediment concentration, represents the second-order spatial derivative of sediment concentration, Represents the changing distribution of sediment concentration in the three-dimensional coordinate (x, y, z) space over time t.

[0036] Preferably, S32, based on the output result of the change distribution Nsc(x, y, z, t) of the spatial distribution concentration of sediment over time t in the three-dimensional coordinate (x, y, z) space identified in the digital twin model, a preliminary evaluation is performed to analyze the sediment concentration distribution in different river areas in the digital twin model, and the specific evaluation content is as follows;

[0037] When the distribution of the change in the spatial distribution concentration of sediment in the three-dimensional coordinate (x, y, z) space over time t Nsc (x, y, z, t)>0, it means that the spatial distribution concentration of sediment in the current river area is abnormal. At this time, the three-dimensional coordinate grid interval of the current three-dimensional coordinate (x, y, z) is highlighted through the visualization interface of the digital twin model, indicating that the sediment concentration in the current river area is abnormal, indicating that the sediment concentration is increasing, which may be due to a large amount of sediment transport, an increase in the deposition area, or a weakening of the diffusion intensity;

[0038] When the distribution of the change in the spatial distribution concentration of sediment over time t in the three-dimensional coordinate (x, y, z) space Nsc(x, y, z, t) ≤ 0, it indicates that the spatial distribution concentration of sediment in the current river area is normal, indicating that the sediment concentration is decreasing, which may be due to sediment deposition, flow dilution, or enhanced diffusion effect.

[0039] Preferably, said S4 includes S41 and S42;

[0040] S41. After preliminarily evaluating the abnormal concentration of sediment spatial distribution in the current river area, a sediment transport algorithm model is constructed, and the standard river movement data set is extracted and input into the sediment transport algorithm model to calculate and output the sediment transport volume Qs, and predict and analyze the sediment transport situation of the river;

[0041] The sediment transport volume Qs is calculated and output by the following sediment transport algorithm model;

[0042] ;

[0043] Where Qs(t) represents the sediment transport at time t, Mc(t) represents the friction coefficient at time t, Jq(t) represents the water flow shear stress at time t, Pp(t) represents the particle density at time t, Fs(t) represents the sediment morphology factor at time t, A represents the water flow cross-sectional area, and is obtained based on the water surface width of the digital twin model.

[0044] Preferably, S42, simultaneously constructing a sediment deposition algorithm model, extracting a standard river movement data set, inputting the sediment deposition algorithm model, calculating and outputting a sediment deposition rate S of the river sediment, and predicting the sediment deposition situation;

[0045] The deposition rate S is calculated and outputted by the following algorithm formula;

[0046] ;

[0047] Where S(t) represents the sedimentation rate at time t, Vs(t) represents the particle settling velocity at time t, Kb(t) represents the riverbed roughness coefficient at time t, and ls(t) represents the water flow velocity at time t.

[0048] Preferably, said S5 includes S51 and S52;

[0049] S51, based on the obtained sediment transport volume Qs and sedimentation rate S, a comprehensive calculation is performed to output a comprehensive sediment deposition index Zns, which comprehensively considers the movement, diffusion and deposition of sediment;

[0050] The comprehensive sediment deposition index Zns is calculated and outputted by the following algorithm formula;

[0051] ;

[0052] Where Zns(t) represents the comprehensive sediment deposition index at time t, a1 and a2 represent the weight values ​​of sediment transport Qs and sedimentation rate S, respectively, and their specific values ​​are set by the user.

[0053] Preferably, S52, based on the output result of the comprehensive sediment deposition index Zns, a secondary comparative evaluation is performed to comprehensively analyze the movement of river sediment under abnormal sediment concentration in the river, and prompt information is generated based on the evaluation result. The specific evaluation content is as follows;

[0054] When the comprehensive sediment deposition index Zns(t) at time t is greater than 1, it means that the current sediment transport volume is abnormal. At this time, the visual interface prompts to accelerate dredging and reinforce the river channel;

[0055] When the comprehensive sediment deposition index Zns(t) at time t is ≤1, it means that the current sediment deposition is abnormal. At this time, the visual interface prompts you to adjust the water flow rate and build a sediment dam.

[0056] A river engineering model multi-data processing and analysis system, comprising a river engineering modeling module, a feature extraction and processing module, a sediment distribution analysis module, a sediment movement analysis module and an abnormal prompt module;

[0057] The river engineering modeling module deploys river engineering monitoring equipment in actual rivers to collect river data in real time, and builds a river engineering server to transmit the collected river data to the river engineering server. At the same time, it accesses the river management system through the API application program interface to extract the actual river engineering data of the current river and transmit it to the river engineering server. In the river engineering server, a digital twin model of the river engineering is constructed based on the river engineering data and river data;

[0058] The feature extraction and processing module extracts the motion feature vectors of the river dynamic simulation in the digital twin model and pre-processes the motion feature vectors to obtain a standard river engineering motion data set;

[0059] The sediment distribution analysis module calculates the sediment spatial distribution concentration Nsc of sediment in the water flow by extracting the standard river movement data set, and based on the output result of the sediment spatial distribution concentration Nsc, preliminarily evaluates the temporal trend of the sediment spatial distribution concentration Nsc in different areas of the river in the digital twin model of the river engineering;

[0060] The sediment movement analysis module extracts the standard river movement data set to calculate and output the sediment transport volume Qs and sedimentation rate S of the river after preliminarily evaluating the abnormal sediment concentration in the current area, and predicts the sediment distribution and movement path of the river as well as the sediment deposition area and deposition rate;

[0061] The abnormal prompt module comprehensively calculates the sediment transport volume Qs and the deposition rate S, outputs a comprehensive sediment deposition index Zns, conducts a secondary comparative evaluation based on the output result of the comprehensive sediment deposition index Zns, comprehensively analyzes the movement of river sediment under abnormal sediment concentration in the river, and generates optimization prompts based on the secondary comparative evaluation results.

[0062] The present invention provides a multi-data processing and analysis method and system for river engineering models, which has the following beneficial effects:

[0063] (1) This method deploys river monitoring equipment in actual rivers. This method can collect real-time river data in different river basins at the same spacing, including sediment movement data, river movement data, and water body data. These data are integrated into the river server through the wireless transmission network NB-IoT, and the river three-dimensional model is constructed using 3DMax software. A visual digital twin model with a three-dimensional coordinate grid is generated through Unity dynamic simulation. The digital twin model can capture and simulate the dynamic characteristics of the river in real time, realize high-precision river data display and dynamic simulation, and provide comprehensive and accurate data support for subsequent analysis.

[0064] (2) This method extracts motion feature vectors from the digital twin model and preprocesses them to generate a standard river motion data set. This method calculates the spatial distribution concentration of sediment Nsc(x, y, z, t) in the three-dimensional coordinate grid through a standardized data set and evaluates its changing trend over time. When the spatial distribution concentration of sediment Nsc(x, y, z, t) is greater than 0, the abnormal area is highlighted using a visualization interface; when the spatial distribution concentration of sediment Nsc(x, y, z, t) is less than or equal to 0, it indicates that the sediment concentration is normal. For abnormal areas, this method further calculates the sediment transport volume Qs and deposition rate S, accurately predicts the movement path, deposition area and speed of sediment, and dynamically analyzes the movement of river sediment. Compared with traditional static analysis methods, this method can track the sediment change trend in real time in a complex dynamic environment and provide a more scientific basis for decision-making.

[0065] (3) This method calculates the sediment transport volume Qs and the deposition rate S, and further outputs the comprehensive sediment deposition index Zns to comprehensively evaluate the sediment transport, deposition and diffusion. When the comprehensive sediment deposition index Zns>1 indicates that the sediment transport volume is abnormal, the system generates optimization prompts through a visual interface and recommends taking measures to accelerate dredging and reinforce the river channel; when the comprehensive sediment deposition index Zns≤1 indicates that the sediment deposition is abnormal, the system prompts to adjust the water flow rate or build a sand dam to improve the sediment deposition situation. Through secondary comparative evaluation and intelligent prompts, this method can comprehensively diagnose the sediment movement of rivers under abnormal sediment concentration, timely discover and solve problems, effectively improve the scientificity and efficiency of river management, and provide strong technical support for water resources management and ecological environment protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 A schematic diagram of a multi-data processing and analysis method for a river engineering model according to the present invention;

[0067] Figure 2 The present invention is a schematic diagram of the steps of a multi-data processing and analysis system for a river engineering model. DETAILED DESCRIPTION

[0068] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention. Example 1

[0069] See also Figure 1 The present invention provides a multi-data processing and analysis method for a river engineering model. To achieve the above purpose, the present invention is implemented through the following technical scheme: comprising the following steps:

[0070] S1. Deploy river engineering monitoring equipment in actual rivers, collect river data in real time, build a river engineering server, transmit the collected river data to the river engineering server, and access the river management system through the API application program interface to extract the actual river engineering data of the current river and transmit it to the river engineering server. In the river engineering server, build a digital twin model of river engineering based on the river engineering data and river data;

[0071] S2, by extracting the motion feature vector of the river dynamic simulation in the digital twin model and preprocessing the motion feature vector, a standard river engineering motion data set is obtained;

[0072] S3. Extract the standard river movement data set to calculate the sediment spatial distribution concentration Nsc of the sediment in the water flow, and based on the output results of the sediment spatial distribution concentration Nsc, preliminarily evaluate the temporal trend of the sediment spatial distribution concentration Nsc in different areas of the river in the river engineering digital twin model;

[0073] S4. If the sediment concentration in the current area is abnormal after preliminary assessment, the standard river movement data set is extracted to calculate and output the sediment transport volume Qs and sedimentation rate S of the river, and predict the sediment distribution and movement path of the river as well as the sediment deposition area and deposition rate;

[0074] S5. The sediment transport volume Qs and the deposition rate S are then comprehensively calculated to output the comprehensive sediment deposition index Zns. Based on the output result of the comprehensive sediment deposition index Zns, a secondary comparative evaluation is performed to comprehensively analyze the movement of river sediment under abnormal sediment concentration in the river, and based on the secondary comparative evaluation results, optimization tips are generated.

[0075] In this embodiment, the method relies on the river monitoring equipment deployed in the actual river to collect sediment movement, river dynamics and water characteristics data in real time, and uses the wireless transmission network NB-IoT to integrate into the river server to build a high-precision digital twin model. Further extract the motion feature vector in the digital twin model, and generate a standardized river movement data set after preprocessing to provide an accurate input basis for subsequent analysis. Based on the standard river movement data set, this method realizes the dynamic calculation and evaluation of the spatial distribution concentration Nsc of sediment in the three-dimensional coordinate grid, and makes a preliminary diagnosis of the sediment concentration distribution in different areas of the river and its trend over time. When the abnormal sediment concentration area is identified, this method predicts the distribution path, deposition area and speed of the sediment by calculating the sediment transport volume Qs and the deposition rate S, and further outputs the comprehensive sediment deposition index Zns for secondary comparative evaluation. The abnormal area is intuitively displayed through the visual interface and optimization prompts are generated. When the sediment transport is abnormal, it is recommended to accelerate dredging and river reinforcement; when the deposition is abnormal, it is recommended to adjust the water flow rate or build a sand dam. This method integrates the whole process of monitoring, analysis, prediction and optimization, which not only improves the diagnostic accuracy of abnormal sediment concentration, but also significantly enhances the scientificity and efficiency of river sediment transport and deposition management. By implementing this method, the goal of efficient monitoring, accurate simulation and intelligent optimization of river sediment movement and deposition has been achieved, which significantly improves the overall level of river management and water resources management, and provides solid technical support for water ecological environment protection and flood disaster prevention and control. Example 2

[0076] Specifically: S1 includes S11 and S12;

[0077] S11. Deploy river monitoring equipment at the same intervals in actual rivers to collect river data of riverbeds in different river basins in real time;

[0078] River monitoring equipment includes sliding friction meters, laser particle size analyzers, viscometers, water level meters, current meters, particle concentration sensors and underwater sonars;

[0079] River data include sediment movement data, river movement data and water body data;

[0080] S12, setting up a wireless transmission network NB-loT to integrate the river engineering monitoring equipment with the river engineering server, transmitting the river data to the river engineering server, and using 3DMax software to construct a river engineering three-dimensional model based on the actual river data obtained and the river engineering data of the actual river;

[0081] River data include riverbed depth, water surface width and slope;

[0082] The acquired three-dimensional model of river engineering is used by Unity and fluid mechanics CFD model to dynamically simulate the three-dimensional model of river engineering based on river data. At the same time, a three-dimensional coordinate grid is set for the three-dimensional model of river engineering, and the three-dimensional coordinates (x, y, z) are marked at each cross point of the three-dimensional coordinate grid, where x represents the horizontal axis coordinate, y represents the vertical axis coordinate, and z represents the vertical axis coordinate. Then a visualization interface is constructed, and the three-dimensional model of river engineering after dynamic simulation is loaded into the visualization interface for integration to obtain the digital twin model of the river engineering.

[0083] This method deploys river monitoring equipment at the same spacing in the actual river to collect key data such as sediment movement, river movement and water characteristics in real time, comprehensively covering the changes in the riverbed in different basins. These data are integrated into the river server through the wireless transmission network NB-IoT, and combined with actual river data such as riverbed depth, water surface width and slope, the river three-dimensional model is constructed using 3DMax software. Subsequently, the river three-dimensional model is dynamically simulated based on the fluid mechanics CFD model to generate a dynamic river digital twin model with three-dimensional coordinate grid markings, and a visualization interface is built through Unity to achieve intuitive display and real-time update of the dynamic changes of the river. This method integrates multi-source data to build a highly accurate digital twin model that can dynamically capture the characteristics of river sediment transport, deposition and flow, significantly improves the breadth and real-time nature of data acquisition, and provides a solid foundation for subsequent sediment movement analysis and governance decisions. After implementing this method, the visualization, dynamicization and efficiency of river sediment movement and deposition processes have been achieved, which has greatly improved the scientificity, systematicness and efficiency of river management, and provided technical support for water resources management, ecological protection and flood control. Example 3

[0084] Specifically: S2 includes S21 and S22;

[0085] S21. After constructing the digital twin model, extracting features of the digital twin model to obtain motion feature vectors of river dynamic simulation;

[0086] The motion characteristic vectors include friction coefficient Mc, sediment morphology factor Fs, sediment diffusion coefficient Dm, particle density Pp, water viscosity Nx, particle settling velocity Vs, water flow shear stress Jq and riverbed roughness coefficient Kb;

[0087] The friction coefficient Mc is collected in real time by a sliding tribometer and then integrated into the digital twin model for extraction;

[0088] The sediment morphology factor Fs is collected in real time by a laser particle size analyzer and then integrated into the digital twin model for extraction;

[0089] The particle density Pp is collected in real time by the particle concentration sensor and then integrated into the digital twin model for extraction;

[0090] The water viscosity Nx is collected in real time by a viscometer and then integrated into the digital twin model for extraction;

[0091] The riverbed roughness coefficient Kb is collected in real time by underwater sonar and then integrated into the digital twin model for extraction;

[0092] The sediment diffusion coefficient Dm is extracted through inversion calculation based on the flow field and sediment characteristics using the fluid mechanics CFD model through the turbulence intensity of the water flow and the particle characteristics. The specific calculation formula is: ; Where Vt represents the turbulent viscosity, Ks represents the sediment diffusion Prandtl value;

[0093] The particle settling velocity Vs is calculated and extracted based on the particle density Pp and the water viscosity Nx. The specific algorithm formula is: , where Pf represents the river water density and g represents the gravitational acceleration;

[0094] The water flow shear stress Jq is calculated and extracted by combining the river velocity and river depth. The specific algorithm formula is: , where h represents the water depth, obtained by the water level gauge, and Sf represents the water flow slope;

[0095] S22. Preprocessing the extracted motion feature vectors, including data cleaning and denoising. After preprocessing, the motion feature vectors are scaled to the same interval using a normalization method to eliminate the dimensional influence of the motion feature vectors and obtain a standard river engineering motion data set.

[0096] In this embodiment, the method extracts the motion feature vectors of the river dynamic simulation after constructing the digital twin model. These features are collected in real time by sliding friction meters, laser particle size analyzers, viscometers, particle concentration sensors, underwater sonars and other equipment, and integrated into the digital twin model, and inversely calculated by the fluid mechanics CFD model. The motion feature vectors are then preprocessed, including data cleaning, denoising and normalization operations, and the motion feature vectors are scaled to a uniform interval to eliminate the dimensional effect, and finally a standard river engineering motion data set is generated. This method significantly improves the accuracy and availability of data through comprehensive extraction and standardized processing of river dynamic characteristics, laying a solid foundation for subsequent sediment transport and deposition analysis. By implementing this method, dynamic monitoring and standardized integration of key river characteristic data are achieved, which not only improves the analysis efficiency and modeling accuracy of river engineering data, but also enhances the comprehensive understanding of river sediment movement and deposition processes, providing strong technical support for river management and decision-making. Example 4

[0097] Specifically: S3 includes S31 and S32;

[0098] S31. Start the digital twin model, extract the constantly changing standard river movement data set in real time, and calculate the sediment spatial distribution concentration Nsc in the three-dimensional coordinate grid in different time periods in real time;

[0099] The sediment spatial distribution concentration Nsc is calculated and output by the following algorithm formula;

[0100] ;

[0101] Where Nsc(x, y, z, t) represents the change in the spatial distribution concentration of sediment in the three-dimensional coordinate (x, y, z) space with time t, Dm(t) represents the sediment diffusion coefficient at time t, Ms represents the mass of sediment, V represents the volume of the water sample, represents the sediment concentration, represents the second-order spatial derivative of sediment concentration, Represents the changing distribution of sediment concentration in the three-dimensional coordinate (x, y, z) space over time t.

[0102] S32. Based on the output results of the change distribution of the spatial distribution concentration of sediment over time t in the three-dimensional coordinate (x, y, z) space identified in the digital twin model, Nsc (x, y, z, t), a preliminary evaluation is conducted to analyze the distribution of sediment concentration in different river areas in the digital twin model. The specific evaluation contents are as follows;

[0103] When the distribution of the change in the spatial distribution concentration of sediment in the three-dimensional coordinate (x, y, z) space over time t Nsc (x, y, z, t)>0, it means that the spatial distribution concentration of sediment in the current river area is abnormal. At this time, the three-dimensional coordinate grid interval of the current three-dimensional coordinate (x, y, z) is highlighted through the visualization interface of the digital twin model, indicating that the sediment concentration in the current river area is abnormal, indicating that the sediment concentration is increasing, which may be due to a large amount of sediment transport, an increase in the deposition area, or a weakening of the diffusion intensity;

[0104] When the distribution of the change in the spatial distribution concentration of sediment over time t in the three-dimensional coordinate (x, y, z) space Nsc(x, y, z, t) ≤ 0, it indicates that the spatial distribution concentration of sediment in the current river area is normal, indicating that the sediment concentration is decreasing, which may be due to sediment deposition, flow dilution, or enhanced diffusion effect.

[0105] In this embodiment, the method extracts the constantly updated standard river motion data set in real time after starting the digital twin model, and uses the algorithm formula to calculate the change distribution Nsc(x, y, z, t) of the spatial distribution concentration of sediment in the three-dimensional coordinate (x, y, z) space over time t. This calculation comprehensively considers the sediment diffusion coefficient Dm(t), sediment mass Ms, water sample volume V and the second-order spatial derivative of sediment concentration, and comprehensively describes the dynamic distribution characteristics of sediment in three-dimensional space over time. Based on the output results of the change distribution Nsc(x, y, z, t) of the spatial distribution concentration of sediment in the three-dimensional coordinate (x, y, z) space over time t, the system further conducts a preliminary assessment of the river area in the digital twin model: when the change distribution Nsc(x, y, z, t) of the spatial distribution concentration of sediment in the three-dimensional coordinate (x, y, z) space over time t>0, the abnormal area is highlighted and the possible reasons for the increase in sediment concentration are prompted; when the change distribution Nsc(x, y, z, t) of the spatial distribution concentration of sediment in the three-dimensional coordinate (x, y, z) space over time t≤0, the sediment concentration reduction is identified and analyzed to be attributed to the deposition or dilution effect. Through this method, the real-time monitoring and dynamic evaluation of the spatial distribution of sediment are successfully realized, and the detection ability and response efficiency of sediment concentration anomalies are comprehensively improved. Based on the visualization function of the digital twin model, the system can intuitively display the distribution characteristics of sediment concentration and its changing trends, providing more scientific and efficient technical support for river sediment transport and deposition analysis. This not only optimizes the formulation of river management strategies, but also significantly improves the ability of flood prevention and control and ecological protection, laying a solid foundation for achieving sustainable management of water resources. Example 5

[0106] Specifically: S4 includes S41 and S42;

[0107] S41. After preliminarily evaluating the abnormal concentration of sediment spatial distribution in the current river area, a sediment transport algorithm model is constructed, and the standard river movement data set is extracted and input into the sediment transport algorithm model to calculate and output the sediment transport volume Qs, and predict and analyze the sediment transport situation of the river;

[0108] The sediment transport volume Qs is calculated and output by the following sediment transport algorithm model;

[0109] ;

[0110] Where Qs(t) represents the sediment transport at time t, Mc(t) represents the friction coefficient at time t, Jq(t) represents the water flow shear stress at time t, Pp(t) represents the particle density at time t, Fs(t) represents the sediment morphology factor at time t, A represents the water flow cross-sectional area, and is obtained based on the water surface width of the digital twin model.

[0111] S42, constructing a sediment deposition algorithm model, extracting a standard river movement data set, inputting it into the sediment deposition algorithm model, calculating and outputting a sediment deposition rate S of the river sediment, and predicting the sediment deposition situation;

[0112] The deposition rate S is calculated and output by the following algorithm formula;

[0113] ;

[0114] Where S(t) represents the sedimentation rate at time t, Vs(t) represents the particle settling velocity at time t, Kb(t) represents the riverbed roughness coefficient at time t, and ls(t) represents the water flow velocity at time t.

[0115] In this embodiment, after preliminarily evaluating the abnormal spatial distribution concentration of sediment in the current river area, the method constructs a sediment transport algorithm model, extracts a standard river movement data set as input, and calculates the sediment transport volume Qs(t). The algorithm combines the friction coefficient Mc(t), the water flow shear stress Jq(t), the particle density Pp(t), the sediment morphology factor Fs(t) and the water flow cross-sectional area A to achieve accurate prediction of the sediment transport situation in the river. At the same time, by constructing a sediment deposition algorithm model, extracting the same data set input model, and calculating the sediment deposition rate S(t). The deposition rate prediction comprehensively considers the riverbed roughness coefficient Kb(t) and the water flow velocity ls(t) to accurately identify the deposition rate and regional distribution of sediment. The implementation of this method realizes the quantitative calculation and dynamic prediction of the sediment transport and deposition process, and comprehensively improves the depth and accuracy of the river sediment movement analysis. Through the dual analysis of sediment transport volume and deposition rate, this method can deeply reveal the movement path and deposition law of sediment in different basins, and provide a scientific basis for the governance and regulation of abnormal areas. This not only optimizes the accuracy of river sediment control measures, but also effectively improves flood disaster prevention and control capabilities and ecological environmental protection levels, ensuring the scientificity and sustainability of river management. Example 6

[0116] Specifically: S5 includes S51 and S52;

[0117] S51, based on the obtained sediment transport volume Qs and sedimentation rate S, a comprehensive calculation is performed to output a comprehensive sediment deposition index Zns, which comprehensively considers the movement, diffusion and deposition of sediment;

[0118] The comprehensive sediment deposition index Zns is calculated and output by the following algorithm formula;

[0119] ;

[0120] Where Zns(t) represents the comprehensive sediment deposition index at time t, a1 and a2 represent the weight values ​​of sediment transport Qs and sedimentation rate S, respectively, and their specific values ​​are set by the user.

[0121] S52, based on the output result of the comprehensive sediment deposition index Zns, a secondary comparative evaluation is performed to comprehensively analyze the movement of river sediment under abnormal sediment concentration in the river, and prompt information is generated based on the evaluation results. The specific evaluation contents are as follows;

[0122] When the comprehensive sediment deposition index Zns(t) at time t is greater than 1, it means that the current sediment transport volume is abnormal. At this time, the visual interface prompts to accelerate dredging and reinforce the river channel;

[0123] When the comprehensive sediment deposition index Zns(t) at time t is ≤1, it means that the current sediment deposition is abnormal. At this time, the visual interface prompts you to adjust the water flow rate and build a sediment dam.

[0124] In this embodiment, the method comprehensively calculates and outputs the comprehensive sediment deposition index Zns(t) based on the calculated sediment transport volume Qs(t) and deposition rate S(t). This index balances the influence of sediment transport and deposition through the weight values ​​a1 and a2 set by the user, and comprehensively reflects the movement, diffusion and deposition of sediment. After the comprehensive sediment deposition index Zns(t) is output, the system further performs a secondary comparative evaluation: when the comprehensive sediment deposition index Zns(t)>1, it indicates that the sediment transport volume is abnormal, and it is recommended to take measures such as accelerated dredging and river channel reinforcement; when the comprehensive sediment deposition index Zns(t)≤1, it indicates that the sediment deposition is abnormal, and it is recommended to adjust the water flow rate or build a sand dam. The evaluation results are intuitively displayed through the visual interface of the digital twin model to ensure that abnormal areas and optimization suggestions can be quickly identified and applied. This method generates a comprehensive and accurate analysis of the comprehensive sediment deposition index Zns(t) by integrating the multi-dimensional factors of sediment transport and deposition, and combines the visual interface to realize the intelligentization of abnormal diagnosis and governance optimization. Through secondary comparative evaluation and optimization prompts, not only the response speed of abnormal river sediment movement is improved, but also the scientificity and pertinence of governance measures are significantly enhanced, the risk of river siltation and flooding is effectively reduced, and reliable technical support is provided for efficient river management and ecological protection. Example 7

[0125] See also Figure 2 , a river engineering model multi-data processing and analysis system, including a river engineering modeling module, a feature extraction and processing module, a sediment distribution analysis module, a sediment movement analysis module and an abnormal prompt module;

[0126] The river engineering modeling module deploys river engineering monitoring equipment in actual rivers to collect river data in real time, and builds a river engineering server to transmit the collected river data to the river engineering server. At the same time, it accesses the river management system through the API application program interface to extract the actual river engineering data of the current river and transmit it to the river engineering server. In the river engineering server, a digital twin model of the river engineering is constructed based on the river engineering data and river data;

[0127] The feature extraction and processing module extracts the motion feature vectors of the river dynamic simulation in the digital twin model and pre-processes the motion feature vectors to obtain a standard river engineering motion data set;

[0128] The sediment distribution analysis module calculates the sediment spatial distribution concentration Nsc of sediment in the water flow by extracting the standard river movement data set, and based on the output result of the sediment spatial distribution concentration Nsc, preliminarily evaluates the temporal trend of the sediment spatial distribution concentration Nsc in different areas of the river in the digital twin model of the river engineering;

[0129] The sediment movement analysis module extracts the standard river movement data set to calculate and output the sediment transport volume Qs and sedimentation rate S of the river after preliminarily evaluating the abnormal sediment concentration in the current area, and predicts the sediment distribution and movement path of the river as well as the sediment deposition area and deposition rate;

[0130] The abnormal prompt module comprehensively calculates the sediment transport volume Qs and the deposition rate S, outputs a comprehensive sediment deposition index Zns, conducts a secondary comparative evaluation based on the output result of the comprehensive sediment deposition index Zns, comprehensively analyzes the movement of river sediment under abnormal sediment concentration in the river, and generates optimization prompts based on the secondary comparative evaluation results.

[0131] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. A multi-data processing and analysis method for river engineering models, characterized by: The following steps are involved: S1. Deploy river engineering monitoring equipment in actual rivers to collect river data in real time, build a river engineering server, transmit the collected river data to the river engineering server, and access the river management system through the API application program interface to extract the actual river engineering data of the current river and transmit it to the river engineering server. In the river engineering server, build a digital twin model of river engineering based on the river engineering data and river data; S2, by extracting the motion feature vector of the river dynamic simulation in the digital twin model and preprocessing the motion feature vector, a standard river engineering motion data set is obtained; S3. Extract the standard river movement data set to calculate the sediment spatial distribution concentration Nsc of the sediment in the water flow, and based on the output results of the sediment spatial distribution concentration Nsc, preliminarily evaluate the temporal trend of the sediment spatial distribution concentration Nsc in different areas of the river in the river engineering digital twin model; S4. If the sediment concentration in the current area is initially assessed to be abnormal, the standard river movement data set is extracted for calculation, and the sediment transport volume Qs and sedimentation rate S of the river are output, and the sediment distribution and movement path of the river, as well as the sediment deposition area and deposition rate are predicted; S5. The sediment transport volume Qs and the deposition rate S are then comprehensively calculated to output the comprehensive sediment deposition index Zns. Based on the output result of the comprehensive sediment deposition index Zns, a secondary comparative evaluation is performed to comprehensively analyze the movement of river sediment under abnormal sediment concentration in the river, and based on the secondary comparative evaluation results, optimization tips are generated.

2. A river engineering model multi-data processing and analysis method according to claim 1, characterized in that: Said S1 includes S11 and S12; S11. Deploy river monitoring equipment at the same intervals in actual rivers to collect river data of riverbeds in different river basins in real time; The river monitoring equipment includes a sliding friction meter, a laser particle size analyzer, a viscometer, a water level meter, a flow meter, a particle concentration sensor and an underwater sonar; The river data includes sediment movement data, river movement data and water body data; S12, setting up a wireless transmission network NB-loT to integrate the river engineering monitoring equipment with the river engineering server, transmitting the river data to the river engineering server, and using 3DMax software to construct a river engineering three-dimensional model based on the actual river data obtained and the river engineering data of the actual river; The river engineering data include riverbed depth, water surface width and slope; The acquired three-dimensional model of river engineering is used by Unity and fluid mechanics CFD model to dynamically simulate the three-dimensional model of river engineering based on river data. At the same time, a three-dimensional coordinate grid is set for the three-dimensional model of river engineering, and the three-dimensional coordinates (x, y, z) are marked at each cross point of the three-dimensional coordinate grid, where x represents the horizontal axis coordinate, y represents the vertical axis coordinate, and z represents the vertical axis coordinate. Then a visualization interface is constructed, and the three-dimensional model of river engineering after dynamic simulation is loaded into the visualization interface for integration to obtain the digital twin model of the river engineering.

3. A river engineering model multi-data processing and analysis method according to claim 2, characterized in that: The S2 includes S21 and S22; S21. After constructing the digital twin model, extracting features of the digital twin model to obtain motion feature vectors of river dynamic simulation; The motion characteristic vector includes friction coefficient Mc, sediment morphology factor Fs, sediment diffusion coefficient Dm, particle density Pp, water viscosity Nx, particle settling velocity Vs, water flow shear stress Jq and riverbed roughness coefficient Kb; The sediment diffusion coefficient Dm is extracted by inversion calculation based on the flow field and sediment characteristics using the fluid mechanics CFD model through the turbulence intensity of the water flow and the particle characteristics. The specific calculation formula is: ; Where Vt represents the turbulent viscosity, Ks represents the sediment diffusion Prandtl value; The particle settling velocity Vs is calculated and extracted based on the particle density Pp and the water viscosity Nx. The specific algorithm formula is: , where Pf represents the river water density and g represents the gravitational acceleration; The water flow shear stress Jq is calculated and extracted by combining the river velocity and river depth. The specific algorithm formula is: , where h represents the water depth and Sf represents the water flow slope; S22. Preprocessing the extracted motion feature vectors, wherein the preprocessing method includes data cleaning and denoising. After the preprocessing, the motion feature vectors are scaled to the same interval using a normalization method to eliminate the dimensional influence of the motion feature vectors and obtain a standard river engineering motion data set.

4. A river engineering model multi-data processing and analysis method according to claim 3, characterized in that: The S3 includes S31 and S32; S31. Start the digital twin model, extract the constantly changing standard river movement data set in real time, and calculate the sediment spatial distribution concentration Nsc in the three-dimensional coordinate grid in different time periods in real time; The sediment spatial distribution concentration Nsc is calculated and outputted by the following algorithm formula; ； Where Nsc(x, y, z, t) represents the change in the spatial distribution concentration of sediment in the three-dimensional coordinate (x, y, z) space with time t, Dm(t) represents the sediment diffusion coefficient at time t, Ms represents the mass of sediment, V represents the volume of the water sample, represents the sediment concentration, represents the second-order spatial derivative of sediment concentration, Represents the changing distribution of sediment concentration in the three-dimensional coordinate (x, y, z) space over time t.

5. A river engineering model multi-data processing and analysis method according to claim 4, characterized in that: S32. Based on the output results of the change distribution of the spatial distribution concentration of sediment over time t in the three-dimensional coordinate (x, y, z) space identified in the digital twin model, Nsc (x, y, z, t), a preliminary evaluation is conducted to analyze the distribution of sediment concentration in different river areas in the digital twin model. The specific evaluation contents are as follows; When the distribution of the change in the spatial distribution concentration of sediment in the three-dimensional coordinate (x, y, z) space over time t Nsc (x, y, z, t)>0, it means that the spatial distribution concentration of sediment in the current river area is abnormal. At this time, the three-dimensional coordinate grid interval of the current three-dimensional coordinate (x, y, z) is highlighted through the visualization interface of the digital twin model, indicating that the sediment concentration in the current river area is abnormal; When the change distribution of the spatial distribution concentration of sediment in the three-dimensional coordinate (x, y, z) space over time t is Nsc(x, y, z, t) ≤ 0, it means that the spatial distribution concentration of sediment in the current river area is normal.

6. A river engineering model multi-data processing and analysis method according to claim 5, characterized in that: The S4 includes S41 and S42; S41. After preliminarily evaluating the abnormal concentration of sediment spatial distribution in the current river area, a sediment transport algorithm model is constructed, and the standard river movement data set is extracted and input into the sediment transport algorithm model to calculate and output the sediment transport volume Qs, and predict and analyze the sediment transport situation of the river; The sediment transport volume Qs is calculated and output by the following sediment transport algorithm model; ； Where Qs(t) represents the sediment transport at time t, Mc(t) represents the friction coefficient at time t, Jq(t) represents the water flow shear stress at time t, Pp(t) represents the particle density at time t, Fs(t) represents the sediment morphology factor at time t, and A represents the water flow cross-sectional area.

7. A river engineering model multi-data processing and analysis method according to claim 6, characterized in that: S42, constructing a sediment deposition algorithm model, extracting a standard river movement data set, inputting it into the sediment deposition algorithm model, calculating and outputting a sediment deposition rate S of the river sediment, and predicting the sediment deposition situation; The deposition rate S is calculated and outputted by the following algorithm formula; ； Where S(t) represents the sedimentation rate at time t, Vs(t) represents the particle settling velocity at time t, Kb(t) represents the riverbed roughness coefficient at time t, and ls(t) represents the water flow velocity at time t.

8. A river engineering model multi-data processing and analysis method according to claim 7, characterized in that: The S5 includes S51 and S52; S51, based on the obtained sediment transport volume Qs and sedimentation rate S, a comprehensive calculation is performed to output a comprehensive sediment deposition index Zns, which comprehensively considers the movement, diffusion and deposition of sediment; The comprehensive sediment deposition index Zns is calculated and outputted by the following algorithm formula; ； Where Zns(t) represents the comprehensive sediment deposition index at time t, a1 and a2 represent the weight values ​​of sediment transport Qs and sedimentation rate S, respectively, and their specific values ​​are set by the user.

9. A river engineering model multi-data processing and analysis method according to claim 8, characterized in that: S52, performing a secondary comparative evaluation based on the output result of the comprehensive sediment deposition index Zns, comprehensively analyzing the movement of river sediment under abnormal sediment concentration in the river, and generating prompt information based on the evaluation result, and the specific evaluation content is as follows; When the comprehensive sediment deposition index Zns(t) at time t is greater than 1, it means that the current sediment transport volume is abnormal. At this time, the visual interface prompts to accelerate dredging and reinforce the river channel; When the comprehensive sediment deposition index Zns(t) at time t is ≤1, it means that the current sediment deposition is abnormal. At this time, the visual interface prompts you to adjust the water flow rate and build a sediment dam.

10. A river engineering model multi-data processing and analysis system, applied to a river engineering model multi-data processing and analysis method according to any one of claims 1 to 9, characterized in that: It includes river engineering modeling module, feature extraction and processing module, sediment distribution analysis module, sediment movement analysis module and abnormal prompt module; The river engineering modeling module deploys river engineering monitoring equipment in actual rivers to collect river data in real time, and builds a river engineering server to transmit the collected river data to the river engineering server. At the same time, it accesses the river management system through the API application program interface to extract the actual river engineering data of the current river and transmit it to the river engineering server. In the river engineering server, a digital twin model of the river engineering is constructed based on the river engineering data and river data; The feature extraction and processing module extracts the motion feature vectors of the river dynamic simulation in the digital twin model and pre-processes the motion feature vectors to obtain a standard river engineering motion data set; The sediment distribution analysis module calculates the sediment spatial distribution concentration Nsc of sediment in the water flow by extracting the standard river movement data set, and based on the output result of the sediment spatial distribution concentration Nsc, preliminarily evaluates the temporal trend of the sediment spatial distribution concentration Nsc in different areas of the river in the digital twin model of the river engineering; The sediment movement analysis module extracts the standard river movement data set to calculate and output the sediment transport volume Qs and sedimentation rate S of the river after preliminarily evaluating the abnormal sediment concentration in the current area, and predicts the sediment distribution and movement path of the river as well as the sediment deposition area and deposition rate; The abnormal prompt module comprehensively calculates the sediment transport volume Qs and the deposition rate S, outputs the comprehensive sediment deposition index Zns, and then performs a secondary comparative evaluation based on the output result of the comprehensive sediment deposition index Zns, comprehensively analyzes the movement of river sediment under abnormal sediment concentration in the river, and generates optimization prompts based on the secondary comparative evaluation results.

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