A backfilling gravel dispatching optimization method based on a monitoring platform

Abstract

This invention discloses an optimized method for backfill crushed stone transportation based on a monitoring platform, comprising: establishing a three-dimensional digital geological model of the site, dividing the site into backfill zones, extracting geological stratification data at the center of each zone, and predicting the backfill volume V for each zone to reach the design intersection elevation by using the stratified summation method based on the soil compression characteristics under one-dimensional consolidation lateral stress state and the settlement theory calculation method. i This process yields settlement data; monitoring points are established, and wireless monitoring methods are used to monitor the surface settlement of each zone. Real-time data is imported into the monitoring platform via 4G / 5G wireless sensing technology. The monitoring platform performs Denaulay triangulation on the entire monitoring area to generate a three-dimensional model mesh, and uses Kriging interpolation technology to generate thermal cloud maps of settlement for each zone from the real-time monitoring information acquired by the surface monitoring sensors. This invention avoids redundant backfill gravel caused by conservative design.

Description

Technical Field

[0001] This invention belongs to the field of land reclamation engineering technology, specifically a method for optimizing the transportation of backfill crushed stone based on a monitoring platform. Background Technology

[0002] In recent years, digital monitoring platforms based on wireless data acquisition have been increasingly applied in engineering construction processes, providing functions such as monitoring data acquisition, monitoring data analysis, and visualization of monitoring content. A wireless monitoring system generally consists of an equipment layer, a monitoring data middleware layer, and a monitoring platform layer. The equipment layer provides various monitoring sensors, and the on-site intelligent monitoring and acquisition base station relays the monitoring data to the server via 4G / 5G technology. From there, the data is transmitted to the monitoring platform via a software interface for use by engineering personnel.

[0003] Currently, monitoring platforms for land reclamation projects primarily focus on data acquisition and analysis, and model display. Furthermore, data analysis often relies on regression fitting, lacking capabilities for strata consolidation analysis and data interaction. Given the large areas and complex hydrological environments of land reclamation projects, influenced by geological conditions, tidal climate, and construction techniques, monitoring data only reflects historical changes. Mathematical analysis of this data is insufficient to predict the trends in subsidence and displacement in different areas within the reclaimed land area, posing challenges to construction safety control, construction analysis, operation and maintenance, and scientific research in land reclamation projects.

[0004] Traditional methods for transporting crushed stone in land reclamation areas often result in excessive crushed stone usage due to conservative design, leading to resource waste and increased burden and cost of material transportation within the site. To overcome these shortcomings and avoid waste of crushed stone and related resources, an optimized method for transporting backfill crushed stone based on a monitoring platform is proposed. Summary of the Invention

[0005] To address the aforementioned problems in the existing technology, this invention provides an optimized method for backfill crushed stone transportation based on a monitoring platform, which avoids redundancy in backfill crushed stone caused by conservative design.

[0006] The technical solution to achieve the above objectives is:

[0007] A method for optimizing the transportation of backfill crushed stone based on a monitoring platform includes:

[0008] Step S1: Establish a three-dimensional digital geological model of the site, divide the site into backfill zones, extract geological stratification data at the center of each zone, and predict the backfill volume V for each zone to reach the design intersection elevation by using the layered summation method based on the soil compression characteristics under one-dimensional consolidation lateral stress state and the settlement theory calculation method. i This allows us to obtain settlement data;

[0009] Step S2: Establish monitoring points and use wireless monitoring methods to monitor the surface settlement of each zone. Import real-time data into the monitoring platform through 4G / 5G wireless sensing technology.

[0010] Step S3: The monitoring platform performs Denaulay triangulation on the entire monitoring range to generate a three-dimensional model mesh, and uses Kriging interpolation technology to generate thermal cloud maps W of settlement amount for each zone from the real-time monitoring information obtained by the surface monitoring sensors. s The surface elevation of each zone was adjusted by measuring the settlement, and a thermal cloud map W of the actual elevation was generated by inverse distance interpolation. r,i This enables the visualization of dynamic adjustment of surface elevation;

[0011] Step S4: Generate a heat map W of the design elevation based on the design intersection elevation. d,i , surface thermal cloud map W r,i Thermal cloud map of design elevation W d,i Perform 3D mesh registration;

[0012] Step S5: Compare the actual elevation heat map W within each zone. r,i Thermal cloud map of design elevation W d,i It automatically calculates the predicted actual elevation heat map W within each zone. r,i Thermal cloud map of design elevation W d,i The difference in the amount of crushed stone between them ΔV i Determine the amount of fill or excavation within each zone;

[0013] Step S6: Calculate the difference in gravel volume ΔV between each zone using the monitoring platform. i Establish a dataset and coordinate set for crushed stone quantity scheduling. The monitoring platform establishes a coordinate set based on the coordinate positions of the center of each partition in the two datasets, which is used for optimal path analysis of crushed stone scheduling.

[0014] In step S7, the monitoring platform visualizes the crushed stone transportation information. The monitoring screen displays the crushed stone transportation route information, transportation time, and maximum single transportation volume in real time, and calculates the comprehensive utilization rate of crushed stone.

[0015] Preferably, step S1 includes:

[0016] Step S11: Using the topographic surface, borehole, geophysical topographic and geological data collected during the geological exploration stage, a three-dimensional digital geological model of the original seabed is established using three-dimensional geological analysis software.

[0017] Step S12: Divide the backfill site into zones according to the construction organization design requirements, determine the unit size of each zone, extract the geological survey data at the center of each area on the three-dimensional digital geological model, and determine the soil layer distribution characteristic values ​​of each zone.

[0018] Step S13: Based on the soil layer distribution at the center of each area, the predicted backfill volume V for each area to reach the design intersection elevation is predicted by using the layered summation method and the settlement theory calculation method based on the soil compression characteristics under one-dimensional consolidation lateral stress state. i .

[0019] Preferably, in step S13, the predicted backfill volume V i The calculation formula is as follows:

[0020] V i =A i ·h i ;

[0021] h i =S i ·h i0i ;

[0022]

[0023] In the formula, V i Let A be the predicted amount of crushed stone for backfilling in the i-th partition. i h is the area of ​​the i-th partition. i Let S be the predicted backfill elevation for the i-th partition. i h represents the total consolidation settlement within the i-th partition. 0i Let m be the design height of the i-th partition. s For empirical coefficients, ΔS di,j Let e ​​be the settlement of the j-th soil layer within the i-th partition. 0i,j Let e ​​be the design value of the porosity of the j-th layer within the i-th partition when it reaches compressive stability under the design value of average self-weight pressure. 1i,j h is the design value of the porosity ratio of the j-th layer within the i-th partition when it reaches compressive stability under the average final pressure design value. i,j Let be the average thickness of the j-th layer of soil in the i-th partition.

[0024] Preferably, in step S2, establishing monitoring points and using wireless monitoring methods to monitor the surface settlement of each zone includes:

[0025] After construction begins, settlement monitoring points will be set up on site to form a monitoring network covering the entire construction area, including monitoring sensors and wireless data acquisition base stations, with no fewer than 9 monitoring points in each zone;

[0026] Magnetic rings are set up at the top elevation of each soil layer as determined by the stratigraphic exploration report, and numbered from 01 down along the depth direction. Layered settlement data of each soil layer are collected through the magnetic rings.

[0027] The monitoring sensors collect topographic points, geological borehole planar information, and boundary ranges for subsequent settlement calculations from the magnetic ring at a fixed frequency. The data is then wirelessly transmitted to the intelligent data acquisition base station at a certain frequency.

[0028] The intelligent data acquisition base station transmits data to the digital monitoring platform via 4G / 5G for automated data processing;

[0029] in,

[0030] The monitoring points collect continuous data on surface subsidence. Once the subsidence value is less than 1.5 mm / d for several consecutive days, it indicates that the subsidence is stable, the original seabed soft soil has been consolidated, and the backfilling construction process is completed.

[0031] Automated data processing includes data noise reduction, data integration, identification and removal of abnormal data.

[0032] Preferably, in step S5, when ΔV i When ΔV is positive, it indicates that excess gravel needs to be removed. i A negative value indicates that excess gravel needs to be added.

[0033] Preferably, in step S6, the dataset and coordinate set expressions for establishing the crushed stone quantity scheduling are as follows:

[0034] A={ΔV i ,ΔV j ,ΔV k ,...,ΔV n};

[0035] B={ΔV α ,ΔV β ,ΔV γ ,...,ΔV m};

[0036] a={(x i ,y i ),(x j ,y j ),(x k ,y k ),...,(x n ,y n )};

[0037] b = {(x α ,y α ),(x β ,y β ),(x γ ,y γ ),...,(x ω ,y ω )};

[0038] In the formula, A is the dataset of the missing square region, B is the dataset of the surplus square region, a is the coordinate set of the missing square region, and b is the coordinate set of the surplus square region.

[0039] Preferably, in step S6, the ant colony algorithm iteratively searches the solution space to obtain the optimal path and maximum reasonable allocation amount for the transport of crushed stone within the entire neighborhood, including:

[0040] Step S61: Initialize the relevant parameters;

[0041] Step S62: Import the required data into the program, perform preliminary processing and analysis on the data, and convert the coordinate positions of each partition into a regional coordinate matrix;

[0042] Step S63: Randomly deploy the vehicles at the initial starting point, and for each vehicle, use a specific algorithm to calculate the next area it should visit;

[0043] Step S64: After each visit, update the pheromone table according to preset rules to reflect the current route selection of the transportation vehicle. Continue to iterate the above steps until all transportation vehicles have completed the visit to all partitions.

[0044] Step S65: The total length of the path traveled by each vehicle is calculated and used as one of the performance evaluation indicators. In each iteration, the optimal solution under the current iteration number is recorded, that is, the transportation scheme with the shortest path length.

[0045] In step S66, the pheromone concentration on the connecting paths of each partition was dynamically updated based on the actual route selection of the transportation vehicles.

[0046] Step S67: Determine whether the maximum number of iterations has been reached. If not, return to step S63; otherwise, terminate the program.

[0047] Step S68: Output the program criteria as the result and output the relevant indicators in the program optimization process as needed.

[0048] Preferably, in step S61, the relevant parameters include the initial size of the transportation vehicle, the pheromone constant, the pheromone factor, the volatile factor, and the maximum number of iterations.

[0049] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention takes the enclosed area divided by the construction organization design as the object, and uses the monitoring data within the area as the basis. Through the algorithm built into the monitoring platform, it compares the predicted values ​​of the area elevation derived from the monitoring data with the design values ​​to calculate the actual amount of crushed stone used in the newly formed land area at the time of handover. Based on the shortage and surplus of different areas, it adjusts the backfill crushed stone within the site, which has the advantages of real-time analysis and parameter feedback. This method takes into account the differences in the actual consolidation settlement due to the different soil conditions in different areas within a large area of ​​land reclamation. The proposed three-dimensional geological model dynamic correction method can quantitatively predict the changing trend of the actual crushed stone demand within the area. This method can effectively reduce the amount of crushed stone redundancy and can also provide data and technical support for the adjustment of measures, resource scheduling, and scientific research analysis during the land reclamation construction process. Attached Figure Description

[0050] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0051] Figure 1 This is a flowchart of an optimized method for backfill crushed stone transportation based on a monitoring platform according to the present invention;

[0052] Figure 2 This is a flowchart in the present invention for predicting the backfill volume for each zone to reach the design intersection elevation;

[0053] Figure 3 This is a flowchart of the process in this invention that uses the ant colony algorithm to iteratively search the solution space and obtain the optimal path and maximum reasonable allocation of crushed stone transportation within the entire neighborhood.

[0054] Figure 4 This is a flowchart of the ant colony algorithm for searching the optimal solution space in this invention;

[0055] Figure 5 This is a schematic diagram of the partitioned transportation in this invention. Detailed Implementation

[0056] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] Traditional methods of transporting crushed stone in land reclamation areas are conservatively designed, resulting in excessive use of crushed stone, which wastes resources and increases the burden and cost of material transportation within the site.

[0058] The method of the present invention is configured in a three-level data transmission architecture, including:

[0059] Terminal layer: The monitoring points are networked using the LoRaWAN protocol, while ensuring data integrity;

[0060] Relay layer: The on-site intelligent base station integrates 4G / 5G communication technology and uses the MQTT protocol to achieve data management;

[0061] Monitoring platform layer: A data filtering engine is deployed on the cloud server to remove outliers and form a time series dataset.

[0062] The specific implementation process is as follows:

[0063] like Figure 1 As shown, a method for optimizing the transportation of backfill crushed stone based on a monitoring platform includes:

[0064] Step S1: Establish a three-dimensional digital geological model of the site, divide the site into backfill zones, extract geological stratification data at the center of each zone, and predict the backfill volume V for each zone to reach the design intersection elevation by using the layered summation method based on the soil compression characteristics under one-dimensional consolidation lateral stress state and the settlement theory calculation method. i .

[0065] like Figure 2 As shown, step S1 includes:

[0066] Step S11: Using the topographic surface, borehole, geophysical topographic and geological data collected during the geological exploration phase, a three-dimensional digital geological model of the original seabed is established using three-dimensional geological analysis software.

[0067] Step S12: Divide the backfill site into zones according to the construction organization design requirements, determine the unit size of each zone, extract the geological survey data at the center of each area on the three-dimensional digital geological model, and determine the soil layer distribution characteristic values ​​of each zone.

[0068] Step S13: Based on the soil layer distribution at the center of each area, the predicted backfill volume V for each area to reach the design intersection elevation is predicted by using the layered summation method and the settlement theory calculation method based on the soil compression characteristics under one-dimensional consolidation lateral stress state. i .

[0069] In the example, the predicted backfill volume V i The calculation formula is as follows:

[0070] V i =A i ·h i ;

[0071] hi =S i ·h 0i ;

[0072]

[0073] In the formula, V i Let A be the predicted amount of crushed stone for backfilling in the i-th partition. i h is the area of ​​the i-th partition. i Let S be the predicted backfill elevation for the i-th partition. i h represents the total consolidation settlement within the i-th partition. 0i Let m be the design height of the i-th partition. s For empirical coefficients, ΔS di,j Let e ​​be the settlement of the j-th soil layer within the i-th partition. 0i,j Let e ​​be the design value of the porosity of the j-th layer within the i-th partition when it reaches compressive stability under the design value of average self-weight pressure. 1i,j h is the design value of the porosity ratio of the j-th layer within the i-th partition when it reaches compressive stability under the average final pressure design value. i,j Let be the average thickness of the j-th layer of soil in the i-th partition.

[0074] In this embodiment, the monitoring platform predicts the actual amount of backfilled crushed stone to reach the handover elevation based on soil parameters and real-time collected monitoring data, as well as measured settlement data during the three-month period from crushed stone backfilling construction to stabilization in each zone, using a settlement prediction method.

[0075] Step S2: Establish monitoring points and use wireless monitoring methods to monitor the surface settlement of each zone. Import real-time data into the monitoring platform through 4G / 5G wireless sensing technology.

[0076] In this embodiment, monitoring points are established, and wireless monitoring methods are used to monitor the surface settlement of each zone, including:

[0077] After construction begins, settlement monitoring points will be set up on site to form a monitoring network covering the entire construction area, including monitoring sensors and wireless data acquisition base stations, with no fewer than 9 monitoring points in each zone;

[0078] Magnetic rings are set up at the top elevation of each soil layer as determined by the stratigraphic exploration report, and numbered from 01 down along the depth direction. Layered settlement data of each soil layer are collected through the magnetic rings.

[0079] The monitoring sensors collect topographic points, geological borehole planar information, and boundary ranges for subsequent settlement calculations from the magnetic ring at a fixed frequency. The data is then wirelessly transmitted to the intelligent data acquisition base station at a certain frequency.

[0080] The intelligent data acquisition base station transmits data to the digital monitoring platform via 4G / 5G for automated data processing;

[0081] in,

[0082] The monitoring points collect continuous data on surface subsidence. Once the subsidence value is less than 1.5 mm / d for several consecutive days, it indicates that the subsidence is stable, the original seabed soft soil has been consolidated, and the backfilling construction process is completed.

[0083] Automated data processing includes data noise reduction, data integration, identification and removal of abnormal data.

[0084] Step S3: The monitoring platform performs Denaulay triangulation on the entire monitoring range to generate a three-dimensional model mesh, and uses Kriging interpolation technology to generate thermal cloud maps W of settlement amount for each zone from the real-time monitoring information obtained by the surface monitoring sensors. s The surface elevation of each zone was adjusted by measuring the settlement, and a thermal cloud map W of the actual elevation was generated by inverse distance interpolation. r,i This allows for the visualization of dynamic adjustment of the surface elevation.

[0085] Step S4: Generate a heat map W of the design elevation based on the design intersection elevation. d,i , surface thermal cloud map W r,i Thermal cloud map of design elevation W d,i Perform 3D mesh registration.

[0086] In the embodiment, a hybrid interpolation model considering the coefficient of variation of geological parameters is used, when the coefficient of variation C V When the coefficient of variation C is relatively small, the ordinary kriging method is used. V When the size is large, the anisotropic inverse distance weighting method is used to establish a refined 3D model mesh and perform 3D mesh registration.

[0087] Step S5: Compare the actual elevation heat map W within each zone. r,i Thermal cloud map of design elevation W d,i It automatically calculates the predicted actual elevation heat map W within each zone. r,i Thermal cloud map of design elevation W d,i The difference in the amount of crushed stone between them ΔV i Determine the amount of fill or excavation within each zone; a zone-based transportation diagram is shown below. Figure 5 As shown, ○ represents the filling area, × represents the excavation area, and → represents the transportation direction.

[0088] In the embodiment, when ΔV i When ΔV is positive, it indicates that excess gravel needs to be removed. i A negative value indicates that excess gravel needs to be added.

[0089] Step S6: Calculate the difference in gravel volume ΔV between each zone using the monitoring platform. i A dataset and coordinate set for crushed stone scheduling are established. The monitoring platform establishes a coordinate set based on the coordinate positions of the center of each partition in the two datasets, which is used for optimal path analysis of crushed stone scheduling.

[0090] In this embodiment, the dataset and coordinate set expressions for establishing the crushed stone quantity scheduling are as follows:

[0091] A={ΔV i ,ΔV j ,ΔV k ,...,ΔV n};

[0092] B={ΔV α ,ΔV β ,ΔV γ ,...,ΔV m};

[0093] a={(x i ,y i ),(x j ,y j ),(x k ,y k ),...,(x n ,y n )};

[0094] b={(x α ,y α ),(x β ,y β ),(x γ ,y γ ),...,(x ω ,y ω )};

[0095] In the formula, A is the dataset of the missing square region, B is the dataset of the surplus square region, a is the coordinate set of the missing square region, and b is the coordinate set of the surplus square region.

[0096] In the embodiment, when ΔV i >+5%V i The time marker is designated as the coexisting square region (Class A partition), when ΔV i <-5% V i The time marker is designated as a missing square area (Class B partition).

[0097] like Figure 3 , 4 As shown, by iteratively searching the solution space using the ant colony algorithm, the optimal path and maximum reasonable allocation of crushed stone within the entire neighborhood are obtained, including:

[0098] Step S61: Initialize the relevant parameters, including the initial size of the transportation vehicle, pheromone constant, pheromone factor, evaporation factor, and maximum number of iterations.

[0099] Step S62: Import the required data into the program, perform preliminary processing and analysis on the data, and convert the coordinate positions of each partition into a regional coordinate matrix;

[0100] Step S63: Randomly deploy the vehicles at the initial starting point, and for each vehicle, use a specific algorithm to calculate the next area it should visit;

[0101] Step S64: After each visit, update the pheromone table according to preset rules to reflect the current route selection of the transportation vehicle. Continue to iterate the above steps until all transportation vehicles have completed the visit to all partitions.

[0102] Step S65: The total length of the path traveled by each vehicle is calculated and used as one of the performance evaluation indicators. In each iteration, the optimal solution under the current iteration number is recorded, that is, the transportation scheme with the shortest path length.

[0103] In step S66, the pheromone concentration on the connecting paths of each partition was dynamically updated based on the actual route selection of the transportation vehicles.

[0104] Step S67: Determine whether the maximum number of iterations has been reached. If not, return to step S63; otherwise, terminate the program.

[0105] Step S68: Output the program criteria as the result and output the relevant indicators in the program optimization process as needed.

[0106] Step S7: The monitoring platform visualizes the crushed stone transportation information. The monitoring screen displays the crushed stone transportation route information, transportation time and maximum single transportation volume in real time. Based on the above information, the platform calculates the total amount of crushed stone redundancy in the enclosure area after the crushed stone scheduling is completed, and calculates the comprehensive utilization rate of crushed stone, thereby realizing the function of optimizing the crushed stone scheduling of the backfill site.

[0107] Finally, it should be noted that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for optimizing the transportation of backfill crushed stone based on a monitoring platform, characterized in that, include: Step S1: Establish a three-dimensional digital geological model of the site, divide the site into backfill zones, extract geological stratification data at the center of each zone, and predict the backfill volume V for each zone to reach the design intersection elevation by using the layered summation method based on the soil compression characteristics under one-dimensional consolidation lateral stress state and the settlement theory calculation method. i ; Step S2: Establish monitoring points and use wireless monitoring methods to monitor the surface settlement of each zone. Import real-time data into the monitoring platform through 4G / 5G wireless sensing technology. Step S3: The monitoring platform performs Denaulay triangulation on the entire monitoring range to generate a three-dimensional model mesh, and uses Kriging interpolation technology to generate thermal cloud maps W of settlement amount for each zone from the real-time monitoring information obtained by the surface monitoring sensors. s The surface elevation of each zone was adjusted by measuring the settlement, and a thermal cloud map W of the actual elevation was generated by inverse distance interpolation. r,i This enables the visualization of dynamic adjustment of surface elevation; Step S4: The monitoring platform can generate a thermal cloud map W of the design elevation based on the design intersection elevation. d,i The actual elevation heat map W r,i Thermal cloud map of design elevation W d,i Perform 3D mesh registration; Step S5: Automatically calculate the predicted actual elevation thermal cloud map W for each zone after the original seabed soft soil consolidation is completed using the settlement prediction method. r,i Compare the actual elevation heat map W in each zone r,i Thermal cloud map of design elevation W d,i The volume difference ΔV between the two is obtained. i This is the difference in the amount of crushed stone, which determines the amount of fill or excavation in each zone. Step S6: Calculate the difference in gravel volume ΔV between each zone using the monitoring platform. i Establish a dataset and coordinate set for crushed stone quantity scheduling. The monitoring platform establishes a coordinate set based on the coordinate positions of the center of each partition in the two datasets, which is used for optimal path analysis of crushed stone scheduling. In step S7, the monitoring platform visualizes the crushed stone transportation information. The monitoring screen displays the crushed stone transportation route information, transportation time, and maximum single transportation volume in real time, and calculates the comprehensive utilization rate of crushed stone.

2. The method for optimizing the transportation of backfill crushed stone based on a monitoring platform according to claim 1, characterized in that, Step S1 includes: Step S11: Using the topographic surface, borehole, geophysical topographic and geological data collected during the geological exploration stage, a three-dimensional digital geological model of the original seabed is established using three-dimensional geological analysis software. Step S12: Divide the backfill site into zones according to the construction organization design requirements, determine the unit size of each zone, extract the geological survey data at the center of each area on the three-dimensional digital geological model, and determine the soil layer distribution characteristic values ​​of each zone. Step S13: Based on the soil layer distribution at the center of each area, the predicted backfill volume V for each area to reach the design intersection elevation is predicted by using the layered summation method and the settlement theory calculation method based on the soil compression characteristics under one-dimensional consolidation lateral stress state. i .

3. The method for optimizing the transportation of backfill crushed stone based on a monitoring platform according to claim 2, characterized in that, In step S13, the predicted backfill volume V i The calculation formula is as follows: In i =A i ·h i ; h i =S i ·h 0i ; In the formula, V i Let A be the predicted amount of crushed stone for backfilling in the i-th partition. i h is the area of ​​the i-th partition. i Let S be the predicted backfill elevation for the i-th partition. i h represents the total consolidation settlement within the i-th partition. 0i Let m be the design height of the i-th partition. s For empirical coefficients, ΔS di,j Let e ​​be the settlement of the j-th soil layer within the i-th partition. 0i,j Let e ​​be the design value of the porosity of the j-th layer within the i-th partition when it reaches compressive stability under the design value of average self-weight pressure. 1i,j h is the design value of the porosity ratio of the j-th layer within the i-th partition when it reaches compressive stability under the average final pressure design value. i,j Let be the average thickness of the j-th layer of soil in the i-th partition.

4. The method for optimizing the transportation of backfill crushed stone based on a monitoring platform according to claim 1, characterized in that, In step S2, monitoring points are established, and wireless monitoring methods are used to monitor the surface settlement of each zone, including: After construction begins, settlement monitoring points will be set up on site to form a monitoring network covering the entire construction area, including monitoring sensors and wireless data acquisition base stations, with no fewer than 9 monitoring points in each zone; Magnetic rings are set up at the top elevation of each soil layer as determined by the stratigraphic exploration report, and numbered from 01 down along the depth direction. Layered settlement data of each soil layer are collected through the magnetic rings. The monitoring sensors collect topographic points, geological borehole planar information, and boundary ranges for subsequent settlement calculations from the magnetic ring at a fixed frequency. The data is then wirelessly transmitted to the intelligent data acquisition base station at a certain frequency. The intelligent data acquisition base station transmits data to the digital monitoring platform via 4G / 5G for automated data processing; in, The monitoring points collect continuous data on surface subsidence. Once the subsidence value is less than 1.5 mm / d for several consecutive days, it indicates that the subsidence is stable, the original seabed soft soil has been consolidated, and the backfilling construction process is completed. Automated data processing includes data noise reduction, data integration, identification and removal of abnormal data.

5. The method for optimizing the transportation of backfill crushed stone based on a monitoring platform according to claim 1, characterized in that, In step S5, when ΔV i When ΔV is positive, it indicates that excess gravel needs to be removed. i A negative value indicates that excess gravel needs to be added.

6. The method for optimizing the transportation of backfill crushed stone based on a monitoring platform according to claim 1, characterized in that, In step S6, the dataset and coordinate set expressions for establishing the crushed stone quantity scheduling are as follows: A={ΔV i ,ΔV j ,ΔV k ,...,ΔV n }; B={ΔV α ,ΔV β ,ΔV γ ,...,ΔV m }; a={(x i ,and i ),(x j ,and j ),(x k ,and k ),...,(x n ,and n )}; b={(x α ,and α ),(x β ,and β ),(x γ ,and γ ),...,(x ω ,and ω )}; In the formula, A is the dataset of the missing square region, B is the dataset of the surplus square region, a is the coordinate set of the missing square region, and b is the coordinate set of the surplus square region.

7. The method for optimizing the transportation of backfill crushed stone based on a monitoring platform according to claim 1, characterized in that, In step S6, the ant colony algorithm iteratively searches the solution space to obtain the optimal path and maximum reasonable allocation amount for the transport of crushed stone within the entire neighborhood, including: Step S61: Initialize the relevant parameters; Step S62: Import the required data into the program, perform preliminary processing and analysis on the data, and convert the coordinate positions of each partition into a regional coordinate matrix; Step S63: Randomly deploy the vehicles at the initial starting point, and for each vehicle, use a specific algorithm to calculate the next area it should visit; Step S64: After each visit, update the pheromone table according to preset rules to reflect the current route selection of the transportation vehicle. Continue to iterate the above steps until all transportation vehicles have completed the visit to all partitions. Step S65: The total length of the path traveled by each vehicle is calculated and used as one of the performance evaluation indicators. In each iteration, the optimal solution under the current iteration number is recorded, that is, the transportation scheme with the shortest path length. In step S66, the pheromone concentration on the connecting paths of each partition was dynamically updated based on the actual route selection of the transportation vehicles. Step S67: Determine whether the maximum number of iterations has been reached. If not, return to step S63; otherwise, terminate the program. Step S68: Output the program criteria as the result and output the relevant indicators in the program optimization process as needed.

8. The method for optimizing the transportation of backfill crushed stone based on a monitoring platform according to claim 7, characterized in that, In step S61, the relevant parameters include the initial size of the transportation vehicle, the pheromone constant, the pheromone factor, the volatile factor, and the maximum number of iterations.

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