Submarine geological parameter fused photovoltaic foundation construction resource allocation method

Abstract

The invention relates to the technical field of marine geological engineering, in particular to a submarine geological parameter fused photovoltaic foundation construction resource allocation method which comprises the following steps: collecting submarine topographic data, rock-soil physical parameters and stratum bearing capacity parameters through a shipborne multi-beam sounding system, a submarine drilling sampling device and a static penetrometer; uniformly mapping various parameters to a three-dimensional geographic coordinate system, and constructing a standardized geological data cube; the stratum shear wave velocity, the standard penetration impact number and the water content are extracted, and a comprehensive geological rigidity index is calculated through fusion; according to index threshold values, three types of construction units of a hard rock area, a transition area and a soft soil area are divided, and a hydraulic impact hammer, a rotary drilling rig and a vibration pile sinking unit are matched; and when monitoring that the geological variation exceeds a set amplitude, automatically adjusting the configuration of equipment in an adjacent area, and generating a dynamic resource allocation scheme. According to the invention, precise configuration and intelligent scheduling of equipment under geological driving can be realized, and the efficiency and safety of submarine photovoltaic foundation construction are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of marine geology engineering, and particularly relates to a photovoltaic foundation construction resource allocation method based on fusion of seabed geological parameters. BACKGROUND

[0002] As a new energy utilization form with renewable and spatial expansion potential, offshore photovoltaic is becoming a key direction of coastal and offshore energy infrastructure construction. In the process of seabed photovoltaic foundation construction, the selection of construction equipment and resource allocation are highly dependent on the geological conditions of the target sea area. In order to ensure the stability and safety of pile foundation installation, it is often necessary to obtain key information such as topographic data, geotechnical physical parameters and stratum bearing capacity parameters of the seabed, and to divide the region and configure the construction equipment accordingly.

[0003] At present, the equipment configuration in photovoltaic foundation construction is mostly based on static survey data and artificial experience, which has the following problems: first, there is a lack of unified data standard and spatial model, making it difficult to fuse multiple geological parameters and form continuous and stable geological index maps; second, the construction area division is often simplified by single parameter or contour line, which cannot reflect the comprehensive influence of multiple indicators, and is easy to cause unbalanced equipment configuration; third, the existing resource allocation strategy is mostly one-time static configuration, which lacks real-time response ability to dynamic changes of geological conditions during construction, and cannot adjust and optimize the unit when the geological conditions change suddenly, which is easy to cause the decline of construction efficiency and even engineering risk. SUMMARY

[0004] The present application provides a photovoltaic foundation construction resource allocation method based on fusion of seabed geological parameters, which is an intelligent resource allocation method that can fuse multi-source geological information, has rigidity quantitative evaluation ability and can dynamically respond to geological changes.

[0005] The photovoltaic foundation construction resource allocation method based on fusion of seabed geological parameters comprises the following steps: S1: synchronously obtaining seabed topographic data, geotechnical physical parameters and stratum bearing capacity parameters of the construction sea area by a shipborne multi-beam sounding system, a seabed drilling sampling device and a static sounding device; S2: mapping each parameter in S1 to a three-dimensional geographic coordinate system to generate a standardized geological data cube with a time stamp; S3: extracting stratum shear wave velocity, standard penetration number and water content in the standardized geological data cube, and generating a comprehensive geological rigidity index of each grid cell by a weighted fusion algorithm; S4: dividing the construction sea area into three types of geological construction units, i.e. hard rock area, transition area and soft soil area, according to the comprehensive geological rigidity index threshold; S5: Assign hydraulic impact hammer units to hard rock areas, assign vibrating pile driving units to soft soil areas, and assign rotary drilling units to transition areas to form an initial equipment allocation scheme; S6: When the real-time monitoring of the comprehensive geological stiffness index of a unit changes by more than ± 15%, trigger the adjacent area equipment scheduling instruction and update the dynamic resource allocation scheme.

[0006] Optionally, the S1 comprises: S11: Perform full-coverage scanning along the planned survey line by the ship-borne multi-beam sounding system, collect raw seafloor topography point cloud data, and output seafloor topography data after coordinate calculation and tide correction; S12: Obtain core samples at preset grid nodes by the seafloor drilling sampling device, perform density testing, particle analysis, and mineral composition detection on the core samples, and generate geotechnical physical parameters including porosity, saturation, and permeability coefficient; S13: Perform penetration testing at adjacent positions of the seafloor drilling sampling device by the static cone penetration tester, record the cone tip resistance curve and sidewall friction resistance curve in real time, and extract the stratum bearing capacity parameter after depth normalization processing; S14: Synchronize the timestamps and spatial coordinates of the seafloor topography data, geotechnical physical parameters, and stratum bearing capacity parameters to form a spatiotemporally aligned original parameter set.

[0007] Optionally, the S2 comprises: S21: Convert the seafloor topography data, geotechnical physical parameters, and stratum bearing capacity parameters in the spatiotemporally aligned original parameter set to the WGS-84 three-dimensional geographic coordinate system, and generate seafloor topography grid data, geotechnical physical parameter grid data, and stratum bearing capacity parameter grid data with coordinate labels; S22: Perform dimensionless processing on the seafloor topography grid data, geotechnical physical parameter grid data, and stratum bearing capacity parameter grid data, respectively, to output standardized seafloor topography data, standardized geotechnical physical parameters, and standardized stratum bearing capacity parameters; S23: Temporally and spatially match the standardized seafloor topography data, standardized geotechnical physical parameters, and standardized stratum bearing capacity parameters according to the same spatial grid unit, embed the timestamps recorded in S14, and construct a standardized geological data cube including spatial coordinates, timestamps, and multi-dimensional geological attributes.

[0008] Optionally, the dimensionless processing on the seafloor topography grid data, geotechnical physical parameter grid data, and stratum bearing capacity parameter grid data comprises: The seafloor topography grid data adopts elevation normalization method to output standardized seafloor topography data; The geotechnical physical parameter grid data adopts range standardization method to output standardized geotechnical physical parameters; The Z-score method is used to normalize the grid data of the formation bearing capacity parameters, and the standardized formation bearing capacity parameters are output.

[0009] Optionally, the S3 includes: S31: Extract three geological parameters, namely, standardized formation shear wave velocity, standardized standard penetration number, and standardized water content, from the standardized geological data cube according to spatial grid cells; S32: Configure preset weight coefficients for the standardized formation shear wave velocity, standardized SPF number, and standardized water content, respectively, and construct a calculation framework for the weighted fusion algorithm. Specifically: Normalized formation shear wave velocity weight coefficient (0.45≤ ≤0.55); Standardized SPF weight coefficient (0.25≤ ≤0.35); Normalized moisture content weight coefficient (0.15≤ ≤0.25); Satisfy the constraints: ; S33: Calculate the comprehensive geological stiffness index through a weighted fusion algorithm to generate a comprehensive geological stiffness index numerical matrix for each grid cell.

[0010] Optionally, the comprehensive geological stiffness index is calculated as: ; in, For the The comprehensive geological stiffness index of the grid cell, is the normalized formation shear wave velocity, N is the normalized standard penetration number, and w is the normalized water content.

[0011] Optionally, the S4 includes: S41: Set the threshold range of the comprehensive geological stiffness index, specifically: Hard rock area demarcation threshold: comprehensive geological stiffness index ≥ upper threshold; Soft soil area demarcation threshold: comprehensive geological stiffness index ≤ lower threshold; Transition zone demarcation threshold: lower threshold < comprehensive geological stiffness index < upper threshold; The upper limit of the threshold is 0.8 times the maximum value of the comprehensive geological stiffness index numerical matrix, and the lower limit of the threshold is 1.2 times the minimum value of the comprehensive geological stiffness index numerical matrix.

[0012] S42: Traverse each grid cell of the comprehensive geological stiffness index numerical matrix and perform geological type determination: When the unit value ≥ upper threshold, mark as hard rock area; When the unit value ≤ lower threshold, mark as soft soil area; When lower threshold < unit value < upper threshold, mark as transition area; Output the geological construction unit type identification matrix with spatial coordinates.

[0013] S43: Perform spatial clustering processing on the geological construction unit type identification matrix, including merging adjacent grid cells of the same type and removing isolated cells with an area less than 50 m², to generate a spatial distribution map of the three types of geological construction units: hard rock area, transition area, and soft soil area.

[0014] Optionally, the S5 includes: S51: Calculate the total area of the hard rock area according to the hard rock area spatial distribution map, and configure the number of hydraulic impact hammer units according to the unit area construction efficiency; S52: Calculate the total area of the soft soil area according to the soft soil area spatial distribution map, and configure the number of vibration pile driving units according to the unit area construction efficiency; S53: Calculate the total area of the transition area according to the transition area spatial distribution map, and configure the number of rotary drilling rigs according to the unit area construction efficiency; S54: Generate an initial equipment allocation scheme, including: Hard rock area deployment scheme: hydraulic impact hammer unit number and corresponding construction grid coordinate set; Soft soil area deployment scheme: vibration pile driving unit number and corresponding construction grid coordinate set; Transition area deployment scheme: rotary drilling rig unit number and corresponding construction grid coordinate set; Equipment scheduling list: total number of hydraulic impact hammer units, total number of vibration pile driving units, and total number of rotary drilling rigs.

[0015] Optionally, the S6 includes: S61: Real-time monitor the standardized geological data cube update data, and when the change amplitude of the comprehensive geological stiffness index of a certain grid cell relative to the initial value exceeds ±15%, mark the cell as a geological variation cell, and extract its spatial coordinates and the comprehensive geological stiffness index after variation; S62: Define the adjacent area as a 3x3 grid range extending from the center of the geological variation cell, and generate adjacent area equipment scheduling instructions: When the increase amplitude of the comprehensive geological stiffness index after variation ≥15%, issue a conversion instruction for the rotary drilling rig units in the adjacent area to the hydraulic impact hammer units; When the decrease amplitude of the comprehensive geological stiffness index after variation ≥15%, issue a conversion instruction for the hydraulic impact hammer units in the adjacent area to the vibration pile driving units; When the variation amplitude is within ±15%, maintain the current equipment configuration; S63: updating the equipment deployment scheme according to the adjacent area equipment scheduling instruction, including: unbinding the original unit in the construction grid of the variation unit and the adjacent area; reassigning the unit type according to the instruction type of S62; correcting the unit quantity distribution in the equipment scheduling list; generating a dynamic resource allocation scheme including a new construction grid coordinate set.

[0016] The beneficial effects of the present application are: The present application jointly collects seabed topographic data, geotechnical physical parameters and stratum bearing capacity parameters through a ship-borne multi-beam sounding system, a seabed drilling and sampling device and a static sounding device, and models through a WGS-84 three-dimensional geographic coordinate system to construct a standardized geological data cube. By using various dimensionless processing methods such as elevation normalization, range standardization and Z-score standardization, different physical quantities are made comparable, and spatial alignment and time synchronization are achieved, greatly improving the comprehensive expression ability of geological data and the accuracy of downstream calculation, effectively supporting the intelligent decision-making of subsequent regional division and equipment allocation.

[0017] The present application fuses three key geological indexes of stratum shear wave velocity, standard penetration number and water content, and calculates a comprehensive geological stiffness index using a weighted fusion algorithm, which can accurately reflect the rigidity strength and construction difficulty difference of each grid unit. On this basis, the system dynamically sets the classification threshold of hard rock area, transition area and soft soil area according to the index value, realizes intelligent zoning of the construction area, and matches different types of construction equipment (hydraulic impact hammer unit, rotary drilling rig unit, vibration pile hammer unit). Compared with the traditional manual experience division method, this mechanism is more scientific and objective, and can effectively reduce the energy waste and construction error caused by improper equipment selection.

[0018] The present application introduces a dynamic resource allocation mechanism, and monitors the change of geological parameters in real time. When the comprehensive geological stiffness index fluctuates by more than ± 15% compared with the initial state, the geological variation unit is automatically identified and the adjacent area is defined with it as the center, and the construction equipment type switching instruction is intelligently issued. Through the dynamic switching of equipment type, the updating of construction grid binding relationship and the reconstruction of scheduling list, the closed-loop optimization response of equipment configuration is realized. This mechanism has the advantages of strong adaptability, high resource utilization rate and low demand for on-site intervention, and can continuously guarantee the effectiveness and stability of the construction scheme in complex seabed geological environment. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only a part of the present application, and other drawings can also be obtained by those skilled in the art without any creative effort.

[0020] Fig. 1 The method flowchart of the embodiment of the present application is shown in the figure. Fig. 2 The S1 flowchart of the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0021] The present application will be described in detail below with reference to the drawings and specific embodiments. It should be noted that, in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and other alternative ways can also be used by those skilled in the art to implement some known technologies; and the drawings are only used to more specifically describe the embodiments, and are not intended to specifically limit the present application.

[0022] As shown in the figure, Figs. 1-2 The seabed geological parameter fusion photovoltaic foundation construction resource allocation method comprises the following steps: S1: The seabed topographic data, rock-soil physical parameters and stratum bearing capacity parameters of the construction sea area are synchronously obtained by a shipborne multi-beam sounding system, a seabed drilling sampling device and a static sounding device, specifically: S11, seabed topographic data acquisition and processing: the shipborne multi-beam sounding system arranged on the bottom of the survey ship is used to perform full-coverage scanning on the construction sea area according to a preset survey line scheme. The survey line spacing is set to 10-30 meters according to the required resolution.

[0023] During the scanning process, the water depth data and the ship heading, roll and pitch angles output by the attitude sensor are synchronously recorded, and the three-dimensional spatial coordinates of each survey point are obtained in combination with the RTK-GPS positioning system.

[0024] The obtained original seabed topographic point cloud data is processed by the following processing flow to generate standardized seabed topographic data: Coordinate calculation: the survey point geographic coordinates are uniformly converted to a three-dimensional geographic coordinate system (WGS84-ECEF).

[0025] Tide correction: the tide level data measured by a nearby tide observation station are used for tide correction to eliminate the depth deviation affected by the tide change.

[0026] Grid interpolation: a Kriging or bilinear interpolation algorithm is used to construct a regular grid seabed topographic surface model.

[0027] S12, Geotechnical Physical Parameter Acquisition: Based on the seabed topography data output in S11, sample grid nodes of seabed drilling sampling devices are arranged according to the equidistance rule, and the recommended grid spacing is 100 meters. Core samples are vertically drilled at each predetermined grid node, and the drilling depth is generally controlled at 10-20 meters.

[0028] The following tests are carried out on the obtained core samples in the laboratory: Density Test: The natural density and dry density are measured using the Archimedes method.

[0029] Particle Analysis: Laser particle size analyzer is used to determine the particle size distribution and distinguish the proportion of sand, silt and clay.

[0030] Mineral Composition Detection: The main mineral component ratio is analyzed by X-ray diffraction instrument.

[0031] Through the above detection, the geotechnical physical parameters of each grid point core are generated, including porosity, saturation, and permeability coefficient.

[0032] S13, Stratum Bearing Capacity Parameter Extraction: In the range of about 2-3 meters adjacent to each seabed drilling sampling device arranged in S12, a static cone penetrometer is arranged to carry out in-situ penetration test, with a penetration depth of 10 meters and a penetration speed controlled at 20 mm / s.

[0033] The following curve data are recorded in real time: cone tip resistance curve, side wall friction resistance curve, and the curve data are normalized according to the penetration depth to output standardized profile data.

[0034] The stratum bearing capacity parameters are calculated, including unconsolidated shear strength and bearing ratio (specific penetration resistance).

[0035] The unconsolidated shear strength is calculated as: ; wherein, is the cone tip resistance, is the total vertical stress, is the resistance coefficient, usually with a value range of 15-20 (recommended value for clayey deposits is 18); Bearing ratio (specific penetration resistance) Conversion: Then the Terzaqhi or Meyerhof formula is used to estimate the ultimate bearing capacity, or for foundation bearing capacity classification.

[0036] S14, Original Parameter Set Construction: The seabed topography data, geotechnical physical parameters and stratum bearing capacity parameters output in the above sub-steps are respectively associated with their sampling time and three-dimensional spatial coordinates to construct a unified parameter structure.

[0037] Each data entry structure is: ; wherein, is a three-dimensional spatial coordinate, is a sampling timestamp, is a water depth, is a rock density, is a porosity, is a saturation, is a tip resistance, is a side friction resistance, is an unconsolidated shear strength.

[0038] Finally, a set of spatio-temporally aligned original parameter sets are formed, providing basic data support for three-dimensional standardized modeling and comprehensive geological stiffness index calculation in subsequent steps.

[0039] S2: mapping each parameter in S1 to a three-dimensional geographic coordinate system to generate a standardized geological data cube with a timestamp, specifically: S21, geographic coordinate system conversion and spatial gridding: projecting and gridding each type of data in the spatio-temporally aligned original parameter set, the specific process is as follows: 1. Geographic coordinate conversion: WGS-84 three-dimensional geographic coordinate system is adopted as the unified reference; Each point cloud data coordinate in the seafloor topographic data is converted to geocentric coordinates; Synchronously convert the spatial sampling point coordinates of rock and soil physical parameters and stratum bearing capacity parameters to ensure the uniformity of the coordinate system.

[0040] 2. Spatial grid construction: Construct a regular three-dimensional spatial grid, with a grid cell length of .

[0041] Project and map the original sampling data to the corresponding spatial grid cells to generate three types of initial grid data: seafloor topographic grid data, rock and soil physical parameter grid data, and stratum bearing capacity parameter grid data.

[0042] S22, grid data dimensionless processing: to eliminate the influence of different parameter dimensions and improve the subsequent multi-source index fusion capability, three types of grid data are processed respectively, including: 1. Seafloor topographic grid data: elevation normalization method, expressed as: ; wherein, is the original water depth value (negative value represents seafloor depth), is the water depth value of the shallowest and deepest place in the entire region, and the standardized seafloor topographic data is output.

[0043] Grid data of geotechnical physical parameters: the following conversion is performed for each parameter (such as porosity, saturation, and permeability coefficient) respectively: ; Each normalized geotechnical physical parameter is reorganized into a standardized geotechnical physical parameter tensor.

[0044] Grid data of formation bearing capacity parameters: Z-score standardization method, expressed as: ; wherein X is the original bearing capacity parameter value, such as cone tip resistance, unconsolidated shear strength, and are the sample mean and standard deviation, respectively, and the output is the standardized formation bearing capacity parameter.

[0045] S23, fusion of standardized data and construction of a cube: the three types of standardized grid data are fused in space and time dimensions to construct the final standardized geological data cube, and the specific process is as follows: 1. Spatial fusion: according to the unified grid number , the standardized seabed topography value, geotechnical physical properties, and formation bearing capacity parameters in each unit are paired to ensure that each grid unit contains a set of three types of standardized values.

[0046] 2. Time matching: call the timestamp recorded in S14 , bind to each grid unit to ensure the spatio-temporal consistency of the data, and the time stamp accuracy is recommended to be controlled to the hour level to reflect the timeliness of the collection.

[0047] 3. Cube structure output: each standardized grid unit is represented as a structure, represented as: ; wherein the first four items are spatial and temporal information, and the subsequent items are standardized attribute data, and finally a standardized geological data cube including spatial coordinates, timestamps, and multi-dimensional geological attributes is formed.

[0048] S3: Extract the formation shear wave velocity, standard penetration number, and water content from the standardized geological data cube, and generate a comprehensive geological stiffness index for each grid unit through a weighted fusion algorithm, which is: S31, geological parameter extraction: extract the standardized formation shear wave velocity, standardized standard penetration number, and standardized water content from the standardized geological data cube according to the spatial grid unit.

[0049] S32, weight coefficient configuration and fusion model construction: to reflect the relative importance of each parameter to the stiffness contribution, the following preset weight coefficient range is set, and a fusion constraint model is established: standardized formation shear wave velocity weight coefficient , value range 0.45≤ ≤0.55; standardized SPT weight coefficient , value range 0.25≤ ≤0.35; standardized water content weight coefficient , value range 0.15≤ ≤0.25; The three need to meet the normalization constraint: ; In the present application = 0.5, = 0.3, = 0.2; S33, weighted fusion calculation and exponential matrix generation: for each spatial grid cell, apply the weighted fusion algorithm to calculate its comprehensive geological stiffness index . Denoted as: ; Wherein, is the comprehensive geological stiffness index of the grid cell, is the normalized formation shear wave velocity, N is the normalized SPT, and w is the normalized water content; Finally, the stiffness index of all grid cells is summarized to generate a comprehensive geological stiffness index value matrix: ; Wherein is the length, width and height distribution dimension of the spatial grid. The matrix serves as the input basis for the classification of geological construction units in S4, realizing the quantitative closed-loop support from original geological parameters to construction decision-making.

[0050] S4: According to the comprehensive geological stiffness index threshold, the construction sea area is divided into hard rock area, transition area and soft soil area three types of geological construction units, specifically: S41, set the comprehensive geological stiffness index threshold interval: to realize the classification of stiffness level, the relative threshold strategy is adopted to set the classification boundary of the comprehensive geological stiffness index matrix, including: 1. Extract the extreme value of the index: from the comprehensive geological stiffness index value matrix , respectively extract the global maximum value and the minimum value .

[0051] 2. Calculate the regional classification threshold: hard rock area boundary threshold : ; soft soil area boundary threshold : ; Transition zone: meet .

[0052] This setting has a relative adaptability, can be overall level floating with the geological stiffness distribution.

[0053] S42, geological type determination and identification matrix generation: traverse all spatial grid cells of the comprehensive geological stiffness index value matrix , execute the following type determination logic: ; 1. Output structure package: the output structure of each cell is: , where Type takes the value of hard rock area, soft soil area or transition zone.

[0054] 2. Generate identification matrix: build an identification matrix with the same G dimension as , used for spatial clustering analysis.

[0055] S43, spatial clustering processing of geological construction unit: to eliminate discrete error classification and boundary burr, improve the engineering practicability of regional division, execute the following clustering and correction operation: 1. Spatial connected domain identification: to eliminate discrete error classification and boundary burr, improve the engineering practicability of regional division, execute the following clustering and correction operation: Perform three-dimensional eight-neighborhood connected domain search on the three types in the identification matrix M; Use seed filling (floodfill) or union set algorithm to mark each connected domain.

[0056] Calculate the corresponding spatial area of each connected domain : ; Where n is the number of connected cells, (consistent with the grid size).

[0057] 2. Eliminate isolated small units: for areas with an area , it is considered to have no independent construction significance, and the correction strategy is executed, using the type of the adjacent maximum area connected block to replace the type of the current isolated block.

[0058] 3. Output spatial distribution map: encode the clustering results into a spatial type layer, output as GeoTIFF or Shapefile format, each pixel / vector unit contains attributes: spatial coordinates, type identification, area and boundary contour.

[0059] S5: assign hydraulic impact hammer units to hard rock areas, assign vibration pile sinking units to soft soil areas, and assign rotary drilling units to transition zones to form an initial equipment allocation scheme, which is: S51, hydraulic impact hammer unit quantity configuration: first, extract all grid cells marked as hard rock area from the hard rock area spatial distribution map, count the total number, multiply the cell area to get the total area of hard rock area. The unit area can be set according to the grid resolution, for example, the standard grid resolution is ten meters by ten meters, then the area of each unit is one hundred square meters.

[0060] Next, according to the unit area construction efficiency of hydraulic impact hammer unit, divide the total area of hard rock area by the daily processing capacity of a single device to determine the theoretical number of required devices. To ensure complete construction coverage, if the construction amount of less than one device is still calculated as one device, that is, rounding up.

[0061] Subsequently, according to the spatial distribution of each grid in the hard rock area, all hard rock area grids are divided into block-shaped connected regions, and the hydraulic impact hammer unit with higher number is preferentially allocated to the region with larger area. Each device is bound to the grid coordinate set it is responsible for, and the device number and working area are marked in the spatial layer.

[0062] For example, if the total area of hard rock area is sixteen thousand square meters, the system will automatically configure eleven hydraulic impact hammer units, and generate device numbers such as "HY-001" to "HY-011", which correspond to the divided construction sub-region grid list respectively.

[0063] S52, vibration pile sinking machine unit quantity configuration: the processing process of soft soil area is consistent with S51. The system reads the soft soil area spatial distribution map, accumulates the number of all grid cells marked as soft soil area, and converts it into the total construction area.

[0064] According to the daily coverable area of the vibration pile sinking machine unit, the required equipment quantity is calculated, and the actual unit quantity is configured by rounding up.

[0065] Spatial aggregation is performed on the soft soil area grid, and the vibration pile sinking machine unit number is reasonably allocated according to the area size and shape, for example, using the number prefix "ZD-", such as "ZD-001", "ZD-002", etc.

[0066] At the same time, the construction grid coordinate set responsible by each vibration pile sinking machine unit is generated, and the deployment position and service area of the device are marked in the visualization layer.

[0067] S53, rotary drilling rig unit quantity configuration: for the transition area, first count all transition area grid cells in the transition area spatial distribution map, and calculate the total area.

[0068] Because the geological characteristics of the transition area have the characteristics of soft and hard interlacing or gradual change, the construction efficiency of the rotary drilling rig unit is relatively low, so a smaller unit area construction capacity is used as the benchmark when configuring the quantity.

[0069] The number of rotary drilling rig units is divided according to the area, and the deployment area of each unit is divided according to the spatial connectivity. Each rotary drilling rig unit is assigned a unique number, such as "ZX-001", "ZX-002", etc., and is bound to the output of the grid coordinate set under its jurisdiction.

[0070] To avoid resource waste, priority is given to ensuring good geographical continuity of the areas responsible for each unit, reducing the frequency of unit movement.

[0071] S54, initial device allocation scheme generation: finally, the system will summarize the deployment information of the three types of construction equipment to form a complete initial device allocation scheme, including: Hard rock area deployment scheme: contains the total number of hydraulic impact hammer units and each unit number, corresponding construction grid coordinate set, equipment service area boundary, etc.

[0072] Soft soil area deployment scheme: contains the total number of vibration pile driving machine units and each unit number, corresponding construction grid coordinate set, equipment distribution center point position, etc.

[0073] Transition zone deployment scheme: contains the total number of rotary drilling rig units and each unit number, responsible space grid set, area shape description, etc.

[0074] Equipment dispatch list: includes the total number of hydraulic impact hammer units, vibration pile driving machine units and rotary drilling rig units, lists the number of each type of equipment, service area number, planned start time, etc. Field, forming a standard input template for construction plan and operation scheduling interface; S6: when the real-time monitoring of the comprehensive geological stiffness index of a unit changes by more than ±15%, trigger the adjacent area equipment scheduling instruction, update the dynamic resource allocation scheme, specifically: S61, geological variation unit detection and marking: continuously monitor the real-time update status of the standardized geological data cube, especially the comprehensive geological stiffness index field.

[0075] In each update period (set to daily or every 4 hours), all spatial grid units are traversed from the latest cube data, the current comprehensive geological stiffness index is extracted, and the initial value recorded in the initial device allocation scheme is compared.

[0076] When the change in the comprehensive geological stiffness index of any grid unit relative to the initial value exceeds ±15%, the system marks the grid unit as a geological variation unit.

[0077] For each geological variation unit, the system extracts its three-dimensional spatial coordinates and the changed comprehensive geological stiffness index, writes it into the geological variation log, and generates a visual highlight identification layer for the dispatch system to call.

[0078] For example, in a certain construction area, the original comprehensive geological stiffness index of grid unit G_132_57 is 0.62, and the updated value is 0.72. The determined change range is 16.1%, which meets the variation condition, and the grid is marked as a geological variation unit.

[0079] S62, adjacent area scheduling instruction generation: perform adjacent area expansion analysis on each geological variation unit, expand one grid unit in all directions above, below, left and right and diagonally from the center of the unit to form a three-by-three nine-grid adjacent area.

[0080] Subsequently, according to the index change direction of the geological variation unit, the following scheduling rules are executed: If the increase of the comprehensive geological stiffness index after the variation is ≥15%, the system determines that the regional geology is hardened, and the rotary drilling rig unit originally deployed in the adjacent area may no longer be suitable, and needs to be switched to a hydraulic impact hammer unit. The system issues a device conversion instruction and records it in the scheduling log.

[0081] If the decrease of the comprehensive geological stiffness index after the variation is ≥15%, the system determines that the regional geology is softened, and the originally deployed hydraulic impact hammer unit may be over-provisioned, and needs to be switched to a vibratory pile driver unit. The system automatically issues a corresponding device switching instruction.

[0082] If the variation range is within ±15%, the system determines that the geological state is relatively stable, and the original device can continue to work without any adjustment.

[0083] The system encapsulates each adjacent area device scheduling instruction as a structured data packet, including the geological variation unit number, the adjacent area grid coordinate set, the variation type, the target device type and the execution priority.

[0084] S63, dynamic resource allocation scheme update: according to the scheduling instructions generated in S62, the system starts the dynamic resource allocation module to modify the device deployment scheme and the device scheduling list as follows: 1. Unbind the original device binding relationship: first, find the device information bound to the current adjacent area grid in the initial device allocation scheme, unbind the device from its corresponding grid coordinate set, and mark the device as to be redeployed.

[0085] 2. Reallocate device type: according to the target device type required in the scheduling instruction, reconfigure the appropriate unit type for the adjacent area grid. Preferably, allocate the same type of device that is currently in idle or standby state; if there is no available device, then call a new device from the standby resource pool for supplementation.

[0086] 3. Update the device scheduling list: adjust the number of each type of device in the device scheduling list, record the device number, change time and scheduling source of the added or released device, and synchronize to the resource scheduling database.

[0087] 4. Generating dynamic resource deployment scheme: merging the latest equipment binding results of the mutation unit and its adjacent area into the equipment deployment master layer. The system outputs the dynamic resource deployment scheme text list and layer file containing the latest equipment number, construction grid coordinate set, equipment type and dispatch source.

[0088] For example, if the grid numbered G_75_120 has a comprehensive geological stiffness index drop of 17.8% during construction, the system detects that the original deployment is a hydraulic impact hammer unit, and under the dispatch instruction, the construction equipment in this area and its adjacent area is re-designated as a vibratory pile driver unit, and a device instance numbered ZD-021 is generated and deployed to the target area, while updating the dispatch list to record the change event.

[0089] The present application covers any alternative, modification, equivalent method and scheme made on the essence and scope of the present application. In order to make the public have a thorough understanding of the present application, specific details are described in the following preferred embodiments of the present application, and the present application can also be fully understood without the description of these details for those skilled in the art. In addition, in order to avoid unnecessary confusion to the essence of the present application, well-known methods, processes, procedures, elements and circuits, etc. are not described in detail.

[0090] The above is only the preferred embodiment of the present application, and it should be pointed out that for ordinary skilled in the art, without departing from the principle of the present application, a number of improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present application.

Claims

1. A photovoltaic foundation construction resource allocation method integrating submarine geological parameters, characterized in that: The following steps are involved: S1: Using a ship-borne multi-beam bathymetric system, a seabed drilling sampling device, and a static cone penetration instrument, the seabed topography data, geophysical parameters, and stratum bearing capacity parameters of the construction area are simultaneously acquired; S2: uniformly map all parameters in S1 to a three-dimensional geographic coordinate system to generate a standardized geological data cube with a timestamp; S3: Extract the formation shear wave velocity, standard penetration number and water content from the standardized geological data cube, and generate the comprehensive geological stiffness index of each grid cell through a weighted fusion algorithm; S4: Divide the construction sea area into three types of geological construction units: hard rock area, transition area and soft soil area according to the comprehensive geological stiffness index threshold; S5: Assign hydraulic impact hammer units to the hard rock area, vibratory pile driving units to the soft soil area, and rotary drilling rig units to the transition area to form an initial equipment allocation plan; S6: When the real-time monitoring shows that the comprehensive geological stiffness index of a unit changes by more than ±15%, the equipment dispatch instruction of the adjacent area is triggered and the dynamic resource allocation plan is updated.

2. The photovoltaic foundation construction resource allocation method based on submarine geological parameter fusion according to claim 1 is characterized in that: Said S1 comprises: S11: Use the ship-borne multi-beam bathymetry system to conduct full-coverage scanning along the planned survey line, collect original seabed topography point cloud data, and output seabed topography data after coordinate solution and tide level correction; S12: Obtain rock core samples at preset grid nodes using a seabed drilling sampling device. Perform density testing, particle analysis, and mineral composition testing on the rock core samples to generate geophysical parameters including porosity, saturation, and permeability. S13: Penetration testing is performed adjacent to the seabed drilling sampling device using a static cone penetration tester. The cone tip resistance curve and sidewall friction resistance curve are recorded in real time. After depth normalization, the formation bearing capacity parameters are extracted. S14: Synchronously record the timestamps and spatial coordinates of seabed topography data, geophysical parameters, and stratum bearing capacity parameters to form a temporally and spatially aligned original parameter set.

3. The photovoltaic foundation construction resource allocation method based on seabed geological parameter fusion according to claim 2 is characterized in that: The S2 includes: S21: The seabed topography data, geotechnical parameters, and stratum bearing capacity parameters in the original parameter set that are aligned in time and space are uniformly converted to the WGS-84 three-dimensional geographic coordinate system to generate seabed topography grid data, geotechnical parameters grid data, and stratum bearing capacity parameter grid data with coordinate labels; S22: performing dimensionless processing on the seabed topography grid data, the geotechnical physical parameter grid data, and the stratum bearing capacity parameter grid data, respectively, and outputting standardized seabed topography data, standardized geotechnical physical parameters, and standardized stratum bearing capacity parameters; S23: The standardized seabed topography data, standardized geophysical parameters, and standardized stratum bearing capacity parameters are spatiotemporally matched according to the same spatial grid units, embedded into the timestamps recorded in S14, and a standardized geological data cube including spatial coordinates, timestamps, and multidimensional geological attributes is constructed.

4. The photovoltaic foundation construction resource allocation method based on submarine geological parameter fusion according to claim 3 is characterized in that: The dimensionless processing of the seabed topography grid data, the geotechnical physical parameter grid data and the stratum bearing capacity parameter grid data respectively includes: The seabed topography grid data adopts the elevation normalization method to output standardized seabed topography data; The geotechnical parameter grid data adopts the range normalization method to output the standardized geotechnical parameters; The Z-score method is used to normalize the grid data of the formation bearing capacity parameters, and the standardized formation bearing capacity parameters are output.

5. The photovoltaic foundation construction resource allocation method based on submarine geological parameter fusion according to claim 4 is characterized in that: The S3 includes: S31: Extract three geological parameters, namely, standardized formation shear wave velocity, standardized standard penetration number, and standardized water content, from the standardized geological data cube according to spatial grid cells; S32: Configure preset weight coefficients for the standardized formation shear wave velocity, standardized SPF number, and standardized water content, respectively, and construct a calculation framework for the weighted fusion algorithm. Specifically: Normalized formation shear wave velocity weight coefficient (0.45≤ ≤0.55); Standardized SPF weight coefficient (0.25≤ ≤0.35); Normalized moisture content weight coefficient (0.15≤ ≤0.25); Satisfy the constraints: ; S33: Calculate the comprehensive geological stiffness index through a weighted fusion algorithm to generate a comprehensive geological stiffness index numerical matrix for each grid cell.

6. The photovoltaic foundation construction resource allocation method based on submarine geological parameter fusion according to claim 5 is characterized in that: The comprehensive geological stiffness index is calculated as: ； in, For the The comprehensive geological stiffness index of the grid cell, is the normalized formation shear wave velocity, N is the normalized standard penetration number, and w is the normalized water content.

7. The photovoltaic foundation construction resource allocation method based on submarine geological parameter fusion according to claim 6 is characterized in that: The S4 includes: S41: Set the threshold range of the comprehensive geological stiffness index, specifically: Hard rock area demarcation threshold: comprehensive geological stiffness index ≥ upper threshold; Soft soil area demarcation threshold: comprehensive geological stiffness index ≤ lower threshold; Transition zone demarcation threshold: lower threshold < comprehensive geological stiffness index < upper threshold; The upper threshold is 0.8 times the maximum value of the comprehensive geological stiffness index numerical matrix, and the lower threshold is 1.2 times the minimum value of the comprehensive geological stiffness index numerical matrix; S42: Traverse each grid cell of the comprehensive geological stiffness index numerical matrix and perform geological type determination: When the cell value is ≥ the upper threshold, it is marked as a hard rock area; When the cell value is ≤ the lower threshold, it is marked as a soft soil area; When the lower threshold value < cell value < upper threshold value, it is marked as a transition zone; Output the geological construction unit type identification matrix with spatial coordinates; S43: Perform spatial clustering on the geological construction unit type identification matrix, including merging adjacent grid cells of the same type and removing isolated cells with an area of ​​less than 50m², to generate spatial distribution maps of three types of geological construction units: hard rock area, transition area, and soft soil area.

8. The photovoltaic foundation construction resource allocation method based on submarine geological parameter integration according to claim 7 is characterized in that: The S5 includes: S51: Calculate the total area of ​​the hard rock area based on the spatial distribution map of the hard rock area, and allocate the number of hydraulic impact hammer units based on the unit area construction efficiency of the hydraulic impact hammer units; S52: Calculate the total area of ​​the soft soil area based on the spatial distribution map of the soft soil area, and allocate the number of vibratory pile driving units based on their unit area construction efficiency; S53: Calculate the total area of ​​the transition zone according to the spatial distribution map of the transition zone, and allocate the number of rotary drilling rigs according to the unit area construction efficiency of the rotary drilling rigs; S54: Generate an initial device allocation plan, including: Deployment plan for hard rock areas: hydraulic impact hammer unit number and corresponding construction grid coordinate set; Deployment plan for soft soil areas: vibratory pile driving unit number and corresponding construction grid coordinate set; Transition zone deployment plan: rotary drilling rig unit number and corresponding construction grid coordinate set; Equipment dispatch list: total number of hydraulic impact hammer units, total number of vibratory pile driving units, and total number of rotary drilling rig units.

9. The photovoltaic foundation construction resource allocation method based on submarine geological parameter fusion according to claim 8 is characterized in that: The S6 includes: S61: Real-time monitoring of the updated data of the standardized geological data cube. When it is detected that the comprehensive geological stiffness index of a grid cell has changed by more than ±15% relative to the initial value, the cell is marked as a geological variation cell, and its spatial coordinates and the comprehensive geological stiffness index after the variation are extracted. S62: With the geological variation unit as the center, expand the 3×3 grid area to the surrounding area to define the adjacent area, and generate the equipment dispatch instructions for the adjacent area: When the increase in the comprehensive geological stiffness index after mutation is ≥15%, a switch command from the rotary drilling rig in the adjacent area to the hydraulic impact hammer unit is issued; When the comprehensive geological stiffness index decreases by 15% or more after the mutation, a command is issued to switch from the hydraulic impact hammer unit in the adjacent area to the vibration pile driving unit; When the variation is within ±15%, the current device configuration is maintained; S63: Updating the device deployment plan according to the neighboring area device scheduling instruction, including: Unbind the construction grid of the original unit in the variant unit and adjacent areas; Reassign the unit type according to the S62 instruction type; Corrected the unit quantity distribution in the equipment scheduling list; Generate a dynamic resource allocation plan that includes a new set of construction grid coordinates.

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