A method, system, device and medium for intelligent construction of a spin-extrusion filling and extrusion compact pile

Abstract

The application relates to an intelligent construction method, system, equipment and medium for rotary extrusion and filling pile construction, and belongs to the technical field of building construction. The construction method comprises the following steps: collecting pile hole three-dimensional coordinate data of a construction area through a Beidou positioning module; acquiring stratum physical and mechanical index data through a data acquisition module based on site geotechnical investigation data; generating a three-dimensional geological model for rotary extrusion and filling construction by combining the pile hole three-dimensional coordinate data and the stratum physical and mechanical index data; calculating initial construction parameters of a rotary extrusion and filling device based on the three-dimensional geological model; sending a rotary extrusion and filling hole forming instruction; dynamically adjusting the rotary speed and the pressing force of a drill rod, and outputting corrected stratum compactness parameters; generating grouting strategy parameters based on a preset mapping table, and sending a high-pressure injection instruction; controlling the drilling speed based on slurry pressure injection amount feedback control, generating pressure injection strategy optimization parameters, and updating the parameters to a construction parameter database. The application ensures the stability and bearing capacity of the pile foundation under different geological conditions.

Description

Technical Field

[0001] This application relates to the field of building construction technology, and in particular to an intelligent construction method, system, equipment and medium for rotary extrusion grouting compaction piles. Background Technology

[0002] Currently, rotary compaction pile (SSPG) technology is a new technology that has been increasingly widely used in pile foundation construction in recent years. This technology uses an integrated rotary compaction machine combined with specialized drilling tools to compact the soil into a hole, and then withdraws the drill after the soil has been compacted to the designed depth, achieving integrated hole formation and grouting. Throughout the construction process, there is no need to squeeze soil out of the hole, resulting in less construction noise and a lower environmental impact. During hole formation, the rotary compaction equipment uses a rotating drill bit to laterally compress the soil to form a dense soil mass, and then presses a fluid, self-compacting, consolidating material upwards from the bottom of the hole, completing the grouting and pile formation operations simultaneously, thus achieving the goal of "hole formation equals pile formation".

[0003] Compared to traditional compaction piles, SSPG technology offers significant advantages. Firstly, it can handle deeper foundations, extending the treatment depth of soft foundations to over 25 meters underground without soil removal. This makes it particularly suitable for collapsible foundations or sites requiring substantial treatment thickness. By compacting the soil and using high-quality grouting materials, it effectively eliminates site collapsibility, increases the bearing capacity of the foundation, and significantly enhances the stability of the pile foundation. Secondly, because the rotary compaction grouting machine can perform simultaneous drilling and grouting, this technology effectively shortens the construction cycle and improves construction efficiency. While meeting engineering quality requirements, SSPG technology saves substantial investment costs compared to traditional cast-in-place piles. Especially in large-scale infrastructure construction, all construction processes and data can be monitored and fed back on-site in a timely manner, achieving a dual improvement in economic benefits and project quality.

[0004] However, in actual construction, due to the non-uniformity of the strata, especially in geological conditions such as soft soil layers, highly saturated soil layers, or alternating soil layers and calcareous nodule layers, construction parameters such as drilling pressure, drilling speed, drill bit lifting speed, grouting pressure, and grout viscosity need to be adjusted in real time. Otherwise, the soil around the pile will not be sufficiently compacted, and the pile diameter formed by the grout at different depths may be uneven, resulting in substandard pile quality and affecting its bearing capacity and stability. Summary of the Invention

[0005] In order to achieve real-time monitoring and dynamic adjustment during construction and to ensure the accuracy and efficiency of rotary extrusion compaction pile technology under different geological conditions, this application provides an intelligent construction method, system, equipment and medium for rotary extrusion compaction piles.

[0006] Firstly, this application provides an intelligent construction method for rotary extrusion grouting compaction piles, employing the following technical solution:

[0007] A method for intelligent construction of rotary compaction piles, the method comprising:

[0008] The three-dimensional coordinate data of pile holes in the construction area were collected using the Beidou positioning module.

[0009] Based on site geotechnical investigation data, the data acquisition module is used to obtain the physical and mechanical properties of the stratigraphy.

[0010] By combining the three-dimensional coordinate data of the pile hole with the physical and mechanical index data of the strata, a three-dimensional geological model for rotary extrusion grouting construction is generated;

[0011] The initial construction parameters of the rotary extrusion grouting equipment are calculated based on the three-dimensional geological model, including the drill rod rotation speed, extrusion pressure threshold and grouting flow rate benchmark value.

[0012] Based on the initial construction parameters, a rotary extrusion grouting command is sent, and the drill rod torque, formation resistance data, current data, and borehole wall deformation data are monitored in real time during the rotary extrusion grouting process.

[0013] Based on the drill rod torque, formation resistance data, current data, and borehole wall deformation data, the drill rod rotation speed and downforce are dynamically adjusted, and the corrected formation compaction parameters are output.

[0014] Based on the corrected formation density parameters, grouting strategy parameters are generated using a preset mapping table, and a high-pressure grouting command is sent.

[0015] Real-time acquisition of grout diffusion pressure data and grout injection volume during high-pressure grouting process;

[0016] Based on the grout diffusion pressure data and grout injection volume, the drilling speed is controlled by feedback, and optimization parameters for the injection strategy are generated and updated to the construction parameter database.

[0017] By adopting the above-mentioned technical solution, integrating BeiDou positioning, borehole radar, real-time data monitoring, and dynamic adjustment strategies, a complete technical chain from geological exploration to construction control was constructed, realizing an intelligent upgrade of the rotary compaction pile construction process. This technical solution enables precise control of the pile foundation construction process, improving construction efficiency and quality. The meticulous control and intelligent adjustment of the entire process not only improves construction accuracy but also optimizes the grouting process, reduces human error, and ensures the stability and bearing capacity of the pile foundation under different geological conditions.

[0018] Secondly, this application provides an intelligent construction system for rotary extrusion grouting compaction piles, which adopts the following technical solution:

[0019] A rotary compaction pile intelligent construction system, the system comprising:

[0020] The Beidou positioning module is used to collect three-dimensional coordinate data of the construction area;

[0021] The data acquisition module is used to obtain geological physical and mechanical index data based on site geotechnical investigation data;

[0022] The model building module is used to combine the three-dimensional coordinate data of the pile hole with the physical and mechanical index data of the strata to generate a three-dimensional geological model of the rotary extrusion grouting construction.

[0023] The parameter calculation module is used to calculate the initial construction parameters of the rotary extrusion grouting equipment based on the three-dimensional geological model, including the drill rod rotation speed, extrusion pressure threshold and grouting flow rate reference value.

[0024] The intelligent control module is used to send rotary extrusion grouting instructions according to the initial construction parameters;

[0025] The data monitoring module is used to monitor drill rod torque, formation resistance data, current data and borehole wall deformation data in real time during the rotary extrusion grouting process;

[0026] The dynamic correction module is used to dynamically adjust the drill rod rotation speed and downforce based on the drill rod torque, formation resistance data, current data and borehole wall deformation data, and output the corrected formation compaction parameters.

[0027] The intelligent control module is used to generate grouting strategy parameters based on a preset mapping table according to the corrected formation compaction parameters, and send high-pressure grouting commands.

[0028] The monitoring and acquisition module is used to collect data on the diffusion pressure of grout in the borehole and the grout injection volume in real time during the high-pressure injection process.

[0029] The grouting strategy optimization module is used to control the drilling speed based on the grout diffusion pressure data and grout injection volume, generate grouting strategy optimization parameters, and update them to the construction parameter database.

[0030] Thirdly, this application provides a computer device, which adopts the following technical solution:

[0031] A computer device includes a memory, a processor, and a computer program stored in the memory, the processor executing the computer program to perform the steps of the method as described in the first aspect.

[0032] Fourthly, this application provides a computer-readable storage medium, which adopts the following technical solution:

[0033] A computer-readable storage medium storing a computer program that can be loaded by a processor and executed as in any of the methods in the first aspect. Attached Figure Description

[0034] Figure 1 This is a schematic diagram of the first process of an intelligent construction method for rotary extrusion grouting compaction piles according to one embodiment of this application.

[0035] Figure 2 This is a schematic diagram of the second process of an intelligent construction method for rotary extrusion grouting compaction piles according to one embodiment of this application.

[0036] Figure 3 This is a schematic diagram of the third process of an intelligent construction method for rotary extrusion grouting compaction piles according to one embodiment of this application.

[0037] Figure 4 This is a schematic diagram of the fourth process of an intelligent construction method for rotary extrusion grouting compaction piles according to one embodiment of this application.

[0038] Figure 5 This is a schematic diagram of the fifth process of an intelligent construction method for rotary extrusion grouting compacted piles according to one embodiment of this application.

[0039] Figure 6 This is a schematic diagram of the sixth process of an intelligent construction method for rotary extrusion grouting compaction piles according to one embodiment of this application. Detailed Implementation

[0040] To make the purpose, technical solution, and advantages of this application clearer, the following description is provided in conjunction with the appendix. Figure 1 -Appendix Figure 6 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0041] This application discloses an intelligent construction method for rotary extrusion grouting compaction piles.

[0042] Reference Figure 1 A method for intelligent construction of rotary compaction piles, comprising the following steps:

[0043] Step S101: Collect three-dimensional coordinate data of pile holes in the construction area using the Beidou positioning module;

[0044] Among them, BeiDou positioning technology is an important component of the Global Navigation Satellite System (GNSS). Its working principle is based on carrier phase differential positioning (RTK) technology to achieve centimeter-level accuracy in spatial coordinate calculation. By receiving signals from at least four satellites and combining them with differential correction from a ground reference station, it can effectively eliminate the influence of atmospheric delay, orbital errors, and other factors, thus providing a reliable spatial reference for precise pile location. This positioning data includes not only planar coordinate information but also elevation data, providing necessary spatial constraints for subsequent 3D geological modeling.

[0045] Step S102: Based on the site geotechnical investigation data, acquire the geological physical and mechanical index data through the data acquisition module;

[0046] Specifically, based on site geotechnical investigation data, the data acquisition module obtains the physical and mechanical properties of the soil. This step involves the integration of in-situ testing and laboratory test data in geotechnical engineering investigation. The physical and mechanical properties typically include, but are not limited to, key parameters such as the soil's natural density, water content, void ratio, compression modulus, internal friction angle, and cohesion. These parameters are obtained through in-situ testing methods such as the Standard Penetration Test (SPT), Static Cone Penetration Test (CPT), and Vane Shear Test, and are further verified and supplemented by laboratory geotechnical tests. The data acquisition module adopts a standardized data interface protocol, ensuring compatibility with digital investigation reports provided by different investigation units. Data preprocessing algorithms eliminate outliers and noise interference, ensuring the accuracy of subsequent modeling.

[0047] Step S103: Combine the three-dimensional coordinate data of the pile hole with the physical and mechanical index data of the strata to generate a three-dimensional geological model for rotary extrusion grouting construction.

[0048] The modeling process employs Kriging interpolation or inverse distance weighted interpolation (IDW) from geostatistics to transform discrete exploration point data into a continuous three-dimensional geological model through spatial interpolation techniques. This model not only reflects the stratigraphic distribution characteristics of the strata but also includes the spatial variation patterns of the mechanical parameters of each soil layer. The geological model constructed using geological modeling software (such as GOCAD and Petrel) has a multi-layered structure, accurately describing the spatial distribution relationships of different geological units such as soft soil, hard soil, sand, and clay layers, providing precise geological basis for subsequent construction parameter calculations.

[0049] Step S104: Calculate the initial construction parameters of the rotary extrusion grouting equipment based on the three-dimensional geological model, including the drill rod rotation speed, extrusion pressure threshold and grouting flow rate benchmark value;

[0050] The determination of the drill rod rotation speed needs to consider factors such as the soil's shear strength, plasticity index, and equipment power limitations. By establishing a mechanical model of the interaction between the drill rod and the soil, the shear rate required for the soil to achieve the best compaction effect is calculated. The setting of the extrusion pressure threshold is based on the soil's lateral confined compression characteristics. The ultimate bearing capacity of the soil is determined by the Mohr-Coulomb failure criterion, and a reasonable pressure control range is determined by combining a safety factor. The calculation of the grouting flow rate benchmark value needs to consider factors such as pile diameter, pile length, soil permeability coefficient, and grout diffusion radius. The optimal combination of grouting parameters is determined by Darcy's law and a grout rheology model.

[0051] Step S105: Send a rotary extrusion grouting command according to the initial construction parameters, and monitor the drill rod torque, formation resistance data, current data and borehole wall deformation data in real time during the rotary extrusion grouting process.

[0052] Among them, the drill rod torque data reflects the tangential resistance of the soil to the drill rod during drilling. The actual drill rod torque is obtained by measuring the torsional torque of the main motor output shaft through a torque sensor and converting it with the transmission ratio. The formation resistance data mainly reflects the axial reaction force experienced by the drill rod during its advance. It is indirectly obtained by measuring the working pressure of the hydraulic cylinder through a pressure sensor. The current data reflects the changes in motor load. Since the motor current is positively correlated with the load torque, the spatial distribution characteristics of the formation shear strength can be inferred by monitoring the changes in the current of the drive motor. The borehole wall deformation data is measured by a combination of tilt and displacement sensors to monitor the verticality deviation and borehole diameter changes in real time during the drilling process.

[0053] Step S106: Based on the drill pipe torque, formation resistance data, current data, and borehole wall deformation data, dynamically adjust the drill pipe rotation speed and downward pressure, and output the corrected formation compaction parameters.

[0054] In some embodiments, the adjustment process employs a fuzzy control algorithm or an adaptive PID control strategy to achieve real-time parameter optimization. The control algorithm first establishes a mapping relationship between input variables (torque, resistance, current, deformation) and output variables (rotation speed, pressure). It then normalizes each parameter using a membership function and establishes a control rule base based on expert experience. When an increase in soil resistance is detected at a certain stratum, the system automatically reduces the drill rod rotation speed and increases the downforce to ensure sufficient soil compaction. Simultaneously, it analyzes the soil compaction process by monitoring the trend of current data changes. When the current value stabilizes and reaches a preset threshold, it determines that the soil at that stratum has met the design compaction requirements, thereby outputting the corresponding stratum compaction parameters.

[0055] Step S107: Based on the corrected formation compaction parameters, generate grouting strategy parameters according to the preset mapping table, and send high-pressure grouting command.

[0056] The pre-defined mapping table is established based on extensive engineering practice data and theoretical analysis results. Through statistical analysis of grout diffusion patterns and grouting effects under different density conditions, a quantitative relationship is established between density parameters and control parameters such as grouting pressure, flow rate, and time. This mapping table is stored in a database and has self-learning and adaptive update functions, enabling continuous improvement and optimization of the mapping relationship based on new engineering data, ensuring the scientific validity and effectiveness of the grouting strategy.

[0057] Step S108: Real-time acquisition of grout diffusion pressure data and grout injection volume during the high-pressure injection process;

[0058] Among them, the grout diffusion pressure data reflects the permeation and diffusion state of the grout in the soil pores. The pressure change in the grout delivery pipeline is measured in real time by a pressure sensor embedded in the drill pipe, and the effective diffusion radius of the grout is calculated by combining the soil permeability coefficient and porosity. The measurement of grout injection volume is achieved by electromagnetic flowmeter or ultrasonic flowmeter, which can accurately measure the amount of grout injected per unit time, providing data support for subsequent drilling speed control.

[0059] Step S109: Based on the grout diffusion pressure data and grout injection volume, the drilling speed is controlled by feedback, and the pressure injection strategy optimization parameters are generated and updated to the construction parameter database.

[0060] This feedback control employs a proportional-integral-derivative (PID) control algorithm from closed-loop control theory. By establishing a dynamic balance between grout injection pressure and drilling speed, it achieves precise control of the grouting process. When the grout injection pressure is lower than the set value, the system automatically reduces the drilling speed to increase the grout pressure in the hole, maintaining a balance between the grout pressure and the hole wall pressure, thus ensuring the pile diameter and pile integrity. Conversely, when the pressure is too high, the drilling speed is appropriately increased to prevent pipe blockage and other adverse phenomena during injection. This real-time feedback adjustment mechanism effectively ensures the uniformity and integrity of the pile body. The resulting optimized parameters are stored in a database as reference data under similar geological conditions, enabling comprehensive monitoring during construction and providing decision support for subsequent projects.

[0061] The above implementation integrates BeiDou positioning, borehole radar, real-time data monitoring, and dynamic adjustment strategies to construct a complete technology chain from geological exploration to construction control, achieving an intelligent upgrade of the rotary extrusion grouting compaction pile construction process. This technical solution enables precise control of the pile foundation construction process, improving construction efficiency and quality. The meticulous control and intelligent adjustment of the entire process not only improves construction accuracy but also optimizes the grouting process, reduces human error, and ensures the stability and bearing capacity of the pile foundation under different geological conditions.

[0062] Reference Figure 2As one implementation of step S101, the steps of acquiring three-dimensional coordinate data of the construction area through the Beidou positioning module, obtaining stratum permeability coefficient and shear strength data, and generating a three-dimensional geological model for rotary extrusion grouting construction by combining preset pile diameter and depth parameters include:

[0063] Step S201: Align the three-dimensional coordinate data with the global coordinate system of the construction area to generate a calibrated three-dimensional coordinate matrix;

[0064] The purpose of coordinate data calibration is to ensure that the coordinate data of the construction area can be matched with the global coordinate system, thereby providing accurate geographic positioning for subsequent construction path planning and geological model establishment.

[0065] Specifically, the BeiDou Navigation Satellite System (BDS) provides centimeter-level accuracy, making precise positioning around construction sites crucial, especially in large-scale infrastructure construction where construction equipment needs to operate accurately within designated areas. After acquiring the three-dimensional coordinate data of the construction site through the BeiDou positioning module, the calibration process involves aligning this coordinate data with the global coordinate system of the construction area. Specifically, this process uses mathematical transformation methods (such as coordinate transformation or coordinate offset calibration) to adjust the local coordinate data to the standard format of the global coordinate system. Through this alignment operation, construction equipment can accurately perform each task during construction, ensuring that the position and depth of each pile foundation meet design requirements.

[0066] Understandably, this calibration process effectively reduces construction errors caused by coordinate deviations, avoiding any deviations due to inaccurate on-site coordinate positioning, thus preventing any impact on the smooth progress of the entire construction project. Through this high-precision calibration method, the coordinate position of each point during construction is precisely controlled, providing a reliable geographic information foundation for subsequent construction operations. This not only ensures the accuracy of location during construction but also improves the level of automation, reduces human error, and enhances construction efficiency and quality.

[0067] Step S202: The three-dimensional coordinate matrix is ​​fused with the stratigraphic physical and mechanical index data to generate a three-dimensional geological parameter field;

[0068] This fusion process employs data assimilation technology to organically combine heterogeneous data from multiple sources. Formation physical and mechanical parameters typically originate from drilling samples and in-situ tests at different depths, exhibiting discrete and discontinuous characteristics. A three-dimensional coordinate matrix provides a continuous spatial framework, and spatial interpolation and data fusion algorithms map discrete mechanical parameters into a continuous three-dimensional space.

[0069] In some embodiments, the process employs inverse distance weighted interpolation (IDW) or radial basis function interpolation (RBF), establishing a weighting function based on the spatial distance between the exploration point and the interpolation point; the closer the exploration point, the greater its influence on the interpolation result. Simultaneously, considering the stratified characteristics of geological structures, a layered interpolation strategy is adopted, performing parameter interpolation separately according to the engineering geological characteristics of different soil layers to ensure the accuracy and rationality of parameters for each soil layer. The generated three-dimensional geological parameter field contains the continuous distribution of key mechanical parameters such as density, compressibility modulus, internal friction angle, and cohesion in three-dimensional space, providing fundamental data support for subsequent construction parameter calculations.

[0070] Step S203: Based on the preset pile diameter and depth parameters, delineate the construction boundary of the pile body in the three-dimensional geological parameter field, and generate a three-dimensional vector geological model within the pile body range using the Kriging interpolation algorithm.

[0071] By defining the construction boundaries of the piles, the location and depth range of the piles during construction can be clearly determined. To ensure the accuracy of the model, the pile boundaries are represented by a cylindrical model, the diameter of which is the preset pile diameter, and the depth direction is discretized in 0.5-meter increments according to design requirements. This discretization operation can simulate the structural characteristics of the piles in detail, while providing a clear geometric framework for subsequent construction.

[0072] In this embodiment, the Kriging interpolation algorithm can be used to infer the geological properties of an unknown area using known geological data. Kriging interpolation is a spatial interpolation method based on statistical principles. Its basic idea is to perform a weighted average based on the spatial correlation of surrounding points. Here, a semi-variogram model (such as a spherical model) is used to quantify the variability between spatial points, thereby improving the accuracy of the interpolation results. In this case, the nugget effect value of the semi-variogram is set to 0.1, and the range is 2.5 meters. These parameters are set based on historical data and geological experience to describe the spatial correlation of the geological data.

[0073] Step S204: Based on the drill bit diameter and maximum torque parameters of the rotary extrusion grouting equipment, calculate the construction disturbance range, mark the disturbance area in the three-dimensional vector geological model, and output a three-dimensional geological model containing the disturbance effects.

[0074] Specifically, construction disturbance correction is used to simulate the actual impact of rotary grouting equipment on the soil layer. During rotary grouting construction, the drill bit diameter and maximum torque of the equipment will disturb the surrounding soil layer, affecting the quality and stability of the pile foundation. Therefore, by calculating the construction disturbance range, the disturbed areas can be marked in the three-dimensional geological model, and the stratum parameters of these areas can be adjusted accordingly. Specifically, the lateral disturbance radius is equal to 1.2 times the drill bit diameter, and the longitudinal disturbance gradient is proportional to the maximum torque and the average shear strength of the stratum.

[0075] In some embodiments, within the disturbed area, the shear strength parameter of the stratum can be reduced by 15%-20% to reflect the impact of construction on the stratum. This adjustment simulates the weakening phenomenon of the soil layer after disturbance during construction, which in turn affects the quality of grouting and pile foundation. By marking and correcting these disturbed areas, the model can more realistically reflect the actual construction situation, providing a reliable basis for subsequent grouting design and pile foundation stability analysis.

[0076] The above implementation method achieves comprehensive analysis and modeling of the geological characteristics of the construction area, which not only improves the accuracy of the construction process but also effectively ensures the quality and stability of pile foundation construction. This three-dimensional geological model has strong adaptability in complex geological environments, enabling it to improve construction efficiency and reduce construction risks while ensuring project quality.

[0077] Reference Figure 3 As one implementation of step S102, the step of calculating the extrusion hole-forming path and initial construction parameters of the rotary extrusion grouting equipment based on a three-dimensional geological model includes:

[0078] Step S301: Extract the coordinate range of the disturbed area based on the three-dimensional geological model;

[0079] The disturbed area refers to the region where the operation of construction equipment, especially the movement of the drill bit, may affect the surrounding strata during rotary grouting. Because the movement of construction equipment and the squeezing action of the drill bit alter the density and structure of the surrounding soil, the disturbed area is crucial for assessing the construction impact and avoiding potential quality problems.

[0080] Specifically, the extraction of disturbed areas typically involves using existing data from the geological model, particularly information on marked disturbed areas, combined with equipment parameters (such as drill bit diameter and maximum torque) to predict the potential impact on the soil layers. The goal of this step is to identify which areas will be directly disturbed during construction, thus providing data support for subsequent path planning and safety avoidance rules. The coordinate range of the extracted disturbed areas provides boundary conditions for subsequent path planning, helping to determine which geological areas can be safely traversed and which need to be avoided.

[0081] Step S302: Based on the preset safety avoidance rules, determine the corresponding path planning range according to the coordinate range of the disturbance area;

[0082] After extracting the disturbed areas, these areas are converted into specific path planning ranges according to preset safety avoidance rules. The core purpose of path planning is to ensure that construction equipment avoids crossing disturbed areas that severely affect the strata during pile foundation construction. In this embodiment, based on the coordinate range of the disturbed areas, the system will set appropriate avoidance rules to ensure that the equipment avoids crossing these marked disturbed areas during movement.

[0083] For example, safety avoidance rules might stipulate that a certain distance (e.g., 0.5 meters) beyond the boundary of the disturbed area be designated as a prohibited path zone. This rule is based on engineering safety considerations, aiming to prevent further disturbance of the soil layers due to improper path selection during construction, especially in sensitive areas or on soft soil layers. The application of these avoidance rules can effectively reduce environmental impact and ensure soil stability during construction.

[0084] Step S303: Based on the shear strength data of the three-dimensional geological model, the path planning range and the preset number of pile holes, divide the construction area priority, plan the equipment movement path and generate the pile hole construction sequence table.

[0085] Based on the established 3D geological model, combined with shear strength data, path planning range, and the preset number of pile holes, the system needs to prioritize the construction process. Shear strength is a key parameter affecting construction difficulty and soil stability; therefore, areas with lower shear strength usually need to be prioritized to ensure the effectiveness and safety of pile foundation construction.

[0086] In some embodiments, the priority division rule for construction areas may be: areas with shear strength less than 50 kPa are marked as priority 1; areas between 50 kPa and 150 kPa are priority 2; and areas greater than 150 kPa are priority 3.

[0087] Based on these priority divisions, the equipment movement paths and the sequence of pile hole construction will be rationally arranged. For example, higher-priority areas need to be constructed first, while lower-priority areas can be constructed later. Path planning uses A... * Path planning algorithms are a common type of graph search algorithm that plans the movement route of a device by finding the shortest path between a known starting point and a destination. * The algorithm's constraints include that the minimum spacing between adjacent pile holes cannot be less than three times the designed pile diameter, thereby ensuring that the equipment will not generate too many overlapping areas or conflicts due to improper path planning during construction.

[0088] Step S304: Calculate the drill pipe rotation speed, extrusion pressure threshold, and grouting flow rate reference value based on the three-dimensional geological model mapping to generate an initial construction parameter set.

[0089] Specifically, by combining key formation parameters (such as permeability coefficient, shear strength, and porosity) from the three-dimensional geological model, the system needs to map and calculate the drill bit rotation speed, extrusion pressure threshold, and grouting flow rate baseline. These construction parameters directly affect the working efficiency of the rotary extrusion grouting equipment and the quality of the pile foundation; therefore, accurate calculation of these parameters is crucial.

[0090] In this embodiment, the drill pipe rotation speed is determined based on shear strength data. Generally, areas with lower shear strength require higher rotation speeds to ensure the drill bit can smoothly penetrate the soil. Conversely, areas with higher shear strength require moderately reduced rotation speeds to prevent excessive wear of the drill bit in hard soil layers.

[0091] Specifically, the extrusion pressure threshold is calculated based on shear strength and porosity, and the extrusion pressure is calculated using the following formula:

[0092] P threshold ==2.5×n×τ;

[0093] In the above formula, n is the porosity and τ is the shear strength. The calculation of the extrusion pressure is based on the soil density and shear strength to ensure that the pressure output of the equipment will not cause damage to the soil structure.

[0094] Specifically, the grouting flow rate benchmark value is calculated using the following formula: Q base =0.8×K×A;

[0095] In the above formula, K is the permeability coefficient, and A is the cross-sectional area of ​​the pile hole. The grouting flow rate is closely related to the permeability of the soil layer; areas with higher permeability coefficients require a larger flow rate to ensure uniform diffusion of the grout.

[0096] In the above embodiments, accurately mapping and calculating these construction parameters can effectively improve the operating efficiency of equipment under complex geological conditions, while ensuring the quality of the pile foundation during construction. By reasonably adjusting parameters such as drill rod rotation speed, extrusion pressure, and grouting flow rate, operational stability during construction can be ensured, avoiding construction failure or ground damage caused by improper parameters.

[0097] Reference Figure 4 As one implementation of step S104, the step of dynamically adjusting the drill pipe rotation speed and downforce based on drill pipe torque, formation resistance data, current data, and borehole wall deformation data, and outputting the corrected formation compaction parameters includes:

[0098] Step S401: Perform data preprocessing on drill pipe torque, formation resistance data, current data, and borehole wall deformation data;

[0099] Because these data are often affected by noise, interference, or measurement errors, directly using the raw data will lead to inaccurate results. Therefore, preprocessing is crucial, mainly including timestamp alignment, noise filtering, and outlier removal.

[0100] Specifically, since different sensors may acquire data at different times, it's necessary to align the timestamps of the acquired data to ensure consistency in the time signature of each data item for subsequent data analysis. Furthermore, sensor data is inevitably affected by noise during measurement; therefore, filtering algorithms (such as low-pass filtering and Kalman filtering) are needed to remove noise and retain useful signals. Additionally, outliers refer to measurement results that significantly deviate from the normal data range, possibly due to instrument malfunction or other external factors. In this step, the data is detected and these outliers are removed to ensure the accuracy of the analysis results.

[0101] Step S402: Based on the preprocessed drill pipe torque and formation resistance data, and combined with the preset reference torque and reference resistance parameters, calculate the normalized real-time formation compaction parameters.

[0102] Specifically, by combining pre-processed drill rod torque data and formation resistance data with preset benchmark torque and resistance parameters, real-time formation density parameters are calculated. Formation density reflects the compactness of the soil layer; areas with higher density indicate a more solid soil layer, while those with lower density indicate a looser soil layer.

[0103] In one embodiment of this application, the specific calculation formula is as follows:

[0104] ;

[0105] In the above formula, C norm T is the real-time formation density parameter. filter For the filtered drill pipe torque data, F filter For the filtered formation resistance data, T base and F base These are the preset reference torque and reference resistance parameters, respectively.

[0106] Understandably, real-time soil compaction parameters can accurately reflect the compaction of the soil layer during construction, helping construction equipment to dynamically adjust its operating parameters and ensure stability and efficiency during construction.

[0107] Step S403: Calculate the borehole wall stability coefficient based on the preprocessed borehole wall deformation data and real-time formation compaction parameters, and trigger the preset stability classification flag.

[0108] The borehole wall stability coefficient is a key indicator for assessing the stability of the borehole wall. In this step, the borehole wall stability coefficient is further calculated using borehole wall deformation data and real-time calculated formation compaction parameters, and a stability classification label is generated based on this coefficient. When the borehole wall stability coefficient S ≥ 0.9, the classification result is stable (green label); when 0.7 ≤ S < 0.9, the classification result is warning (yellow label); when S < 0.7, the classification result is dangerous (red label). The borehole wall stability coefficient S and the classification result are output.

[0109] In one embodiment of this application, the specific calculation formula is as follows:

[0110] ;

[0111] In the above formula, S is the hole wall stability coefficient, and D clean D represents the deformation of the hole wall after cleaning. max C is the maximum threshold for hole wall deformation. target For the preset target density, C norm This is a real-time formation density parameter.

[0112] Understandably, by calculating the borehole wall stability coefficient, the stability of the borehole wall can be assessed in real time, providing a basis for whether parameters need to be adjusted during construction, and providing a judgment standard for subsequent dynamic adjustments, ensuring that the borehole wall does not undergo excessive deformation or collapse during construction.

[0113] Step S404: Based on current data, stability classification indicators and real-time formation compaction parameters, dynamically adjust the drill pipe rotation speed and downforce, and output the real-time formation compaction parameters.

[0114] Specifically, current data reflects changes in motor load and is a crucial indicator of equipment operating status. Monitoring current changes helps determine if the construction process is proceeding normally. An abnormally high current may indicate equipment overload or the encounter with a hard interlayer, requiring a reduction in drill rod rotation speed or downward pressure to prevent equipment damage. The dynamic adjustment algorithm employs a fuzzy PID control strategy, using stability classification indicators as the primary control input and real-time formation compaction parameters as auxiliary inputs. Intelligent adjustment of control parameters is achieved through a fuzzy rule base. When the stability indicator is unstable or in a dangerous state, the control system automatically reduces drill rod rotation speed and downward pressure to ensure construction safety. When the formation compaction parameter is high, the construction parameters are appropriately increased to improve efficiency. The adjustment process follows the energy balance principle and optimal control theory, ensuring maximum construction efficiency while maintaining construction quality and safety. The output real-time formation compaction parameter not only reflects the current formation compaction state but also provides crucial data support for subsequent pile quality assessment and construction process optimization.

[0115] In some embodiments, if the stability coefficient S < 0.7, it indicates poor borehole stability, requiring a reduction in drill rod rotation speed and activation of the high-frequency vibration module to improve borehole stability. In this case, the drill rod rotation speed is reduced by 20%, and the high-frequency vibration module is activated to help loosen the soil. If 0.7 ≤ S < 0.9, it indicates good borehole stability, but further adjustments are still needed. The drill rod rotation speed is reduced by 10%, and the downward pressure is adjusted using the following formula:

[0116] P new =P current +k·(C target -C norm );

[0117] In the above formula, k is the pressure compensation coefficient, and P new For the corrected downforce, P current The downforce before correction. Based on the real-time formation density, the downforce is increased as needed to improve construction results.

[0118] If the stability coefficient S ≥ 0.9, the hole wall stability is good, and the current drill pipe parameters can be maintained, avoiding unnecessary adjustments.

[0119] Understandably, the dynamic adjustment mechanism ensures that the rotation speed and downward pressure of the drill pipe are always kept within the optimal range, avoiding the negative impact of excessively fast or slow operation on the borehole wall. This effectively improves construction efficiency while protecting the stability of the borehole wall and preventing excessive deformation.

[0120] In the above embodiments, intelligent adjustments are made based on the real-time density of the formation and the stability of the borehole wall to ensure precise control of the drill pipe parameters. By dynamically adjusting the drill pipe rotation speed and downward pressure, construction efficiency is effectively improved while protecting the stability of the borehole wall, avoiding formation deformation and borehole wall collapse. This technical solution greatly enhances the stability and safety of the construction process and has high engineering application value.

[0121] Reference Figure 5 As one implementation of step S107, the step of generating optimized parameters for the pressure grouting strategy by feedback control of the drilling speed based on grout diffusion pressure data and grout injection volume includes:

[0122] Step S501: Perform data cleaning and baseline calculation on the slurry diffusion pressure data to obtain the cleaned pressure data sequence and pressure fluctuation baseline value.

[0123] The slurry diffusion pressure data may be affected by noise, pulse interference and other measurement errors during the actual acquisition process, so these data must be preprocessed.

[0124] The specific data processing workflow includes time window truncation, median filtering, and baseline calculation. First, the collected pressure sensor data is truncated into 5-second time windows to reduce the amount of data and ensure that each data point is within a relatively fixed time range for easier subsequent processing. Then, a median filter is used to smooth the raw data, with a filter window size of 7. Median filtering effectively eliminates impulse noise (such as abnormal pressure changes within a short period) and retains a relatively stable signal. Finally, a moving average method (with a window size of 10) is used to calculate the baseline value of pressure fluctuations. This aims to obtain the normal fluctuation range of the pressure data for subsequent calculation of the pressure fluctuation index.

[0125] Understandably, data cleaning removes noise and outliers, making subsequent analysis and decision-making more accurate. Baseline calculations provide a standard reference for subsequent fluctuation event detection, ensuring that subsequent analysis is based on data within the normal fluctuation range, thereby improving the reliability of the entire grouting strategy optimization.

[0126] Step S502: Calculate the real-time pressure fluctuation index based on the pressure data sequence after cleaning and the baseline value of pressure fluctuation;

[0127] The real-time pressure fluctuation index is calculated based on the pressure data sequence and baseline value after cleaning. This index measures the amplitude of grout pressure changes and reflects the stability of grout diffusion during construction. A larger fluctuation index indicates more severe pressure fluctuations in the grout, which may indicate an unstable construction environment or problems.

[0128] In this embodiment of the application, the specific formula for calculating the real-time pressure fluctuation index δ is as follows:

[0129] ;

[0130] In the above formula, P clean For pressure data after cleaning, P base This is the baseline value.

[0131] Understandably, the real-time pressure fluctuation index can quantify the degree of grout pressure fluctuation, helping construction personnel to monitor abnormal fluctuations during the grout diffusion process in real time. By calculating this index, abnormal fluctuations can be detected and responded to promptly, thereby improving the accuracy and safety of grouting construction.

[0132] Step S503: Determine whether the real-time pressure fluctuation index exceeds the preset threshold within multiple consecutive time windows; if not, proceed to step S504; if yes, proceed to step S505.

[0133] Step S504: Mark as a stable event and maintain the current pressure gradient and slurry viscosity ratio;

[0134] Step S505: Mark the event as a high volatility event and generate an event marking state;

[0135] The high-fluctuation event flagging is used to alert to potential instability during construction, allowing for corresponding optimization measures. For example, if the pressure fluctuation index δ > 15% within three consecutive time windows, the system triggers a high-fluctuation event flag. This detection step ensures timely flagging and alarm triggering when significant fluctuations occur, providing a basis for subsequent optimization strategy adjustments. The identification of high-fluctuation events ensures rapid response to potential problems during construction, reducing construction quality issues caused by excessive fluctuations.

[0136] Step S506: Based on the event marker status and the current grouting strategy parameters, generate pressure gradient correction values ​​and grout viscosity adjustment ratios, and control the drilling speed based on grout injection volume feedback to form an optimized parameter set;

[0137] When a high-fluctuation event is detected, the current pressure gradient needs to be adjusted to reduce the amplitude of pressure fluctuations, thereby making the slurry diffusion more uniform and stable. The specific correction value is calculated based on 88% of the current pressure gradient. Additionally, to cope with high-fluctuation events, the slurry viscosity also needs to be appropriately adjusted. Typically, during high fluctuations, the slurry viscosity will increase by about 10% (i.e., an adjustment ratio of 1.08 times) to improve the slurry's fluidity and stability. The feedback control of the drilling speed adopts a closed-loop control structure, comparing the actual injection volume with the target injection volume. By establishing a transfer function relationship between the injection volume error and the drilling speed, precise speed adjustment is achieved.

[0138] Understandably, by dynamically adjusting the pressure gradient and grout viscosity, it is possible to effectively intervene in unstable situations that occur during construction, thereby improving the uniformity and stability of grout diffusion, enhancing grouting quality and construction efficiency. The optimized parameters enable the system to make intelligent adjustments based on real-time data, ensuring that construction is always in the best possible state.

[0139] Step S507: Bind the optimized parameter set with the current construction location information and update it to the construction parameter database.

[0140] The system binds the generated set of optimized parameters to the current construction location information (such as pile hole number and depth coordinates) and updates it to the construction parameter database. This operation ensures that each construction process has corresponding optimized parameter records, which facilitates subsequent querying and analysis.

[0141] In the above embodiments, grouting parameters can be dynamically optimized during construction, thereby improving the diffusion effect of the grout and the construction quality. By adjusting the pressure gradient and grout viscosity in real time, this method effectively addresses high fluctuation events that may occur during construction, ensuring pressure stability during the construction process. Furthermore, the database recording of construction parameters and the generation of optimization instructions ensure precise management and continuous improvement of the construction process.

[0142] Reference Figure 6 As a further implementation of the construction method, after the step of sending the rotary extrusion grouting command according to the extrusion grouting path and initial construction parameters, the method further includes:

[0143] Step S601: Real-time monitoring of the video stream of the rotary extrusion filling equipment's operation site;

[0144] Specifically, multiple wide-angle high-definition cameras are deployed at key locations on the piling machine (such as the top of the drill rod, the equipment platform, and the surrounding area). These cameras typically employ 4K resolution sensors to capture real-time video stream data at a rate of 30 frames per second. The video stream is transmitted to the embedded processing unit via fiber optic or 5G networks, ensuring low latency (less than 100 milliseconds) and high bandwidth transmission to avoid data loss or lag. Video stream acquisition relies on the photoelectric conversion principle of image sensors (such as CMOS or CCD) to transform the physical scene into a digital pixel array, and combines H.265 encoding technology to compress the data volume to adapt to the wireless transmission environment.

[0145] For example, in rotary extrusion grouting operations, the high-speed rotation of the drill rod generates a large amount of dust and vibration. The camera needs to be equipped with an IP67 protection rating and an automatic white balance algorithm to handle image quality under harsh lighting conditions and ensure the reliability and continuity of video data.

[0146] Step S602: Analyze moving individuals in the video stream of the work site using an image recognition algorithm;

[0147] Among them, "moving individuals" include people and moving objects around the device; "moving individuals" refers to any non-static object, whose detection relies on the feature extraction layer (such as the ResNet backbone network) to calculate gradient direction and texture pattern, and output class label (such as "person" or "vehicle") and confidence score.

[0148] Specifically, image recognition algorithms are typically based on convolutional neural network (CNN) architectures, such as YOLOv5. This algorithm employs a single-stage detection mechanism, dividing video frames into grid cells and predicting the bounding box and class probability for each cell. In practice, the algorithm first extracts features of moving targets (e.g., pixel variation regions between consecutive frames) using frame difference or optical flow methods, and then classifies and identifies moving individuals (including construction workers, vehicles, or other moving obstacles).

[0149] In practical applications, the pre-trained model, combined with transfer learning techniques, uses the COCO dataset (CommonObjects in Context) and is fine-tuned for construction site scenarios to improve recognition accuracy (e.g., above 98%). For example, during drill pipe operations, the algorithm can distinguish moving workers from background noise, achieve semantic segmentation through a deep learning model, and transform the raw video stream into structured threat data to support safety decision-making.

[0150] Step S603: Determine whether a moving individual has been detected entering the preset distance range of the drill pipe radius; if yes, proceed to step S604; if no, do not perform any operation.

[0151] Specifically, based on the geometric transformation principle in machine vision, the 2D video coordinate system is converted into a 3D world coordinate system to accurately calculate the distance between the moving individual and the drill pipe. The preset distance range is defined as a safety buffer zone radiating outward from the center point of the drill pipe (e.g., a radius of 1.5 meters), and its value is derived from equipment safety specifications (e.g., the radius of injury caused by centrifugal force generated when the drill pipe rotates). First, depth information is calculated using camera calibration parameters (e.g., intrinsic and extrinsic parameter matrices), and the actual distance is estimated by combining the parallax principle of monocular or binocular vision; if a multi-camera system is used, triangulation can be used to improve accuracy.

[0152] It should be noted that the preset distance range can be dynamically adjusted (based on the drill pipe extension and retraction length and rotation speed), and individual trajectories are predicted through a Kalman filter to prevent misjudgment.

[0153] Step S604: Send an emergency stop command to the rotary extrusion filling equipment and transmit the video stream of the operation site to the management terminal and overlay the equipment operating parameters.

[0154] Specifically, the emergency stop command is sent to the main controller of the rotary extrusion filling equipment via CAN bus or industrial Ethernet protocol (such as Modbus TCP). The command is encoded as a specific fault safety code, directly cutting off the power to the drill rod motor and activating the mechanical brake. The response time is controlled within 50 milliseconds to comply with the IEC 61508 safety standard. Simultaneously, the video stream is pushed in real-time to the management terminal (such as a PC or large-screen cockpit) via the RTMP protocol. OpenGL or DirectX technology is used to overlay and display equipment operating parameters (including drill rod speed, depth, current readings, etc.). The overlay process uses an alpha channel blending algorithm to render text or graphics layers onto the video frames, ensuring that the operator can intuitively identify the abnormal context. For example, when a worker is detected entering a danger zone, the system not only stops the equipment immediately but also annotates the video stream with parameter trend graphs (such as a sudden drop in speed curve) to aid in post-event analysis.

[0155] In the above implementation, through real-time acquisition and analysis of video streams, the system can accurately identify mobile threats and make dynamic judgments based on preset distances, ensuring the efficiency and pertinence of risk response. Emergency stop commands and data visualization provide immediate intervention and decision support. Thus, in the high-speed drilling environment, the system can avoid collision accidents in advance, optimize construction continuity and reduce the rate of operational errors, and ultimately provide a traceable safety guarantee framework for foundation treatment projects.

[0156] In practical application, this application combines rotary extrusion grouting and high-pressure grouting methods, introducing an intelligent monitoring and collaborative management technology solution to improve the automation level and quality control capabilities of the construction process. This solution constructs a multi-source sensing system to achieve comprehensive acquisition and real-time feedback of key construction parameters, including but not limited to drill rod pressing speed, hole verticality, formation impedance characteristics, grouting volume of fluidized solidified soil, and drill bit spatial position information. Through various sensors deployed on the piling machine, changes in various physical states during drilling can be dynamically acquired, and combined with a positioning module, high-precision spatial positioning can be achieved, thus replacing the traditional manual layout method and improving the accuracy and efficiency of construction positioning.

[0157] The collected data undergoes preliminary processing via edge computing devices before being transmitted to a remote intelligent management and control platform, forming a closed-loop control mechanism. Based on this, the system dynamically adjusts construction parameters according to the correlations between data from multiple dimensions. For example, it optimizes the drill rod rotation speed and downward pressure distribution based on depth, speed, and current variation curves. When borehole wall deformation or verticality deviation exceeds the allowable range, it automatically triggers the vertical adjustment function to ensure borehole quality. Simultaneously, a dual-feedback control strategy is employed during the pressure grouting process. Through real-time monitoring and comparative analysis of pressure and flow data, the deviation between the actual grouting volume and the theoretical model is calibrated, ensuring the stability and consistency of the grouting process. Furthermore, when the system identifies abnormal operating conditions, it can promptly issue early warning signals and push them to the central monitoring terminal and mobile interface for rapid response and handling by on-site personnel.

[0158] Furthermore, to enhance construction safety and traceability, this application integrates a panoramic safety monitoring system. Utilizing multiple cameras working collaboratively, it achieves comprehensive coverage of the environment surrounding the piling machine, and combines this with artificial intelligence visual recognition algorithms to detect personnel or moving objects in hazardous areas in real time. Upon detecting any abnormal intrusion, an emergency stop procedure is immediately initiated to prevent accidents. Simultaneously, all video stream data and construction parameters are synchronously uploaded and bound to a cloud platform, supporting historical scene playback by timestamp and generating a 3D heat map to assist in quality assessment and subsequent traceability. Through a mobile interface, cross-platform synchronous display and management of construction data are also possible, providing various digital results, including pile length statistics and material consumption reports, offering reliable data for project acceptance and quality management.

[0159] In summary, by organically integrating the aforementioned technical features with steps such as geological modeling and parameter adjustment in the construction method, a complete "perception-decision-execution" closed-loop system is formed, which significantly enhances the intelligence level and controllability of the construction process, realizes the transformation from traditional experience-driven to data-driven, and has good application prospects and promotion value.

[0160] This application also discloses an intelligent construction system for rotary extrusion grouting compaction piles.

[0161] The Beidou positioning module is used to collect three-dimensional coordinate data of the construction area;

[0162] The model building module is used to obtain the permeability coefficient and shear strength data of the strata, and combine them with the preset pile diameter and depth parameters to generate a three-dimensional geological model for rotary extrusion grouting construction.

[0163] The parameter calculation module is used to calculate the extrusion hole-forming path and initial construction parameters of the rotary extrusion grouting equipment based on a three-dimensional geological model. The initial construction parameters include the drill rod rotation speed, the extrusion pressure threshold, and the grouting flow rate reference value.

[0164] The intelligent control module is used to send rotary extrusion grouting commands based on the extrusion grouting path and initial construction parameters;

[0165] The data monitoring module is used to monitor drill rod torque, formation resistance data, and borehole wall deformation data in real time during the rotary extrusion grouting process.

[0166] The dynamic correction module is used to dynamically adjust the drill pipe rotation speed and downforce based on drill pipe torque, formation resistance data and borehole wall deformation data, and output the corrected formation compaction parameters and borehole wall stability coefficient.

[0167] The grouting strategy module is used to generate grouting strategy parameters based on a preset mapping table according to the corrected formation compaction parameters; the grouting strategy parameters include the grouting pressure gradient and the grout viscosity ratio.

[0168] The intelligent control module is used to send high-pressure injection commands based on grouting strategy parameters;

[0169] The monitoring and acquisition module is used to collect slurry diffusion pressure data in real time during the high-pressure injection process;

[0170] The grouting strategy optimization module is used to generate grouting strategy optimization parameters based on grout diffusion pressure data and update them to the construction parameter database.

[0171] The intelligent construction system for rotary extrusion grouting compacted piles according to the embodiments of this application can realize any of the above-mentioned intelligent construction methods, and the specific working process of each module in the intelligent construction system can refer to the corresponding process in the above-mentioned method embodiments.

[0172] In the several embodiments provided in this application, it should be understood that the provided methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for example, the division of a certain module is merely a logical functional division, and in actual implementation there may be other division methods, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed.

[0173] This application also discloses a computer device.

[0174] Computer equipment, including memory, processor, and computer program stored on memory and executable on processor, wherein the processor executes computer program to implement an intelligent construction method for rotary extrusion grouting compaction piles as described above.

[0175] This application also discloses a computer-readable storage medium.

[0176] A computer-readable storage medium storing a computer program that can be loaded by a processor and executed as described above in any of the intelligent construction methods for rotary extrusion compaction piles.

[0177] The computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device; the program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0178] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0179] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.

Claims

1. An intelligent construction method for rotary extrusion grouting compaction piles, characterized in that, The construction method includes: The three-dimensional coordinate data of pile holes in the construction area were collected using the Beidou positioning module. Based on site geotechnical investigation data, the data acquisition module is used to obtain the physical and mechanical properties of the stratigraphy. By combining the three-dimensional coordinate data of the pile hole with the physical and mechanical index data of the strata, a three-dimensional geological model for rotary extrusion grouting construction is generated; The initial construction parameters of the rotary extrusion grouting equipment are calculated based on the three-dimensional geological model, including the drill rod rotation speed, extrusion pressure threshold and grouting flow rate benchmark value. Based on the initial construction parameters, a rotary extrusion grouting command is sent, and the drill rod torque, formation resistance data, current data, and borehole wall deformation data are monitored in real time during the rotary extrusion grouting process. Based on the drill rod torque, formation resistance data, current data, and borehole wall deformation data, the drill rod rotation speed and downforce are dynamically adjusted, and the corrected formation compaction parameters are output. Based on the corrected formation density parameters, grouting strategy parameters are generated using a preset mapping table, and a high-pressure grouting command is sent. Real-time acquisition of grout diffusion pressure data and grout injection volume during high-pressure grouting process; Based on the grout diffusion pressure data and grout injection volume, the drilling speed is controlled by feedback, and optimization parameters for the injection strategy are generated and updated to the construction parameter database.

2. The intelligent construction method for rotary extrusion grouting compaction piles according to claim 1, characterized in that, The steps for generating a three-dimensional geological model for rotary extrusion grouting construction by combining the three-dimensional coordinate data of the pile hole with the physical and mechanical properties of the strata include: Align the three-dimensional coordinate data with the global coordinate system of the construction area to generate a calibrated three-dimensional coordinate matrix; The three-dimensional coordinate matrix is ​​fused with the stratigraphic physical and mechanical index data to generate a three-dimensional geological parameter field; Based on the preset pile diameter and depth parameters, the construction boundary of the pile body is delineated in the three-dimensional geological parameter field, and a three-dimensional vector geological model within the pile body range is generated by the Kriging interpolation algorithm. Based on the drill bit diameter and maximum torque parameters of the rotary extrusion grouting equipment, the construction disturbance range is calculated, and the disturbance area is marked in the three-dimensional vector geological model, outputting a three-dimensional geological model containing the disturbance effects.

3. The intelligent construction method for rotary extrusion grouting compaction piles according to claim 2, characterized in that, The steps for calculating the initial construction parameters of the rotary extrusion grouting equipment based on the three-dimensional geological model include: The coordinate range of the disturbed area is extracted based on the three-dimensional geological model. Based on preset safety avoidance rules, the corresponding path planning range is determined according to the coordinate range of the disturbance area; Based on the shear strength data of the three-dimensional geological model, the path planning range, and the preset number of pile holes, the construction area priority is divided, the equipment movement path is planned, and a pile hole construction sequence table is generated. The initial construction parameter set is generated by calculating the drill pipe rotation speed, extrusion pressure threshold, and grouting flow rate based on the three-dimensional geological model.

4. The intelligent construction method for rotary extrusion grouting compaction piles according to claim 1, characterized in that, The steps for dynamically adjusting the drill pipe rotation speed and downforce based on the drill pipe torque, formation resistance data, current data, and borehole wall deformation data, and outputting the corrected formation compaction parameters, include: Data preprocessing is performed on the drill pipe torque, formation resistance data, current data, and borehole wall deformation data; Based on the preprocessed drill pipe torque and formation resistance data, and combined with the preset benchmark torque and benchmark resistance parameters, the normalized real-time formation density parameters are calculated. Based on the preprocessed borehole wall deformation data and the real-time formation compaction parameters, the borehole wall stability coefficient is calculated, and a preset stability classification indicator is triggered. Based on the current data, stability classification indicators, and real-time formation compaction parameters, the drill pipe rotation speed and downforce are dynamically adjusted, and the real-time formation compaction parameters are output.

5. The intelligent construction method for rotary extrusion grouting compaction piles according to claim 4, characterized in that, Based on the preprocessed drill pipe torque and formation resistance data, and combined with the preset benchmark torque and benchmark resistance parameters, the specific calculation formula for the normalized real-time formation density parameter is as follows: ; In the above formula, C norm T is the real-time formation density parameter. filter For the filtered drill pipe torque data, F filter For the filtered formation resistance data, T base and F base These are the preset reference torque and reference resistance parameters, respectively.

6. The intelligent construction method for rotary extrusion grouting compaction piles according to claim 1, characterized in that, Based on the slurry diffusion pressure data and slurry injection volume, the steps for generating optimized parameters for the injection strategy by feedback control of the drilling speed include: The slurry diffusion pressure data is cleaned and baseline is calculated to obtain the cleaned pressure data sequence and pressure fluctuation baseline value. Calculate the real-time pressure fluctuation index based on the pressure data sequence after cleaning and the baseline value of pressure fluctuation; Determine whether the real-time pressure fluctuation index exceeds a preset threshold within multiple consecutive time windows; if so, mark it as a high fluctuation event and generate an event marking status. Based on the event marker status and the current grouting strategy parameters, a pressure gradient correction value and a grout viscosity adjustment ratio are generated. Based on the grout injection volume feedback control, the drilling speed is controlled to form an optimized parameter set. The optimized parameter set is bound to the current construction location information and updated to the construction parameter database.

7. The intelligent construction method for rotary extrusion grouting compaction piles according to any one of claims 1 to 6, characterized in that, Following the step of sending the rotary extrusion grouting command based on the initial construction parameters, the method further includes: Real-time monitoring of video streams from the rotary extrusion filling equipment's operating site; The image recognition algorithm is used to analyze moving individuals in the video stream of the work site; the moving individuals include people around the equipment and moving objects. Determine whether a moving individual has been detected entering the preset distance range of the drill pipe radius; If so, an emergency stop command is sent to the rotary extrusion filling equipment, and the video stream of the operation site is transmitted to the management terminal and the equipment operating parameters are overlaid and displayed.

8. An intelligent construction system for rotary extrusion grouting compaction piles, characterized in that, The system includes: The Beidou positioning module is used to collect three-dimensional coordinate data of pile holes in the construction area; The data acquisition module is used to obtain geological physical and mechanical index data based on site geotechnical investigation data; The model building module is used to combine the three-dimensional coordinate data of the pile hole with the physical and mechanical index data of the strata to generate a three-dimensional geological model of the rotary extrusion grouting construction. The parameter calculation module is used to calculate the initial construction parameters of the rotary extrusion grouting equipment based on the three-dimensional geological model, including the drill rod rotation speed, extrusion pressure threshold and grouting flow rate reference value. The intelligent control module is used to send rotary extrusion grouting instructions according to the initial construction parameters; The data monitoring module is used to monitor drill rod torque, formation resistance data, current data and borehole wall deformation data in real time during the rotary extrusion grouting process; The dynamic correction module is used to dynamically adjust the drill rod rotation speed and downforce based on the drill rod torque, formation resistance data, current data and borehole wall deformation data, and output the corrected formation compaction parameters. The intelligent control module is used to generate grouting strategy parameters based on a preset mapping table according to the corrected formation compaction parameters, and send high-pressure grouting commands. The monitoring and acquisition module is used to collect data on the diffusion pressure of grout in the borehole and the grout injection volume in real time during the high-pressure injection process. The grouting strategy optimization module is used to control the drilling speed based on the grout diffusion pressure data and grout injection volume, generate grouting strategy optimization parameters, and update them to the construction parameter database.

9. A computer device, characterized in that: The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer program is stored that can be loaded by a processor and executed as described in any one of claims 1 to 7.

Images