Differential settlement double-path grouting cooperative control system for building pressure-bearing uplift pile

Abstract

The invention belongs to the technical field of construction engineering, and particularly relates to a building pressure-bearing uplift pile differential settlement double-path grouting cooperative control system which constructs a construction time sequence data set covering geology, design and real-time monitoring through an acquisition module; a displacement prediction module is used for inputting data into a soil squeezing effect prediction model and a differential settlement prediction model which are subjected to dynamic parameter correction, and accurate soil squeezing displacement and differential adjacent pile body settlement difference prediction values are output respectively; the parameter optimization module generates a construction control instruction including an optimized construction parameter reference value based on the predicted value and a preset threshold value; the control feedback module acquires dynamic feedback data in real time, calculates deviation, dynamically adjusts parameters and generates a control instruction to drive field equipment to execute, finally cooperative dynamic control over the three key targets of the soil squeezing effect, differential settlement and joint waterproofing is achieved, and the construction quality and safety of complex pile foundation engineering are effectively guaranteed.

Description

Technical Field

[0001] This invention belongs to the field of construction engineering technology, and in particular relates to a dual-path grouting collaborative control system for differential settlement of building bearing and tension piles. Background Technology

[0002] As urban buildings become increasingly taller and more multifunctional, the number of engineering projects involving adjacent bearing piles in the main building and tensile piles in the basement is growing. This creates construction conditions with significant differences in pile length between adjacent piles, resulting in dynamic changes in soil displacement effects, significant differences in settlement characteristics, and high requirements for coordinated waterproofing structures. Under these conditions, static pressure construction can easily lead to multiple technical challenges. The driving of long piles generates a significant soil displacement effect, causing excessive horizontal displacement of the soil in the area of ​​short piles, which in turn leads to deflection of short piles and distortion of the pile body under stress. The large difference in pile length results in significant differences in the bearing strata of adjacent piles, and a mismatch between bearing capacity and deformation characteristics, making differential settlement control extremely difficult and prone to causing cracking of the superstructure and potential waterproofing failure. At the joints of tensile piles, the leakage rate of traditional sealing processes is high due to soil displacement disturbance and settlement deformation, making it difficult to meet the waterproofing requirements of the basement.

[0003] In existing technologies, a common approach to soil squeezing control and settlement adjustment is based on traditional construction theories. This includes optimizing construction sequences (such as intermittent construction) and deploying pressure relief holes to mitigate the soil squeezing effect, using conventional grouting techniques to enhance pile bearing capacity and control settlement, and employing a single sealing material such as rubber waterstops for joint waterproofing. While this method is effective for small pile length differences, it has significant limitations in scenarios with large pile length differences: Soil squeezing effect prediction relies on empirical formulas, failing to consider the real-time impact of dynamic construction parameters such as pile driving speed and pile spacing, resulting in low prediction accuracy and a lack of precise basis for pressure relief hole placement and construction speed control; settlement control uses uniform grouting parameters without differentiated design for the stress characteristics of long and short piles, making precise control of settlement differences difficult; and joint waterproofing is a single-layer protection, failing to form a synergistic sealing system that resists deformation and disturbance, making it difficult to control leakage rates at a low level.

[0004] Another approach combines theoretical models with experimental verification. This involves establishing a theoretical model of the soil squeezing effect, conducting centrifuge model tests to predict settlement trends, and using composite waterproof materials to improve joint sealing performance. While this method improves technical accuracy, it still has shortcomings: the theoretical model of the soil squeezing effect does not integrate regional engineering data, parameter corrections lack specificity, and it is difficult to adapt to different geological conditions such as silty clay and silty sand layers; settlement control lacks a closed-loop system of prediction, monitoring, feedback, and regulation, and grouting parameter adjustments lag behind settlement development; joint waterproofing does not consider the coupling effect of construction disturbance and subsequent settlement deformation, the sealing structure has poor adaptability to deformation characteristics, and there is a lack of real-time means to judge the sealing quality.

[0005] Therefore, the technical problem that the existing technology urgently needs to solve is how to achieve accurate prediction and dynamic control of the soil squeezing effect in the static pressure construction scenario of adjacent piles with large pile length differences, so as to ensure construction quality and structural safety. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention proposes a dual-path grouting collaborative control system for differential settlement of bearing-pressure and tension-resistant piles. This system constructs a construction time-series dataset encompassing geology, design, and real-time monitoring through a data acquisition module. A displacement prediction module inputs data into a dynamically parameter-corrected soil squeezing effect prediction model and a differential settlement prediction model, outputting accurate predicted values ​​for soil radial displacement and differential settlement between adjacent piles, respectively. A parameter optimization module generates construction control commands, including optimized construction parameter benchmarks, based on the predicted values ​​and preset thresholds. A control feedback module collects dynamic feedback data in real time, calculates deviations, dynamically adjusts parameters, and generates control commands to drive on-site equipment execution. Ultimately, this system achieves collaborative dynamic control of three key objectives: soil squeezing effect, differential settlement, and joint waterproofing, effectively ensuring the construction quality and safety of complex pile foundation projects.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] The dual-path grouting collaborative control system for differential settlement of bearing-pressure and tension-resistant piles includes:

[0009] The data acquisition module is used to acquire geological survey data, pile design parameters, and real-time monitoring data of the construction area, and to construct a construction time-series dataset.

[0010] The displacement prediction module is used to input the construction time series dataset into the soil squeezing effect prediction model to obtain the predicted value of the radial displacement of the soil; wherein, the soil squeezing effect prediction model is constructed based on the modified Vesic hole enlargement theory, and introduces the pile driving speed influence coefficient, the static displacement theoretical value and the group pile effect reduction coefficient for dynamic correction;

[0011] The settlement prediction module is used to input the construction time series dataset into the differential settlement prediction model to obtain the predicted value of the settlement difference between adjacent piles; wherein, the differential settlement prediction model is constructed based on the Terzaghi consolidation equation and the Mindlin stress decoupling.

[0012] The parameter optimization module is used to determine the optimized construction parameter benchmark values ​​and generate construction control instructions based on the predicted value of the radial displacement of the soil and the predicted value of the settlement difference of the adjacent piles, and in combination with the preset soil displacement control threshold and settlement difference control threshold.

[0013] The control feedback module is used to respond to construction control commands and collect dynamic feedback data from the construction site in real time. It compares the dynamic feedback data with the corresponding predicted values, calculates the deviation value, and dynamically adjusts the benchmark values ​​of the construction parameters based on the deviation value to generate a set of construction parameters optimized in real time.

[0014] Specifically, the real-time monitoring data includes: pile driving speed, pile verticality, soil radial displacement, pore water pressure, and pile top settlement data;

[0015] The construction parameter benchmark values ​​include: the layout spacing and depth parameters of pressure relief holes, the staggered driving sequence parameters of long and short piles, the basic parameters for post-grouting at the pile tip of bearing piles, the basic parameters for post-grouting at the pile side of tension piles, and the triple waterproofing structural parameters of the bamboo joint of the pile body; the basic parameters for post-grouting at the pile tip of bearing piles include at least the grouting volume and water-cement ratio; the basic parameters for post-grouting at the pile side of tension piles include at least the grouting pressure; the dynamic feedback data includes at least the measured values ​​of the radial displacement of the soil and the measured values ​​of the settlement difference between adjacent piles; the real-time optimized set of construction parameters includes: the pressure relief hole spacing dynamically optimized based on displacement prediction values, the pile driving speed dynamically adjusted based on settlement difference, the real-time grouting volume and pressure of the pile tip compensation grouting of bearing piles, and the real-time pressure and stabilization time of the pile side compensation grouting of tension piles.

[0016] Specifically, the process of obtaining the predicted values ​​of soil radial displacement with dynamic parameter correction includes:

[0017] Obtain the soil shear modulus, initial horizontal stress, and ultimate borehole expansion pressure;

[0018] Based on the soil shear modulus, the initial horizontal stress and the ultimate borehole expansion pressure, the theoretical value of static displacement is calculated using the modified Vesic borehole expansion theory.

[0019] Obtain the pile driving speed, and calculate the pile driving speed influence coefficient based on the pile driving speed using an empirical formula;

[0020] Obtain the pile diameter and pile spacing, and calculate the pile group effect reduction coefficient based on the pile diameter and pile spacing using the pile group effect reduction formula;

[0021] The first intermediate displacement value is obtained by multiplying the theoretical value of static displacement with the influence coefficient of pile driving speed.

[0022] The predicted value of the radial displacement of the soil is obtained by multiplying the first intermediate displacement value with the reduction coefficient of the pile group effect.

[0023] Specifically, the optimization process of the soil displacement effect prediction model includes:

[0024] Obtain the measured value of the radial displacement of the soil, and calculate the model prediction deviation value based on the measured value of the radial displacement of the soil and the predicted value of the radial displacement of the soil.

[0025] Based on the judgment result that the predicted deviation value of the model exceeds the preset error threshold, the coefficients of the empirical formula or the group pile effect reduction formula are dynamically adjusted to obtain the optimized soil squeezing effect prediction model.

[0026] Specifically, the process of obtaining the predicted settlement difference value between adjacent piles also includes:

[0027] Obtain the soil compression index determined by indoor compression tests, the initial void ratio of the soil determined by the geological survey report, and the additional stress at the pile bottom calculated based on the pile end resistance;

[0028] Based on the soil compression index, the initial void ratio of the soil and the additional stress at the pile bottom, the Terzaghi one-dimensional consolidation theory is used to obtain the principal consolidation settlement of a single pile under a preset time length. Based on the principal consolidation settlement of a single pile under a preset time length multiplied by the corresponding degree of consolidation, the actual principal consolidation settlement of a single pile under a preset time length is obtained.

[0029] Based on the additional stress at the pile bottom and the pile length and pile spacing in the pile design parameters, the additional stress increment caused by the construction of adjacent piles at a specified location is obtained.

[0030] Based on the actual principal consolidation settlement of the single pile and the additional stress increment, the predicted value of the settlement difference between adjacent piles is obtained.

[0031] Specifically, the optimization process of the differential settlement prediction model includes:

[0032] Based on the predicted settlement difference between adjacent piles, combined with the pore water pressure value and pile top settlement data from the real-time monitoring data, the differential settlement test verification value is obtained.

[0033] The measured value of the settlement difference between adjacent piles in the dynamic feedback data obtained by the control feedback module is directly compared with the predicted value of the settlement difference between adjacent piles. The instantaneous prediction deviation value of the settlement prediction model is obtained by calculating the absolute difference between the two.

[0034] Based on the judgment result that the instantaneous prediction deviation value exceeds the preset error threshold, the optimized differential settlement prediction model is obtained by iteratively adjusting the soil compression index in the Terzaghi one-dimensional consolidation theory or the stress diffusion coefficient in the Mindlin stress solution, with the differential settlement test verification value and the measured value of the settlement difference between adjacent piles as the optimization target.

[0035] Specifically, the soil displacement control threshold includes a first displacement threshold and a second displacement threshold, wherein the first displacement threshold is less than the second displacement threshold;

[0036] The generation of construction control instructions includes:

[0037] When the predicted value of the radial displacement of the soil is less than or equal to the first displacement threshold, a first control command is generated, wherein the first control command is to keep the pile driving speed less than or equal to the first speed threshold.

[0038] When the predicted radial displacement of the soil is greater than the first displacement threshold and less than or equal to the second displacement threshold, a second control command is generated. The second control command is to reduce the pile driving speed to the second speed threshold and start the pressure relief hole to drain water.

[0039] When the predicted radial displacement of the soil is greater than the second displacement threshold, a third control command is generated. The third control command is to suspend pile driving and start double-liquid grouting around the pile.

[0040] Wherein, the first displacement threshold and the second displacement threshold are preset values, and the first displacement threshold is less than the second displacement threshold;

[0041] The spacing of the pressure relief holes is determined by a linkage optimization algorithm based on the predicted radial displacement of the soil, the equivalent radius of the pile in the pile design parameters, and the preset allowable displacement value.

[0042] Specifically, generating construction control instructions also includes:

[0043] The predicted settlement difference between adjacent piles obtained by the settlement prediction module is compared with a preset settlement difference warning threshold for judgment.

[0044] When it is determined that the predicted settlement difference between adjacent piles is greater than or equal to the settlement difference warning threshold, a fourth control instruction is generated, including: based on the grouting volume compensation calculation formula, using the predicted settlement difference between adjacent piles, the area of ​​influence around the pile, and the soil layer correction coefficient as input, calculating and determining the benchmark grouting volume for the bearing pile end compensation grouting, and simultaneously determining the benchmark grouting pressure and benchmark stabilization time for the tension pile side compensation grouting.

[0045] Specifically, dynamically adjusting the benchmark values ​​of the construction parameters based on the deviation values ​​includes:

[0046] Based on the dynamic feedback data obtained by the control feedback module, a safety review and parameter fine-tuning are performed, specifically as follows:

[0047] The first deviation value, calculated based on the measured value of the soil radial displacement and the corresponding predicted value of the soil radial displacement, is compared with the first deviation tolerance. If the first deviation value continues to exceed the first deviation tolerance, a fifth control command is generated to trigger dynamic correction of the empirical formula coefficients in the soil squeezing effect prediction model.

[0048] Specifically, dynamically adjusting the benchmark values ​​of the construction parameters based on the deviation values ​​further includes:

[0049] The second deviation value, calculated based on the measured value of the settlement difference between adjacent piles and the corresponding predicted value of the settlement difference between adjacent piles, is compared with the second deviation tolerance. If the second deviation value continues to exceed the second deviation tolerance, a sixth control command is generated to trigger dynamic correction of the soil compression index or stress diffusion coefficient in the differential settlement prediction model.

[0050] Compared with the prior art, the beneficial effects of the present invention are:

[0051] This invention addresses the shortcomings of existing technologies by integrating regional historical data to dynamically correct the Vesic borehole enlargement theory model and the Terzaghi-Mindlin coupled model, achieving accurate prediction of soil displacement and differential settlement, providing reliable input for optimizing construction parameters. Based on this prediction result and a dual-path differential grouting strategy—namely, end-pressure grouting for bearing piles and side-compensation grouting for pull-out piles—combined with a triple-coordinated sealing structure for pile joints, differential settlement and joint leakage are actively controlled. Furthermore, through closed-loop feedback between real-time monitoring data and predicted values, the layout of pressure relief holes, pile driving speed, and grouting parameters are dynamically adjusted, achieving coordinated adaptive control of the construction process. Ultimately, these technologies work together to achieve overall effects such as reducing soil disturbance, ensuring coordinated deformation of pile foundations, and improving waterproofing reliability, while significantly improving construction efficiency and first-pass yield. Attached Figure Description

[0052] Figure 1 This is a flowchart of the dual-path grouting collaborative control system for differential settlement of bearing-pressure and tension-resistant piles in Embodiment 1 of the present invention.

[0053] Figure 2 This is a logical diagram illustrating the construction of the soil squeezing effect prediction model in Embodiment 1 of the present invention;

[0054] Figure 3 This is a logic diagram for constructing the differential settlement prediction model in Embodiment 1 of the present invention. Detailed Implementation

[0055] Example 1

[0056] Please see Figure 1The present invention provides an embodiment of a dual-path grouting collaborative control system for differential settlement of bearing-load-bearing and tension-resistant piles in buildings, comprising the following steps:

[0057] The data acquisition module is used to obtain geological survey data of the construction area, pile design parameters, and real-time monitoring data of the construction site to construct a construction time-series dataset.

[0058] The displacement prediction module is used to input the construction time series dataset into a dynamically parameter-corrected soil squeezing effect prediction model, and output the predicted radial displacement value of the soil and its influence range. The soil squeezing effect prediction model is constructed based on the modified Vesic hole enlargement theory, and dynamically corrected by introducing the pile driving speed influence coefficient, the static displacement theoretical value, and the group pile effect reduction coefficient. Specifically:

[0059] It should be further explained that the construction process of the soil squeezing effect prediction model in this embodiment includes:

[0060] Based on the modified Vesic hole enlargement theory, a static displacement calculation model is constructed. The static displacement calculation model uses soil shear modulus, initial horizontal stress and ultimate hole enlargement pressure as core input parameters to calculate the theoretical value of soil radial static displacement.

[0061] Using pile driving speed as the independent variable, a calculation model for the influence coefficient of pile driving speed is constructed. The calculation model for the influence coefficient of pile driving speed includes a foundation constant term and a linear correlation coefficient of pile driving speed.

[0062] Based on the formula for reducing the pile group effect, a calculation model for the pile group effect reduction coefficient is constructed. The calculation model for the pile group effect reduction coefficient takes the pile diameter and the pile spacing as input parameters, and includes the correlation coefficient of the pile group effect attenuation.

[0063] Based on the static displacement calculation model, the pile driving speed influence coefficient calculation model, and the group pile effect reduction coefficient calculation model, a soil squeezing effect prediction model is established through multiplicative coupling. The output of the soil squeezing effect prediction model is the predicted value of the radial displacement of the soil.

[0064] Parameters such as soil shear modulus, initial horizontal stress, ultimate borehole expansion pressure, actual pile driving speed, pile diameter, and pile spacing in the construction area are obtained and input into the soil squeezing effect prediction model to obtain the predicted value of soil radial displacement. Simultaneously, the measured value of soil radial displacement under the corresponding working condition is obtained, and the model prediction deviation between the predicted value and the measured value of soil radial displacement is calculated. If the model prediction deviation exceeds a preset error threshold, the basic constant term and the linear correlation coefficient of pile driving speed in the pile driving speed influence coefficient calculation model and the group pile effect attenuation correlation coefficient in the group pile effect reduction coefficient calculation model are dynamically adjusted according to the deviation. After iterative optimization, a soil squeezing effect prediction model with satisfactory accuracy is obtained.

[0065] The settlement prediction module is used to input the construction time series dataset into the differential settlement prediction model and output the predicted value of the differential settlement between adjacent piles. In this embodiment, the differential settlement prediction model is constructed based on the Terzaghi consolidation equation and the Mindlin stress decoupling, specifically as follows:

[0066] Based on Terzaghi's one-dimensional consolidation theory, a calculation model for the principal consolidation settlement of a single pile is constructed. The calculation model uses the soil compression index, the initial void ratio of the soil, and the additional stress at the pile bottom as core input parameters. The soil compression index is determined by indoor compression tests, the initial void ratio of the soil is determined by the geological survey report, and the additional stress at the pile bottom is calculated based on the pile end resistance. This model is used to calculate the principal consolidation settlement of a single pile under a preset time.

[0067] Based on the Mindlin stress solution, an additional stress increment calculation model is constructed. The additional stress increment calculation model takes the additional stress at the pile bottom, the pile length and the pile spacing in the pile design parameters as input parameters. The pile lengths are the lengths of the bearing pile and the tensile pile, respectively, and the pile spacing is not less than 5 times the pile diameter. This model is used to obtain the additional stress increment caused by the construction of adjacent piles at a specified location.

[0068] Based on the principle of stress superposition, a differential settlement theory prediction model is constructed. The differential settlement theory prediction model takes the output results of the single pile main consolidation settlement calculation model and the output results of the additional stress increment calculation model as inputs, and obtains the predicted value of the settlement difference between adjacent piles through algebraic summation.

[0069] A differential settlement test verification model was constructed. Based on the predicted value of the settlement difference between adjacent piles, the model combined with the pore water pressure value and pile top settlement data from real-time monitoring data. The differential settlement test verification value was obtained through a geotechnical centrifuge model test. The pore water pressure value was collected by a pore pressure gauge, and the pile top settlement data was collected by a distributed optical fiber sensor. The acceleration of the geotechnical centrifuge model test was 100 times the acceleration of gravity.

[0070] The measured value of the settlement difference between adjacent piles is acquired by the control feedback module and directly compared with the predicted value of the settlement difference between adjacent piles. The absolute difference between the two is calculated as the instantaneous prediction deviation value. If the instantaneous prediction deviation value exceeds the preset error threshold, the soil compression index in the Terzaghi one-dimensional consolidation theory or the stress diffusion coefficient in the Mindlin stress solution is iteratively adjusted with the experimental verification value of differential settlement and the measured value of the settlement difference between adjacent piles as the optimization target. After iterative convergence, the optimized differential settlement prediction model is obtained.

[0071] The parameter optimization module is used to determine the optimized construction parameter benchmark values ​​and generate construction control instructions based on the predicted value of the radial displacement of the soil and the predicted value of the settlement difference of the adjacent piles, and in combination with the preset soil displacement control threshold and settlement difference control threshold.

[0072] The control feedback module is used to respond to construction control commands and collect dynamic feedback data from the construction site in real time. It compares the dynamic feedback data with the corresponding predicted values, calculates the deviation value, and dynamically adjusts the benchmark values ​​of the construction parameters based on the deviation value, generating a real-time optimized set of construction parameters. The real-time optimized set of construction parameters is then converted into corresponding control commands for the construction equipment and distributed to the static pressure pile driver, grouting equipment, and waterproofing construction tools. These control commands drive the corresponding equipment to perform actions, achieving coordinated dynamic control of soil squeezing effect, differential settlement, and joint waterproofing during construction.

[0073] It should be further noted that the real-time monitoring data in this embodiment includes: pile driving speed, pile verticality, soil radial displacement, pore water pressure, and pile top settlement data.

[0074] The construction parameter benchmarks in this embodiment include: the spacing and depth parameters of the pressure relief holes, the interval driving sequence parameters of long piles and short piles, the basic parameters for post-grouting at the pile end of the bearing pile, the basic parameters for post-grouting at the pile side of the tension pile, and the triple waterproofing structural parameters of the bamboo joint of the pile body; wherein, the basic parameters for post-grouting at the pile end of the bearing pile include at least the grouting volume and water-cement ratio; the basic parameters for post-grouting at the pile side of the tension pile include at least the grouting pressure.

[0075] The dynamic feedback data in this embodiment includes at least the measured values ​​of the radial displacement of the soil and the measured values ​​of the settlement difference between adjacent piles.

[0076] In addition, the dynamic feedback data in this embodiment also includes the strain of the rubber waterstop and the stress data of the epoxy resin sealing layer in the joint sealing structure;

[0077] The set of real-time optimized construction parameters in this embodiment includes: pressure relief hole spacing dynamically optimized based on displacement prediction values, pile driving speed dynamically adjusted based on settlement difference, real-time grouting volume and pressure of bearing pile end compensation grouting, real-time pressure and stabilization time of tension pile side compensation grouting, and rubber pre-compression ratio, epoxy resin grouting pressure and stainless steel sleeve bolt pre-tightening force parameters in the triple sealing construction of the joint.

[0078] In one specific implementation, the construction sequence and borehole position parameter benchmark values ​​determined by the parameter optimization module correspond to the specific engineering implementation measures of skip-driving process and pressure relief hole layout: the skip-driving process requires long piles and short piles to be constructed alternately, and the distance between adjacent piles is not less than 5 times the pile diameter, so as to reduce the superimposed soil squeezing effect caused by group pile construction; pressure relief holes need to be preset in the short pile area, with a diameter of 200 mm, and the layout spacing adopts a standard grid of 2 m × 2 m, which reduces the pore water pressure and lateral squeezing pressure of the soil through active pressure relief; and the specific execution process of the control feedback module to dynamically adjust the construction parameters based on the real-time collected soil displacement feedback data is dynamic displacement monitoring, that is, by installing high-precision tilt sensors with a resolution of 0.001° at key positions of the pile body, the verticality of the pile body and the changes in soil displacement are captured in real time, and 0.5 mm per minute is used as the dynamic control threshold for pile driving speed. Once the monitoring data approaches the threshold, the pile driving speed is automatically adjusted to ensure that the soil disturbance during construction is within a controllable range.

[0079] Further explanation is needed; please refer to [link / reference]. Figure 2 The process for obtaining the predicted radial displacement of soil with dynamic parameter correction provided in this embodiment includes:

[0080] A101, based on the geological survey data obtained by the acquisition module, obtains the soil shear modulus, initial horizontal stress and ultimate borehole expansion pressure;

[0081] A102, based on the soil shear modulus, the initial horizontal stress, and the ultimate borehole enlargement pressure, the theoretical value of static displacement is calculated using the modified Vesic borehole enlargement theory, specifically as follows:

[0082] ;

[0083] in, The expression describes the radial displacement at a distance r from the pile center, where R is the equivalent pile radius, which is 0.25m in this embodiment. The ultimate borehole expansion pressure is set at 160 kPa in this embodiment. The initial horizontal stress is 60 kPa in this embodiment, and G is the soil shear modulus, which is 12 MPa in this embodiment.

[0084] A103. Obtain the pile driving speed, and based on the pile driving speed, calculate the pile driving speed influence coefficient using an empirical formula. The empirical formula is: ,in, This refers to the pile driving speed;

[0085] The empirical formula in this embodiment is obtained by digitizing regional construction experience data: by analyzing the measured data of similar projects in the target area over the past five years, the empirical formula for the influence coefficient of pile driving speed is obtained through regression analysis.

[0086] In real-time prediction, the system substitutes the monitored pile driving speed value into this formula to directly calculate K, which is more consistent with the local soft soil conditions. v The coefficient of determination R² = 0.93 of this empirical formula statistically confirms the high reliability of this empirical relationship, thus enabling the soil squeezing effect prediction model to be dynamically corrected and regionally calibrated based on local engineering experience.

[0087] A104. Obtain the pile diameter and pile spacing. Based on the pile diameter and pile spacing, calculate the pile group effect reduction coefficient using the pile group effect reduction formula. Specifically: Where D is the pile diameter and s is the pile spacing; this embodiment uses a data-driven method to achieve regionalization and refinement of soil squeezing effect prediction: The adjustment coefficient for reducing the pile group effect is set and adjusted by those skilled in the art based on actual working condition data;

[0088] Furthermore, in this embodiment, when a conventional construction condition occurs where the pile spacing s ≥ 3D, the system, based on the pile diameter and pile spacing, calls historical data to construct an empirical function K for pile data correction from the regional database. g =1- Calculate the reduction factor for the pile group effect using 0.25 (D / s); The experience adjustment coefficient set by the technical personnel of this application based on historical experience data;

[0089] At the same time, when the compression modulus E is identified s For hard shell layers with a strength ≥25MPa, an automatic correction is triggered, multiplying the predicted radial displacement of the soil by a stiffness correction factor of 0.85, thereby quantifying the constraint effect of the hard shell layer on the displacement.

[0090] The application scenarios corresponding to the two group pile effect reduction coefficients in this embodiment are hierarchically adapted and complementary: among which The general formula derived from theory is applicable to the calculation of group pile effect reduction under various pile spacing conditions; another K g =1- 0.25 (D / s) is an empirical formula constructed based on regional historical engineering data, and it is only applicable to conventional construction conditions where the pile spacing is not less than 3 times the pile diameter.

[0091] A105, the first intermediate displacement value is obtained by multiplying the theoretical value of static displacement with the influence coefficient of pile driving speed;

[0092] A106, based on the multiplication of the first intermediate displacement value and the reduction coefficient of the pile group effect, the predicted value of the soil radial displacement is obtained, specifically: ,in This represents the predicted radial displacement of the soil.

[0093] This embodiment also provides the optimization process for the soil squeezing effect prediction model, including...

[0094] A107, Obtain the measured value of the radial displacement of the soil, and calculate the model prediction deviation value based on the measured value of the radial displacement of the soil and the predicted value of the radial displacement of the soil.

[0095] A108, based on the judgment result that the predicted deviation value of the model exceeds the preset error threshold, dynamically adjust the coefficients of the empirical formula or the group pile effect reduction formula to obtain the optimized soil squeezing effect prediction model.

[0096] The soil squeezing effect prediction model is based on the modified Vesic borehole enlargement theory. By clarifying the values ​​of key parameters such as soil shear modulus and initial horizontal stress and substituting them into the theoretical formula to calculate the theoretical value of static displacement, it solidifies the theoretical foundation of the prediction and ensures the scientific nature of displacement calculation under static conditions. For the dynamic characteristics of pile driving, an empirical formula for the pile driving speed influence coefficient is obtained by regressing measured data from similar projects in the target area over the past five years. This quantifies regional construction experience data, making the calculation of the pile driving speed influence coefficient more consistent with local soft soil conditions. Simultaneously, it endows the model with dynamic correction capabilities based on local experience, effectively quantifying the dynamic impact of pile driving speed on soil squeezing displacement. Combining pile diameter and pile spacing parameters, the model calls empirical functions from the regional database to calculate the group pile effect reduction coefficient. For hard shell layers (Es≥25MPa), it automatically triggers stiffness correction, multiplying the predicted radial displacement value of the soil by a correction factor of 0.85. Through a data-driven method, it achieves a refined adaptation of the group pile effect to the stratum characteristics, quantitatively reflecting the constraint effect of the hard shell layer and solving the impact of soil variability on prediction accuracy. Finally, the model compares the theoretical value of static displacement with K... v K g The predicted value is obtained by step-by-step coupled calculation of the coefficients, and the formula coefficients are dynamically adjusted based on the measured deviations, forming a closed-loop mechanism of "theoretical calculation - regional calibration - dynamic optimization". This enables the soil squeezing effect prediction model to not only rely on the classical hole expansion theory to ensure the rationality of the prediction, but also to adapt to the engineering characteristics and soil variability of soft soil areas through regionalized empirical formulas, stratum adaptive correction and real-time deviation calibration. This greatly improves the accuracy and reliability of soil squeezing effect prediction, and provides precise technical support for displacement control and scheme optimization in pile foundation construction.

[0097] Further explanation is needed; please refer to [link / reference]. Figure 3 The process of obtaining the predicted settlement difference value between adjacent piles in this embodiment also includes:

[0098] B101, the soil compression index, which characterizes the compressibility of the soil, is obtained through indoor consolidation tests. The initial void ratio, which characterizes the initial state of the soil, is obtained through geotechnical test reports. Based on the characteristic value of the vertical compressive bearing capacity of a single pile in the pile design parameters, and according to the relationship between total stress and additional stress in the bearing capacity theory of the pile tip bearing stratum, the initial self-weight stress of the soil at the pile tip is deducted from the characteristic value of the bearing capacity to obtain the additional stress at the pile bottom that acts on the soil below the pile tip plane and causes compressive deformation.

[0099] The soil compression index and the initial void ratio are used to drive the Terzaghi one-dimensional consolidation theory to calculate the principal consolidation settlement of a single pile.

[0100] The additional stress at the pile bottom is simultaneously used as a common load input for the Terzaghi one-dimensional consolidation theory and the Mindlin stress solution, so as to obtain the settlement component and stress increment respectively, and then couple them to obtain the theoretical prediction value of differential settlement.

[0101] B102, based on the soil compression index, the initial void ratio of the soil, and the additional stress at the pile bottom, the Terzaghi one-dimensional consolidation theory is used to calculate the effective stress growth process of the foundation soil layer under load, thereby obtaining the principal consolidation settlement of a single pile over a preset time period. The actual principal consolidation settlement of a single pile over a preset time period is obtained by multiplying the principal consolidation settlement of the single pile over the preset time period by the corresponding degree of consolidation. The Terzaghi one-dimensional consolidation theory is as follows: S c The principal consolidation settlement of a single pile is the core output result obtained by calculation using the Terzaghi one-dimensional consolidation theory, used to characterize the principal settlement component of a single pile foundation over time under the action of the additional stress.

[0102] It should be noted that the calculation of the main consolidation settlement of a single pile reflects the degree of soil consolidation at different time intervals through the consolidation time coefficient, thereby obtaining the settlement at the corresponding time point. This reflects the process of settlement development over time, and the above parameters are the basic input items for calculating the consolidation time coefficient and the corresponding settlement in this theory. The degree of consolidation in this embodiment is obtained by combining the consolidation time coefficient (which is calculated by those skilled in the art based on the soil consolidation coefficient, consolidation time, and compressibility layer thickness H) with the correspondence of Terzaghi's one-dimensional consolidation theory. Specifically, for soil layers with single-sided or double-sided drainage, the consolidation completion ratio of the soil at that moment can be determined by referring to the theoretical curve of the degree of consolidation and the consolidation time coefficient in Terzaghi's one-dimensional consolidation theory based on the value of the consolidation time coefficient.

[0103] C cThe soil compression index is determined by indoor compression tests. This parameter is obtained through indoor consolidation tests and is a core soil mechanical index characterizing the compressibility of the bearing layer at the pile tip. Its value directly determines the amount of volume compression of the soil under load.

[0104] H refers to the thickness of the compressible layer within the main influence range of the additional stress at the pile end. Its determination depends on the division of the bearing layer and the underlying layer in the geological exploration data. It is an important geometric parameter for calculating the cumulative settlement.

[0105] The initial void ratio of the soil, determined by the geological survey report, is taken as 1.2. This parameter is obtained directly from the geological survey report and characterizes the initial compaction state of the soil before loading; it is one of the base parameters for calculating settlement.

[0106] The initial effective stress refers to the in-situ initial effective self-weight stress of the soil at the pile tip before construction. Its value is calculated based on the soil unit weight and groundwater level in the geological survey report and is the benchmark for calculating stress increment.

[0107] The additional stress at the pile bottom is determined based on the pile end resistance. In this embodiment, the value is 80 kPa. This parameter is obtained by back-calculating the pile body design bearing capacity after deducting the initial self-weight stress at the pile end. It represents the net load increment transmitted from the pile to the bearing layer and causing compression.

[0108] B103, based on the additional stress at the pile bottom and the pile length and pile spacing in the pile design parameters, the Mindlin elastic theory stress solution is used to calculate the distribution of vertical additional stress caused by vertical concentrated force in a homogeneous elastic semi-infinite body, and to obtain the additional stress increment caused by the construction of adjacent piles at a specified location.

[0109] It should be further explained that this embodiment uses the stress solution of Mindlin's elasticity theory to calculate the distribution of vertical additional stress caused by vertical concentrated force in a homogeneous elastic semi-infinite body, including:

[0110] B1031, based on the additional stress at the pile bottom, the vertical load applied to the pile end of the adjacent pile is equivalent to a vertical concentrated force acting at the depth of the pile end of the adjacent pile;

[0111] B1032, based on the pile design parameters, obtain the spatial coordinates of the target pile end plane, the pile length and spatial coordinates of the adjacent piles, and the pile spacing vector between the target pile and the adjacent piles;

[0112] B1033, based on the magnitude of the vertical concentrated force, the depth of the adjacent pile tip, the horizontal component of the pile spacing vector, and the difference in pile tip depth between the target pile and the adjacent pile, the classical analytical solution of Mindlin elasticity theory regarding the vertical additional stress caused by the vertical concentrated force at any point in a homogeneous elastic semi-infinite body is called to calculate the first vertical additional stress component caused by the construction of a single adjacent pile at a specified position on the pile tip plane of the target pile;

[0113] B1034, traverse all adjacent piles that affect the target pile, repeat B1033, and obtain the second vertical additional stress component, the third vertical additional stress component, up to the Nth vertical additional stress component caused by the construction of each adjacent pile at the specified position.

[0114] B1035, based on the first vertical additional stress component, the second vertical additional stress component, up to the Nth vertical additional stress component, using the stress superposition principle, by algebraically summing all components, the additional stress increment caused by the construction of all adjacent piles at a specified position on the target pile end plane is obtained.

[0115] B104, based on the actual principal consolidation settlement of the single pile and the additional stress increment, a coupled calculation is performed using the stress superposition principle. The predicted settlement difference between adjacent piles is obtained by algebraically summing the settlement of each pile itself and the additional settlement caused by the influence of adjacent piles. Specifically:

[0116] B1041, obtain the additional stress at the bottom of the first target pile and the additional stress at the bottom of the second adjacent pile;

[0117] B1042, based on the additional stress at the bottom of the second adjacent pile, the depth of the pile tip of the second adjacent pile, the pile spacing between the first target pile and the second adjacent pile, and the depth of each layer of the first target pile body, the vertical stress solution of the Mindlin elastic theory is called to calculate the vertical additional stress value caused by the construction of the second adjacent pile at the midpoint of each layer of the first target pile body.

[0118] B1043, based on the thickness of each layer of the first target pile body, the compression modulus of the soil layer around the first target pile, and the vertical additional stress value at the midpoint of each layer of the first target pile body, the layer summation method is adopted. By multiplying the ratio of the vertical additional stress value of each layer to the compression modulus of the layer by the layer thickness and then summing them, the additional settlement of the first target pile caused by the construction of the second adjacent pile is obtained.

[0119] B1044, obtain the self-primary consolidation settlement of the first target pile;

[0120] B1045, add the self-main consolidation settlement amount to the influence additional settlement amount to obtain the total settlement amount of the first target pile under the influence of the second adjacent pile;

[0121] B1046, For the second adjacent pile, repeat B1042 to B1045 to obtain the total settlement of the second adjacent pile under the influence of the first target pile;

[0122] B1047, calculate the absolute value of the difference between the total settlement of the first target pile and the total settlement of the second adjacent pile, and obtain the predicted value of the settlement difference between adjacent piles between the first target pile and the second adjacent pile.

[0123] It should be further noted that this embodiment also provides an optimization process for the differential settlement prediction model, including:

[0124] B105. Based on the predicted settlement difference between adjacent piles, combined with the pore water pressure value and pile top settlement data in the real-time monitoring data, a geotechnical centrifuge model test is used for physical simulation verification. By reproducing the pile-soil interaction process under a high gravity acceleration field and measuring the settlement difference, the differential settlement test verification value is obtained.

[0125] It should be further explained that this embodiment uses a geotechnical centrifuge model test to physically simulate and verify the predicted settlement difference between adjacent piles, specifically including:

[0126] B1051. Based on the soil layer distribution and mechanical parameters in the geological survey data, and the pile length, pile diameter and pile spacing in the pile design parameters, the scale of the scaled model is determined, and model soil material that matches the physical and mechanical properties of the original soil is used to prepare a geotechnical centrifuge test model containing a simulated 32-meter long bearing pile and a 14-meter short tension pile arranged adjacent to each other.

[0127] B1052, The geotextile centrifuge test model was installed in an NHRI-500gt geotextile centrifuge. The centrifuge was started and stabilized in a centrifugal acceleration field of 100 times the gravitational acceleration to obtain a soil self-weight stress field equivalent to the engineering prototype in the model; the specific setting parameters are shown in Table 1:

[0128] Table 1:

[0129]

[0130] B1053, under the condition of stable operation in the high gravity acceleration field, apply a preload equal to 1.3 times the characteristic value of the vertical compressive bearing capacity of a single pile to the adjacent pile combination in the test model to simulate the actual bearing state of the engineering pile;

[0131] B1054, during the application and maintenance of the preload, the pile top settlement data with an accuracy of ±0.1 mm is collected in real time by distributed fiber optic sensors deployed on the top of the model pile; at the same time, the pore water pressure data with a range of 200 kPa and an accuracy of 0.1% of the full scale is collected in real time by pore pressure gauges embedded in the soil around the pile.

[0132] B1055, based on the pile top settlement data collected by the distributed optical fiber sensor, calculate the settlement of the long bearing pile and the short tension pile after the load stabilizes, and calculate the settlement difference between the two, and use the difference as the verification value of the differential settlement test.

[0133] B106, Based on the measured value of the settlement difference between adjacent piles in the dynamic feedback data obtained by the control feedback module, the predicted value of the settlement difference between adjacent piles is directly compared, and the instantaneous prediction deviation value of the settlement prediction model is obtained by calculating the absolute difference between the two.

[0134] B107. Based on the judgment result that the instantaneous prediction deviation value exceeds the preset error threshold, the least squares parameter back analysis technique is adopted. By using the differential settlement test verification value and the measured value of the settlement difference between adjacent piles as the optimization target, the soil compression index in the Terzaghi one-dimensional consolidation theory or the stress diffusion coefficient in the Mindlin stress solution is iteratively adjusted to complete the training and parameter optimization of the differential settlement prediction model.

[0135] It should be further explained that the specific steps for training and optimizing the differential settlement prediction model using the least squares parameter back analysis technique in this embodiment include:

[0136] B1071, Set a set of parameters to be optimized, wherein the set of parameters to be optimized includes at least the soil compression index in the Terzaghi one-dimensional consolidation theory and the stress diffusion coefficient in the Mindlin stress solution;

[0137] In this embodiment, the selection to optimize the soil compression index and the stress diffusion coefficient is a targeted decision made based on the model error sources and engineering control requirements disclosed in the technical report of this application.

[0138] The soil compression index is the core constitutive parameter controlling the amount of settlement in Terzaghi's one-dimensional consolidation theory. Its value directly depends on the representativeness of the soil samples from the laboratory test. However, the heterogeneity of the soil in the field leads to significant spatial variability of this parameter, which is one of the main sources of deviation in theoretical settlement prediction.

[0139] The stress diffusion coefficient is a key parameter in the Mindlin stress solution that characterizes the attenuation law of load transmission in the soil. Its theoretical value is based on the assumption of homogeneous elasticity. However, hard interlayers, lenses, or anisotropic properties in actual soil layers can significantly change the stress diffusion path, leading to inaccurate calculation of the additional stress caused by the influence of adjacent piles.

[0140] Therefore, by using the centrifuge test verification value and the field measured value as targets, and by simultaneously optimizing the two mechanism parameters that respectively dominate "self-settlement" and "interaction" through back analysis, it is possible to most directly and effectively correct the model's description of soil compression characteristics and load transfer law, so that the differential settlement prediction is close to both the physical mechanism and engineering reality. This is the theoretical basis for achieving precise and coordinated control in this application.

[0141] B1072 defines a comprehensive objective function, which is a weighted sum of a first deviation sum of squares and a second deviation sum of squares; wherein, the first deviation sum of squares is calculated based on the predicted value of the settlement difference between adjacent piles output by the differential settlement prediction model and the verified value of the differential settlement test; the second deviation sum of squares is calculated based on the predicted value of the settlement difference between adjacent piles output by the differential settlement prediction model and the measured value of the settlement difference between adjacent piles.

[0142] B1073, Based on the differential settlement prediction model under the current parameter set, the corresponding predicted values ​​of the differential settlement between adjacent piles are calculated respectively;

[0143] B1074, Based on the predicted value of the settlement difference between adjacent piles, the verified value of the differential settlement test, and the measured value of the settlement difference between adjacent piles, calculate the current value of the comprehensive objective function;

[0144] B1075, the gradient descent method is used to iteratively adjust the parameter values ​​in the set of parameters to be optimized, and B1073 and B1074 are repeated after each adjustment to recalculate the value of the comprehensive objective function;

[0145] B1076, repeat B1075 until the value of the comprehensive objective function is less than the preset convergence threshold or the number of iterations reaches the preset upper limit, and determine the corresponding parameter set at this time as the final optimized parameters, thus completing the training and parameter optimization of the differential settlement prediction model.

[0146] The differential settlement prediction model provided in this embodiment significantly improves the mechanism adaptability, accuracy, and engineering practicality of differential settlement prediction for pile foundations through a full-process technical design involving theoretical coupling, physical verification, and dynamic optimization. The core effects are derived based on the following technical principles:

[0147] The differential settlement prediction model uses Terzaghi's one-dimensional consolidation theory and Mindlin's elastic theory stress solution as its dual cores. It obtains the soil compression index and initial void ratio through indoor tests, and combines the additional stress at the pile tip (calculated by deducting the initial self-weight stress, which is 80 kPa in this example) to drive theoretical calculations. It not only relies on Terzaghi theory to accurately capture the time development characteristics of the main consolidation settlement of a single pile, but also uses Mindlin stress solution to convert the load of adjacent piles into equivalent vertical concentrated forces. Through spatial coordinate positioning, stress component calculation and superposition principle, it quantifies the additional stress increment caused by the construction of adjacent piles. Then, it couples the layered summation method to achieve accurate superposition of the pile's own settlement and the additional settlement caused by adjacent influences, which solves the technical pain point of traditional models that cannot take into account the settlement of a single pile and the interaction of pile groups.

[0148] A model containing a combination of long and short piles was prepared using an NHRI-500gt geocentrifuge with 100 times gravity field test and equivalent materials with undisturbed soil properties. A preload of 1.3 times bearing capacity was applied, and data was collected by distributed fiber optic sensors and pore pressure gauges to provide high-precision physical verification basis for theoretical prediction, effectively making up for the difference between the pure theoretical model and the engineering prototype.

[0149] The least squares parameter back analysis technique is adopted, and a weighted comprehensive objective function is constructed using centrifuge test verification values ​​and field measured values. The soil compression index, which dominates its own settlement, and the stress diffusion coefficient, which dominates load transfer, are optimized in a targeted manner. The model is iteratively converged through gradient descent (until the objective function is less than the convergence threshold), and the parameter deviations caused by soil heterogeneity and anisotropy are dynamically corrected. This forms a closed-loop mechanism of "theoretical coupled calculation - physical simulation verification - dynamic parameter optimization", which enables the model to not only conform to the core mechanism of soil consolidation and stress transfer, but also to adapt to complex field strata conditions. This significantly improves the reliability of differential settlement prediction and provides precise technical support for settlement control, structural safety protection, and construction scheme optimization in pile foundation engineering.

[0150] It should be further explained that the generation of construction control instructions in this embodiment includes:

[0151] C1011. When the predicted value of the radial displacement of the soil is less than or equal to the first displacement threshold, a first control command is generated. The first control command is to keep the pile driving speed less than or equal to the first speed threshold.

[0152] C1012. When the predicted radial displacement of the soil is greater than the first displacement threshold and less than or equal to the second displacement threshold, a second control command is generated. The second control command is to reduce the pile driving speed to the second speed threshold and start the pressure relief hole to drain water.

[0153] Specifically, based on the predicted radial displacement of the soil, the equivalent radius of the pile in the pile design parameters, and the preset allowable displacement value, the spacing of the pressure relief holes is calculated and determined through a linkage optimization algorithm.

[0154] In this embodiment, the spacing of the pressure relief holes is calculated and determined using a linkage optimization algorithm, specifically as follows: S j The optimized spacing for the j-th pressure relief hole refers to the spacing of the pressure relief holes calculated and output by the parameter optimization module based on this algorithm, used to guide on-site construction. Its theoretical calculation result is between 1.8 meters and 2.2 meters; R0 is the pile equivalent radius, which refers to the calculated value of the pile equivalent radius based on the pile diameter in the pile design parameters and considering the soil squeezing effect. In this embodiment, it is 0.25 meters, and is the basic geometric parameter for calculating the soil squeezing influence range; u adm The allowable displacement value refers to the pre-set control threshold for soil displacement according to engineering specifications and design requirements. In this embodiment, it is set to 5 mm, which is a static benchmark for judging whether the construction status is safe and whether optimization control measures need to be initiated.

[0155] Furthermore, when generating the second control command, the parameter optimization module in this embodiment performs the following linkage optimization steps:

[0156] Step 1: Based on the predicted radial displacement of the soil and combined with the preset location information of the ring sensor, construct a spatial distribution map of soil displacement within a 3-meter radius of the pile edge.

[0157] Step 2: Based on the spatial distribution map of soil displacement, when the displacement value in a certain direction exceeds 20% of the average displacement distribution value, the direction is determined to be the displacement concentration direction, and the displacement distribution gradient in that direction is calculated.

[0158] Step 3: Based on the preset pressure relief hole layout coordinates in the pile design parameters, select the pressure relief holes located within the ±45 degree fan-shaped area of ​​the displacement concentration direction and within 3 meters of the target pile edge, and determine them as the target pressure relief hole group.

[0159] Step four: Based on the displacement distribution gradient, the linkage optimization algorithm is invoked to calculate the optimized pressure relief intensity parameters for each pressure relief hole in the target pressure relief hole group. The specific calculation formula is: pressure relief valve opening adjustment coefficient. =0.5+0.1 Gradient value, where the gradient value is the displacement distribution gradient, and the opening adjustment coefficient. Used to regulate the drainage efficiency of the pressure relief hole;

[0160] Step 5: Based on the displacement distribution gradient, dynamically adjust the second velocity threshold of 0.6 meters per minute to generate a local deceleration command: for the displacement concentration area, the pile driving speed command value is... meters per minute;

[0161] Step six: The second control command sequentially integrates the coordinates and activation priority of the target pressure relief hole group, the real-time opening command of each pressure relief hole calculated based on the β value, and the local pile driving speed command of the displacement concentration area, forming a spatially differentiated collaborative control strategy package for the predicted high-risk area.

[0162] C1013. When the predicted value of the radial displacement of the soil is greater than the second displacement threshold, a third control command is generated. The benchmark value of the construction parameter corresponding to the third control command is to suspend pile driving and start double-liquid grouting around the pile.

[0163] Specifically, in this embodiment, the soil displacement is decomposed into three levels of control standards to form a quantitative construction response system, as shown in Table 2:

[0164] Table 2:

[0165]

[0166] The implementation process of graded control of soil squeezing effect in this embodiment constructs a closed-loop adaptive control system of monitoring-judgment-response-goal orientation; the system monitors the radial displacement of the soil in real time and performs precise control based on the following three-level criteria:

[0167] Efficiency guarantee zone (displacement value ≤ 9 mm): control the pile driving speed to ≤ 1.2 m / min for conventional construction.

[0168] The core performance indicator at this stage is to maintain optimal construction efficiency while ensuring that soil displacement is kept at a low risk level, and to avoid unnecessary delays caused by slowdowns.

[0169] Risk buffer zone (displacement value in the range of 9 to 14 mm): The system automatically reduces the pile driving speed to 0.6 meters per minute and simultaneously opens the preset pressure relief hole for active pressure relief.

[0170] The effectiveness indicators at this stage are rapid intervention and suppression of displacement growth trends. By combining "deceleration and pressure reduction" measures, a risk buffer is formed to prevent displacement from further expanding to the warning level, thus buying time for core control measures to respond.

[0171] Safety protection zone (displacement value ≥ 14 mm): The system immediately suspends pile driving construction and simultaneously initiates the double-liquid grouting procedure around the pile. The highest priority performance indicator at this stage is to ensure project safety and pile foundation stability. Suspending construction to block the source of disturbance, while simultaneously reinforcing the soil around the pile through grouting to form rigid constraints, is a fundamental safety guarantee measure to prevent the development of plastic deformation of the soil and avoid project risks.

[0172] In this embodiment, the grouting parameters for the bearing pile during the double-liquid grouting process are as follows: Automatic control formula for grouting volume: In this embodiment, the automatic grouting volume control formula represents the grouting volume to be determined at the pile tip of the bearing pile, D represents the designed target reinforcement diameter, which is 1.2 times the pile diameter in the pile design parameters, d represents the pile diameter in the pile design parameters, L represents the effective diffusion length of the grout in the soil below the pile tip along the pile axis, and its value is dynamically determined based on the soil permeability coefficient and void ratio parameters in the geological survey data through empirical relationships, and ρ represents the density of the grout, which is 1450 kg per cubic meter in this embodiment.

[0173] The underlying principle of this formula is to quantify the reinforcement target of "pear-shaped diffusion" into an equivalent hollow cylindrical geometric model with the pile body as the axis, outer diameter D, inner diameter d, and height L. By calculating the volume of this model and multiplying it by the grout density ρ, the macroscopic end resistance enhancement design is transformed into a precise grouting material dosage Q, thereby achieving closed-loop quantitative control from dynamic geological parameters to the determination of construction instructions.

[0174] The grouting parameters for the pull-out piles during the double-liquid grouting process around the piles in this embodiment are shown in Table 3 below:

[0175] Table 3:

[0176]

[0177] In this embodiment, the control logic for the two-liquid grouting of the pull-out pile is executed by the control feedback module, specifically divided into two progressive stages: initial grouting and re-grouting.

[0178] Initial injection stage: Use an injection pressure of 1.8 to 2.2 MPa and stabilize the pressure for at least 15 minutes to initially form a continuous reinforcement ring in the soil around the pile. At the same time, monitor the pile lifting amount (control value ≤ 0.5 mm per minute) to prevent the soil from splitting or the pile from floating too much due to excessive pressure.

[0179] If further reinforcement is needed based on real-time settlement monitoring feedback, the system automatically switches to the re-grouting stage, increasing the grouting pressure to 2.5 to 3.0 MPa and extending the pressure stabilization time to at least 30 minutes to further compact and expand the reinforcement ring. At this time, the uplift monitoring threshold is tightened to ≤0.2 mm per minute, achieving more precise control over the grouting energy input, thereby effectively improving the side friction resistance while ensuring the stability of the pile-soil system.

[0180] This multi-stage parameter control mechanism is the core execution logic for realizing "pulsating pressure-stabilized grouting technology" and achieving the goal of coordinated settlement control.

[0181] It should be further explained that, in the soil squeezing effect control process of this embodiment, refined construction management is achieved based on four core process parameters: First, the diameter of the pressure relief hole is designed with 300 mm as the benchmark, allowing a manufacturing and installation deviation of ±5 mm. Preliminary geometric verification is performed using prefabricated templates, and final spatial positioning verification is completed by combining three-dimensional laser scanning technology. Second, the depth of the pressure relief hole must ensure that it enters the hard plastic soil layer defined in the geological survey report by no less than 2 meters, allowing a negative construction deviation of 0.5 meters. During construction, a special casing with scale markings is used as a limiting device to intuitively control the drilling depth. Third, the pore water pressure dissipation rate is set to be no less than 70% of the initial pore water pressure, allowing fluctuations of ±5% in the monitored value. This indicator is continuously collected by an automatic pore water pressure gauge buried in the soil and fed back to the control system. Finally, the static pressure construction rate is strictly controlled within the range of 0.8 to 1.2 meters per minute, and the instantaneous rate fluctuation must not exceed 0.3 meters per minute. This requirement is achieved by dynamically adjusting the motor speed through a variable frequency pile driving system equipped with a closed-loop control program. The aforementioned multi-parameter collaborative control system together constitutes a key engineering measure to suppress the soil displacement effect.

[0182] C102. Based on the predicted settlement difference between adjacent piles obtained by the settlement prediction module, compare and determine with the preset settlement difference early warning threshold:

[0183] C1021. When it is determined that the predicted value of the settlement difference between adjacent piles is greater than or equal to the settlement difference warning threshold, a fourth control instruction is generated, including: based on the grouting volume compensation calculation formula, using the predicted value of the settlement difference between adjacent piles, the area of ​​influence around the pile and the soil layer correction coefficient as input, calculating and determining the benchmark grouting volume for the bearing pile end compensation grouting, and simultaneously determining the benchmark grouting pressure and benchmark stabilization time for the tension pile side compensation grouting;

[0184] The dual-path grouting compensation mechanism in this embodiment is shown in Table 4 below, specifically as follows:

[0185] Table 4:

[0186]

[0187] The dual-path grouting compensation mechanism in this embodiment originates from the mechanical concept of targeted compensation for the drastically different load transfer paths and failure modes of bearing piles and tension piles. Its core lies in actively modifying the pile-soil interface properties at specific locations using grout as a medium to precisely reinforce their respective weak points. Specifically, for bearing piles, the load is mainly transferred to the deep bearing layer through the pile tip. The underlying principle is to utilize pile tip grouting to form a cement-soil composite reinforcement with a "pear-shaped" spatial distribution centered on the pile tip through infiltration, splitting, and compression within the silty sand layer.

[0188] This enhancer achieves two key functions:

[0189] 1) Geometric effect: It significantly increases the diameter of the effective bearing area (up to 1.2D), transforming point-like end bearings into surface-like or even volume-like bearings;

[0190] 2) Material effect: Modifying the original silt into high-strength cement soil significantly improves the compression modulus and ultimate bearing capacity of the soil in the area.

[0191] formula It reveals the power-law relationship between the grouting volume Q and the diffusion radius R, which is essentially a manifestation of the transport and dissipation law of grout in porous media;

[0192] The parameters of grouting volume ≥1.5t and water-cement ratio 0.6 are the quantitative engineering thresholds to ensure the formation of a reinforcement with sufficient volume and high early strength. For short, tension-resistant piles, their bearing capacity is mainly provided by pile-soil skin friction. The underlying principle is to utilize pile-side grouting to form a continuous, dense, annular cement-soil solidification shell in the soil surrounding the pile. Its core logic is:

[0193] 1) Interface strengthening: The grout penetrates into the pile-soil contact surface and the pores of the adjacent soil. After solidification, it eliminates the micro-voids and partially transforms the originally potentially slippery frictional interface into a cohesive bonding interface.

[0194] 2) Soil reinforcement: The solidified shell (thickness ≥150mm) formed has a much higher strength than the original soil, which is equivalent to increasing the effective radial stiffness and roughness of the pile body, so that the tensile shear surface is transferred from the pile-soil interface to the interior of the reinforced soil with higher strength.

[0195] Grouting pressure ≥2MPa is the minimum energy requirement to overcome soil resistance and achieve effective penetration and micro-splitting. The essence of the pulsating pressure stabilization technology (fluctuation ≤±0.1MPa) lies in maintaining the pressure within the optimal window through dynamic balance, which can achieve continuous penetration without causing structural hydraulic splitting damage to the soil, thus ensuring the uniformity and continuity of the reinforcement ring.

[0196] In summary, the underlying logic of this mechanism is "targeted reinforcement" based on the load transfer path: for bearing piles, it strengthens the bearing area at their ends and the stiffness of the bearing layer; for pull piles, it strengthens the interfacial bonding performance on their sides and the shear strength of the surrounding soil. Through the synergistic effect of differentiated grouting parameters (volume vs. pressure) and core processes (pear-shaped diffusion vs. pulsating pressure stabilization), the vertical stiffness of adjacent long and short piles is essentially adjusted, thereby actively and precisely controlling their settlement difference, achieving a paradigm shift from "passively bearing differential deformation" to "actively coordinating deformation".

[0197] It should be further explained that in this embodiment, a fiber optic grating sensor network with an accuracy of ±0.1 mm is deployed on the top of the pile to collect settlement data in real time. When the monitored differential settlement gradient reaches or exceeds a preset warning threshold of 2 mm per meter, the system automatically triggers the grouting compensation program and, according to the control logic formula... Calculate the required compensation grouting volume; where Q comp This represents the amount of compensating grout to be injected (in liters). A represents the measured value of the settlement difference between adjacent piles obtained from real-time monitoring. s The value represents the area of ​​influence around the pile determined based on the pile diameter and the range of influence. K represents the soil layer correction factor determined based on geological survey data (for example, a value of 0.8 for silty soil layers).

[0198] It should be further explained that the process of dynamically adjusting the benchmark value of the construction parameters based on the deviation value in this embodiment includes:

[0199] C103. Based on the dynamic feedback data obtained by the control feedback module, perform safety verification and model parameter fine-tuning, specifically as follows:

[0200] C1031. A first deviation value is calculated based on the measured value of the soil radial displacement and the corresponding predicted value of the soil radial displacement, and compared with a first deviation tolerance; if the first deviation value continues to exceed the first deviation tolerance, a fifth control command is generated to trigger dynamic correction of the empirical formula coefficients in the soil squeezing effect prediction model.

[0201] Specific examples are as follows: When the system finds that the measured value of the radial displacement of the soil is consistently higher than the model prediction value and the deviation exceeds the allowable range during continuous construction of piles such as P12, P35 and P68, it determines that there is a difference between the regional geological conditions and the original empirical parameters. Then, it automatically triggers the iterative correction of the empirical formula coefficients, such as dynamically adjusting the regression parameters in the pile driving speed influence coefficient, so that the corrected model prediction is more in line with the actual response of the current site, thereby realizing the autonomous evolution of the prediction accuracy of the soil squeezing effect.

[0202] This embodiment boasts strong engineering practicality, directly employing measurable parameters such as pile driving speed and pile spacing. The calculation process requires only four arithmetic operations, avoiding reliance on complex finite element analysis while maintaining rigorous technical logic. It can be directly used to guide construction plan development. Its data is traceable, with key coefficients Kv and Kg sourced from statistical databases of several projects in the target area, while verification data comes from on-site measurements of this project, thus forming a complete closed-loop feedback system. The method's risk is highly controllable, with construction response thresholds set through clearly quantified graded control standards, and its prediction error range controlled within 5%, meeting the accuracy requirements of the JGJ106-2014 standard. On-site verification involved deploying five sets of displacement sensors with a range of ±50 mm and an accuracy of 0.1 mm in a ring at a distance of 3 meters from the pile edge to monitor soil displacement, simultaneously recording pile driving speed, depth, and hydraulic pressure values, ensuring the comprehensiveness and reliability of the verification data. Data comparison is shown in Table 5.

[0203] Table 5:

[0204]

[0205] The monitoring scheme in this embodiment uses five sets of displacement sensors with a range of ±50 mm and an accuracy of 0.1 mm, arranged in a ring at a distance of 3 meters from the pile edge, to simultaneously record the pile driving speed, depth, and oil pressure value, thus realizing the on-site measurement and verification of soil displacement. Data comparison shows that the theoretical prediction value for pile P12 is 11.6 mm, the measured value is 12.1 mm, and the error is +4.3%; the theoretical prediction value for pile P35 is 11.9 mm, the measured value is 11.7 mm, and the error is -1.7%; and the theoretical prediction value for pile P68 is 11.4 mm, the measured value is 11.9 mm, and the error is +4.4%. Based on this, it can be concluded that the prediction accuracy of the empirical formula reaches 95.2%, and the average absolute error does not exceed 5%, verifying the reliability and applicability of the soil displacement effect prediction model in actual engineering.

[0206] C1032. The second deviation value calculated based on the measured value of the settlement difference between adjacent piles and the corresponding predicted value of the settlement difference between adjacent piles is compared with the second deviation tolerance; if the second deviation value continues to exceed the second deviation tolerance, a sixth control command is generated to trigger dynamic correction of the soil compression index or stress diffusion coefficient in the differential settlement prediction model.

[0207] In this embodiment, the underlying principle of the deviation early warning mechanism is rooted in the phased adaptive closed-loop control theory. Its specific implementation logic is as follows: During the penetration phase, the control feedback module collects pile attitude data in real time through a high-precision tilt sensor. When the algorithm identifies that the verticality deviation is continuously greater than 0.5% within a continuous 3-meter penetration depth, the system determines that the pile body has a trend of deviation, and then generates and executes a "pile lifting and re-pressurization" command to eliminate the plastic displacement that has occurred. Simultaneously, it links the "axis correction" system to re-align the pile body.

[0208] During the pile splicing stage, the module obtains the planar coordinates of the pile section through the real-time differential positioning system. When the calculated planar positioning deviation of a single section exceeds 20 mm, it is determined that the pile splicing accuracy is out of tolerance, and an instruction is immediately generated to drive the "hydraulic fine-tuning device" to perform real-time pose compensation in three-dimensional space.

[0209] During the final pressing stage, the module integrates monitoring data on total displacement and pressure at the pile top. When the cumulative displacement at the pile top exceeds 8 mm, it is determined that the pile end bearing capacity is insufficient or that plastic flow has occurred in the soil around the pile. This generates a "dynamic pressure replenishment" command to adjust the final pile pressing force and simultaneously triggers the "pile grouting" program to solidify the soil with grout to provide additional lateral restraint and end reinforcement.

[0210] This mechanism constructs a complete adaptive control closed loop of "state perception - threshold judgment - precise execution" by setting quantitative perception thresholds (0.5%, 20 mm, 8 mm) that match the construction stage and corresponding physical intervention measures. It is the core control logic to ensure the final verticality and pile position accuracy of the pile foundation.

[0211] C104. Based on the measured strain values ​​of the rubber waterstop and the measured stress values ​​of the epoxy resin sealing layer in the joint sealing structure, compare them with their respective design allowable ranges; if any measured value exceeds its design allowable range, generate a seventh control command to trigger the adjustment of the construction parameters of the triple waterproof structure of the pile bamboo joint.

[0212] It should be further noted that, in this embodiment, when the control feedback module performs the aforementioned safety review and parameter fine-tuning, the following preventative linkage steps are also included:

[0213] When the measured value of the settlement difference between adjacent piles or the predicted value of the settlement difference between adjacent piles reaches a preset attention threshold that is lower than the settlement difference warning threshold, an eighth control command is generated.

[0214] The eighth control command is used to perform the following operations:

[0215] (1) Increase the frequency of collecting the measured strain values ​​of the rubber waterstop and the measured stress values ​​of the epoxy resin sealing layer in the joint sealing structure from the basic monitoring frequency to the preset high-frequency monitoring frequency.

[0216] (2) For the strain and stress measurement sequences collected at the high-frequency monitoring frequency, the signal time-frequency analysis algorithm is called for in-depth processing to identify their changing trends and abnormal fluctuation characteristics;

[0217] (3) Based on the identification results of the changing trend and abnormal fluctuation characteristics, generate and output the preventive inspection and maintenance recommendation parameters for the triple waterproof structure of the bamboo joint of the pile body.

[0218] It should be further noted that the control feedback module in this embodiment is also used to perform multi-objective cooperative arbitration, the specific steps of which include:

[0219] The priority order of the soil squeezing effect control command, the settlement coordination control command, and the pile safety control command is defined, wherein: the pile safety control command has the highest priority; the settlement coordination control command has the second highest priority; and the soil squeezing effect control command has the lowest priority.

[0220] When the control feedback module determines, based on the real-time judgment of the dynamic feedback data, that at least two of the following need to be generated simultaneously or continuously within a short period of time: the soil squeezing effect control command, the settlement coordination control command, and the pile body safety control command, the multi-objective coordinated arbitration is initiated.

[0221] The multi-objective collaborative arbitration generates and outputs a sorted and integrated final construction instruction sequence based on a preset priority order.

[0222] The final construction instruction sequence ensures that the highest priority construction instruction is generated and issued for execution first. During the execution of the highest priority instruction, the system continuously monitors relevant dynamic feedback data. Only after the execution conditions of the highest priority instruction are lifted can the system determine whether to generate and execute the next priority construction instruction based on arbitration logic.

[0223] In this embodiment, the pile safety control command corresponds to pile safety control. For example, the "pile lifting and re-pressurization + axis correction" command is triggered when the verticality deviation is greater than 0.5% within a continuous depth of 3 meters (i.e., exceeding the threshold in the "skewness warning mechanism"); or the "dynamic pressure replenishment + pile perimeter grouting" command is triggered when the cumulative value of the pile top displacement exceeds 8 mm.

[0224] In this embodiment, the settlement coordination control command corresponds to settlement coordination control. For example, a "dual-path compensation grouting" command containing specific grouting parameters is triggered when the measured settlement difference between adjacent piles reaches or exceeds a warning threshold of 3 mm.

[0225] In this embodiment, the soil squeezing effect control command corresponds to soil squeezing effect control. For example, a second control command is generated when the predicted radial displacement of the soil is in the range of 9 to 14 mm, which is "reduce speed to 0.6 m / min and activate pressure relief hole".

[0226] It should be further explained that the implementation process of the triple waterproof structure of the bamboo-joint joint of the bearing-bearing and tension-resistant pile in this embodiment includes:

[0227] Based on a preset pre-compression ratio, a preset compression force is applied to the EPDM rubber waterstop embedded in the bamboo joint, causing the rubber waterstop to undergo a preset compression deformation, thereby obtaining a pre-compressed sealing layer with a preset initial sealing contact stress.

[0228] The pre-compression rate is between 30% and 35%, exceeding the 15% requirement stipulated in industry standards. The material hardness of the EPDM rubber waterstop is 60HA, and the manufacturing deviation of this hardness is allowed to be ±5 degrees. The installation groove of the rubber waterstop is provided with a V-shaped guide groove structure to guide the possible seepage direction.

[0229] Based on the pre-set requirements for the impermeability grade and grouting density of the pile joint, high-pressure grouting is performed into the annular gap formed by the bamboo-joint assembly through a pre-set spiral grouting channel inside the joint. The grouting material is nano-modified epoxy resin. After the epoxy resin material is completely cured, a permeability coefficient of no more than 1×10⁻ is obtained. 9 Structural bonding interfaces with a strength of cm / s;

[0230] The nano-modified epoxy resin has a material impermeability grade of P12, which meets the national first-class waterproof standard.

[0231] Furthermore, in one embodiment of this invention, a spiral grouting channel is arranged inside the bamboo joint of the pile body, extending continuously in a spiral shape along the annular gap of the joint. The grout inlet of the grouting channel is located at the lower part of the joint, and the grout outlet is located at the upper part of the joint. A number of grouting microholes are evenly opened on the inner wall of the channel, and the microholes are evenly distributed throughout the annular gap. During the grouting construction, the epoxy resin material is continuously advanced along the spiral channel and diffuses evenly into the gap through the microholes, realizing all-round grouting and filling of all parts of the annular gap. From the structural design level, the grouting coverage and filling uniformity of the epoxy resin material in the joint gap are guaranteed.

[0232] Based on the preset requirements for sleeve structure strength and connection fastening force, a 316L stainless steel sleeve with a wall thickness of not less than 5 mm is used to externally wrap the bamboo joint that has been sealed. An initial preload of 350 N·m is applied using double-row M20 high-strength bolts. This preload allows for ±5% construction control deviation, thereby obtaining a mechanical locking band that can provide rigid mechanical restraint and long-term locking force.

[0233] The 316L stainless steel sleeve has a tensile strength of not less than 520 MPa; the butt joint end of the stainless steel sleeve is machined with a 45-degree chamfer structure, which is used to compensate for the ±1.5 mm axis alignment deviation that may occur during the on-site installation of the bamboo joint pile.

[0234] Based on the ultimate strain data of the EPDM rubber waterstop, the elastic modulus data of the cured nano-modified epoxy resin, the constraint stress data provided by the stainless steel sleeve, and the effective sealing length data of the rubber waterstop in the groove, mechanical compatibility calculations verify that the maximum allowable slippage at the joints of the triple waterproof structure is not less than 5 mm when subjected to external loads. This verification ensures the sealing reliability of the sealing system under 1.5 times the design pull-out force and ±3 mm slippage deformation.

[0235] Based on real-time collected epoxy resin grouting pressure data, adhesive layer continuity image data collected based on infrared thermal imaging technology, and bolt preload force data collected based on digital torque sensor, online quality judgment and feedback control are performed on the compression state of the pre-compression sealing layer, the grouting integrity of the structural bonding interface, and the fastening state of the mechanical locking band during and after construction.

[0236] The real-time monitoring alarm threshold for grouting pressure data is set to 0.3 MPa to 0.5 MPa; the infrared thermal imaging detection equipment has a detection resolution of 0.1 mm for the continuity of the adhesive layer; when the deviation between the actual value of the bolt preload force fed back by the digital torque sensor and the target value is greater than 3%, the system automatically triggers the bolt locking command.

[0237] The implementation process of coordinated control of displacement, settlement, and joint of bearing-bearing and tension-resistant piles involved in this embodiment includes:

[0238] D101. The control feedback module synchronously receives three types of real-time data from the acquisition module: the measured value of the radial displacement of the soil, the measured value of the settlement difference between adjacent piles, and the measured value of the strain of the rubber waterstop and the measured value of the stress of the epoxy resin sealing layer in the joint sealing structure.

[0239] D102. The control feedback module simultaneously receives the predicted value of the radial displacement of the soil from the displacement prediction module and the predicted value of the differential settlement between adjacent piles from the settlement prediction module.

[0240] D103. Based on the measured value of the radial displacement of the soil and the corresponding predicted value of the radial displacement of the soil, calculate the first deviation value and compare the first deviation value with the first preset displacement interval threshold.

[0241] D104. Based on the measured value of the settlement difference between adjacent piles and the corresponding predicted value of the settlement difference between adjacent piles, calculate and obtain the second deviation value, and compare the second deviation value with the preset settlement difference control threshold.

[0242] D105. Compare the measured strain values ​​of the rubber waterstop and the measured stress values ​​of the epoxy resin sealing layer with their respective preset design allowable ranges.

[0243] D106. When the first deviation value falls into the first preset displacement range, a first type of construction instruction is generated and output to maintain the current pile driving speed; when the first deviation value falls into the second preset displacement range, a second type of construction instruction is generated and output, which includes reducing the pile driving speed and activating the pressure relief hole; when the first deviation value falls into the third preset displacement range, a third type of construction instruction is generated and output, which includes pausing pile driving and activating double-liquid grouting around the pile.

[0244] D107. When the second deviation value reaches or exceeds the settlement difference control threshold, a fourth type of construction instruction is generated and output to trigger dual-path compensation grouting; the instruction simultaneously includes the grouting parameters at the pile end of the bearing pile and the grouting parameters on the pile side of the pull-out pile, which are determined according to the grouting volume compensation calculation formula.

[0245] D108. When either the measured strain value of the rubber waterstop or the measured stress value of the epoxy resin sealing layer exceeds its design allowable range, a fifth type of construction instruction is generated and output to adjust the construction parameters of the triple waterproof structure of the bamboo joint of the pile.

[0246] D109. The control feedback module integrates and prioritizes the first, second, third, fourth and fifth types of construction instructions to form a unified set of real-time optimized construction parameters.

[0247] D110. Convert the real-time optimized construction parameter set into corresponding equipment control commands and simultaneously send them to the static pressure pile driver, grouting equipment and waterproof construction tools.

[0248] D111, The static pressure pile driver receives instructions to adjust the pile driving speed or to pause; the grouting equipment receives instructions to perform pressure grouting and pressure stabilization control at the pile end or pile side; the waterproof construction tool receives instructions to adjust the pre-compression ratio, grouting pressure or bolt pre-tightening force of the joint sealing layer.

[0249] D112. Based on the new round of dynamic feedback data obtained after executing the device control command, the control feedback module repeatedly executes D101 to D111.

[0250] D113. If the first deviation value continues to exceed the preset model error tolerance, then the dynamic correction of the empirical formula coefficients in the soil squeezing effect prediction model is triggered.

[0251] D114. If the second deviation value continues to exceed the preset model error tolerance, then the least squares method is used to back-analyze and optimize the parameters of the soil compression index or stress diffusion coefficient in the differential settlement prediction model.

[0252] Through the above steps, the displacement control subsystem, settlement control subsystem, and joint waterproofing control subsystem, under the scheduling of the control feedback module, achieve collaborative operation based on shared real-time data and unified decision-making logic, jointly ensuring the controlled state of soil squeezing effect, differential settlement, and joint sealing performance during construction.

[0253] This embodiment achieves precise coordinated control of soil squeezing effect, differential settlement, and joint waterproofing performance by constructing a full-chain collaborative management and control system of "prediction-control-feedback-optimization". The core effects are derived from the following technical principles and methods: The system uses a data-driven prediction model as a prerequisite, dynamically corrects the soil squeezing effect prediction model based on regional experience data, and optimizes the parameters of the differential settlement prediction model through parameter back analysis to achieve advanced quantitative early warning of construction disturbance, providing accurate basis for proactive intervention. For the soil squeezing effect, a three-level graded control strategy is adopted (conventional construction in low-risk areas, deceleration + pressure relief holes in medium-risk areas, and pressure cessation + double-liquid grouting in high-risk areas). Through linkage optimization algorithms, the spacing and opening of pressure relief holes are accurately calculated, and the pile driving speed is dynamically adjusted. Combined with the phased parameter control and quantitative grouting volume formula of double-liquid grouting, a progressive control of "deceleration and pressure reduction - grouting reinforcement" is formed, which effectively suppresses soil plastic deformation, and the prediction error is controlled within the allowable range of the specification, meeting the industry accuracy requirements. To address differential settlement, a dual-path grouting compensation mechanism is employed. For bearing piles, grouting at the pile tip expands the bearing layer reinforcement; for tension piles, grouting along the pile side forms a reinforcing ring. This targeted reinforcement strengthens the weak points in load transfer for both types of piles, actively adjusting vertical stiffness to coordinate settlement differences. Combined with high-precision fiber optic sensors for real-time monitoring and triggering of compensation programs, this transforms the process from passively bearing deformation to actively coordinating it. For joint waterproofing, a triple waterproofing structure (pre-compression waterstop, epoxy sealing layer, and stainless steel sleeve) is used. Preset pre-compression ratios, spiral grouting channels, and rigid mechanical constraints ensure the reliability of the sealing system under load and displacement. High-frequency monitoring and thermal imaging detection enable process quality control. The system constructs a multi-objective collaborative arbitration mechanism through a control feedback module, prioritizing pile safety > settlement control > soil squeezing effect. It integrates various control commands and fine-tunes prediction model parameters in a closed loop, upgrading traditional decentralized experience-based control to data-driven collaborative intelligent control. This significantly improves construction controllability, engineering reliability, and intelligence, providing core technical support for multi-dimensional risk prevention and quality assurance in bearing and tension pile engineering.

[0254] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments under the guidance of the present invention without departing from the spirit and scope of the claims. All of these variations are within the protection scope of the present invention.

Claims

1. A dual-path grouting collaborative control system for differential settlement of bearing-load-bearing and tension-resistant piles in buildings, characterized in that, include: The data acquisition module is used to acquire geological survey data, pile design parameters, and real-time monitoring data of the construction area, and to construct a construction time-series dataset. The displacement prediction module is used to input the construction time series dataset into the soil squeezing effect prediction model to obtain the predicted value of the radial displacement of the soil; wherein, the soil squeezing effect prediction model is constructed based on the modified Vesic hole enlargement theory, and introduces the pile driving speed influence coefficient, the static displacement theoretical value and the group pile effect reduction coefficient for dynamic correction; The settlement prediction module is used to input the construction time series dataset into the differential settlement prediction model to obtain the predicted value of the settlement difference between adjacent piles; wherein, the differential settlement prediction model is constructed based on the Terzaghi consolidation equation and the Mindlin stress decoupling. The parameter optimization module is used to determine the optimized construction parameter benchmark values ​​and generate construction control instructions based on the predicted value of the radial displacement of the soil and the predicted value of the settlement difference of the adjacent piles, and in combination with the preset soil displacement control threshold and settlement difference control threshold. The control feedback module is used to respond to construction control commands and collect dynamic feedback data from the construction site in real time. It compares the dynamic feedback data with the corresponding predicted values, calculates the deviation value, and dynamically adjusts the benchmark values ​​of the construction parameters based on the deviation value to generate a set of construction parameters optimized in real time.

2. The dual-path grouting collaborative control system for differential settlement of bearing-pressure anti-uplift piles as described in claim 1, characterized in that, The real-time monitoring data includes: pile driving speed, pile verticality, soil radial displacement, pore water pressure, and pile top settlement data. The construction parameter benchmark values ​​include: the layout spacing and depth parameters of pressure relief holes, the interval skipping construction sequence parameters of long piles and short piles, the basic parameters of post-grouting at the pile end of bearing piles, the basic parameters of post-grouting at the pile side of tension piles, and the triple waterproof structure parameters of the bamboo joint of the pile body; among which, the basic parameters of post-grouting at the pile end of bearing piles include at least the grouting volume and water-cement ratio. The basic parameters for the back-side grouting of the tension pile include at least the grouting pressure; The dynamic feedback data includes at least the measured values ​​of the radial displacement of the soil and the measured values ​​of the settlement difference between adjacent piles. The set of real-time optimized construction parameters includes: pressure relief hole spacing dynamically optimized based on displacement prediction values, pile driving speed dynamically adjusted based on settlement difference, real-time grouting volume and pressure of bearing pile end compensation grouting, real-time pressure and stabilization time of tension pile side compensation grouting, and rubber pre-compression ratio, epoxy resin grouting pressure and stainless steel sleeve bolt pre-tightening force parameters in the triple seal construction of the joint.

3. The dual-path grouting collaborative control system for differential settlement of bearing-pressure and tension-resistant piles as described in claim 2, characterized in that, The process of obtaining the predicted radial displacement value of the soil includes: Obtain the soil shear modulus, initial horizontal stress, and ultimate borehole expansion pressure; Based on the soil shear modulus, the initial horizontal stress and the ultimate borehole expansion pressure, the theoretical value of static displacement is calculated using the modified Vesic borehole expansion theory. Obtain the pile driving speed, and calculate the pile driving speed influence coefficient based on the pile driving speed using an empirical formula; Obtain the pile diameter and pile spacing, and calculate the pile group effect reduction coefficient based on the pile diameter and pile spacing using the pile group effect reduction formula; The first intermediate displacement value is obtained by multiplying the theoretical value of static displacement with the influence coefficient of pile driving speed. The predicted value of the radial displacement of the soil is obtained by multiplying the first intermediate displacement value with the reduction coefficient of the pile group effect.

4. The dual-path grouting collaborative control system for differential settlement of bearing-pressure anti-uplift piles as described in claim 3, characterized in that, The optimization process of the soil displacement effect prediction model includes: Obtain the measured value of the radial displacement of the soil, and calculate the model prediction deviation value based on the measured value of the radial displacement of the soil and the predicted value of the radial displacement of the soil. Based on the judgment result that the predicted deviation value of the model exceeds the preset error threshold, the coefficients of the empirical formula or the group pile effect reduction formula are dynamically adjusted to obtain the optimized soil squeezing effect prediction model.

5. The dual-path grouting collaborative control system for differential settlement of bearing-pressure anti-uplift piles as described in claim 4, characterized in that, The process of obtaining the predicted settlement difference value of adjacent piles includes: Obtain the soil compression index determined by indoor compression tests, the initial void ratio of the soil determined by the geological survey report, and the additional stress at the pile bottom calculated based on the pile end resistance; Based on the soil compression index, the initial void ratio of the soil and the additional stress at the pile bottom, the Terzaghi one-dimensional consolidation theory is used to obtain the principal consolidation settlement of a single pile under a preset time. The actual principal consolidation settlement of a single pile under a preset time period is obtained by multiplying the principal consolidation settlement of the single pile by the corresponding degree of consolidation. Based on the additional stress at the pile bottom and the pile length and pile spacing in the pile design parameters, the additional stress increment caused by the construction of adjacent piles at a specified location is obtained. Based on the actual principal consolidation settlement of the single pile and the additional stress increment, the predicted value of the settlement difference between adjacent piles is obtained.

6. The dual-path grouting collaborative control system for differential settlement of bearing-pressure anti-uplift piles as described in claim 5, characterized in that, The optimization process of the differential settlement prediction model includes: Based on the predicted settlement difference between adjacent piles, combined with the pore water pressure value and pile top settlement data from the real-time monitoring data, the differential settlement test verification value is obtained. The measured value of the settlement difference between adjacent piles in the dynamic feedback data obtained by the control feedback module is directly compared with the predicted value of the settlement difference between adjacent piles. The instantaneous prediction deviation value of the settlement prediction model is obtained by calculating the absolute difference between the two. Based on the judgment result that the instantaneous prediction deviation value exceeds the preset error threshold, the optimized differential settlement prediction model is obtained by iteratively adjusting the soil compression index in the Terzaghi one-dimensional consolidation theory or the stress diffusion coefficient in the Mindlin stress solution, with the differential settlement test verification value and the measured value of the settlement difference between adjacent piles as the optimization target.

7. The dual-path grouting collaborative control system for differential settlement of bearing-pressure anti-uplift piles as described in claim 6, characterized in that, The soil displacement control threshold includes a first displacement threshold and a second displacement threshold, wherein the first displacement threshold is less than the second displacement threshold; The generation of construction control instructions includes: When the predicted value of the radial displacement of the soil is less than or equal to the first displacement threshold, a first control command is generated, wherein the first control command is to keep the pile driving speed less than or equal to the first speed threshold. When the predicted radial displacement of the soil is greater than the first displacement threshold and less than or equal to the second displacement threshold, a second control command is generated. The second control command is to reduce the pile driving speed to the second speed threshold and start the pressure relief hole to drain water. When the predicted radial displacement of the soil is greater than the second displacement threshold, a third control command is generated. The third control command is to suspend pile driving and start double-liquid grouting around the pile. Wherein, the first displacement threshold and the second displacement threshold are preset values, and the first displacement threshold is less than the second displacement threshold; The spacing of the pressure relief holes is determined by a linkage optimization algorithm based on the predicted radial displacement of the soil, the equivalent radius of the pile in the pile design parameters, and the preset allowable displacement value.

8. The dual-path grouting collaborative control system for differential settlement of bearing-pressure anti-uplift piles as described in claim 7, characterized in that, The generation of construction control instructions also includes: The predicted settlement difference between adjacent piles obtained by the settlement prediction module is compared with a preset settlement difference warning threshold for judgment. When it is determined that the predicted settlement difference between adjacent piles is greater than or equal to the settlement difference warning threshold, a fourth control instruction is generated, including: based on the grouting volume compensation calculation formula, using the predicted settlement difference between adjacent piles, the area of ​​influence around the pile, and the soil layer correction coefficient as input, calculating and determining the benchmark grouting volume for the bearing pile end compensation grouting, and simultaneously determining the benchmark grouting pressure and benchmark stabilization time for the tension pile side compensation grouting.

9. The dual-path grouting collaborative control system for differential settlement of bearing-pressure anti-uplift piles as described in claim 8, characterized in that, The step of dynamically adjusting the benchmark value of the construction parameters based on the deviation value includes: Based on the dynamic feedback data obtained by the control feedback module, a safety review and model parameter fine-tuning are performed, specifically as follows: The first deviation value calculated based on the measured value of the soil radial displacement and the corresponding predicted value of the soil radial displacement is compared with the first deviation tolerance. If the first deviation value continues to exceed the first deviation tolerance, a fifth control command is generated to trigger dynamic correction of the empirical formula coefficients in the soil squeezing effect prediction model.

10. The dual-path grouting collaborative control system for differential settlement of bearing-pressure anti-uplift piles as described in claim 9, characterized in that, The method of dynamically adjusting the benchmark value of the construction parameters based on the deviation value also includes: The second deviation value, calculated based on the measured value of the settlement difference between adjacent piles and the corresponding predicted value of the settlement difference between adjacent piles, is compared with the second deviation tolerance. If the second deviation value continues to exceed the second deviation tolerance, a sixth control command is generated to trigger dynamic correction of the soil compression index or stress diffusion coefficient in the differential settlement prediction model.

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