Method and system for reinforcing a stockyard ground in cooperation with vibro-compaction and geocell

Abstract

The application relates to the field of civil engineering, and discloses a stockyard foundation reinforcement method and system cooperating with vibration rolling and geocell, which comprises the following steps: constructing a three-dimensional digital twin model of the site based on geological information to determine an initial construction scheme; acquiring multi-dimensional data streams such as positioning, vibration response and equipment dynamics in real time during vibration rolling operation; calculating foundation stiffness indexes in real time based on the data streams and generating a thermal map to visually monitor the compaction state; further calculating a compaction efficiency ratio, and determining that the vibration rolling operation is completed when the compaction efficiency ratio meets a preset termination condition; and finally, reversely correcting the digital twin model by using the final measured data. The system comprises a model construction and pre-play module, an intelligent monitoring component, a state evaluation and decision module and a model closed-loop correction module. The application improves the construction quality, efficiency and economy of foundation reinforcement by constructing a closed-loop intelligent control process integrating prediction, monitoring, decision and optimization.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of civil engineering, in particular to a method and system for reinforcing a stockyard foundation by vibration rolling and geocell cooperation. BACKGROUND

[0002] In the construction of large-scale stockyards and other infrastructure, foundation treatment is a key link to ensure the long-term stability of the structure. Although traditional methods such as dynamic compaction or preloading are used, their inherent defects are increasingly prominent. Dynamic compaction can treat a certain depth of foundation, but it is limited by lower daily efficiency and has a greater impact on the surrounding environment due to its strong construction vibration. Preloading, on the other hand, requires months or even longer consolidation time, which severely restricts the progress of the project and results in poor economic efficiency. In addition, these traditional methods often do not work well when dealing with soft soil layers with high water content, and they generally have high energy consumption.

[0003] In order to improve the performance of the foundation, geocell, as a new type of geosynthetic material, is introduced into foundation reinforcement. However, in the prior art, the application of geocell often does not form an effective synergy with the subsequent compaction process. If the compaction process is not properly controlled, even if geocell is used, problems such as geocell relaxation, uneven filling, and overall depression of the cushion may occur, ultimately leading to poor internal drainage and insufficient overall bearing capacity, and failing to fully utilize the potential of three-dimensional constraint.

[0004] Therefore, the present application proposes a method and system for reinforcing a stockyard foundation by vibration rolling and geocell cooperation to solve the problems of the prior art. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a method and system for reinforcing a stockyard foundation by vibration rolling and geocell cooperation, which solves the problem of low construction efficiency, poor quality uniformity, and difficulty in fully utilizing the synergy effect of vibration rolling and geocell in foundation reinforcement construction due to the lack of real-time data feedback and intelligent process control.

[0006] To achieve the above purpose, the present application is implemented by the following technical solutions: The present application provides a method for reinforcing a stockyard foundation by vibration rolling and geocell cooperation, the method comprising the following steps:

[0007] S10, driving a pile into the foundation to be reinforced, and laying a geocell on the top surface of the pile and filling graded gravel filler to form a composite foundation structure;

[0008] S20, before construction, based on geological information, topographic information and the layout of the geocell and the pile in the composite foundation structure, a three-dimensional digital twin model of the site is constructed, and the compaction effect under different rolling parameter combinations is simulated in the three-dimensional digital twin model to determine an initial construction scheme;

[0009] S30, when the vibration roller is performing vibration rolling work on the graded broken stone filler in the composite foundation structure according to the initial construction scheme, the intelligent monitoring component installed on the vibration roller is used to obtain positioning data, vibration response data and equipment dynamics data at each position on the rolling path in real time, and a multi-dimensional physical response data stream is formed;

[0010] S40, based on the vibration response data in the multi-dimensional physical response data stream, the foundation stiffness index at each position on the rolling path is calculated in real time, and the positioning data is combined to generate a foundation stiffness thermal map of the compaction state of the entire construction area;

[0011] S50, according to the increment of the foundation stiffness index and the input work represented by the equipment dynamics data in the multi-dimensional physical response data stream, the compaction efficiency ratio of each position on the rolling path is calculated in real time, and when the compaction efficiency ratio meets the preset termination condition, it is determined that the vibration rolling work at the corresponding position is completed;

[0012] S60, after the vibration rolling work is completed, the soil mechanics parameters in the three-dimensional digital twin model are corrected in reverse by using the finally generated foundation stiffness thermal map and the collected multi-dimensional physical response data stream.

[0013] Preferably, step S10 specifically comprises:

[0014] S11, on the leveled foundation, the geocell is unfolded, tensioned and anchored by the pile;

[0015] S12, the graded broken stone filler is filled into the geocell in layers, wherein the maximum particle size of the graded broken stone filler is less than two-thirds of the height of the geocell;

[0016] S13, before the vibration rolling work is performed, the filled graded broken stone filler is subjected to at least one static pressure rolling.

[0017] Preferably, step S20 specifically comprises:

[0018] S21, according to the geological information, topographic information, geocell layout and pile layout, a three-dimensional grid model of the site is established, and soil mechanics parameters are assigned to the three-dimensional grid model;

[0019] S22, adopt a mechanical rock-soil coupling dynamics algorithm to simulate a plurality of different roller compaction parameter combinations on the three-dimensional grid model, the roller compaction parameter combinations including a roller compaction path, a driving speed, a vibration frequency and an amplitude;

[0020] S23, according to the simulation results of each roller compaction parameter combination, a set of roller compaction parameter combinations is selected as the initial construction scheme; wherein the simulation results at least include a predicted foundation stiffness distribution, an identified potential risk area and an estimated theoretical energy consumption.

[0021] Preferably, in step S30, the intelligent monitoring component includes:

[0022] a positioning data acquisition module;

[0023] an accelerometer mounted on the vibratory roller vibratory drum for acquiring the vibration response data;

[0024] a controller area network bus interface for acquiring the equipment dynamics data;

[0025] wherein the positioning data acquisition module is selected from at least one of the following:

[0026] a global navigation satellite system receiver, the global navigation satellite system receiver supports dual-frequency positioning;

[0027] an ultra-wideband positioning unit, the ultra-wideband positioning unit includes a plurality of ultra-wideband base stations deployed at the edge of the site and an ultra-wideband tag carried on the vibratory roller, and realizes three-dimensional positioning through a time-of-flight ranging algorithm;

[0028] a laser radar and simultaneous localization and mapping fusion unit, the laser radar is a hybrid solid-state laser radar, and the fusion unit generates a three-dimensional point cloud of the working area in combination with a mapping algorithm;

[0029] a global navigation satellite system / inertial navigation system tight coupling unit, the inertial navigation system tight coupling unit includes a dual-antenna real-time kinematic positioning and orientation module and an industrial-grade inertial measurement unit, and realizes positioning through baseband level data fusion.

[0030] Preferably, step S40 specifically includes:

[0031] S41, performing fast Fourier transform on the vibration response data synchronized with each positioning data timestamp acquired from the multi-dimensional physical response data stream to obtain the distribution of its energy at different harmonic frequency points;

[0032] S42, based on the obtained harmonic energy distribution, calculating the foundation stiffness index corresponding to each positioning data using a foundation stiffness index calculation formula to form a discrete data point set;

[0033] The formula for calculating the foundation stiffness index is as follows:

[0034] ;

[0035] In the formula, It is an index of foundation stiffness; The vibration response data of the first The energy of the first harmonic; The total energy of the vibration response data; This is an index for the order of harmonic analysis; This is the highest order of harmonic analysis;

[0036] S43. Using the Kriging space interpolation algorithm, the discrete data point set is processed to estimate the foundation stiffness index of the unmeasured areas within the entire construction area, forming gridded stiffness data covering the entire construction area.

[0037] S44. Color each stiffness value in the generated gridded stiffness data according to a preset color mapping table to generate the foundation stiffness heat map.

[0038] Preferably, step S50 specifically includes:

[0039] S51. Using the calculated foundation stiffness index as input, and combining the input work represented by the equipment dynamics data from the multidimensional physical response data stream, the compaction efficiency ratio is calculated using the compaction efficiency ratio calculation formula.

[0040] The formula for calculating the compaction efficiency ratio is:

[0041] ;

[0042] In the formula, For the first The compaction efficiency of rolling is higher than that of rolling. For the first The foundation stiffness index after compaction; For the first The foundation stiffness index after compaction; To complete the first The total mechanical work input during compaction; The index for the number of rolling passes;

[0043] S52, with the aforementioned compaction efficiency ratio As a criterion for judgment, when the compaction efficiency ratio Number of rolling passes When the rate of change is lower than the preset slope threshold, or when the compaction efficiency ratio is lower than the preset slope threshold, when the value of the vibration phase lock loss deviation is lower than a preset minimum effective threshold value, it is determined that the vibration rolling operation is completed.

[0044] Preferably, the method further comprises a spring phenomenon early warning step, which is performed in parallel during the execution of the steps S30 to S50, and specifically comprises:

[0045] By real-time monitoring of the vibration phase lock loss deviation and the driving power surge of the vibratory roller, the spring phenomenon occurring in the composite foundation structure during the rolling process is judged and warned, and when the warning is triggered, an instruction to adjust the working mode of the vibratory roller is automatically issued.

[0046] Preferably, the vibration phase lock loss deviation is monitored by:

[0047] A magneto-electric phase sensor is installed at the vibratory wheel shaft end of the vibratory roller, and a synchronous phase encoder is installed at the drive shaft end of the exciter of the vibratory roller, the magneto-electric phase sensor and the synchronous phase encoder are respectively electrically connected to the vehicle-mounted data acquisition unit through signal cables, and the phase difference signals of the vibratory wheel and the exciter are collected in real time to calculate the vibration phase lock loss deviation;

[0048] The driving power surge is monitored by:

[0049] Data communication is established between the engine control module of the vibratory roller and the controller area network (CAN) bus interface, and the engine output power, hydraulic system pressure and torque signal of the driving wheel of the vibratory roller are acquired in real time; and a torque sensor is installed at the output end of the gearbox of the vibratory roller, which is used to measure the torque value output by the gearbox in real time to obtain the measured torque data, and the measured torque data is sent to the vehicle-mounted controller through a wireless transmission module, the vehicle-mounted controller combines the measured torque data, the engine output power and the driving wheel speed data obtained through the CAN bus, and calculates the instantaneous power fluctuation value according to the following formula: The driving power surge is determined by comparing the rated power threshold value; wherein is the measured torque data, is the driving wheel angular velocity, is the transmission efficiency coefficient; the driving wheel speed data is converted to the driving wheel angular velocity according to the following formula: , is the driving wheel speed data;

[0050] The composite judgment and warning is realized by the following method:

[0051] ​A vibration phase lockout deviation threshold value and a driving power surge threshold value are preset; a multi-parameter fusion algorithm based on fuzzy logic is used to compare the real-time monitored vibration phase lockout deviation with the vibration phase lockout deviation threshold value and compare the real-time monitored driving power surge value with the driving power surge threshold value; when both of them exceed the corresponding threshold values at the same time and last for a predetermined length of time, the spring phenomenon is determined; a warning signal is sent through a vehicle-mounted sound and light alarm, and warning information is synchronously uploaded to a remote monitoring platform;

[0052] The adjustment working mode instruction automatically issued when the warning is triggered comprises:

[0053] The vehicle-mounted controller sends a frequency reduction instruction to the exciter through the CAN bus to reduce the excitation frequency to 50%-70% of the original frequency; at the same time, a speed reduction instruction is sent to the driving system to reduce the driving speed to 30%-50% of the original speed; if the warning is not removed within a preset time after adjustment, a shutdown instruction is automatically sent, and the operation is restarted after the foundation state is confirmed manually.

[0054] Preferably, step S60 specifically comprises:

[0055] S61, the finally generated foundation stiffness thermal map is taken as the real compaction result, and the compaction effect predicted by the initial soil body mechanical parameters in step S20 is compared to determine the compaction state prediction deviation between the prediction result of the three-dimensional digital twin model and the real compaction result;

[0056] S62, taking minimizing the compaction state prediction deviation as the target, an inversion analysis algorithm is used to iteratively adjust the dynamic elastic modulus and damping ratio parameters related to the compaction state of the composite foundation structure in the three-dimensional digital twin model;

[0057] S63, when the compaction state prediction deviation converges to below a preset threshold value, the finally adjusted dynamic elastic modulus and damping ratio parameters are solidified to the three-dimensional digital twin model, and the reverse correction is completed.

[0058] The second aspect of the application provides a stockyard foundation reinforcement system coordinated with vibration rolling and geocell, which is applied to the method described above, and the system comprises:

[0059] A model construction and pre-play module is used to construct a three-dimensional digital twin model according to input site foundation data and layout information of the composite foundation structure, and run a virtual pre-play to determine an initial construction scheme;

[0060] The intelligent monitoring assembly is configured on the vibratory roller, and the intelligent monitoring assembly comprises a set of sensing devices for collecting positioning data, vibration response data and equipment dynamics data of each position on a rolling path of the vibratory roller in real time when a composite foundation structure is subjected to vibratory rolling operation, so as to form a multidimensional physical response data stream.

[0061] The state evaluation and decision module is in communication connection with the intelligent monitoring assembly, is used for calculating a foundation stiffness index of each position on the rolling path and a compaction efficiency ratio in real time according to the multidimensional physical response data stream, and generating a completion judgment of the vibratory rolling operation according to a preset termination condition; and generating a foundation stiffness thermal map of a compaction state of the entire construction area according to the foundation stiffness index of each position on the rolling path and in combination with the positioning data.

[0062] The model closed-loop correction module is used for receiving the foundation stiffness thermal map generated by the state evaluation and decision module and the multidimensional physical response data stream collected by the intelligent monitoring assembly after the vibratory rolling operation is completed, and correcting the three-dimensional digital twin model reversely according to the foundation stiffness thermal map and the multidimensional physical response data stream.

[0063] 1. By constructing a three-dimensional digital twin model of the site before construction for simulation and rehearsal, and reversely correcting the model by using the measured data after construction, the present application establishes a technical system capable of self iteration and evolution; this makes the formulation of the construction scheme more scientific and forward-looking, and with the continuous accumulation of engineering data, the prediction of the geological conditions and the simulation of the compaction effect of the model will be more and more accurate, thereby systematically improving the planning level and risk avoidance ability of the subsequent engineering.

[0064] 2. The present application introduces a compaction efficiency ratio as the core evaluation and termination basis of the vibratory rolling operation. The index directly relates the effective increase of the foundation stiffness to the mechanical work input by the equipment, and realizes the change from reaching the quality to reaching the quality in an economic way; compared with the traditional method which depends on fixed rolling times or a single stiffness threshold, the present method can dynamically identify and terminate invalid or inefficient vibratory rolling operation, thereby improving the construction efficiency and reducing unnecessary equipment energy consumption.

[0065] 3. The present application generates a continuous foundation stiffness thermal map covering the entire construction area by combining high-precision positioning data and vibration response data of the vibratory wheel; this full-area, visual quality monitoring method replaces the traditional discrete, sampling detection method, and can identify local weak points and uneven areas without omission; this guarantees the comprehensive control of the compaction quality of the composite foundation structure, and is conducive to realizing the high uniformity and consistency of the construction quality.

[0066] 4、The spring phenomenon is monitored and warned in parallel, the real-time analysis of the key dynamic parameters of the vibrating road roller is carried out, the spring phenomenon can be predicted in the early stage, and the automatic adjustment of the working mode of the equipment is triggered, the active risk intervention mechanism can effectively avoid the structure damage and equipment damage risk caused by excessive vibration of the foundation, and the safety of the on-site operation is improved. BRIEF DESCRIPTION OF DRAWINGS

[0067] Figure 1 The method flowchart of the embodiment of the application is shown in the figure.

[0068] Figure 2 The front view schematic diagram of the composite foundation construction of the embodiment of the application is shown in the figure.

[0069] Figure 3 The top view schematic diagram of the composite foundation construction of the embodiment of the application is shown in the figure.

[0070] Figure 4 The embodiment of the application is shown in the figure. Figure 2 The enlarged composite foundation structure section schematic diagram of the embodiment of the application is shown in the figure.

[0071] Figure 5 The system function module block diagram of the embodiment of the application is shown in the figure.

[0072] Figure 6 The digital twin model closed-loop correction logic schematic diagram of the embodiment of the application is shown in the figure.

[0073] Figure 7 The foundation stiffness thermal diagram of the embodiment of the application is shown in the figure.

[0074] Figure 8 The compaction efficiency ratio change relationship curve schematic diagram of the embodiment of the application is shown in the figure.

[0075] Figure 9 The vibrating compaction path schematic diagram of the wide site of the embodiment of the application is shown in the figure.

[0076] Figure 10 The vibrating compaction path schematic diagram of the narrow site of the embodiment of the application is shown in the figure.

[0077] Explanation of reference numerals:

[0078] 1, geocell; 2, bamboo pile; 3, vibrating road roller; 4, graded gravel filler; 5, intelligent monitoring component;

[0079] 10, model construction and pre-performance module; 20, intelligent monitoring component; 30, state evaluation and decision module; 40, model closed-loop correction module. DETAILED DESCRIPTION

[0080] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the specification of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work belong to the scope of protection of the present application.

[0081] With reference to Figure 1 The embodiment of the present application provides a stockyard foundation reinforcement method based on vibration rolling and cooperation of geocell, comprising the following steps:

[0082] S10, driving a pile body on the foundation to be reinforced, and laying a geocell on the top surface of the pile body and filling graded gravel filler to form a composite foundation structure;

[0083] S20, before construction, based on geological information, topographic information, and the layout of the geocell and the layout of the pile body in the composite foundation structure, a three-dimensional digital twin model of the site is constructed, and the compaction effect under different rolling parameter combinations is simulated in the three-dimensional digital twin model to determine an initial construction scheme;

[0084] S30, when the vibration roller performs vibration rolling operation on the graded gravel filler in the composite foundation structure according to the initial construction scheme, the intelligent monitoring assembly installed on the vibration roller is used to obtain positioning data, vibration response data and equipment dynamics data at each position on the rolling path in real time, and a multi-dimensional physical response data stream is formed;

[0085] S40, based on the vibration response data in the multi-dimensional physical response data stream, the foundation stiffness index at each position on the rolling path is calculated in real time, and the positioning data is combined to generate a foundation stiffness thermal map of the compaction state of the entire construction area;

[0086] S50, according to the increment of the foundation stiffness index and the input work represented by the equipment dynamics data in the multi-dimensional physical response data stream, the compaction efficiency ratio of each position on the rolling path is calculated in real time, and when the compaction efficiency ratio meets the preset termination condition, it is determined that the vibration rolling operation at the corresponding position is completed;

[0087] S60, after the vibration rolling operation is completed, the soil mechanics parameters in the three-dimensional digital twin model are corrected in reverse by using the finally generated foundation stiffness thermal map and the collected multi-dimensional physical response data stream.

[0088] With reference to Figures 2 to 4, the constructed composite foundation structure includes a pretreated foundation surface layer, a geocell 1 laid on the foundation surface layer, a graded gravel filler 4 filled in the geocell 1, a pile for fixing the geocell 1, and a pile body for tensioning the geocell 1 during construction, the pile body being a bamboo pile 2 (there can also be a concrete pile, a steel pile, etc.); a vibratory roller 3 performs vibratory rolling work above the geocell 1 after filling the graded gravel filler 4.

[0089] As shown in Figure 5 , the vibratory rolling and geocell-coordinated stockyard foundation reinforcement system can include:

[0090] A model construction and pre-performance module 10 is configured to construct a three-dimensional digital twin model according to input site foundation data and layout information of the composite foundation structure, and to run a virtual pre-performance to determine an initial construction scheme.

[0091] An intelligent monitoring component 20 is a hardware set installed on the vibratory roller 3, and includes a set of sensing devices for collecting positioning data, vibration response data, and equipment dynamics data at each position on the rolling path of the vibratory roller 3 in real time during vibratory rolling work on the composite foundation structure, to form a multi-dimensional physical response data stream; the intelligent monitoring component 20 includes a high-precision positioning terminal, an acceleration sensor, and a Controller Area Network (CAN) bus interface.

[0092] A state evaluation and decision module 30 is in communication connection with the intelligent monitoring component 20, and is configured to receive and process the real-time multi-dimensional physical response data stream, to calculate a foundation stiffness index in real time, and to generate a foundation stiffness thermal map of the compaction state of the entire construction area according to the foundation stiffness index at each position on the rolling path, in combination with the positioning data; the real-time multi-dimensional physical response data stream includes the positioning data, the vibration response data, and the equipment dynamics data at each position on the rolling path acquired in real time; the state evaluation and decision module 30 is also configured to calculate a compaction efficiency ratio, and to determine whether the vibratory rolling work is completed according to a preset termination condition.

[0093] A model closed-loop correction module 40 is configured to receive the foundation stiffness thermal map generated by the state evaluation and decision module and the multi-dimensional physical response data stream collected by the intelligent monitoring component 20 after the vibratory rolling work is completed, and to correct the three-dimensional digital twin model in reverse according to the foundation stiffness thermal map and the multi-dimensional physical response data stream. Specifically, it receives the final measured data after construction is completed, corrects the soil mechanics parameters in the three-dimensional digital twin model through inverse analysis, and sends the corrected soil mechanics parameters to the model construction and pre-performance module 10.

[0094] Embodiment One

[0095] As Figure 1 shown, the method provided by the embodiment of the application constructs a closed-loop control process integrating prediction, monitoring, decision-making and optimization to accurately manage the quality and process of ground reinforcement.

[0096] The method first performs step S10 of physical construction of the composite foundation; this step is the physical basis for all subsequent intelligent vibration rolling operations; in the specific operation, geocell 1 is laid on the foundation, and graded gravel filler 4 is backfilled, so that the mechanical properties of the original foundation are changed, and a working object with specific initial conditions is provided for subsequent vibration compaction.

[0097] Before the physical construction starts, step S20 of digital twin pre-performance is performed; this step belongs to the feedforward control link, and the purpose is to predict the compaction effect through simulation to provide initial guidance parameters for actual operation; based on the geological survey data of the site, the mechanical parameters of the soil body and the equipment parameters (such as excitation force and vibration frequency) of the vibration roller 3, a three-dimensional finite element or discrete element dynamics model is constructed; by simulating the walking and vibration process of the vibration roller 3 in the virtual model, the compaction degree growth law of the foundation under different rolling passes and the final bearing capacity can be preliminarily predicted, so as to preset the initial operation scheme such as rolling path, speed and pass number.

[0098] After the on-site vibration rolling operation starts, the process enters the real-time monitoring and evaluation link, i.e. steps S30 and S40; in step S30, the intelligent monitoring component 5 installed on the vibration roller 3 continuously collects two types of data along the actual rolling path: one is the running state data of the roller itself, such as the acceleration response of the vibration wheel; the other is the real-time position coordinates of the roller obtained through the high-precision positioning terminal; these data constitute the input for quantitative evaluation of the compaction process.

[0099] In step S40, the data collected in step S30 is processed and analyzed in real time; by performing harmonic analysis on the vibration wheel acceleration signal, the response characteristics after interaction with the foundation are extracted, and the foundation stiffness index representing the dynamic mechanical properties of the foundation is calculated; combined with the position coordinates, the index is rendered on a two-dimensional plane, i.e. a foundation stiffness thermal map as Figure 7 shown is generated, realizing visual monitoring of the uniformity of the compaction quality of the construction area.

[0100] Based on the results of real-time evaluation, the method enters step S50 to make intelligent decisions for vibratory rolling operation; this step is the execution link of closed-loop control; its decision basis is not the absolute value of foundation stiffness alone, but the efficiency of compaction, i.e. the compaction efficiency ratio; by calculating the effective work done by the vibratory roller 3 on the foundation in a single pass of vibratory rolling operation, and the resulting increment of foundation stiffness value, the compaction efficiency ratio can be obtained; see Figure 8 The curve shown in the figure, when the ratio falls below the preset threshold, indicates that the reinforcement effect brought about by continued rolling is very small, at which point the system determines that the vibratory rolling operation in this area has been completed, and can instruct the operator to stop working, avoiding ineffective rolling and overloading.

[0101] Finally, the entire process realizes the final closed-loop feedback and model correction through step S60; after the construction of the entire site or a large area is completed, the final measured data of the foundation bearing capacity obtained on site through traditional detection methods (such as plate loading test) is compared with the prediction results of the digital twin model in step S20. If there is a deviation, an inversion analysis program is started to automatically iteratively adjust the initial soil mechanical parameters in the digital twin model with the goal of reducing the deviation; the corrected model can more accurately reflect the true engineering geological characteristics of the site, thereby providing more accurate pre-visualization results for subsequent construction in other areas, and realizing the continuous optimization and iteration of the technical model.

[0102] The above method is described in detail as follows:

[0103] In the composite foundation construction step of step S10, see Figure 2 , Figure 3 and Figure 4 This step constructs a composite foundation structure with preliminary bearing capacity and restraint capacity. The original foundation is leveled and the surface is pre-compacted; then, the geocell 1 is unfolded on the leveled foundation surface; the geocell 1 is made of high-density polyethylene (HDPE) material, the height of the cell sheet can be 150-200 mm, and the torch spacing can be 400-600 mm; to ensure that the geocell 1 remains open during filling, bamboo stakes 2 are used to punch into the ground at predetermined intervals around the perimeter and at specific internal nodes for tensioning and temporary fixation.

[0104] After the geocell 1 is tensioned and fixed, graded gravel filler 4 is filled into it; the graded gravel filler 4 uses continuous gradation, the maximum particle size is not greater than 2 / 3 of the height of the geocell, and is less than 100 mm, and the clay content is less than 5%; the filling process is carried out in layers, and the virtual paving thickness of each layer is matched with the compaction capacity of the vibratory roller 3.

[0105] In the digital twin pre-rolling step of step S20, the purpose of this step is to predict the compaction behavior under different construction schemes through numerical simulation before physical construction, so as to select a set of initial construction parameters. This step specifically includes the following processes:

[0106] Three-dimensional digital twin model construction, first, a high-fidelity three-dimensional digital twin model of the site is constructed. This process includes the following elements:

[0107] In the geometric modeling step, the three-dimensional topographic data of the site is imported as the basic geometry of the model.

[0108] In the geological modeling step, according to the geological survey report, the layered geological structure of the foundation is established in the model, and the geometric entities of the geocell 1 and the graded gravel filling 4 constructed in step S10 are accurately arranged.

[0109] In the material attribute and constitutive model assignment step, the initial physical and mechanical parameters of each layer of soil and graded gravel filling in the geological model are assigned, such as elastic modulus, Poisson's ratio, density, internal friction angle, cohesion, etc. A constitutive model suitable for describing the behavior of soil is defined, and in this embodiment, the Mohr-Coulomb or Drucker-Prager constitutive model is preferred.

[0110] In the mechanical geotechnical coupled dynamics simulation step, based on the constructed digital twin model, a mechanical geotechnical coupled dynamics algorithm is used to simulate multiple sets of rolling parameter combinations including different rolling paths, driving speeds, vibration frequencies and amplitudes.

[0111] In the road roller modeling step, the vibratory road roller 3 is modeled as a multi-body dynamics system with specific mass, moment of inertia and stiffness.

[0112] In the load and boundary application step, the excitation force applied by the vibratory drum of the vibratory road roller 3 is defined as a periodic load and applied to the surface of the graded gravel filling in the model. At the same time, appropriate boundary conditions such as non-reflecting boundary are set for the bottom and sides of the entire model.

[0113] In the transient dynamics analysis step, transient dynamics analysis is performed to simulate the propagation of vibratory waves in the soil as the vibratory road roller 3 moves according to the pre-set rolling path and driving speed, as well as the spatio-temporal evolution of the soil particle displacement field, stress field, strain field and density field caused thereby.

[0114] In the simulation result output step, for each rolling parameter combination, the simulation output compaction effect includes the predicted foundation stiffness distribution map, the potential risk area identified due to local stress concentration or excessive deformation, and the estimated theoretical energy consumption.

[0115] The initial construction scheme is determined by comparing multiple simulation results, and a set of rolling parameters that can achieve the best balance between ensuring compaction quality (optimal foundation stiffness), avoiding construction risks (minimum risk area), and considering economy (lower theoretical energy consumption) is selected as the initial construction scheme of step S30.

[0116] In other embodiments, the core numerical calculation method for simulation can be Finite Difference Method (FDM) or Boundary Element Method (BEM) in addition to Finite Element Method (FEM) or Discrete Element Method (DEM); the model for defining the soil constitutive can be Cambridge model or more complex elastic-plastic damage model in addition to Mohr-Coulomb model or Drucker-Prager model, which can better reflect the complex stress path.

[0117] In the multi-dimensional data real-time acquisition step S30, the intelligent monitoring assembly 20 (i.e. the aforementioned intelligent monitoring assembly 5) installed on the vibratory roller 3 synchronously collects multi-dimensional data when the vibratory roller 3 is working on site.

[0118] The intelligent monitoring assembly 20 is responsible for real-time acquisition of multi-dimensional physical response data on site, specifically including:

[0119] The positioning data acquisition module is used to acquire the three-dimensional coordinates and attitude of the vibratory roller in the construction site in real time. In different implementation scenarios, the positioning data acquisition module can select any one or a combination of the following technologies according to the needs of accuracy, cost and environmental adaptability:

[0120] (1) Global Navigation Satellite System (GNSS) receiver, GNSS receiver supports dual-frequency (L1+L5) positioning, horizontal positioning accuracy ≤0.1m, suitable for continuous high-precision positioning in open areas such as stockyard foundation.

[0121] (2) Ultra-Wideband (UWB) positioning unit, which includes multiple UWB base stations pre-deployed on the edge of the stockyard foundation and a UWB tag carried on the vibratory roller. Three-dimensional positioning is achieved through Time of Flight (TOF) ranging algorithm, with positioning accuracy up to ±10cm, especially suitable for grid-based accurate positioning scenarios after the laying of geocell.

[0122] (3) Laser Radar (LiDAR) and Simultaneous Localization and Mapping (SLAM) fusion unit, the laser radar is preferably a hybrid solid-state laser radar, and the scanning accuracy is ≤2 cm. This unit combines the SLAM algorithm and can generate a high-precision three-dimensional point cloud map of the work area in real time, maintain the continuity of positioning in the scene where the GNSS signal is blocked or poor, and provide dynamic correction data for the three-dimensional terrain of the digital twin model.

[0123] (4) GNSS / Inertial Navigation System (INS) tight coupling unit, which includes a dual-antenna Real-Time Kinematic (RTK) positioning and orientation module and an industrial-grade Inertial Measurement Unit (IMU). This unit performs data fusion at the baseband level, even in the case of temporary loss of GNSS signal (for example, loss time ≤30 minutes), it can still maintain a positioning accuracy of ≤0.5 m, thereby ensuring the integrity of the compaction data collection and avoiding data breakpoints caused by positioning interruption.

[0124] Vibration response data acquisition unit, which is one or more industrial-grade accelerometers firmly installed on the vibrating wheel of the vibratory roller, used to accurately measure the high-frequency vibration acceleration signal of the vibrating wheel during operation, i.e. vibration response data.

[0125] Device dynamics data acquisition unit, which is a Controller Area Network (CAN) bus interface. This interface is directly connected to the vehicle-mounted CAN bus of the vibratory roller itself, used to read and decode device dynamics data representing the working state of the roller in real time, such as engine speed, throttle opening, gear information, hydraulic system pressure and actual working frequency of the vibration system, etc.

[0126] The system adopts a two-level distributed computing architecture of vehicle-mounted controller (edge) and remote server (cloud) to balance the real-time requirements of field operation and the complex optimization requirements of background models.

[0127] The vehicle-mounted controller is a local data collection and real-time decision-making core of the system, which is a solid and durable industrial computer fixedly arranged in a cab of the vibratory roller. The positioning data acquisition module is electrically connected with the vehicle-mounted controller through an industrial communication interface (such as Ethernet or RS485), and transmits the high-frequency positioning data stream to the vehicle-mounted controller in real time. The accelerometer is electrically connected with a vehicle-mounted data acquisition unit through a dedicated shielded cable. The analog vibration signal collected by the accelerometer is preprocessed by the vehicle-mounted data acquisition unit, such as high-speed sampling and analog-digital conversion, and then transmitted to the vehicle-mounted controller. The CAN bus interface decodes the captured message from the CAN bus of the vibratory roller into readable digital signals through a CAN bus decoder, and then transmits the signals to the vehicle-mounted controller.

[0128] The remote server (or edge computing node cluster) is a background data center and model optimization platform of the system, which is responsible for storing massive historical data and performing complex digital twin model correction calculation. The vehicle-mounted controller is integrated with a wireless communication module (such as 5G or industrial Wi-Fi). The vehicle-mounted controller collects and preliminarily processes the positioning data, vibration response data, device dynamics data, and results of local real-time calculation of ground stiffness and compaction efficiency ratio, and uploads the data to the remote server in real time or in batches through the wireless module, for final archiving of the ground stiffness thermal map and closed-loop correction of the digital twin model.

[0129] In the ground state real-time evaluation step of step S40, in order to quantify the compaction state of the ground, the vibration response data acquired in real time need to be processed; a vertical acceleration signal under stable working conditions is intercepted , a fast Fourier transform (FFT) is applied to the signal to convert it from the time domain to the frequency domain, and the acceleration amplitude spectrum is obtained; from the amplitude spectrum, the working fundamental frequency of the vibratory roller 3 is extracted , and the amplitude corresponding to the fundamental frequency , and the amplitude corresponding to the first harmonic . Based on the amplitudes, the ground stiffness index is calculated using the following formula : ;

[0130] In the formula, K is the ground stiffness index, which is dimensionless; C is a device calibration coefficient, which is dimensionless and obtained by calibration with a traditional detection method (such as a bearing plate test) according to the specific roller model and sensor installation position; A is the Fourier transform amplitude of the acceleration signal at the working fundamental frequency f0; and B is the Fourier transform amplitude of the acceleration signal at the first harmonic f0.

[0131] ​​​​​​In another specific embodiment, the foundation stiffness index can be calculated using a method based on energy spectrum analysis, which can more comprehensively reflect the changes in the nonlinear stiffness of the foundation. The calculation formula is as follows: ;

[0132] In the formula, This is a dimensionless index of foundation stiffness; the larger the value, the higher the foundation stiffness. The first in the vibration response data The energy of a first harmonic can be characterized by the square of the amplitude at that harmonic frequency. The total energy of the vibration response data is equal to the sum of the squares of its signal in the time domain (according to Passawell's theorem). This is an index for the order of harmonic analysis; This represents the highest order of harmonic analysis. As the foundation is compacted and its stiffness increases, the nonlinear characteristics of the vibration response intensify, and energy transfers from the fundamental frequency to higher harmonics. Therefore, this energy level is a good characterization of foundation stiffness. By calculating the proportion of higher harmonic energy in the total energy, the compaction state of the foundation can be effectively and stably quantified. Similarly, the calculated values ​​at each location point... Spatial interpolation of the values ​​can generate a thermal map of foundation stiffness.

[0133] like Figure 7 As shown, the foundation stiffness index calculated for each GNSS positioning point is... The values ​​are spatially interpolated on a two-dimensional geographic coordinate plane, and different colors or grayscale values ​​are assigned according to the magnitude of the values ​​to generate a foundation stiffness heat map. This foundation stiffness heat map can be used to visually display the distribution and uniformity of compacted material throughout the entire construction area.

[0134] In other embodiments, the foundation stiffness index can be calculated not only based on the harmonic amplitude ratio of Fourier transform, but also based on the energy characteristics extracted by wavelet transform, or by analyzing statistical characteristics such as kurtosis and margin of the vibration signal. Spatial interpolation methods, besides Kriging interpolation, can also include inverse distance weighting (IDW) or spline function interpolation.

[0135] In the intelligent decision-making step of vibratory compaction operation in step S50, in order to determine the optimal number of compaction passes and achieve intelligent decision-making, this embodiment of the invention introduces the compaction efficiency ratio as a decision-making basis; this index quantifies the foundation reinforcement effect brought about by unit compaction work; the calculation of the vibratory roller on the first compaction pass... The compaction work input to the foundation during a single pass of rolling ( This work is mainly provided by the vibration system and can be estimated based on the kinetic energy of the vibrating wheel. The calculation formula is as follows: ;

[0136] In the formula: For the first The compaction work per pass of rolling mill, measured in joules; The mass of the vibrating wheel is expressed in kilograms. and The first The maximum and minimum values ​​of the vertical vibration velocity of the vibrating wheel during compaction; The fundamental frequency of the vibrating wheel is expressed in Hertz (Hz). For the first The vertical amplitude of the vibratory roller during compaction can be measured by analyzing the acceleration signal. We obtain the result by performing a second integral.

[0137] In obtaining the first Stiffness index of foundation after compaction and the Stiffness index of foundation after compaction Afterwards, the compaction efficiency ratio Defined as the ratio of the increment in foundation stiffness to the input compaction work per pass, the calculation formula is:

[0138] ;

[0139] In the formula, For the first The compaction efficiency of rolling is higher than that of rolling. For the first The foundation stiffness index after compaction; For the first The foundation stiffness index after compaction; To complete the first The total mechanical work input during compaction; This is the index for the number of rolling passes.

[0140] like Figure 8 As shown, in the initial stage of compaction, the compaction efficiency is higher than that of rolling. The soil is relatively high, and as the number of compaction passes increases, the foundation gradually becomes denser. It shows a downward trend; when continuously monitored The value is less than the preset termination threshold. If the vibratory compaction operation in the area is deemed to have met the requirements, compaction should be stopped.

[0141] Furthermore, the compaction intelligent decision-making system S50 also includes real-time monitoring and proactive intervention for over-compaction risks. During vibratory compaction, the onboard controller continuously compares the real-time calculated foundation stiffness index with the upper stiffness threshold predicted in the digital twin model S20 or preset based on material properties. When the foundation stiffness index exceeds this upper threshold, the system determines that there is a risk of over-compaction or foundation shear failure and automatically triggers an early warning.

[0142] Specifically, after the warning is triggered, the vehicle controller sends a frequency reduction command to the vibratory roller's exciter via the CAN bus, adjusting the excitation frequency from 25-30Hz to 15-20Hz; simultaneously, it sends a deceleration command to the drive system, reducing the travel speed from 3-5km / h to 1-2km / h; if the warning is not lifted within 30 seconds after adjustment, a stop command is automatically sent, and operations resume after manual confirmation of the foundation condition. This strategy, by actively reducing input energy, effectively avoids excessive disturbance and damage to the foundation structure, ensuring the safety and quality of construction.

[0143] The parallel monitoring and early warning of the spring phenomenon is as follows: During the compaction process, the presence of the foundation spring phenomenon is monitored in parallel; this phenomenon is judged by monitoring two dimensions: vibration phase lock-out deviation and driving power surge; based on this, a composite judgment index for the spring phenomenon is constructed. : ;

[0144] In the formula, A composite judgment index for the spring phenomenon; , These are the weighting coefficients. ; This represents the deviation between the measured vibration phase of the vibrating wheel and the phase of the exciter. This refers to the reference phase deviation under normal operating conditions. The standard deviation of the driving power of the vibratory roller or the main pump pressure of the hydraulic system reflects the degree of power fluctuation. This is the average value of the driving power or the main pump pressure of the hydraulic system; when The system issues a warning when the preset alarm threshold is exceeded.

[0145] In the model closed-loop correction step of step S60, refer to Figure 6 After the vibration compaction operation is completed, a closed-loop correction of the model is performed to improve the accuracy of the three-dimensional digital twin model.

[0146] Specifically, the inversion analysis algorithm includes the following steps:

[0147] At representative measuring points on the site, the actual bearing capacity index of the foundation is obtained through standard methods such as bearing plate tests or heavy dynamic penetration tests. ;

[0148] Then, define the model bias objective function , which is in the form of weighted least squares of simulation results and measured results:

[0149] In the formula, is the model bias objective function; is the vector of soil mechanical parameters to be corrected; is the total number of measured points for comparison; is the weight coefficient of the th measured point; is the simulated predicted bearing capacity index in the model when the soil parameters are at the position point ; is the actual measured bearing capacity index at the same position point in the physical world.

[0150] By using optimization algorithms such as gradient descent method, genetic algorithm or particle swarm optimization, find the parameter set that minimizes the objective function ; the optimal parameter set is the corrected soil mechanical parameter, which is used to update the three-dimensional digital twin model. In other embodiments, the optimization algorithm for finding the optimal parameter set can be simulated annealing algorithm or ant colony algorithm in addition to the gradient descent method, genetic algorithm or particle swarm optimization.

[0151] The following describes the specific engineering application steps of the method of the embodiment of the application in combination with a port mixed ore stockyard project.

[0152] Step one, this step performs site pretreatment, using excavators or bulldozers to remove humus soil on the surface of the specified area; for the proven weak area, use the replacement method for treatment; then, use the land leveler to fine level the site, and perform elevation measurement through the laser land leveler to ensure that the site flatness deviation is not greater than ± 50 mm;

[0153] Step two, this step performs the laying and fixing of geocell, on the pretreated foundation surface, lay and tension the geocell along the longitudinal direction of the stockyard; during the laying process, ensure that the overlapping width of adjacent sheets is not less than 500 mm; use U-shaped nails to anchor the geocell, and the spacing of the U-shaped nails is not greater than 300 mm; at the corners of the site, radially cut the geocell sheets to disperse local stress;

[0154] ​Step three, this step performs graded gravel filling and adaptive compaction layering, that is, graded gravel filling and vibration rolling operation; the virtual paving thickness of the first layer of filling is controlled at 200mm to 300mm; after filling, 1 pass of rolling is performed in the static rolling mode (that is, without starting the vibration function) using a 20-ton vibration roller to achieve preliminary stabilization of the filling; after filling of each subsequent layer of filling, vibration rolling is started, and adaptive rolling parameters are selected according to the type of filling: for filling mainly of sandy soil, a high-frequency low-amplitude mode is adopted, the vibration frequency is set at 40Hz to 50Hz, and the amplitude is set at 0.8mm to 1.2mm; for filling mainly of clayey soil, a low-frequency high-amplitude mode is adopted, the vibration frequency is set at 20Hz to 25Hz, and the amplitude is set at 1.8mm to 2.2mm; for special areas such as abutment backfill where compaction equipment is difficult to reach, a 1-ton to 2-ton micro-roller is used to supplement compaction in the high-frequency low-amplitude mode.

[0155] Step four, this step performs intelligent quality control throughout the process, and strict quality control is performed throughout the vibration rolling operation; the moisture content control ensures that the moisture content deviation of the filling is controlled within ±2% of the optimal moisture content; the moisture content is detected by the drying method or by using a portable moisture content detector to quickly determine it on site; when the detected value is low, water is added using a watering truck; when the detected value is high, the filling is loosened and dried using a grader. The intelligent monitoring of the rolling track coverage includes: a structure vibration monitor installed on the vibration roller and a Beidou positioning system synchronously transmit the collected vibration parameters (such as vibration acceleration and main frequency) and high-precision position data to the monitoring terminal at the construction site. The monitoring terminal performs the following analysis: spatial interpolation (such as Kriging interpolation) is performed on discrete position coordinates to generate continuous rolling track lines; through a track matching algorithm, the track lines are geometrically compared with the boundary of the preset rolling area, and the area is rasterized; the number of times each grid unit is covered by the track line is counted, and a coverage heat map is generated based on the number of coverages; when the monitoring terminal identifies a missed rolling area with a track density lower than a set threshold, it automatically marks the coordinate range and issues an instruction to the operator to guide the operator to supplement the rolling in the missed rolling area until the track coverage reaches 100%.

[0156] Step five, this step performs quality detection and final acceptance; after each layer of vibration rolling operation is completed, the compaction degree is detected using the pit filling sand method to ensure that the compaction degree is not less than 95%; after all vibration rolling operations are completed, final quality acceptance is performed; the acceptance standards include: the characteristic value of the foundation bearing capacity is not less than 200kPa; the post-construction settlement is not greater than 30mm; the differential settlement is not greater than 0.1%.

[0157] Example two

[0158] In a specific engineering embodiment, the vibration rolling and geocell coordinated stockyard foundation reinforcement method specifically comprises the following steps:

[0159] Step one, construction preparation and site pretreatment. Before construction, the stockyard foundation reinforcement area is cleaned to remove sundries, silt and loose soil layer within a range of 0.4 m from the surface to ensure the site is level. At the same time, according to the design drawings, the site is measured and marked to determine the geocell laying range, vibration rolling boundary and elevation control point, and temporary drainage ditches are set up around the site to drain surface water and avoid water immersion of the foundation. If there are local weak areas in the site, the replacement method is used for treatment. The replacement method refers to when there are local weak areas (for example, the thickness of the silt layer is more than 0.5 m) in the site, the soft soil layer in the area is completely excavated by an excavator to the relatively hard soil layer below, and then graded broken stone is filled in layers, with each layer having a thickness of not more than 300 mm. After the layers are spread and leveled, compaction is performed to replace the original soft soil layer. After replacement, a 20-ton vibrating roller is used for stable compaction for 1-2 times, with the rolling speed controlled at 30-40 m / min. Through the weight and slight vibration of the vibrating roller, the replaced broken stone layer is initially compacted to ensure that the surface layer has no obvious tire marks and is not loose.

[0160] Step two, foundation surface compaction treatment. This step performs initial rolling on the cleaned foundation surface, using a 20-ton vibrating roller for stable compaction for 1-2 times at a rolling speed of 30-40 m / min to ensure that the surface soil has a compactness of more than 85%. During the rolling process, if spring phenomenon is found, construction needs to be temporarily stopped and treated. Spring phenomenon refers to the phenomenon that the surface soil of the foundation layer bounces back and settles unstably under the load of the roller due to the high water content of the soil, which causes the pore water between the soil particles to be unable to be discharged in time. The treatment measures include excavation and replacement or airing. When excavation and replacement is used, the soft soil area with spring phenomenon is completely excavated using an excavator, with the excavation range exceeding the soft soil affected area by more than 500 mm and the depth reaching the relatively hard soil layer below. Then, graded mountain stone is filled in layers, with each layer having a thickness of not more than 300 mm. A 20-ton vibrating roller is used for layer-by-layer rolling for not less than 4 times until the compactness of the area reaches the design requirements. When airing is used, the surface soil is first loosened (depth of about 200-300 mm), and the water content is reduced using natural ventilation and sunlight. When the water content is reduced to within ±2% of the optimum water content, rolling is performed again.

[0161] Step three, geocell laying and fixing. In this step, geocells are laid on the compacted ground surface according to the design requirements. The geocells are made of high-molecular polymer honeycomb structure with a height of not less than 100 mm. In a specific implementation, the geocells are formed by ultrasonic welding or riveting of high-density polyethylene (HDPE) sheets, with a single cell size of 400 mm x 400 mm and a cell sheet thickness of not less than 1.1 mm. The longitudinal and transverse breaking tensile forces are both not less than 180 kN / m, and the right-angle tear strength is not less than 80 kN / m. When laying, the geocells are fully opened, and a steel rivet pile with a length of 500 mm is used to fix each cell at the top, with a spacing of not more than 1.5 m. Bamboo stakes are used to assist in tensioning on both sides. The laying range of the geocells should exceed the ground reinforcement boundary by not less than 0.25 m, and the overlapping width of adjacent cell sheets should be not less than 500 mm. The overlapping part is connected by buckles. In order to enhance the node connection strength, the surface of the cell sheet is provided with uniformly distributed slits or pre-made holes for insertion with curved connectors (such as the combination of a limiting frame and an inverted L-shaped needle), forming a mechanical interlock. The large grid size design is beneficial for adapting to the layered filling of graded gravel, and the hoop effect is formed by the frictional restraint of the geocell side wall and the gravel skeleton, effectively inhibiting the lateral displacement of particles under high-frequency vibration load.

[0162] Step four, filling graded gravel in the geocells. In this step, graded gravel is filled into the fixed geocells, with a maximum particle size of not more than 30 mm. The filling is done in layers, with each layer having a thickness of 2 / 3 of the height of the geocell (about 60-70 mm), and the filled material is manually leveled after filling. Graded gravel refers to aggregate prepared by mixing different sizes of gravel in a certain proportion, with a particle size distribution that meets the design requirements, and the total content of flat and long particles not exceeding 20%. The stone aggregate crushing value is not more than 30%. Layered filling refers to a construction method of laying and compacting filling materials layer by layer according to a certain thickness, ensuring that each layer of material is fully compacted.

[0163] Step five, vibration and compaction. After filling is completed, a 20-ton vibration roller is used for vibration and compaction. During compaction, first, static pressure is applied for 1 pass at a speed of 10-15 km / h, then the vibration function is turned on, and vibration and compaction are carried out for not less than 4 passes at a speed of 10-20 km / h, with an overlapping width of 300-500 mm between adjacent compaction zones. Further, the driving route of compaction is planned according to the relationship between the site width and the minimum turning radius of the vibration roller, to ensure the continuity and efficiency of compaction.

[0164] Reference Figure 9 When the construction site width is greater than four times the turning radius of the vibration roller, the site is symmetrically divided into two halves along the center line of the road, and the compaction driving route is planned as Figure 9The compactor travels in the manner shown. Such path planning can ensure that the compactor completes turning within the site without the need for an additional turning area, thereby improving work efficiency.

[0165] Referring to Figure 10 When the width of the construction site is less than four times the turning radius of the vibratory compactor, it is difficult to turn within the site. In this case, a turning site is set up at each end of the construction site according to the actual situation, and the compactor travels in the manner shown to ensure that each rolling pass is a straight line. Figure 10 The compactor travels in the manner shown to ensure that each rolling pass is a straight line.

[0166] During the rolling process, the adjacent rolling passes can also be staggered in the orthogonal travel directions. Staggering in the orthogonal travel directions means that the travel direction of the previous rolling pass is perpendicular to the travel direction of the subsequent rolling pass. For example, the first rolling pass is in the longitudinal direction of the site, and the second rolling pass is in the transverse direction of the site, so as to eliminate the rolling blind area and ensure uniform compaction. At the same time, water is appropriately sprayed by a water spraying vehicle according to the weather conditions, so that the water content of the crushed stone is in the optimal range of 5% to 8%.

[0167] Step six, quality detection and supplementary rolling. After the rolling is completed, the effect of the foundation reinforcement is detected. The compaction degree in the range of 0-0.8m below the foundation delivery surface is detected, and the requirement is that the main road area is not less than 95%, and the other areas are not less than 94%. At the same time, the comprehensive modulus of resilience is detected, and the requirement is that the comprehensive modulus of resilience of the foundation delivery surface of the main road area is not less than 40MPa, and the comprehensive modulus of resilience of the other areas is not less than 35MPa. If the detection result is not up to standard, 1-2 additional vibratory rolling passes are added for the unqualified area until the requirement is met.

[0168] The compaction degree detection can adopt the ring knife method or the sand filling method. The ring knife method is to take soil samples by a ring knife, calculate the ratio of the dry density to the maximum dry density, and is suitable for fine-grained soil. The sand filling method is to fill the standard sand in the test pit, calculate the volume of the test pit, and then calculate the ratio of the dry density to the maximum dry density of the soil, which is suitable for coarse-grained soil.

[0169] The comprehensive modulus of resilience detection adopts the bearing plate test. The load is applied in stages at the detection point, and the settlement is measured. The modulus of resilience of the foundation is calculated according to the relationship between the load and the settlement, and the elastic deformation characteristics of the foundation under the action of the load are comprehensively reflected.

[0170] Step seven, connection of subsequent procedures. After the foundation reinforcement is qualified, the subsequent engineering construction is carried out. During the construction process, heavy machinery is avoided from directly rolling the edge area of the geocell. If temporary materials need to be stacked, steel plates need to be laid under the materials to disperse the load and prevent the damage to the reinforced foundation structure. The materials here include but are not limited to mountain stone for backfilling, graded crushed stone, cement, sand and gravel, steel bars for concrete construction, and various prefabricated components, etc.

[0171] Example three

[0172] As Figure 5 shown, the present application also provides a vibration roller and geocell collaborative yard foundation reinforcement system, which comprises a model construction and pre-play module 10, an intelligent monitoring component 20, a state evaluation and decision module 30, and a model closed-loop correction module 40.

[0173] The model construction and pre-play module 10 is an offline computing module deployed on a workstation or server; the model construction and pre-play module 10 runs before the construction operation starts, and the initial construction scheme generated thereby is input to the state evaluation and decision module 30 as configuration data.

[0174] The intelligent monitoring component 20 is a set of hardware installed on the vehicle body of the vibration roller 3; it works continuously during the vibration roller operation and is the real-time data source of the system.

[0175] The state evaluation and decision module 30 establishes a real-time data communication connection with the intelligent monitoring component 20; this connection can be realized through industrial Ethernet, CAN bus, or 4G / 5G wireless communication network, ensuring that the position coordinates, acceleration signals, and equipment state data collected by the intelligent monitoring component 20 can be streamed to the state evaluation and decision module 30 in a low-latency manner; the state evaluation and decision module 30 can be a rugged vehicle-mounted computer installed in the cab of the vibration roller 3, or a computing service deployed on a remote server.

[0176] The model closed-loop correction module 40 has a data transmission path with the state evaluation and decision module 30; after the completion of the entire or phased construction task, the state evaluation and decision module 30 transmits the final ground stiffness index data and rolling process data covering the entire construction area accumulated and stored to the model closed-loop correction module 40; this data transmission is a non-real-time bulk data transmission.

[0177] The model closed-loop correction module 40 is also an offline computing module; it receives data from the state evaluation and decision module 30 and receives external input of artificial field detection data (such as bearing plate test data); after running the inversion analysis program, the model closed-loop correction module 40 outputs the corrected soil mechanical parameters, which are used to update the parameter database inside the model construction and pre-play module 10, thereby constituting the closed-loop correction path of the entire system.

[0178] The hardware carrier of the model building and simulation module 10 is a high-performance graphics workstation or server, which is internally configured with large-capacity memory and high-performance graphics processors to support complex dynamic calculations; in terms of software composition, the model building and simulation module 10 is internally built with commercial or self-developed three-dimensional finite element or discrete element analysis software; when executing step S20, the software first imports the site geological stratification data and terrain elevation data stored in the form of files, and allows the user to input the constitutive model parameters of each soil layer through the graphical interface; then, the software automatically or interactively generates a three-dimensional grid model containing the soil body, the geocell 1 and the graded gravel filler 4, and defines the dynamic characteristics of the vibratory roller 3 as a moving boundary load in the model; by solving the transient dynamic equation, the module outputs a simulation result file of the time-varying stress field, displacement field and density field of the foundation during the rolling process.

[0179] The intelligent monitoring assembly 20 is an integrated hardware unit, which is fixedly installed on the frame or cab of the vibratory roller 3, and the internal sensor probe is installed at the specified position. The intelligent monitoring assembly 20 specifically includes: a Beidou / GNSS positioning terminal supporting real-time dynamic (RTK) differential technology, whose antenna is installed on the top of the vibratory roller 3 without obstruction, and outputs data frames containing high-precision three-dimensional coordinates and UTC time stamps in compliance with the NMEA-0183 protocol through a serial port; an industrial-grade MEMS (Micro-Electro-Mechanical System) acceleration sensor (for example, packaged as an SR-VM monitor), whose measurement axis is fixedly installed in the vertical direction on the bearing seat of the vibratory roller 3, and outputs digital acceleration time series data with a high sampling rate (for example, 512Hz) through its internal analog-to-digital converter; and a CAN bus adapter connected to the CAN bus diagnostic interface of the vibratory roller 3 through a physical cable, used to listen to and analyze the broadcast CAN messages, and extract the device state data defined by the Parameter Group Number (PGN) of engine speed, torque percentage, etc.; in some specific applications, the intelligent monitoring assembly can also be integrated with an inclination sensor to monitor the attitude of the roller, a gyroscope to assist in path calculation, or an infrared temperature sensor to monitor the paving temperature of special fillers such as asphalt.

[0180] The physical form of the state assessment and decision module 30 can be an industrial tablet computer or a rugged vehicle-mounted computing unit installed in the cab, or a set of software services deployed on a local or cloud server; the core algorithm program running inside it receives multiple data streams from the intelligent monitoring component 20 in real time by establishing a data stream processing pipeline; the algorithm first uses the timestamp to align and synchronize data from different sources; for each data block at a time step or spatial location point, the program automatically performs the function of step S40, i.e. calls the fast Fourier transform function to process the acceleration data, calculates the ground stiffness index , and updates a stiffness database bound to the geographic coordinates; at the same time, the program performs the function of step S50, calculates the single-pass compaction work based on the amplitude and device parameters , and calculates the compaction work efficiency ratio combined with the stiffness values of the previous and subsequent passes ; when is less than the preset threshold value, the state assessment and decision module 30 outputs a determination result of job completion, which can be displayed as a visual alarm through its user interface, or generates a control instruction.

[0181] The model closed-loop correction module 40 is a software program running after the completion of the construction task, deployed on the computer of the engineering technician; the data input interface of the model closed-loop correction module 40 is used to receive the final full-field compaction data file (e.g. CSV) derived by the state assessment and decision module 30, and the measured ground bearing capacity values of several key points measured by standard methods such as bearing plate test on the site by manual input. The module internally implements an inversion analysis program based on an optimization algorithm (e.g. genetic algorithm or gradient descent method). The inversion analysis program aims to reduce the weighted squared difference between the model simulation predicted value and the measured value (i.e. model bias objective function), automatically and iteratively adjusts the soil mechanical parameter vector used by the model construction and pre-play module 10. Each iteration calls the simulation kernel for calculation until the objective function value converges to the preset tolerance range. The module finally outputs a set of optimized soil mechanical parameters, which are used to update the material database of the model construction and pre-play module 10.

[0182] The above specific embodiments do not constitute a limitation on the scope of protection of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for reinforcing the foundation of a stockpile site using a combination of vibratory compaction and geocell technology, characterized in that, The method includes the following steps: S10. Drive piles into the foundation to be reinforced, and lay geocells on the top surface of the piles and fill them with graded crushed stone filler to form a composite foundation structure. S20. Before construction, based on geological information, topographic information, and the layout of geocells and piles in the composite foundation structure, a three-dimensional digital twin model of the site is constructed. By simulating the compaction effect under different combinations of rolling parameters in the three-dimensional digital twin model, the initial construction plan is determined. S30. When the vibratory roller performs vibratory compaction of the graded crushed stone fill in the composite foundation structure according to the initial construction plan, the intelligent monitoring component installed on the vibratory roller acquires the positioning data, vibration response data and equipment dynamics data of each position on the compaction path in real time, forming a multi-dimensional physical response data stream. S40. Based on the vibration response data in the multidimensional physical response data stream, calculate the foundation stiffness index at each location on the compaction path in real time, and combine it with the positioning data to generate a foundation stiffness heat map of the compaction state of the entire construction area. S50. Based on the increment of the foundation stiffness index and the input work represented by the equipment dynamics data in the multidimensional physical response data stream, calculate the compaction efficiency ratio at each position on the compaction path in real time. When the compaction efficiency ratio meets the preset termination condition, determine that the vibration compaction operation at the corresponding position is completed. S60. After the vibration compaction operation is completed, the soil mechanical parameters in the three-dimensional digital twin model are corrected in reverse using the final generated foundation stiffness thermal map and the collected multidimensional physical response data stream. Step S20 specifically includes: S21. Based on geological information, topographic information, geocell layout and pile layout, establish a three-dimensional mesh model of the site, and assign soil mechanical parameters to the three-dimensional mesh model. S22. Using a mechanical-soil coupled dynamics algorithm, simulations are performed on the three-dimensional mesh model for multiple combinations of different compaction parameters, including compaction path, travel speed, vibration frequency, and amplitude. S23. Based on the simulation results of each rolling parameter combination, select the optimal rolling parameter combination as the initial construction scheme; wherein, the simulation results include at least the predicted foundation stiffness distribution, the identified potential risk areas, and the estimated theoretical energy consumption; Step S40 specifically includes: S41. Perform a fast Fourier transform on the vibration response data obtained from the multidimensional physical response data stream and synchronized with the timestamps of each positioning data to obtain the distribution of its energy at different harmonic frequency points. S42. Based on the obtained harmonic energy distribution, the foundation stiffness index is calculated using the foundation stiffness index calculation formula to form a discrete data point set corresponding to each location data. The formula for calculating the foundation stiffness index is as follows: ； In the formula, It is an index of foundation stiffness; The vibration response data of the first The energy of the first harmonic; The total energy of the vibration response data; This is an index for the order of harmonic analysis; This is the highest order of harmonic analysis; S43. Using the Kriging space interpolation algorithm, the discrete data point set is processed to estimate the foundation stiffness index of the unmeasured areas within the entire construction area, forming gridded stiffness data covering the entire construction area. S44. Color each stiffness value in the generated gridded stiffness data according to a preset color mapping table to generate the foundation stiffness heat map. Step S50 specifically includes: S51. Using the calculated foundation stiffness index as input, and combining the input work represented by the equipment dynamics data from the multidimensional physical response data stream, the compaction efficiency ratio is calculated using the compaction efficiency ratio calculation formula. The formula for calculating the compaction efficiency ratio is: ； In the formula, For the first The compaction efficiency of rolling is higher than that of rolling. For the first The foundation stiffness index after compaction; For the first The foundation stiffness index after compaction; To complete the first The total mechanical work input during compaction; The index for the number of rolling passes; S52, with the aforementioned compaction efficiency ratio As a criterion for judgment, when the compaction efficiency ratio Number of rolling passes When the rate of change is lower than the preset slope threshold, or when the compaction efficiency ratio is lower than the preset slope threshold, When the value is lower than the preset minimum effective threshold, the vibration compaction operation is considered complete.

2. The method for reinforcing the foundation of a stockpile site using a combination of vibratory compaction and geocells as described in claim 1, characterized in that, Step S10 specifically includes: S11. On the leveled foundation, unfold, tension, and anchor the geocell using the pile body; S12. The graded crushed stone filler is layered into the geocell, wherein the maximum particle size of the graded crushed stone filler is less than two-thirds of the height of the geocell. S13. Before performing the vibratory compaction operation, the filled graded crushed stone filler shall be subjected to at least one pass of static compaction.

3. The method for reinforcing the foundation of a stockpile site using a combination of vibratory compaction and geocells as described in claim 1, characterized in that, In step S30, the intelligent monitoring component includes: Location data acquisition module; An accelerometer installed on the vibratory roller drum is used to acquire the vibration response data. The controller area network bus interface is used to acquire the device's dynamic data.

4. The method for reinforcing the foundation of a stockpile site using a combination of vibratory compaction and geocells as described in claim 1, characterized in that, The method further includes a spring phenomenon warning step, which is performed in parallel during the execution of steps S30 to S50, and specifically includes: By real-time monitoring of the vibration phase lock-out deviation and running power surge of the vibratory roller, a combined judgment and early warning are made on the spring phenomenon that occurs in the composite foundation structure during the rolling process, and an instruction to adjust the working mode is automatically issued to the vibratory roller when the early warning is triggered.

5. The method for reinforcing the foundation of a stockpile site using a combination of vibratory compaction and geocells as described in claim 4, characterized in that, The vibration phase unlocking deviation is monitored by the following devices: A magnetoelectric phase sensor is installed at the end of the vibratory roller's vibratory wheel shaft, and a synchronous phase encoder is installed at the end of the vibratory roller's exciter's drive shaft. The magnetoelectric phase sensor and the synchronous phase encoder are electrically connected to the vehicle-mounted data acquisition unit via signal cables to collect the phase difference signal between the vibratory wheel and the exciter in real time and calculate the vibration phase lock-up deviation. The power surge is monitored by the following devices: The engine control module of the vibratory roller establishes data communication with the CAN bus interface of the controller local area network to acquire the engine output power, hydraulic system pressure, and torque signal of the drive wheel of the vibratory roller in real time. A torque sensor is installed at the output end of the gearbox of the vibratory roller to measure the torque value output by the gearbox in real time to obtain measured torque data. The measured torque data is sent to the vehicle controller through a wireless transmission module. The vehicle controller combines the measured torque data with the engine output power and drive wheel speed data to calculate the instantaneous power fluctuation value and compare it with the rated power threshold to determine the driving power surge. The composite judgment and early warning are implemented through the following methods: A pre-set threshold for vibration phase lockout deviation and a threshold for driving power surge are used. A multi-parameter fusion algorithm based on fuzzy logic is employed to compare the real-time monitored vibration phase lockout deviation with the threshold and the real-time monitored driving power surge value with the threshold. When both exceed the corresponding threshold simultaneously and remain so for a predetermined duration, a spring phenomenon is identified. A warning signal is issued via an onboard audible and visual alarm, and the warning information is simultaneously uploaded to a remote monitoring platform.

6. The method for reinforcing the foundation of a stockpile site using a combination of vibratory compaction and geocells as described in claim 1, characterized in that, Step S60 specifically includes: S61. The final generated foundation stiffness thermal map is used as the actual compaction result and compared with the compaction effect predicted by the initial soil mechanical parameters in step S20 to determine the compaction state prediction deviation between the prediction result of the three-dimensional digital twin model and the actual compaction result. S62. With the goal of minimizing the predicted deviation of the compaction state, an inversion analysis algorithm is used to iteratively adjust the dynamic elastic modulus and damping ratio parameters related to the compaction state of the composite foundation structure in the three-dimensional digital twin model. S63. When the predicted deviation of the compaction state converges to below the preset threshold, the final adjusted dynamic elastic modulus and damping ratio parameters are solidified into the three-dimensional digital twin model to complete the reverse correction.

7. A landfill foundation reinforcement system combining vibratory compaction and geocells, applied to the method described in any one of claims 1-6, characterized in that, The system includes: The model building and pre-simulation module is used to build a three-dimensional digital twin model based on the input site foundation data and layout information of the composite foundation structure, and run a virtual pre-simulation to determine the initial construction plan; An intelligent monitoring component is configured on a vibratory roller. The intelligent monitoring component includes a set of sensing devices for collecting positioning data, vibration response data and equipment dynamics data at various locations on the compaction path of the vibratory roller in real time during vibratory compaction of the composite foundation structure, so as to form a multi-dimensional physical response data stream. The state assessment and decision-making module is communicatively connected to the intelligent monitoring component. It is used to calculate the foundation stiffness index and compaction efficiency ratio at each location on the compaction path in real time based on the multi-dimensional physical response data stream, and generate a completion judgment of the vibratory compaction operation based on preset termination conditions. Based on the foundation stiffness index at each location on the compaction path and combined with the positioning data, it generates a foundation stiffness heat map of the compaction state of the entire construction area. The model closed-loop correction module is used to receive the foundation stiffness heat map generated by the state assessment and decision module and the multidimensional physical response data stream collected by the intelligent monitoring component after the vibration compaction operation is completed, and to reverse correct the three-dimensional digital twin model based on the foundation stiffness heat map and the multidimensional physical response data stream.

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