Open caisson sinking friction dynamic regulation and control method based on multi-parameter real-time feedback

Abstract

The invention provides an open caisson sinking friction dynamic regulation and control method based on multi-parameter real-time feedback, and relates to the technical field of open caisson construction.The method comprises the steps that multi-source parameters in the open caisson sinking process are monitored in real time; on the basis of the real-time monitoring values of the multi-source parameters, the real-time effective contact area between the well wall and the soil body in the sinking process of the open caisson is determined according to the Pearson multi-scale contact theory, and the real-time friction coefficient in the sinking process of the open caisson is calculated on the basis of a soil body plasticity index and a rate-state friction equation expanded by pore water pressure; and real-time friction resistance in the open caisson process is calculated based on the real-time effective contact area and the real-time friction coefficient, a regulation and control instruction is generated at least based on the real-time friction resistance and a preset physical critical condition, and the open caisson sinking process is dynamically regulated and controlled. And parameters used for calculating the real-time friction resistance are fed back and updated according to the real-time monitoring values of the regulated and controlled multi-source parameters, and the parameters are used for calculating the real-time friction resistance in the follow-up process.

Description

Technical Field

[0001] This invention relates to the field of caisson construction technology, and in particular to a method for dynamic control of caisson sinking friction based on real-time feedback of multiple parameters. Background Technology

[0002] During the sinking of large concrete caissons, the frictional resistance between the caisson wall and the soil is the core factor affecting construction safety and efficiency.

[0003] Current methods for controlling the sinking of caissons mainly rely on a passive response mode based on empirical thresholds from monitoring data. Typically, the frictional resistance between the caisson wall and the soil is estimated based on a simplified Coulomb's law, and then compared with a static safety threshold to control the sinking process.

[0004] However, at the mechanistic level, the simplified Coulomb's law reduces the dynamic and complex interaction between soil and rock structures to static Coulomb friction, ignoring the rheological properties of the soil and the actual evolution of the contact interface. At the parameter level, the simplified Coulomb's law treats the friction coefficient and soil parameters as constant values, which is disconnected from the dynamic process of soil properties changing with depth and other disturbances during actual construction. Ultimately, the frictional resistance estimated based on the simplified Coulomb's law has a large error when the working conditions change, which in turn makes it easy for accidents such as tilting, stagnation or sudden settlement to occur during actual construction.

[0005] Therefore, a method is still needed to accurately predict the frictional resistance during the sinking of the caisson, and to make full use of the dynamic monitoring information of the actual construction process to optimize the control of the sinking process. Summary of the Invention

[0006] This invention provides a dynamic control method for caisson sinking friction based on multi-parameter real-time feedback, which solves the defect of low accuracy in predicting friction resistance during caisson sinking in the prior art. It realizes a dynamic control method for caisson sinking friction based on multi-parameter real-time feedback, which actively controls the friction resistance at the interface between the caisson wall and the soil based on the predicted real-time friction resistance, thereby achieving optimized control of the caisson sinking process.

[0007] This invention provides a method for dynamic control of caisson sinking friction based on real-time feedback of multiple parameters, comprising: Real-time monitoring of multiple parameters during the caisson sinking process, including normal stress between the caisson wall and the soil, soil shear wave velocity, pore water pressure, and caisson sinking speed; Based on the real-time monitoring values ​​of multi-source parameters, the real-time effective contact area between the well wall and the soil during the sinking process of the caisson is determined according to the Persson multi-scale contact theory, and the real-time friction coefficient during the sinking process is calculated based on the rate-state friction equation of soil plasticity index and pore water pressure expansion. The real-time frictional resistance during the caisson sinking process is calculated based on the real-time effective contact area and the real-time friction coefficient. Control commands are generated based on at least the real-time frictional resistance and preset physical critical conditions to dynamically control the caisson sinking process. The parameters used to calculate the real-time frictional resistance are updated based on the real-time monitoring values ​​of the multi-source parameters after control, and used for the calculation of the real-time frictional resistance in subsequent processes.

[0008] According to the present invention, a method for dynamic control of caisson sinking friction based on multi-parameter real-time feedback is provided. The preset physical critical conditions include an instability resistance threshold and an effective yield strength threshold of the soil. The control commands include grouting control commands and water pressure control commands. The step of generating control commands based at least on the real-time friction resistance and the preset physical critical conditions to dynamically control the caisson sinking process includes: When the real-time frictional resistance is greater than the instability resistance threshold, a grouting control command is triggered. When the real-time effective stress exceeds the effective yield strength threshold of the soil, a water pressure control command is triggered.

[0009] The present invention provides a method for dynamic control of caisson sinking friction based on real-time feedback of multiple parameters, which further includes: The shear strength attenuation rate of the regulated soil and the grout diffusion radius are calculated to evaluate the regulation effect and serve as input for parameter feedback updates.

[0010] The present invention provides a method for dynamic control of caisson sinking friction based on real-time feedback of multiple parameters, which further includes: A PID controller is constructed using the difference between the real-time pore water pressure and the target pore water pressure as the deviation, which is used to calculate the amount of water to be regulated. The water pressure control command is generated based on the controlled water volume.

[0011] According to the present invention, a dynamic control method for caisson sinking friction based on multi-parameter real-time feedback is provided, wherein the rate-state friction equation derived from the soil plasticity index and pore water pressure is: ; In the formula, The coefficient of friction, The static friction between the caisson sidewall and the soil is considered. The sinking speed of the caisson For reference speed, For contact state variables, As a reference state variable, I P The soil plasticity index. Pore ​​water pressure, For time, , , and To adjust the parameters.

[0012] According to the present invention, a method for dynamic control of caisson sinking friction based on multi-parameter real-time feedback is provided, wherein the step of determining the real-time effective contact area between the caisson wall and the soil during the sinking process based on Persson's multi-scale contact theory includes: The cumulative roughness energy spectrum is determined by inverting the soil power spectral density function based on the soil shear wave velocity. The theoretical contact area ratio is determined based on the cumulative roughness energy spectrum. The real-time effective contact area is calculated based on the product of the theoretical contact area ratio and the theoretical contact area between the caisson sidewall and the soil.

[0013] The present invention provides a method for dynamic control of caisson sinking friction based on multi-parameter real-time feedback, which further includes minimizing the total friction work of the system as the optimization objective of the dynamic control process.

[0014] This invention also provides a dynamic control system for caisson sinking friction based on real-time feedback of multiple parameters, comprising: The acquisition module is used to monitor multi-source parameters in real time during the sinking process of the caisson, including the normal stress between the caisson wall and the soil, the soil shear wave velocity, the pore water pressure, and the sinking speed of the caisson. The prediction module is used to determine the real-time effective contact area between the well wall and the soil during the sinking process based on the real-time monitoring values ​​of multi-source parameters, according to Persson's multi-scale contact theory, and to calculate the real-time friction coefficient during the sinking process based on the rate-state friction equation which is derived from the soil plasticity index and pore water pressure. The control module is used to calculate the real-time frictional resistance during the caisson sinking process based on the real-time effective contact area and the real-time friction coefficient. It generates control commands based at least on the real-time frictional resistance and preset physical critical conditions to dynamically control the caisson sinking process. It also updates the parameters used to calculate the real-time frictional resistance based on the real-time monitoring values ​​of the multi-source parameters after control, which are used for the calculation of the real-time frictional resistance in subsequent processes.

[0015] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the dynamic control method for caisson sinking friction based on real-time feedback of multiple parameters as described above.

[0016] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the dynamic control method for caisson sinking friction based on real-time feedback of multiple parameters as described above.

[0017] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements the dynamic control method for caisson sinking friction based on real-time feedback of multiple parameters as described above.

[0018] The present invention provides a dynamic control method for caisson sinking friction based on multi-parameter real-time feedback. By using Persson theory and combining real-time acoustic inversion of the soil power spectrum to dynamically update the cumulative roughness energy spectrum value, a multi-scale friction mechanism that adapts to the spatiotemporal evolution of the soil structure is calculated. At the same time, a dynamic equation for the friction coefficient is constructed by using the extended RSF method to accurately predict the real-time frictional resistance during the caisson sinking process. Based on the real-time frictional resistance, a caisson sinking control scheme is determined, thus establishing a physical driving prediction and dynamic control system for the frictional resistance between the well wall and the soil during the caisson sinking process. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the dynamic control method for caisson sinking friction based on real-time feedback of multiple parameters provided by the present invention. Figure 2 This is a schematic diagram of the simulation results of the normal stress and side friction of the caisson under different loads and loading steps in the caisson process according to the present invention. Figure 3 This is a schematic diagram of the structure of the caisson sinking friction dynamic control system based on multi-parameter real-time feedback provided by the present invention; Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0022] The following is combined Figure 1 This invention introduces a dynamic control method for caisson sinking friction based on real-time feedback of multiple parameters, such as... Figure 1 As shown, it includes: Step 101: Monitor multi-source parameters of the caisson sinking process in real time, including normal stress between the caisson wall and the soil, soil shear wave velocity, pore water pressure and caisson sinking speed. Deploy appropriate sensors or measuring equipment to monitor multi-source parameters between the well wall and the soil during the sinking process of the caisson.

[0023] Optionally, by deploying fiber optic grating sensors in a matrix on the well wall, the normal stress between the well wall and the soil can be obtained based on wavelength drift decoupling. Preferably, the fiber Bragg grating sensors are deployed at a spacing of 1.5 meters × 1.5 meters.

[0024] Optionally, a piezoelectric acoustic probe array is arranged in a ring at the cutting edge to calculate the soil shear wave velocity using the transmit-receive time difference. And the soil shear strength is obtained by inversion. , This represents the soil density.

[0025] Alternatively, pore water pressure can be measured using a piezometer installed on the outside of the well wall.

[0026] Optionally, the sinking speed of the caisson can be monitored in real time via a GNSS receiver installed on top of the caisson.

[0027] In other feasible implementations, other feasible sensors or sensor networks can also be used to achieve real-time monitoring of multi-source parameters.

[0028] Step 102: Based on the real-time monitoring values ​​of multi-source parameters, determine the real-time effective contact area between the well wall and the soil during the sinking process of the caisson according to the Persson multi-scale contact theory, and calculate the real-time friction coefficient during the sinking process of the caisson based on the rate-state friction equation which is derived from the soil plasticity index and pore water pressure. In the study of the contact surface and side friction of the caisson, three levels of load (Load-1, Load-2, Load-3) and continuous loading steps (Step1-4) were set up through simulation to simulate the actual force evolution process caused by the increase of sinking depth and the change of soil pressure during the sinking process of the caisson.

[0029] like Figure 2As shown in the simulation results, the normal pressure and side friction exhibit a significant nonlinear growth pattern with increasing loading step. In the initial loading stage, the side friction increases rapidly with increasing normal pressure; however, as the contact interface gradually compacts, the rate of increase in friction gradually slows down, exhibiting typical nonlinear friction response characteristics. This simulation result demonstrates that the frictional behavior between the well wall and the soil interface does not simply satisfy the assumptions of "constant friction coefficient and fixed contact area" in the traditional Coulomb's law of friction, but rather manifests as a friction mechanism where the contact area dynamically changes with the evolution of the contact state.

[0030] Furthermore, referring to Figure 2 Simulation results show that, under the same length conditions, the normal pressure on the contact surface increases significantly with increasing load level, and the absolute value of the corresponding normal compressive stress increases synchronously. This verifies the premise for applying Pearson's multi-scale contact theory in the caisson process: as the normal pressure increases, the micro-protrusions of the rough interface gradually compact, and the proportion of the effective contact area of ​​the interface increases accordingly. Based on this, this invention proposes to calculate the real-time effective area during the caisson process based on Pearson's multi-scale contact theory.

[0031] To accurately calculate the real-time frictional resistance of the caisson during the caisson process, this invention, based on the Persson multi-scale contact theory framework, couples the surface roughness of the concrete caisson with the homogeneous characteristics of the soil particle structure through a power spectral density function, describing the frictional resistance from micro-convexity (10) to micro-convexity (10) ... -6 The evolution of the actual contact area across macroscopic undulations (m) is used to obtain the real-time effective contact area between the caisson sidewall and the soil during the caisson process, replacing the conventionally used theoretical area of ​​the caisson sidewall for calculating frictional resistance.

[0032] Specifically, Persson's multiscale contact theory is an original theoretical framework describing the contact behavior of rough surfaces. This theory overcomes the limitations of traditional contact mechanics based on the assumption of discrete micro-convexities, solving the contact problem of cross-scale rough interfaces through a continuous-scale integration method. Its physical core lies in treating the morphological features of rough surfaces as fractal geometry, utilizing the power spectral density function of surface height undulations. C ( q () is used as the core description parameter.

[0033] The key expression for the actual contact area ratio derived from Persson's multi-scale contact theory is as follows: ; In the formula, Indicates the actual contact area. The theoretical contact area is represented by erf(), which represents the error function. The root mean square of the surface roughness. G This represents the cumulative roughness energy spectrum.

[0034] The cumulative roughness energy spectrum is based on the power spectral density function. The points are obtained through integration.

[0035] Therefore, by monitoring the real-time shear wave velocity during the caisson sinking process, the power spectral density function of the soil-caisson wall interface can be obtained through acoustic inversion. Then further calculations can be performed. G The actual contact area is calculated based on the area ratio contact formula and the theoretical contact area between the well wall and the soil.

[0036] On the other hand, this invention extends the Dieterich Rate-and-State Friction (RSF) law by introducing the soil plasticity index and pore water pressure to expand the original RSF method, thereby constructing a dynamic equation for the friction coefficient and calculating a more accurate real-time friction coefficient: ; In the formula, The coefficient of friction, The static friction between the caisson sidewall and the soil is considered. The sinking speed of the caisson For reference speed, For contact state variables, As a reference state variable, I P The soil plasticity index. Pore ​​water pressure, For time, , , and To adjust the parameters.

[0037] The soil plasticity index is obtained by pre-calibration through geotechnical tests.

[0038] Based on this, the real-time friction coefficient during the caisson sinking process can be calculated using the extended RSF method, based on real-time monitoring of the caisson sinking speed, pore water pressure, and a pre-determined soil plasticity index.

[0039] Step 103: Calculate the real-time frictional resistance of the caisson process based on the real-time effective contact area and the real-time friction coefficient. Generate control commands based at least on the real-time frictional resistance and preset physical critical conditions to dynamically control the caisson sinking process. Update the parameters used to calculate the real-time frictional resistance based on the real-time monitoring values ​​of the multi-source parameters after control, for use in the subsequent calculation of the real-time frictional resistance.

[0040] After determining the real-time friction coefficient and the real-time effective contact area, the real-time frictional resistance can be calculated using the real-time data of the coupled normal stress. : ; In the formula, S Indicates the contact surface area. Shear strength, for t Normal stress at time, for t pore water pressure at all times for t Effective contact area at all times This is the real-time friction coefficient.

[0041] Through the above methods, at the theoretical level, this invention creatively couples Persson's multiscale fractal theory in solid contact mechanics with the rate-state friction rate in geotechnical engineering. It simultaneously characterizes the rheological properties of soil reflected by the soil plasticity index, the bonding timeliness reflected by the contact state variables in the extended RSF, and the seepage field-stress coupling effect reflected by the transient term of pore water pressure. This allows for accurate and real-time monitoring of the real-time frictional resistance of the caisson throughout the entire caisson sinking process. Based on the more accurate real-time frictional resistance data, control commands are generated to regulate the caisson sinking process.

[0042] Optionally, one or more physical critical conditions can be preset to automatically regulate the sinking process of the caisson based on real-time frictional resistance and its derived parameters.

[0043] For example, by pre-setting an instability resistance threshold as a physical critical condition, when the real-time frictional resistance exceeds the preset instability resistance threshold, soil instability can be determined, and the soil needs to be stabilized in a timely manner by grouting or other feasible methods to prevent soil collapse.

[0044] For example, a speed threshold can be set directly. When the monitored real-time sinking speed of the caisson exceeds the preset speed threshold, the sinking speed can be indirectly controlled by adjusting the pore water pressure.

[0045] Optionally, the physical critical conditions can be pre-configured by those skilled in the art based on experience, combined with influencing factors such as the soil environment and caisson quality during the sinking construction, and the corresponding control instructions for each physical critical condition can be pre-configured according to the actual feasible control scheme at the construction site.

[0046] Based on this, if the real-time frictional resistance and / or other direct or indirect monitoring parameters monitored during the caisson process violate the preset physical critical conditions, the corresponding control command can be directly triggered to dynamically control the caisson process.

[0047] Furthermore, as the soil types traversed by the caisson change and / or the control commands affect the physical and mechanical properties of the soil, the contact state and material properties of the interface between the caisson wall and the soil also change. This leads to a mismatch between the key coefficients for calculating real-time frictional resistance based on previous working conditions (such as the coefficients of each term in the extended RSF equation) and the current actual working conditions. Therefore, by dynamically updating the key coefficients involved in the real-time frictional resistance calculation using real-time monitoring values ​​of multi-source parameters and corresponding inversion and assimilation algorithms, the accuracy of real-time frictional resistance prediction throughout the caisson process is further improved.

[0048] This invention utilizes Persson theory and combines real-time acoustic inversion to dynamically update the cumulative roughness energy spectrum value of the soil power spectrum, thereby calculating a multi-scale friction mechanism that adapts to the spatiotemporal evolution of soil structures. Simultaneously, it constructs a dynamic equation for the friction coefficient using an extended RSF method to accurately predict the real-time frictional resistance during the caisson sinking process. Based on the real-time frictional resistance, it determines the caisson sinking control scheme, establishing a physical driving prediction and dynamic control system for the caisson wall-soil frictional resistance during the caisson sinking process.

[0049] In the present invention, the dynamic control method for caisson sinking friction based on multi-parameter real-time feedback includes the preset physical critical conditions including an instability resistance threshold and an effective yield strength threshold of the soil, and the control commands include grouting control commands and water pressure control commands; the step of generating control commands based at least on the real-time friction resistance and the preset physical critical conditions to dynamically control the caisson sinking process includes: When the real-time frictional resistance is greater than the instability resistance threshold, a grouting control command is triggered. When the real-time effective stress exceeds the effective yield strength threshold of the soil, a water pressure control command is triggered.

[0050] In this embodiment, the instability resistance threshold and the effective yield strength threshold of the soil are preset as preset physical critical conditions.

[0051] Optionally, the instability resistance threshold is based on the maximum static friction resistance F. crit The upper limit of friction force, which is not allowed to be exceeded during the sinking operation, is determined, and in this embodiment, it is preferably 0.75F. crit This serves as a better early warning system, triggering corresponding control commands when the real-time frictional resistance approaches the critical value, thus preventing "sudden sinking" accidents.

[0052] Specifically, a real-time frictional resistance greater than the instability resistance threshold indicates that the current real-time frictional resistance is approaching a critical condition and requires active drag reduction. Optionally, in this embodiment, a grouting control command is configured for this physical proximity condition to trigger the grouting control command under this condition, thereby achieving active lubrication and drag reduction through grouting.

[0053] Optionally, the grouting control command is used to invoke the zoned grouting system, enabling independent control of grouting in each zone. Optionally, the grout can be bentonite grout or other existing grouts that can provide lubrication and drag reduction, and grouting is performed according to preset pressure and preset flow rate. The preset pressure and preset flow rate can be determined empirically.

[0054] Preferably, the slurry viscosity according to Adaptive adjustment, where, The initial viscosity of the slurry. This represents the shear rate.

[0055] Optionally, the effective yield strength threshold of the soil is based on the effective yield strength of the soil. The critical stress value characterizing the soil entering plastic deformation or undergoing shear failure during the sinking operation is determined; in this embodiment, it is preferably 1.25. This allows for the triggering of control measures when the real-time effective stress drops to near the effective yield strength of the soil, thereby reducing pore water pressure and preventing soil collapse.

[0056] Among them, real-time effective stress Real-time monitoring value of normal stress Subtract pore water pressure When the real-time effective stress exceeds the effective yield strength threshold of the soil, the difference is used to promote drainage consolidation through negative pressure precipitation, thereby enhancing the shear strength of the soil. By actively raising the effective yield strength of the soil, the effective stress is restored to a safety margin under the new safety benchmark.

[0057] By using the above methods, the real-time frictional resistance and real-time effective stress are monitored during the caisson process, and the caisson status is monitored based on predetermined physical critical conditions, so as to trigger control measures in a timely manner, prevent "sudden sinking" or "hanging" accidents during the caisson process, and realize a dynamic control system based on real-time frictional resistance.

[0058] The present invention, a method for dynamic control of caisson sinking friction based on real-time feedback of multiple parameters, further includes: A PID controller is constructed using the difference between the real-time pore water pressure and the target pore water pressure as the deviation, which is used to calculate the amount of water to be regulated. The water pressure control command is generated based on the controlled water volume.

[0059] In this embodiment, a negative pressure precipitation system is constructed based on a PID controller to control the pumping volume. Adjustments are needed: , ; In the formula, , and These are the proportional gain coefficient, integral gain coefficient, and differential gain coefficient, respectively, representing the pore water pressure deviation based on real-time pore water pressure. With target pore water pressure The difference is defined.

[0060] Optionally, the target pore water pressure is based on the overlying soil. The pressure is determined, and in this embodiment, it is preferably 0.7. .

[0061] A PID controller based on pore water pressure deviation was constructed using the above method to achieve closed-loop control of the pumping volume, stabilizing the pore water pressure within the safe threshold limited by the overlying soil pressure, so as to eliminate the risk of soil instability caused by excessive pore pressure during the caisson process.

[0062] Then, based on the control quantity output by the PID controller, a water pressure control command is generated to achieve automatic control of pore water pressure.

[0063] The present invention, a method for dynamic control of caisson sinking friction based on real-time feedback of multiple parameters, further includes: The shear strength attenuation rate of the regulated soil and the grout diffusion radius are calculated to evaluate the regulation effect and serve as input for parameter feedback updates.

[0064] In order to evaluate the effect of the control measures and determine whether the caisson construction can continue or whether further control measures are needed, this embodiment uses an acoustic probe to monitor the attenuation rate of the soil shear strength after grouting.

[0065] The attenuation rate of soil shear strength is defined as the change in soil shear strength. Soil shear strength when triggering control command The ratio. Optionally, if the attenuation rate is less than a preset attenuation threshold, the control effect is deemed to have met the requirements. The preset attenuation threshold is an empirical value, set to 35% in this embodiment.

[0066] Furthermore, since control measures such as grouting / dewatering can also cause changes in the physical properties of the soil, in order to improve the accuracy of real-time frictional resistance prediction after control, this embodiment also inverts the grout diffusion radius based on real-time monitored shear wave velocity. R : ; In the formula, express t The cumulative grouting volume over time, This indicates the effective porosity of the soil.

[0067] Based on this, the actual value of the grout diffusion radius obtained from real-time shear wave velocity inversion is compared with the theoretical value of the grout diffusion radius calculated from the pre-calibrated effective porosity of the soil based on geotechnical tests. If the difference is less than an empirical threshold, the pre-calibrated effective porosity of the soil is considered effective; otherwise, the actual value of the effective porosity of the soil is obtained from the actual value of the grout diffusion radius inversion, and the effective porosity of the soil is updated. Finally, based on the actual value of the effective porosity of the soil and the pre-constructed relationship between porosity and soil power spectral density, the parameters used to calculate the real-time contact area are updated to achieve dynamic feedback optimization of the model parameters.

[0068] In the dynamic control method for caisson sinking friction based on multi-parameter real-time feedback of this invention, the rate-state friction equation derived from the expansion of soil plasticity index and pore water pressure is as follows: ; In the formula, The coefficient of friction, The static friction between the caisson sidewall and the soil is considered. The sinking speed of the caisson For reference speed, For contact state variables, As a reference state variable, I P The soil plasticity index. Pore ​​water pressure, For time, , , and To adjust the parameters.

[0069] Among them, the contact state variable characterizes the suppressive effect of pore water pressure transients on friction, satisfying the following conditions: , This represents the critical distance, which is the sliding distance required for the contact point to be completely refreshed.

[0070] The soil plasticity index is obtained in advance through geotechnical testing, and can be resampled and dynamically updated after the soil physical properties change due to control measures or other reasons during construction.

[0071] constant sinking speed v In this case, It is a first-order linear ordinary differential equation: ; In the formula, Indicates the reference state variable. This indicates the real-time sinking speed of the caisson. t Indicates the time of sinking.

[0072] Preferably, due to the speed during the sinking of the caisson The state variables may change over time; therefore, numerical methods are used to solve for them. : ; In the formula, Indicates the next moment k +1 contact state variable, Indicates the current time k Contact state variables, express k The sinking speed of the caisson at any given moment. Indicates the time step.

[0073] The above method enables the calculation of contact state variables based on real-time monitoring of the caisson sinking speed, and further calculation of the real-time friction coefficient, which is convenient for engineering applications.

[0074] In the dynamic control method for caisson sinking friction based on multi-parameter real-time feedback of this invention, the step of determining the real-time effective contact area between the caisson wall and the soil during the sinking process according to Persson's multi-scale contact theory includes: The cumulative roughness energy spectrum is determined by inverting the soil power spectral density function based on the soil shear wave velocity. The theoretical contact area ratio is determined based on the cumulative roughness energy spectrum. The real-time effective contact area is calculated based on the product of the theoretical contact area ratio and the theoretical contact area between the caisson sidewall and the soil.

[0075] In one feasible implementation, the theoretical expression for the real-time effective contact area based on Persson's theory is as follows: ; In the formula, express t Real-time effective contact area at any given moment. Represents the Persson function, The power spectral density at the interface between the well wall and the soil is obtained by inverting the soil power spectral density based on the real-time acquired shear wave velocity. express t The depth of the well at any given moment.

[0076] The expression for the Persson function is as follows: ; In the formula, This represents the theoretical contact area at time t.

[0077] in, , representing the roughness energy spectrum; For equivalent modulus, For power spectral density, q Indicates the mode of wave loss, This indicates that the lower limit of integration has been lost. This indicates the loss of the upper limit of integration.

[0078] Based on this, the soil power spectral density can be determined sequentially using the monitored soil shear wave velocity. Cumulative roughness energy spectrum Then determine the theoretical contact area ratio Ultimately, the real-time effective contact area can be calculated.

[0079] Preferably, although the above method can also realize the calculation of real-time effective area and dynamic optimization and updating of parameters, in order to make it more convenient to apply to engineering practice, this embodiment also provides a method for calculating real-time effective contact area considering the overconsolidation ratio of soil: ; In the formula, and The adjustment coefficient is determined by geotechnical testing. For soil yield strength, For effective stress, The overconsolidation ratio of the soil. This represents the theoretical contact area.

[0080] Alternatively, considering the influence of caisson depth and control measures on the physical properties of the soil, the adjustment coefficient in the above formula can be adjusted. and It can also be updated based on feedback from multiple sources monitored in real time.

[0081] For example, the roughness energy spectrum is inverted based on the real-time monitored shear wave velocity, and the real-time effective contact area is calculated based on the theoretical formula of the Persson model. This is then compared with the real-time effective contact area calculated using the formula incorporating OCR, and the adjustment coefficient is inverted and dynamically updated based on the difference. and It is understandable that if the soil layer type does not change during the current caisson process, or if the physical properties of the soil are not adjusted through control measures, the adjustment coefficient does not need to be repeatedly calibrated and updated, thus achieving a balance between calculation time and accuracy in engineering practice.

[0082] In the present invention, the dynamic control method for caisson sinking friction based on multi-parameter real-time feedback takes minimizing the total friction work of the system as the optimization objective of the dynamic control process.

[0083] In this embodiment, the caisson process is optimized by actively controlling and reducing the interfacial shear strength, with the goal of minimizing the total frictional work of the system.

[0084] Among them, interfacial shear strength The total frictional work of the system is calculated as follows: ; ; In the formula, Indicates real-time shear strength. Indicates the initial time. shear strength, The real-time friction coefficient, Indicates normal stress, This indicates pore water pressure.

[0085] In the formula, This represents the total frictional work of the system. v Indicates the real-time sinking speed. S Indicates the contact area. Indicates sliding displacement. Indicates the initial position.

[0086] Specifically, during the caisson process, the system calculates and monitors the total frictional work in real time. and will As a macroeconomic energy indicator, the value reflects the system's energy consumption level and guides the entire regulation process.

[0087] For example, with minimizing the total frictional work of the system as the optimization objective, the dissipation constraint is defined by the dissipation of the second law of thermodynamics, and the interfacial shear strength is used as the control variable. A series of optimal interfacial shear strength values ​​are obtained, and the key coefficient values ​​and / or boundary conditions of various control commands / control measures are determined based on these optimal values.

[0088] The following describes the dynamic control system for caisson sinking friction based on real-time feedback of multiple parameters provided by the present invention. The dynamic control system for caisson sinking friction based on real-time feedback of multiple parameters described below can be referred to in correspondence with the dynamic control method for caisson sinking friction based on real-time feedback of multiple parameters described above.

[0089] like Figure 3 As shown, the caisson sinking friction dynamic control system based on multi-parameter real-time feedback of the present invention includes an acquisition module 301, a prediction module 302 and a control module 303. The acquisition module 301 is used to monitor multi-source parameters in real time during the sinking process of the caisson, including the normal stress between the caisson wall and the soil, the soil shear wave velocity, the pore water pressure and the sinking speed of the caisson. Deploy appropriate sensors or measuring equipment to monitor multi-source parameters between the well wall and the soil during the sinking process of the caisson.

[0090] Optionally, by deploying fiber optic grating sensors in a matrix on the well wall, the normal stress between the well wall and the soil can be obtained based on wavelength drift decoupling. Preferably, the fiber Bragg grating sensors are deployed at a spacing of 1.5 meters × 1.5 meters.

[0091] Optionally, a piezoelectric acoustic probe array is arranged in a ring at the cutting edge to calculate the soil shear wave velocity using the transmit-receive time difference. And the soil shear strength is obtained by inversion. , This represents the soil density.

[0092] Alternatively, pore water pressure can be measured using a piezometer installed on the outside of the well wall.

[0093] Optionally, the sinking speed of the caisson can be monitored in real time via a GNSS receiver installed on top of the caisson.

[0094] In other feasible implementations, other feasible sensors or sensor networks can also be used to achieve real-time monitoring of multi-source parameters.

[0095] The prediction module 302 is used to determine the real-time effective contact area between the well wall and the soil during the sinking process based on the real-time monitoring values ​​of multi-source parameters, according to Persson's multi-scale contact theory, and to calculate the real-time friction coefficient during the sinking process based on the rate-state friction equation expanded by the soil plasticity index and pore water pressure. To accurately calculate the real-time frictional resistance of the caisson during the caisson process, this invention, based on the Persson multi-scale contact theory framework, couples the surface roughness of the concrete caisson with the homogeneous characteristics of the soil particle structure through a power spectral density function, describing the frictional resistance from micro-convexity (10) to micro-convexity (10) ... -6 The evolution of the actual contact area across macroscopic undulations (m) is used to obtain the real-time effective contact area between the caisson sidewall and the soil during the caisson process, replacing the conventionally used theoretical area of ​​the caisson sidewall for calculating frictional resistance.

[0096] Specifically, Persson's multiscale contact theory is an original theoretical framework describing the contact behavior of rough surfaces. This theory breaks through the limitations of traditional contact mechanics based on the assumption of discrete micro-convexities and solves the contact problem of cross-scale rough interfaces through continuous scale integration. Its physical core lies in treating the morphological features of rough surfaces as fractal geometry and using the power spectral density function C(q) of the surface height undulation as the core descriptive parameter.

[0097] The key expression for the actual contact area ratio derived from Persson's multi-scale contact theory is as follows: ; In the formula, Indicates the actual contact area. The theoretical contact area is represented by erf(), which represents the error function. The root mean square (RMS) of the roughness of the interface. G This represents the cumulative roughness energy spectrum.

[0098] The cumulative roughness energy spectrum is based on the power spectral density function. The points are obtained through integration.

[0099] Therefore, by monitoring the real-time shear wave velocity during the caisson sinking process, the power spectral density function of the soil-caisson wall interface can be obtained through acoustic inversion. Then further calculations can be performed. G The actual release area is calculated based on the area ratio contact formula and the theoretical contact area between the well wall and the soil.

[0100] On the other hand, this invention extends the Dieterich Rate-and-State Friction (RSF) law by introducing the soil plasticity index and pore water pressure to extend the original RSF method, thereby constructing a dynamic equation for the friction coefficient and calculating a more accurate real-time friction coefficient.

[0101] Based on this, the real-time friction coefficient during the caisson sinking process can be calculated using the extended RSF method, based on real-time monitoring of the caisson sinking speed, pore water pressure, and a pre-determined soil plasticity index.

[0102] The control module 303 is used to calculate the real-time frictional resistance of the caisson process based on the real-time effective contact area and the real-time friction coefficient, generate control commands based at least on the real-time frictional resistance and preset physical critical conditions, dynamically control the caisson sinking process, and update the parameters used to calculate the real-time frictional resistance according to the real-time monitoring values ​​of the multi-source parameters after control, for use in the calculation of the real-time frictional resistance in subsequent processes.

[0103] After determining the real-time friction coefficient and the real-time effective contact area, the real-time frictional resistance can be calculated using the real-time data of the coupled normal stress. : ; In the formula, S Indicates the contact surface area. Shear strength, for t Normal stress at time, for t pore water pressure at all times for t Effective contact area at all times This is the real-time friction coefficient.

[0104] Through the above methods, at the theoretical level, this invention creatively couples Persson's multiscale fractal theory in solid contact mechanics with the rate-state friction rate in geotechnical engineering. It simultaneously characterizes the rheological properties of soil reflected by the soil plasticity index, the bonding timeliness reflected by the contact state variables in the extended RSF, and the seepage field-stress coupling effect reflected by the transient term of pore water pressure. This allows for accurate and real-time monitoring of the real-time frictional resistance of the caisson throughout the entire caisson sinking process. Based on the more accurate real-time frictional resistance data, control commands are generated to regulate the caisson sinking process.

[0105] Optionally, one or more physical critical conditions can be preset to automatically regulate the sinking process of the caisson based on real-time frictional resistance and its derived parameters.

[0106] For example, by pre-setting an instability resistance threshold as a physical critical condition, when the real-time frictional resistance exceeds the preset instability resistance threshold, soil instability can be determined, and the soil needs to be stabilized in a timely manner by grouting or other feasible methods to prevent soil collapse.

[0107] For example, a speed threshold can be set directly. When the monitored real-time sinking speed of the caisson exceeds the preset speed threshold, the sinking speed can be indirectly controlled by adjusting the pore water pressure.

[0108] Optionally, the physical critical conditions can be pre-configured by those skilled in the art based on experience, combined with influencing factors such as the soil environment and caisson quality during the sinking construction, and the corresponding control instructions for each physical critical condition can be pre-configured according to the actual feasible control scheme at the construction site.

[0109] Based on this, if the real-time frictional resistance and / or other direct or indirect monitoring parameters monitored during the caisson process violate the preset physical critical conditions, the corresponding control command can be directly triggered to dynamically control the caisson process.

[0110] Furthermore, as the soil types traversed by the caisson change and / or the control commands affect the physical and mechanical properties of the soil, the contact state and material properties of the interface between the caisson wall and the soil also change. This leads to a mismatch between the key coefficients for calculating real-time frictional resistance based on previous working conditions (such as the coefficients of each term in the extended RSF equation) and the current actual working conditions. Therefore, by dynamically updating the key coefficients involved in the real-time frictional resistance calculation using real-time monitoring values ​​of multi-source parameters and corresponding inversion and assimilation algorithms, the accuracy of real-time frictional resistance prediction throughout the caisson process is further improved.

[0111] This invention utilizes Persson theory and combines real-time acoustic inversion to dynamically update the cumulative roughness energy spectrum value of the soil power spectrum, thereby calculating a multi-scale friction mechanism that adapts to the spatiotemporal evolution of soil structures. Simultaneously, it constructs a dynamic equation for the friction coefficient using an extended RSF method to accurately predict the real-time frictional resistance during the caisson sinking process. Based on the real-time frictional resistance, it determines the caisson sinking control scheme, establishing a physical driving prediction and dynamic control system for the caisson wall-soil frictional resistance during the caisson sinking process.

[0112] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other through the communication bus 440. The processor 410 can call logic instructions in the memory 430 to execute a dynamic control method for caisson sinking friction based on multi-parameter real-time feedback. This method includes: real-time monitoring of multi-source parameters during the caisson sinking process, including normal stress between the caisson wall and the soil, soil shear wave velocity, pore water pressure, and caisson sinking speed; determining the real-time effective contact area between the caisson wall and the soil during the sinking process based on the real-time monitoring values ​​of the multi-source parameters, according to Persson's multi-scale contact theory, and calculating the real-time friction coefficient during the sinking process based on the rate-state friction equation extended by the soil plasticity index and pore water pressure; calculating the real-time frictional resistance during the caisson process based on the real-time effective contact area and the real-time friction coefficient; generating control instructions based at least on the real-time frictional resistance and preset physical critical conditions to dynamically control the caisson sinking process; and updating the parameters used to calculate the real-time frictional resistance based on the real-time monitoring values ​​of the multi-source parameters after control, for use in subsequent calculations of the real-time frictional resistance.

[0113] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0114] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the dynamic control method for caisson sinking friction based on multi-parameter real-time feedback provided by the above methods. The method includes: real-time monitoring of multi-source parameters during the caisson sinking process, including normal stress between the caisson wall and the soil, soil shear wave velocity, pore water pressure, and caisson sinking speed; determining the real-time effective contact area between the caisson wall and the soil during the caisson sinking process based on the real-time monitoring values ​​of the multi-source parameters, according to Persson's multi-scale contact theory, and calculating the real-time friction coefficient during the caisson sinking process based on the rate-state friction equation extended by the soil plasticity index and pore water pressure; calculating the real-time frictional resistance during the caisson process based on the real-time effective contact area and the real-time friction coefficient; generating control commands based at least on the real-time frictional resistance and preset physical critical conditions to dynamically control the caisson sinking process; and updating the parameters used to calculate the real-time frictional resistance based on the real-time monitoring values ​​of the multi-source parameters after control, for use in subsequent calculations of the real-time frictional resistance.

[0115] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the above-described method for dynamic control of caisson sinking friction based on multi-parameter real-time feedback. This method includes: real-time monitoring of multi-source parameters during the caisson sinking process, including normal stress between the caisson wall and the soil, soil shear wave velocity, pore water pressure, and caisson sinking speed; determining the real-time effective contact area between the caisson wall and the soil during the sinking process based on the real-time monitoring values ​​of the multi-source parameters, according to Persson's multi-scale contact theory, and calculating the real-time friction coefficient during the sinking process based on the rate-state friction equation extended by the soil plasticity index and pore water pressure; calculating the real-time frictional resistance during the caisson process based on the real-time effective contact area and the real-time friction coefficient; generating control commands based at least on the real-time frictional resistance and preset physical critical conditions to dynamically control the caisson sinking process; and updating the parameters used to calculate the real-time frictional resistance based on the real-time monitoring values ​​of the multi-source parameters after control, for use in subsequent calculations of the real-time frictional resistance.

[0116] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0117] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0118] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for dynamic control of caisson sinking friction based on real-time feedback of multiple parameters, characterized in that, include: Real-time monitoring of multiple parameters during the caisson sinking process, including normal stress between the caisson wall and the soil, soil shear wave velocity, pore water pressure, and caisson sinking speed; Based on the real-time monitoring values ​​of multi-source parameters, the real-time effective contact area between the well wall and the soil during the sinking process of the caisson is determined according to the Persson multi-scale contact theory, and the real-time friction coefficient during the sinking process is calculated based on the rate-state friction equation of soil plasticity index and pore water pressure expansion. The real-time frictional resistance during the caisson sinking process is calculated based on the real-time effective contact area and the real-time friction coefficient. Control commands are generated based on at least the real-time frictional resistance and preset physical critical conditions to dynamically control the caisson sinking process. The parameters used to calculate the real-time frictional resistance are updated based on the real-time monitoring values ​​of the multi-source parameters after control, and used for the calculation of the real-time frictional resistance in subsequent processes.

2. The method for dynamic control of caisson sinking friction based on multi-parameter real-time feedback according to claim 1, characterized in that, The preset physical critical conditions include the instability resistance threshold and the effective yield strength threshold of the soil; the control commands include grouting control commands and water pressure control commands. The step of generating control commands based at least on the real-time frictional resistance and preset physical critical conditions to dynamically control the sinking process of the caisson includes: When the real-time frictional resistance is greater than the instability resistance threshold, a grouting control command is triggered. When the real-time effective stress exceeds the effective yield strength threshold of the soil, a water pressure control command is triggered.

3. The method for dynamic control of caisson sinking friction based on real-time feedback of multiple parameters as described in claim 2, characterized in that, Also includes: The shear strength attenuation rate of the regulated soil and the grout diffusion radius are calculated to evaluate the regulation effect and serve as input for parameter feedback updates.

4. The method for dynamic control of caisson sinking friction based on multi-parameter real-time feedback according to claim 2, characterized in that, Also includes: A PID controller is constructed using the difference between the real-time pore water pressure and the target pore water pressure as the deviation, which is used to calculate the amount of water to be regulated. The water pressure control command is generated based on the controlled water volume.

5. The method for dynamic control of caisson sinking friction based on real-time feedback of multiple parameters as described in any one of claims 1-4, characterized in that, The rate-state friction equation, which is derived from the soil plasticity index and pore water pressure, is as follows: ； In the formula, The coefficient of friction, The static friction between the caisson sidewall and the soil is considered. The sinking speed of the caisson For reference speed, For contact state variables, As a reference state variable, I P The soil plasticity index. Pore ​​water pressure, For time, , , and To adjust the parameters.

6. The method for dynamic control of caisson sinking friction based on real-time feedback of multiple parameters as described in any one of claims 1-4, characterized in that, The steps for determining the real-time effective contact area between the well wall and the soil during the caisson sinking process based on Persson's multi-scale contact theory include: The cumulative roughness energy spectrum is determined by inverting the soil power spectral density function based on the soil shear wave velocity. The theoretical contact area ratio is determined based on the cumulative roughness energy spectrum. The real-time effective contact area is calculated based on the product of the theoretical contact area ratio and the theoretical contact area between the caisson sidewall and the soil.

7. The method for dynamic control of caisson sinking friction based on real-time feedback of multiple parameters as described in claim 1, characterized in that, Also includes: The optimization objective of the dynamic control process is to minimize the total frictional work of the system.

8. A dynamic control system for caisson sinking friction based on multi-parameter real-time feedback, characterized in that, include: The acquisition module is used to monitor multi-source parameters in real time during the sinking process of the caisson, including the normal stress between the caisson wall and the soil, the soil shear wave velocity, the pore water pressure, and the sinking speed of the caisson. The prediction module is used to determine the real-time effective contact area between the well wall and the soil during the sinking process based on the real-time monitoring values ​​of multi-source parameters, according to Persson's multi-scale contact theory, and to calculate the real-time friction coefficient during the sinking process based on the rate-state friction equation which is derived from the soil plasticity index and pore water pressure. The control module is used to calculate the real-time frictional resistance during the caisson sinking process based on the real-time effective contact area and the real-time friction coefficient. It generates control commands based at least on the real-time frictional resistance and preset physical critical conditions to dynamically control the caisson sinking process. It also updates the parameters used to calculate the real-time frictional resistance based on the real-time monitoring values ​​of the multi-source parameters after control, which are used for the calculation of the real-time frictional resistance in subsequent processes.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the dynamic control method for caisson sinking friction based on real-time feedback of multiple parameters as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the dynamic control method for caisson sinking friction based on real-time feedback of multiple parameters as described in any one of claims 1 to 7.

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