N-jet method superhigh pressure jet grouting self-adapting construction control method

Abstract

The application discloses a kind of N-Jet method superhigh pressure jet grouting self-adapting construction control method, belongs to geotechnical engineering construction control technical field, including stratum impedance identification, impedance perception control modeling and self-adapting construction control.The application is modeling analysis to the pressure change caused by construction disturbance, and realizes the decoupling of construction disturbance and stratum response by residual feature extraction, improves the accuracy of stratum impedance identification, realizes real-time perception to the stratum state of construction area;Based on stratum impedance parameter, the cutting energy state is perceived modeling, and the construction parameters are optimized by constructing self-adapting construction control model, so that jet energy can be dynamically matched according to different stratum conditions, improve jet cutting efficiency and grouting reinforcement effect;Periodic correction is carried out to construction parameters by real-time equivalent cutting energy feedback, realizes construction process closed-loop self-adapting control, reduces the dependence of artificial experience adjustment, improves construction process stability and pile quality consistency.

Description

Technical Field

[0001] This invention belongs to the field of geotechnical engineering construction control technology, specifically referring to an adaptive construction control method for N-Jet ultra-high pressure jet grouting. Background Technology

[0002] N-Jet ultra-high pressure jet grouting is a foundation treatment technology that uses ultra-high pressure jets to cut and break up the strata and mix them with grout to form a solidified body. It is widely used in engineering fields such as soft soil foundation reinforcement, underground engineering water shut-off, and foundation reinforcement of existing buildings. During construction, construction parameters such as jet pressure, grout flow rate, boom lifting speed, and rotation speed directly affect the jet energy effect, and further influence the pile diameter, uniformity, and reinforcement quality.

[0003] However, due to the significant heterogeneity of the geological structure within the construction area, the soil density, particle composition, and mechanical properties vary at different locations, resulting in substantial variations in the energy consumption and cutting effect of the jet grouting in different strata. Currently, during the N-Jet method of ultra-high pressure jet grouting, construction parameters are typically set based on experience or adjusted according to the judgment of the construction personnel, lacking the ability to perceive changes in geological impedance during construction in real time. This makes it difficult to dynamically match the jetting energy according to the actual geological conditions, affecting the stability of the construction results.

[0004] Meanwhile, during ultra-high pressure jet grouting, the pressure response is affected not only by changes in formation impedance but also by construction disturbances. Existing technologies typically rely directly on pressure changes to determine formation conditions, which can easily lead to misinterpreting pressure fluctuations caused by construction disturbances as formation changes, resulting in insufficient accuracy in formation identification. Furthermore, current construction control methods often lack correlation analysis between formation conditions, energy input, and construction parameters, making it impossible to collaboratively optimize construction parameters based on real-time formation conditions. This can easily lead to localized energy shortages or excesses, affecting the grouting reinforcement effect and construction stability.

[0005] Therefore, there is an urgent need for an adaptive construction control method that can accurately identify the formation impedance during the N-Jet ultra-high pressure jet grouting process, dynamically optimize construction parameters based on formation conditions, and achieve closed-loop adjustment by combining construction feedback, so as to improve the intelligence level of the construction process and the stability of pile quality. Summary of the Invention

[0006] To address the above issues and overcome the shortcomings of existing technologies, this invention provides an adaptive construction control method for N-Jet ultra-high pressure jet grouting, which includes the following steps:

[0007] Step S1: Formation impedance identification;

[0008] Step S2: Impedance sensing control modeling;

[0009] Step S3: Adaptive construction control.

[0010] Further, in step S1, the formation impedance identification specifically involves collecting pressure response signals and construction parameters during the N-Jet method ultra-high pressure jet grouting construction process, constructing a pressure response feature vector, modeling and analyzing the impact of construction disturbances in the pressure response and decoupling the process, extracting impedance-sensitive feature vectors characterizing the formation response, and then obtaining formation impedance parameters through the establishment of a formation impedance identification model, including the following steps:

[0011] Step S11, time-frequency feature construction, is used to obtain the pressure response feature vector reflecting the change of formation impedance during the ultra-high pressure jetting process of the N-Jet method. Specifically, by collecting the pressure response signal during the construction process of ultra-high pressure jetting grouting of the N-Jet method, multi-scale frequency domain analysis is performed on the pressure response signal to extract the pressure frequency features, amplitude features and energy distribution features at different time scales, and construct the pressure response feature vector.

[0012] Step S12 synchronous modeling of construction disturbance state, specifically, synchronously collecting construction parameters during the N-Jet method ultra-high pressure jet grouting construction process, constructing a construction disturbance state vector based on the construction parameters and their changes, and then establishing a mapping relationship between the construction disturbance state vector and the pressure response signal change based on the construction disturbance state vector to obtain the theoretical construction disturbance pressure response.

[0013] Step S13, pressure response decoupling analysis, is used to separate the pressure changes caused by construction disturbance from the pressure changes caused by formation impedance. Specifically, by calculating the difference between the pressure response signal and the theoretical construction disturbance pressure response, the influence of pressure disturbance caused by changes in construction parameters is separated to obtain the residual pressure response. Then, frequency domain analysis is performed on the residual pressure response to extract the residual pressure main frequency, residual pressure amplitude, and residual frequency band energy, and an impedance-sensitive feature vector is constructed.

[0014] Step S14 involves establishing a formation impedance identification model, specifically by fusing the pressure response feature vector and the impedance-sensitive feature vector to construct a comprehensive impedance feature, which is then input into the pre-established impedance identification model for feature mapping calculation to obtain the formation impedance parameters corresponding to the current construction state.

[0015] Further, in step S2, the impedance-sensing control modeling specifically involves sensing and modeling the cutting energy state based on formation impedance parameters, and establishing an adaptive control model for construction parameters using a reinforcement learning algorithm to obtain construction optimization parameters dynamically adjusted according to the formation state. This includes the following steps:

[0016] Step S21 is to model the cutting energy state at a depth, which is used to establish the correlation between formation impedance and cutting energy state. Specifically, it is to calculate the cutting energy per unit depth based on construction parameters, and then introduce formation impedance parameters to dynamically correct the cutting energy per unit depth to obtain the equivalent cutting energy.

[0017] Step S22 Control model construction: Specifically, the target cutting energy is determined based on the formation impedance parameters. The construction state space is constructed by combining the formation impedance parameters, construction parameters and equivalent cutting energy. The action space is set according to the adjustment amount corresponding to the construction parameters. The reward function is constructed based on the deviation between the equivalent cutting energy and the target cutting energy and the amplitude of the control action. The mapping relationship between the state and the action is trained by the reinforcement learning algorithm to establish an adaptive construction control model.

[0018] Step S23 involves optimizing and controlling construction parameters. Specifically, the formation impedance parameters, equivalent cutting energy, and current construction parameters are input into the adaptive construction control model to obtain the optimal construction parameter adjustment amount. The current construction parameters are then adjusted to obtain the optimized construction parameters.

[0019] Further, in step S3, the adaptive construction control is used to control the N-Jet equipment to perform jet grouting based on the construction optimization parameters obtained in step S2, and to perform feedback correction based on the cutting energy state during the construction process. Specifically, the construction optimization parameters are converted into equipment execution commands to control the construction equipment actuator to perform ultra-high pressure jet grouting construction. During the construction process, construction parameters are collected in real time, the real-time equivalent cutting energy is calculated, and the construction parameters for the next control cycle are corrected based on the deviation between the real-time equivalent cutting energy and the target cutting energy, thereby realizing closed-loop adaptive control of the N-Jet jet grouting process.

[0020] The beneficial effects achieved by the present invention using the above solution are as follows:

[0021] (1) This scheme collects pressure response signals and construction parameters during the ultra-high pressure jet grouting process, models and analyzes the pressure changes caused by construction disturbance, and decouples construction disturbance and formation response by extracting residual features, thereby improving the accuracy of formation impedance identification and realizing real-time perception of the formation status in the construction area.

[0022] (2) This scheme uses the formation impedance parameters to sense and model the cutting energy state, and optimizes the construction parameters by constructing an adaptive construction control model, so that the jetting energy can be dynamically matched according to different formation conditions, thereby improving the jet cutting efficiency and grouting reinforcement effect.

[0023] (3) This scheme uses real-time equivalent cutting energy feedback to periodically correct construction parameters, realizes closed-loop adaptive control of the N-Jet method ultra-high pressure jet grouting process, reduces reliance on manual experience adjustment, and improves the stability of the construction process and the consistency of pile quality. Attached Figure Description

[0024] Figure 1 A schematic diagram of the process for an adaptive construction control method for ultra-high pressure jet grouting using the N-Jet method provided by this invention;

[0025] Figure 2 This is a flowchart illustrating the process of formation impedance identification in step S1.

[0026] Figure 3 A schematic diagram of the process for modeling impedance sensing control in step S2.

[0027] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. Detailed Implementation

[0028] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0029] In the description of this invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0030] Example 1, see Figure 1 This invention provides an adaptive construction control method for ultra-high pressure jet grouting using the N-Jet method, which includes the following steps:

[0031] Step S1: Formation impedance identification;

[0032] Step S2: Impedance sensing control modeling;

[0033] Step S3: Adaptive construction control.

[0034] Example 2, see Figure 1 and Figure 2This embodiment is based on the above embodiment. In step S1, the formation impedance identification specifically involves collecting pressure response signals and construction parameters during the N-Jet method ultra-high pressure jet grouting construction process, constructing a pressure response feature vector, modeling and analyzing the impact of construction disturbances in the pressure response and decoupling the process, extracting impedance-sensitive feature vectors characterizing the formation response, and then obtaining formation impedance parameters through the establishment of a formation impedance identification model. The process includes the following steps:

[0035] Step S11, time-frequency feature construction, is used to obtain the pressure response feature vector reflecting the change of formation impedance during the ultra-high pressure jetting process of the N-Jet method. Specifically, by collecting the pressure response signal during the construction process of ultra-high pressure jetting grouting of the N-Jet method, multi-scale frequency domain analysis is performed on the pressure response signal to extract the pressure frequency features, amplitude features and energy distribution features at different time scales, and construct the pressure response feature vector.

[0036] In the specific implementation process, the multi-scale frequency domain analysis specifically involves dividing the pressure response signal according to different time scales, performing frequency domain analysis on the pressure response signal at each scale, obtaining the corresponding spectrum information, and extracting pressure frequency features, amplitude features, and energy distribution features to construct a pressure response feature vector.

[0037] Step S12 synchronous modeling of construction disturbance state, specifically, synchronously collecting construction parameters during the N-Jet method ultra-high pressure jet grouting construction process, and constructing a construction disturbance state vector based on the construction parameters and their changes. Then, based on the construction disturbance state vector, a mapping relationship between the construction disturbance state vector and the change in pressure response signal is established to obtain the theoretical construction disturbance pressure response caused by the change in construction parameters under the current construction state.

[0038] In the specific implementation process, since the pressure change during the N-Jet ultra-high pressure jet grouting process is affected not only by the change in formation impedance, but also by the equipment operating status and the adjustment of construction actions, construction parameters are acquired simultaneously while collecting pressure response signals. The construction parameters include jetting pressure, grout flow rate, boom lifting speed and boom rotation speed.

[0039] The formula for calculating the construction disturbance state vector is:

[0040] ;

[0041] In the formula, X c Let P represent the construction disturbance state vector, Q represent the slurry flow rate, V represent the boom lifting speed, and R represent the boom rotation speed. This indicates the change in the lifting speed of the spray boom. This indicates the change in the rotational speed of the spray boom;

[0042] Specifically, the mapping relationship between the construction disturbance state vector and the change in pressure response signal can be established using a regression model trained based on historical construction data. During the training process, the construction disturbance state vector is used as the input, and the change in pressure response signal caused by the change in corresponding construction parameters during historical construction is used as the training target.

[0043] Step S13, pressure response decoupling analysis, is used to separate the pressure changes caused by construction disturbance from the pressure changes caused by formation impedance. Specifically, by calculating the difference between the pressure response signal and the theoretical construction disturbance pressure response, the influence of pressure disturbance caused by changes in construction parameters is separated to obtain the residual pressure response. Then, frequency domain analysis is performed on the residual pressure response to extract the residual pressure main frequency, residual pressure amplitude, and residual frequency band energy, and an impedance-sensitive feature vector is constructed.

[0044] In practical implementation, the impedance-sensitive eigenvector is used to characterize the formation response characteristics after removing construction disturbances, and the calculation formula is as follows:

[0045] ;

[0046] In the formula, X z f represents the impedance-sensitive eigenvector. r Indicates the residual pressure main frequency, A r E represents the residual pressure amplitude. r Represents the residual frequency band energy;

[0047] Step S14 Establishment of Formation Impedance Identification Model: Specifically, the pressure response feature vector and impedance-sensitive feature vector are fused to construct a comprehensive impedance feature and input into the pre-established impedance identification model. Feature mapping calculation is then performed to obtain the formation impedance parameters corresponding to the current construction state.

[0048] In the specific implementation process, the fusion specifically involves normalizing the pressure response feature vector and the impedance sensitivity feature vector to eliminate the dimensional differences between different feature parameters, and then weighting and splicing them according to preset weights to obtain a comprehensive impedance feature vector.

[0049] The impedance identification model can be implemented using a support vector regression model, a random forest model, a neural network model, or a long short-term memory network model, and the model parameters are trained and optimized using historical construction data. Specifically, the comprehensive impedance characteristics obtained during historical construction are used as the model input, and the formation impedance parameters obtained by calibration through geotechnical test parameters, standard penetration test results, or historical construction feedback data are used as the model output labels to construct a training sample set and iteratively update the internal parameters of the model, so that the impedance identification model can establish a mapping relationship between comprehensive impedance characteristics and formation impedance parameters.

[0050] By performing the above operations, this solution simultaneously collects pressure response signals and construction parameters during the ultra-high pressure jet grouting process, models and analyzes the pressure changes caused by construction disturbances, and decouples construction disturbances from formation responses through residual feature extraction, thereby improving the accuracy of formation impedance identification and enabling real-time perception of the formation status in the construction area.

[0051] Example 3, see Figure 1 and Figure 3 This embodiment is based on the above embodiment. In step S2, the impedance sensing control modeling specifically involves sensing and modeling the cutting energy state based on the formation impedance parameters, and establishing an adaptive control model for construction parameters using a reinforcement learning algorithm to obtain construction optimization parameters that are dynamically adjusted according to the formation state. This includes the following steps:

[0052] Step S21 is to model the cutting energy state at depth, which is used to establish the correlation between formation impedance and cutting energy state. Specifically, the cutting energy per unit depth is calculated based on construction parameters, and then formation impedance parameters are introduced to dynamically correct the cutting energy per unit depth, so as to obtain the equivalent cutting energy considering the influence of formation impedance.

[0053] In practical implementation, the cutting energy per unit depth is used to characterize the effect of the current construction parameters, and the calculation formula is as follows:

[0054] ;

[0055] In the formula, E d P represents the cutting energy per unit depth; Q represents the slurry flow rate; and V represents the boom lifting speed.

[0056] The formula for calculating the equivalent cutting energy is as follows:

[0057] ;

[0058] In the formula, E e Represents the equivalent cutting energy. Z represents the formation impedance influence coefficient, used to characterize the degree of influence of formation impedance variation on cutting energy per unit depth. Specifically, it is determined by fitting the relationship between formation impedance parameters and cutting energy variations in historical construction data. s Indicates formation impedance parameters;

[0059] Step S22 Control model construction: Specifically, the target cutting energy is determined based on the formation impedance parameters. The construction state space is constructed by combining the formation impedance parameters, construction parameters and equivalent cutting energy. The action space is set according to the adjustment amount corresponding to the construction parameters. The reward function is constructed based on the deviation between the equivalent cutting energy and the target cutting energy and the amplitude of the control action. The mapping relationship between the state and the action is trained by the reinforcement learning algorithm to establish an adaptive construction control model.

[0060] In the specific implementation process, the target cutting energy determined based on formation impedance parameters is used to dynamically adjust the reinforcement learning control target according to different formation impedance states. The calculation formula is as follows:

[0061] ;

[0062] In the formula, E0 represents the target cutting energy, and E0 represents the foundation cutting energy. Specifically, it is obtained by conducting experimental construction within the target construction area and statistically analyzing the average cutting energy per unit depth when the pile quality requirements are met. This represents the formation impedance adjustment coefficient, which is specifically determined by fitting the correspondence between formation impedance parameters and cutting energy requirements per unit depth in historical construction data.

[0063] The action space is used to describe the range of construction parameter adjustments that the model can perform, and the adjustment amounts of spray pressure, spray boom rotation speed and spray boom lifting speed are used as control actions;

[0064] The formula for calculating the reward function is as follows:

[0065] ;

[0066] In the formula, r(k) represents the reward function value of the k-th control cycle, and k represents the control cycle index. This represents the energy error weight, and its specific value is set according to the construction control accuracy requirements. This represents the equivalent cutting energy in the k-th control cycle. This represents the target cutting energy in the k-th control cycle. This represents the weight of the motion smoothing constraint, and its value is set according to the equipment's response capability and the allowable range of variation of construction parameters. This represents the control action in the k-th control cycle. The L2 norm operator is used to measure the magnitude of change in control actions.

[0067] Step S23 involves optimizing and controlling construction parameters. Specifically, the formation impedance parameters, equivalent cutting energy, and current construction parameters are input into the adaptive construction control model to obtain the optimal construction parameter adjustment amount. The current construction parameters are then adjusted to obtain the optimized construction parameters.

[0068] By performing the above operations, this scheme uses formation impedance parameters to perceive and model the cutting energy state, and optimizes the construction parameters by constructing an adaptive construction control model, so that the jetting energy can be dynamically matched according to different formation conditions, thereby improving the jet cutting efficiency and grouting reinforcement effect.

[0069] Example 4, see Figure 1 This embodiment is based on the above embodiment. In step S3, the adaptive construction control is used to control the N-Jet equipment to perform jet grouting construction according to the construction optimization parameters obtained in step S2, and to perform feedback correction according to the cutting energy state during the construction process. Specifically, the construction optimization parameters are converted into equipment execution instructions, the construction equipment execution mechanism is controlled to perform ultra-high pressure jet grouting construction, and construction parameters are collected in real time during the construction process, the real-time equivalent cutting energy is calculated, and the construction parameters of the next control cycle are corrected according to the deviation between the real-time equivalent cutting energy and the target cutting energy, so as to realize the closed-loop adaptive control of the N-Jet jet grouting process.

[0070] In the specific implementation process, the construction parameters for the next control cycle are corrected based on the deviation between the real-time equivalent cutting energy and the target cutting energy. Specifically, the difference between the real-time equivalent cutting energy and the target cutting energy is calculated to obtain the equivalent cutting energy deviation. When the equivalent cutting energy deviation is within a preset range, the current construction optimization parameters are maintained and continue to be executed. Otherwise, the equivalent cutting energy deviation is fed back to the adaptive construction control model established in step S22, and the adaptive construction control model generates the optimal construction parameter adjustment amount for the next control cycle. The preset range is specifically determined by statistically analyzing the equivalent cutting energy fluctuation range that meets the pile quality requirements in historical construction data.

[0071] By performing the above operations, this scheme periodically corrects the construction parameters through real-time equivalent cutting energy feedback, realizing closed-loop adaptive control of the N-Jet method ultra-high pressure jet grouting process, reducing reliance on manual experience adjustments, and improving the stability of the construction process and the consistency of pile quality.

[0072] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0073] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

[0074] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. An adaptive construction control method for ultra-high pressure jet grouting using the N-Jet method, characterized in that: The method includes the following steps: Step S1 Formation impedance identification specifically involves collecting pressure response signals and construction parameters during the N-Jet method ultra-high pressure jet grouting construction process, constructing a pressure response feature vector, modeling and analyzing the impact of construction disturbances in the pressure response and decoupling the process, extracting impedance-sensitive feature vectors that characterize the formation response characteristics, and then obtaining formation impedance parameters through the formation impedance identification model. The sub-steps of step S1 include step S11 time-frequency feature construction, step S12 synchronous modeling of construction disturbance state, step S13 pressure response decoupling analysis, and step S14 formation impedance identification model establishment. Step S2, impedance sensing control modeling, specifically involves sensing and modeling the cutting energy state based on formation impedance parameters, and establishing an adaptive control model for construction parameters using reinforcement learning algorithms to obtain construction optimization parameters that are dynamically adjusted according to the formation state. The sub-steps of step S2 include step S21 deep cutting energy state modeling, step S22 control model construction, and step S23 construction parameter optimization control. Step S3 is adaptive construction control, which is used to control the N-Jet equipment to perform spraying construction based on the construction optimization parameters obtained in step S2, and to make feedback corrections based on the cutting energy state during the construction process.

2. The adaptive construction control method for ultra-high pressure jet grouting using the N-Jet method according to claim 1, characterized in that: Step S11, time-frequency feature construction, is used to obtain the pressure response feature vector reflecting the change of formation impedance during the ultra-high pressure jetting process of the N-Jet method. Specifically, by collecting the pressure response signal during the construction process of ultra-high pressure jetting grouting of the N-Jet method, multi-scale frequency domain analysis is performed on the pressure response signal to extract the pressure frequency characteristics, amplitude characteristics and energy distribution characteristics at different time scales, and to construct the pressure response feature vector.

3. The adaptive construction control method for N-Jet ultra-high pressure jet grouting according to claim 2, characterized in that: Step S12 involves synchronous modeling of construction disturbance state, specifically by synchronously collecting construction parameters during the N-Jet method ultra-high pressure jet grouting construction process, constructing a construction disturbance state vector based on the construction parameters and their changes, and then establishing a mapping relationship between the construction disturbance state vector and the pressure response signal change based on the construction disturbance state vector to obtain the theoretical construction disturbance pressure response.

4. The adaptive construction control method for ultra-high pressure jet grouting using the N-Jet method according to claim 3, characterized in that: Step S13, pressure response decoupling analysis, is used to separate the pressure changes caused by construction disturbance from the pressure changes caused by formation impedance. Specifically, by calculating the difference between the pressure response signal and the theoretical construction disturbance pressure response, the influence of pressure disturbance caused by changes in construction parameters is separated to obtain the residual pressure response. Then, frequency domain analysis is performed on the residual pressure response to extract the residual pressure main frequency, residual pressure amplitude, and residual frequency band energy, and an impedance-sensitive feature vector is constructed.

5. The adaptive construction control method for ultra-high pressure jet grouting using the N-Jet method according to claim 4, characterized in that: Step S14 involves establishing a formation impedance identification model, specifically by fusing the pressure response feature vector and the impedance-sensitive feature vector to construct a comprehensive impedance feature, which is then input into the pre-established impedance identification model for feature mapping calculation to obtain the formation impedance parameters corresponding to the current construction state.

6. The adaptive construction control method for ultra-high pressure jet grouting in the N-Jet method according to claim 5, characterized in that: Step S21 is to model the cutting energy state at a depth, which is used to establish the correlation between formation impedance and cutting energy state. Specifically, it is to calculate the cutting energy per unit depth based on construction parameters, and then introduce formation impedance parameters to dynamically correct the cutting energy per unit depth to obtain the equivalent cutting energy. Step S22 involves constructing the control model, specifically by determining the target cutting energy based on the formation impedance parameters, constructing the construction state space by combining the formation impedance parameters, construction parameters, and equivalent cutting energy, setting the action space according to the adjustment amount corresponding to the construction parameters, constructing a reward function based on the deviation between the equivalent cutting energy and the target cutting energy and the amplitude of the control action, and training the mapping relationship between the state and the action through a reinforcement learning algorithm to establish an adaptive construction control model.

7. The adaptive construction control method for ultra-high pressure jet grouting using the N-Jet method according to claim 6, characterized in that: Step S23 involves optimizing and controlling construction parameters. Specifically, the formation impedance parameters, equivalent cutting energy, and current construction parameters are input into the adaptive construction control model to obtain the optimal construction parameter adjustment amount. The current construction parameters are then adjusted to obtain the optimized construction parameters.

8. The adaptive construction control method for ultra-high pressure jet grouting using the N-Jet method according to claim 7, characterized in that: In step S3, the adaptive construction control is used to control the N-Jet equipment to perform jet grouting based on the construction optimization parameters obtained in step S2, and to perform feedback correction based on the cutting energy state during the construction process. Specifically, the construction optimization parameters are converted into equipment execution commands to control the construction equipment actuator to perform ultra-high pressure jet grouting construction. During the construction process, construction parameters are collected in real time, the real-time equivalent cutting energy is calculated, and the construction parameters for the next control cycle are corrected based on the deviation between the real-time equivalent cutting energy and the target cutting energy, thereby realizing closed-loop adaptive control of the N-Jet jet grouting process.

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