A construction method for inclined bracing of foundation pit

Abstract

The present invention discloses a construction method for inclined bracing of foundation pits, belonging to the technical field of foundation pit support engineering. A construction method for inclined bracing of foundation pits includes the following steps: S1. Based on the depth-stratified initial inclination parameter framework, dynamically correct the support geometric shape and axial force reference in combination with the soil layer wave velocity; S2. Three-dimensional laser grid and ink line verification, output tolerance drawings, and lock the S3 process when exceeding the limit; S3. Excavate according to the sine ratio, stop excavation in case of abnormal seepage, and dynamically compress the installation window period of the inclined strut with axial force data; S4. Stage torque control; S5. Wireless sensing monitors the axial force, and a linkage of ±15% deviation triggers S6 grouting compensation and reuse of the detachable sleeve monitoring unit; S6. The grouting pressure is linearly related to the depth, and when the foundation displacement exceeds the limit, the pressure is increased by 0.2 MPa / level, and the S7 redundancy threshold is interlocked; S7. Construct a three-dimensional acceptance model by integrating multi-source data, and automatically generate an evaluation report by comparing with the standard; The beneficial effects include millimeter-level precision construction control, achieving the effect of optimizing the full-cycle cost.

Description

Technical Field

[0001] The present invention relates to the technical field of foundation pit support engineering, and more specifically, to a construction method for inclined support of a foundation pit. Background Art

[0002] With the development of urban underground space towards deeper, larger and more complex directions, traditional inclined support technologies for foundation pits are facing severe challenges. Existing methods mostly adopt fixed inclination angle designs, ignoring the impact of dynamic changes in geological conditions on the support system, resulting in problems such as stress concentration or insufficient stiffness in the support structure. In conventional construction, the setting of pre-axial force parameters relies on empirical formulas and lacks dynamic adaptation to soil layer characteristics, often causing excessive support deformation in soft soil or high water table strata. The positioning system mostly uses a single manual layout method, and the cumulative error is difficult to control, especially in deep foundation pits, where millimeter-level deviation cumulative effects are likely to occur. Existing monitoring systems mostly operate as independent modules, with serious data island phenomena and unable to achieve real-time closed-loop optimization of construction parameters. More critically, traditional methods lack dynamic coupling control of the support installation window period and excavation progress, leading to an increased risk of support lag. According to statistics, approximately 23% of foundation pit accidents are caused by the lag in the response of the support system. These defects seriously restrict the safety and economy of deep foundation pit construction, and there is an urgent need to establish a dynamic control system with intelligent decision-making capabilities. Summary of the Invention

[0003] The present invention proposes a construction method for inclined support of a foundation pit, aiming to achieve adaptive adjustment of construction parameters according to geological conditions and project progress by establishing a closed-loop system of inclination angle dynamic compensation, multi-source data interlock control and intelligent decision-making optimization, and significantly improving the safety and construction efficiency of deep foundation pit support structures.

[0004] Technical Solution: A construction method for inclined support of a foundation pit includes the following steps:

[0005] S1. Establish a dynamic adjustment mechanism for the reference inclination angle based on the designed depth of the foundation pit and geological conditions: The reference inclination angle is the angle between the axis of the inclined support and the vertical direction of the foundation pit. The initial reference inclination angle is set at 35 degrees, and a gradient compensation of 0.2 degrees is carried out for each 1-meter increase in depth. When the detected value of the soil layer shear wave velocity is lower than the critical threshold, the geological compensation mechanism is triggered to supplement and correct the reference inclination angle; simultaneously execute: Calculate the theoretical reference value of the pre-axial force according to the logarithmic relationship of the foundation pit depth, and then perform mechanical adaptation calculation and correction on this theoretical reference value according to the compressive bearing capacity corresponding to the thickness of the embedded steel plate and the design value of the shear bearing capacity of high-strength bolts to generate the final reference value; form a dual reference system including geometric parameters and mechanical parameters;

[0006] S2. Generate a 3D laser positioning grid based on the geometric reference parameters output by S1. After verifying the 3D laser positioning grid with the manual ink line reference line, output a digital construction drawing with a tolerance threshold, and transmit the deviation data to the S4 fillet welding compensation module and the S7 acceptance model in real time. When the limit is exceeded, trigger an alarm and lock the subsequent S3 excavation process;

[0007] S3. According to the reference dip angle determined in step S1, which is compensated by the depth gradient and corrected by the geological conditions, calculate the single-layer excavation depth according to the proportional relationship of its sine value. When the exposed surface film covering monitoring system detects abnormal seepage or stress mutation, automatically block the hydraulic excavator; at the same time, according to the S1 reference dip angle parameter and the S5 real-time axial force monitoring data, dynamically adjust the duration of the inclined strut installation window period through a time-varying algorithm, and reduce the window period according to the exponential law as the excavation depth increases and ensure the minimum safety duration;

[0008] S4. Build a dynamic adjustment model and perform staged torque control: Based on the S2 positioning deviation data stream (lateral deviation Δx, longitudinal deviation Δy) and the S3 structural strain rate ε, establish a dynamic calculation model for the fillet welding compensation amount:

[0009]

[0010] Where: is the lateral and longitudinal characteristic lengths of the foundation pit, is the reference strain rate (set to 0.5 microstrain / second), is the positioning deviation weight coefficient (dynamic range 0.5 - 1.5), is the strain rate weight coefficient (dynamic range 0.8 - 1.2); The model fits the parameters in real time through the recursive least squares method and outputs the fillet welding compensation amount Q (unit: mm); Perform staged torque control: Initial tightening stage: Apply torque ; Secondary pre-tightening stage: Adjust the torque according to the compensation amount Q

[0011]

[0012] Where is the allowable maximum compensation amount (set to 10mm);

[0013] Final tightening stage: Apply torque and detect the residual stress distribution through ultrasonic testing. When the difference between any two points in the detected residual stress distribution exceeds 12%, then reverse correct according to and the update formula is:

[0014]

[0015] Where, denotes the old value of the weight coefficient, denotes the new value of the weight coefficient;

[0016] S5. Receive the designed value of the preloading axial force in S1 to construct a stress monitoring network, and collect the axial force data of the inclined struts through the wireless sensing unit in a grid pattern. When the real-time axial force deviates from the designed value by ±15%, trigger the compensation mechanism, and establish a non-linear mapping relationship for the compensation amount based on the grouting pressure gradient in S6; when the support system is demolished, the stress monitoring unit can be detachably reused through the protective sleeve, and the reuse status data is transmitted back to the acceptance and evaluation system in S7 in real time;

[0017] S6. The initial grouting pressure establishes a linear relationship based on the depth parameter in S1. When receiving the signal that the thermal distribution map of the foundation displacement in S5 exceeds the limit, start the graded pressurized grouting mode, and the pressure gradient increases by 0.2 MPa / level. The upper pressure limit establishes a dynamic interlocking mechanism with the displacement redundancy threshold of the acceptance model in S7;

[0018] S7. Integrate the positioning topology data in S2 and the axial force cloud map in S5 to construct a three-dimensional acceptance model, perform spatial registration on the positioning topology data in S2 and the axial force cloud map in S5, and automatically identify the non-compliant areas by comparing with the design standards; for the non-compliant areas, preferentially use the correction strategy of the reference inclination angle in S1 to supplement the inclined supports, and the secondary option triggers the slurry filling and strengthening mechanism in S6; iterate and optimize the initial parameter group in S1 through the machine learning algorithm to form a closed-loop control system with parameter self-adaptation.

[0019] Preferably, the specific steps of S1 are as follows:

[0020] S1-1. Calculation of the logarithmic relationship of the foundation pit depth: Take the natural logarithm value of the foundation pit depth as the calculation base. When the depth reaches the reference threshold of 5 meters, the preloading axial force value is compensated according to the gradient of increasing by 15% for each increase of 1 unit in the natural logarithm, and the maximum compensation amount does not exceed 200% of the designed value, and the output parameter is used as the preloading axial force design reference for the S5 step;

[0021] S1-2. Geological compensation mechanism: When the soil layer shear wave velocity values of three consecutive detection points are all lower than 80% of the critical threshold, trigger the reference inclination angle compensation mechanism, the compensation amplitude is 5 degrees and the cumulative number of times does not exceed two, and the compensation result is synchronously transmitted to the inclination angle control module in the S3 step in real time.

[0022] Preferably, the specific steps of S2 are as follows:

[0023] S2-1. Three-dimensional grid construction: Take the center of the foundation pit bottom surface as the coordinate origin, and distribute the laser positioning points along the reference inclination angle direction according to the sine curve distribution density. The distance between adjacent points is inversely proportional to the square root of the foundation pit depth. When the depth increases by 5 meters, the distance is reduced by 20%, and the generated data is used as the reference input for the fillet weld compensation in the S4 step;

[0024] S2-2. Dynamic tolerance adjustment: When the foundation pit depth exceeds 15 meters, the lateral deviation threshold is dynamically adjusted at a ratio of 0.3 mm reduction per meter of depth, and the longitudinal deviation threshold remains 120% of the initial value. Overlimit data directly triggers the acceptance model alarm mechanism in step S7.

[0025] Preferably, the specific steps of S3 are as follows:

[0026] S3-1. Window period calculation: Establish an exponential decay relationship between the excavation depth and the installation window period. The initial 4-hour window period is shortened to 60% of the original duration when the depth reaches 8 meters. The decay coefficient takes the natural logarithm value of the depth value, and the output parameter controls the axial force acquisition frequency in step S5.

[0027] S3-2. Safety duration guarantee: By superimposing the minimum response time of the hydraulic system of 0.8 hours and the structural strain buffer time of 0.4 hours, the lower limit value of the window period is determined to be 1.2 hours and cannot be breached. The limit value data is transmitted back to the positioning verification system in step S2 in real time.

[0028] Preferably, the specific steps of S4 are as follows:

[0029] S4-1. Multi-stage torque control: Initial tightening stage: Apply 50% of the design torque ( ), maintain stress relaxation for 10 minutes. Secondary pre-tightening stage: Based on the weld bead compensation amount Q output by the dynamic adjustment model, according to the formula:

[0030]

[0031] Adjust the torque, where Q is calculated in real time by the S4 main step model; if the strain rate ε exceeds the reference value , then an additional strain compensation term is superimposed, and the torque upper limit is 150% of the design value.

[0032] Final tightening stage: Apply 100% of the design torque ( );

[0033] S4-2. Residual stress verification: After final tightening, use ultrasonic testing to detect the residual stress distribution, and require that the difference between any two points ≤ 12%;

[0034] When overlimit, call the S5 axial force monitoring unit for cross-verification and calculate the model error:

[0035]

[0036] According to the formula

[0037]

[0038] Reverse-correct the weight coefficient , the updated parameters are written into the dynamic adjustment model;

[0039] The verification results are synchronized to the S7 acceptance model for subsequent parameter optimization of the construction section.

[0040] Preferably, the S5 specifically includes the following steps:

[0041] S5-1. Compensation trigger: When the real-time axial force value deviates from the design value by up to ±15% deviation, activate the compensation mechanism linked to the S6 step. The compensation amount is calculated according to the square root ratio of the grouting pressure gradient, and the trigger threshold is dynamically adjusted according to the S1 pre-loading axial force reference value;

[0042] S5-2. Unit reuse: When the support is removed, perform double-index verification on the monitoring unit, requiring the calibration error to be less than 0.8% and the protective structure to be undamaged. The reused status data is encrypted and transmitted to the S7 acceptance system and fed back to the positioning accuracy optimization algorithm in the S2 step.

[0043] Preferably, the S6 specifically includes the following steps:

[0044] S6-1. Pressure grading control: When the foundation displacement reaches the yellow warning area of the thermal distribution map, start the 0.2MPa foundation grouting. After entering the red warning area, increase by 0.2MPa for each level. The pressure upper limit value is 125% of the S7 displacement redundancy threshold, and the warning grading standard is inherited from the S2 positioning deviation historical data;

[0045] S6-2. Pressure interlock: When the grouting pressure gradient is increased to the third level, automatically call the S5 axial force data to establish a pressure-axial force feedback loop. The pressure increase is adjusted to 80% of the previous level value, and the feedback loop parameters are synchronized to the S3 excavation control time sequence table.

[0046] Preferably, the S7 specifically includes the following steps:

[0047] S7-1. Three-dimensional model construction and deviation evaluation: Based on the coordinate data (accuracy ±0.3mm) of the S2 laser positioning grid and the S5 axial force monitoring data (sampling frequency ≥1Hz), use the following method to construct a three-dimensional acceptance model:

[0048] S7-1-1. Mesh divide the foundation pit support structure through the Delaunay triangulation algorithm, and the mesh density is dynamically encrypted according to

[0049]

[0050] ( , is the depth) as the depth increases;

[0051] S7-1-2. Use the Kriging interpolation method to generate a continuous axial force contour map, and the calculation formula is:

[0052]

[0053] Among them, is the weight coefficient for semi-variogram calculation, is the drift term in the depth direction;

[0054] represents the predicted axial force value at the coordinate ; represents the lateral coordinate of the foundation pit; represents the longitudinal coordinate of the foundation pit; z represents the depth of the foundation pit in the vertical direction represents the th measured axial force value of the monitoring point, which is obtained through grid acquisition by the wireless sensing unit in step S5;

[0055] S7-1-3. Establish a deviation evaluation matrix:

[0056]

[0057] When , it is determined as a non-compliant area;

[0058] Among them: represents the lateral positioning deviation of the foundation pit support structure, that is, the difference between the actual position and the design coordinate in the lateral direction; represents the longitudinal positioning deviation; represents the lateral deviation threshold; represents the longitudinal deviation threshold; represents the measured axial force value; represents the designed axial force value;

[0059] S7-2. Reinforcement decision driven by curvature analysis, perform cubic spline curvature analysis on the non-compliant area:

[0060] S7-2-1. Fit the axial force distribution curve and calculate the curvature:

[0061]

[0062] Among them, represents the curvature of the axial force distribution curve; : the first derivative of the axial force distribution function ; represents the second derivative of the axial force distribution function ;

[0063] S7-2-2. When , give priority to triggering the S1 reference inclination correction

[0064]

[0065] Among them, represents the corrected reference inclination angle; represents the reference inclination angle before correction; : Sign function, which determines the inclination adjustment direction according to the sign of the difference between the measured axial force and the designed axial force: If , , the inclination angle increases by 5°; if , , the inclination angle decreases by 5°.

[0066] S7-2-3. When is satisfied, trigger the secondary grouting of S6, and the grouting pressure is dynamically adjusted according to

[0067]

[0068] Among them, represents the grouting pressure;

[0069] for dynamic adjustment;

[0070] S7-3. Parameter self-adaptive optimization and verification:

[0071] S7-3-1. Use the exponential moving average algorithm (EMA) to update the initial parameters of S1, and the formula is:

[0072]

[0073] Among them, is the updated initial reference inclination angle, is the initial reference inclination angle before update, is the reference inclination angle actually adopted in the current construction section, is the attenuation factor, is the weight of the current data, and n represents the nth construction;

[0074] S7-3-2. The updated parameters are simulated and verified through the S2 positioning system to ensure that the three-dimensional laser positioning deviation ≤ 0.5 mm / m (lateral), ≤ 1.0 mm / m (longitudinal). After the verification is passed, it is synchronized to the construction control module;

[0075] S7-3-3. Use the support vector regression machine (SVR) to train the historical data, optimize the weight of the deviation evaluation matrix, with the positioning deviation accounting for 60% and the axial force deviation accounting for 40%, to form a parameter optimization closed loop.

[0076] Compared with the prior art, the advantages of the present invention are:

[0077] (1) Dynamic dip angle compensation mechanism: By integrating geological parameters and engineering depth characteristics, a gradient adaptive adjustment model is constructed, which can dynamically optimize the support dip angle according to the formation mechanical properties and excavation depth, effectively balance the stress distribution under different working conditions, significantly improve the adaptability of the support structure to complex strata, and solve the local stress concentration problem caused by the traditional fixed dip angle design.

[0078] (2) Closed-loop control system with multi-source data interlock: Integrate multi-dimensional data streams such as high-precision positioning, real-time stress monitoring, and grouting pressure feedback, establish a dynamic joint adjustment mechanism for construction parameters, realize the full-process collaborative control from excavation to support, break through the technical limitations of lagging parameter adjustment and data islanding in traditional methods, and ensure the real-time matching of construction response and geological changes.

[0079] (3) Intensive design of reusable monitoring units and intelligent optimized construction time sequence control: Adopt modular sensor structure and protective sleeve integration technology to realize the rapid disassembly, installation and reuse of monitoring units, greatly reduce the equipment loss cost. At the same time, through encrypted data transmission and long-term performance tracking, provide continuous data support for the optimization of construction parameters; Based on the dynamic relationship model between excavation depth and structural safety threshold, automatically adjust the support installation window period, combined with the double guarantee mechanism of hydraulic system response and structural buffer time, effectively avoid the risk of lagging support, and ensure the precise synchronization of the support system and the excavation progress. Specific implementation mode

[0080] Embodiment, a construction method for inclined support of foundation pit, comprising the following steps:

[0081] S1. Establish a dynamic adjustment mechanism for the reference dip angle based on the designed depth and geological conditions of the foundation pit: The reference dip angle is the angle between the inclined support axis and the vertical direction of the foundation pit. The initial reference dip angle is set at 35 degrees, and a gradient compensation of 0.2 degrees is carried out for every 1-meter increase in depth. When the detected value of the soil layer shear wave velocity is lower than the critical threshold, trigger the geological compensation mechanism to supplement and correct the reference dip angle; Synchronously execute: Calculate the theoretical reference value of the pre-loading axial force according to the logarithmic relationship of the foundation pit depth, and then carry out mechanical adaptation calculation and correction on this theoretical reference value according to the compressive bearing capacity corresponding to the thickness of the embedded steel plate and the design value of the shear bearing capacity of high-strength bolts to generate the final reference value; Form a dual reference system including geometric parameters and mechanical parameters;

[0082] S2. Generate a three-dimensional laser positioning grid based on the geometric reference parameters output by S1. After the three-dimensional laser positioning grid is verified with the manual ink line reference line, output a digital construction drawing with a tolerance threshold, and transmit the deviation data to the S4 fillet weld compensation module and the S7 acceptance model in real time. When it exceeds the limit, trigger an alarm and lock the subsequent S3 excavation process;

[0083] S3. Calculate the single-layer excavation depth according to the proportional relationship of the sine value of the reference dip angle determined in step S1, which has been compensated by the depth gradient and corrected by the geological conditions. When the abnormal seepage or stress mutation is detected by the film covering monitoring system on the exposed surface, the hydraulic excavating device is automatically blocked. At the same time, according to the S1 reference dip angle parameter and the S5 real-time axial force monitoring data, the time-varying algorithm is used to dynamically adjust the duration of the inclined strut installation window period, and the window period is reduced according to the exponential law as the excavation depth increases, and the minimum safety duration is ensured.

[0084] S4. Build a dynamic adjustment model and perform phased torque control: Based on the S2 positioning deviation data stream (lateral deviation Δx, longitudinal deviation Δy) and the S3 structural strain rate ε, establish a dynamic calculation model for the fillet weld compensation amount:

[0085]

[0086] Where: is the lateral and longitudinal characteristic lengths of the foundation pit, is the reference strain rate (set to 0.5 microstrain / second), is the positioning deviation weight coefficient (dynamic range 0.5~1.5), is the strain rate weight coefficient (dynamic range 0.8~1.2); the model fits the parameters in real time through the recursive least squares method and outputs the fillet weld compensation amount Q (unit: millimeter); perform phased torque control: Initial tightening stage: Apply torque , Secondary pre-tightening stage: Adjust the torque according to the compensation amount Q

[0087]

[0088] Where is the allowable maximum compensation amount (set to 10mm);

[0089] Final tightening stage: Apply torque , Detect the residual stress distribution by ultrasonic wave. When the difference between any two points in the detected residual stress distribution exceeds 12%, then reverse correct according to and the update formula is:

[0090]

[0091] Where, represents the old value of the weight coefficient, represents the new value of the weight coefficient;

[0092] S5. Receive the designed value of the pre-loading axial force in S1 to construct a stress monitoring network. Grid-collect the axial force data of the inclined struts through wireless sensing units. When the real-time axial force deviates from the designed value by ±15%, trigger the compensation mechanism, and the compensation amount establishes a non-linear mapping relationship based on the grouting pressure gradient in S6; when the support system is demolished, the stress monitoring unit can be detachably reused through a protective sleeve, and the reuse status data is transmitted back to the acceptance and evaluation system in S7 in real time;

[0093] S6. The initial grouting pressure establishes a linear relationship based on the depth parameter in S1. When receiving the signal that the thermal distribution map of the foundation displacement in S5 exceeds the limit, start the graded pressure-increasing grouting mode, and the pressure gradient increases by 0.2 MPa / level. The upper pressure limit establishes a dynamic interlock mechanism with the displacement redundancy threshold of the acceptance model in S7;

[0094] S7. Integrate the positioning topology data in S2 and the axial force cloud map in S5 to construct a three-dimensional acceptance model. Perform spatial registration on the positioning topology data in S2 and the axial force cloud map in S5, and automatically identify the non-compliant areas by comparing with the design standards; for the non-compliant areas, preferentially adopt the inclination correction strategy of the reference inclination in S1 to supplement the inclined supports, and the secondary option triggers the grout supplement and strengthening mechanism in S6; iterate and optimize the initial parameter set in S1 through machine learning algorithms to form a closed-loop control system with self-adaptive parameters.

[0095] The specific S1 includes the following steps:

[0096] S1-1. Calculation of the logarithmic relationship of the foundation pit depth: The core is to establish a non-linear compensation relationship between the foundation pit depth and the pre-loading axial force. Take the natural logarithm value of the foundation pit depth as the calculation base number. When the foundation pit depth reaches the benchmark threshold of 5 meters, the system starts the logarithmic compensation mechanism. For example, when the foundation pit depth increases from 5 meters to 6 meters (the natural logarithm increment is about 0.182), the pre-loading axial force value needs to be increased at a gradient of 15% corresponding to each unit logarithmic increment. In specific implementation, if the designed pre-loading axial force benchmark is 1000 kN, when the depth increases by 1 natural logarithm unit (such as from 5 meters to about 8.2 meters), the axial force is increased to 1150 kN, but the total compensation does not exceed 200% of the designed value (i.e., 2000 kN). This mechanism effectively deals with the non-linear increase of the lateral pressure of deep soil masses and avoids resource waste caused by excessive compensation;

[0097] S1-2. Geological compensation mechanism: The shear wave velocity of the soil layer is a key index reflecting the geological conditions. When the wave velocity values of three consecutive detection points are all lower than 80% of the critical threshold, it indicates that there are significant soft or loose areas in the soil layer. At this time, the system automatically triggers the inclination compensation mechanism and increases the benchmark inclination by 5 degrees. For example, if the initial inclination is 35 degrees, it is adjusted to 40 degrees after the first compensation, and the upper limit of the cumulative number of times is two, that is, the maximum compensation amplitude is 10 degrees. The corrected inclination parameter is synchronously transmitted to the inclination control module in S3 in real time to ensure that the installation angle of the inclined strut is dynamically adapted to the geological conditions and prevent the failure of the support caused by insufficient soil strength.

[0098] S2 specifically includes the following steps:

[0099] S2-1. Three-dimensional grid construction: For the construction of the three-dimensional laser positioning grid, the center of the foundation pit bottom surface is used as the coordinate origin, and the laser positioning points are distributed along the reference inclination direction according to the sine curve density. The distance between adjacent points is inversely proportional to the square root of the foundation pit depth. For example, when the depth is 10 meters, the distance is set to 1 / √10 (about 31.6%) of the initial value. For every 5-meter increase in depth, the distance is further reduced by 20%. This distribution method can optimize the density of positioning points and ensure the measurement accuracy in the deep area. The generated three-dimensional grid data is used as the benchmark input for S4 fillet weld compensation, providing a spatial reference for subsequent deviation correction;

[0100] S2-2. Dynamic tolerance adjustment: When the foundation pit depth exceeds 15 meters, the lateral deviation threshold is dynamically adjusted by reducing 0.3 mm per meter of depth. For example, when the depth is 16 meters, the lateral tolerance is reduced by 0.3 mm, while the longitudinal tolerance remains 120% of the initial value. If a deviation exceeding the limit is detected (such as the lateral deviation exceeding the adjusted threshold), the system directly triggers the alarm mechanism of the S7 acceptance model and pauses the S3 excavation process until the manual review is completed. This mechanism balances the high requirement for lateral stability and the controllability of longitudinal deformation in deep foundation pit construction.

[0101] S3 specifically includes the following steps:

[0102] S3-1. Window period calculation: The installation window period has an exponential decay relationship with the excavation depth, and the initial window period is 4 hours. When the depth reaches 8 meters, the window period is shortened to 60% of the original duration (i.e., 2.4 hours), and the decay coefficient takes the natural logarithm value of the depth. For example, when the depth is 12 meters, the decay coefficient is the natural logarithm of 12 ≈ 2.485, and the window period is further reduced to 1.2 hours. This algorithm ensures the construction efficiency in the deep area and, at the same time, guarantees the data timeliness by dynamically adjusting the S5 axial force acquisition frequency (such as increasing from once per hour to once every 30 minutes);

[0103] S3-2. Safety duration guarantee: The lower limit value of the window period is determined by the superposition of the minimum response time of the hydraulic system (0.8 hours) and the structural strain buffer time (0.4 hours), that is, 1.2 hours. For example, when the depth causes the calculated value of the window period to be less than 1.2 hours, the system is forced to lock at 1.2 hours and feedbacks the limit value data to the S2 positioning verification system to prevent equipment response lag or structural instability caused by insufficient time.

[0104] S4 specifically includes the following steps:

[0105] S4-1. Multi-stage torque control: Initial tightening stage: Apply 50% of the design torque ( ), maintain stress relaxation for 10 minutes. Secondary pre-tightening stage: Based on the fillet weld compensation amount Q output by the dynamic adjustment model, according to the formula:

[0106]

[0107] Adjust the torque, where Q is calculated in real time by the S4 main step model; if the strain rate ε exceeds the reference value , then an additional strain compensation term is superimposed, and the torque upper limit is 150% of the design value.

[0108] Final tightening stage: Apply 100% of the design torque ( );

[0109] S4-2. Residual stress verification. After final tightening, use ultrasonic testing to detect the residual stress distribution, and require that the difference between any two points ≤ 12%;

[0110] When it exceeds the limit, call the S5 axial force monitoring unit for cross-verification and calculate the model error:

[0111]

[0112] According to the formula

[0113]

[0114] Reverse-correct the weight coefficient , and write the updated parameters into the dynamic adjustment model;

[0115] Synchronize the verification results to the S7 acceptance model for parameter optimization of subsequent construction sections.

[0116] The specific steps of the above-mentioned S5 are as follows:

[0117] S5-1. Compensation trigger. When the real-time axial force deviates from the design value by ±15% (for example, when the design axial force is 1000 kN and the measured value reaches 1150 kN or 850 kN), the system activates the compensation mechanism linked with S6. The compensation amount is calculated according to the square root ratio of the grouting pressure gradient. For example, if the grouting pressure gradient is 0.2 MPa / level, the compensation amount is a multiple of the square root of the pressure gradient (such as √0.2 ≈ 0.447 times), ensuring the physical relevance between the grouting volume and the axial force deviation;

[0118] S5-2. Unit reuse. When the support is removed, conduct double-index verification on the monitoring unit: the calibration error needs to be less than 0.8%, and the protective structure needs to be undamaged. For example, if the calibration error of a certain unit is 0.5% and the protective sleeve is intact, it is marked as reusable, and its status data is encrypted and transmitted to the S7 acceptance system and fed back to the S2 positioning accuracy optimization algorithm to improve the measurement accuracy of subsequent construction.

[0119] The specific steps of the above-mentioned S6 are as follows:

[0120] S6 - 1. Pressure hierarchical control, the grouting pressure is adjusted hierarchically according to the thermal distribution map of foundation displacement. When the foundation displacement enters the yellow warning area (such as the displacement reaches 20 mm), start the basic grouting at 0.2 MPa; after entering the red warning area (the displacement reaches 30 mm), increase by 0.2 MPa for each level, and the pressure upper limit is 125% of the S7 displacement redundancy threshold (for example, if the threshold is 1.6 MPa, the upper limit is 2.0 MPa). The warning classification standard is inherited from the S2 historical deviation data to ensure that the grouting strategy matches the geological risk level;

[0121] S6 - 2. Pressure interlock, when the grouting pressure is increased to the third level (0.6 MPa), the system calls the S5 axial force data to establish a pressure - axial force feedback loop, and the pressure increase amplitude is adjusted to 80% of the previous level value (for example, if the previous increment is 0.2 MPa, the subsequent increment is adjusted to 0.16 MPa) to avoid soil splitting caused by sudden pressure rise. The feedback loop parameters are synchronized to the S3 excavation control time sequence table to optimize the coordination efficiency of deep excavation and grouting.

[0122] The specific steps of S7 are as follows:

[0123] S7 - 1. Three - dimensional model construction and deviation evaluation: Based on the coordinate data of the S2 laser positioning grid (accuracy ±0.3 mm) and the S5 axial force monitoring data (sampling frequency ≥1 Hz), use the following method to construct a three - dimensional acceptance model:

[0124] S7 - 1 - 1. Mesh the foundation pit support structure through the Delaunay triangulation algorithm, and the mesh density is dynamically encrypted according to

[0125]

[0126] ( , is the depth) as the depth increases;

[0127] S7 - 1 - 2. Use the Kriging interpolation method to generate a continuous axial force contour map, and the calculation formula is:

[0128]

[0129] Among them, is the weight coefficient calculated by the semi - variogram, is the drift term in the depth direction;

[0130] represents the predicted axial force value at the coordinate ; represents the lateral coordinate of the foundation pit; represents the longitudinal coordinate of the foundation pit; z represents the vertical depth of the foundation pit represents the The measured axial force values of each monitoring point are obtained through grid sampling by the wireless sensing unit in step S5;

[0131] S7-1-3. Establish a deviation evaluation matrix:

[0132]

[0133] When it is determined as a non-compliant area;

[0134] Where: represents the lateral positioning deviation of the foundation pit support structure, that is, the difference between the actual position and the design coordinates in the lateral direction; represents the longitudinal positioning deviation; represents the lateral deviation threshold; represents the longitudinal deviation threshold; represents the measured axial force value; represents the designed axial force value;

[0135] S7-2. Reinforcement decision driven by curvature analysis, perform cubic spline curvature analysis on the non-compliant area:

[0136] S7-2-1. Fit the axial force distribution curve and calculate the curvature:

[0137]

[0138] Where, represents the curvature of the axial force distribution curve; : the axial force distribution function the first derivative of; represents the axial force distribution function the second derivative of;

[0139] S7-2-2. When it preferentially triggers the S1 reference inclination correction

[0140]

[0141] Where, represents the corrected reference inclination; represents the reference inclination before correction; : sign function, determines the inclination adjustment direction according to the sign of the difference between the measured axial force and the designed axial force: if , , the inclination increases by 5°; if , , the inclination decreases by 5°.

[0142] S7-2-3. When When it is triggered, the secondary grouting of S6 is carried out, and the grouting pressure is dynamically adjusted according to

[0143]

[0144] ;

[0145] S7-3. Parameter Adaptive Optimization and Verification:

[0146] S7-3-1. The exponential moving average algorithm (EMA) is used to update the initial parameters of S1, and the formula is:

[0147]

[0148] Among them, is the updated initial reference inclination angle, is the initial reference inclination angle before update, is the reference inclination angle actually used in the current construction section, is the attenuation factor, is the weight of the current data, and n represents the nth construction;

[0149] S7-3-2. The updated parameters are simulated and verified through the S2 positioning system to ensure that the three-dimensional laser positioning deviation ≤ 0.5 mm / m (lateral) and ≤ 1.0 mm / m (longitudinal). After the verification is passed, they are synchronized to the construction control module;

[0150] S7-3-3. The support vector regression machine (SVR) is used to train the historical data to optimize the weight of the deviation evaluation matrix. The proportion of the positioning deviation is 60%, and the proportion of the axial force deviation is 40%, forming a parameter optimization closed loop.

[0151] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and the descriptions in the specification are only the preferred examples of the present invention and do not limit the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A construction method for inclined bracing of foundation pit, characterized in that, It includes the following steps: S1. Establish a dynamic adjustment mechanism for the reference inclination angle based on the designed depth of the foundation pit and geological conditions: The reference inclination angle is the angle between the inclined support axis and the vertical direction of the foundation pit. The initial reference inclination angle is set at 35 degrees, with a gradient compensation of 0.2 degrees for every 1-meter increase in depth. When the detected value of the soil layer shear wave velocity is lower than the critical threshold, the geological compensation mechanism is triggered to supplement and correct the reference inclination angle; simultaneously execute: Calculate the theoretical reference value of the prestressed axial force based on the logarithmic relationship of the foundation pit depth, and then perform mechanical adaptation calculation and correction on this theoretical reference value according to the compressive bearing capacity corresponding to the thickness of the embedded steel plate and the design value of the shear bearing capacity of high-strength bolts to generate the final reference value; form a dual reference system including geometric parameters and mechanical parameters; S2. Generate a three-dimensional laser positioning grid based on the geometric reference parameters output by S1. After the three-dimensional laser positioning grid is verified with the artificial ink line reference line, output a digital construction drawing with a tolerance threshold, and transmit the deviation data to the S4 fillet weld compensation module and the S7 acceptance model in real time. When it exceeds the limit, trigger an alarm and lock the subsequent S3 excavation process; S3. Calculate the single-layer excavation depth according to the positive proportional relationship of the sine value of the reference inclination angle determined in step S1, which has been compensated by the depth gradient and corrected according to the geological conditions. When the exposed surface film covering monitoring system detects abnormal seepage or stress mutation, automatically block the hydraulic excavating device; at the same time, according to the S1 reference inclination angle parameter and the S5 real-time axial force monitoring data, dynamically adjust the duration of the inclined support installation window period through a time-varying algorithm, and reduce the window period according to an exponential law as the excavation depth increases and ensure the minimum safety duration; S4. Construct a dynamic adjustment model and execute staged torque control: Based on the S2 positioning deviation data stream and the S3 structural strain rate ε, establish a dynamic calculation model for the fillet weld compensation amount; Wherein: is the lateral and longitudinal characteristic lengths of the foundation pit, is the reference strain rate, is the positioning deviation weight coefficient, is the strain rate weight coefficient; the model fits the parameters in real time through the recursive least squares method and outputs the fillet weld compensation amount Q; perform phased torque control: initial tightening stage: apply torque , secondary pre-tightening stage: adjust the torque according to the compensation amount Q Among them The allowable maximum compensation amount is set to 10 mm; Final tightening stage: Apply torque , detect the residual stress distribution by ultrasonic testing. When the difference between any two points in the detected residual stress distribution exceeds 12%, then Reverse correction , and the update formula is: Among them, represents the old value of the weight coefficient, represents the new value of the weight coefficient; S5. Receive the S1 prestressed axial force design value to construct a stress monitoring network, and collect the inclined support axial force data in a grid pattern through wireless sensing units. When the real-time axial force deviates from the design value by ±15%, trigger the compensation mechanism, and the compensation amount establishes a non-linear mapping relationship based on the S6 grouting pressure gradient; when the support system is demolished, the stress monitoring unit can be detachably reused through a protective sleeve, and the reuse status data is transmitted back to the S7 acceptance evaluation system in real time; S6. The initial grouting pressure establishes a linear relationship according to the S1 depth parameter. When receiving the signal that the S5 foundation displacement thermal distribution map exceeds the limit, start the staged pressure-increasing grouting mode, with the pressure gradient increasing by 0.2 MPa / level, and establish a dynamic interlock mechanism between the pressure upper limit and the displacement redundancy threshold of the S7 acceptance model; S7. Integrate the S2 positioning topology data and the S5 axial force cloud map to construct a three-dimensional acceptance model, perform spatial registration on the S2 positioning topology data and the S5 axial force cloud map, and automatically identify the non-compliant areas by comparing with the design standards; for the non-compliant areas, preferentially use the S1 reference inclination angle correction strategy to supplement the inclined support, and the secondary option triggers the S6 grouting reinforcement mechanism; iterate and optimize the S1 initial parameter set through machine learning algorithms to form a closed-loop control system with parameter self-adaptation.

2. The construction method of an inclined support for a foundation pit according to claim 1, characterized in that, The specific steps of S1 are as follows: S1-1. Calculation of the logarithmic relationship of foundation pit depth: Taking the natural logarithm value of the foundation pit depth as the calculation base, when the depth reaches the reference threshold of 5 meters, the pre-applied axial force value is compensated at a gradient of increasing by 15% for each unit increase in the natural logarithm, and the maximum compensation amount does not exceed 200% of the design value. The output parameter is used as the pre-applied axial force design reference for step S5. S1-2. Geological compensation mechanism: When the soil layer shear wave velocity values of three consecutive detection points are all lower than 80% of the critical threshold, the reference inclination compensation mechanism is triggered. The compensation amplitude is 5 degrees and the cumulative number of times does not exceed two. The compensation result is synchronously transmitted to the inclination control module of step S3 in real time.

3. A construction method for inclined bracing of foundation pits according to claim 1, characterized in that The specific steps of S2 are as follows: S2-1. Three-dimensional grid construction: Taking the center of the foundation pit bottom surface as the coordinate origin, laser positioning points are arranged along the reference inclination direction according to the density distribution of the sine curve. The distance between adjacent points is inversely proportional to the square root of the foundation pit depth. When the depth increases by 5 meters, the distance is reduced by 20%. The generated data is used as the reference input for the fillet weld compensation in step S4. S2-2. Dynamic tolerance adjustment: When the foundation pit depth exceeds 15 meters, the lateral deviation threshold is dynamically adjusted at a ratio of reducing 0.3 mm per meter of depth, and the longitudinal deviation threshold remains 120% of the initial value. The over-limit data directly triggers the acceptance model alarm mechanism in step S7.

4. A construction method for inclined bracing of foundation pits according to claim 1, characterized in that, The specific steps of S3 are as follows: S3-1. Window period calculation: Establish an exponential decay relationship between the excavation depth and the installation window period. The initial 4-hour window period is shortened to 60% of the original duration when the depth reaches 8 meters. The decay coefficient takes the natural logarithm value of the depth value. The output parameter controls the axial force acquisition frequency in step S5. S3-2. Safety duration guarantee: By superimposing the minimum response time of 0.8 hours of the hydraulic system and the structural strain buffer time of 0.4 hours, the lower limit value of the window period is determined to be 1.2 hours and cannot be exceeded. The limit value data is transmitted back to the positioning verification system in step S2 in real time.

5. A construction method for inclined bracing of foundation pits according to claim 1, characterized in that, The specific steps of S4 are as follows: S4-1. Multi-stage torque control: Initial tightening stage: Apply 50% of the design torque , maintain stress relaxation for 10 minutes; Secondary pre-tightening stage: Based on the fillet weld compensation amount Q output by the dynamic adjustment model, according to the formula Adjust the torque, where Q is calculated in real time by the S4 main step model; if the strain rate ε exceeds the reference value , then an additional strain compensation term is superimposed, and the torque upper limit is 150% of the design value Final tightening stage: Apply 100% of the design torque. S4-2. Residual stress verification: After final tightening, ultrasonic detection is used to detect the residual stress distribution, and it is required that the difference between any two points ≤ 12%. When over-limit, call the S5 axial force monitoring unit for cross-verification and calculate the model error: According to the formula Reverse correction weight coefficient , and the updated parameters are written into the dynamic adjustment model; The verification result is synchronized to the S7 acceptance model for parameter optimization in the subsequent construction section.

6. A construction method for inclined bracing of foundation pits according to claim 1, characterized in that The specific steps of S5 are as follows: S5-1. Compensation trigger: When the real-time axial force value deviates from the design value by up to ±15% deviation, activate the compensation mechanism linked to step S6. The compensation amount is calculated according to the square root ratio of the grouting pressure gradient. The trigger threshold is dynamically adjusted according to the S1 pre-applied axial force reference value. S5-2. Unit reuse: When the support is removed, double-index verification is carried out on the monitoring unit, and it is required that the calibration error is less than 0.8% and the protective structure is not damaged. The reuse status data is encrypted and transmitted to the S7 acceptance system and feedback to the positioning accuracy optimization algorithm in step S2.

7. A construction method for inclined bracing of foundation pits according to claim 1, characterized in that The specific steps of S6 are as follows: S6-1. Pressure hierarchical control: When the foundation displacement reaches the yellow warning area of the thermal distribution map, initiate 0.2 MPa foundation grouting. After entering the red warning area, increase it by 0.2 MPa for each level. The upper limit of the pressure is 125% of the S7 displacement redundancy threshold. The warning classification standard is inherited from the S2 positioning deviation historical data; S6-2. Pressure interlock: When the grouting pressure gradient is increased to the third level, automatically call the S5 axial force data to establish a pressure-axial force feedback loop. Adjust the pressure increase amplitude to 80% of the previous level value, and synchronize the feedback loop parameters to the S3 excavation control time sequence table.

8. A construction method for inclined bracing of foundation pit according to claim 1, characterized in that, The specific steps of S7 are as follows: S7-1. Three-dimensional model construction and deviation evaluation: Based on the coordinate data of the S2 laser positioning grid and the S5 axial force monitoring data, use the following method to construct a three-dimensional acceptance model: S7-1-1. Use the Delaunay triangulation algorithm to divide the grid of the foundation pit support structure. The grid density changes with depth according to Dynamic encryption, wherein meter, is the depth; S7-1-2. Use the Kriging interpolation method to generate a continuous axial force nephogram. The calculation formula is: Among them, is the weight coefficient for semi-variogram calculation, is the drift term in the depth direction; Indicates the predicted axial force value at the coordinate; Indicates the lateral coordinate of the foundation pit; Indicates the longitudinal coordinate of the foundation pit; z represents the depth of the foundation pit in the vertical direction; Indicates the measured axial force value of the th monitoring point, obtained through the grid collection of the wireless sensing unit in step S5; S7-1-3. Establish a deviation evaluation matrix: When it is determined as a non-compliant area; Wherein: represents the lateral positioning deviation of the foundation pit support structure, that is, the difference in the lateral direction between the actual position and the design coordinates; represents the longitudinal positioning deviation; represents the lateral deviation threshold; represents the longitudinal deviation threshold; represents the measured axial force value; represents the designed axial force value; S7-2. Reinforcement decision-making driven by curvature analysis: Conduct cubic spline curvature analysis on the unqualified area: S7-2-1. Fitting the axial force distribution curve And calculate the curvature: Among them, represents the curvature of the axial force distribution curve; : the first derivative of the axial force distribution function ; represents the second derivative of the axial force distribution function ; S7-2-2. When it is the case, preferentially trigger the S1 reference inclination correction Among them, represents the corrected reference inclination angle; represents the reference inclination angle before correction; represents the sign function, which determines the inclination adjustment direction according to the sign of the difference between the measured axial force and the designed axial force: if , , the inclination angle increases by 5°; if , , the inclination angle decreases by 5° S7-2-3. When occurs, trigger the secondary grouting of S6, and the grouting pressure is as follows: Among them, represents the grouting pressure; Perform dynamic adjustment; S7-3. Parameter adaptive optimization and verification: S7-3-1. Use the exponential moving average algorithm to update the S1 initial parameters. The formula is: Among them, is the updated initial reference inclination angle, is the initial reference inclination angle before update, is the reference inclination angle actually adopted in the current construction section, is the attenuation factor, is the weight of the current data, and n represents the nth construction; S7-3-2. Verify the updated parameters through the S2 positioning system to ensure that the three-dimensional laser positioning deviation is ≤0.5 mm / m horizontally and ≤1.0 mm / m vertically. After passing the verification, synchronize them to the construction control module; S7-3-3. Train the historical data using the support vector regression machine to optimize the weight of the deviation evaluation matrix. The proportion of the positioning deviation is 60%, and the proportion of the axial force deviation is 40%, forming a parameter optimization closed loop.

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