Scene analysis method for interaction of pile and karst cave in construction process

Abstract

The invention belongs to the technical field of pile foundation construction, and particularly relates to a scene sound analysis method for interaction of a pile and a karst cave in a construction process, which comprises the following steps of: step 1, high-precision karst cave form detection: arranging crossed measuring lines with the pile foundation as a center, the length of the measuring lines being more than or equal to 20m and the spacing being less than or equal to 1m, synchronously adopting a high-energy acceleration tamper and the impact energy being more than or equal to 50kJ, active source surface waves are excited, the impact frequency ranges from 2 Hz to 5 Hz, environment noise is collected to serve as passive source surface waves, a three-component detector array is used for receiving, and the sampling rate is larger than or equal to 500 Hz. According to the method for analyzing the interaction scene sound of the pile and the karst cave in the construction process, by setting the method for analyzing the interaction scene sound of the pile and the karst cave in the construction process, wave velocity changes in the vertical direction and the horizontal direction and anomalies in high-speed and low-speed areas are analyzed, and the thickness of a covering layer and the burying depth of bed rock are deduced; the development depth, the scale and the space distribution condition of the monolith and the karst caves are determined.

Description

Technical Field

[0001] This invention relates to the field of pile foundation construction technology, and in particular to a method for analyzing the impact of the interaction between piles and karst caves during construction. Background Technology

[0002] Foundation construction refers to the process of driving or drilling piles (usually column-shaped structures made of steel, concrete, wood, etc.) into the ground to support the weight of buildings or other structures and transfer the load to deeper soil or rock layers. Pile foundations are commonly used for soft soil foundations or buildings with heavy loads to reinforce the foundation.

[0003] Without a clear understanding of the development of karst caves at the pile locations before pile foundation construction, karst cave leakage and grouting are likely to occur, which can easily lead to serious accidents such as borehole collapse, drilling rig overturning, drill bit burial, suspended pile cap, overall pile foundation subsidence, and cracking of surrounding buildings. This greatly increases the difficulty of pile foundation construction, affects the quality of pile foundation construction, and makes it impossible to accurately monitor the state of the sleeve driven into the ground. As a result, it is impossible to take advantage of the large number of actual pile foundations on site and collect rich data resources, and combine them with advanced detection data. Summary of the Invention

[0004] To address the technical challenges of existing pile and karst cave monitoring methods during construction, which cannot be combined with advanced detection technology to achieve segmented construction schemes for pile foundations with different underlying karst cave types, and which cannot utilize abundant actual monitoring data during construction to iteratively optimize the advanced detection technology, this invention proposes a method for analyzing the impact of pile and karst cave interaction during construction.

[0005] The present invention proposes a method for analyzing the impact of the interaction between piles and karst caves during construction, comprising the following steps: Step 1, high-precision karst cave morphology detection: a cross-shaped survey line is laid out with the pile foundation as the center, the survey line length is ≥20m and the spacing is ≤1m, and a high-energy accelerometer is used simultaneously to excite active source surface waves with an impact energy ≥50kJ and an impact frequency of 2-5Hz, and environmental noise is collected as a passive source surface wave and received using a three-component geophone array with a sampling rate ≥500Hz;

[0006] Step 2: After bandpass filtering the signal, apply linear Ladon transform to extract dispersion energy and generate the fundamental-order surface wave dispersion curve;

[0007] Step 3: Using a generalized pattern recognition algorithm based on global optimization, the surface wave dispersion curve is inverted. The objective function of the inversion is to minimize the L2 norm of the dispersion curve residual, so as to obtain two-dimensional shear wave velocity profiles below the four survey lines. The four profile data are then fused by Kriging space interpolation to construct a three-dimensional shear wave velocity model with the pile foundation as the core.

[0008] Step 4: By analyzing the changes in wave velocity in the vertical and horizontal directions, and the anomalies in high-speed and low-speed areas, we can infer the thickness of the overburden, the burial depth of the bedrock, and the development depth, scale, and spatial distribution of monoliths and caves.

[0009] Step 5: Block-based design of pile foundation: Based on the 3D Vs model, construction schemes are classified according to the scale of the karst cave, the degree of interaction, and the interface inclination angle;

[0010] Step 6, Intelligent monitoring of construction parameters: After the detection device is installed on the sleeve to be installed, the hydraulic clamp presses the sleeve down. The IMU module, ultrasonic probe and strain gauge on the detection device monitor the attitude of the sleeve and the initial verticality and the risk of hole collapse.

[0011] Step 7: Combining the karst cave morphology and actual geological data collected during construction, further optimize the model inversion algorithm of advanced detection technology and active and passive source surface wave detection technology through back-analysis; and gradually correct the differences.

[0012] Preferably, the formula for extracting dispersion energy using the linear Ladon transform in step two is: Where R(p,w) is the result of the Ladon transform (energy distribution function in the slowness-frequency domain), representing the energy at slowness p and angular frequency w, u(x,w) represents the frequency domain seismic signal at position x and angular frequency w, where x is the spatial coordinate (the position of the geophone along the survey line), and e iwpx Let dx be a plane wave, dx be the spatial calculus, the integral variable along the survey line, and i be the imaginary unit.

[0013] Preferably, the objective function for wave velocity profile inversion in step three is... d obs To observe the dispersion curve, the m-model parameters are... V s The shear wave velocity distribution is given by h, formation thickness, ρ, and δ. cave Cave morphology parameters (elliptical eccentricity), λΓ is the regularization term (suppressing multiple solutions), λ is the regularization coefficient, d obs For the observed data vector, d calc (m) is the forward simulation data vector (the theoretical response calculated based on model m);

[0014] A generalized pattern recognition algorithm is adopted: an initial model population is generated (Monte Carlo random sampling), and iterative updates are performed: the model is optimized through crossover and mutation using a genetic algorithm to minimize the residual L2 norm;

[0015] Kriging interpolation was used on the two-dimensional Vs profile obtained by inversion from the four survey lines: Among them, w iw is the weighting coefficient. i Determined by the variogram γ(h): V represents the wave velocity value to be estimated (the predicted wave velocity value at spatial location x0). s(xi) Let be the known wave velocity value (the measured wave velocity at the i-th measuring point), n be the number of known points participating in the interpolation (taking 4-16 neighboring points), and γ(h) be the variogram (a function describing the spatial correlation of wave velocity). i0 This is the distance vector (the Euclidean distance between the known point and the predicted point);

[0016] Output: High-resolution 3D Vs model of the central area of ​​the pile foundation (mesh accuracy ≤ 0.5m).

[0017] Preferably, in step four, the identification of overburden thickness and bedrock burial depth includes: vertical wave velocity gradient analysis: calculating the wave velocity gradient in the depth z direction. Where z is the depth coordinate. Wave velocity-depth change rate (the change in wave velocity per meter of depth), engineering criterion: gradient abrupt change point. Indicator bedrock interface, gradient abrupt change point Indicator of the abrupt change in gradient at the top of the cave. Indicates a homogeneous soil layer, with the overburden thickness H = depth of the abrupt change point;

[0018] Cave and Monolith Identification: Anomaly Identification Criteria: V S At speeds <150 m / s, the morphological characteristics are isolated, low-velocity closed regions, and the criterion formula is V. S ≤μ-2σ,V S At speeds >800 m / s, the morphological characteristic is a localized high-speed bulge, and the criterion formula is V. S ≥μ+2σ, 150 <V S At speeds <300 m / s, the morphological characteristics are strip-shaped low-speed regions, and the criterion formula is as follows: μ is the average shear wave velocity within the study area. σ represents the standard deviation of the shear wave velocity within the study area. Where N is the number of wave velocity measurement points within the selected background area, and V s,i The measured wave velocity at position i;

[0019] Spatial distribution calculation: Cave size: Calculate the volume of the low-velocity region V=∫∫∫ Ω dV(Ω:V s <150m / s), where Ω is the definition of the cave region, dV is the volume element, and V<1m 3 It is a small karst cave, 5m 3 ≤V<5m 3 It is a medium-sized karst cave with a depth of V ≥ 5m. 3 It is a large karst cave;

[0020] Burial depth: Centroid depth of the anomaly zone:

[0021] Inclination angle: Calculated by slicing the interface normal vectors.

[0022] Preferably, the pile foundation block classification construction strategy in step five is as follows: small isolated karst caves with a diameter of less than 1m are filled by grouting and conventional drilling.

[0023] For medium-sized karst cave groups with diameters between 1 and 3 meters, casing installation and high-pressure grouting are carried out.

[0024] For large karst caves / fracture zones with diameters greater than 3m, cast-in-place concrete columns and pile foundations are relocated.

[0025] Preferably, in step six, the intelligent monitoring of construction parameters includes: sleeve monitoring: IMU module: real-time measurement of the casing inclination angle θ (accuracy ±0.1°), calculated using the following formula: (a y a z (Y / Z axis acceleration);

[0026] Ultrasonic probe: ranging Among them, υ s Let Δt be the speed of sound and Δt be the echo time difference.

[0027] Strain gauge: Sleeve stress σ=E·ε, where E is the elastic modulus and ε is the strain;

[0028] Control logic: If θ>5° or d<0.5m, trigger the hydraulic system to correct the deviation.

[0029] Preferably, the specific optimization method in step seven is as follows: Active source frequency adjustment: If shallow caverns are missed, increase the high-frequency component (→10Hz), the formula is as follows. Among them, f new f is the adjusted active source frequency (optimized impact vibration dominant frequency). old The active source frequency currently in use is set to the original tamping frequency (2-5Hz), Δz is the error depth (the difference between the detected depth and the true depth), k is the adjustment coefficient (an empirical parameter that controls the frequency adjustment amplitude), and H is the current effective surface wave detection depth (the maximum exploration depth related to the old frequency).

[0030] Inversion objective function correction: Add interface gradient constraint term: in, The wave velocity gradient revealed during construction;

[0031] Passive source noise utilization optimization: Adjust the weights of the environmental noise dispersion curve based on the actual Vs model. Among them, fc The frequency band sensitive to karst caves (calibrated from construction data), f is the current frequency (effective surface wave frequency band 1-50Hz), f width The bandwidth parameter controls the weighted attenuation rate (related to the size of the karst cave).

[0032] Preferably, the detection device in step six includes a support device, a fixing device, and a monitoring component;

[0033] The support device is located on the outer surface of the sleeve and supports the monitoring component. The support device includes a pin with a rack and pinion. One end of the pin is inserted into the outer surface of the sleeve to fix the monitoring component.

[0034] The fixing device is located on the outer surface of the support device and fixes the two support devices. The fixing device includes a fixing block, which fixes the two support devices.

[0035] The monitoring component is located on the outer surface of the support device, and the IMU module, ultrasonic probe and strain gauge of the monitoring component monitor the attitude of the sleeve.

[0036] Preferably, the support device further includes a support housing, the inner wall of which is slidably inserted into one end of the insertion pin, a drive gear is rotatably connected to the inner wall of the support housing, the drive gear meshes with the rack of the insertion pin, and a half-tooth ring is rotatably connected to the inner wall of the support housing, the half-tooth ring meshes with the drive gear.

[0037] Preferably, the fixing device further includes a fixing housing, which is fixedly installed on the outer surface of the supporting housing. One end of the two fixing housings is slidably inserted into each other. An annular groove is fixedly installed on the inner wall of the fixing housing. The inner wall of the annular groove is slidably inserted into the outer surface of the fixing block. A push handle is fixedly installed on the outer surface of the fixing block. A push hydraulic cylinder is hinged to the inner wall of the fixing housing by a pin. One end of the piston rod of the push hydraulic cylinder is hinged to one end of the push handle by a pin.

[0038] The ultrasonic probe is fixedly installed on the lower surface of the support housing. The strain gauge is fixedly installed on the outer surface of the support housing and contacts the outer surface of the sleeve. A driving hydraulic cylinder is fixedly installed on the outer surface of one of the support housings. One end of the piston rod of the driving hydraulic cylinder is fixedly installed with one end of the insertion pin. A support frame is fixedly installed on the outer surface of the other support housing. A detection hydraulic cylinder is fixedly installed on the outer surface of the support frame. A push plate is fixedly installed on one end of the piston rod of the detection hydraulic cylinder. A push bracket is slidably inserted into the outer surface of the push plate. A return spring is fixedly installed on one end of the limit rod of the push bracket. One end of the return spring is fixedly installed with the outer surface of the push plate. One end of the outer surface of the push plate is fixedly installed with the outer surface of the IMU module through a connecting rod.

[0039] The beneficial effects of this invention are as follows:

[0040] 1. By setting up a detection device, the sleeve can be quickly fixed and disassembled without the need to install strain gauges and IMU modules on each sleeve for monitoring, reducing cost investment. By pushing the hydraulic cylinder, the fixing blocks inside the interlocking fixed shells are deflected and interlock with the annular grooves inside the other fixed shell, thus completing the fixation between the two fixed shells. The opposite support shell is sleeved on the outer surface of the sleeve, which facilitates the insertion of the insertion pin into the insertion hole of the sleeve, thus fixing the support shell on the sleeve. This allows the IMU module, ultrasonic probe, and strain gauge to monitor the attitude of the sleeve and the initial verticality and the risk of orifice collapse.

[0041] 2. By setting up a method for analyzing the interaction between piles and karst caves during construction, two sets of intersecting linear survey lines were deployed. High-energy accelerated impact was used as the seismic source to generate active source surface waves, and environmental noise was collected as a passive source surface wave. High-resolution linear Ladon transform technology was applied to extract the dispersion characteristic energy of the surface waves, and a generalized pattern recognition algorithm based on global optimization was used to invert the surface wave dispersion curve to obtain two-dimensional shear wave velocity profiles below the four survey lines. Subsequently, Kriging space interpolation was used to construct a three-dimensional shear wave velocity model with the pile foundation as the core. By analyzing the wave velocity changes in the vertical and horizontal directions, and the anomalies in the high-speed and low-speed regions, the thickness of the overburden, the burial depth of the bedrock, and the development depth of the monolith and karst cave were inferred. This study investigates the scale and spatial distribution of karst caves, and proposes innovative methods for refined detection deployment and algorithm optimization in karst cave areas by combining active and passive surface wave technologies. By integrating the detection results of advanced detection technology, it enables segmented construction schemes for pile foundations with different underlying karst cave types. Furthermore, based on actual site requirements, real-time monitoring equipment for pile foundation construction process parameters is developed. Utilizing abundant actual monitoring data during construction, the advanced detection technology is repeatedly optimized and iterated. This solves the technical problems of existing methods that cannot combine pile and karst cave monitoring with the detection results of advanced detection technology to achieve segmented construction schemes for pile foundations with different underlying karst cave types, and cannot utilize abundant actual monitoring data during construction for repeated optimization and iteration of the advanced detection technology. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of a method for analyzing the impact of the interaction between piles and karst caves during construction, as proposed in this invention.

[0043] Figure 2 This is a three-dimensional diagram of a semi-toothed ring structure used in the method for analyzing the impact of pile-karst cave interaction during construction proposed in this invention.

[0044] Figure 3 This is a three-dimensional view of the hydraulic cylinder structure used in the analysis of the impact of the interaction between piles and karst caves during construction, as proposed in this invention.

[0045] Figure 4 This is a three-dimensional view of the fixed block structure in the method for analyzing the impact of the interaction between piles and karst caves during construction proposed in this invention.

[0046] Figure 5 This is a three-dimensional view of the hydraulic cylinder structure used in the analysis of the impact of the interaction between piles and karst caves during construction, as proposed in this invention.

[0047] In the diagram: 1. Support housing; 11. Drive gear; 12. Pin; 13. Half-tooth ring; 2. Fixed housing; 21. Ring groove; 22. Fixing block; 23. Push handle; 24. Pushing hydraulic cylinder; 3. Ultrasonic probe; 31. Strain gauge; 32. IMU module; 33. Drive hydraulic cylinder; 34. Support frame; 35. Detection hydraulic cylinder; 36. Push plate; 37. Push frame; 38. Return spring. Detailed Implementation

[0048] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0049] A method for analyzing the impact of pile-karst cave interaction during construction includes the following steps: Step 1, high-precision karst cave morphology detection: A cross-shaped survey line is laid out with the pile foundation as the center. The survey line length is ≥20m and the spacing is ≤1m. Simultaneously, a high-energy accelerometer is used with an impact energy ≥50kJ to excite active source surface waves with an impact frequency of 2-5Hz. Environmental noise is collected as a passive source surface wave for a duration ≥30 minutes. A three-component geophone array is used to receive the signal. The geophone array is laid out at equal intervals (horizontal spacing ≤0.5m, depth error ≤2cm) with a sampling rate ≥500Hz.

[0050] Step 2: After bandpass filtering the signal, apply linear Radon transform to extract dispersion energy and generate the fundamental-order surface wave dispersion curve.

[0051] The formula for extracting dispersion energy using the linear Ladon transform in step two is as follows: Where R(p,w) is the result of the Ladon transform (energy distribution function in the slowness-frequency domain), representing the energy at slowness p and angular frequency w, u(x,w) represents the frequency domain seismic signal at position x and angular frequency w, where x is the spatial coordinate (the position of the geophone along the survey line), and e iwpx Let dx be a plane wave, dx be the spatial calculus, the integral variable along the survey line, and i be the imaginary unit.

[0052] Step 3: Using a generalized pattern recognition algorithm based on global optimization, the surface wave dispersion curve is inverted. The objective function of the inversion is to minimize the L2 norm of the dispersion curve residual, so as to obtain two-dimensional shear wave velocity profiles below the four survey lines. The four profile data are then fused by Kriging space interpolation to construct a three-dimensional shear wave velocity model with the pile foundation as the core.

[0053] Preferably, the objective function for wave velocity profile inversion in step three is... d obs To observe the dispersion curve, the m-model parameters are... Vs The shear wave velocity distribution is given by h, formation thickness, ρ, and δ. cave Cave morphology parameters (elliptical eccentricity), λΓ is the regularization term (suppressing multiple solutions), λ is the regularization coefficient, d obs For the observed data vector, d calc (m) is the forward simulation data vector (the theoretical response calculated based on model m).

[0054] A generalized pattern recognition algorithm is adopted: an initial model population is generated (Monte Carlo random sampling), and iterative updates are performed: the model is optimized through crossover and mutation using a genetic algorithm to minimize the residual L2 norm.

[0055] Kriging interpolation was used on the two-dimensional Vs profile obtained by inversion from the four survey lines: Among them, w i w is the weighting coefficient. i Determined by the variogram γ(h): V represents the wave velocity value to be estimated (the predicted wave velocity value at spatial location x0). s(xi) Let be the known wave velocity value (the measured wave velocity at the i-th measuring point), n be the number of known points participating in the interpolation (taking 4-16 neighboring points), and γ(h) be the variogram (a function describing the spatial correlation of wave velocity). i0 This is the distance vector (the Euclidean distance between the known point and the predicted point).

[0056] Output: High-resolution 3D Vs model of the central area of ​​the pile foundation (mesh accuracy ≤ 0.5m).

[0057] Step 4: By analyzing the changes in wave velocity in the vertical and horizontal directions, and the anomalies in high-speed and low-speed areas, we can infer the thickness of the overburden, the burial depth of the bedrock, and the development depth, scale, and spatial distribution of monoliths and caves.

[0058] Step four involves identifying the thickness of the overburden and the depth of the bedrock: Vertical wave velocity gradient analysis: Calculating the wave velocity gradient in the z-direction of depth. Where z is the depth coordinate. Wave velocity-depth change rate (the change in wave velocity per meter of depth), engineering criterion: gradient abrupt change point. Indicator bedrock interface, gradient abrupt change point Indicator of the abrupt change in gradient at the top of the cave. Indicates a homogeneous soil layer, with the thickness of the overburden layer H = the depth of the abrupt change point.

[0059] Cave and Monolith Identification: Anomaly Identification Criteria: V S At speeds <150 m / s, the morphological characteristics are isolated, low-velocity closed regions, and the criterion formula is V. S ≤μ-2σ,V SAt speeds >800 m / s, the morphological characteristic is a localized high-speed bulge, and the criterion formula is V. S ≥μ+2σ, 150 <V S At speeds <300 m / s, the morphological characteristics are a strip-shaped low-speed region, and the criterion formula is ▽V S • n>50°, μ is the average shear wave velocity within the study area. σ represents the standard deviation of the shear wave velocity within the study area. Where N is the number of wave velocity measurement points within the selected background area, and V s,i Let be the measured wave velocity at position i.

[0060] Spatial distribution calculation: Cave size: Calculate the volume of the low-velocity region V=∫∫∫ Ω dV(Ω:V s <150m / s), where Ω is the definition of the cave region, dV is the volume element, and V<1m 3 It is a small karst cave, 5m 3 ≤V<5m 3 It is a medium-sized karst cave with a depth of V ≥ 5m. 3 It is a large karst cave.

[0061] Burial depth: Centroid depth of the anomaly zone:

[0062] Inclination angle: Calculated by slicing the interface normal vectors.

[0063] Step 5: Block-based design of pile foundation: Based on the 3D Vs model, construction schemes are classified according to the scale of the karst cave, the degree of interaction, and the interface inclination angle.

[0064] Step 5: Block-based construction strategy for pile foundations: Small, isolated karst caves with a diameter of less than 1m are filled with grout and conventionally drilled.

[0065] For medium-sized karst cave groups with diameters between 1 and 3 meters, casing installation and high-pressure grouting are carried out.

[0066] For large karst caves / fracture zones with diameters greater than 3m, cast-in-place concrete columns and pile foundations are relocated.

[0067] Step 6, Intelligent Monitoring of Construction Parameters: After installing the detection device on the sleeve to be installed, the hydraulic clamp presses the sleeve down. The IMU module 32, ultrasonic probe 3, and strain gauge 31 on the detection device monitor the sleeve's attitude, initial verticality, and risk of borehole collapse.

[0068] Step 6 Intelligent monitoring of construction parameters: Sleeve monitoring: IMU module 32: Real-time measurement of the casing inclination angle θ (accuracy ±0.1°), the calculation formula is: (a y a z(Y / Z axis acceleration).

[0069] Ultrasonic probe 3: Distance measurement Among them, υ s Let t be the speed of sound, and Δt be the echo time difference.

[0070] Strain gauge 31: Sleeve stress σ=E·ε, where E is the elastic modulus and ε is the strain.

[0071] Control logic: If θ>5° or d<0.5m, trigger the hydraulic system to correct the deviation.

[0072] Step 7: Combining the karst cave morphology and actual geological data collected during construction, further optimize the model inversion algorithm of advanced detection technology and active and passive source surface wave detection technology through back-analysis; and gradually correct the differences.

[0073] The specific optimization method in step seven is as follows: Active source frequency adjustment: If shallow caverns are missed, increase the high-frequency component (→10Hz), the formula is as follows. Among them, f new f is the adjusted active source frequency (optimized impact vibration dominant frequency). old The active source frequency currently in use is set to the original tamping frequency (2-5Hz), Δz is the error depth (the difference between the detected depth and the true depth), k is the adjustment coefficient (an empirical parameter that controls the frequency adjustment range), and H is the current effective surface wave detection depth (the maximum exploration depth related to the old frequency).

[0074] Inversion objective function correction: Add interface gradient constraint term: in, The wave velocity gradient revealed during construction.

[0075] Passive source noise utilization optimization: Adjust the weights of the environmental noise dispersion curve based on the actual Vs model. Among them, f c The frequency band sensitive to karst caves (calibrated from construction data), f is the current frequency (effective surface wave frequency band 1-50Hz), f width The bandwidth parameter controls the weighted attenuation rate (related to the size of the karst cave).

[0076] like Figures 1-5 As shown, the detection device in step six includes a support device, a fixing device, and a monitoring component.

[0077] The support device is located on the outer surface of the sleeve and supports the monitoring component. The support device includes a pin 12 with a rack. One end of the pin 12 is inserted into the outer surface of the sleeve to fix the monitoring component.

[0078] The fixing device is located on the outer surface of the support device and fixes the two support devices. The fixing device includes a fixing block 22, which fixes the two support devices.

[0079] The monitoring component is located on the outer surface of the support device. The IMU module 32, ultrasonic probe 3, and strain gauge 31 of the monitoring component monitor the attitude of the sleeve.

[0080] like Figures 2-3 As shown, the support device also includes a support housing 1. The inner wall of the support housing 1 is slidably inserted into one end of the insertion pin 12. Insertion holes distributed in an annular array are provided on the sleeve to facilitate insertion with the insertion pin 12. A drive gear 11 is rotatably connected to the inner wall of the support housing 1. The drive gear 11 meshes with the rack of the insertion pin 12. A half-tooth ring 13 is rotatably connected to the inner wall of the support housing 1. The half-tooth ring 13 meshes with the drive gear 11.

[0081] like Figures 2-5 As shown, specifically, in order to facilitate quick fixing between two symmetrically distributed support shells 1, the fixing device also includes a fixing shell 2. The fixing shell 2 is fixedly installed on the outer surface of the support shell 1. One end of the two fixing shells 2 is slidably inserted into each other. An annular groove 21 is fixedly installed on the inner wall of the fixing shell 2. The inner wall of the annular groove 21 is slidably inserted into the outer surface of the fixing block 22. A push handle 23 is fixedly installed on the outer surface of the fixing block 22. A push hydraulic cylinder 24 is hinged to the inner wall of the fixing shell 2 by a pin. One end of the piston rod of the push hydraulic cylinder 24 is hinged to one end of the push handle 23 by a pin.

[0082] To push the insertion pin 12, the ultrasonic probe 3 is fixedly installed on the lower surface of the support housing 1 in a ring array. The strain gauge 31 is fixedly installed on the outer surface of the support housing 1 and then contacts the outer surface of the sleeve. The strain gauge 31 is also arranged in a ring array. A driving hydraulic cylinder 33 is fixedly installed on the outer surface of one support housing 1. One end of the piston rod of the driving hydraulic cylinder 33 is fixedly installed with one end of the insertion pin 12. A support frame 34 is fixedly installed on the outer surface of the other support housing 1. A detection hydraulic cylinder 35 is fixedly installed on the outer surface of the support frame 34. A push plate 36 is fixedly installed on one end of the piston rod of the detection hydraulic cylinder 35. A push bracket 37 is slidably inserted into the outer surface of the push plate 36. A return spring 38 is fixedly installed on one end of the limit rod of the push bracket 37. One end of the return spring 38 is fixedly installed with the outer surface of the push plate 36. In order to push the IMU module 32 to the center position of the sleeve so as to monitor the attitude of the sleeve, one end of the outer surface of the push plate 36 is fixedly installed with the outer surface of the IMU module 32 through a connecting rod.

[0083] Working principle: When the detection device is required, after the two symmetrically distributed support shells 1 are placed on both sides of the sleeve, the opposite fixed shells 2 at both ends are slidably inserted into each other. By activating the push hydraulic cylinder 24 in the fixed shell 2, the push hydraulic cylinder 24 pushes the push handle 23 to deflect. The push handle 23 drives the fixed block 22 to deflect in the annular groove 21. After the two fixed blocks 22 are inserted into the other annular groove 21 respectively, the fixed shells 2 are fixed, thereby fixing the two ends of the support shell 1.

[0084] The detection hydraulic cylinder 35 and the drive hydraulic cylinder 33 are activated. The piston rod of the drive hydraulic cylinder 33 pushes the insertion pin 12 to move. The rack of the insertion pin 12 drives the drive gear 11 to rotate. Thus, the drive gear 11 drives the remaining insertion pins 12 to rotate through the transmission of the half-tooth ring 13. One insertion pin 12 on the support housing 1 is inserted into the insertion hole of the sleeve. The detection hydraulic cylinder 35 on the other side pushes the push plate 36 and the push frame on the push plate 36. The push frame drives the insertion pin 12 to move. After the insertion pin 12 moves and is inserted into the insertion hole of the sleeve, it is limited. The push plate 36 continues to push, which compresses the return spring 38. The push plate 36 drives the IMU module 32 to pass through the center of the insertion pin 12 and is located at the center of the sleeve. The attitude of the sleeve during the installation process is monitored by the cooperation of the ultrasonic probe 3, the IMU module 32 and the strain gauge 31.

[0085] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for analyzing the impact of the interaction between piles and karst caves during construction, characterized in that: The steps include: Step 1, High-precision karst cave morphology detection: A cross-shaped survey line is laid out with the pile foundation as the center. The survey line length is ≥20m and the spacing is ≤1m. At the same time, a high-energy accelerometer is used with an impact energy of ≥50kJ to excite active source surface waves with an impact frequency of 2-5Hz. Environmental noise is collected as a passive source surface wave and received by a three-component detector array with a sampling rate of ≥500Hz. Step 2: After bandpass filtering the signal, apply linear Ladon transform to extract dispersion energy and generate the fundamental-order surface wave dispersion curve; Step 3: Using a generalized pattern recognition algorithm based on global optimization, the surface wave dispersion curve is inverted. The objective function of the inversion is to minimize the L2 norm of the dispersion curve residual, so as to obtain two-dimensional shear wave velocity profiles below the four survey lines. The four profile data are then fused by Kriging space interpolation to construct a three-dimensional shear wave velocity model with the pile foundation as the core. Step 4: By analyzing the changes in wave velocity in the vertical and horizontal directions, and the anomalies in high-speed and low-speed areas, we can infer the thickness of the overburden, the burial depth of the bedrock, and the development depth, scale, and spatial distribution of monoliths and caves. Step 5: Block-based design of pile foundation: Based on the 3D Vs model, construction schemes are classified according to the scale of the karst cave, the degree of interaction, and the interface inclination angle; Step 6, Intelligent monitoring of construction parameters: After the detection device is installed on the sleeve to be installed, the hydraulic clamp presses the sleeve down, and the IMU module (32), ultrasonic probe (3) and strain gauge (31) on the detection device monitor the attitude of the sleeve and the initial verticality and the risk of hole collapse. Step 7: Combining the karst cave morphology and actual geological data collected during construction, further optimize the model inversion algorithm of advanced detection technology and active and passive source surface wave detection technology through back-analysis; and gradually correct the differences.

2. The method for analyzing the impact of pile-karst cave interaction during construction as described in claim 1, characterized in that: The formula for extracting dispersion energy using linear Ladon transform in step two is as follows: Where R(p,w) is the energy distribution function in the slowness-frequency domain, representing the energy at slowness p and angular frequency w, u(x,w) represents the frequency domain seismic signal at position x and angular frequency w, where x is the spatial coordinate (the position of the geophone along the survey line), and e iwpx Let dx be a plane wave, dx be the spatial calculus, the integral variable along the survey line, and i be the imaginary unit.

3. The method for analyzing the impact of pile-karst cave interaction during construction as described in claim 2, characterized in that: The objective function of wave velocity profile inversion in step three d obs To observe the dispersion curve, the m-model parameters are... V s The shear wave velocity distribution is given by h, formation thickness, ρ, and δ. cave Cave morphology parameters (elliptical eccentricity), λΓ is the regularization term (suppressing multiple solutions), λ is the regularization coefficient, d obs For the observed data vector, d calc (m) is the forward simulation data vector (the theoretical response calculated based on model m); A generalized pattern recognition algorithm is adopted: an initial model population is generated (Monte Carlo random sampling), and iterative updates are performed: the model is optimized through crossover and mutation using a genetic algorithm to minimize the residual L2 norm; Kriging interpolation was used on the two-dimensional Vs profile obtained by inversion from the four survey lines: Among them, w i w is the weighting coefficient. i Determined by the variogram γ(h): V is the predicted wave velocity at spatial location x0. s(xi) Let γ(h) be the measured wave velocity at the i-th measuring point, n be the number of known points involved in the interpolation (taking 4-16 neighboring points), and γ(h) be the variogram function. i0 This is the distance vector (the Euclidean distance between the known point and the predicted point); Output: High-resolution 3D Vs model of the central area of ​​the pile foundation (mesh accuracy ≤ 0.5m).

4. The method for analyzing the impact of pile-karst cave interaction during construction as described in claim 3, characterized in that: In step four, the identification of overburden thickness and bedrock burial depth includes: vertical wave velocity gradient analysis: calculating the wave velocity gradient in the depth z direction. Where z is the depth coordinate. Wave velocity-depth change rate (the change in wave velocity per meter of depth), engineering criterion: gradient abrupt change point: Indicator bedrock interface, gradient abrupt change point: Indicator of abrupt gradient change points on the ceiling of a sinkhole: Indicates a homogeneous soil layer, with the overburden thickness H = depth of the abrupt change point; Cave and Monolith Identification: Anomaly Identification Criteria: V S At speeds <150 m / s, the morphological characteristics are isolated, low-velocity closed regions, and the criterion formula is V. S ≤μ-2σ,V S At speeds >800 m / s, the morphological characteristic is a localized high-speed bulge, and the criterion formula is V. S ≥μ+2σ, 150 <V S At speeds <300 m / s, the morphological characteristics are strip-shaped low-speed regions, and the criterion formula is as follows: μ is the average shear wave velocity within the study area. σ represents the standard deviation of the shear wave velocity within the study area. Where N is the number of wave velocity measurement points within the selected background area, and V s,i The measured wave velocity at position i; Spatial distribution calculation: Cave size: Calculate the volume of the low-velocity region V=∫∫∫ Ω dV(Ω:V s <150m / s), where Ω is the definition of the cave region, dV is the volume element, and V<1m 3 It is a small karst cave, 5m 3 ≤V<5m 3 It is a medium-sized karst cave with a depth of V ≥ 5m. 3 It is a large karst cave; Burial depth: Centroid depth of the anomaly zone: Inclination angle: Calculated by slicing the interface normal vectors.

5. The method for analyzing the impact of pile-karst cave interaction during construction as described in claim 4, characterized in that: The construction strategy for pile foundation block classification in step five is as follows: small isolated karst caves with a diameter of less than 1m are filled by grouting and conventional drilling. For medium-sized karst cave groups with diameters between 1 and 3 meters, casing installation and high-pressure grouting are carried out. For large karst caves / fracture zones with diameters greater than 3m, cast-in-place concrete columns and pile foundations are relocated.

6. The method for analyzing the impact of pile-karst cave interaction during construction as described in claim 5, characterized in that: In step six, the intelligent monitoring of construction parameters includes: sleeve monitoring: IMU module (31): real-time measurement of the sleeve inclination angle θ (accuracy ±0.1°), and the calculation formula is: Among them, a y a z Y / Z axis acceleration; Ultrasonic probe (3): ranging Among them, υ s Let Δt be the speed of sound and Δt be the echo time difference. Strain gauge (31): Sleeve stress σ=E·ε, where E is the elastic modulus and ε is the strain; Control logic: If θ>5° or d<0.5m, trigger the hydraulic system to correct the deviation.

7. The method for analyzing the impact of pile-karst cave interaction during construction as described in claim 6, characterized in that: The specific optimization method in step seven is as follows: Active source frequency adjustment: If shallow caverns are missed, increase the high-frequency component (→10Hz), the formula is as follows. Among them, f new f is the adjusted active source frequency (optimized impact vibration dominant frequency). old The active source frequency currently in use is set to the original tamping frequency (2-5Hz), Δz is the error depth (the difference between the detected depth and the true depth), k is the adjustment coefficient (an empirical parameter that controls the frequency adjustment amplitude), and H is the current effective surface wave detection depth (the maximum exploration depth related to the old frequency). Inversion objective function correction: Add interface gradient constraint term: in, The wave velocity gradient revealed during construction; Passive source noise utilization optimization: Adjust the weights of the environmental noise dispersion curve based on the actual Vs model. Among them, f c The frequency band sensitive to karst caves (calibrated from construction data), f is the current frequency (effective surface wave frequency band 1-50Hz), f width The bandwidth parameter controls the weighted attenuation rate (related to the size of the karst cave).

8. The method for analyzing the impact of pile-karst cave interaction during construction as described in claim 1, characterized in that: The detection device in step six includes a support device, a fixing device, and a monitoring component; The support device is located on the outer surface of the sleeve and supports the monitoring component. The support device includes a pin (12) with a rack. One end of the pin (12) is inserted into the outer surface of the sleeve to fix the monitoring component. The fixing device is located on the outer surface of the support device and fixes the two support devices. The fixing device includes a fixing block (22), which fixes the two support devices. The monitoring component is located on the outer surface of the support device, and the IMU module (32), ultrasonic probe (3) and strain gauge (31) of the monitoring component monitor the attitude of the sleeve.

9. The method for analyzing the impact of pile-karst cave interaction during construction as described in claim 8, characterized in that: The support device further includes a support housing (1), the inner wall of which is slidably inserted into one end of the insertion pin (12), the inner wall of which is rotatably connected to a drive gear (11), the drive gear (11) meshing with the rack of the insertion pin (12), and the inner wall of which is rotatably connected to a half-tooth ring (13), the half-tooth ring (13) meshing with the drive gear (11).

10. The method for analyzing the impact of pile-karst cave interaction during construction as described in claim 9, characterized in that: The fixing device also includes a fixing shell (2), which is fixedly installed on the outer surface of the supporting shell (1). One end of the two fixing shells (2) is slidably inserted into each other. An annular groove (21) is fixedly installed on the inner wall of the fixing shell (2). The inner wall of the annular groove (21) is slidably inserted into the outer surface of the fixing block (22). A push handle (23) is fixedly installed on the outer surface of the fixing block (22). A push hydraulic cylinder (24) is hinged to the inner wall of the fixing shell (2) by a pin. One end of the piston rod of the push hydraulic cylinder (24) is hinged to one end of the push handle (23) by a pin. The ultrasonic probe (3) is fixedly installed on the lower surface of the support shell (1). The strain gauge (31) is fixedly installed on the outer surface of the support shell (1) and then contacts the outer surface of the sleeve. A driving hydraulic cylinder (33) is fixedly installed on the outer surface of one of the support shells (1). One end of the piston rod of the driving hydraulic cylinder (33) is fixedly installed with one end of the insertion pin (12). A support frame (34) is fixedly installed on the outer surface of the other support shell (1). A detection hydraulic cylinder (35) is fixedly installed on the outer surface of the support frame (34). A push plate (36) is fixedly installed on one end of the piston rod of the detection hydraulic cylinder (35). A push bracket (37) is slidably inserted into the outer surface of the push plate (36). A return spring (38) is fixedly installed on one end of the limiting rod of the push bracket (37). One end of the return spring (38) is fixedly installed with the outer surface of the push plate (36). One end of the outer surface of the push plate (36) is fixedly installed with the outer surface of the IMU module (32) through a connecting rod.

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