A method and system for monitoring deformation of shield excavation surface underpassing airport runway

Abstract

The present invention provides a method and system for monitoring the deformation of a shield excavation face underpassing an airport runway. The method and system generate pressure load response characteristics based on pressure fluctuation time series data of a cutterhead hydraulic cylinder in a shield machine in combination with dynamic load distribution data and static load distribution data. The deformation trajectory of the shield excavation face and the displacement change of the bottom soil underpassing the airport runway are obtained, and point cloud registration processing is performed to obtain registered data to extract two-dimensional deformation monitoring data of the shield excavation face and the bottom soil in the horizontal and vertical directions. Based on the pressure load response characteristics, the two-dimensional deformation monitoring data and the surface settlement monitoring data underpassing the airport runway, a deformation trend prediction result of the shield excavation face is obtained. The present invention realizes high-precision real-time monitoring and trend prediction of the coordinated deformation of the shield excavation face and the runway structure in the scenario of underpassing the airport runway, thereby ensuring the safety of runway operation and precise control of shield construction.

Description

Technical Field

[0001] The invention relates to the technical field of construction engineering, and in particular to a method and system for monitoring deformation of an excavation surface of a shield machine that passes under an airport runway. Background Art

[0002] During the construction of the shield tunnel under the airport runway, the vibration work after the concrete segments are assembled needs to dynamically adjust the vibration intensity under complex environmental temperature and humidity conditions to ensure the coordination of concrete density and runway structure deformation control. Since the airport runway is extremely sensitive to uneven settlement, and the temperature and humidity fluctuations in the underground working environment will significantly affect the setting speed and rheological properties of the concrete, the traditional fixed parameter vibration mode is prone to excessive voids in the concrete or excessive vibration to cause micro cracks in the segments, thereby exacerbating the risk of coordinated deformation between the excavation surface and the runway structure.

[0003] The typical technical solution currently available is a segmented control method for vibration intensity based on the linkage between temperature and humidity sensors and fixed thresholds. This method collects environmental data in real time through temperature and humidity sensors deployed in the segment assembly area of ​​the shield machine, triggers the preset vibration intensity adjustment rules based on the data, and adjusts the vibration parameters in a step-by-step manner in combination with the segment installation gap data monitored by the laser displacement meter. The existing solution has some defects, such as relying only on single-dimensional data, and the vibration intensity cannot be adjusted according to the actual deformation; the fixed threshold and adjustment formula are difficult to adapt to the influence of temperature and humidity interaction on the rheological properties of concrete. Summary of the invention

[0004] The present invention provides a method and system for monitoring the deformation of a shield excavation surface under an airport runway, so as to solve the problems in the prior art of relying on single-dimensional data, the inability to dynamically adjust the vibration intensity according to the actual deformation, and the difficulty in adapting to the influence of the nonlinear interaction of temperature and humidity on the rheological properties of concrete.

[0005] In a first aspect, the present invention provides a method for monitoring deformation of a shield excavation face for underpass of an airport runway, comprising:

[0006] Based on the pressure fluctuation time series data of the cutterhead hydraulic cylinder in the shield machine, combined with the dynamic load distribution data of the airport runway surface during the aircraft take-off and landing stage and the static load distribution data during the shutdown stage, the pressure load response characteristics associated with the shield machine's propulsion direction are generated;

[0007] Obtaining the deformation trajectory of the shield excavation surface and the displacement change of the bottom soil under the airport runway, performing point cloud registration processing on the deformation trajectory and the displacement change to obtain registered data;

[0008] Extracting two-dimensional deformation monitoring data of the shield excavation surface and the bottom soil in the horizontal direction and the vertical direction from the registered data;

[0009] Perform a correlation analysis on the pressure load response characteristics, the two-dimensional deformation monitoring data, and the surface settlement monitoring data of the tunnel boring machine (TBM) under the airport runway to obtain the prediction result of the deformation trend of the TBM excavation face.

[0010] Optionally, obtain the deformation trajectory of the TBM excavation face and the displacement change of the bottom soil mass of the tunnel under the airport runway, and perform point cloud registration processing on the deformation trajectory and the displacement change to obtain the registered data, including:

[0011] Generate deformation trajectory data based on the deformation trajectory of the TBM excavation face scanned by a laser scanning device along a preset circular scanning path;

[0012] Based on the bottom soil mass data corresponding to multiple different times scanned by the laser scanning device at a preset period, identify the coordinate offset of the bottom soil mass within the preset scanning period, and generate displacement change data based on the coordinate offset;

[0013] Adjust the scanning frequency of the laser scanning device according to the advancing distance of the TBM to generate synchronous deformation trajectory data and synchronous displacement change data;

[0014] Construct a three-dimensional coordinate system with the axis of the TBM as the reference, and map the synchronous deformation trajectory data and the synchronous displacement change data into the three-dimensional coordinate system to generate a deformation trajectory point cloud and a displacement change point cloud;

[0015] Set high-reflectivity marker points on the inner wall surface of the cutting ring of the TBM to perform dynamic compensation on the deformation trajectory point cloud and the displacement change point cloud, and generate a compensated deformation trajectory point cloud and a compensated displacement change point cloud;

[0016] Calculate the position offset of the compensated deformation trajectory point cloud in the horizontal advancing direction of the TBM and the height change of the compensated displacement change point cloud in the vertical direction to generate the registered data.

[0017] Optionally, set high-reflectivity marker points on the inner wall surface of the cutting ring of the TBM to perform dynamic compensation on the deformation trajectory point cloud and the displacement change point cloud, and generate a compensated deformation trajectory point cloud and a compensated displacement change point cloud, including:

[0018] Set a plurality of high-reflectivity marker points on the inner wall surface of the cutting ring of the TBM, wherein the spatial coordinates of each high-reflectivity marker point are pre-calibrated in the three-dimensional coordinate system;

[0019] Extract the real-time coordinates of each high-reflectivity marker point from the deformation trajectory point cloud and the displacement change point cloud, and calculate the coordinate offset vector between the real-time coordinates and the calibrated spatial coordinates;

[0020] Decomposing the coordinate offset vector into a longitudinal offset component and a lateral offset component, so as to perform reverse translation correction on the point cloud coordinates in the deformation trajectory point cloud and the displacement change point cloud, and obtain a corrected deformation trajectory point cloud and a corrected displacement change point cloud;

[0021] According to the pitch angle data and yaw angle data of the shield machine attitude sensor, rotation compensation is performed on the corrected deformation trajectory point cloud and the corrected displacement change point cloud to obtain a rotation-compensated deformation trajectory point cloud and a rotation-compensated displacement change point cloud;

[0022] According to the height change of the bottom soil in the rotationally compensated displacement change point cloud, the position offset of the rotationally compensated deformation trajectory point cloud is reversely corrected to generate a compensated deformation trajectory point cloud. According to the position offset of the rotationally compensated deformation trajectory point cloud, the height change of the displacement change point cloud is reversely corrected to generate a compensated displacement change point cloud.

[0023] In a second aspect, the present invention provides a shield excavation face deformation monitoring system for underpass of an airport runway, comprising:

[0024] A generation module is used to generate pressure load response characteristics associated with the propulsion direction of the shield machine based on the pressure fluctuation time series data of the cutter head hydraulic cylinder in the shield machine, combined with the dynamic load distribution data of the airport runway surface during the aircraft take-off and landing phase and the static load distribution data during the shutdown phase;

[0025] A registration module is used to obtain the deformation trajectory of the shield excavation surface and the displacement change of the bottom soil under the airport runway, and perform point cloud registration processing on the deformation trajectory and the displacement change to obtain registered data;

[0026] An extraction module, used to extract two-dimensional deformation monitoring data of the shield excavation surface and the bottom soil in the horizontal direction and the vertical direction from the registered data;

[0027] The analysis module is used to correlate and analyze the pressure load response characteristics, the two-dimensional deformation monitoring data, and the surface settlement monitoring data of the underpass airport runway to obtain the deformation trend prediction result of the shield excavation face.

[0028] In a third aspect, the present invention provides a computing device comprising a processor and a memory, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute a method for monitoring deformation of a shield excavation face passing under an airport runway as described in any one of the first aspects.

[0029] In a fourth aspect, the present invention provides a computer storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement a method for monitoring deformation of a shield excavation face for passing under an airport runway as described in any one of the first aspects.

[0030] In the present invention, based on the pressure fluctuation time series data of the cutter head hydraulic cylinder in the shield machine, combined with the dynamic load distribution data of the airport runway surface during the aircraft take-off and landing stage and the static load distribution data during the shutdown stage, a pressure load response feature associated with the propulsion direction of the shield machine is generated; the deformation trajectory of the shield excavation surface and the displacement change of the bottom soil under the airport runway are obtained, and the deformation trajectory and the displacement change are subjected to point cloud registration processing to obtain the registered data; the two-dimensional deformation monitoring data of the shield excavation surface and the bottom soil in the horizontal direction and the vertical direction are extracted from the registered data; the pressure load response feature, the two-dimensional deformation monitoring data and the surface settlement monitoring data under the airport runway are correlated and analyzed to obtain the deformation trend prediction result of the shield excavation surface. The technical solution provided by the present invention solves the problem of separation between mechanical parameters and external load data in traditional methods, and provides a mechanical coupling basis for deformation trend analysis; solves the problem of inconsistent spatiotemporal benchmarks of multi-source deformation data, and improves the accuracy and credibility of data space synchronization; through the bidirectional deformation characteristics of horizontal propulsion direction displacement and vertical settlement direction displacement, it breaks through the limitations of traditional single-direction monitoring, and accurately captures the composite deformation mode under the superposition of shield thrust and aircraft load; through multimodal correlation analysis, it realizes the overall state evaluation of the shield-runway system, and solves the defects of isolated analysis of mechanical system and soil deformation in traditional monitoring. Further breakthroughs in the core problems of separation of excavation face and runway deformation data, large vibration and noise interference, and single-dimensional monitoring limitations in traditional monitoring, through spatiotemporal synchronous scanning, vibration compensation and bidirectional displacement correlation mechanism, it realizes the physical linkage monitoring of shield thrust and runway structure deformation, improves data consistency and anti-interference ability, and provides high-precision, multi-dimensional collaborative deformation monitoring input for the scene of underpass airport runway.

[0031] These and other aspects of the present invention will become more apparent from the following description of the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1A flowchart of a shield excavation face deformation monitoring method provided by an embodiment of the present invention;

[0034] Figure 2 A structural schematic diagram of a shield excavation face deformation monitoring system provided by an embodiment of the present invention;

[0035] Figure 3 A structural schematic diagram of a computing device provided by an embodiment of the present invention. Detailed implementation manners

[0036] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0037] In some processes described in the specification and claims of the present invention and the above-mentioned drawings, a plurality of operations appear in a specific order. However, it should be clearly understood that these operations may not be executed in the order in which they appear herein or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions such as "first" and "second" in this article are used to distinguish different messages, devices, modules, etc., and do not represent a sequence, nor do they limit that "first" and "second" are of different types.

[0038] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0039] Figure 1 A flowchart of a shield excavation face deformation monitoring method provided by an embodiment of the present invention is as follows Figure 1 shown, and the method includes:

[0040] In view of the high-precision monitoring requirements for the coordinated deformation of the shield excavation face and the runway structure in the scenario of tunneling under an airport runway, traditional methods rely only on a single deformation data source and do not incorporate the coupling effects of shield thrust and aircraft loads, resulting in lagging deformation prediction and insufficient accuracy, and unable to meet the millimeter-level deformation control requirements of the runway structure. Through the design of a multi-source heterogeneous data collaboration mechanism, the present invention first integrates the time-series data of the hydraulic cylinder pressure of the shield machine and the load distribution characteristics of the runway, quantifies the thrust-force mapping relationship, and solves the problem of the separation of mechanical parameters and environmental loads in traditional methods. Secondly, the dual-array laser scanning and dynamic point cloud registration technology are used to synchronously collect the deformation trajectory of the excavation face and the displacement change of the runway soil body, and generate two-dimensional deformation monitoring data through spatial reference unification and vibration compensation, breaking through the limitations of single-direction monitoring. Finally, multi-modal correlation analysis is carried out in combination with surface settlement data, a coupling relationship between shield propulsion parameters and runway deformation is established, and active prediction of the deformation trend based on the mechanical transmission chain is realized, shortening the early warning response time and improving the accuracy, directly overcoming the defects of data isolation, response lag, and single direction in the existing technology. Based on this, the present invention provides a method for monitoring the deformation of the shield excavation face for tunneling under an airport runway, as Figure 1 , including:

[0041] Step 101: Based on the time-series data of the pressure fluctuations of the cutterhead hydraulic cylinders in the shield machine, combined with the dynamic load distribution data on the surface of the airport runway during the aircraft takeoff and landing phases and the static load distribution data during the parking phase, generate pressure-load response characteristics associated with the shield machine propulsion direction;

[0042] In this step, the time-series data of pressure fluctuations refers to the hydraulic pressure change data continuously recorded over time by the cutterhead hydraulic cylinders in the shield machine during propulsion. The dynamic load distribution data refers to the dynamic pressure distribution data applied to the surface of the airport runway during the aircraft takeoff and landing phases. The static load distribution data refers to the static pressure distribution data applied to the runway surface during the aircraft parking phase. The pressure-load response characteristics refer to the dynamic characteristic parameters characterizing the interaction relationship between the shield thrust and the runway structure force.

[0043] In this step, first, the mean value, variance, and peak frequency characteristics of the time-series data of pressure fluctuations are extracted through a pressure fluctuation analysis model; synchronously combined with the dynamic load impact coefficient (such as the aircraft model-load comparison table) and static load distribution weight (such as the parking position density map) in the runway load distribution data, the pressure fluctuation characteristics and the load distribution data are spatially and temporally correlated and matched by dynamic load superposition to generate pressure-load response characteristics, and the load transfer effect of the shield thrust on the runway structure under the airport during different propulsion stages is quantified.

[0044] Step 102: Obtain the deformation trajectory of the shield excavation face and the displacement change of the bottom soil body of the tunnel under the airport runway, and perform point cloud registration processing on the deformation trajectory and the displacement change to obtain the registered data;

[0045] In this step, the deformation trajectory of the shield excavation face refers to the three-dimensional deformation path of the contour of the excavated soil mass in front of the shield machine during the propulsion process, which is captured by continuous deformation point cloud data obtained through high-speed laser scanning. The displacement change of the bottom soil mass refers to the three-dimensional position offset of the soil mass under the airport runway caused by shield construction disturbance, which is obtained through the reverse laser scanning of the soil movement trajectory data. The registered data refers to the synchronized calibration data after unifying the spatial reference and compensating for vibration of the deformation trajectory point cloud of the shield excavation face and the displacement point cloud of the bottom soil mass of the runway, and has a consistent spatio-temporal coordinate system.

[0046] In this step, through a dual-array high-speed three-dimensional laser scanning device installed on the cutter head ring of the shield machine, the first array captures the deformation trajectory of the excavation face with a circular scanning path to generate a deformation trajectory point cloud; the second array scans the bottom soil mass of the runway in reverse through the reserved holes in the segment to generate a displacement change point cloud; the dynamic point cloud registration technology is adopted to establish a three-dimensional coordinate system based on the axis of the shield machine, map the two sets of point cloud data to this coordinate system, and compensate for the vibration error through the real-time coordinate offset of the high-reflectivity marker points to generate the registered data.

[0047] Step 103: Extract the two-dimensional deformation monitoring data of the shield excavation face and the bottom soil mass in the horizontal and vertical directions from the registered data;

[0048] In this step, the two-dimensional deformation monitoring data refers to the combined monitoring data set of the displacement amount (X-axis) in the horizontal propulsion direction of the shield excavation face and the vertical settlement amount (Z-axis) of the bottom soil mass of the runway extracted from the registered data.

[0049] In this step, the registered data is divided into grids according to a preset grid. The horizontal direction is divided into grids with the shield machine propulsion step distance as the unit length, and the maximum positive offset of the X coordinate of the point cloud in each unit is statistically calculated as the horizontal deformation value; the vertical direction is divided into grids with the layered thickness of the bottom soil mass of the runway as the unit height, and the maximum settlement amount of the Z coordinate of the point cloud in each unit is statistically calculated as the vertical deformation value; the horizontal deformation mutation area is identified through the displacement gradient analysis model, and the layered settlement contribution degree in the vertical direction is quantified in combination with the layered compression analysis model, and the above results are synthesized to generate a two-dimensional data set including the horizontal-vertical displacement correlation characteristics.

[0050] Step 104: Conduct a correlation analysis on the pressure load response characteristics, the two-dimensional deformation monitoring data, and the surface settlement monitoring data of the shield tunneling under the airport runway to obtain the deformation trend prediction result of the shield excavation face;

[0051] In this step, the surface settlement monitoring data refers to the vertical settlement amount and settlement rate data of the runway surface collected in real time through high-precision settlement sensors arranged on the runway surface. The deformation trend prediction result refers to the prediction index of the future deformation amount, deformation direction, and deformation rate of the shield excavation face.

[0052] In this step, a spatio-temporal correlation analysis model is used to bind the pressure load response characteristics, two-dimensional deformation data, and surface settlement data according to the time stamp and spatial position; based on the shield thrust-soil response transfer chain model, a linear regression relationship between the peak pressure fluctuation and the horizontal deformation value, and a non-linear coupling relationship between the vertical settlement and the surface settlement are established. Through a multi-modal data fusion algorithm, a joint analysis matrix is generated, and combined with the deformation conduction delay correction mechanism, the deformation trend of the excavation face within the next 3 propulsion steps is predicted, and the deformation trend prediction result is generated.

[0053] For example, when the shield machine advances under the runway, the pressure fluctuation data of the hydraulic system shows that the peak frequency is 2 Hz. Combining the dynamic load distribution and the static load during shutdown of the B747-8 model during this period, the pressure load response characteristics are generated, showing that the load transfer efficiency in the middle section of the propulsion direction is the highest; the double-array laser scanning device captures the local collapse deformation trajectory of the excavation face and the displacement change of the soil at the bottom of the runway. After vibration compensation registration, the registered data is generated; the horizontal deformation data extracted from the registered data shows that the horizontal displacement gradient in the collapse area is 0.5 mm / m, and the vertical direction data shows that the compression ratio of the underlying soil is 70%; the correlation analysis shows that the peak pressure fluctuation is strongly correlated with the horizontal deformation, and the surface settlement lags behind the vertical settlement by 2 steps. It is predicted that the deformation in the next stage will be conducted to the east side of the runway to trigger a deviation correction instruction to adjust the pressure distribution of the hydraulic cylinder.

[0054] The embodiment of the present invention solves the problem of lag in deformation prediction caused by data isolation in the traditional method; realizes active prediction and closed-loop control of the deformation trend, and improves the safety and deformation control accuracy of construction.

[0055] The present invention provides a specific embodiment. Step 102: Obtain the deformation trajectory of the shield excavation face and the displacement change of the soil at the bottom of the runway under the airport. Perform point cloud registration processing on the deformation trajectory and the displacement change to obtain the registered data, which specifically includes the following steps:

[0056] Step 201: Based on the deformation trajectory of the shield excavation face scanned by the laser scanning device along a preset circular scanning path, generate deformation trajectory data;

[0057] In this step, the preset circular scanning path refers to a closed circular scanning route set by the laser scanning device circumferentially on the cutting ring of the shield machine, covering the entire circumference of the excavation face contour, and is used to continuously collect deformation trajectory data. The deformation trajectory data refers to the data of the change of the shield excavation face contour continuously collected by the laser scanning device along the circular scanning path, reflecting the spatio-temporal distribution characteristics of soil collapse, uplift and other deformations during the propulsion process.

[0058] In this step, a first set of three-dimensional laser scanning devices installed on the cutting ring of the shield machine continuously scans the shield excavation face along a preset circular path to obtain data related to the shield excavation face. The three-dimensional coordinate changes of the contour points of the shield excavation face in this data are captured through high-speed laser ranging technology to generate deformation trajectory data containing time stamps. This deformation trajectory data records the deformation amounts at each position of the excavation face in real time for subsequent synchronous analysis and compensation processing.

[0059] Step 202: Based on the bottom soil data corresponding to multiple different times scanned by the laser scanning device at a preset period, identify the coordinate offset of the bottom soil within the preset scanning period. Based on the coordinate offset, generate displacement change data;

[0060] In this step, the bottom soil data refers to the set of three-dimensional coordinate points obtained by scanning the bottom soil of the airport runway with the laser scanning device. The preset scanning period refers to the frequency setting for the laser scanning device to collect data at fixed time intervals. The coordinate offset refers to the three-dimensional coordinate difference of the same soil area in different scanning periods. The displacement change data refers to the dataset for quantifying the displacement of the bottom soil of the runway generated based on the coordinate offset.

[0061] In this step, a second set of three-dimensional laser scanning devices is set at a specified position of the segments already assembled at the tail of the shield machine. Periodic scanning of the bottom soil of the airport runway is carried out through the holes filled with light-transmitting materials towards the bottom soil of the airport runway. The three-dimensional coordinate data of the soil surface obtained from each scan is compared with the initial reference scan data in terms of spatial position to identify the coordinate offset of the soil within consecutive scanning periods. Based on the coordinate offset, displacement change data reflecting the displacement direction and amplitude of the soil is generated. Among them, the axis direction of the holes filled with light-transmitting materials is perpendicular to the extension direction of the shield tunneling under the airport runway, so that the scanning beam covers the entire width of the bottom soil of the runway.

[0062] Step 203: According to the advancing distance of the shield machine, adjust the scanning frequency of the laser scanning device to generate synchronous deformation trajectory data and synchronous displacement change data;

[0063] In this step, the advancing distance of the shield machine refers to the actual displacement of the cutter head of the shield machine along the axis direction, which is used to synchronously adjust the scanning frequency to match the advancing speed. The synchronous deformation trajectory data refers to the deformation trajectory data generated after dynamically adjusting the scanning frequency according to the advancing distance of the shield machine, and its time stamp is strictly bound to the real-time position of the shield machine. The synchronous displacement change data refers to the displacement change data collected synchronously with the advancing distance of the shield machine to ensure the spatio-temporal consistency of the deformation and displacement data.

[0064] In this step, the propulsion distance is obtained in real time through the shield machine propulsion encoder, and the laser scanning frequency is dynamically adjusted according to the propulsion speed, so that the timestamps of the deformation trajectory data and the displacement change data are strictly matched with the real-time position of the shield machine, generating spatiotemporally synchronized deformation trajectory data and displacement change data.

[0065] Step 204: Based on the axis of the shield machine, a three-dimensional coordinate system is constructed, and the synchronous deformation trajectory data and the synchronous displacement change data are mapped into the three-dimensional coordinate system to generate a deformation trajectory point cloud and a displacement change point cloud.

[0066] In this step, the axis of the shield machine refers to the central reference line of the main structure of the shield machine, which is defined as the X-axis direction in the three-dimensional coordinate system and serves as the core basis for unified spatial reference. The three-dimensional coordinate system refers to a spatial reference system established with the axis of the shield machine as the X-axis, the horizontal direction perpendicular to the axis as the Y-axis, and the vertical direction as the Z-axis, which is used to uniformly map deformation and displacement data. The deformation trajectory point cloud refers to a three-dimensional point set generated after mapping the synchronous deformation trajectory data into the three-dimensional coordinate system, which describes the geometric characteristics of the excavation face contour deformation. The displacement change point cloud refers to a three-dimensional point set generated after mapping the synchronous displacement change data into the three-dimensional coordinate system, which describes the geometric characteristics of the soil displacement at the bottom of the runway.

[0067] In this step, through a coordinate transformation algorithm, each deformation position in the synchronous deformation trajectory data is mapped into the three-dimensional coordinate system constructed based on the axis of the shield machine according to the time series to generate a deformation trajectory point cloud. At the same time, each displacement measurement value in the synchronous displacement change data is converted into three-dimensional space coordinates based on the spatial projection path of the scanning beam to generate a displacement change point cloud.

[0068] Step 205: On the inner wall surface of the cutting ring of the shield machine, high-reflectivity marker points are set to perform dynamic compensation on the deformation trajectory point cloud and the displacement change point cloud, generating a compensated deformation trajectory point cloud and a compensated displacement change point cloud.

[0069] In this step, the cutting ring of the shield machine refers to the annular structural component at the front end of the shield machine where the cutter head and the laser scanning device are installed, which is used to support the excavation face and fix the scanning device. The high-reflectivity marker points refer to physical marker points with high reflectivity characteristics set on the inner wall surface of the cutting ring of the shield machine, whose coordinates are pre-calibrated and are used to dynamically compensate for the point cloud offset caused by vibration. The compensated deformation trajectory point cloud refers to a three-dimensional point set after correcting the vibration offset of the deformation trajectory point cloud, eliminating the interference of mechanical vibration on the deformation monitoring data. The compensated displacement change point cloud refers to a three-dimensional point set after correcting the vibration offset of the displacement change point cloud, eliminating the interference of mechanical vibration on the displacement monitoring data.

[0070] In this step, highly reflective marking points are set on the inner wall surface of the cutter head ring of the shield machine for coordinate reference correction; dynamic compensation is achieved through the following process, including extracting the real-time coordinates of the marking points from the deformation trajectory point cloud and the displacement change point cloud; calculating the offset between the coordinates of the marking points and the calibrated coordinates; performing reverse translation correction on all points in the two types of point clouds; and combining the pitch angle data of the attitude sensor of the shield machine to perform rotational compensation on the point cloud after reverse translation correction to generate a compensated deformation trajectory point cloud and a compensated displacement change point cloud.

[0071] Step 206: Calculate the position offset of the compensated deformation trajectory point cloud in the horizontal propulsion direction of the shield machine and the height change of the compensated displacement change point cloud in the vertical direction to generate registered data;

[0072] In this step, the position offset refers to the coordinate change amount of each point in the compensated deformation trajectory point cloud along the propulsion direction (X-axis) of the shield machine, reflecting the deformation amplitude in the horizontal direction. The height change amount refers to the coordinate change amount of each point in the compensated displacement change point cloud along the vertical direction (Z-axis), reflecting the settlement or uplift amplitude of the soil at the bottom of the runway.

[0073] In this step, the compensated deformation trajectory point cloud and the compensated displacement change point cloud are divided into multiple grid units at a preset interval. Calculate the position offset of the compensated deformation trajectory point cloud in the horizontal propulsion direction within each grid unit, that is, statistically calculate the maximum X coordinate offset of the points within each grid unit in the horizontal propulsion direction; calculate the height change of the compensated displacement change point cloud in the vertical direction, that is, statistically calculate the maximum height change of the Z coordinates of the points within each grid unit in the vertical direction; associate the position offset and the height change of the same grid unit to generate registered data.

[0074] The embodiment of the present invention solves the problem of inaccurate deformation monitoring caused by mechanical vibration in the traditional method through laser scanning and dynamic compensation technology; it breaks through the defect of the fragmentation of single-dimensional data.

[0075] The present invention provides a specific embodiment. In step 205, highly reflective marking points are set on the inner wall surface of the cutter head ring of the shield machine to perform dynamic compensation on the deformation trajectory point cloud and the displacement change point cloud, and generate a compensated deformation trajectory point cloud and a compensated displacement change point cloud, which specifically include the following steps:

[0076] Step 211: Set a plurality of highly reflective marking points on the inner wall surface of the cutter head ring of the shield machine, wherein the spatial coordinates of each highly reflective marking point are pre-calibrated in the three-dimensional coordinate system;

[0077] In the shield machine assembly stage, this step calibrates the spatial coordinates of multiple high-reflectivity marked points evenly distributed on the inner wall surface of the cutting ring of the shield machine through a total station measurement system, records their precise positions, and uses them as the basis for subsequent dynamic compensation.

[0078] Step 212: Extract the real-time coordinates of each high-reflectivity marked point from the deformation trajectory point cloud and the displacement change point cloud, and calculate the coordinate offset vector between the real-time coordinates and the calibrated spatial coordinates;

[0079] In this step, the coordinate offset vector refers to the spatial position difference vector between the real-time coordinates of the high-reflectivity marked point and its calibrated coordinates in the three-dimensional coordinate system.

[0080] In this step, in the deformation trajectory point cloud and the displacement change point cloud, based on the high-reflectivity characteristics of each high-reflectivity marked point, all points in the point cloud with brightness values greater than the threshold are screened out through a preset brightness threshold, and the screened points are clustered into independent point groups according to spatial coordinates, with each point group corresponding to a high-reflectivity marked point; for each point group, the average value of the three-dimensional coordinates of all points in the point group is taken as the real-time coordinates of the high-reflectivity marked point; the three components of the real-time coordinates of each high-reflectivity marked point are respectively subtracted from the corresponding components of its calibrated spatial coordinates to obtain the coordinate differences in three directions, and the coordinate differences in the three directions are combined into a coordinate offset vector according to the shield machine axis direction, the horizontal direction perpendicular to the axis, and the vertical direction.

[0081] Step 213: Decompose the coordinate offset vector into a longitudinal offset component and a transverse offset component to perform reverse translation correction on the point cloud coordinates in the deformation trajectory point cloud and the displacement change point cloud, and obtain the corrected deformation trajectory point cloud and the corrected displacement change point cloud;

[0082] In this step, the longitudinal offset component refers to the component of the coordinate offset vector along the shield machine axis direction, which reflects the mechanical vibration error caused by the forward or backward movement of the shield machine. The transverse offset component refers to the component of the coordinate offset vector perpendicular to the shield machine axis direction, which reflects the error caused by the vibration of the shield machine.

[0083] This step uses a vector decomposition mechanism to decompose the coordinate offset vector into a longitudinal offset component along the shield machine axis direction and a transverse offset component perpendicular to the axis, and then corrects the coordinates of each point in the deformation trajectory point cloud and the displacement change point cloud, including longitudinal correction, where the X coordinate of all points is subtracted by ΔX; transverse correction, where the Y coordinate of all points is subtracted by ΔY and the Z coordinate is subtracted by ΔZ; after correction, the coordinates of the high-reflectivity marked point are restored to the calibrated value, that is, the real-time coordinates of the high-reflectivity marked point are restored to (X0, Y0, Z0), and the remaining point cloud data is corrected synchronously to generate the corrected deformation trajectory point cloud and the corrected displacement change point cloud.

[0084] Step 214: According to the pitch angle data and yaw angle data of the shield machine attitude sensor, perform rotational compensation on the corrected deformed trajectory point cloud and the corrected displacement change point cloud to obtain a rotationally compensated deformed trajectory point cloud and a rotationally compensated displacement change point cloud;

[0085] In this step, the pitch angle data refers to the angle of rotation of the shield machine around the Y-axis; the yaw angle data refers to the angle of rotation of the shield machine around the Z-axis.

[0086] In this step, the pitch angle data and yaw angle data are obtained in real time through the attitude sensor, and the rotation matrix is used to perform rotational compensation on the corrected point cloud. This is completed by rotating the deformed trajectory point cloud and the displacement change point cloud around the axis of the shield machine by an angle equal to the opposite of the pitch angle and yaw angle. After rotational compensation, a rotationally compensated deformed trajectory point cloud and a rotationally compensated displacement change point cloud are generated, eliminating data tilt or offset caused by changes in the shield machine attitude.

[0087] Step 215: According to the height change amount of the bottom soil in the rotationally compensated displacement change point cloud, perform reverse correction on the position offset amount of the rotationally compensated deformed trajectory point cloud to generate a compensated deformed trajectory point cloud. According to the position offset amount of the rotationally compensated deformed trajectory point cloud, perform reverse correction on the height change amount of the displacement change point cloud to generate a compensated displacement change point cloud;

[0088] The reverse correction process in this step includes defining a correction logic, including setting a correlation proportionality coefficient between the position offset amount of the deformed trajectory point cloud and the height change amount of the displacement change point cloud; then performing two-way correction. By traversing each grid cell, reading the height change amount of the displacement change point cloud, and correcting the position offset amount of the rotationally compensated deformed trajectory point cloud according to the preset soil mechanics proportionality coefficient; synchronously reading the position offset amount of the deformed trajectory point cloud and correcting the height change amount of the rotationally compensated displacement change point cloud according to the preset soil mechanics proportionality coefficient; iterating the above operations until the preset convergence condition is met, and finally generating a compensated deformed trajectory point cloud and a compensated displacement change point cloud.

[0089] Through the dynamic compensation mechanism of high-reflectivity marker points in the embodiments of the present invention, the problem of point cloud data distortion caused by mechanical vibration and attitude changes in traditional methods is solved; through the two-way correction technology, the limitation of isolated processing of horizontal and vertical deformation data is broken through, and the accurate elimination of the coupling effect of soil deformation is realized; by combining the synergistic effects of rotational compensation and translational correction, the reliability and consistency of deformation monitoring of the shield excavation surface and runway soil body are significantly improved, providing high-precision data support for deformation control under complex working conditions.

[0090] The present invention provides a specific embodiment. In step 206, calculate the position offset of the compensated deformed trajectory point cloud in the horizontal propulsion direction of the shield machine and the height change of the compensated displacement change point cloud in the vertical direction to generate the registered data, which specifically includes the following steps:

[0091] Step 221: Along the horizontal propulsion direction of the shield machine, divide the compensated deformed trajectory point cloud into multiple horizontal monitoring units, and statistically calculate the average offset of the abscissa coordinates of all points in the compensated deformed trajectory point cloud in the horizontal monitoring unit relative to the initial reference horizontal position to generate the position offset in the horizontal propulsion direction;

[0092] In this step, the horizontal propulsion direction of the shield machine refers to the direction in which the shield machine advances forward along its axis, and is used to describe the change trend of the horizontal component of the deformation of the excavation face and the soil displacement. The horizontal monitoring unit refers to an equally spaced data statistical area divided along the horizontal propulsion direction (X-axis). The initial reference horizontal position refers to the average value of the initial X-axis coordinates of all points in the horizontal monitoring unit determined by measurement before construction. The average offset refers to the arithmetic mean of the difference between the current X-axis coordinates of all points in the same horizontal monitoring unit and the initial reference horizontal position.

[0093] In this step, with the axis of the shield machine as the X-axis direction, the compensated deformed trajectory point cloud is divided into a continuous plurality of horizontal monitoring units along the X-axis at a preset interval. The length of each horizontal monitoring unit is 1 / 10 of the diameter of the shield machine cutter head, and the starting boundary is aligned with the initial propulsion position of the shield machine cutter head. Before the shield machine starts to advance, record the initial value of the X-axis coordinates of all points in each horizontal monitoring unit in the compensated deformed trajectory point cloud as the initial reference horizontal position. During the advancement of the shield machine, real-time obtain the X-axis coordinates of all points in the compensated deformed trajectory point cloud in each horizontal monitoring unit, calculate the difference between the X coordinate of each point and the initial reference horizontal position of the corresponding horizontal monitoring unit to obtain the offset of a single point. Take the arithmetic mean of the offsets of all points in each horizontal monitoring unit to generate the position offset in the horizontal propulsion direction of the unit. According to the division order of the horizontal monitoring units, arrange the average offsets of all units according to the time stamp to generate a sequence of position offsets in the horizontal propulsion direction corresponding to the advancement distance of the shield machine.

[0094] Step 222: Along the vertical propulsion direction of the shield machine, divide the compensated displacement change point cloud into multiple vertical monitoring units, and statistically calculate the average height change of the ordinate coordinates of all points in the compensated displacement change point cloud in the vertical monitoring unit relative to the initial reference vertical position to generate the height change in the vertical direction;

[0095] In this step, the vertical propulsion direction of the shield machine is perpendicular to the axis of the shield machine (usually defined as the Z-axis direction), which is used to describe the change trend of the vertical component of the settlement or uplift of the soil at the bottom of the runway. The vertical monitoring unit refers to the equal-height data statistical area divided along the vertical direction (Z-axis). The height of each unit is in a preset ratio to the thickness of the soil layers at the bottom of the runway and is used to statistically analyze the settlement data in layers. The initial reference vertical position refers to the average value of the initial Z-axis coordinates of all points within the vertical monitoring unit determined through survey before construction, which serves as the reference benchmark for calculating height changes. The average height change refers to the arithmetic mean of the differences between the current Z-axis coordinates of all points within the same vertical monitoring unit and the initial reference vertical position, representing the overall vertical deformation amplitude of the unit.

[0096] In this step, a division coordinate system in the vertical direction (Z-axis) is established with the axis of the shield machine as the reference; according to the designed thickness of the soil at the bottom of the airport runway, the compensated displacement change point cloud is divided into N equal-height vertical monitoring units along the Z-axis direction; the displacement change point cloud data at the corresponding position in the previous scan cycle is taken as the initial reference; for the point cloud within each vertical monitoring unit, the Z-axis coordinate position in the previous cycle is recorded as the initial reference vertical position; for each vertical monitoring unit in the current scan cycle, the Z-axis coordinates of all the point cloud within the unit are extracted; the difference between the current Z-axis coordinate of each point and its corresponding initial reference vertical position coordinate is calculated to obtain the height change of each point; the arithmetic mean of the height changes of all points is taken; the above process is repeated for all N vertical monitoring units to generate the corresponding average height change for each unit; the average height changes of all vertical monitoring units are arranged in the order of the unit spatial positions; for each vertical monitoring unit, its average height change is marked at the midpoint position of the unit in space; based on the average height changes of all vertical monitoring units, the height change along the vertical direction of the soil is generated.

[0097] Step 223: Map the corresponding position offsets and height changes at the same timestamp according to the spatial position coordinates of the horizontal monitoring unit and the vertical monitoring unit to generate a two-way displacement dataset;

[0098] In this step, the two-way displacement dataset refers to a structured data set formed by associating the position offsets of the horizontal monitoring unit with the height changes of the corresponding vertical monitoring unit according to the spatial position and timestamp.

[0099] This step is based on the central point coordinates of the horizontal monitoring unit and the central point coordinates of the vertical monitoring unit. When the spatial position difference between the two does not exceed the preset tolerance range, it is determined that the horizontal monitoring unit and the vertical monitoring unit belong to the same monitoring section in the shield machine propulsion direction; the position offset of the horizontal monitoring unit belonging to the same monitoring section and the height change of the vertical monitoring unit are bound into a displacement correlation pair; all monitoring sections are traversed, and all displacement correlation pairs at the same timestamp are arranged in the order of the monitoring section number to generate a two-way displacement dataset containing the one-to-one correspondence between the position offset and the vertical settlement amount.

[0100] Step 224: Calculate the first ratio of the position offset of each horizontal monitoring unit in the two-way displacement dataset and the height change of the corresponding vertical monitoring unit. When the first ratio exceeds the preset threshold, correct the position offset to generate the registered data;

[0101] In this step, the preset threshold refers to the maximum allowable ratio of the horizontal displacement amount to the vertical settlement amount set based on the soil mechanics characteristics.

[0102] This step is for each horizontal monitoring unit in the two-way displacement dataset and its corresponding vertical monitoring unit. First, calculate the average position offset of all points in the horizontal monitoring unit, divide it by the average height change of all points in the vertical monitoring unit to obtain the first ratio of the horizontal and vertical displacements; when the first ratio is greater than the preset threshold, calculate the corrected position offset according to the position offset of the horizontal monitoring unit × preset threshold ÷ current actual ratio = corrected position offset; if the ratio is less than or equal to the preset threshold, retain the original position offset; finally, recombine the corrected position offset and the corresponding height change to generate the registered data.

[0103] The embodiment of the present invention breaks through the technical bottleneck of the non-linearity of soil mechanics response and realizes the precise coordinated control of shield thrust and runway deformation; solves the problem of distorted deformation prediction caused by soil anisotropy.

[0104] The present invention provides a specific embodiment. Step 103, extract the two-dimensional deformation monitoring data of the shield excavation surface and the bottom soil in the horizontal and vertical directions from the registered data, which specifically includes the following steps:

[0105] Step 301: Divide the horizontal propulsion direction displacement dataset corresponding to the shield excavation surface in the registered data into multiple continuous grid units, and count the maximum positive offset and the maximum negative offset of the horizontal direction coordinates of all data points in each grid unit relative to the original horizontal position to generate a horizontal direction deformation monitoring vector;

[0106] In this step, the horizontal advancement direction displacement data set refers to the set of displacement data of all monitoring points on the horizontal advancement direction (X-axis) of the shield machine after laser scanning and dynamic compensation processing. The original horizontal position refers to the original coordinate positions of each point on the excavation face contour calibrated by laser scanning before the shield machine starts to advance in the horizontal direction (X-axis). Different from the initial reference horizontal position in step 221, the original horizontal position is obtained based on the original construction data and is directly related to the initial state of the shield machine, and is used to calculate the real-time deformation amount of the excavation face contour. The initial reference horizontal position is obtained based on the compensated stage data and is related to the real-time construction progress, and is used to calculate the position offset of the compensated deformation trajectory point cloud during the subsequent advancement process. The maximum positive offset refers to the maximum displacement amount of the monitoring point in the forward direction of the shield machine (positive direction of the X-axis) relative to the initial reference horizontal position in the horizontal advancement direction. The maximum negative offset refers to the maximum displacement amount of the monitoring point in the backward direction of the shield machine (negative direction of the X-axis) relative to the initial reference horizontal position in the horizontal advancement direction. The horizontal direction deformation monitoring vector refers to a two-dimensional data vector composed of the maximum positive offset and the maximum negative offset of all monitoring points within the same grid cell.

[0107] In this step, with the axis of the shield machine as the reference direction, the horizontal advancement direction displacement data set in the registered data is divided into multiple consecutive grid cells according to half of the single-step advancement distance of the shield machine. The starting end of each grid cell is seamlessly connected to the end of the previous cell; within each grid cell, the horizontal coordinates of all data points are traversed, and the coordinate difference of each point relative to the original horizontal position (the horizontal coordinate of the center point of the same grid cell in the previous scanning cycle of the shield machine) is calculated. The maximum positive value in the difference is recorded as the maximum positive offset, and at the same time, the maximum negative value in the difference is recorded as the maximum negative offset; the maximum positive offset and the maximum negative offset of each grid cell are stored in the order of the grid cell numbers to generate a horizontal direction deformation monitoring vector.

[0108] Step 302: Divide the vertical direction displacement data set corresponding to the soil body at the bottom of the runway in the registered data into multiple monitoring areas, and count the maximum settlement amount and the maximum heave amount of the vertical coordinates of all data points in each monitoring area relative to the original height position to generate a vertical direction deformation monitoring vector;

[0109] In this step, the vertical displacement data set refers to the set of displacement data of all monitoring points of the soil mass at the bottom of the runway in the vertical direction (Z-axis) after laser scanning and dynamic compensation processing, including the real-time settlement or uplift amount of each point relative to the original height position. The monitoring area refers to the equally spaced vertical monitoring units divided along the extension direction of the runway (Y-axis), and the width of each unit is the same as the spacing of the transverse joints of the runway pavement, which is used to match the independent load-bearing sections of the runway structure. The original height position refers to the original elevation value of each monitoring point of the soil mass at the bottom of the runway determined by geological survey before shield construction in the vertical direction (Z-axis); different from the initial reference vertical position in step 222, the original height position is the absolute height reference in the actual physical space, obtained based on geographical survey data, and is used to calculate the settlement or uplift amount of the soil mass at the bottom of the runway, while the initial reference vertical position is the logical reference in the three-dimensional coordinate system, constructed based on the axis of the shield machine and serving for spatial data registration. The maximum settlement amount refers to the maximum value of the downward displacement of the monitoring point relative to the original height position in the vertical direction, reflecting the degree of settlement caused by soil compression or loss. The maximum uplift amount refers to the maximum value of the upward displacement of the monitoring point relative to the original height position in the vertical direction, reflecting the degree of uplift caused by soil expansion or groundwater pressure change. The vertical deformation monitoring vector refers to the two-dimensional data vector composed of the maximum settlement amount and the maximum uplift amount of all monitoring points in the same monitoring area, which is used to quantify the compression and expansion characteristics of the vertical deformation.

[0110] In this step, along the extension direction of the airport runway, with the spacing of the transverse joints of the rigid runway pavement as the reference, the vertical displacement data set is divided into multiple monitoring areas with equal width, and the width of each monitoring area is equal to the center distance between two adjacent transverse joints; within each monitoring area, traverse the vertical coordinates of all data points, and calculate the difference between the current vertical coordinate of each point and the original height position determined by the pre-construction survey. When the difference is positive, it represents the uplift amount, and when it is negative, it represents the settlement amount; select the largest positive value among all the differences of all points in each monitoring area as the maximum uplift amount of this area, and the smallest negative value as the maximum settlement amount of this area. Take the maximum uplift amount and the maximum settlement amount as the vertical deformation monitoring vector of this monitoring area, and this value contains the horizontal-vertical bidirectional displacement correlation characteristics.

[0111] Step 303: According to the spatial position coordinates of the grid cells and the monitoring areas, associate and bind the horizontal deformation monitoring vector and the vertical deformation monitoring vector at the same time stamp to generate the two-dimensional deformation monitoring data to be verified;

[0112] In this step, the two-dimensional deformation monitoring data to be verified refers to the preliminary associated data set formed by binding the horizontal deformation monitoring vector and the vertical deformation monitoring vector at the same time stamp according to the spatial position (the corresponding relationship between the grid cells and the monitoring areas), and it has not passed the physical rationality verification.

[0113] This step is based on the spatial coordinate ranges of the horizontal grid cells and the vertical monitoring regions. The central point coordinates of each grid cell are projected into the corresponding monitoring region coordinate system. If the central point is within the coordinate boundary of a certain monitoring region, the horizontal deformation monitoring vectors (maximum positive offset, maximum negative offset) of the grid cell are merged with the vertical deformation monitoring vectors (maximum settlement, maximum uplift) of this monitoring region to generate associated data entries containing the extreme values of horizontal displacement and vertical displacement. For each associated data entry, the maximum positive offset in the horizontal direction is multiplied by the absolute value of the maximum settlement in the vertical direction to obtain the horizontal-vertical displacement coupling coefficient. At the same time, the maximum negative offset in the horizontal direction is multiplied by the absolute value of the maximum uplift in the vertical direction to obtain the reverse displacement coupling coefficient. Based on the comparison result between the coupling coefficient and the preset threshold, the associated data entries that meet the conditions are screened out to form two-dimensional deformation monitoring data with two-way displacement association characteristics.

[0114] Step 304: Based on the mechanical properties of the rigid pavement structure under the airport runway, perform ratio verification on the positive offset of the horizontal deformation monitoring vector and the settlement of the vertical deformation monitoring vector in the two-dimensional deformation monitoring data to generate two-dimensional deformation monitoring data.

[0115] In this step, the mechanical properties of the rigid pavement structure refer to the flexural stiffness, load transfer efficiency, and deformation coordination ability of the concrete pavement under the airport runway under the action of loads. The positive offset refers to the amount of soil forward movement caused by the shield thrust. The settlement refers to the vertical settlement caused by soil compression or loss.

[0116] Based on the mechanical properties of the rigid pavement structure under the airport runway, this step sets a ratio threshold for the horizontal positive offset and the vertical settlement. For each monitoring unit in the two-dimensional deformation monitoring data, calculate the absolute value of the horizontal positive offset value of the monitoring unit divided by the vertical settlement value. If this absolute value is greater than the ratio threshold, it is determined that the deformation data of this monitoring unit does not conform to the co-deformation law of the rigid pavement and the soil body. Remove the horizontal positive offset and the corresponding vertical settlement of this monitoring unit from the two-dimensional deformation monitoring data, and retain the deformation data of the remaining monitoring units as the corrected two-dimensional deformation monitoring data.

[0117] The embodiment of the present invention realizes avoiding masking local abnormal deformations due to global data averaging; it can quickly identify the maximum deformation range and whether the current deformation exceeds the safety threshold.

[0118] The present invention provides a specific embodiment. In step 104, the pressure load response characteristics, the two-dimensional deformation monitoring data, and the surface settlement monitoring data of the shield tunneling under the airport runway are subjected to correlation analysis to obtain the deformation trend prediction result of the shield excavation face, which specifically includes the following steps:

[0119] Step 401: Divide the pressure load response characteristics into multiple settlement analysis segments, extract the peak characteristics and periodic characteristics of the pressure fluctuations of the cutterhead hydraulic cylinders in the settlement analysis segments, and generate a pressure load feature vector. The settlement analysis segments correspond to the grid cells in the two-dimensional deformation monitoring data;

[0120] In this step, the settlement analysis segment refers to a specific data interval divided according to the shield machine propulsion direction or time series. The peak characteristic refers to the difference between the maximum and minimum pressure values in the pressure fluctuation time series data of the cutterhead hydraulic cylinders within a certain settlement analysis segment, as well as the number of extreme points where the pressure exceeds a preset threshold. The periodic characteristic refers to the mean value of the time intervals between adjacent peaks in the pressure fluctuation time series data within a certain settlement analysis segment and its standard deviation. The pressure load feature vector refers to a multi-dimensional vector composed of peak characteristics and periodic characteristics.

[0121] In this step, the time series data corresponding to the pressure load response characteristics is divided into settlement analysis segments with the same length as the horizontal grid cell length according to the shield machine propulsion direction; within each settlement analysis segment, the difference between the maximum and minimum pressure values of the cutterhead hydraulic cylinders is statistically calculated as the peak characteristic, and at the same time, the average value of the time intervals between adjacent pressure wave peaks is calculated as the periodic characteristic; the peak characteristic is divided by the average pressure value of this settlement analysis segment to generate a normalized peak coefficient, and the periodic characteristic is multiplied by the shield machine propulsion speed to generate an equivalent spatial period length; the normalized peak coefficient and the equivalent spatial period length are arranged and combined in chronological order to generate a pressure load feature vector.

[0122] Step 402: Divide the surface settlement monitoring data of the shield tunneling under the airport runway into multiple settlement analysis segments, extract the mean value and change trend of the surface settlement rate, and generate a surface settlement feature vector. The settlement analysis segments correspond to the monitoring areas in the two-dimensional deformation monitoring data;

[0123] In this step, the surface settlement monitoring data of the shield tunneling under the airport runway is divided into multiple continuous settlement analysis segments according to the runway extension direction. The length of each settlement analysis segment is the same as the width of the monitoring area in the vertical direction of the two-dimensional deformation monitoring data, and each settlement analysis segment covers the runway surface range corresponding to a monitoring area; within each settlement analysis segment, the arithmetic mean value of all surface settlement monitoring values within a preset time window is calculated as the mean value, and the quotient of the absolute value of the difference between the mean values of adjacent two time windows and the time interval is calculated as the change trend; the two are combined into a surface settlement feature vector.

[0124] Step 403: Establish a spatio-temporal correspondence relationship among the pressure load eigenvector, the horizontal deformation monitoring vector and the vertical deformation monitoring vector in the two-dimensional deformation monitoring data, and the surface settlement eigenvector;

[0125] In this step, the spatio-temporal correspondence relationship refers to the matching and correlation rules among the pressure load eigenvector, the horizontal deformation monitoring vector, the vertical deformation monitoring vector, and the surface settlement eigenvector in terms of time stamps and spatial positions.

[0126] Based on the spatial coordinate mapping relationship between the real-time position of the shield machine and the surface monitoring area under the airport runway, this step first aligns the time stamps of the pressure load eigenvector with those of the two-dimensional deformation monitoring data. By intercepting the pressure data segment and the deformation data segment within the same shield machine propulsion distance interval, it ensures that the time windows of the two completely overlap. Then, spatial matching is carried out. For the pressure load eigenvector, according to the position in the shield machine propulsion direction, each settlement analysis segment is mapped to the center point coordinates of the corresponding grid cell. For the surface settlement eigenvector, according to the runway pavement number or geographical coordinates, each settlement analysis segment is mapped to the center point coordinates of the corresponding monitoring area. Finally, spatio-temporal association binding is performed. For the data segment within each time window, the characteristic data that satisfies the condition that the distance between the center coordinates of the grid cell and the projection coordinates of the cutter head hydraulic cylinder is less than the preset threshold and the distance between the center coordinates of the monitoring area and the projection coordinates of the runway surface monitoring point is less than the preset threshold is associated as the same spatio-temporal unit, thereby establishing the spatio-temporal correspondence relationship.

[0127] Step 404: Construct a joint analysis data set based on the spatio-temporal correspondence relationship;

[0128] In this step, the joint analysis data set refers to a structured data set formed by integrating the pressure load eigenvector, the two-dimensional deformation monitoring data, and the surface settlement eigenvector through the spatio-temporal correspondence relationship, including the time stamps, spatial coordinates, eigenvalue, and association labels of each analysis segment, and is used for multi-modal data collaborative analysis.

[0129] This step binds the settlement analysis segment data at the same timestamp with the corresponding grid cell data in the horizontal direction through the real-time position coordinates of the shield machine. Meanwhile, the settlement analysis segment data within the geographical coordinate range of the same runway section is associated with the corresponding vertical monitoring area data through coordinate range overlap determination, obtaining the bound pressure load characteristic vector, horizontal deformation monitoring vector, vertical deformation monitoring vector, and surface settlement characteristic vector. These vectors are arranged in chronological order, and the position coordinates of the shield machine at each time point are used as spatial indices. Multiply the peak feature in the pressure load characteristic vector by the maximum positive offset of the horizontal deformation monitoring vector, and multiply the mean value in the surface settlement characteristic vector by the maximum settlement of the vertical deformation monitoring vector to generate a combined analysis dataset.

[0130] Step 405: Generate a linkage status flag based on the combined analysis dataset to construct a spatial distribution map of the deformation trend of the shield excavation face based on the linkage status flag;

[0131] In this step, the linkage status flag refers to a classification label generated based on the correlation between different features in the combined analysis dataset. The spatial distribution map of the deformation trend refers to a graphical representation that uses a two-dimensional or three-dimensional spatial grid as the base, maps the linkage status flag to the corresponding spatial position through visualization technology, and superimposes the deformation expansion direction and intensity information.

[0132] This step calculates the product of the change amplitude of the pressure load characteristic vector and the horizontal deformation monitoring vector, and then divides it by the average of their respective maximum historical change amplitudes to generate the first correlation intensity coefficient; calculates the synchronization index of the change trends of the vertical deformation monitoring vector and the surface settlement characteristic vector, which is obtained by dividing the number of time points with the same change direction by the total number of time points; when the first correlation intensity coefficient is greater than the preset linkage threshold and the synchronization index is greater than the preset synchronization threshold, assign a linkage status flag to this analysis unit; arrange all the analysis units with linkage status flags according to their spatial positions on the shield excavation face, and perform weighted aggregation on the density and intensity of adjacent flags to generate a spatial distribution map.

[0133] Step 406: Generate a deformation trend prediction result of the shield excavation face based on the distribution characteristics and evolution laws of each region in the spatial distribution map of the deformation trend;

[0134] In this step, the distribution characteristics refer to the spatial position, area ratio, and geometric shape characteristics of different linkage status regions in the spatial distribution map of the deformation trend. The evolution law refers to the expansion direction, area change rate, and morphological evolution trend of each region in the spatial distribution map of the deformation trend over time.

[0135] This step calculates the area change rate by statistically calculating the ratio of the area difference in each region within consecutive time intervals to its initial area; determines the deformation gradient direction by identifying the maximum change direction of the horizontal deformation monitoring value and the vertical deformation monitoring value within the region; obtains the boundary movement speed by calculating the ratio of the displacement distance of the region boundary at adjacent timestamps to the time interval; multiplies the area change rate by a preset load influence coefficient, and superimposes the vector synthesis result of the boundary movement speed and the deformation gradient direction to generate a trend weight factor for each region; performs weighted superposition on the historical deformation data according to the trend weight factor to generate a predicted deformation increment value within the next three propulsion step distances; superimposes the predicted deformation increment value with the current deformation state, and performs boundary constraint based on the deformation resistance threshold of the rigid pavement of the airport runway. When the superimposed result exceeds the threshold, the increment value is reduced proportionally to generate a predicted deformation trend result.

[0136] The embodiment of the present invention provides a key basis for the analysis of the deformation mechanism under complex geological conditions; intuitively displays the deformation trend of each region of the shield excavation face, and can quickly identify abnormal regions.

[0137] The present invention provides a specific embodiment. Step 405: Generate a linkage state marker according to the combined analysis data set, and construct a spatial distribution map of the deformation trend of the shield excavation face based on the linkage state marker, which specifically includes the following steps:

[0138] Step 411: Traverse each analysis unit in the combined analysis data set, calculate the second ratio of the change amplitude of the peak feature in the pressure load feature vector to the change amplitude of the maximum positive offset of the horizontal direction deformation monitoring vector. If the second ratio is within the first preset interval, assign a first type of linkage marker to the corresponding analysis unit;

[0139] In this step, the analysis unit refers to the smallest data processing unit divided according to a preset rule in the combined analysis data set. The first preset interval refers to the threshold range set according to the mechanical relationship between the shield thrust and the soil shear strength. The first type of linkage marker refers to the marker given to the unit when the ratio of the pressure peak change amplitude to the horizontal deformation positive offset change amplitude in the analysis unit is within the first preset interval.

[0140] This step obtains the peak characteristic values of the pressure load eigenvector in the current analysis unit at two adjacent time points, subtracts the peak characteristic value of the previous time point from the peak characteristic value of the latter time point to obtain the change amplitude of the peak characteristic; obtains the maximum positive offset value of the horizontal deformation monitoring vector in the current analysis unit at two adjacent time points, subtracts the maximum positive offset value of the previous time point from the maximum positive offset value of the latter time point to obtain the change amplitude of the maximum positive offset; divides the change amplitude of the peak characteristic by the change amplitude of the maximum positive offset to obtain the second ratio of the current analysis unit; if the second ratio is greater than or equal to the lower limit of the first preset interval and less than or equal to the upper limit of the first preset interval, then assign a first type of linkage mark to this analysis unit.

[0141] Step 412: Calculate the third ratio of the maximum settlement in the vertical deformation monitoring vector to the mean value in the surface settlement eigenvector. If the third ratio is within the second preset interval, then assign a second type of linkage mark to the corresponding analysis unit;

[0142] In this step, the second preset interval refers to the threshold range set based on the soil compression modulus and the runway structure stiffness. The second type of linkage mark refers to the mark assigned to the unit when the ratio of the vertical settlement amount to the surface settlement mean value in the analysis unit is within the second preset interval.

[0143] In this step, within the monitoring area in the vertical direction corresponding to the analysis unit, traverse all the vertical deformation monitoring values, screen out all the negatively changing values and take the value with the largest absolute value as the maximum settlement; within the surface settlement analysis segment corresponding to the analysis unit, count the settlement data of all surface settlement monitoring points and calculate their arithmetic mean as the mean value; divide the value of the maximum settlement by the value of the mean to obtain the third ratio of the maximum settlement to the mean; judge whether this third ratio is within the second preset interval. If it is satisfied, then mark the current analysis unit with the second type of linkage mark.

[0144] Step 413: Mark the analysis units assigned with the first type of linkage mark and the second type of linkage mark as the linkage units of the shield thrust and the runway deformation, and map the geographical position coordinates of the linkage units to a preset two-dimensional space grid, and the preset two-dimensional space grid is generated based on the coordinates of the three-dimensional coordinate system;

[0145] In this step, the linkage unit of the shield thrust and the runway deformation refers to the analysis unit that simultaneously has the first type of linkage mark and the second type of linkage mark. The preset two-dimensional space grid refers to the plane grid generated based on the axis direction (X-axis) of the shield machine and the runway extension direction (Y-axis) in the three-dimensional coordinate system.

[0146] When the analysis unit satisfies both types of markings simultaneously, it is marked as a linkage unit for shield thrust and runway deformation; extract the geographical location coordinates of the linkage unit, discretize the X coordinate and Y coordinate according to the preset grid resolution, and finally complete the mapping. The specific process is as follows: divide the X coordinate value in the shield machine propulsion direction by the grid resolution, take the integer part to determine its grid index on the X axis for X grid division; divide the Y coordinate value in the runway extension direction by the grid resolution, take the integer part to determine its grid index on the Y axis for Y grid division; use the combination of (X index, Y index) of each linkage unit as its unique position identifier in the preset two-dimensional space grid, ignoring the vertical height coordinate Z for two-dimensional space grid mapping to generate a two-dimensional space grid.

[0147] Step 414: Cluster the linkage units according to the density distribution of the linkage units in the preset two-dimensional space grid to obtain a high-pressure load strongly related area, a deformation lag area, and a runway deformation conduction area;

[0148] In this step, the density distribution refers to the number or aggregation degree of linkage units in the two-dimensional space grid. The high-pressure load strongly related area refers to the area where linkage units are densely distributed. The deformation lag area refers to the area where linkage units are discretely distributed. The runway deformation conduction area refers to the area that is not marked as a linkage unit but the surface settlement continues to increase.

[0149] This step counts the number of linkage units existing in the eight grid units adjacent to each grid unit, divides the number by eight to obtain the density distribution value; for grid units with a density distribution value greater than or equal to the preset density threshold, if itself and its adjacent grid units are all linkage units, they are merged into a continuously distributed high-pressure load strongly related area; for linkage units with a density distribution value less than the preset density threshold and existing in isolation, they are marked as a discretely distributed deformation lag area; for grid units not marked as linkage units, calculate the sum of the increments of the change trend in the surface settlement eigenvector within three consecutive time stamps, and if the sum exceeds the preset trend threshold, they are marked as a runway deformation conduction area.

[0150] Step 415: Based on the spatial distribution relationship of the high-pressure load strongly related area, the deformation lag area, and the runway deformation conduction area, superimpose the expansion direction and the area change amount of each area to generate a spatial distribution map of the deformation trend of the shield excavation face;

[0151] In this step, the spatial distribution relationship refers to the relative position and coverage range of the high-pressure load strongly related area, the deformation lag area, and the runway deformation conduction area in the two-dimensional space grid. The expansion direction refers to the propagation direction of the deformation trend of a certain area. The area change amount refers to the difference in the coverage area of each area at different time points.

[0152] The process of generating the deformation trend spatial distribution map in this step is as follows: first, based on the coordinates of the center points of the high-pressure load-related areas, they are connected along the shield machine advancement direction to form a regional expansion baseline; the discrete distribution units of the deformation hysteresis area are grouped according to the vertical distance from the baseline to form a hysteresis area cluster; the coordinates of the boundary points where the outer contour of the runway deformation conduction area is aligned with the runway extension direction are extracted to define the deformation conduction range, thereby establishing the spatial distribution relationship between the high-pressure area, the hysteresis area and the conduction area; then, the ratio of the centroid displacement of the high-pressure load-related area to the time interval is calculated to generate an expansion direction vector, and the area difference is counted as the area change, and the change in the number of statistical units in the deformation hysteresis area cluster is calculated. The expansion direction of the cluster geometric center along the runway extension direction is measured and marked, and the mean radial movement distance of the boundary points at adjacent time points on the boundary line of the conduction area is calculated as the expansion direction vector and the area difference is obtained; finally, in the two-dimensional space grid, the high-pressure area is filled in red, the lag area cluster is filled in yellow, and the area within the boundary line of the conduction area is filled in blue. An arrow proportional to the modulus of the expansion vector is drawn at the centroid of the high-pressure area, and a circular mark proportional to the area change is marked at the center of the lag area. Contour lines and dotted arrows related to the absolute value of the area change are superimposed on the boundary of the conduction area. All elements are superimposed in layers according to the time series to generate a spatial distribution map of the deformation trend that integrates the spatial distribution relationship, expansion direction and area change.

[0153] The embodiments of the present invention enhance the sensitivity to the synchronous changes of the high pressure load on the excavation surface and the surface deformation; accurately locate the potential risk points of abnormal settlement of the runway structure, and effectively distinguish between normal deformation and abnormal deformation.

[0154] Figure 2 A schematic diagram of the structure of a shield excavation face deformation monitoring system for underpass an airport runway is provided in accordance with an embodiment of the present invention. Figure 2 As shown, the system includes:

[0155] A generating module 21 is used to generate a pressure load response characteristic associated with the propulsion direction of the shield machine based on the pressure fluctuation time series data of the cutter head hydraulic cylinder in the shield machine, combined with the dynamic load distribution data of the airport runway surface during the aircraft take-off and landing stage and the static load distribution data during the shutdown stage;

[0156] A registration module 22 is used to obtain the deformation trajectory of the shield excavation surface and the displacement change of the bottom soil under the airport runway, and perform point cloud registration processing on the deformation trajectory and the displacement change to obtain registered data;

[0157] An extraction module 23 is used to extract two-dimensional deformation monitoring data of the shield excavation surface and the bottom soil in the horizontal direction and the vertical direction from the registered data;

[0158] The analysis module 24 is used to correlate and analyze the pressure load response characteristics, the two-dimensional deformation monitoring data, and the surface settlement monitoring data of the underpass airport runway to obtain the deformation trend prediction result of the shield excavation face.

[0159] Figure 2 The shield excavation face deformation monitoring system for underpass airport runway can be performed Figure 1 The implementation principle and technical effect of the shield excavation face deformation monitoring method for underpassing an airport runway described in the illustrated embodiment will not be described in detail. The specific manner in which each module and unit performs operations in the shield excavation face deformation monitoring system for underpassing an airport runway in the above embodiment has been described in detail in the embodiment of the method, and will not be described in detail here.

[0160] In one possible design, Figure 2 The shield excavation face deformation monitoring system for underpass of an airport runway in the illustrated embodiment can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0161] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0162] The processing component 32 is used to: generate a pressure load response feature associated with the propulsion direction of the shield machine based on the pressure fluctuation time series data of the cutter head hydraulic cylinder in the shield machine, combined with the dynamic load distribution data of the airport runway surface during the aircraft take-off and landing stage and the static load distribution data during the shutdown stage; obtain the deformation trajectory of the shield excavation surface and the displacement change of the bottom soil under the airport runway, perform point cloud registration processing on the deformation trajectory and the displacement change to obtain the registered data; extract the two-dimensional deformation monitoring data of the shield excavation surface and the bottom soil in the horizontal and vertical directions from the registered data; correlate and analyze the pressure load response feature, the two-dimensional deformation monitoring data and the surface settlement monitoring data under the airport runway to obtain the deformation trend prediction result of the shield excavation surface.

[0163] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component may also be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to perform the above method.

[0164] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0165] Of course, the computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0166] The input / output interface provides an interface between the processing component and the peripheral interface module, which may be an output device, an input device, etc.

[0167] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0168] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0169] The embodiment of the present invention further provides a computer storage medium storing a computer program, which can achieve the above-mentioned Figure 1 The illustrated embodiment is a method for monitoring deformation of a shield excavation surface that is used when passing under an airport runway.

[0170] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0171] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0172] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0173] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring deformation of shield excavation surface for underpass of airport runway, characterized in that: Including: Based on the pressure fluctuation time series data of the cutter head hydraulic cylinders in a shield machine, combining the dynamic load distribution data of the airport runway surface during the aircraft takeoff and landing phases and the static load distribution data during the parking phase, generating pressure load response characteristics associated with the shield machine's propulsion direction; Obtaining the deformation trajectory of the shield excavation face and the displacement changes of the bottom soil mass under the airport runway, performing point cloud registration processing on the deformation trajectory and the displacement changes to obtain registered data; Extracting two-dimensional deformation monitoring data of the shield excavation face and the bottom soil mass in the horizontal and vertical directions from the registered data; Performing correlation analysis on the pressure load response characteristics, the two-dimensional deformation monitoring data, and the surface settlement monitoring data of the shield machine passing under the airport runway to obtain the deformation trend prediction result of the shield excavation face.

2. The method according to claim 1, wherein Obtaining the deformation trajectory of the shield excavation face and the displacement changes of the bottom soil mass under the airport runway, performing point cloud registration processing on the deformation trajectory and the displacement changes to obtain registered data, including: Generating deformation trajectory data based on the deformation trajectory of the shield excavation face scanned by a laser scanning device along a preset circular scanning path; Based on the bottom soil mass data corresponding to multiple different times scanned by the laser scanning device at a preset period, identifying the coordinate offset amount of the bottom soil mass within the preset scanning period, and generating displacement change data based on the coordinate offset amount; Adjusting the scanning frequency of the laser scanning device according to the shield machine's propulsion distance to generate synchronous deformation trajectory data and synchronous displacement change data; Taking the shield machine axis as a reference, constructing a three-dimensional coordinate system, and mapping the synchronous deformation trajectory data and synchronous displacement change data into the three-dimensional coordinate system to generate a deformation trajectory point cloud and a displacement change point cloud; Setting high-reflectivity marking points on the inner wall surface of the shield machine's cutting ring to perform dynamic compensation on the deformation trajectory point cloud and the displacement change point cloud, generating a compensated deformation trajectory point cloud and a compensated displacement change point cloud; Calculating the position offset amount of the compensated deformation trajectory point cloud in the horizontal propulsion direction of the shield machine and the height change amount of the compensated displacement change point cloud in the vertical direction to generate registered data.

3. The method according to claim 2, wherein Setting high-reflectivity marking points on the inner wall surface of the shield machine's cutting ring to perform dynamic compensation on the deformation trajectory point cloud and the displacement change point cloud, generating a compensated deformation trajectory point cloud and a compensated displacement change point cloud, including: Setting multiple high-reflectivity marking points on the inner wall surface of the shield machine's cutting ring, where the spatial coordinates of each high-reflectivity marking point are pre-calibrated in the three-dimensional coordinate system; Extracting the real-time coordinates of each high-reflectivity marking point from the deformation trajectory point cloud and the displacement change point cloud, and calculating the coordinate offset vector between the real-time coordinates and the calibrated spatial coordinates; Decomposing the coordinate offset vector into a longitudinal offset component and a transverse offset component to perform reverse translation correction on the point cloud coordinates in the deformation trajectory point cloud and the displacement change point cloud to obtain a corrected deformation trajectory point cloud and a corrected displacement change point cloud; According to the pitch angle data and yaw angle data of the shield machine attitude sensor, perform rotational compensation on the corrected deformed trajectory point cloud and the corrected displacement change point cloud to obtain the rotationally compensated deformed trajectory point cloud and the rotationally compensated displacement change point cloud; According to the height change amount of the bottom soil body in the rotationally compensated displacement change point cloud, perform reverse correction on the position offset amount of the rotationally compensated deformed trajectory point cloud to generate the compensated deformed trajectory point cloud. According to the position offset amount of the rotationally compensated deformed trajectory point cloud, perform reverse correction on the height change amount of the displacement change point cloud to generate the compensated displacement change point cloud.

4. The method according to claim 2, wherein Calculate the position offset amount of the compensated deformed trajectory point cloud in the horizontal propulsion direction of the shield machine and the height change amount of the compensated displacement change point cloud in the vertical direction to generate the registered data, including: Along the horizontal propulsion direction of the shield machine, divide the compensated deformed trajectory point cloud into multiple horizontal monitoring units, and count the average offset amount of the horizontal axis coordinates of all points in the compensated deformed trajectory point cloud in the horizontal monitoring unit relative to the initial reference horizontal position to generate the position offset amount in the horizontal propulsion direction; Along the vertical propulsion direction of the shield machine, divide the compensated displacement change point cloud into multiple vertical monitoring units, and count the average height change amount of the vertical axis coordinates of all points in the compensated displacement change point cloud in the vertical monitoring unit relative to the initial reference vertical position to generate the height change amount in the vertical direction; According to the spatial position coordinates of the horizontal monitoring unit and the vertical monitoring unit, map the corresponding position offset amount and height change amount at the same timestamp to generate a two-way displacement dataset; Calculate the first ratio of the position offset amount of each horizontal monitoring unit in the two-way displacement dataset and the height change amount of the corresponding vertical monitoring unit. When the first ratio exceeds the preset threshold, correct the position offset amount to generate the registered data.

5. The method according to claim 1, wherein Extract the two-dimensional deformation monitoring data of the shield excavation face and the bottom soil body in the horizontal and vertical directions from the registered data, including: Divide the displacement dataset in the horizontal propulsion direction corresponding to the shield excavation face in the registered data into multiple continuous grid units, and count the maximum positive offset amount and the maximum negative offset amount of the horizontal direction coordinates of all data points in each grid unit relative to the original horizontal position to generate the deformation monitoring vector in the horizontal direction; Divide the displacement dataset in the vertical direction corresponding to the runway bottom soil body in the registered data into multiple monitoring areas, and count the maximum settlement amount and the maximum uplift amount of the vertical direction coordinates of all data points in each monitoring area relative to the original height position to generate the deformation monitoring vector in the vertical direction; According to the spatial position coordinates of the grid unit and the monitoring area, associate and bind the deformation monitoring vector in the horizontal direction and the deformation monitoring vector in the vertical direction at the same timestamp to generate the two-dimensional deformation monitoring data to be verified; Based on the mechanical characteristics of the rigid pavement structure under the airport runway, the proportional verification is carried out on the forward offset of the horizontal deformation monitoring vector and the settlement of the vertical deformation monitoring vector in the two-dimensional deformation monitoring data, and the two-dimensional deformation monitoring data is generated.

6. The method according to claim 1, characterized in that, The pressure load response characteristics, the two-dimensional deformation monitoring data and the surface settlement monitoring data under the airport runway are analyzed in association to obtain the prediction result of the deformation trend of the shield excavation face, including: The pressure load response characteristics are divided into multiple settlement analysis segments, and the peak characteristics and periodic characteristics of the pressure fluctuation of the cutter head hydraulic cylinder in the settlement analysis segments are extracted to generate a pressure load characteristic vector, and the settlement analysis segments correspond to the grid units in the two-dimensional deformation monitoring data; The surface settlement monitoring data under the airport runway is divided into multiple settlement analysis segments, and the mean value and change trend of the surface settlement rate are extracted to generate a surface settlement characteristic vector, and the settlement analysis segments correspond to the monitoring areas in the two-dimensional deformation monitoring data; The spatio-temporal correspondence relationships are established among the pressure load characteristic vector, the horizontal deformation monitoring vector and the vertical deformation monitoring vector in the two-dimensional deformation monitoring data, and the surface settlement characteristic vector; Based on the spatio-temporal correspondence relationships, a joint analysis data set is constructed; According to the joint analysis data set, a linkage state mark is generated to construct a spatial distribution map of the deformation trend of the shield excavation face based on the linkage state mark; Based on the distribution characteristics and evolution laws of each region in the spatial distribution map of the deformation trend, the prediction result of the deformation trend of the shield excavation face is generated.

7. The method according to claim 6, wherein According to the joint analysis data set, a linkage state mark is generated to construct a spatial distribution map of the deformation trend of the shield excavation face, including: Traverse each analysis unit in the joint analysis data set, calculate the second ratio of the change amplitude of the peak characteristics in the pressure load characteristic vector to the change amplitude of the maximum forward offset of the horizontal deformation monitoring vector. If the second ratio is within the first preset interval, the first type of linkage mark is assigned to the corresponding analysis unit; Calculate the third ratio of the maximum settlement in the vertical deformation monitoring vector to the mean value in the surface settlement characteristic vector. If the third ratio is within the second preset interval, the second type of linkage mark is assigned to the corresponding analysis unit; The analysis units assigned with the first type of linkage mark and the second type of linkage mark are marked as the linkage units of the shield thrust and runway deformation, and the geographical position coordinates of the linkage units are mapped to a preset two-dimensional space grid, and the preset two-dimensional space grid is generated based on the coordinates of the three-dimensional coordinate system; According to the density distribution of the linkage units in the preset two-dimensional space grid, the linkage units are clustered to obtain a high-pressure load strongly correlated area, a deformation lag area and a runway deformation conduction area; Based on the spatial distribution relationships of the high-pressure load strongly correlated area, the deformation lag area and the runway deformation conduction area, the expansion directions and area change amounts of each area are superimposed to generate a spatial distribution map of the deformation trend of the shield excavation face.

8. A shield excavation face deformation monitoring system for underpass airport runway, characterized in that: Including: A generation module, configured to generate pressure load response characteristics associated with the shield machine propulsion direction based on the pressure fluctuation time series data of the cutter head hydraulic cylinders in the shield machine, in combination with the dynamic load distribution data on the airport runway surface during the aircraft takeoff and landing phases and the static load distribution data during the parking phase; A registration module, configured to obtain the deformation trajectory of the shield excavation face and the displacement change of the bottom soil mass under the airport runway, and perform point cloud registration processing on the deformation trajectory and the displacement change to obtain the registered data; An extraction module, configured to extract two-dimensional deformation monitoring data of the shield excavation face and the bottom soil mass in the horizontal and vertical directions from the registered data; An analysis module, configured to perform correlation analysis on the pressure load response characteristics, the two-dimensional deformation monitoring data, and the surface settlement monitoring data of the airport runway undercrossing to obtain a prediction result of the deformation trend of the shield excavation face.

9. A computing device, characterized in that, It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for monitoring the deformation of the shield excavation face undercrossing the airport runway according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that, A computer program is stored, and when the computer program is executed by a computer, it implements a method for monitoring the deformation of the shield excavation face undercrossing the airport runway according to any one of claims 1 to 7.

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