Tunnel settlement data acquisition method and system based on laser ranging

Abstract

The invention relates to the technical field of tunnel settlement data acquisition and analysis, in particular to a tunnel settlement data acquisition method and system based on laser ranging, and the method comprises the following steps: S1, equipment is a monitoring device comprising a holder and two laser ranging sensors with a fixed included angle, the first sensor horizontally points to the side wall of a tunnel, and the second sensor horizontally points to the side wall of the tunnel; the second sensor points to the tunnel vault at an included angle theta; s2, point distribution and base point selection, wherein monitoring points are distributed in the tunnel according to a preset rule, and a zero reference point is arranged in a stable area of a tunnel portal; in the scheme, through integration of the double laser sensors and automatic holder scanning, high-density and high-precision automatic continuous data acquisition of the tunnel section is realized, and the defects of low efficiency and insufficient coverage of a traditional method are overcome; meanwhile, by means of intelligent coordinate transformation, a deformation calculation model and a multi-stage early warning mechanism, real-time calculation, trend prediction and graded automatic alarm of settlement and convergence parameters are achieved.

Description

Technical Field

[0001] This invention relates to the field of tunnel settlement data acquisition and analysis technology, and in particular to a method and system for acquiring tunnel settlement data based on laser ranging. Background Technology

[0002] Tunnel settlement is one of the core aspects of safety monitoring during the construction and operation of tunnel projects. Timely and accurate monitoring is crucial for preventing structural instability and ensuring construction and operational safety.

[0003] Traditional methods for collecting tunnel settlement data mainly rely on manual total station measurements, leveling, or fixed single-point sensor monitoring. These methods are inefficient, risky, and dependent on manual on-site operations. Data collection is discrete and time-consuming, making it difficult to achieve high-frequency continuous monitoring. Furthermore, they are unsafe to operate in the harsh environment inside tunnels. In addition, the spatial coverage density of tunnels is limited, and traditional methods can usually only obtain sparse point data, making it difficult to fully capture the continuous deformation characteristics of the entire tunnel cross section and easily missing local abrupt change areas.

[0004] To address this, this invention proposes a method and system for acquiring tunnel settlement data based on laser ranging. By integrating dual laser sensors and an automated gimbal scanning system, it achieves high-density, high-precision, automated continuous data acquisition of tunnel cross-sections, overcoming the shortcomings of traditional methods such as low efficiency and insufficient coverage. Simultaneously, by leveraging intelligent coordinate transformation, deformation calculation models, and multi-level early warning mechanisms, it realizes real-time calculation, trend prediction, and graded automatic alarms for settlement and convergence parameters, significantly improving the real-time performance, continuity, and timeliness and scientific rigor of risk warnings. This provides a complete technical solution for the dynamic perception and precise control of tunnel engineering safety status. Summary of the Invention

[0005] The technical problem to be solved: relying on manual on-site operation, data collection is scattered and has a long cycle, making it difficult to achieve high-frequency continuous monitoring.

[0006] To address the shortcomings of existing technologies, this invention provides a method and system for acquiring tunnel settlement data based on laser ranging, thereby solving the technical problems mentioned in the background section.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A method and system for acquiring tunnel settlement data based on laser ranging, the method comprising the following steps:

[0009] S1. The equipment consists of a monitoring device including a pan-tilt unit and two laser rangefinders with a fixed angle, wherein the first sensor points horizontally toward the tunnel sidewall and the second sensor points at the tunnel arch at an angle θ.

[0010] S2. Layout and Base Point Selection: Layout monitoring points in the tunnel according to predetermined rules, and set a zero reference point in the stable area at the tunnel entrance. Correlate and calibrate the positions of all monitoring devices through a continuous laser reference chain.

[0011] S3. Data Acquisition: Control the pan-tilt unit of the monitoring device to rotate at a preset step angle, drive the two laser sensors to synchronously acquire the distance values ​​between the tunnel sidewall and the arch, and synchronously record the pan-tilt unit rotation angle, time information and environmental sensor data.

[0012] S4. Data Processing: Convert the collected polar coordinate distance measurement data into standard Cartesian coordinate data of the tunnel cross section, and calculate the settlement and convergence of the tunnel by comparing the current cross section data with the initial reference data.

[0013] S5. Trend Analysis and Early Warning: Based on the calculated historical deformation data, a trend prediction model is established to calculate the deformation rate and acceleration in real time, and triggers corresponding levels of early warning and response processes according to preset multi-level thresholds.

[0014] In one possible implementation, step S2 specifically includes:

[0015] The spacing of longitudinal monitoring points is dynamically determined based on the tunnel's surrounding rock grade, maximum net width, and curvature. Based on the geological risk level, monitoring devices are installed symmetrically on one or both sides of the tunnel, and the number of monitoring points is increased in key areas.

[0016] A continuous laser reference chain is constructed, consisting of a zero-reference laser emitting station and photoelectric receiving units of each monitoring device, for calibrating and monitoring the displacement of the device itself.

[0017] In one possible implementation, step S3 specifically includes:

[0018] It supports three acquisition modes: timed active reporting, host computer polling, and triggering. The acquisition cycle and triggering conditions can be dynamically configured according to monitoring needs. The pan-tilt unit is controlled to scan according to the preset step angle and rotation range to ensure that the laser covers key measuring points of the tunnel section. Environmental parameters and device status are recorded simultaneously during the acquisition process.

[0019] During data acquisition, the pan-tilt unit performs round-trip scanning and ensures consistency through data comparison, while eliminating abnormal ranging values ​​in real time. It integrates temperature, humidity, and vibration sensors for environmental compensation and data acquisition interruption control, and periodically performs automatic device position calibration through a reference chain.

[0020] In one possible implementation, the data processing in step S4 includes coordinate transformation:

[0021] Based on the installation coordinates of the monitoring device, the rotation angle of the pan-tilt unit, the fixed angle of the laser, and the distance measurement value, the polar coordinate data is converted into three-dimensional coordinates in the tunnel space; the installation deviation is corrected by using the reference chain offset and the inclination measurement value; the oblique section data collected by the pan-tilt unit at different rotation angles is uniformly mapped to the standard tunnel cross section through geometric projection.

[0022] In one possible implementation, the data processing in step S4 includes deformation parameter calculation:

[0023] By comparing the current cross-sectional profile data with the initial zero-state data, the tunnel deformation is calculated: the settlement is obtained by calculating the difference in the vertical coordinates of the measuring point at the top of the tunnel; the convergence is obtained by calculating the difference in the horizontal distance between the corresponding measuring points on both sides of the tunnel.

[0024] In one possible implementation, the data processing step S4 further includes the integration and calculation of cross-sectional deformation values:

[0025] Based on the deformation of each measuring point obtained from the solution, the average settlement and average convergence of a single monitoring section are calculated to form parameters characterizing the overall deformation state of the section.

[0026] In one possible implementation, step S5 specifically includes:

[0027] Based on historical deformation data, a deformation trend model is constructed by integrating multiple prediction algorithms, and real-time deformation rate and acceleration are extracted;

[0028] A dual warning threshold based on absolute and relative values ​​of settlement, convergence, deformation rate, and acceleration is established to form a multi-level warning standard of yellow, orange, and red.

[0029] Based on the comparison results between real-time data and thresholds, the system automatically triggers warnings of the corresponding level and executes response actions including shortening the data collection cycle, multi-level alarm notifications, and activating emergency monitoring.

[0030] In one possible implementation, a tunnel settlement data acquisition system based on laser ranging, performing the method as described in any one of claims 1 to 7, includes a device control unit, a data acquisition unit, and a data analysis unit.

[0031] The equipment control unit is used to perform the initialization of the monitoring device, gimbal rotation control, laser sensor start / stop, reference chain construction and calibration, and the scheduling and management of acquisition modes;

[0032] The data acquisition unit is used to receive and record the raw data from the laser rangefinder, gimbal encoder, and environmental sensor, and to perform preliminary filtering and preprocessing.

[0033] The data analysis unit is used to perform coordinate transformation, deformation parameter calculation, trend model construction, early warning logic judgment, and output deformation results and early warning information.

[0034] Beneficial effects compared to existing technologies:

[0035] 1. This solution achieves high-density, high-precision automated acquisition of tunnel settlement data by integrating dual laser sensors and an automated pan-tilt unit. The method uses two laser rangefinders with a fixed angle, combined with a pan-tilt unit whose rotation angle can be precisely controlled, enabling synchronous and continuous multi-point measurements of the tunnel sidewalls and arch, covering key areas of the entire cross-section. Through three acquisition modes—timed, polling, and triggered—the acquisition frequency and range can be flexibly adjusted according to engineering needs. Real-time error correction and abnormal interruption handling are performed using temperature, humidity, and vibration sensors. This approach not only significantly improves data acquisition efficiency and spatial coverage density but also effectively reduces random errors and system biases through multiple measurements, real-time filtering, and benchmark chain calibration, ensuring the reliability and integrity of the original data and providing a precise and stable data foundation for subsequent deformation analysis.

[0036] 2. In this scheme, dynamic monitoring, trend prediction, and graded response of tunnel deformation are achieved through an intelligent data processing model and a multi-level early warning mechanism. The system uses geometric correction, coordinate transformation, and oblique section projection algorithms to convert polar coordinate measurement data into standard cross-sectional coordinates and automatically calculates settlement and convergence. Based on historical data, a trend prediction model integrating multiple algorithms is constructed, which can calculate deformation rate and acceleration in real time and identify gradual and abrupt deformation. By setting dual thresholds combining absolute and relative thresholds, the system achieves three-level early warning: yellow, orange, and red. The system automatically adjusts the data acquisition strategy and triggers alarm and notification processes at different levels according to the early warning level. This mechanism not only improves the real-time perception and risk assessment capabilities of tunnel safety status but also enables timely emergency response when deformation is abnormal, providing scientific and systematic decision support for the daily maintenance and handling of sudden risks in tunnel engineering. Attached Figure Description

[0037] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0038] Figure 1 This is a schematic diagram illustrating the working principle of the active device of the present invention;

[0039] Figure 2 This is a schematic diagram of the cross-sectional measurement of the present invention;

[0040] Figure 3 This is a schematic diagram of a single-sided wiring of the present invention;

[0041] Figure 4 This is a schematic diagram of the bilateral wiring in the key monitoring area of ​​the present invention;

[0042] Figure 5 This is a schematic diagram illustrating the principle of active device monitoring tunnel deformation according to the present invention;

[0043] Figure 6 This is a flowchart of the method steps of the present invention;

[0044] Figure 7 This is a schematic diagram of the system framework of the present invention. Detailed Implementation

[0045] Preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, the present invention can also be implemented in various different forms, and therefore the present invention is not limited to the embodiments described below.

[0046] The technical solution in this application embodiment is to solve the problems mentioned in the background art, and the overall idea is as follows:

[0047] Example:

[0048] Please refer to Figures 1 to 6 As shown in the figure, this embodiment introduces a method for acquiring tunnel settlement data based on laser ranging, including the following steps:

[0049] S1. Equipment Preparation

[0050] like Figure 1 As shown, the active device includes a gimbal for adjusting the rotation direction of the top laser sensor group and two laser rangefinders.

[0051] The laser sensor selected for this module features USB power supply and an onboard 500mA self-resetting fuse or fusible resistor to protect the computer motherboard from accidental burnout. When programming the chip, it can use the target system's own power supply or draw power from the USB port using a programmer. It supports USB 1.1 or USB 2.0 communication and fully supports operating systems such as WIN98, WINME, WIN2000, WINXP, VISTA, and WIN7. Using imported original chips, it features high-speed and stable programming. Its theoretical maximum measurement distance is 80 meters. The laser sensor mounted on the pan-tilt unit has the advantages of multi-point measurement and a wide measurement range, which greatly improves hardware utilization.

[0052] The two laser rangefinders used in this module form a fixed angle θ between them. That is, the light beam S1 from laser sensor 1 hits the tunnel sidewall horizontally, and the light beam S2 from laser sensor 2 hits the tunnel top surface. The fixed angle θ formed by the angle between the light beams S1 and S2 is set according to different tunnels. When measuring the tunnel deformation value, the active device is fixed to the tunnel sidewall, and the value of θ is determined through field testing.

[0053] S2. Selection of Layout Points and Base Points

[0054] S2.1 Site Layout Planning and Precise Implementation: The site layout plan combines tunnel geological conditions, cross-sectional dimensions, monitoring level, and equipment coverage to achieve an optimal balance between monitoring density and economy. Key technical details are as follows:

[0055] Longitudinal spacing: The coverage area of ​​a single unit is 50m-100m. The spacing needs to be dynamically adjusted according to the surrounding rock grade, tunnel width, and curvature. The specific calculation formula is as follows: in, The vertical spacing between the dots; The surrounding rock coefficient is specifically divided into five levels, including Level I surrounding rock. Level II Level III Level IV Level V ; This is the maximum clear width of the tunnel; This is the tunnel curvature correction factor for straight tunnels. curve radius hour , hour , hour ;

[0056] Example: For a straight tunnel in Class III surrounding rock with a maximum clear width of 12m, what is the spacing between the observation points? Rounded to 50m, it falls within the range of 50m-100m; if it is a curved tunnel with Class V surrounding rock, its ,but Rounded to 40m, it needs to be encrypted to below the lower limit of the coverage area;

[0057] Horizontal layout, such as Figure 3 and Figure 4 As shown:

[0058] Single-sided placement: Suitable for conventional monitoring sections, adaptable to surrounding rock grades I-III, with no adverse geological conditions. The device is installed at the junction of the tunnel wall and the arch, i.e., 30cm above the arch waist. Installation height: ,in To ensure the tunnel sidewall height, laser 1 is projected horizontally onto the opposite sidewall, and laser 2 is projected onto the center of the arch.

[0059] Dual-sided deployment: Suitable for key monitoring sections, adaptable to surrounding rock grades IV-V, water-rich sections, and fault fracture zones. The devices on both sides are symmetrically installed with a symmetry deviation of ≤0.5m, forming a closed measurement loop, increasing the monitoring density by 1 time, and the data redundancy is ≥2. Errors can be reduced through cross-validation of dual-sided data.

[0060] Densification in key areas: In critical areas such as tunnel entrances, lining joints, and sections of abrupt changes in surrounding rock, the spacing between monitoring points is reduced by 30%-50%. For example, the conventional spacing is 50m, but after densification, it is reduced to 25m-35m to ensure the capture of localized concentrated deformation.

[0061] S2.2, Reference Chain Construction and Calibration: Construct a zero reference point and a continuous photoelectric reference chain for the monitoring device to verify the device's own positional stability, as detailed below:

[0062] Located in a stable area at the tunnel entrance, specifically ≥50m from the entrance, with surrounding rock grade ≥I and no settlement or deformation, a 50cm×50cm×30cm concrete-cast fixed platform is used, with a steel plate ≥10mm thick pre-embedded inside to ensure long-term stability of the reference point. The zero-reference point laser transmitter is fixed to the pre-embedded steel plate, and the transmission direction is calibrated using a high-precision theodolite to ensure that the laser beam is parallel to the tunnel axis with a parallelism error ≤0.01°. The height of the transmitter is consistent with the height of the photoelectric receiving unit of the monitoring device to avoid vertical deviation.

[0063] Starting with the first monitoring device closest to the benchmark point, adjust the position of its photoelectric receiving unit to ensure accurate reception of the benchmark laser signal and record the offset of the receiving unit. Adjust subsequent devices sequentially to ensure that the laser transmitter of each device is aligned with the receiving unit of the previous device, forming a continuous laser link with a total link deviation ≤ ±0.1mm / 100m. For long tunnels ≥1000m, set an auxiliary benchmark point at the other end of the tunnel to construct a closed benchmark chain and verify the link closure error, which should be ≤ ±0.3mm / km. If the error exceeds the range, readjust the position of the intermediate devices.

[0064] After the baseline chain is established, the system performs the first all-round scan, driving the gimbal to rotate at a step angle of 0.5°, collecting the coordinate data of the entire tunnel cross section, and recording it as the initial zero-state data, including the three-dimensional coordinates (X0, Y0, Z0) of each measuring point, the laser ranging value S0, the gimbal angle θ0, etc., which are stored in the local database of the device and the host computer database as the benchmark for subsequent deformation comparison.

[0065] S3, Data Acquisition

[0066] S3.1 Acquisition Mode and Parameter Configuration

[0067] The data collection modes are divided into three types: timed active reporting mode, host computer polling mode, and trigger-based data collection mode.

[0068] The timed active reporting mode is suitable for routine monitoring. The collection cycle can be set remotely via a host computer, with a range of 10 minutes to 24 hours and a default cycle of 30 minutes. In high-risk tunnels or during construction, the cycle can be shortened to 5-10 minutes, and during operation, it can be extended to 1-2 hours. The device automatically starts collecting data according to the set cycle and actively reports the data after collection is completed, with a reporting delay of ≤3 seconds.

[0069] The host computer polling mode is suitable for emergency monitoring or data supplementation. The host computer sends acquisition instructions to each device in address order, with a polling period of ≤30s (20 devices). The device starts acquisition immediately after receiving the instruction, with a response time of ≤500ms.

[0070] When the device detects that the offset of the laser reference chain exceeds the threshold or the vibration sensor is triggered, i.e., the trigger-type acquisition mode, it automatically starts high-frequency acquisition with a cycle of 1 minute, and resumes normal mode after 30 minutes of continuous acquisition to ensure the capture of sudden deformation.

[0071] To adapt to tunnel cross-sectional dimensions, geological conditions, and other working conditions, and to clarify core parameters such as gimbal step angle and laser emission frequency, it is necessary to reduce random and systematic errors, ensure complete coverage of key measuring points, and guarantee that the collected data is accurate, stable, and reliable. This will provide a precise foundation for subsequent data processing, deformation calculation, and early warning analysis. Therefore, it is necessary to calibrate key acquisition parameters, specifically including:

[0072] Gimbal rotation parameters: The step angle can be adjusted within the range of 0.1°-1°. The higher the monitoring accuracy requirement, the smaller the step angle. For example, the step angle is set to 0.1° for sub-millimeter accuracy and 0.5° for conventional accuracy. The rotation range is adjusted according to the tunnel cross-section. The rotation range is ±60° when the point is set on one side and ±45° when the point is set on both sides, to ensure that the laser covers the key measuring points of the entire cross-section.

[0073] Laser ranging parameters: laser emission frequency ≥10Hz, ranging at each measuring point ≥3 times in a single acquisition, and the average value is taken as the effective ranging value to reduce random errors; the ranging range is set according to the tunnel width, the range is set to 20m for conventional tunnels with a width ≤15m, and the range is set to 40m for wide-section tunnels with a width of 15-30m. To ensure measurement accuracy, the ranging value must be within 30%-80% of the effective range.

[0074] S3.2 Acquisition Process and Accuracy Control

[0075] After the device is powered on or the data acquisition cycle is started, initialization is performed first. The pan-tilt unit is reset to the mechanical zero point. Then, the pan-tilt unit rotates clockwise at a preset step angle. For each rotation angle, laser 1 and laser 2 simultaneously emit laser pulses to acquire the ranging values ​​S1 (side wall) and S2 (arch). At the same time, the current angle φ of the pan-tilt unit, the acquisition timestamp, and the reference laser offset Δ are recorded. After rotating to the maximum angle, the device rotates counterclockwise to collect data. The data acquired during the return trip is compared with the data acquired during the forward trip. If the deviation is ≤ ±0.2mm, the average value is taken. If the deviation exceeds the average value, the data at that measurement point is reacquired.

[0076] During the data acquisition process, preliminary preprocessing is performed in real time to remove abnormal values ​​such as distance values ​​exceeding the measurement range and differences ≥2mm between the measured and adjacent measurement points. When the proportion of abnormal values ​​exceeds 5%, the data acquisition for that section is restarted. After the data acquisition for each section is completed, a data acquisition status report is generated and uploaded synchronously with the data.

[0077] To ensure data acquisition accuracy, temperature and humidity sensors are used to collect data and correct ranging errors. Data acquisition is paused when the vibration sensor detects excessive vibration and restarted after stabilization. In addition, the reference is automatically calibrated every 10 cross-sections to correct for device displacement or loosening deviations.

[0078] S4, Data Processing

[0079] S4.1 Geometric correction and coordinate transformation converts the distance measurement data in polar coordinates into Cartesian coordinates of the tunnel cross-section, laying the foundation for deformation calculation:

[0080] Polar coordinate to Cartesian coordinate transformation: such as Figure 5 As shown, given the device's installation coordinates (X0, Y0, Z0), gimbal rotation angle φ, laser emission angle θ, and laser ranging values ​​S1 and S2, the conversion formula is as follows:

[0081] Coordinates of laser measuring point 1: ;

[0082] Coordinates of laser measuring point 2: ;

[0083] Considering minor deviations during device installation, namely horizontal deviations Vertical deviation Introduce a correction factor:

[0084] Horizontal deviation correction: ,in Calculated from the offset of the photoelectric reference chain: ( This is the horizontal offset. (for device spacing).

[0085] Vertical deviation correction: ,in The corrected Z-coordinate of laser measuring point 2, obtained from the inclinometer measurement, is as follows: .

[0086] For non-vertical cross-sectional data generated by gimbal rotation, a projection mapping model is used to convert it into standard cross-sectional data:

[0087] Geometric relationship between inclined section and standard cross section: when the gimbal rotates by an angle At this time, the laser measures the data of the inclined section, which needs to be projected onto a standard cross-section. Let the angle between the inclined section and the standard cross-section be θ. The coordinates of the measuring points on the inclined section are ( , , The standard cross-sectional mileage, i.e., the installation mileage of the device, is given by the projection formula:

[0088] Horizontal projection (XY plane): ;

[0089] Vertical projection (Z-axis): (The vertical direction is not affected by the inclined section);

[0090] Mileage correction: Mileage of the standard cross section corresponding to the inclined section This ensures that the data belongs to the correct mileage section.

[0091] The corrected coordinate data under different rotation angles are grouped according to the standard cross-sectional mileage, with each group corresponding to a mileage section. Within the same section, the data is further classified according to the location of the measuring points, namely the crown, waist, and sidewalls, to form standardized cross-sectional profile data. Where: i is the cross-section number, and j is the measuring point number.

[0092] S4.2 Deformation parameter calculation: By comparing the current cross-sectional profile data with the initial reference data, the settlement and convergence are calculated. The core calculations are as follows:

[0093] Settlement calculation: Settlement is defined as the change in coordinates of the crown measuring point in the vertical direction (Z-axis). First, the Z-coordinates of the crown measuring points are extracted from the initial reference data. (j is the arch crown measuring point number); then, extract the Z coordinate of the corresponding arch crown measuring point from the current measurement data. ; Calculate settlement (like This indicates that the vaulted ceiling has sunk. (Indicates the crown rise); and the average cross-sectional settlement. Where m is the number of measuring points on the arch crown, the default is 3 points: the center of the arch crown, the left arch crown, and the right arch crown); the initial Z-coordinate of the arch crown center is determined by a certain cross-section. For example, the current measurement of the Z coordinate When, then the settlement amount .

[0094] Convergence calculation: Convergence is defined as the change in relative distance between corresponding measuring points on both sides of the tunnel in the horizontal direction (XY plane). First, the coordinates of the measuring points on the left side wall are extracted from the initial reference data. Coordinates of the measuring points corresponding to the right side wall Calculate the initial relative distance: Then extract the coordinates of the corresponding measuring points from the current measurement data. and Calculate the current relative distance: Then the convergence quantity (like This indicates tunnel convergence. (Indicating tunnel expansion), then the average convergence of the cross-section is: (k represents the number of sidewall measuring points, with a default of 3 pairs at the arch waist, middle of the sidewall, and lower part of the sidewall). Taking the initial coordinates of the left arch waist measuring point (2.500m, 0m) and the right arch waist measuring point (9.500m, 0m) of a certain section as an example, the initial distance... Currently measuring the left arch waist (2.499m, 0m) and right arch waist (9.500m, 0m), current distance. Then the convergence quantity .

[0095] S5. Trend Analysis and Early Warning

[0096] S5.1, Core Technology of Trend Analysis

[0097] Multi-algorithm fusion modeling: Based on historical monitoring data (at least 30 days of continuous data), linear regression, exponential smoothing, and grey prediction model (GM(1,1)) are integrated to construct a three-dimensional trend model. ( Let 'a' be the deformation value at time t, 'b' be the initial deformation base, 'c' be the instantaneous velocity, 'd' be the acceleration, and 'd' be the trend decay coefficient. The model parameters are iteratively optimized using the least squares method to determine the goodness of fit. ;

[0098] Key parameter extraction: Real-time calculation of deformation rate (Unit: mm / d) and acceleration (Unit: mm / d²), set both velocity and acceleration thresholds as criteria. If the velocity exceeds the threshold and the acceleration is positive, trigger an enhanced warning.

[0099] Sliding window analysis: A 7-day sliding window is used to smooth the data, calculate the mean, standard deviation and maximum fluctuation of deformation within the window, identify abrupt deformation (i.e., daily deformation exceeding 3 times the standard deviation of the window mean) and gradual deformation, and match different early warning strategies accordingly.

[0100] Spatial correlation analysis: Correlate the deformation trends of adjacent monitoring sections within a 50m range before and after. If multiple sections simultaneously show accelerated deformation or exceed the threshold, it is judged as a regional deformation risk, and the warning level is upgraded.

[0101] S5.2, Multi-level Early Warning Mechanism

[0102] (a) Setting the early warning threshold

[0103] Threshold calibration basis: Combining the tunnel surrounding rock grade, lining structure strength, design allowable deformation value (e.g., allowable settlement value for Grade III surrounding rock ≤30mm, allowable convergence value ≤20mm), and engineering experience, a dual standard of absolute threshold and relative threshold is adopted:

[0104] Absolute thresholds: Settlement (yellow ≥ 5 mm, orange ≥ 10 mm, red ≥ 15 mm); Convergence (yellow ≥ 3 mm, orange ≥ 6 mm, red ≥ 9 mm);

[0105] Relative thresholds: deformation rate (yellow ≥ 0.5 mm / d, orange ≥ 1.0 mm / d, red ≥ 2.0 mm / d), acceleration (yellow ≥ 0.1 mm / d², orange ≥ 0.3 mm / d², red ≥ 0.5 mm / d²).

[0106] Dynamic threshold adjustment: The threshold is dynamically adjusted according to the tunnel construction stage, such as relaxing the threshold by 20% during the excavation period and tightening it by 10% during the operation period; manual fine-tuning is supported through the host computer software, and the adjustment range is ±50% of the default value.

[0107] (II) Early Warning Triggering and Response Process

[0108] Triggering logic: The corresponding level of warning is triggered if any of the following conditions are met: a single indicator reaches the corresponding level threshold; two or more single indicators reach the yellow threshold, which upgrades to an orange warning; or an orange warning lasts for 24 hours without relief or the indicator continues to rise, which upgrades to a red warning.

[0109] Yellow alert: The host computer pop-up notification and local audible and visual alarm will automatically shorten the data collection cycle to 50% of the original cycle and continue monitoring for 24 hours.

[0110] Orange alert: In addition to the actions taken in a yellow alert, send SMS / APP push to the project leader and technical leader, generate an emergency monitoring report on the host computer, and start encrypted data collection at adjacent sections;

[0111] Red Alert: The entire system responds to the highest level, with high-frequency triggering of audible and visual alarms, simultaneous notification of the responsible parties in construction, design, construction, and supervision, automatic activation of the emergency data collection mode with a 1-minute cycle, and uploading real-time data to the emergency command platform.

[0112] (III) Early Warning Review and Cancellation

[0113] Data verification: After the warning is triggered, the system automatically performs a secondary verification on the data collected in the last 10 times, removes outliers and recalculates the deformation parameters. If the verification result still exceeds the threshold, the warning is confirmed to be valid; if it is caused by data error, the warning is automatically lifted and the cause of the error is recorded.

[0114] Warning cancellation: Yellow warning requires deformation value to be below the threshold and rate ≤ 0.2 mm / d for 12 consecutive hours; Orange warning requires indicators to meet the standard for 24 consecutive hours; Red warning requires manual on-site verification and reinforcement measures, and the system to collect data 3 times and all of them meet the standard, and the person in charge can manually cancel it on the platform.

[0115] In summary, this embodiment also introduces a data acquisition system that executes the above-described data acquisition method. The system includes a device control unit, a data acquisition unit, and a data analysis unit, specifically:

[0116] The equipment control unit executes the above steps S1, S2, and S3. By controlling the pan-tilt unit to reset and rotate, the laser rangefinder sensor to start and stop and configure parameters, the zero reference point laser transmitter station to calibrate, the reference chain to build and the device attitude to correct, the acquisition mode to switch and the abnormal acquisition interruption and restart, the equipment is initialized and ready, the reference chain is reliably built, and the acquisition process is precise and controllable. This ensures that the laser sensor and pan-tilt unit operate stably according to the preset working conditions and avoids the impact of installation deviations, vibrations, etc. on the acquisition.

[0117] The data acquisition unit executes steps S3 and S4 above. It emits laser pulses and receives reflected signals through the laser range sensor, acquires the distance values ​​between the tunnel sidewall and the arch, and simultaneously records the pan-tilt rotation angle φ, acquisition timestamp, reference laser offset Δ, and temperature, humidity / vibration data. It performs preliminary preprocessing to achieve complete capture of the original measurement data of the tunnel cross section, filter invalid data, and provide real and reliable basic data support for subsequent coordinate transformation and deformation calculation.

[0118] The data analysis unit executes steps S4 and S5 above. Through geometric correction and coordinate transformation algorithms, oblique section projection mapping model, and settlement and convergence calculation formulas, it integrates linear regression, exponential smoothing method and GM(1,1) model to construct a trend prediction model, extract deformation rate and acceleration parameters, and execute dual-standard multi-level early warning logic to accurately calculate tunnel deformation parameters, predict deformation development trends, and trigger graded early warnings in a timely manner, providing scientific decision support for tunnel safety status assessment and emergency response.

[0119] Finally, it should be noted that the above embodiments are merely examples for clearly illustrating the present invention and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method and system for acquiring tunnel settlement data based on laser ranging, characterized in that, The method includes the following steps: S1. The equipment consists of a monitoring device including a pan-tilt unit and two laser rangefinders with a fixed angle, wherein the first sensor points horizontally toward the tunnel sidewall and the second sensor points at the tunnel arch at an angle θ. S2. Layout and Base Point Selection: Layout monitoring points in the tunnel according to predetermined rules, and set a zero reference point in the stable area at the tunnel entrance. Correlate and calibrate the positions of all monitoring devices through a continuous laser reference chain. S3. Data Acquisition: Control the pan-tilt unit of the monitoring device to rotate at a preset step angle, drive the two laser sensors to synchronously acquire the distance values ​​between the tunnel sidewall and the arch, and synchronously record the pan-tilt unit rotation angle, time information and environmental sensor data. S4. Data Processing: Convert the collected polar coordinate distance measurement data into standard Cartesian coordinate data of the tunnel cross section, and calculate the settlement and convergence of the tunnel by comparing the current cross section data with the initial reference data. S5. Trend Analysis and Early Warning: Based on the calculated historical deformation data, a trend prediction model is established to calculate the deformation rate and acceleration in real time, and triggers corresponding levels of early warning and response processes according to preset multi-level thresholds.

2. The method and system for acquiring tunnel settlement data based on laser ranging as described in claim 1, characterized in that, Step S2 specifically includes: The spacing of longitudinal monitoring points is dynamically determined based on the tunnel's surrounding rock grade, maximum net width, and curvature. Based on the geological risk level, monitoring devices are installed symmetrically on one or both sides of the tunnel, and the number of monitoring points is increased in key areas. A continuous laser reference chain is constructed, consisting of a zero-reference laser emitting station and photoelectric receiving units of each monitoring device, for calibrating and monitoring the displacement of the device itself.

3. The method and system for acquiring tunnel settlement data based on laser ranging as described in claim 1, characterized in that, Step S3 specifically includes: It supports three acquisition modes: timed active reporting, host computer polling, and triggering. The acquisition cycle and triggering conditions can be dynamically configured according to monitoring needs. The pan-tilt unit is controlled to scan according to the preset step angle and rotation range to ensure that the laser covers key measuring points of the tunnel section. Environmental parameters and device status are recorded simultaneously during the acquisition process. During data acquisition, the pan-tilt unit performs round-trip scanning and ensures consistency through data comparison, while eliminating abnormal distance measurements in real time. It integrates temperature, humidity, and vibration sensors for environmental compensation and data acquisition interruption control, and periodically performs automatic device position calibration through a reference chain.

4. The method and system for acquiring tunnel settlement data based on laser ranging as described in claim 1, characterized in that, The data processing in step S4 includes coordinate transformation: Based on the installation coordinates of the monitoring device, the rotation angle of the pan-tilt unit, the fixed angle of the laser, and the distance measurement value, the polar coordinate data is converted into three-dimensional coordinates in the tunnel space; the installation deviation is corrected by using the reference chain offset and the inclination measurement value; the oblique section data collected by the pan-tilt unit at different rotation angles is uniformly mapped to the standard tunnel cross section through geometric projection.

5. The method and system for acquiring tunnel settlement data based on laser ranging as described in claim 1, characterized in that, The data processing in step S4 includes deformation parameter calculation: By comparing the current cross-sectional profile data with the initial zero-state data, the tunnel deformation is calculated: the settlement is obtained by calculating the difference in the vertical coordinates of the measuring point at the top of the tunnel; the convergence is obtained by calculating the difference in the horizontal distance between the corresponding measuring points on both sides of the tunnel.

6. The method and system for acquiring tunnel settlement data based on laser ranging as described in claim 1, characterized in that, The data processing step S4 also includes the integration and calculation of cross-sectional deformation values: Based on the deformation of each measuring point obtained from the solution, the average settlement and average convergence of a single monitoring section are calculated to form parameters characterizing the overall deformation state of the section.

7. The method and system for acquiring tunnel settlement data based on laser ranging as described in claim 1, characterized in that, Step S5 specifically includes: Based on historical deformation data, a deformation trend model is constructed by integrating multiple prediction algorithms, and real-time deformation rate and acceleration are extracted; A dual warning threshold based on absolute and relative values ​​of settlement, convergence, deformation rate, and acceleration is established to form a multi-level warning standard of yellow, orange, and red. Based on the comparison results between real-time data and thresholds, the system automatically triggers warnings of the corresponding level and executes response actions including shortening the data collection cycle, multi-level alarm notifications, and activating emergency monitoring.

8. A tunnel settlement data acquisition system based on laser ranging, performing the method as described in any one of claims 1 to 7, characterized in that, The system includes a device control unit, a data acquisition unit, and a data analysis unit. The equipment control unit is used to perform the initialization of the monitoring device, gimbal rotation control, laser sensor start / stop, reference chain construction and calibration, and the scheduling and management of acquisition modes; The data acquisition unit is used to receive and record the raw data from the laser rangefinder, gimbal encoder, and environmental sensor, and to perform preliminary filtering and preprocessing. The data analysis unit is used to perform coordinate transformation, deformation parameter calculation, trend model construction, early warning logic judgment, and output deformation results and early warning information.

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