Interior and exterior deformation monitoring method integrating Beidou GNSS and inclinometer

Abstract

The invention discloses an interior and exterior deformation monitoring method integrating a Beidou GNSS and an inclinometer, and belongs to the technical field of geotechnical engineering and structural health monitoring. The method comprises the following steps: arranging a monitoring system and establishing a unified space-time reference; synchronously acquiring data of the Beidou and the inclinometer; establishing an error state observation equation, utilizing Beidou orifice absolute displacement constraint, performing dynamic inversion distribution on the accumulated error of the inclinometer along the depth through adaptive Kalman filtering, and obtaining a corrected internal absolute displacement field; and fusing earth surface and internal displacement data, reconstructing a continuous three-dimensional deformation field and carrying out early warning. According to the method, the problems of non-uniform space-time reference of multi-source data and accumulative errors of the inclinometer are solved, physical assimilation of internal and external deformation fields is realized, and the precision, continuity and reliability of deformation monitoring are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of geotechnical engineering and structural health monitoring technology, and in particular to a method for monitoring internal and external deformation by integrating BeiDou GNSS and an inclinometer. Background Technology

[0002] Deformation monitoring is an important means of ensuring the safety of geotechnical engineering and structures. At present, the monitoring technologies for surface and internal deformation are relatively mature, but they often operate independently, resulting in problems such as data fragmentation and poor complementarity.

[0003] In existing technologies, surface deformation monitoring mainly relies on Global Navigation Satellite Systems (GNSS), including the BeiDou system. GNSS technology can provide high-precision absolute three-dimensional coordinates and has advantages such as all-weather operation, automation, and no line-of-sight between stations, making it the mainstream method for surface displacement monitoring. However, GNSS monitoring can only reflect the macroscopic displacement of the surface location of the monitoring point and cannot penetrate the surface to obtain deep deformation information inside the soil and rock mass, leaving blind spots in the identification of deep sliding surfaces and shear deformation zones.

[0004] Inclinometers are currently the most widely used instruments for monitoring internal deformation. By installing an inclinometer tube inside the borehole, the inclinometer measures the dip angle changes at different depths, and the horizontal displacement is calculated through integration. Inclinometers can accurately reflect the displacement distribution patterns within the formation and are an effective tool for identifying the location of slip surfaces. However, traditional inclinometer monitoring techniques have inherent drawbacks: First, inclinometers measure relative displacement, lacking an absolute spatial reference, making them susceptible to zero-point drift over long-term monitoring; second, displacement calculation uses a recursive integration method from the borehole opening or bottom to the other end, causing measurement errors to accumulate with depth, reducing the reliability of deep displacement data; third, the traditional "borehole displacement calibration" method simply corrects the starting point at the borehole opening without considering the error propagation mechanism along depth, failing to fundamentally eliminate accumulated errors.

[0005] In recent years, some projects have attempted to combine GNSS with inclinometers, typically by simply mounting the GNSS antenna at the opening of the inclinometer borehole and using GNSS displacement to correct the starting point of the inclinometer data. This simple "overlay" combination suffers from the following technical bottlenecks: Inconsistent spatiotemporal references: GNSS and inclinometers typically use independent data acquisition devices with asynchronous sampling frequencies and time reference deviations, resulting in phase differences during data fusion and an inability to accurately reflect instantaneous deformation states.

[0006] Missing error model: Most existing methods only perform simple "first and last corrections" and do not establish a state space model of the error along the depth direction. This makes it impossible to effectively transfer the absolute constraints of the borehole opening to each measuring point in the depth, resulting in insufficient long-term stability of the inclination data.

[0007] Low information fusion: The surface displacement provided by GNSS and the internal displacement provided by the inclinometer are not physically assimilated, making it impossible to construct a continuous and unified three-dimensional deformation field. The monitoring data still shows a "point" or "line" distribution, making it difficult to fully reveal the three-dimensional deformation mechanism of the rock and soil.

[0008] Therefore, there is an urgent need for a monitoring method that can deeply integrate BeiDou GNSS and inclinometer data, unify spatiotemporal references, dynamically eliminate accumulated errors, and reconstruct a three-dimensional deformation field. Summary of the Invention

[0009] The purpose of this invention is to provide a method for monitoring internal and external deformation by integrating BeiDou GNSS and inclinometers, in order to solve the technical problems in the prior art such as inconsistent spatiotemporal references of multi-source monitoring data, difficulty in dynamically eliminating cumulative errors of inclinometers, and separation of internal and external deformation fields, so as to achieve high-precision, high-reliability, and comprehensive deformation monitoring.

[0010] To achieve the above objectives, this invention provides a method for monitoring internal and external deformation by integrating BeiDou GNSS and an inclinometer, comprising the following steps: S1. Monitoring system deployment and spatiotemporal reference establishment: Monitoring boreholes were installed at key monitoring sections of the structure to be monitored. Fixed inclinometer sensor arrays were deployed along the depth direction within the boreholes, and BeiDou GNSS receivers were installed at the borehole openings. All sensors were connected via a multi-source data synchronization acquisition terminal, utilizing the terminal's built-in high-precision real-time clock and satellite timing module to achieve microsecond-level time synchronization between BeiDou GNSS data and inclinometer data. An independent coordinate system was established for the project, calibrating the absolute coordinates of the borehole opening and the initial azimuth of the inclinometer tubes, thus constructing a unified spatial reference.

[0011] S2. Synchronous acquisition and preprocessing of multi-source data: The control acquisition terminal synchronously acquires raw BeiDou GNSS observation data (pseudorange, carrier phase) and inclinometer dual-axis tilt data at a preset sampling frequency. RTK differential calculation is performed on the BeiDou data to obtain the absolute displacement time series of the borehole opening; low-pass filtering is applied to the inclinometer tilt data, and the relative displacement of each measuring point relative to the borehole opening is calculated based on the geometric parameters of the inclinometer tube.

[0012] S3. Dynamic correction of cumulative error of inclinometer: An error state-space model is constructed. The difference between the orifice displacement calculated by the inclinometer integration and the orifice displacement measured by BeiDou is defined as the observation vector, and the measurement error at each measuring point is defined as the state vector. Using an adaptive Kalman filter algorithm, the absolute displacement constraint of the orifice is used as the observation update to correct the state estimate of each depth measuring point, thereby realizing the dynamic distribution and compensation of the cumulative error along the depth and outputting the corrected internal absolute displacement field.

[0013] S4. Assimilation and reconstruction of internal and external deformation fields: Based on the BeiDou displacement data of all borehole openings, a continuous surface deformation field was constructed using Kriging interpolation. Based on the corrected internal absolute displacement data of each borehole, a three-dimensional deformation field inside the strata was constructed using three-dimensional spline interpolation. Dirichlet boundary conditions were applied at the interface between the surface and the strata to force the internal field to match the surface field, achieving physical assimilation and reconstructing a continuous three-dimensional deformation field.

[0014] S5. Fusion Deformation Analysis and Early Warning: Based on the reconstructed 3D deformation field, characteristic indicators such as displacement rate, displacement gradient, and shear deformation zone location are extracted. Combining historical data and environmental factors, a time-series prediction model is used for trend analysis. Multi-level dynamic early warning thresholds are set to achieve automated safety warnings.

[0015] Preferably, in step S1, the method for establishing the spatial reference is as follows: an engineering independent coordinate system is established based on the adjustment results of the first phase of BeiDou observation data in the monitoring area; the three-dimensional geodetic coordinates of each borehole opening are obtained and converted into engineering coordinates; the initial azimuth angle of the guide wheel groove of the inclinometer is determined by using an inclinometer, and the transformation relationship between the local coordinate system of the inclinometer and the engineering independent coordinate system is established.

[0016] Preferably, in step S3, the specific implementation process of adaptive Kalman filtering is as follows: establish a state transition matrix, assuming that the error between adjacent measuring points is linear or exponentially distributed; establish an observation equation, expressing the total error of the orifice as the sum of the errors of each measuring point; through prediction and update steps, use BeiDou observations to make optimal estimation of the state vector, and obtain the error correction amount of each measuring point.

[0017] Preferably, in step S4, the Kriging interpolation method uses an anisotropic variation function model to set range parameters in different directions according to the deformation characteristics of the geological body, so as to accurately characterize the spatial correlation of surface deformation.

[0018] Preferably, the method also includes a data anomaly handling and redundancy monitoring mode: when the BeiDou signal loses lock due to obstruction, the system automatically switches to the inclinometer relative monitoring mode and records the period of lock loss for subsequent data repair; when the data of a single inclinometer sensor is abnormal, interpolation of adjacent measuring points is used to replace it to ensure the continuity of the integration path.

[0019] Preferably, in step S5, the warning threshold is a dynamic threshold that is adaptively adjusted according to the life cycle stage of the monitored object (such as the construction period or the operation period) and seasonal changes in ambient temperature.

[0020] Preferably, the method further includes a visualization step: mapping the reconstructed three-dimensional deformation field onto the engineering three-dimensional model to generate displacement cloud maps, contour maps, and displacement distribution curves of arbitrary profiles, supporting monitoring personnel to intuitively identify the deformation state.

[0021] Therefore, the internal and external deformation monitoring method of the present invention, which integrates BeiDou GNSS and inclinometer with the above-mentioned structure, has the following beneficial effects: (1) This invention solves the problem of spatiotemporal inconsistency of multi-source data by hardware-level synchronous acquisition and spatial calibration, laying the foundation for deep data fusion.

[0022] (2) This invention uses the absolute displacement of Beidou as an external constraint and uses Kalman filtering to distribute the error in reverse, which effectively suppresses the cumulative error of the inclinometer's deep displacement and improves the long-term accuracy of internal deformation monitoring.

[0023] (3) This invention breaks through the monitoring limitations of “point” and “line”, realizes the physical assimilation of the deformation field of the surface and deep part of the earth, and can intuitively and continuously display the overall deformation state of the rock and soil, thus improving the ability to identify hidden diseases.

[0024] (4) The present invention designs a redundancy mechanism in which Beidou and inclinometer are backups of each other, which enhances the adaptability of the monitoring system in complex environments.

[0025] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the overall process of the monitoring method of the present invention. Detailed Implementation

[0027] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0028] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0029] Example like Figure 1As shown, this invention provides a method for monitoring internal and external deformation by integrating BeiDou GNSS and an inclinometer, comprising the following steps: S1. Monitoring system deployment and spatiotemporal reference establishment: Monitoring boreholes were installed at key monitoring sections of the structure to be monitored. Fixed inclinometer sensor arrays were deployed along the depth direction within the boreholes, and BeiDou GNSS receivers were installed at the borehole openings. All sensors were connected via a multi-source data synchronization acquisition terminal, utilizing the terminal's built-in high-precision real-time clock and satellite timing module to achieve microsecond-level time synchronization between BeiDou GNSS data and inclinometer data. An independent coordinate system was established for the project, calibrating the absolute coordinates of the borehole opening and the initial azimuth of the inclinometer tubes, thus constructing a unified spatial reference.

[0030] S2. Synchronous acquisition and preprocessing of multi-source data: The control acquisition terminal synchronously acquires raw BeiDou GNSS observation data (pseudorange, carrier phase) and inclinometer dual-axis tilt data at a preset sampling frequency. RTK differential calculation is performed on the BeiDou data to obtain the absolute displacement time series of the borehole opening; low-pass filtering is applied to the inclinometer tilt data, and the relative displacement of each measuring point relative to the borehole opening is calculated based on the geometric parameters of the inclinometer tube.

[0031] S3. Dynamic correction of cumulative error of inclinometer: An error state-space model is constructed. The difference between the orifice displacement calculated by the inclinometer integration and the orifice displacement measured by BeiDou is defined as the observation vector, and the measurement error at each measuring point is defined as the state vector. Using an adaptive Kalman filter algorithm, the absolute displacement constraint of the orifice is used as the observation update to correct the state estimate of each depth measuring point, thereby realizing the dynamic distribution and compensation of the cumulative error along the depth and outputting the corrected internal absolute displacement field.

[0032] S4. Assimilation and reconstruction of internal and external deformation fields: Based on the BeiDou displacement data of all borehole openings, a continuous surface deformation field was constructed using Kriging interpolation. Based on the corrected internal absolute displacement data of each borehole, a three-dimensional deformation field inside the strata was constructed using three-dimensional spline interpolation. Dirichlet boundary conditions were applied at the interface between the surface and the strata to force the internal field to match the surface field, achieving physical assimilation and reconstructing a continuous three-dimensional deformation field.

[0033] S5. Fusion Deformation Analysis and Early Warning: Based on the reconstructed 3D deformation field, characteristic indicators such as displacement rate, displacement gradient, and shear deformation zone location are extracted. Combining historical data and environmental factors, a time-series prediction model is used for trend analysis. Multi-level dynamic early warning thresholds are set to achieve automated safety warnings.

[0034] Taking a high slope monitoring project on a highway as an example, the specific method is as follows: S100, Project Overview and System Deployment: A high slope of a highway has a maximum height of 65m, and the strata are mainly composed of gravelly soil and strongly weathered mudstone. Three monitoring boreholes (numbered ZK1, ZK2, and ZK3) were installed on the main sliding section of the slope, each with a depth of 40m.

[0035] A fixed array of inclinometers is installed in each borehole. The model used is a MEMS dual-axis inclinometer from a certain brand, with a range of ±15° and a resolution of 0.001°. The spacing between the inclinometers is set to 2m, and 20 sensors are installed in each borehole.

[0036] Each borehole opening is fitted with a concrete observation pier, and a Beidou GNSS receiver (supporting both BDS and GPS systems) is installed with an antenna 1.2m high.

[0037] All sensor cables converge at the data acquisition box at the foot of the slope. The acquisition box houses a self-developed multi-source synchronous acquisition terminal. This terminal incorporates a high-precision OCXO crystal oscillator and utilizes BeiDou satellite timing signals for calibration, outputting PPS pulses to control each acquisition channel, ensuring data synchronization accuracy between BeiDou and the inclinometer is better than 1μs. The sampling frequency is set to 1Hz.

[0038] Spatial benchmark calibration was completed on-site: using a total station and static GNSS measurements, the coordinates of each borehole opening point in the engineering independent coordinate system were determined. The azimuth angle of the A-axis (main measuring direction) of each borehole inclinometer was determined using a clinometer, and it was correlated with the X-axis (main sliding direction) of the engineering coordinate system to establish a coordinate transformation matrix.

[0039] S200, Data Acquisition and Preprocessing: The system runs continuously, collecting data in real time.

[0040] The BeiDou data is processed using network RTK technology to obtain the plane displacement of the orifice, with an accuracy better than ±5mm.

[0041] The original data from the inclinometer is the biaxial tilt angle ( First, a moving average filter is applied with a window length of 10 sampling points. Then, based on the diameter of the inclinometer tube... Calculate the relative horizontal displacement increment at each measuring point. Where $L$ is the distance between measuring points. The cumulative relative displacement of each measuring point relative to the orifice is obtained through cumulative calculation. .

[0042] S300, Dynamic Correction of Cumulative Error: After 30 days of monitoring, a discrepancy was found between the borehole displacement calculated by the ZK1 borehole inclinometer and the displacement measured by the BeiDou system. The BeiDou measurement showed a borehole displacement of 12.5 mm outward from the slope, while the inclinometer's integrated value was 14.2 mm, indicating a significant discrepancy. To eliminate this accumulated error, the following correction algorithm is performed: (1) Establish the state vector ,in For the first Estimated measurement error for each measuring point.

[0043] (2) Establish the observation equation ,in Observational bias , The observation matrix is ​​taken here as an all-1 vector, representing the total deviation formed by the sum of the errors at each measurement point.

[0044] (3) Define the state transition equation Assuming the error propagates linearly along the depth, the state transition matrix $\Phi$ is set as a lower triangular matrix to achieve smooth error propagation.

[0045] (4) Run the Kalman filter. Use the BeiDou displacement as the observation update to iteratively correct the state vector.

[0046] (5) Output the corrected internal displacement field .

[0047] After calibration, the orifice displacement is consistent with that of Beidou, and the smoothness of the displacement curves of each measuring point in the depth is improved, eliminating the "tailing" phenomenon at the end caused by the accumulation of errors.

[0048] S400, internal and external deformation field assimilation and reconstruction: To comprehensively assess the slope deformation state, a three-dimensional field reconstruction was performed.

[0049] Surface deformation field construction: Using GNSS data from three boreholes and data from two surface monitoring points around the slope, ordinary Kriging interpolation was employed. Considering the principal directionality of slope deformation, the main range of the variation function was set to 30m along the slope and the secondary range to 15m across the slope, generating a surface displacement grid.

[0050] Internal deformation field construction: Using the displacement data of the three boreholes ZK1, ZK2, and ZK3 after correction as control points, a three-dimensional displacement mesh covering the interior of the slope is constructed using a three-dimensional thin plate spline interpolation algorithm.

[0051] Boundary constraint fusion: During the interpolation process, the surface mesh and the internal mesh are forced to have the same numerical values ​​at the orifice position to achieve seamless splicing.

[0052] The reconstruction results show a significant abrupt displacement gradient zone at a depth of 15m in borehole ZK2, presumably the location of a potential slip surface. This information cannot be obtained solely from surface GNSS monitoring, and even uncorrected inclinometer data may lead to misjudgment due to error interference.

[0053] S500, Early Warning and Analysis: The system automatically calculates the maximum displacement rate based on the reconstructed model. On a certain day, during heavy rainfall, the system detected a sudden increase in the displacement rate at a depth of 15m in borehole ZK2 to 5mm / d, and the surface displacement rate increased simultaneously.

[0054] The system triggered a yellow alert, automatically generating an alert report including a surface displacement cloud map, deep displacement curves, and a 3D deformation animation, which was then sent to management personnel via SMS. Based on this, management personnel implemented slope toe counter-pressure measures, effectively controlling further deformation.

[0055] This embodiment verifies that the method proposed in this invention effectively solves the problem of multi-source data fusion, significantly improves monitoring accuracy and early warning timeliness, and has good engineering practical value.

[0056] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for monitoring internal and external deformation by integrating BeiDou GNSS and an inclinometer, characterized in that, Includes the following steps: S1. Install monitoring boreholes in the structure to be monitored, install a fixed inclinometer sensor array along the depth inside the borehole, and install a Beidou GNSS receiver at the borehole opening. A multi-source data synchronous acquisition terminal is used to achieve microsecond-level time synchronization between the Beidou GNSS receiver and each inclinometer sensor. S2. Construct a spatial coordinate system association model, spatially associate the BeiDou coordinates of the borehole opening with the installation depth and initial attitude of the inclinometer, and establish a unified spatial benchmark. S3. Synchronously collect BeiDou GNSS raw observation data and inclinometer dual-axis tilt angle data, perform data preprocessing, and obtain the absolute displacement time sequence of borehole opening and the relative displacement of each measuring point. S4. Establish the error state observation equation, use the absolute displacement of the Beidou aperture to constrain the inclinometer integration path in real time, and use adaptive Kalman filtering to dynamically invert and distribute the inclinometer integration cumulative error along the depth direction to each depth measuring point to obtain the corrected internal absolute displacement field. S5. Construct an internal and external deformation field fusion model, physically assimilate the external point displacement monitored by Beidou and the internal absolute displacement field reconstructed by the inclinometer, and form a continuous three-dimensional deformation field through surface deformation field interpolation, internal deformation field interpolation and boundary constraint fusion. S6. Extract deformation indices based on the reconstructed 3D deformation field, perform deformation analysis and trend prediction, and trigger early warnings according to preset thresholds.

2. The method for monitoring internal and external deformation by integrating BeiDou GNSS and an inclinometer according to claim 1, characterized in that, In step S4, the state vector of the adaptive Kalman filter is the error term of each depth measuring point, and the observation vector is the difference between the absolute displacement of the Beidou aperture and the inclinometer integrated aperture displacement. The state transition matrix is ​​constructed using a linear interpolation model, assuming that the error between adjacent measuring points is linearly distributed along the depth, thereby realizing the dynamic distribution of the total aperture error to each measuring point.

3. The method for monitoring internal and external deformation by integrating BeiDou GNSS and an inclinometer as described in claim 1, characterized in that, The internal and external deformation field fusion model in step S5 specifically includes: A continuous surface deformation field is constructed using absolute displacement data from BeiDou monitoring points at the borehole openings of all monitoring boreholes, employing either Kriging interpolation or radial basis function interpolation. A three-dimensional deformation field inside the formation is constructed based on the corrected internal absolute displacement data of each borehole using either three-dimensional spline interpolation or finite element shape function method. Boundary constraints are applied at the interface between the surface and the monitoring borehole to force the internal deformation field and the surface deformation field to be continuous at the interface, thus achieving seamless connection between the internal and external deformation fields.

4. The method for monitoring internal and external deformation by integrating BeiDou GNSS and an inclinometer according to claim 3, characterized in that, Kriging interpolation employs an anisotropic semivariogram model, whose principal axis direction is set according to the principal deformation direction of the structure to be monitored, in order to reflect the spatial anisotropic characteristics of the deformation field.

5. The method for monitoring internal and external deformation by integrating BeiDou GNSS and an inclinometer according to claim 1, characterized in that, The multi-source data synchronous acquisition terminal has a built-in high-precision real-time clock and GPS timing module. The sampling frequency is adjustable between 1Hz and 10Hz, and the data is stored with timestamps to ensure the spatiotemporal consistency of Beidou and inclinometer data.

6. The method for monitoring internal and external deformation by integrating BeiDou GNSS and an inclinometer according to claim 1, characterized in that, It also includes a redundancy processing mode: when the BeiDou GNSS signal is lost or the positioning accuracy is lower than the preset threshold, the system automatically switches to the inclinometer relative deformation monitoring mode and only outputs relative displacement data; when the inclinometer sensor fails or the data is abnormal, the system performs spatiotemporal interpolation based on the BeiDou monitoring point data and the historical deformation field model to maintain the continuity of the deformation field.

7. The method for monitoring internal and external deformation by integrating BeiDou GNSS and an inclinometer according to claim 1, characterized in that, In step S6, the deformation indicators include: maximum displacement rate and direction, displacement depth distribution curve, shear deformation zone location identification, and deformation trend prediction. The early warning adopts a multi-level early warning mechanism, and the thresholds at each level are dynamically updated using an adaptive threshold algorithm based on historical deformation rates and seasonal variation patterns.

8. The method for monitoring internal and external deformation by integrating BeiDou GNSS and an inclinometer according to claim 1, characterized in that, It also includes the visualization output of the deformation field: the reconstructed 3D deformation field is displayed in real time on the monitoring platform in the form of cloud map, contour map, vector map or 3D dynamic model, supporting multi-view interactive viewing.

9. The method for monitoring internal and external deformation by integrating BeiDou GNSS and an inclinometer according to claim 1, characterized in that, It also includes differential comparison of multi-period data: the three-dimensional deformation field at the current moment is differentially calculated with the deformation field at the initial moment or any historical moment to obtain the cumulative deformation field, which is used to identify deformation concentration areas and evolution trends.

10. The method for monitoring internal and external deformation by integrating BeiDou GNSS and an inclinometer according to claim 1, characterized in that, It also includes integration with building information modeling or geographic information systems: overlaying the reconstructed three-dimensional deformation field onto the engineering BIM model or GIS map to realize the spatial correlation display and analysis of monitoring data and engineering structure.

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