A dam slope deformation monitoring method based on measurement robot and GNSS fusion

Abstract

The present application relates to a kind of dam slope deformation monitoring method based on measurement robot and GNSS fusion.The method comprises: signal synchronization and delay correction are carried out to the dual-mode observation pier of GNSS and measurement robot prism target, and time-space reference network is constructed;Anti-interference laser pulse is emitted by controlling measurement robot, environmental vibration is offset, and vibration compensation coordinate set is output;Dam slope displacement field is obtained by variable weight adaptive fusion processing;The abnormal area exceeding the first deformation threshold in displacement field is scanned with encryption, and polarized interference phase diagram is generated;Self-adaptive data stream is formed by three-level dynamic classification coding, and reference point drift component is calculated by combining dual-mode observation pier, and net deformation set is extracted;Finally, net deformation set is mapped to BIM model, and color temperature gradient three-dimensional deformation situation diagram is constructed, the area exceeding the second deformation threshold triggers early warning, and three-dimensional early warning atlas is generated.The present application can realize the high-precision space-time unification of multi-source data, and significantly improve the monitoring consistency and anti-interference ability under complex environment.

Description

Technical Field

[0001] This invention relates to the field of dam slope deformation monitoring technology, and specifically to a dam slope deformation monitoring method based on the fusion of a measurement robot and GNSS. Background Technology

[0002] Dam slope deformation monitoring refers to the process of continuously and systematically measuring and analyzing changes in displacement, settlement, and tilt of the dam slope and dam body using specialized instruments and techniques in order to assess the stability and safety status of the dam slope.

[0003] In recent years, dam slope deformation monitoring technology has gradually developed towards multi-source sensor fusion, with the collaborative application of Global Navigation Satellite System (GNSS) and surveying robots (such as high-precision total stations) becoming a research hotspot. Existing technologies typically utilize GNSS reference stations to establish a large-scale absolute coordinate reference frame, combined with a total station to perform millimeter-level precision local measurements on key areas of the dam slope, thus achieving an organic integration of deformation information at both macroscopic and microscopic levels. This combined measurement approach leverages the stability advantages of GNSS in large-scale, continuous monitoring, and the sensitivity of the total station in high-precision, high-resolution local measurements, providing comprehensive data support for dam slope safety status assessment.

[0004] However, the reliability and accuracy of existing technologies still face significant challenges in complex environments. First, due to the lack of a high-precision unified spatiotemporal reference, there are millisecond-level time synchronization errors and spatial registration deviations between GNSS and total stations, making it difficult to deeply integrate multi-source sensor data. In areas with large deformation gradients, displacement field reconstruction errors are significant, seriously affecting the consistency and reliability of monitoring data. Second, in the face of interference conditions such as strong winds, mechanical vibrations, or significant temperature differences, existing systems lack effective dynamic error suppression and compensation capabilities. GNSS multipath effect errors increase to the centimeter level, and the angle measurement accuracy of total stations is also significantly deteriorated by vibration, making it difficult to guarantee the stability and accuracy of monitoring data in complex environments. In addition, existing methods have not yet achieved deep integration of deformation data and engineering models, lacking closed-loop management capabilities from data to decision-making, and cannot support dynamic visualization and intelligent early warning of deformation trends, limiting further improvement in disaster early warning response efficiency. Summary of the Invention

[0005] The purpose of this invention is to provide a method for monitoring dam slope deformation based on the fusion of measurement robots and GNSS. This method can achieve high-precision spatiotemporal unification of GNSS and measurement robot data, providing a reliable benchmark for multi-source sensor fusion and significantly improving the data consistency of dam slope deformation monitoring. Furthermore, it can effectively suppress dynamic errors to ensure the stability and accuracy of monitoring data in complex environments. It also has the closed-loop management capability from data to decision-making, improving the efficiency of disaster early warning and response.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] In a first aspect, the present invention provides a method for monitoring dam slope deformation based on the fusion of a measurement robot and GNSS, the method comprising:

[0008] Signal synchronization and delay correction were performed on the dual-mode observation piers of GNSS and the prism target of the surveying robot to obtain a spatiotemporal reference network;

[0009] Based on the spatiotemporal reference network, the measurement robot emits anti-interference laser pulses towards the dual-mode observation pier, cancels out environmental vibrations, and outputs a vibration compensation coordinate set;

[0010] A weighted adaptive fusion of the vibration compensation coordinate set and the spatiotemporal reference network is performed to output the dam slope displacement field.

[0011] A dense scan is performed on the abnormal regions in the dam slope displacement field that exceed the first deformation threshold to generate a polarization interferometric phase map;

[0012] The polarimetric interferometric phase map is subjected to three-level dynamic classification and coding to form an adaptive data stream, and the reference point drift component is obtained through dual-mode observation piers to obtain the net deformation set;

[0013] The net deformation set is mapped to the BIM model to construct a three-dimensional deformation status map of color temperature gradient. An early warning display is triggered for abnormal areas that exceed the second deformation threshold, and a three-dimensional early warning map is generated.

[0014] As a preferred embodiment of the present invention, the sub-step for obtaining the spatiotemporal reference network is as follows:

[0015] By using bend-resistant special optical fiber, the dual-mode observation pier of the GNSS receiver and the prism target of the measurement robot is connected to the GNSS reference station to obtain an optical fiber transmission network;

[0016] The atomic clock signal of the GNSS reference station is transmitted using an optical fiber transmission network, and signal synchronization and delay correction are performed to obtain a spatiotemporal reference network.

[0017] As a preferred embodiment of the present invention, the specific steps for the measuring robot to cancel environmental vibrations and output a vibration compensation coordinate set when emitting anti-interference laser pulses to the dual-mode observation pier are as follows:

[0018] Real-time acquisition of environmental vibration data; adjustment of the emission angle of anti-interference laser pulses.

[0019] Based on the angle adjustment results, the vibration effect is offset and vibration compensation data is obtained;

[0020] Based on the vibration compensation data and combined with the spatiotemporal reference network, a vibration compensation coordinate set is output.

[0021] As a preferred embodiment of the present invention, the specific steps for performing variable-weight adaptive fusion of the vibration compensation coordinate set and the spatiotemporal reference network to output the dam slope displacement field are as follows:

[0022] Based on the obtained vibration compensation coordinate set and the GNSS receiver measurement data of the dual-mode observation pier in the spatiotemporal reference network, multi-source data alignment is performed to obtain spatiotemporal aligned data.

[0023] The spatiotemporal aligned data is dynamically weighted to obtain the optimal weight ratio; based on the optimal weight ratio, the displacement field of the dam slope is obtained by weighted fusion calculation through the displacement field solution model.

[0024] As a preferred embodiment of the present invention, the method for obtaining the polarization interference phase map is as follows:

[0025] The deformation gradient analysis algorithm is used to compare the dam slope displacement field with the first deformation threshold and detect abnormal areas that exceed the first deformation threshold.

[0026] The abnormal region is subjected to multi-angle encrypted scanning to obtain the original radar echo data of the abnormal region, and phase calculation and coherence analysis are performed to generate a polarization interferometric phase map.

[0027] As a preferred embodiment of the present invention, the three-level dynamic classification and encoding processing of the polarization interferometric phase map to form an adaptive data stream includes the following specific steps.

[0028] The deformation gradient magnitude of the polarimetric interferometric phase map is calculated and vectorized to obtain the polarimetric interferometric deformation gradient distribution map; a three-level dynamic classification is performed to obtain classified and coded polarimetric interferometric data.

[0029] The polarization interferometric data is subjected to adaptive encoding processing to obtain compressed polarization interferometric data;

[0030] The compressed polarization interference data is bandwidth adaptively encapsulated to output an adaptive data stream.

[0031] As a preferred embodiment of the present invention, the method for obtaining the net deformation set is specifically as follows:

[0032] The reference point drift component is calculated based on the adaptive data stream and the environmental strain data collected in real time through the dual-mode observation pier.

[0033] The drift component of the reference point is corrected in real time, and the drift compensation parameters are output.

[0034] Environmental interference components are extracted from the drift compensation parameters and the adaptive data stream;

[0035] The environmental disturbance components are differentially calculated based on the net deformation solution algorithm to obtain the net deformation set.

[0036] As a preferred embodiment of the present invention, the method for generating the three-dimensional early warning map is specifically as follows:

[0037] The net deformation set is transformed into the engineering coordinate system under the BIM model to obtain aligned net deformation data; the aligned net deformation data is mapped to the BIM model mesh nodes through the BIM model mapping algorithm to generate a BIM model carrying displacement attributes.

[0038] The displacement-color temperature mapping calculation is performed on the BIM model data carrying displacement attributes to generate a three-dimensional deformation situation map, and abnormal areas exceeding the second deformation threshold are identified and marked to obtain a three-dimensional deformation situation map of the marked abnormal areas.

[0039] The deformation gradient and historical trend analysis of the three-dimensional deformation situation map of the marked abnormal area are performed to generate early warning level parameters, and dynamic early warning annotation is performed to obtain a three-dimensional early warning map.

[0040] In a second aspect, the present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, it implements any step of the dam slope deformation monitoring method based on the fusion of measurement robot and GNSS as described in the first aspect of the present invention.

[0041] Thirdly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the dam slope deformation monitoring method based on the fusion of a measurement robot and GNSS as described in the first aspect of the present invention.

[0042] In summary, the beneficial effects of the present invention are as follows:

[0043] 1. This invention breaks through the technical bottleneck of millisecond-level time synchronization and spatial registration deviation between GNSS and measurement robots by constructing a spatiotemporal reference network based on fiber optic synchronization. It achieves high-precision spatiotemporal unification of GNSS and measurement robot data. The ultra-high synchronization accuracy and anti-interference characteristics provide a reliable reference for multi-source sensor fusion, significantly improve the data consistency of dam slope deformation monitoring, and greatly improve the accuracy of displacement field reconstruction. Especially in key areas with large deformation gradients, it effectively ensures the consistency and reliability of monitoring data.

[0044] 2. Based on the synergistic optimization of hardware and algorithms, this invention can effectively offset the effects of environmental interference such as strong winds, mechanical vibrations, and temperature-induced deformation. The system can dynamically suppress the deterioration of GNSS multipath errors and total station angle measurement errors, and output "net deformation" data after vibration compensation and environmental error correction, thus maintaining excellent monitoring accuracy and data stability even in complex and harsh environments.

[0045] 3. This invention deeply integrates net deformation data with BIM models to dynamically generate a three-dimensional deformation situation map with color temperature gradient mapping, realizing an intuitive and visual expression of deformation information; combined with an intelligent early warning mechanism, the system can automatically identify abnormal deformation areas and issue graded early warnings, realizing closed-loop management of the entire process from deformation detection and analysis to engineering emergency response, thereby significantly improving the accuracy of disaster early warning and response efficiency. Attached Figure Description

[0046] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a flowchart of the dam slope deformation monitoring method;

[0048] Figure 2 This is a flowchart illustrating the steps involved in generating a spatiotemporal reference network in an embodiment of the present invention.

[0049] Figure 3 This is a flowchart illustrating the steps for obtaining an adaptive data stream in an embodiment of the present invention;

[0050] Figure 4 This is a flowchart illustrating the steps for outputting a three-dimensional early warning map in an embodiment of the present invention. Detailed Implementation

[0051] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed merely to enable those skilled in the art to better understand and implement the subject matter described herein, and are not intended to limit the scope, applicability, or examples set forth in the claims. The function and arrangement of the elements discussed may be changed without departing from the scope of this specification. Various processes or components may be omitted, substituted, or added as needed in the various examples. For example, the described methods may be performed in a different order than described, and steps may be added, omitted, or combined. Furthermore, features described in some examples may be combined in other examples.

[0052] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0053] like Figure 1 As shown, this embodiment provides a method for monitoring dam slope deformation based on the fusion of a measurement robot and GNSS. The method includes:

[0054] S02, perform signal synchronization and delay correction on the dual-mode observation piers of GNSS and the prism target of the measurement robot to obtain the spatiotemporal reference network;

[0055] Specifically, such as Figure 2 As shown, S02 also includes a sub-step (the step of obtaining the spatiotemporal reference network):

[0056] S021, through bending-resistant special optical fiber, connects the dual-mode observation pier of the GNSS receiver and the prism target of the measuring robot to the GNSS reference station to obtain an optical fiber transmission network;

[0057] Specifically, the installation locations of dual-mode observation piers for GNSS receivers and prism targets of measuring robots were selected on the dam slope surface. Specialized, bend-resistant optical fibers were used to connect the dual-mode observation piers to the fiber optic interfaces of the GNSS reference station. OTDR was used to test the fiber optic link loss. An atomic clock signal generator from the GNSS reference station was connected at the GNSS reference station end. Carrier phase observations and time signals were transmitted at the STM-1 standard rate. At the dual-mode observation pier end, an optical-to-electrical converter was used to restore the electrical signal. The transmission delay was calculated using a bidirectional time comparison method, completing the physical connection of the fiber optic transmission network and obtaining the fiber optic transmission network.

[0058] S022 utilizes an optical fiber transmission network to transmit atomic clock signals from a GNSS reference station, and performs signal synchronization and delay correction to obtain a spatiotemporal reference network.

[0059] Specifically, the atomic clock signal of the GNSS reference station is transmitted through an optical fiber transmission network. The atomic clock signal is received at the dual-mode observation pier and the signal arrival timestamp is recorded. The GNSS reference station records the signal transmission timestamp. The optical fiber transmission delay is obtained by using a bidirectional time comparison method with an exemplary delay of ≤5ns. Temperature compensation is applied to the signal arrival timestamp with an exemplary compensation coefficient of 0.03ns / ℃. The compensated signal arrival timestamp is then time-aligned with the observation data of the GNSS receiver to complete signal synchronization and delay correction, thus obtaining the spatiotemporal reference network.

[0060] S04, based on a spatiotemporal reference network, the measurement robot emits anti-interference laser pulses towards the dual-mode observation pier and cancels out environmental vibrations, outputting a vibration compensation coordinate set;

[0061] Specifically, S04 includes the following sub-steps:

[0062] S041, Based on the spatiotemporal reference network, the measurement robot emits anti-interference laser pulses towards the prism target of the dual-mode observation pier;

[0063] Specifically, based on the spatiotemporal reference network, the measurement robot emits 532-nanometer wavelength laser pulses to the prism target of the dual-mode observation pier via a laser emitter. The wavelength laser pulses are modulated using chaotic coding, with an exemplary repetition frequency of 10 Hz. The acousto-optic modulator built into the measurement robot adjusts the laser emission angle according to the real-time wind speed data, with an exemplary angle adjustment range of ±0.5 milliradians. After being reflected by the prism target, the laser pulses are received by the measurement robot, which records the round-trip time of the wavelength laser pulses and aligns it with the timestamp of the spatiotemporal reference network to complete the anti-interference laser pulse emission.

[0064] S042 collects environmental vibration data in real time and adjusts the emission angle of the anti-interference laser pulse; based on the angle adjustment result, it cancels the vibration effect and obtains vibration compensation data; based on the vibration compensation data, combined with the spatiotemporal reference network, it outputs a vibration compensation coordinate set.

[0065] The robot's built-in three-axis accelerometer continuously collects and records environmental vibration data. / / Three-axis instantaneous acceleration values. For the acquired... / / The three-axis instantaneous acceleration values ​​are digitally filtered, and a Butterworth second-order low-pass filter is used to eliminate high-frequency noise. The filtered values ​​are then processed... / / Numerical integration of the three-axis instantaneous acceleration values ​​is performed, and the vibration displacement is calculated using the trapezoidal integration method. Based on the calculated vibration displacement, a PID control algorithm drives the piezoelectric crystal of the acousto-optic modulator to adjust the emission angle of the laser emitter in real time, compensating for the ranging error caused by vibration. The emission angle of the compensated anti-interference laser pulse is synchronized with the 1PPS time signal of the spatiotemporal reference network. The final output is a vibration-compensated coordinate set containing three-dimensional coordinates (east, north, and elevation) and a UTC timestamp.

[0066] The expression for calculating the vibration displacement using the trapezoidal integral method is:

[0067] ;

[0068] in, It is the first The vibration displacement at each sampling time. It is the current number The vibration displacement at each sampling time. It is a fixed sampling time interval. It is the first After filtering at each sampling time / / Three-axis instantaneous acceleration values, It is the first After filtering at each sampling time / / Three-axis instantaneous acceleration values, It is a discrete sampling time sequence variable.

[0069] S06, perform variable weight adaptive fusion of vibration compensation coordinate set and spatiotemporal reference network to output dam slope displacement field;

[0070] Specifically, S06 includes the following sub-steps:

[0071] S061, based on the obtained vibration compensation coordinate set and the GNSS receiver measurement data of the dual-mode observation pier in the spatiotemporal reference network, multi-source data alignment is performed to obtain spatiotemporal aligned data;

[0072] The process involves extracting the UTC timestamps from the vibration compensation coordinate set and the GPS timestamps from the GNSS receiver measurement data of the dual-mode observation piers in the spatiotemporal reference network. A time alignment algorithm is then used to unify the time reference of both the vibration compensation coordinate set and the GNSS receiver measurement data of the dual-mode observation piers in the spatiotemporal reference network to the GPST time-stamping system. The carrier phase observation values ​​output from the GNSS receiver measurement data of the dual-mode observation piers are read to obtain GNSS three-dimensional coordinate data. The spatial coordinates of the vibration compensation coordinate set are then transformed to the WGS84 coordinate system and spatially registered with the GNSS three-dimensional coordinate data. The seven-parameter coordinate transformation parameters for the spatial coordinates of the vibration compensation coordinate set to the WGS84 coordinate system are calculated using least squares adjustment. Finally, the time-aligned vibration compensation coordinate set and the GNSS three-dimensional coordinate data are weighted and fused. An exemplary weight allocation ratio is 60% for laser measurement data and 40% for GNSS three-dimensional coordinate data. The spatiotemporally aligned data is then output.

[0073] It should be noted that the GNSS receiver measurement data of the dual-mode observation pier in the spatiotemporal reference network comes from: the GNSS receiver of the dual-mode observation pier continuously receives L1 / L2 band signals from multiple GNSS satellites, records carrier phase and pseudorange observations, receives differential correction data from the GNSS reference station through an optical fiber transmission network, performs real-time dynamic differential positioning calculation using a dual-frequency ionospheric desiccation combination algorithm, uses Kalman filtering to fuse carrier phase and pseudorange observations, and outputs GNSS three-dimensional coordinate data synchronized with the spatiotemporal reference network, thus obtaining the GNSS receiver measurement data of the dual-mode observation pier in the spatiotemporal reference network.

[0074] S062, dynamically assign weights to the spatiotemporal aligned data to obtain the optimal spatiotemporal aligned data weight ratio; based on the optimal spatiotemporal aligned data weight ratio, perform weighted fusion calculation through the displacement field solution model to obtain the dam slope displacement field.

[0075] The accuracy indices of the vibration compensation coordinate set and GNSS 3D coordinate data in the spatiotemporal alignment data are extracted. The variance components are calculated back based on the accuracy indices of the vibration compensation coordinate set and GNSS 3D coordinate data in the spatiotemporal alignment data. The initial weight of the spatiotemporal alignment data is calculated according to the principle of weighting by the inverse of variance. The weight of the spatiotemporal alignment data is dynamically adjusted in combination with the displacement field change rate. When the dam slope displacement rate exceeds the exemplary value of 5 mm / h, the weight of the GNSS 3D coordinate data is increased to the exemplary value of 0.4, and the weight of the vibration compensation coordinate set is adjusted to 0.6 accordingly. The optimal weight ratio of the spatiotemporal alignment data is output.

[0076] The optimal spatiotemporal aligned data weight ratio is input into the displacement field solution model, which employs a grid point interpolation algorithm. The grid spacing for the exemplary dam slope displacement field is 0.5 meters. The coordinate differences between the vibration compensation coordinate set and the GNSS 3D coordinate data at the grid nodes of the dam slope displacement field are fused according to the optimal spatiotemporal aligned data weight ratio. The exemplary weight for the contribution value of the vibration compensation coordinate set to the grid nodes of the dam slope displacement field is 0.6, and the exemplary weight for the contribution value of the GNSS 3D coordinate data is 0.4. The displacement of unmeasured points is calculated using Kriging interpolation, with an exemplary range parameter set to 3 meters. The fused dam slope displacement field grid node displacements are then smoothed using a 9-point moving average filter to eliminate high-frequency noise before outputting the dam slope displacement field.

[0077] S08, perform a dense scan on the abnormal regions in the dam slope displacement field that exceed the first deformation threshold, and generate a polarization interferometric phase map;

[0078] S081, the deformation gradient analysis algorithm is used to compare the dam slope displacement field with the first deformation threshold and detect abnormal areas that exceed the first deformation threshold.

[0079] Specifically, the three-dimensional displacement of the dam slope is extracted from the grid nodes of the dam slope displacement field, and the rate of change of dam slope displacement between adjacent grid nodes is calculated as the deformation gradient value. A 3×3 sliding window is used to traverse the entire dam slope displacement field. The ratio of the displacement difference between the center point of the sliding window and the surrounding 8 nodes to the node spacing is used as the planar deformation gradient component. The elevation deformation gradient is calculated by the ratio of the adjacent elevation difference to the vertical spacing. The planar deformation gradient component and the elevation deformation gradient are synthesized to obtain the deformation gradient value of the dam slope displacement field grid node. The deformation gradient value of the dam slope displacement field grid node is compared point by point with a first deformation threshold, which is exemplarily set to 2 mm / m. When the deformation gradient value of a point exceeds the first deformation threshold, the 5×5 abnormal area grid region is marked as a potential abnormal area. Adjacent potential abnormal areas are merged, and isolated areas with an area smaller than 10 square meters (exemplary) are removed. The abnormal areas exceeding the first deformation threshold are output.

[0080] It should be noted that the process for setting the first deformation threshold is as follows: the threshold range for concrete dam foundations is set to 1.5-2.5 mm / m, and for earth-rock dams it is set to 2.5-3.5 mm / m; the value is adjusted in conjunction with the project's operating years, with the lower limit taken for the first 10 years, the median for 10-20 years, and the upper limit for over 20 years; the 95th percentile value is taken as an example for statistical reference based on historical monitoring data; the first deformation threshold is set to an example value of 2 mm / m.

[0081] S082 performs multi-angle encrypted scanning of the anomalous area to obtain the original radar echo data of the anomalous area, and performs phase calculation and coherence analysis to generate a polarization interferometric phase map.

[0082] After obtaining the original radar echo data by performing multi-angle encrypted scanning of the abnormal area, the terrain phase is eliminated by using the repeating orbit differential interferometry technique: historical reference radar data is selected as the master image and the current radar data is selected as the slave image. The differential interferogram is generated by performing conjugate product operation on the complex coherence matrices of the master image and the slave image.

[0083] The topographic phase component is calculated based on pre-stored elevation benchmark data of the anomalous area. The topographic phase component is removed from the differential interferogram to obtain the entangled phase field. The entangled phase field (range -π to +π) after removing the topographic phase component is subjected to phase unwrapping processing: the minimum cost flow algorithm is used to divide the entangled phase field into a regular grid network with the same grid size as the dam slope displacement field; the phase gradient values ​​of adjacent regular grid nodes are calculated, and a regular grid network flow graph with the absolute value of the phase gradient difference as the weight is constructed; the position with the minimum phase change is determined as the source point, and the position with the maximum phase change is determined as the sink point; the Ford-Fulkerson algorithm is applied to solve for the minimum cutting path; the phase difference values ​​of adjacent regular grid nodes are integrated along the direction of the minimum cutting path, and when the cumulative absolute value of the phase difference exceeds 2π, an integer multiple of 2π phase compensation is added; a continuously distributed unentangled phase field is generated, and a polarimetric interferometric phase map with the deformation phase value as the core parameter is output.

[0084] S10, the polarization interferometric phase map is subjected to three-level dynamic classification and coding processing to form an adaptive data stream, and the reference point drift component is obtained through the dual-mode observation pier to obtain the net deformation set;

[0085] S101, calculate the deformation gradient magnitude of the polarimetric interferometric phase map and perform vector synthesis to obtain the polarimetric interferometric deformation gradient distribution map; perform three-level dynamic classification to obtain classified and coded polarimetric interferometric data;

[0086] Specifically, such as Figure 3 As shown, the deformation phase values ​​in the polarimetric interferometric phase map are extracted, and the deformation gradient amplitude is calculated according to the grid node distribution of the dam slope displacement field. A 3×3 sliding window is used to traverse the polarimetric interferometric phase map; the deformation gradient components in the plane and elevation directions are synthesized, and the vector amplitude is obtained to obtain the polarimetric interferometric deformation gradient distribution map.

[0087] A three-level classification threshold is set, with an example first-level threshold of 1 mm / m and a second-level threshold of 3 mm / m. The gradient magnitude of each grid node in the polarimetric interferometric deformation gradient distribution map is compared point-by-point with the three-level classification threshold: gradient magnitudes less than the first-level threshold are marked as normal, those between the first and second-level thresholds are marked as warning, and those greater than the second-level threshold are marked as emergency. Morphological closing operations are performed on the classification results to eliminate isolated noise points, outputting polarimetric interferometric data containing classification codes (example codes: normal class 00, warning class 01, emergency class 10).

[0088] It should be noted that in this embodiment, the setting process for the first and second level thresholds is as follows: based on the range of concrete dams, the threshold is set to an exemplary 1.5-2.5 mm / m, and for earth-rock dams, it is set to an exemplary 2.5-3.5 mm / m; the values ​​are adjusted in conjunction with the years of operation of the project, with the lower limit of the range taken for newly built projects within the exemplary 10 years of operation, the median value taken for exemplary 10-20 years, and the upper limit taken for exemplary projects over 20 years; referring to the gradient distribution of dam slope deformation under historical normal operating conditions, the exemplary 95th percentile value is taken as a statistical reference; the comprehensive engineering safety level coefficient is corrected, with the exemplary coefficient for important projects being 0.9, for general projects being 1.0, and for minor projects being 1.1; the exemplary value of the first level threshold is 1 mm / m, and the exemplary value of the second level threshold is 3 mm / m.

[0089] Furthermore, the expression for calculating the deformation gradient amplitude based on the grid node distribution of the dam slope displacement field is as follows:

[0090] ;

[0091] in, It is the magnitude of the deformation gradient. It is eastward ( (Direction) Deformation gradient components, It is the phase field The partial derivative, It is eastward ( Spatial differential operator of axis), It is north ( (axis) deformation gradient components, It is north ( Spatial differential operator of axis), It is in the direction of elevation ( (axis) deformation gradient components, It is in the direction of elevation ( Spatial differential operator of axis.

[0092] S102 performs adaptive encoding on the polarimetric interferometric data to obtain compressed polarimetric interferometric data; then performs bandwidth adaptive encapsulation on the compressed polarimetric interferometric data to output an adaptive data stream.

[0093] Specifically, classification labels (normal class 00, early warning class 01, emergency class 10) are extracted from the polarimetric interferometric data of classification coding. A run-length encoding algorithm is used to compress consecutive identical coded regions: the grid node sequence of the dam slope displacement field is scanned, the number of nodes with consecutive identical classification codes is counted, and coded values ​​and repetition data pairs are generated. An exemplary compression rate of up to 60% is achieved. Differential coding is then performed on the compressed consecutive identical coded regions, recording the amount of coding change rather than the absolute value of adjacent consecutive identical coded region pairs.

[0094] In this embodiment, the encapsulation strategy is dynamically selected based on the current network bandwidth: when the bandwidth is greater than the exemplary 10Mbps, a lossless encapsulation format is used, encapsulating complete metadata (including timestamps, coordinate systems, and precision indicators); when the bandwidth is less than or equal to the exemplary 10Mbps, a lossy encapsulation format is used, retaining only the coordinates of emergency-type regions and deformation gradient magnitudes. Error correction check codes are added during the encapsulation process; the exemplary method uses the CRC-16 check algorithm, with 2 bytes of check bits appended to each frame of data. The output is an adaptive data stream containing compressed data, an encapsulation format identifier, and check codes.

[0095] S103 calculates the benchmark drift component based on adaptive data stream and environmental strain data collected in real time through dual-mode observation piers; performs real-time error correction on the benchmark drift component and outputs drift compensation parameters;

[0096] Specifically, the classification labels (normal class 00, early warning class 01, emergency class 10) and encapsulated metadata (timestamp, coordinate system, deformation gradient amplitude) in the classified polarimetric interferometric data contained in the compressed polarimetric interferometric data in the adaptive data stream are analyzed to trigger the graphene strain sensing layer built into the dual-mode observation pier to start data acquisition, with an exemplary sampling frequency of 20Hz. The resistance change output by the graphene strain sensing layer is read and converted into a micro-strain value through a calibration curve, with an exemplary strain measurement range of ±500με. The strain difference between adjacent sampling periods is acquired in real time, and when the strain difference between sampling periods exceeds an exemplary 5με / second, it is marked as a valid temperature deformation signal. Combined with the thermal expansion coefficient of the dual-mode observation pier structure, the exemplary thermal expansion coefficient of the concrete base is taken as 9×10. -6 / ℃, calculate the three-dimensional thermal drift components of the dual-mode observation pier benchmark. A moving average filter is used to eliminate high-frequency noise; the window width is set to an example of 10 sampling points. The output includes drift compensation parameters in the east, north, and altitude directions.

[0097] In this embodiment, the expression for calculating the three-dimensional thermal drift component of the dual-mode observation pier reference point is as follows:

[0098] ;

[0099] in, It is the three-dimensional thermal drift component of the dual-mode observation pier reference point. The coefficient of thermal expansion of the concrete base is taken as 9 × 10⁻⁶ for example. -6 / ℃, It is the temperature change of the concrete base. It is the characteristic dimension vector of the concrete base structure.

[0100] S104, extract environmental interference components from drift compensation parameters and adaptive data stream; perform differential calculation on environmental interference components based on net deformation solution algorithm to obtain net deformation set.

[0101] Specifically, the drift components in the east, north, and elevation directions are extracted from the drift compensation parameters and time-aligned with the deformation gradient magnitude in the adaptive data stream. The corresponding east, north, and elevation drift components are vector-subtracted from the deformation gradient magnitude to eliminate temperature-induced reference point displacement interference. The rate of change of deformation between adjacent time slices is calculated using a sliding window difference method, with an example window width of 5 sampling points. Median filtering is applied to the difference results to remove transient noise interference; an example filtering window is a 3×3 grid. The output includes net deformation sets in the east, north, and elevation directions.

[0102] S12, map the net deformation set to the BIM model, construct a three-dimensional deformation situation map of color temperature gradient, trigger early warning display for abnormal areas exceeding the second deformation threshold, and generate a three-dimensional early warning map.

[0103] S121, transform the net deformation set to the engineering coordinate system under the BIM model to obtain aligned net deformation data; map the aligned net deformation data to the BIM model mesh nodes through the BIM model mapping algorithm to generate a BIM model carrying displacement attributes;

[0104] Specifically, such as Figure 4 As shown, the WGS84 coordinate system 3D coordinate data of the dam slope (east / north / height) in the net deformation set is read. The pre-stored engineering coordinate system transformation parameters of the BIM model are called, and a seven-parameter Helmholtz transformation is performed to convert the coordinates to the BIM engineering coordinate system. The coordinate system transformation parameters include, for example, three translations, three rotation angles, and one scale factor. The transformed WGS84 coordinate system 3D coordinate data of the dam slope (east / north / height) is matched with BIM mesh nodes using a BIM model mapping algorithm: the Euclidean distance between the net deformation data points and the BIM mesh nodes is calculated. When the distance is less than the example 0.1 meters, the deformation is assigned to the corresponding BIM node. For unmatched BIM mesh nodes, an inverse distance weighted interpolation algorithm is used to calculate the deformation of the unmatched BIM mesh nodes. The search radius is set to 3 meters for example, and the inverse distance weighting exponent is 2. A BIM model with displacement attributes is generated.

[0105] S122, perform displacement-color temperature mapping calculation on BIM model data with displacement attributes, generate a three-dimensional deformation situation map, and identify and mark abnormal areas that exceed the second deformation threshold to obtain a three-dimensional deformation situation map of the marked abnormal areas.

[0106] Specifically, the eastward, northward, and elevation displacements of each grid node in the BIM model with displacement attributes are extracted, and the composite displacement modulus is calculated. Composite displacement modulus values ​​less than the exemplary 2 mm are mapped to blue, values ​​between 2 and 5 mm are mapped to yellow, and values ​​greater than 5 mm are mapped to red. The color temperature data is mapped onto the BIM model surface using a graphics rendering engine to generate a 3D deformation status map. Grid nodes in the 3D deformation status map whose composite displacement modulus values ​​exceed a second deformation threshold (exemplarily set to 5 mm) are identified. Adjacent abnormal nodes are merged, and isolated areas smaller than the exemplary 5 square meters are removed. Abnormal area boundaries are marked with red borders in the 3D deformation status map, and the marked abnormal areas are output as a 3D deformation status map.

[0107] It should be noted that in this embodiment, the process of setting the second deformation threshold is as follows: based on the exemplary concrete dam benchmark value, it is set to 4-6 mm, and for the exemplary earth-rock dam, it is set to 6-8 mm; the value is adjusted in combination with the engineering operation years, taking the lower limit for the exemplary operation within 10 years, the median value for 10-20 years, and the upper limit for more than 20 years; 80% of the exemplary maximum allowable deformation is used as a control reference; and finally, the second deformation threshold is determined to be 5 mm.

[0108] S123, perform deformation gradient and historical trend analysis on the three-dimensional deformation situation map of the marked abnormal area, generate early warning level parameters, and perform dynamic early warning annotation to obtain a three-dimensional early warning map.

[0109] Specifically, the composite displacement modulus values ​​of each BIM grid node in the 3D deformation situation map of the anomaly area are extracted, and the displacement rate change rate over an exemplary 72-hour period is calculated. An exemplary three-level early warning judgment rule is set: a displacement rate change rate less than 0.2 mm / hour is a green warning, 0.2-0.5 mm / hour is a yellow warning, and greater than 0.5 mm / hour is a red warning. Displacement acceleration trends are identified through time series analysis; the warning level is raised when the displacement increment exceeds 0.1 mm for three consecutive monitoring cycles. Dynamic warning indicators are overlaid on the 3D deformation situation map: a green warning is displayed with a static green border, a yellow warning with a 1Hz flashing yellow border, and a red warning with a 2Hz flashing red border overlaid with a pulse warning mark. A 3D early warning map containing warning level parameters and dynamic annotation information is output.

[0110] In another possible embodiment, the present invention also provides a computer device including a memory and a processor, the memory storing a computer program, wherein: when the computer program is executed by the processor, it implements the dam slope deformation monitoring method based on the fusion of measurement robot and GNSS as described in the present invention.

[0111] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0112] In another possible embodiment, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements the dam slope deformation monitoring method based on the fusion of measurement robot and GNSS as described in the present invention.

[0113] The computer storage medium 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 Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0114] In summary, this invention achieves high-precision spatiotemporal unification of GNSS and surveying robot data by constructing a fiber-optic synchronized spatiotemporal reference network. The ultra-high synchronization accuracy and anti-interference characteristics provide a reliable benchmark for multi-source sensor fusion, significantly improving the data consistency of dam slope deformation monitoring. Furthermore, through the dynamic generation of three-dimensional early warning maps, net deformation data is deeply integrated with the BIM model. Utilizing color temperature gradient mapping and intelligent early warning mechanisms, closed-loop management from deformation detection to engineering emergency response is achieved, greatly improving the efficiency of disaster early warning response. At the same time, through hardware-algorithm collaborative optimization, excellent monitoring accuracy can still be maintained under complex environmental conditions.

[0115] Several embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, and are not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technological improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for monitoring dam slope deformation based on the fusion of a measurement robot and GNSS, characterized in that, include: By using bend-resistant special optical fiber, the dual-mode observation pier of the GNSS receiver and the prism target of the measurement robot is connected to the GNSS reference station to obtain an optical fiber transmission network; The atomic clock signal of the GNSS reference station is transmitted using an optical fiber transmission network, and signal synchronization and delay correction are performed to obtain a spatiotemporal reference network; Based on a spatiotemporal reference network, the measurement robot emits anti-interference laser pulses toward the prism target of the dual-mode observation pier; Real-time acquisition of environmental vibration data, adjustment of the emission angle of anti-interference laser pulses to offset the vibration effect to obtain vibration compensation data, and combined with a spatiotemporal reference network to output a vibration compensation coordinate set; A weighted adaptive fusion of the vibration compensation coordinate set and the spatiotemporal reference network is performed to output the dam slope displacement field. The deformation gradient analysis algorithm is used to compare the dam slope displacement field with the first deformation threshold and detect abnormal areas that exceed the first deformation threshold. Multi-angle encrypted scanning is performed on the abnormal area to obtain the original radar echo data of the abnormal area, and phase calculation and coherence analysis are performed to generate a polarimetric interferometric phase map. The polarimetric interferometric phase map is subjected to three-level dynamic classification and coding to form an adaptive data stream, and the reference point drift component is obtained through dual-mode observation piers to obtain the net deformation set; The net deformation set is transformed to the engineering coordinate system of the BIM model to obtain aligned net deformation data, and then mapped to the BIM model mesh nodes through the BIM model mapping algorithm to generate a BIM model with displacement attributes. Displacement-color temperature mapping calculation is performed on BIM model data with displacement attributes to generate a three-dimensional deformation status map, and abnormal areas exceeding the second deformation threshold are identified and marked to obtain a three-dimensional deformation status map of the marked abnormal areas. The deformation gradient and historical trend analysis of the three-dimensional deformation situation map of the marked abnormal area are performed to generate early warning level parameters, and dynamic early warning annotation is performed to obtain a three-dimensional early warning map.

2. The method for monitoring dam slope deformation based on the fusion of a measurement robot and GNSS as described in claim 1, characterized in that, The specific steps for performing variable-weight adaptive fusion of the vibration compensation coordinate set and the spatiotemporal reference network to output the dam slope displacement field are as follows: Based on the GNSS receiver measurement data of the dual-mode observation pier in the vibration compensation coordinate set and spatiotemporal reference network, multi-source data alignment is performed to obtain spatiotemporally aligned data. Dynamic weight allocation is performed on the spatiotemporally aligned data to obtain the optimal weight ratio, and the displacement field of the dam slope is obtained by weighted fusion calculation through the displacement field solution model.

3. The method for monitoring dam slope deformation based on the fusion of a measurement robot and GNSS as described in claim 2, characterized in that, The three-level dynamic classification and encoding process for the polarization interferometric phase map to form an adaptive data stream is performed as follows: The deformation gradient magnitudes of the polarimetric interferometric phase map are calculated and vectorized to obtain the polarimetric interferometric deformation gradient distribution map. Then, a three-level dynamic classification is performed to obtain classified and coded polarimetric interferometric data. Adaptive encoding is performed on the classified polarimetric interferometric data to obtain compressed polarimetric interferometric data, which is then encapsulated with bandwidth adaptation to output an adaptive data stream.

4. The method for monitoring dam slope deformation based on the fusion of a measurement robot and GNSS as described in claim 3, characterized in that, The net deformation set is obtained by analyzing the reference point drift component using a dual-mode observation pier, and the specific steps are as follows: Based on adaptive data stream, environmental strain data is collected in real time through dual-mode observation piers, and the drift component of the reference point is calculated for real-time error correction, and drift compensation parameters are output. Environmental interference components are extracted from the drift compensation parameters and adaptive data stream, and differential calculation is performed using the net deformation solution algorithm to obtain the net deformation set.

5. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the dam slope deformation monitoring method based on the fusion of measurement robot and GNSS as described in any one of claims 1 to 4.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the dam slope deformation monitoring method based on the fusion of measurement robot and GNSS as described in any one of claims 1 to 4.

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