Dam slope deformation monitoring method based on fusion of measuring robot and GNSS (Global Navigation Satellite System)

Abstract

The invention relates to a dam slope deformation monitoring method based on fusion of a measuring robot and a GNSS (Global Navigation Satellite System). The method comprises the following steps: performing signal synchronization and delay correction on a dual-mode observation pillar of a GNSS and a prism target of a measurement robot, and constructing a space-time reference network; controlling the measurement robot to emit an anti-interference laser pulse, counteracting environment vibration, and outputting a vibration compensation coordinate set; obtaining a dam slope displacement field through variable weight adaptive fusion processing; performing encryption scanning on an abnormal area exceeding a first deformation threshold in the displacement field to generate a polarization interferometric phase diagram, forming an adaptive data stream through three-stage dynamic classification coding, calculating a reference point drift component in combination with a dual-mode observation pillar, and extracting a net deformation set; and finally, mapping the net deformation set to a BIM model, constructing a color temperature gradient three-dimensional deformation situation map, triggering early warning for an area exceeding a second deformation threshold value, and generating a three-dimensional early warning map. According to the method, high-precision space-time unification of multi-source data can be realized, and the monitoring consistency and the anti-interference capability in a complex environment are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of dam slope deformation monitoring, in particular to a dam slope deformation monitoring method based on fusion of measurement robots and GNSS. BACKGROUND

[0002] Dam slope deformation monitoring refers to the process of using specialized instruments and techniques to continuously and systematically measure and analyze the displacement, settlement, and inclination changes of the dam slope and body, 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, and the collaborative application of Global Navigation Satellite System (GNSS) and measurement robots (such as high-precision total stations) has become a research hotspot. The existing technology usually establishes a large-scale absolute coordinate reference frame with the help of GNSS reference stations, and combines the total station to implement millimeter-level precision local measurement on key areas of the dam slope, thereby realizing the organic combination of deformation information at macro and micro levels. This combined measurement method takes advantage of the stability of GNSS in large-scale and continuous monitoring, and the sensitivity of the total station in high-precision and high-resolution local measurement, providing comprehensive data support for dam safety status assessment.

[0004] However, the reliability and accuracy of existing technology in complex environments still face significant challenges. First, due to the lack of a high-precision unified time-space reference, there is a millisecond-level time synchronization error and spatial registration deviation between GNSS and the total station, making it difficult to deeply fuse multi-source sensor data, and the displacement field reconstruction error is significant in areas with large deformation gradients, seriously affecting the consistency and reliability of the monitoring data; secondly, in the face of strong wind, mechanical vibration or significant temperature difference and other interference conditions, the existing system lacks effective dynamic error suppression and compensation capability, GNSS multipath effect error increases to centimeter level, and total station angle measurement accuracy is also significantly deteriorated by vibration, making it difficult to guarantee the stability and accuracy of monitoring data in complex environments; in addition, the existing method has not realized the deep fusion of deformation data and engineering model, lacks closed-loop management capability from data to decision, and cannot support dynamic visualization and intelligent early warning of deformation trend, limiting the further improvement of disaster early warning response efficiency. SUMMARY

[0005] The purpose of the present application is to provide a dam slope deformation monitoring method based on fusion of measurement robots and GNSS, which can realize high-precision spatio-temporal unification of GNSS and measurement robot data, provide a reliable reference for multi-source sensor fusion, significantly improve the data consistency of dam slope deformation monitoring; and can effectively suppress dynamic error to guarantee the stability and accuracy of monitoring data in complex environments; also has the closed-loop management capability from data to decision, improving the efficiency of disaster early warning response.

[0006] To achieve the above object, the technical scheme adopted by the present application is specifically as follows:

[0007] In the first aspect, the present application provides a dam slope deformation monitoring method based on fusion of measurement robot and GNSS, which comprises the following steps:

[0008] Signal synchronization and delay correction are performed on the dual-mode observation pier of GNSS and measurement robot prism target to obtain a space-time reference network;

[0009] Based on the space-time reference network, the measurement robot transmits anti-interference laser pulses to the dual-mode observation pier and offsets environmental vibration to output a vibration-compensated coordinate set;

[0010] The vibration-compensated coordinate set and the space-time reference network are adaptively fused with variable weights to output a dam slope displacement field;

[0011] The abnormal regions in the dam slope displacement field that exceed a first deformation threshold are scanned in detail to generate a polarized interference phase map;

[0012] The polarized interference phase map is processed by three-level dynamic classification coding to form an adaptive data stream, and the reference point drift component is obtained through the dual-mode observation pier to obtain a net deformation set;

[0013] The net deformation set is mapped to a BIM model to construct a color temperature gradient three-dimensional deformation pattern, and an abnormal region that exceeds a second deformation threshold triggers an early warning display to generate a three-dimensional early warning atlas.

[0014] As a preferred embodiment of the present application, the acquisition sub-step of the space-time reference network is specifically as follows,

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

[0016] The atomic clock signal of the GNSS reference station is transmitted through the optical fiber transmission network, and signal synchronization and delay correction are performed to obtain the space-time reference network.

[0017] As a preferred embodiment of the present application, when the measurement robot transmits anti-interference laser pulses to the dual-mode observation pier, the specific steps of offsetting environmental vibration and outputting a vibration-compensated coordinate set are as follows:

[0018] Real-time collection of environmental vibration data is performed to adjust the emission angle of the anti-interference laser pulse;

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

[0020] Based on the vibration compensation data, the vibration-compensated coordinate set is output in combination with the space-time reference network.

[0021] As a preferred embodiment of the present application, the vibration-compensated coordinate set is adaptively fused with the time-space reference network with variable weights, and the specific steps for outputting the dam slope displacement field are as follows:

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

[0023] The time-space aligned data is subjected to dynamic weight distribution to obtain an optimal time-space aligned data weight ratio; based on the optimal time-space aligned data weight ratio, weighted fusion calculation is performed through a displacement field solving model to obtain the dam slope displacement field.

[0024] As a preferred embodiment of the present application, the method for obtaining the polarimetric interferometric phase map is as follows:

[0025] The dam slope displacement field is compared and detected with the first deformation threshold value through a deformation gradient analysis algorithm, and an abnormal area exceeding the first deformation threshold value is output.

[0026] The abnormal area is subjected to multi-angle encryption scanning to obtain original radar echo data of the abnormal area, and phase solving and coherence analysis are performed to generate a polarimetric interferometric phase map.

[0027] As a preferred embodiment of the present application, the polarimetric interferometric phase map is subjected to three-level dynamic classification and coding processing to form an adaptive data stream, and the specific steps are as follows,

[0028] The deformation gradient amplitude of the polarimetric interferometric phase map is calculated and subjected to vector synthesis to obtain a polarimetric interferometric deformation gradient distribution map; three-level dynamic classification is performed to obtain polarimetric interferometric data with classification codes.

[0029] The polarimetric interferometric data is subjected to adaptive coding processing to obtain compressed polarimetric interferometric data.

[0030] The compressed polarimetric interferometric data is subjected to bandwidth adaptive packaging to output an adaptive data stream.

[0031] As a preferred embodiment of the present application, the method for obtaining the net deformation set is 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 reference point drift component is subjected to real-time error correction, and a drift compensation parameter is output.

[0034] The drift compensation parameter and the adaptive data stream are subjected to environmental interference component extraction.

[0035] The net deformation set is converted to an engineering coordinate system under a BIM model to obtain aligned net deformation data.

[0036] As a preferred embodiment of the present application, the method for generating the three-dimensional early warning map specifically comprises:

[0037] The net deformation set is converted to an engineering coordinate system under a BIM model to obtain aligned net deformation data; the aligned net deformation data is mapped to a BIM model grid node through a BIM model mapping algorithm to generate a BIM model carrying displacement attributes;

[0038] The BIM model data carrying displacement attributes is subjected to displacement-color temperature mapping calculation to generate a three-dimensional deformation trend map, and an abnormal region exceeding a second deformation threshold is identified and labeled to obtain a three-dimensional deformation trend map of a labeled abnormal region;

[0039] The three-dimensional deformation trend map of the labeled abnormal region is subjected to deformation gradient and historical trend analysis to generate early warning grade parameters, and dynamic early warning labeling is performed to obtain a three-dimensional early warning map.

[0040] In a second aspect, the present application further provides a computer device comprising a memory and a processor, and the memory stores a computer program, wherein the computer program is executed by the processor to implement any step of the dam slope deformation monitoring method based on fusion of a measurement robot and GNSS according to the first aspect of the present application.

[0041] In a third aspect, the present application further provides a computer readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement any step of the dam slope deformation monitoring method based on fusion of a measurement robot and GNSS according to the first aspect of the present application.

[0042] In summary, the present application has the following beneficial effects:

[0043] 1. The present application breaks through the technical bottleneck of millisecond-level time synchronization and spatial registration deviation between GNSS and measurement robots by constructing a time-space reference network based on optical fiber synchronization, realizes high-precision space-time unification of GNSS and measurement robot data, and provides a reliable reference for multi-source sensor fusion with ultra-high synchronization accuracy and anti-interference characteristics, significantly improves the data consistency of dam slope deformation monitoring, greatly improves the displacement field reconstruction accuracy, especially in the key area with large deformation gradient, effectively guarantees the consistency and reliability of the monitoring data.

[0044] 2. The present application is based on the synergistic optimization of hardware and algorithm, which can effectively offset the influence of environmental interference such as strong wind, mechanical vibration and temperature difference deformation; the system can dynamically suppress the deterioration of GNSS multipath error and total station angle measurement error, and output "net deformation" data after vibration compensation and environmental error correction, so as to maintain excellent monitoring accuracy and data stability in complex and harsh environment.

[0045] 3. The present application dynamically generates a three-dimensional deformation trend map with color temperature gradient mapping by deeply fusing net deformation data with BIM model, realizes intuitive and visual expression of deformation information; combined with intelligent early warning mechanism, the system can automatically identify abnormal deformation area and carry out hierarchical early warning, realizes the whole process closed-loop management from deformation detection, analysis to engineering emergency response, thereby greatly improves the accuracy and response efficiency of disaster warning. BRIEF DESCRIPTION OF DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0047] Figure 1 The flowchart of the present application is shown in the figure.

[0048] Figure 2 The step flowchart of generating the space-time reference network in the embodiment of the present application is shown in the figure.

[0049] Figure 3 The step flowchart of obtaining adaptive data stream in the embodiment of the present application is shown in the figure.

[0050] Figure 4 The step flowchart of outputting three-dimensional early warning atlas in the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0051] The subject matter described herein will now be discussed with reference to example implementations. It should be understood that the discussion of these implementations is merely meant to provide a better understanding of the subject matter described herein and is not meant to restrict the scope, applicability, or examples set forth in the claims. Changes to the function and arrangement of elements can be made without departing from the scope of the subject matter described herein. Various examples can omit, substitute, or add various procedures or components as appropriate. For instance, the methods described can be performed in an order different than that described, and various steps can be added, omitted, or combined. Also, features described with respect to some examples can be combined in other examples.

[0052] Second, the "one embodiment" or "an embodiment" referred to herein means a specific feature, structure, characteristic, or combination of features and / or characteristics described herein that can be included in at least one implementation of the present application. The various appearances of "in one embodiment" or "an embodiment" in the specification are not necessarily all referring to the same embodiment.

[0053] As shown in Figure 1 The embodiment provides a dam slope deformation monitoring method based on fusion of measurement robot and GNSS.

[0054] S02, signal synchronization and delay correction are performed on the dual-mode observation pier of the GNSS and the measurement robot prism target, and a space-time reference network is obtained.

[0055] Specifically, as shown in Figure 2 S02 further includes a sub-step (acquisition step of space-time reference network):

[0056] S021, the dual-mode observation pier of the GNSS receiver and the measurement robot prism target is connected with the GNSS reference station through the anti-bending special optical fiber, and an optical fiber transmission network is obtained.

[0057] Specifically, the installation positions of the dual-mode observation pier of the GNSS receiver and the measurement robot prism target are selected on the dam slope surface, the anti-bending special optical fiber is used to connect the optical fiber interface of the dual-mode observation pier and the GNSS reference station, the OTDR is used to test the optical fiber link loss, the atomic clock signal generator of the GNSS reference station is connected at the GNSS reference station end, the carrier phase observation value and the time signal are transmitted at the STM-1 standard rate, the telecommunication signal is restored through the photoelectric converter at the dual-mode observation pier end, the transmission delay is calculated by using the bidirectional time comparison method, the physical connection of the optical fiber transmission network is completed, and the optical fiber transmission network is obtained.

[0058] S022, the atomic clock signal of the GNSS reference station is transmitted through the optical fiber transmission network, and signal synchronization and delay correction are performed, and a space-time reference network is obtained.

[0059] Specifically, the atomic clock signal of the GNSS reference station is transmitted through the optical fiber transmission network, the atomic clock signal is received at the dual-mode observation pier end and the signal arrival time stamp is recorded, the signal sending time stamp is recorded at the GNSS reference station end, the bidirectional time comparison method is used to obtain the optical fiber transmission delay, the exemplary delay amount is ≤5ns, the signal arrival time stamp is temperature compensated, the exemplary compensation coefficient is 0.03ns / ℃, the compensated signal arrival time stamp is time aligned with the GNSS receiver observation data, signal synchronization and delay correction are completed, and a space-time reference network is obtained.

[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, is the vibration displacement amount at the i th sampling time point, is the vibration displacement amount at the i th sampling time point, is the vibration displacement amount at the i th sampling time point, is the vibration displacement amount at the i th sampling time point, is the fixed sampling time interval, is the vibration displacement amount at the i th sampling time point, is the filtered three-axis instantaneous acceleration value at the i th sampling time point, / / is the vibration displacement amount at the i th sampling time point, is the filtered three-axis instantaneous acceleration value at the i th sampling time point, / / is the vibration displacement amount at the i th sampling time point, is the filtered three-axis instantaneous acceleration value at the i th sampling time point, is the discrete sampling time point sequence variable.

[0069] S06, performing variable weight adaptive fusion on the vibration compensation coordinate set and the space-time reference network to output a dam slope displacement field;

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

[0071] S061, based on the obtained GNSS receiver measurement data of the dual-mode observation pier in the vibration compensation coordinate set and the space-time reference network, performing multi-source data alignment and obtaining space-time aligned data;

[0072] Extract the UTC time stamp of the vibration compensation coordinate set and the GPS time stamp of the GNSS receiver measurement data of the dual-mode observation pier in the space-time reference network, and use a time alignment algorithm to unify the time reference of the vibration compensation coordinate set and the GNSS receiver measurement data of the dual-mode observation pier in the space-time reference network to the GPST time scale system; read the carrier phase observation value output by the GNSS receiver measurement data of the dual-mode observation pier, obtain GNSS three-dimensional coordinate data, convert the spatial coordinates of the vibration compensation coordinate set to the WGS84 coordinate system, and perform spatial registration with the GNSS three-dimensional coordinate data. The seven-parameter coordinate conversion parameters for converting the spatial coordinates of the vibration compensation coordinate set to the WGS84 coordinate system are calculated by least squares adjustment; weight fusion is performed on the time-aligned vibration compensation coordinate set and the GNSS three-dimensional coordinate data, and the exemplary weight distribution ratio is 60% for laser measurement data and 40% for GNSS three-dimensional coordinate data. Output space-time aligned data;

[0073] It should be noted that the GNSS receiver measurement data of the dual-mode observation pier in the space-time reference network is derived from: the GNSS receiver of the dual-mode observation pier continuously receives the L1 / L2 frequency band signals of multiple GNSS satellites, records the carrier phase and pseudorange observation values, receives the differential correction data of the GNSS reference station through the optical fiber transmission network, uses the dual-frequency ionosphere elimination combination algorithm for real-time dynamic differential positioning solution, fuses the carrier phase and pseudorange observation values using Kalman filtering, and outputs the GNSS three-dimensional coordinate data synchronized with the space-time reference network time to obtain the GNSS receiver measurement data of the dual-mode observation pier in the space-time reference network.

[0074] S062, dynamic weight allocation is performed on the space-time alignment data to obtain an optimal space-time alignment data weight ratio; based on the optimal space-time alignment data weight ratio, weighted fusion calculation is performed through a displacement field solving model to obtain a dam slope displacement field.

[0075] The precision indicators of the vibration compensation coordinate set and the GNSS three-dimensional coordinate data in the space-time alignment data are extracted, the variance components are inversely calculated according to the precision indicators of the vibration compensation coordinate set and the GNSS three-dimensional coordinate data in the space-time alignment data, the initial space-time alignment data weight is calculated according to the inverse weight principle of variance, and the space-time alignment data weight is dynamically adjusted in combination with the displacement field change rate. When the dam slope displacement rate exceeds an example value of 5 mm / hour, the GNSS three-dimensional coordinate data weight is increased to an example value of 0.4, the vibration compensation coordinate set weight is adjusted to 0.6 accordingly, and the optimal space-time alignment data weight ratio is output.

[0076] The optimal space-time alignment data weight ratio is input into the displacement field solving model, the displacement field solving model uses a grid point interpolation algorithm, and the example grid spacing of the dam slope displacement field is 0.5 meters. The coordinate difference values of the vibration compensation coordinate set and the GNSS three-dimensional coordinate data at the dam slope displacement field grid nodes are fused according to the optimal space-time alignment data weight ratio, the vibration compensation coordinate set has an example weight of 0.6 in the contribution value at the dam slope displacement field grid nodes, and the GNSS three-dimensional coordinate data has an example weight of 0.4 in the contribution value. The displacement amount of the unmeasured point is calculated through Kriging interpolation, and the example range parameter is set to 3 meters. The fused dam slope displacement field grid node displacement amount is smoothed, a 9-point moving average filter is used to eliminate high-frequency noise, and the dam slope displacement field is output.

[0077] S08, the abnormal area exceeding the first deformation threshold in the dam slope displacement field is scanned to generate a polarized interference phase diagram;

[0078] S081, the dam slope displacement field is compared and detected with the first deformation threshold through a deformation gradient analysis algorithm, and the abnormal area exceeding the first deformation threshold is output;

[0079] Specifically, the three-dimensional displacement of the dam slope grid node of the dam slope displacement field is extracted, and the dam slope displacement change rate between adjacent grid nodes of the dam slope displacement field is calculated as the deformation gradient value; a 3x3 sliding window is used to traverse the entire dam slope displacement field, and the ratio of the displacement difference between the center point of the sliding window and the eight surrounding nodes to the node spacing is taken as the plane deformation gradient component; the elevation direction deformation gradient is calculated by the ratio of the adjacent elevation difference to the vertical spacing; the plane deformation gradient component and the elevation direction 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 with the first deformation threshold value point by point, and the first deformation threshold value is exemplarily taken as 2 mm / m. When the deformation gradient value of a certain point exceeds the first deformation threshold value, the 5x5 abnormal area grid area where the point is located is marked as a potential abnormal area. The adjacent potential abnormal areas are merged and processed, and isolated areas with an area less than exemplarily 10 square meters are removed, and the abnormal areas exceeding the first deformation threshold value are output.

[0080] It should be noted that the setting process of the first deformation threshold value is: the threshold value range of the exemplarily concrete dam foundation is set to 1.5-2.5 mm / m, and the earth-rock dam is set to 2.5-3.5 mm / m; the value is adjusted in combination with the engineering operation period, and the lower limit is taken within 10 years, the median value is taken within 10-20 years, and the upper limit is taken above 20 years; the exemplarily 95% quantile value is taken as the statistical reference according to the historical monitoring data; the first deformation threshold value is exemplarily taken as 2 mm / m.

[0081] S082, the abnormal area is scanned from multiple angles to obtain the original radar echo data of the abnormal area, and phase unwrapping and coherence analysis are performed to generate a polarized interferometric phase map.

[0082] After obtaining the original radar echo data by scanning the abnormal area from multiple angles, the terrain phase is eliminated by using the repeat track differential interferometric technique: the historical reference radar data is selected as the main image, and the current radar data is selected as the slave image; the complex coherence matrix of the main image and the slave image is generated by conjugate multiplication operation to generate a differential interferogram.

[0083] The terrain phase component is calculated based on the pre-stored elevation reference data of the abnormal area, and the terrain phase component is removed from the differential interferogram to obtain a wrapped phase field. The wrapped phase field after removing the terrain phase component (value range: -π to +π) is subjected to phase unwrapping processing: the wrapped phase field is divided into a regular grid network consistent with the grid size of the dam slope displacement field by using the minimum cost flow algorithm; the phase gradient values of adjacent regular grid nodes are calculated, and a regular grid network flow graph weighted by the absolute value of the phase gradient difference 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 the minimum cut path; the adjacent regular grid node phase difference value is integrated in the direction of the minimum cut path, and when the absolute value of the cumulative phase difference exceeds 2π, the phase compensation of an integer multiple of 2π is added; a continuously distributed unwrapped phase field is generated, and a polarimetric interferometric phase image with deformation phase value as the core parameter is output.

[0084] S10, performing three-level dynamic classification coding processing on the polarimetric interferometric phase image to form an adaptive data stream, and obtaining a net deformation set by removing a reference point drift component through a dual-mode observation pier;

[0085] S101, calculating the deformation gradient amplitude of the polarimetric interferometric phase image and performing vector synthesis to obtain a polarimetric interferometric deformation gradient distribution map; performing three-level dynamic classification to obtain polarimetric interferometric data with classification coding;

[0086] Specifically, as shown in Figure 3 the deformation phase value in the polarimetric interferometric phase image is extracted, and the deformation gradient amplitude is calculated according to the distribution of the dam slope displacement field grid nodes. A 3x3 sliding window is used to traverse the polarimetric interferometric phase image; the deformation gradient components in the plane and elevation directions are synthesized to obtain the vector amplitude to obtain a polarimetric interferometric deformation gradient distribution map;

[0087] The three-level classification threshold values are set, and the exemplary first-level threshold value is 1 mm / m, and the second-level threshold value is 3 mm / m. The gradient amplitude of each grid node in the polarimetric interferometric deformation gradient distribution map is compared with the three-level classification threshold values point by point: the gradient amplitude less than the first-level threshold value is marked as normal, the gradient amplitude between the first-level threshold value and the second-level threshold value is marked as pre-warning, and the gradient amplitude greater than the second-level threshold value is marked as emergency. The classification results are subjected to morphological closing operation processing to eliminate isolated noise points, and polarimetric interferometric data containing classification codes (exemplary codes: normal 00, pre-warning 01, and emergency 10) are output.

[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 according to the current network bandwidth: when the bandwidth is greater than 10 Mbps, the lossless encapsulation format is adopted, and the complete metadata (including timestamp, coordinate system, and precision index) is encapsulated; when the bandwidth is less than or equal to 10 Mbps, the lossy encapsulation format is adopted, and only the coordinates of the emergency area and the gradient amplitude are reserved. Error correction check code is added in the encapsulation process, and CRC-16 check algorithm is used as an example. 2 bytes of check bits are appended to each frame of data. The output adaptive data stream contains compressed data, encapsulation format identifier, and check code.

[0095] S103, based on the adaptive data stream and the environmental strain data collected in real time through the dual-mode observation pier, the drift component of the reference point is calculated; the drift component of the reference point is corrected in real time, and the drift compensation parameter is output;

[0096] Specifically, the classification mark (normal class 00, warning class 01, and emergency class 10) and the encapsulated metadata (timestamp, coordinate system, and gradient amplitude) in the classified and encoded polarized interference data in the compressed polarized interference data in the adaptive data stream are parsed, the built-in graphene strain sensing layer of the dual-mode observation pier is triggered to start data collection, and the sampling frequency is 20 Hz as an example. The resistance change amount output by the graphene strain sensing layer is read, which is converted into micro-strain value through the calibration curve, and the strain measurement range is ±500με as an example. The strain difference value of the adjacent sampling period is obtained in real time, and when the strain difference value of the adjacent sampling period exceeds 5με / s as an example, it is marked as an effective temperature deformation signal. Combined with the thermal expansion coefficient of the dual-mode observation pier structure, the thermal expansion coefficient of the concrete base is taken as 9×10 -6 / ℃, the three-dimensional thermal drift component of the reference point of the dual-mode observation pier is calculated. The sliding average filter is used to eliminate high-frequency noise, and the window width is set to 10 sampling points as an example. The drift compensation parameters in the east / north / high directions are output;

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

[0098] ;

[0099] Among them, is the three-dimensional thermal drift component of the reference point of the dual-mode observation pier, is the thermal expansion coefficient of the concrete base, which is taken as 9×10 -6 / ℃ as an example, is the temperature change of the concrete base, is the structural feature size vector of the concrete base.

[0100] S104, the environmental interference component extraction is performed on the drift compensation parameter and the adaptive data stream; the differential calculation is performed on the environmental interference component based on the net deformation solving algorithm, and the net deformation set is obtained.

[0101] Specifically, the east / north / high three-direction drift components in the drift compensation parameters are extracted and matched with the deformation gradient amplitude in the adaptive data stream in time alignment. The east / north / high three-direction drift components at the corresponding moment are subtracted from the deformation gradient amplitude vector to eliminate the temperature-induced reference point displacement interference. The sliding window difference method is used to calculate the deformation rate of adjacent time slices, and the window width is exemplarily set to 5 sampling points. The median filter is performed on the difference result to eliminate transient noise interference, and the filter window is exemplarily taken as 3x3 grid. The net deformation set containing east, north and elevation directions is output.

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

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

[0104] Specifically, as shown in Figure 4 , the WGS84 coordinate system dam slope east / north / high three-dimensional coordinate data of the net deformation set is read, the pre-stored engineering coordinate system conversion parameters of the BIM model are called, and the seven-parameter Helmert transformation is performed to convert the coordinates to the BIM engineering coordinate system. The coordinate system conversion parameters include exemplarily three translation amounts, three rotation angles and one scale factor. The WGS84 coordinate system dam slope east / north / high three-dimensional coordinate data after conversion is matched with the BIM grid node through the BIM model mapping algorithm: the Euclidean distance between the net deformation data point and the BIM grid node is calculated, and when the distance is less than exemplarily 0.1 meters, the deformation variable is assigned to the corresponding BIM node. For the unmatched BIM grid node, the inverse distance weighted interpolation algorithm is used to calculate the deformation variable of the unmatched BIM grid node, and the search radius is exemplarily set to 3 meters, and the inverse distance weight index is taken as 2. The BIM model with displacement attributes is generated.

[0105] S122, perform displacement-color temperature mapping calculation on the BIM model data carrying displacement attributes to generate a three-dimensional deformation pattern, identify and label the abnormal area exceeding the second deformation threshold, and obtain a three-dimensional deformation pattern of the labeled abnormal area;

[0106] Specifically, the eastward displacement, the northward displacement and the elevation displacement of each mesh node in the BIM model with displacement attributes are extracted, and a synthetic displacement modulus is calculated. When the synthetic displacement modulus is less than 2 mm, it is mapped to blue, between 2 mm and 5 mm, it is mapped to yellow, and greater than 5 mm, it is mapped to red. The color temperature data is mapped to the surface of the BIM model by a graphic rendering engine to generate a three-dimensional deformation trend map. The mesh nodes with a synthetic displacement modulus exceeding a second deformation threshold in the three-dimensional deformation trend map are identified, and the second deformation threshold is exemplarily set to 5 mm. The adjacent abnormal nodes are regionally merged, and isolated regions with an area less than 5 square meters are removed. The abnormal region boundary is marked with a red frame in the three-dimensional deformation trend map, and the three-dimensional deformation trend map with the marked abnormal region is output.

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

[0108] S123, deformation gradient and historical trend analysis is performed on the three-dimensional deformation trend map with the marked abnormal region to generate a warning level parameter and dynamic warning marking to obtain a three-dimensional warning map.

[0109] Specifically, the synthetic displacement modulus of each BIM mesh node in the three-dimensional deformation trend map with the marked abnormal region is extracted, and a displacement rate change rate within an exemplary 72 hours is calculated. An exemplary three-level warning determination rule is set: the displacement rate change rate is less than 0.2 mm / hour for green warning, 0.2-0.5 mm / hour for yellow warning, and greater than 0.5 mm / hour for red warning. A displacement acceleration trend is identified through time series analysis, and the warning level is raised when the displacement increment exceeds 0.1 mm in three consecutive monitoring periods. Dynamic warning identifiers are superimposed in the three-dimensional deformation trend map: green warning is displayed as a static green frame, yellow warning is displayed as a 1Hz flickering yellow frame, and red warning is displayed as a 2Hz flickering red frame superimposed with a pulse warning marker. A three-dimensional warning map containing the warning level parameter and dynamic marking information is output.

[0110] In another possible embodiment, the present application also provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the case of the dam slope deformation monitoring method based on the fusion of the measurement robot and the GNSS is realized.

[0111] The computer device can be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected by a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is configured to perform wired or wireless communication with an external terminal. The wireless communication can be achieved by WIFI, an operator network, NFC (Near Field Communication) or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, a trackball or a touchpad arranged on the shell of the computer device, or an external keyboard, a touchpad or a mouse, etc.

[0112] In another possible implementation, the present application further provides a computer readable storage medium, which stores a computer program, wherein the computer program is executed by a processor to implement the dam slope deformation monitoring method based on fusion of measurement robot and GNSS.

[0113] The computer storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic memory, a flash memory, a magnetic disk or an optical disk.

[0114] In summary, the application realizes high-precision space-time unification of GNSS and measurement robot data by constructing a fiber-optic synchronous space-time reference network, and provides a reliable reference for multi-source sensor fusion with ultra-high synchronization precision and anti-interference characteristics, significantly improving the data consistency of dam slope deformation monitoring; further through the dynamic generation of three-dimensional early warning atlas, the net deformation data is deeply fused with the BIM model, and by using the color temperature gradient mapping and intelligent early warning mechanism, the closed-loop management from deformation detection to engineering emergency response is realized, which greatly improves the disaster early warning response efficiency, and through the collaborative optimization of hardware-algorithm, the excellent monitoring precision can still be maintained under complex environmental conditions.

[0115] Numerous modifications and variations of the embodiments described herein are possible in light of the above teachings. It is therefore to be understood that, within the scope of the claims and their equivalents, many variants of the described embodiments can be made. The choice of words in the description is intended to best explain the principles of the embodiments, practical application, or technical improvement in the art, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A dam slope deformation monitoring method based on measurement robot and GNSS fusion, characterized in that the method comprises the steps of The method comprises the following steps: Signal synchronization and delay correction are performed on the dual-mode observation pier for GNSS and measuring robot prism targets to obtain a space-time reference network; Anti-interference laser pulses are emitted by the measuring robot to the dual-mode observation pier, and environmental vibrations are offset to output a vibration-compensated coordinate set based on the space-time reference network; Variable-weight adaptive fusion is performed on the vibration-compensated coordinate set and the space-time reference network to output a dam slope displacement field; Anomalous regions exceeding a first deformation threshold in the dam slope displacement field are scanned to generate a polarimetric interferometric phase map; Three-level dynamic classification and coding processing is performed on the polarimetric interferometric phase map to form an adaptive data stream, and reference point drift components are obtained through the dual-mode observation pier to obtain a net deformation set; The net deformation set is mapped to a BIM model to construct a color temperature gradient three-dimensional deformation pattern, and an abnormal region exceeding a second deformation threshold triggers an early warning display to generate a three-dimensional early warning atlas.

2. The dam slope deformation monitoring method based on fusion of measurement robot and GNSS according to claim 1, characterized in that, The space-time reference network is obtained by the following sub-steps: The dual-mode observation pier for GNSS and measuring robot prism targets is connected to the GNSS reference station through anti-bending special optical fibers to obtain an optical fiber transmission network; The atomic clock signal of the GNSS reference station is transmitted through the optical fiber transmission network, and signal synchronization and delay correction are performed to obtain the space-time reference network.

3. The dam slope deformation monitoring method based on fusion of measurement robot and GNSS according to claim 2, characterized in that, When the measuring robot emits anti-interference laser pulses to the dual-mode observation pier, the following steps are performed to offset environmental vibrations and output a vibration-compensated coordinate set: Real-time environmental vibration data is collected, and the emission angle of the anti-interference laser pulse is adjusted; Based on the angle adjustment result, the vibration influence is offset to obtain vibration compensation data; Based on the vibration compensation data, the vibration-compensated coordinate set is output in combination with the space-time reference network.

4. The dam slope deformation monitoring method based on fusion of measurement robot and GNSS according to claim 3, characterized in that, The following steps are performed to perform variable-weight adaptive fusion on the vibration-compensated coordinate set and the space-time reference network to output a dam slope displacement field: Based on the obtained vibration-compensated coordinate set and the GNSS receiver measurement data of the dual-mode observation pier in the space-time reference network, multi-source data alignment is performed to obtain space-time aligned data; Dynamic weight distribution is performed on the space-time aligned data to obtain the optimal space-time aligned data weight ratio; based on the optimal space-time aligned data weight ratio, weighted fusion calculation is performed through a displacement field solving model to obtain a dam slope displacement field.

5. The dam slope deformation monitoring method based on fusion of measurement robot and GNSS according to claim 4, characterized in that, The following method is used to obtain the polarimetric interferometric phase map: The dam slope displacement field is compared with the first deformation threshold through a deformation gradient analysis algorithm to output an anomalous region exceeding the first deformation threshold; The anomalous region is scanned at multiple angles to obtain original radar echo data of the anomalous region, and phase solving and coherence analysis are performed to generate a polarimetric interferometric phase map.

6. The dam slope deformation monitoring method based on fusion of measurement robot and GNSS according to claim 5, characterized in that, The following steps are performed to perform three-level dynamic classification and coding processing on the polarimetric interferometric phase map to form an adaptive data stream: The deformation gradient amplitude of the polarimetric interferometric phase map is calculated and vector synthesis is performed to obtain a polarimetric interferometric deformation gradient distribution map; three-level dynamic classification is performed to obtain classified and coded polarimetric interferometric data; Adaptive coding processing is performed on the polarimetric interferometric data to obtain compressed polarimetric interferometric data; Bandwidth adaptive packaging is performed on the compressed polarimetric interferometric data to output an adaptive data stream.

7. The dam slope deformation monitoring method based on fusion of measurement robot and GNSS according to claim 6, characterized in that, The obtaining method of the net deformation set is specifically: calculating a reference point drift component based on the adaptive data stream and environmental strain data collected in real time by a dual-mode observation pier; performing real-time error correction on the reference point drift component and outputting a drift compensation parameter; extracting an environmental interference component from the drift compensation parameter and the adaptive data stream; performing differential calculation on the environmental interference component based on a net deformation solving algorithm to obtain the net deformation set.

8. The dam slope deformation monitoring method based on fusion of measurement robot and GNSS according to claim 7, characterized in that, The generation method of the three-dimensional early warning atlas is specifically: converting the net deformation set to an engineering coordinate system under a BIM model to obtain aligned net deformation data; mapping the aligned net deformation data to a BIM model grid node through a BIM model mapping algorithm to generate a BIM model carrying displacement attributes; performing displacement-color temperature mapping calculation on the BIM model data carrying displacement attributes to generate a three-dimensional deformation trend map, identifying an abnormal area exceeding a second deformation threshold for labeling, and obtaining a three-dimensional deformation trend map of the labeled abnormal area; performing deformation gradient and historical trend analysis on the three-dimensional deformation trend map of the labeled abnormal area to generate early warning level parameters, and performing dynamic early warning labeling to obtain a three-dimensional early warning atlas. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The computer program is executed by a processor to implement the steps of the dam slope deformation monitoring method based on the fusion of measurement robots and GNSS according to any one of claims 1-8.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by a processor to implement the steps of the dam slope deformation monitoring method based on the fusion of measurement robots and GNSS according to any one of claims 1-8.

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