A high-slope deformation monitoring method and system, and a storage medium

Abstract

The application relates to the technical field of slope deformation monitoring, in particular to a high-slope deformation monitoring method and system and a storage medium. The method comprises the following steps: receiving first displacement data, second displacement data, horizontal displacement data and water pressure data; fusing the first displacement data and the second displacement data to obtain displacement data, and generating displacement collaborative analysis results based on the displacement data; generating coupling analysis results based on the displacement collaborative analysis results and the water pressure data; generating a sliding surface analysis result based on the horizontal displacement data; extracting constraint conditions from the sliding surface analysis result and the water pressure data, applying the constraint conditions to a preset slope simulation model, and performing parameter inversion based on the displacement data to obtain slope stability parameters; and determining a comprehensive risk index and a dominant risk factor based on the displacement collaborative analysis results, the coupling analysis results, the sliding surface analysis result and the slope stability parameters. The application can realize accurate monitoring of high-slope deformation.

Description

Technical Field

[0001] This application relates to the field of slope deformation monitoring technology, and in particular to a method, system, and storage medium for monitoring the deformation of high slopes. Background Technology

[0002] In fields such as transportation infrastructure, the stability of high slopes is directly related to the safety of road operations, the surrounding environment, and the safety of people's lives and property. Therefore, it is crucial to accurately monitor the deformation of high slopes and identify risks in a timely manner. Currently, the field of high slope deformation monitoring includes technologies such as geological exploration, remote sensing monitoring, ground displacement observation, and intelligent monitoring and early warning systems. Among these, traditional geological exploration relies on manual labor and has a long cycle, remote sensing monitoring is easily affected by the environment, and ground displacement observation focuses on collecting single-type displacement data. Although existing intelligent monitoring systems are becoming more diversified, they generally lack the ability to integrate and analyze multi-source monitoring data (such as micro-displacement, macro-displacement, horizontal displacement, and water pressure data), making it difficult to accurately identify high deformation risks. Summary of the Invention

[0003] To address the issue of insufficient accuracy in identifying high slope deformation in existing technologies, this application provides a method, system, and storage medium for monitoring high slope deformation.

[0004] Firstly, this application provides a method for monitoring the deformation of high slopes, employing the following technical solution: A method for monitoring deformation of high slopes, comprising: It receives the first displacement data collected by the CCD micro-deformation monitoring instrument, the second displacement data of the GPS monitoring point relative to the displacement monitoring pile, the horizontal displacement data collected by the fiber optic inclinometer, and the water pressure data collected by the pore water pressure gauge; Displacement data is obtained by fusing the first displacement data and the second displacement data, and displacement collaborative analysis results are generated based on the displacement data; Based on the displacement co-analysis results and the water pressure data, a coupled analysis result is generated; Based on the horizontal displacement data, generate slip surface analysis results; Constraints are extracted from the slip surface analysis results and water pressure data, applied to the preset slope simulation model, and parameter inversion is performed based on the displacement data to obtain slope stability parameters. Based on the displacement synergy analysis results, the coupling analysis results, the slip surface analysis results, and the slope stability parameters, the comprehensive risk index and the dominant risk factors are determined.

[0005] By adopting the above technical solution, four types of multi-source data are first received: CCD micro-deformation, GPS, fiber optic inclinometer, and pore water pressure. Then, displacement data is fused to generate collaborative analysis results, and coupled analysis is performed with water pressure data. The slip surface is identified based on horizontal displacement data, and stability parameters are inverted using slip surface and water pressure data as constraints. Finally, the multi-dimensional results are fused to determine the risk index and dominant factors, realizing a closed-loop process from data acquisition and multi-dimensional analysis to risk identification. This breaks the limitations of single data monitoring, can comprehensively capture slope deformation patterns and risk causes, and significantly improves the accuracy and comprehensiveness of risk identification.

[0006] In a preferred embodiment, this application can be further configured such that the displacement data includes the coordinate data of each displacement monitoring point on the slope cross-section at each monitoring time; The generation of displacement collaborative analysis results based on the displacement data includes: Based on the displacement data, determine the horizontal composite displacement sequence of each displacement monitoring point and the horizontal displacement direction angle in unit vector form; The sum of the horizontal displacement direction angles of all displacement monitoring points on the slope section is calculated to obtain the composite vector, and the direction of the composite vector is calculated as the potential main sliding direction; Determine the total number of all displacement monitoring points on the slope cross section, calculate the length of the composite vector, and calculate the ratio of the composite vector length to the total number to obtain the displacement direction consistency coefficient; A correlation coefficient matrix is ​​constructed based on the horizontal combined displacement sequence of each monitoring point. The potential main sliding direction, the displacement direction consistency coefficient, and the correlation coefficient matrix constitute the displacement collaborative analysis result.

[0007] By adopting the above technical solution, based on the coordinate data of the slope cross-section displacement monitoring points, the horizontal composite displacement sequence and direction angle of each point are determined. The potential main sliding direction is obtained by synthesizing the vector. The ratio of the composite vector length to the total number of monitoring points is calculated to obtain the displacement direction consistency coefficient. Then, a correlation coefficient matrix is ​​constructed. This not only accurately locks the possible dominant sliding direction of the slope, but also quantifies the degree of coordination and displacement correlation of the displacement directions of each monitoring point, and clearly grasps the overall coordination and local differences of slope deformation.

[0008] In a preferred embodiment, this application can be further configured such that: the construction of the correlation coefficient matrix based on the horizontal combined displacement sequence of each displacement monitoring point includes: For each displacement monitoring point, a displacement rate sequence is determined based on the horizontal combined displacement sequence of the displacement monitoring point; A displacement rate matrix is ​​constructed based on the displacement rate sequence of each displacement monitoring point within a preset time window. In the displacement rate matrix, rows represent displacement monitoring points, columns represent monitoring times, and elements represent the displacement rate sequence of the corresponding displacement monitoring point within the preset time window at the corresponding monitoring time. A correlation coefficient matrix is ​​constructed based on the displacement rate matrix, and the elements of the correlation coefficient matrix represent the correlation between the displacement rates of two corresponding displacement monitoring points within the preset time window.

[0009] By adopting the above technical solution, displacement rate sequences are extracted from the horizontal composite displacement sequences of each monitoring point, a displacement rate matrix within a preset time window is constructed, and a correlation coefficient matrix is ​​generated. By focusing on the correlation analysis of displacement rates, interference information in the cumulative displacement value can be effectively filtered out, and the synchronous response relationship of deformation rates of different monitoring points within a specific time period can be accurately captured, providing data support for judging the transmission path and linkage characteristics of slope deformation.

[0010] In a preferred embodiment, this application may be further configured such that the water pressure data includes the water pressure value at each water pressure monitoring point on the slope cross section at each monitoring time; The generation of coupled analysis results based on the displacement co-analysis results and the water pressure data includes: Extract the water pressure value sequence of the target water pressure monitoring point from the water pressure data, wherein the target water pressure monitoring point is any water pressure monitoring point on the slope section; Determine the target displacement monitoring point that matches the target water pressure monitoring point, and extract the displacement rate sequence of the target displacement monitoring point from the displacement collaborative analysis results; Based on the water pressure value sequence and the displacement rate sequence, determine the response delay and response gain of the target water pressure monitoring point; Based on the response delay and response gain of all water pressure monitoring points on the slope section, the coupling mode, water pressure sensitivity coefficient and stability trend are determined. The coupling mode includes shallow slippage mode and deep burrowing mode. The coupling mode, the water pressure sensitivity coefficient, and the stability trend constitute the coupling analysis results.

[0011] By adopting the above technical solution, the water pressure value sequence of the target water pressure monitoring point is extracted, the corresponding displacement monitoring point is matched and its displacement rate sequence is obtained, the response delay and gain are determined, and the coupling mode, water pressure sensitivity coefficient and stability trend are determined by combining the data of all water pressure monitoring points. This achieves quantitative analysis of the relationship between water pressure and displacement, can accurately distinguish between two coupling modes: shallow slippage and deep burrowing, and clarifies the sensitivity of the slope to water pressure changes and the stability evolution trend.

[0012] In a preferred embodiment, this application can be further configured such that: determining the response delay and response gain of the target water pressure monitoring point based on the water pressure value sequence and the displacement rate sequence includes: Identify the peak water pressure time of the water pressure value sequence and the peak displacement rate time of the displacement rate sequence, and calculate the response delay between the peak displacement rate time and the peak water pressure time; Identify peak water pressure and background water pressure values ​​from the water pressure value sequence, and calculate the water pressure increment based on the peak water pressure and the background water pressure values; Identify the peak displacement rate and background displacement rate value from the displacement rate sequence of the target displacement monitoring point, and calculate the displacement rate increment based on the peak displacement rate and the background displacement rate value; The response gain is calculated based on the increment of the water pressure value and the increment of the displacement rate.

[0013] By adopting the above technical solution, the peak moments of water pressure and displacement rate are identified to calculate the response delay. The peak and background values ​​are extracted to obtain the increments of water pressure and displacement rate to calculate the response gain. This achieves accurate quantification of the time difference and intensity correlation between water pressure change and displacement response, and can clearly characterize the timeliness and degree of influence of water pressure on slope deformation.

[0014] In a preferred embodiment, this application may be further configured such that the horizontal displacement data includes the coordinate data of each fiber grating sensor on the fiber grating inclinometer at each monitoring time; The generation of slip surface analysis results based on the horizontal displacement data includes: Determine the depth data for each fiber Bragg grating sensor, construct a displacement rate-depth curve based on the depth data and the horizontal displacement data, and identify the slip surface depth from the displacement rate-depth curve; The equivalent shear modulus of the slope is retrieved, and a strain energy density depth curve is constructed based on the displacement rate depth curve and the equivalent shear modulus. The cumulative strain energy is obtained by integrating the strain energy density depth curve. The strain energy release rate is calculated based on the cumulative strain energy at each monitoring moment; The slip surface depth, the cumulative strain energy, and the strain energy release rate constitute the slip surface analysis results.

[0015] By adopting the above technical solution, a displacement rate depth curve is constructed by combining the depth and horizontal displacement data of the fiber optic grating sensor to identify the depth of the slip surface. The equivalent shear modulus is retrieved to construct a strain energy density depth curve and integrated to obtain the cumulative strain energy. Then, the strain energy release rate is calculated. This not only accurately locates the specific depth of the slip surface, but also captures the energy accumulation and release patterns during the slip surface formation process through energy indicators, and predicts the evolution trend and instability risk of the slip surface in advance.

[0016] In a preferred embodiment, this application can be further configured such that: the parameter inversion based on the displacement data to obtain slope stability parameters includes: Construct an objective function, which characterizes the difference between the displacement predicted by the model and the actual monitored displacement; An optimization algorithm is used to update the equivalent internal friction angle and equivalent cohesion in each iteration. Displacement simulation is performed using the preset slope simulation model, and the function value of the objective function is calculated. When the function value of the objective function meets the preset optimization target or reaches the maximum number of iterations, the iteration stops, and the slope stability parameters obtained by the inversion of the preset slope simulation model are received. The slope stability parameters include the equivalent internal friction angle and the equivalent cohesion.

[0017] By adopting the above technical solution, an objective function is constructed to characterize the difference between the predicted displacement and the actual monitored displacement. An optimization algorithm is used to iteratively update the equivalent internal friction angle and cohesion. The objective function value is calculated through simulation. When the optimization objective is met or the maximum number of iterations is reached, stable parameters are output. This effectively solves the problem of the disconnect between traditional stable parameters and the actual situation on site, and enables the parameters obtained by inversion to accurately match the stress state of the slope on site.

[0018] Secondly, this application provides a high slope deformation monitoring system, which adopts the following technical solution: A high slope deformation monitoring system includes: a CCD micro-deformation monitoring instrument, displacement monitoring piles, a GPS monitoring device, a fiber optic inclinometer, a pore water pressure gauge, and electronic equipment installed on each slope cross section, wherein the slope cross sections are arranged at first preset distances along the route direction; The CCD micro-deformation monitoring instrument is installed on the slope surface to collect the first displacement data of the slope. The displacement monitoring pile is buried at a second preset distance outside the slope line of the slope section to provide a displacement monitoring benchmark. The GPS monitoring device is installed at the GPS monitoring point on the slope section to collect the second displacement data of the GPS monitoring point relative to the displacement monitoring pile; The fiber optic inclinometer is installed at the top of the slope section to collect horizontal displacement data of the slope depth. The pore water pressure gauge is buried in the soil below the slope section and is used to collect water pressure data. The electronic device is used to perform the high slope deformation monitoring method as described in any of the first aspects.

[0019] In a preferred embodiment, this application can be further configured as: an electronic device, including: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: perform the high slope deformation monitoring method as described in any of the first aspects.

[0020] Thirdly, this application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the high slope deformation monitoring method as described in any of the first aspects.

[0021] Fourthly, this application provides a computer program product, which adopts the following technical solution: A computer program product includes a computer program that, when executed by a processor, implements the high slope deformation monitoring method as described in any of the first aspects.

[0022] In summary, this application includes the following beneficial technical effects: This application receives data from four sources: CCD micro-deformation, GPS, fiber optic inclinometer, and pore water pressure. It then integrates displacement data to generate collaborative analysis results, performs coupled analysis with water pressure data, identifies the slip surface based on horizontal displacement data, and uses slip surface and water pressure data as constraints to invert stability parameters. Finally, it integrates multi-dimensional results to determine the risk index and dominant factors, realizing a closed-loop process from data acquisition and multi-dimensional analysis to risk identification. This breaks the limitations of single data monitoring, comprehensively captures slope deformation patterns and risk causes, and significantly improves the accuracy and comprehensiveness of risk identification. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating a high slope deformation monitoring method provided in an embodiment of this application; Figure 2 This is a schematic diagram of the slope cross-section provided in the embodiments of this application; Figure 3 This is a schematic diagram of the layout of GPS monitoring points and CCD monitoring points provided in the embodiments of this application; Figure 4 This is a schematic diagram of the structure of the fiber optic grating inclinometer provided in the embodiments of this application; Figure 5 This is a schematic diagram of the installation of the pore water pressure gauge provided in the embodiments of this application; Figure 6 This is a longitudinal layout diagram of the pore water pressure gauge provided in the embodiments of this application; Figure 7This is a schematic diagram of the structure of a high slope deformation monitoring system provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0024] The following is in conjunction with the appendix Figure 1 To be continued Figure 8 This application will be described in further detail.

[0025] This specific embodiment is merely an explanation of this application and is not intended to limit it. After reading this specification, those skilled in the art can make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0026] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0028] It should be noted that, in the optional embodiments of this application, the data related to object information, when applied to specific products or technologies, requires the permission or consent of the object. Furthermore, the collection, use, and processing of this data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. In other words, if the embodiments of this application involve data related to an object, it must be obtained with the object's authorization and consent, the authorization and consent of relevant departments, and in accordance with the relevant laws, regulations, and standards of the country and region. If the embodiments involve personal information, the acquisition of all personal information requires the individual's consent. If sensitive information is involved, the separate consent of the information subject is required. The embodiments also need to be implemented with the object's authorization and consent.

[0029] This application provides a method for monitoring the deformation of high slopes, such as... Figure 1As shown, the method provided in this application embodiment is executed by an electronic device, which can be a server or a terminal device. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication. This application embodiment does not impose any limitations on this connection. The method includes steps S101-S106, wherein: S101 receives the first displacement data collected by the CCD micro-deformation monitoring instrument, the second displacement data of the GPS monitoring point relative to the displacement monitoring pile, the horizontal displacement data collected by the fiber optic inclinometer, and the water pressure data collected by the pore water pressure gauge.

[0030] See Figure 2 The diagram shows a schematic of the slope cross-section. The slope cross-section is the monitoring cross-section. To meet the needs of slope deformation monitoring and reduce monitoring costs, this embodiment sets up monitoring cross-sections at each slope platform and at the top of the slope within the deep cut slope area, and sets up slope cross-sections (monitoring cross-sections) at first preset intervals along the route direction. Optionally, the first preset interval is 20m, and the corresponding road markers for each slope cross-section are: K22+960, K22+980, K23+000, K23+020, K23+040, and K23+060.

[0031] The high slope deformation monitoring method provided in this embodiment only applies to a single slope cross-section. The CCD micro-deformation monitor can acquire slope stability information through the mutual conversion of photoelectric signals, achieving wireless and digital monitoring of high slopes. This reduces manual labor, lowers costs, and provides high monitoring accuracy, with a maximum range of 1000m. Furthermore, based on remote wireless signal control, it is more suitable for long-term monitoring of high slopes along highways. However, during slope and road construction, ground vibrations are inevitable during foundation compaction, road rolling, and other construction processes, disrupting the CCD micro-deformation monitoring data and causing fluctuations. Therefore, this embodiment combines a GPS monitoring device to collect displacement data.

[0032] See Figure 3 The diagram shows the layout of GPS monitoring points (GPS measuring points) and CCD monitoring points (CCD measuring points). Displacement monitoring piles are installed at the second predetermined distance outside the slope line of the slope section to provide a displacement monitoring benchmark; these piles must be firmly installed. During excavation, fixed piles are installed at the corresponding slope platform locations up to the slope toe, serving as GPS monitoring points. Figure 3GPS monitoring points are installed on steps 1, 2, 3, 4, and 5, with each point equipped with a GPS monitoring device. Steps 2, 3, and 4 in the middle of the slope are located in an area of ​​interbedded granite gneiss and breccia, exhibiting uneven weathering and making them prone to landslides, collapses, and debris flows. Therefore, during data monitoring, CCD micro-deformation monitoring instruments are installed on steps 2, 3, and 4, forming a monitoring section from top to bottom.

[0033] See Figure 4 The diagram illustrates the structure of a fiber optic grating inclinometer. The inclinometer is embedded at the top of the slope section to collect horizontal displacement data of the slope depth. Compared to traditional inclinometers, the fiber optic grating inclinometer offers advantages such as high measurement accuracy, long transmission distance, strong anti-interference capability, and automatic data acquisition. A borehole is drilled at the top of each slope section, ensuring it is vertical and the depth depends on geological conditions, reaching at least 50cm into the underlying moderately weathered granite gneiss layer. Fiber optic sensors are fixed symmetrically on both sides of the inclinometer tube, which is then placed into the borehole and secured with cement mortar. The bottom of the fiber optic grating inclinometer is placed at least 50cm into hard soil or bedrock where horizontal displacement in the depth direction is zero; therefore, the fiber optic grating inclinometer can be simulated as a cantilever beam with a fixed bottom and a free upper section. Meanwhile, the cement mortar provides a protective layer around the fiber Bragg grating inclinometer. Even when the soil deforms, the fiber Bragg grating inclinometer's axis remains a smooth, continuous curve, and the displacement at the top of the inclinometer is significantly less than its total length. This allows for precise measurement of deep slope displacement and identification of the slip surface.

[0034] See Figure 5 The diagram shows a schematic of the installation of a pore water pressure gauge. The pore water pressure gauge is a steel wire type, installed in the soil below the slope section to collect water pressure data. The installation method is borehole installation (mud slurry wall forming is not recommended), with holes drilled downwards at the fourth step position of each monitoring section (e.g., ...). Figure 5 The drilling depth depends on the geological conditions, requiring drilling below the underlying moderately weathered granite gneiss layer. After drilling to the required depth or elevation at the installation location, clean fine sand is first filled into the bottom of the hole, then the probe is inserted, followed by sand filling around the probe, and finally, the upper part of the borehole is completely sealed with expansive soil. For the borehole method, the probe should be installed at least one week before construction to allow sufficient time for excess pore water pressure caused by installation to dissipate, improving the accuracy of subsequent testing. Three pore water pressure gauges should be installed in each borehole, with a longitudinal spacing of at least 5 meters. Figure 6 The diagram shows the longitudinal layout of the pore water pressure gauge.

[0035] During slope construction, the displacement of the fixed piles should be observed every 15 days; once every 7 days during the rainy season; once every day during heavy rainfall and sudden rainstorms; once every 30 days from the completion of slope construction until the road is open to traffic for 1.5 years; if the deformation shows an increasing trend, continuous monitoring should be carried out. The monitoring cycle should be linked to construction and rainfall, and monitoring should be intensified during the rainy season and slope excavation. The monitoring frequency can be reduced after completion; the monitoring should end 1-2 years after completion.

[0036] The system employs a pre-set monitoring frequency. CCD micro-deformation monitoring instruments, displacement monitoring piles, GPS monitoring devices, fiber optic inclinometers, and pore water pressure gauges are installed at each slope section to continuously acquire data at each monitoring moment. The resulting first displacement data, second displacement data, horizontal displacement data, and water pressure data are time-series data including the monitoring time timestamps. The collected first and second displacement data are based on the monitoring piles, and the horizontal displacement data is based on the bottom of the fiber optic inclinometer. Based on the placement of these references, the received first, second, and horizontal displacement data are converted to a world coordinate system and represented in three-dimensional form.

[0037] S102. The first displacement data and the second displacement data are merged to obtain displacement data, and the displacement collaborative analysis results are generated based on the displacement data.

[0038] See Figure 3 GPS monitoring points are installed on steps 1, 2, 3, 4, and 5; CCD micro-deformation monitoring instruments are installed on steps 2, 3, and 4. For steps 1 and 5, the corresponding GPS monitoring points are used as displacement monitoring points, and the second displacement data of the corresponding GPS monitoring points is used as the displacement data of the slope surface. For steps 2, 3, and 4, the GPS monitoring points and CCD monitoring points on each step are used as a single displacement monitoring point, and the first and second displacement data are fused to obtain the displacement data of the corresponding displacement monitoring point.

[0039] The fusion method is as follows: Weather data is acquired, and weather categories are determined based on this data, including severe weather and good weather. Weights are preset for the first and second displacement data under severe and good weather conditions, with the sum of their weights being 1. Under severe weather conditions, the CCD's optical path is easily blocked or interfered with, potentially leading to data distortion or complete loss. GPS, however, is unaffected and provides stable and continuous data; therefore, the weight of the first displacement data is lower than that of the second. Under good weather conditions, the CCD micro-deformation monitor can leverage its high precision and high sampling rate to capture micro-deformations at the micrometer or even sub-micrometer level; therefore, the weight of the first displacement data is higher than that of the second. The first and second displacement data are then weighted and summed based on their respective weights, and the result is used as the displacement data.

[0040] The displacement coordination analysis results include the potential main sliding direction, the displacement direction consistency coefficient, and the correlation coefficient matrix. The potential main sliding direction represents the overall movement direction of all displacement monitoring points on the slope. The displacement direction consistency coefficient, ranging from 0 to 1, indicates the degree of consistency in the movement directions of all displacement monitoring points; a larger value indicates a more consistent movement direction. The elements of the correlation coefficient matrix indicate whether the change rate of displacement rates at corresponding two displacement monitoring points is synchronized.

[0041] S103. Generate coupled analysis results based on displacement co-analysis results and water pressure data.

[0042] The coupling analysis results include coupling modes, water pressure sensitivity coefficients, and stability trends. Coupling modes include shallow slippage and deep embankment modes. The coupling modes indicate how water induces slope deformation; the shallow slippage mode indicates that surface sliding occurs rapidly after rainfall, while the deep embankment mode indicates that water slowly seeps into deeper areas, inducing deep slippage only after a longer period. The stability trend indicates how slope stability changes over time (deterioration, stabilization, or improvement).

[0043] S104. Generate slip surface analysis results based on horizontal displacement data.

[0044] The results of the slip surface analysis include slip surface depth, cumulative strain energy, and strain energy release rate. Slip surface depth indicates the location of the main slip surface within the slope. Cumulative strain energy represents the total energy accumulated internally during slope deformation. The strain energy release rate represents the energy released per unit time; a sharp increase in the rate is a precursor to failure.

[0045] S105. Extract constraints from the slip surface analysis results and water pressure data, apply the constraints to the preset slope simulation model, and perform parameter inversion based on displacement data to obtain slope stability parameters.

[0046] Specifically, the slip surface depth is extracted from the slip surface analysis results, and the slip surface depth and water pressure data are applied as constraints to a pre-defined slope simulation model. An objective function is constructed, representing the difference between the model-predicted displacement and the actual monitored displacement. An optimization algorithm is used to update the equivalent internal friction angle and equivalent cohesion in each iteration. Displacement simulation is performed using the pre-defined slope simulation model, and the function value of the objective function is calculated. When the function value of the objective function satisfies the pre-defined optimization objective, the iteration stops, and the slope stability parameters obtained from the inversion of the pre-defined slope simulation model are received. These slope stability parameters include the equivalent internal friction angle and equivalent cohesion.

[0047] S106. Based on the results of displacement synergy analysis, coupling analysis, slip surface analysis, and slope stability parameters, determine the comprehensive risk index and dominant risk factors.

[0048] This embodiment does not limit the method of determining the comprehensive risk index and dominant risk factors based on displacement synergy analysis results, coupling analysis results, slip surface analysis results, and slope stability parameters. Optionally, a pre-trained model can be used, with the displacement synergy analysis results, coupling analysis results, slip surface analysis results, and slope stability parameters as model inputs, and the model outputs the comprehensive risk index and dominant risk factors. Alternatively, the displacement synergy analysis results, coupling analysis results, slip surface analysis results, and slope stability parameters can be input into an AI model for analysis to obtain the comprehensive risk index and dominant risk factors.

[0049] The displacement direction consistency coefficient can be extracted from the displacement co-analysis results, the water pressure sensitivity coefficient and stability trend (value 0 for improvement, value 0.5 for stability, and value 1 for acceleration) can be extracted from the coupling analysis results, the strain energy release rate can be extracted from the slip surface analysis results, and the equivalent internal friction angle and equivalent cohesion can be extracted from the slope stability parameters. Based on a preset strain energy release rate range, the strain energy release rate is normalized, and the result of (maximum value of the range - current strain energy release rate) / (maximum value of the range - minimum value of the range) is used as the normalized strain energy release rate result. Then, the loss degree of the equivalent internal friction angle and equivalent cohesion is calculated separately, with the loss degree = (initial value - current value) / initial value, thus obtaining the normalized results of the equivalent internal friction angle and equivalent cohesion. Based on preset weights, the displacement direction consistency coefficient, water pressure sensitivity coefficient, strain energy release rate, stability trend, equivalent internal friction angle, and equivalent cohesion are weighted and summed. The product of the result and 100 is used as the comprehensive risk index. The parameter with the largest value among the displacement direction consistency coefficient, water pressure sensitivity coefficient, strain energy release rate, stability trend, equivalent internal friction angle, and equivalent cohesion is considered the dominant factor if its maximum value exceeds a preset minimum threshold; otherwise, it is determined to be a combination of multiple factors. Each parameter is mapped to a risk factor: the displacement direction consistency coefficient corresponds to the deformation synergy factor, the water pressure sensitivity coefficient corresponds to the water pressure factor, the strain energy release rate corresponds to the accelerated energy release, the stability trend corresponds to the accelerated deformation trend, and the equivalent internal friction angle and equivalent cohesion correspond to the material strength degradation.

[0050] This embodiment first receives four types of multi-source data: CCD micro-deformation, GPS, fiber optic inclinometer, and pore water pressure. Then, it integrates displacement data to generate collaborative analysis results, combines water pressure data for coupled analysis, identifies the slip surface based on horizontal displacement data, and uses slip surface and water pressure data as constraints to invert stability parameters. Finally, it integrates multi-dimensional results to determine the risk index and dominant factors, realizing a closed-loop process from data acquisition and multi-dimensional analysis to risk identification. This breaks the limitations of single data monitoring, comprehensively captures slope deformation patterns and risk causes, and significantly improves the accuracy and comprehensiveness of risk identification.

[0051] One possible implementation of this application embodiment is that the displacement data includes the coordinate data of each displacement monitoring point on the slope cross section at each monitoring time; Displacement collaborative analysis results are generated based on displacement data, including: Based on the displacement data, determine the horizontal resultant displacement sequence of each displacement monitoring point and the horizontal displacement direction angle in unit vector form; The sum of the horizontal displacement direction angles of all displacement monitoring points on the slope cross section is used to obtain the composite vector, and the direction of the composite vector is used as the potential main sliding direction. Determine the total number of all displacement monitoring points on the slope cross section, calculate the length of the composite vector, and calculate the ratio of the composite vector length to the total number to obtain the displacement direction consistency coefficient. A correlation coefficient matrix is ​​constructed based on the horizontal combined displacement sequence of each monitoring point. Among them, the consistency coefficient of the potential main sliding direction and the displacement direction, and the correlation coefficient matrix constitute the displacement synergy analysis results.

[0052] In this embodiment, the coordinate data in the displacement data includes east, north, and celestial coordinates. For each displacement monitoring point i, at each monitoring time, the displacement component of i is calculated based on the displacement data. The displacement component includes an eastward displacement component ΔE and a northward displacement component ΔN. The eastward displacement component ΔE = current eastward coordinate - initial eastward coordinate, and the northward displacement component ΔN = current northward coordinate - initial northward coordinate. Horizontal resultant displacement. D represents the total displacement of i on the horizontal plane. The horizontal displacement direction angle... North is defined as 0°, and east as 90°. The direction angles are then converted to unit vector form to eliminate the influence of the magnitude of the displacement. , .

[0053] For each displacement monitoring point, at each monitoring time, calculate the resultant horizontal displacement and the horizontal displacement direction angle in unit vector form to obtain the resultant horizontal displacement sequence and the unit vector sequence. Calculate the sum of the horizontal displacement direction angles in unit vector form for all displacement monitoring points on the slope cross-section at the current monitoring time to obtain the composite vector, represented as (x_total, y_total). Potential main sliding direction. Length of the synthesized vector The displacement direction consistency coefficient ranges from 0 to 1, with a larger value indicating higher displacement consistency.

[0054] This embodiment uses the coordinate data of slope cross-section displacement monitoring points as a basis to determine the horizontal composite displacement sequence and direction angle of each point. The potential main sliding direction is obtained by synthesizing the vector. The ratio of the composite vector length to the total number of monitoring points is calculated to obtain the displacement direction consistency coefficient. Then, a correlation coefficient matrix is ​​constructed. This not only accurately locks the possible dominant sliding direction of the slope, but also quantifies the degree of coordination and displacement correlation of the displacement directions of each monitoring point, and clearly grasps the overall coordination and local differences of slope deformation.

[0055] One possible implementation of this application embodiment involves constructing a correlation coefficient matrix based on the combined horizontal displacement sequence of each displacement monitoring point, including: For each displacement monitoring point, the displacement rate sequence is determined based on the horizontal combined displacement sequence of the displacement monitoring point; A displacement rate matrix is ​​constructed based on the displacement rate sequence of each displacement monitoring point within a preset time window. In the displacement rate matrix, rows represent displacement monitoring points, columns represent monitoring times, and elements represent the displacement rate sequence of the corresponding displacement monitoring point within the preset time window at the corresponding monitoring time. A correlation coefficient matrix is ​​constructed based on the displacement rate matrix. The elements of the correlation coefficient matrix represent the correlation between the displacement rates of two corresponding displacement monitoring points within a preset time window.

[0056] For each displacement monitoring point, the horizontal composite displacement sequence is numerically differentiated over time to obtain the displacement rate sequence. An N×T displacement rate matrix is ​​constructed, where rows represent displacement monitoring points, the total number of displacement monitoring points is represented by N, columns represent monitoring times, and T is the number of monitoring times within a preset time window.

[0057] Furthermore, the N×N Pearson correlation coefficient matrix of the displacement rate matrix is ​​calculated to obtain the correlation coefficient matrix.

[0058] This embodiment extracts the displacement rate sequence from the horizontal composite displacement sequence of each monitoring point, constructs a displacement rate matrix within a preset time window, and then generates a correlation coefficient matrix. By focusing on the correlation analysis of displacement rates, it can effectively filter out interference information in the cumulative displacement value, accurately capture the synchronous response relationship of deformation rate of different monitoring points within a specific time period, and provide data support for judging the transmission path and linkage characteristics of slope deformation.

[0059] One possible implementation of this application embodiment is that the water pressure data includes the water pressure value of each water pressure monitoring point on the slope cross section at each monitoring time; Coupled analysis results are generated based on displacement co-analysis results and water pressure data, including: Extract the water pressure value sequence of the target water pressure monitoring point from the water pressure data. The target water pressure monitoring point is any water pressure monitoring point on the slope section. Determine the target displacement monitoring point that matches the target water pressure monitoring point, and extract the displacement rate sequence of the target displacement monitoring point from the displacement co-analysis results; Based on the water pressure value sequence and displacement rate sequence, determine the response delay and response gain of the target water pressure monitoring point; Based on the response delay and response gain of all water pressure monitoring points on the slope section, the coupling mode, water pressure sensitivity coefficient and stability trend are determined. The coupling mode includes shallow slippage mode and deep thrusting mode. The coupling mode, water pressure sensitivity coefficient, and stability trend constitute the coupling analysis results.

[0060] In this embodiment, based on the locations of the water pressure monitoring points and displacement monitoring points, the nearest displacement monitoring point is assigned to each water pressure monitoring point. A water pressure curve is constructed based on the water pressure value sequence of the target water pressure monitoring point, and a displacement rate curve is constructed based on the displacement rate sequence of the target displacement monitoring point. A dynamic time warping algorithm is used to align the shapes of the water pressure curve and the displacement rate curve. Based on the alignment result, the time difference between the displacement rate curve and the water pressure curve is calculated. The time difference represents how long it takes for the slope displacement to change after a change in water pressure.

[0061] Based on the determined time difference, multiple water pressure change events are identified from the water pressure value sequence and displacement rate sequence. The response delay and response gain of the target water pressure monitoring point in each water pressure change event are determined, and the average response delay and average response gain are calculated as the final response delay and response gain of the target water pressure monitoring point.

[0062] Delay and gain thresholds are pre-set based on experience. If more than half of the water pressure monitoring points have a response delay lower than the delay threshold and a response gain higher than the gain threshold, it is determined to be a shallow slippery mode; if more than half of the water pressure monitoring points have a response delay higher than the delay threshold and a response gain lower than the gain threshold, it is determined to be a deep slippery mode. All other cases are determined to be atypical modes. The response gains of all water pressure monitoring points are summarized, and the maximum or average value is used as the water pressure sensitivity coefficient. This coefficient can also be multiplied by a preset normalization coefficient to normalize it to the range of 0-1.

[0063] For each water pressure monitoring point, its response delay and response gain are analyzed in multiple consecutive water pressure change events. When the response delay decreases or the response gain increases with time, the stability trend is judged to be deteriorating; when the response delay increases or the response gain decreases with time, the stability trend is judged to be improving; when there is no obvious trend in response delay and response gain, the stability trend is judged to be stable.

[0064] This embodiment extracts the water pressure value sequence of the target water pressure monitoring point, matches the corresponding displacement monitoring point and obtains its displacement rate sequence, determines the response delay and gain, and then combines the data of all water pressure monitoring points to determine the coupling mode, water pressure sensitivity coefficient and stability trend, realizing the quantitative analysis of the relationship between water pressure and displacement. It can accurately distinguish between two coupling modes: shallow slippage and deep scouring, and clarify the sensitivity of the slope to water pressure changes and the stability evolution trend.

[0065] One possible implementation of this application embodiment involves determining the response delay and response gain of a target water pressure monitoring point based on a water pressure value sequence and a displacement rate sequence, including: Identify the peak water pressure time of the water pressure value sequence and the peak displacement rate time of the displacement rate sequence, and calculate the response delay between the peak displacement rate time and the peak water pressure time; Identify peak and background water pressure values ​​from the water pressure value sequence, and calculate the water pressure increment based on the peak and background water pressure values; Identify the peak displacement rate and background displacement rate from the displacement rate sequence of the target displacement monitoring point, and calculate the displacement rate increment based on the peak displacement rate and background displacement rate. The response gain is calculated based on the increments of water pressure and displacement rate.

[0066] The peak water pressure moment represents the moment when the driving force propelling slope deformation reaches its maximum, typically occurring after rainfall infiltration has ceased or reached equilibrium. The peak displacement rate moment represents the moment when the slope deformation response is most intense; under the lubricating and softening effects of water, the shear strength on the slip zone decreases to its minimum, resulting in the fastest sliding speed. The response delay is the time required for water to seep from the monitoring point to the potential slip surface and exert sufficient softening and lubrication effects. A short response delay means that water can quickly affect the slip zone, indicating shallow, well-permeable slips (such as shallow sliding). A long response delay means that water takes a long time to reach and affect the deep slip zone, indicating deep, poorly permeable slips (such as deep scouring).

[0067] Response gain represents the increase in displacement rate caused by a unit increase in water pressure. A large response gain indicates that the slope is highly sensitive to water; even a slight increase in water pressure will cause a sharp increase in the deformation rate. This is a typical characteristic of shallow slips or slopes in an extremely unstable state. A small response gain indicates that the slope is not sensitive to water or has a different response mechanism. It may require a large change in water pressure to cause a slight acceleration in deformation, which may be related to deep thrust or high rock strength.

[0068] Specifically, complete water pressure change events are identified from the water pressure value sequence. The identification method is as follows: the water pressure value sequence is numerically differentiated to obtain a water pressure change rate sequence. A pre-set change rate threshold is used to determine whether the water pressure change is significant. When a specific number of consecutive points in the water pressure value sequence have positive values ​​and all exceed the change rate threshold, the first point is marked as the event start point. When the water pressure change rate falls from a positive value to zero or a negative value, the recorded time is the water pressure peak time, completing the recording of one water pressure change event. The water pressure peak time of each water pressure change event is then found from the displacement rate sequence.

[0069] For each water pressure change event, the time difference following the peak water pressure moment is determined as the peak displacement rate moment of that event. The peak water pressure moment and the initial water pressure moment are determined from the water pressure value sequence. The initial water pressure moment is used as the background water pressure value, and the difference between the peak and background values ​​is calculated as the water pressure increment. Similarly, the peak displacement rate moment and the initial displacement rate moment are determined from the displacement rate sequence. The initial displacement rate moment is used as the background displacement rate value, and the difference between the peak and background values ​​is calculated as the displacement rate increment. The time difference between the peak displacement rate moment and the peak water pressure moment is calculated as the response delay for that water pressure change event. The displacement rate increment and the water pressure increment are calculated as the response gain for that water pressure change event.

[0070] This embodiment identifies the peak times of water pressure and displacement rate to calculate the response delay, extracts the peak and background values ​​to obtain the increments of water pressure and displacement rate to calculate the response gain, and achieves accurate quantification of the time difference and intensity correlation between water pressure change and displacement response. It can clearly characterize the timeliness and degree of influence of water pressure on slope deformation triggering.

[0071] One possible implementation of this application embodiment is that the horizontal displacement data includes the coordinate data of each fiber grating sensor on the fiber grating inclinometer at each monitoring time; Slip surface analysis results are generated based on horizontal displacement data, including: Determine the depth data for each fiber Bragg grating sensor, construct a displacement rate-depth curve based on the depth data and horizontal displacement data, and identify the slip surface depth from the displacement rate-depth curve; The equivalent shear modulus of the slope is retrieved, and a strain energy density depth curve is constructed based on the displacement rate depth curve and the equivalent shear modulus. The cumulative strain energy is obtained by integrating the strain energy density depth curve. The strain energy release rate is calculated based on the cumulative strain energy at each monitoring moment; The slip surface depth, cumulative strain energy, and strain energy release rate constitute the slip surface analysis results.

[0072] In this embodiment, a displacement-depth curve is constructed based on the horizontal displacement data and depth data at the current monitoring time. The horizontal axis of the displacement-depth curve is the depth z of the corresponding fiber optic grating sensor, and the vertical axis is the horizontal displacement D of the corresponding fiber optic grating sensor. The displacement-depth curve represents the bending shape of the borehole at different depths.

[0073] Calculate the first derivative of the displacement dD / dz in the displacement-depth curve to obtain the displacement-rate-depth curve. This curve represents the degree of shear deformation along the borehole depth direction. The larger the slope (displacement rate), the greater the displacement difference per unit depth, i.e., the more severe the shear deformation. Identify the depth corresponding to the point with the largest displacement rate from the displacement-rate-depth curve, which is the slip surface depth. The slip surface depth is the interface where the soil undergoes the maximum relative displacement.

[0074] When a material undergoes elastic deformation, it stores energy, much like a stretched spring. This energy is called strain energy. The formula for calculating the strain energy stored per unit volume (strain energy density u) is u = (1 / 2) × stress × strain. Based on Hooke's Law in elasticity theory, stress τ = shear modulus G × strain γ, therefore, strain energy density u = (1 / 2) × G × strain × strain.

[0075] The equivalent shear modulus G is a material parameter of the slope soil, describing the material's resistance to shear deformation. It can be determined through experiments or back analysis. In soil mechanics, based on the bending theory of beams, the shear strain at a certain depth z of the inclinometer tube can be approximated as the first derivative of the displacement with respect to depth. Therefore, the displacement-to-depth curve is used as the shear strain γ(z,t), representing the change of shear strain with depth at the current monitoring time t. The formula for strain energy density per unit volume simplifies to: u(z,t) = 1 / 2 × G × γ(z,t) 2 u(z,t) represents the elastic strain energy stored in a unit volume of soil at depth z at the current monitoring time t.

[0076] Integrating u(z,t) along the entire borehole depth z yields the total strain energy accumulated across the slope cross section, i.e., the cumulative strain energy, which reflects the total amount of accumulated damage within the slope.

[0077] The cumulative strain energy is calculated at each monitoring moment to obtain a cumulative strain energy sequence. The sequence is then differentiated over time to obtain the change in the strain energy release rate over time. A strain energy release rate > 0 indicates that energy is accumulating, the slope is storing stress, and deformation is mainly elastic; a strain energy release rate < 0 indicates that energy is being released, the slope is undergoing irreversible plastic deformation or failure, and is a precursor to instability. A sharp increase (positive value) or a sharp decrease (negative value) in the strain energy release rate are key signals of drastic changes in stability.

[0078] This embodiment combines the depth and horizontal displacement data of the fiber optic grating sensor to construct a displacement rate-depth curve to identify the depth of the slip surface, retrieves the equivalent shear modulus to construct a strain energy density-depth curve and integrates it to obtain the cumulative strain energy, and then calculates the strain energy release rate. This not only accurately locates the specific depth of the slip surface, but also captures the energy accumulation and release patterns during the slip surface formation process through energy indicators, and predicts the evolution trend and instability risk of the slip surface in advance.

[0079] One possible implementation of this application embodiment involves performing parameter inversion based on displacement data to obtain slope stability parameters, including: Construct an objective function that represents the difference between the displacement predicted by the model and the actual monitored displacement; An optimization algorithm is used to update the equivalent internal friction angle and equivalent cohesion in each iteration. Displacement simulation is performed using a pre-set slope simulation model, and the function value of the objective function is calculated. When the function value of the objective function meets the preset optimization objective or reaches the maximum number of iterations, the iteration stops, and the slope stability parameters obtained by the preset slope simulation model inversion are received. The slope stability parameters include the equivalent internal friction angle and the equivalent cohesion.

[0080] In this embodiment, the sum of squares of the differences between the predicted and actual values ​​of all displacement monitoring points is constructed as the objective function. The objective function represents the degree of mismatch between the mechanical parameters and the actual situation in the current iteration process. The larger the function value of the objective function, the less accurate the model parameters are. The optimization algorithm can be a particle swarm optimization algorithm or a genetic algorithm; this embodiment is not limited to either. The preset slope simulation model can be a finite element simulation model, constructed based on the actual physical structure of the slope. The equivalent internal friction angle and equivalent cohesion are strength parameters of the slope soil or rock mass, used to reflect the ability to resist sliding failure forces.

[0081] This embodiment constructs an objective function to represent the difference between the predicted displacement and the actual monitored displacement. It uses an optimization algorithm to iteratively update the equivalent internal friction angle and cohesion. The objective function value is calculated through simulation. When the optimization objective is met or the maximum number of iterations is reached, stable parameters are output. This effectively solves the problem of the disconnect between traditional stable parameters and the actual situation on site, and enables the parameters obtained by inversion to accurately match the stress state of the slope on site.

[0082] The above embodiments introduce a method for monitoring the deformation of high slopes from the perspective of process flow. The following embodiments introduce a system for monitoring the deformation of high slopes from the perspective of system composition. For details, please refer to the following embodiments.

[0083] This application provides a high slope deformation monitoring system, such as Figure 7As shown, the system may include: a CCD micro-deformation monitoring instrument, displacement monitoring pile, GPS monitoring device, fiber optic inclinometer, pore water pressure gauge and electronic equipment installed on each slope section, with the slope sections arranged at first preset distances along the route direction; The CCD micro-deformation monitoring instrument is installed on the slope surface to collect the first displacement data of the slope. Displacement monitoring piles are installed at the second preset distance outside the slope line of the slope section to provide a displacement monitoring benchmark. GPS monitoring devices, GPS monitoring points buried in the slope section, are used to collect second displacement data of the GPS monitoring points relative to the displacement monitoring piles; A fiber optic grating inclinometer is installed at the top of the slope section to collect horizontal displacement data of the slope depth. A pore water pressure gauge is buried in the soil below the slope section to collect water pressure data.

[0084] The high slope deformation monitoring system provided in this application is applicable to the above method embodiments, and will not be described again here.

[0085] This application provides an electronic device, such as... Figure 8 As shown, Figure 8 The illustrated electronic device 800 includes a processor 801 and a memory 803. The processor 801 and the memory 803 are connected, for example, via a bus 802. Optionally, the electronic device 800 may also include a transceiver 804. It should be noted that in practical applications, the transceiver 804 is not limited to one type, and the structure of this electronic device 800 does not constitute a limitation on the embodiments of this application.

[0086] Processor 801 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 801 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0087] Bus 802 may include a pathway for transmitting information between the aforementioned components. Bus 802 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 802 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 8 The symbol is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0088] The memory 803 may be ROM (Read Only Memory) or other types of static storage devices capable of storing static information and instructions, RAM (Random Access Memory) or other types of dynamic storage devices capable of storing information and instructions, or EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0089] The memory 803 is used to store the application code for executing the scheme of this application, and its execution is controlled by the processor 801. The processor 801 is used to execute the application code stored in the memory 803 to implement the content shown in the aforementioned embodiments of the high slope deformation monitoring method.

[0090] Figure 8 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0091] This application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the contents shown in the aforementioned embodiments of the high slope deformation monitoring method.

[0092] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0093] This application provides a computer program product, including a computer program, which, when executed by a processor, implements the content shown in the aforementioned high slope deformation monitoring method embodiment.

[0094] The above are only some embodiments of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for monitoring deformation of high slopes, characterized in that, include: It receives the first displacement data collected by the CCD micro-deformation monitoring instrument, the second displacement data of the GPS monitoring point relative to the displacement monitoring pile, the horizontal displacement data collected by the fiber optic inclinometer, and the water pressure data collected by the pore water pressure gauge; Displacement data is obtained by fusing the first displacement data and the second displacement data, and displacement collaborative analysis results are generated based on the displacement data; Based on the displacement co-analysis results and the water pressure data, a coupled analysis result is generated; Based on the horizontal displacement data, generate slip surface analysis results; Constraints are extracted from the slip surface analysis results and water pressure data, applied to the preset slope simulation model, and parameter inversion is performed based on the displacement data to obtain slope stability parameters. Based on the displacement synergy analysis results, the coupling analysis results, the slip surface analysis results, and the slope stability parameters, the comprehensive risk index and the dominant risk factors are determined. The displacement data includes the coordinate data of each displacement monitoring point on the slope cross section at each monitoring time; The generation of displacement collaborative analysis results based on the displacement data includes: Based on the displacement data, determine the horizontal composite displacement sequence of each displacement monitoring point and the horizontal displacement direction angle in unit vector form; The sum of the horizontal displacement direction angles of all displacement monitoring points on the slope section is calculated to obtain the composite vector, and the direction of the composite vector is calculated as the potential main sliding direction; Determine the total number of all displacement monitoring points on the slope cross section, calculate the length of the composite vector, and calculate the ratio of the composite vector length to the total number to obtain the displacement direction consistency coefficient; A correlation coefficient matrix is ​​constructed based on the horizontal combined displacement sequence of each monitoring point. The potential main sliding direction, the displacement direction consistency coefficient, and the correlation coefficient matrix constitute the displacement collaborative analysis result.

2. The method for monitoring high slope deformation according to claim 1, characterized in that, The construction of the correlation coefficient matrix based on the horizontal combined displacement sequence of each displacement monitoring point includes: For each displacement monitoring point, a displacement rate sequence is determined based on the horizontal combined displacement sequence of the displacement monitoring point; A displacement rate matrix is ​​constructed based on the displacement rate sequence of each displacement monitoring point within a preset time window. In the displacement rate matrix, rows represent displacement monitoring points, columns represent monitoring times, and elements represent the displacement rate sequence of the corresponding displacement monitoring point within the preset time window at the corresponding monitoring time. A correlation coefficient matrix is ​​constructed based on the displacement rate matrix, and the elements of the correlation coefficient matrix represent the correlation between the displacement rates of two corresponding displacement monitoring points within the preset time window.

3. The method for monitoring high slope deformation according to claim 1, characterized in that, The water pressure data includes the water pressure value at each water pressure monitoring point on the slope cross section at each monitoring time; The generation of coupled analysis results based on the displacement co-analysis results and the water pressure data includes: Extract the water pressure value sequence of the target water pressure monitoring point from the water pressure data, wherein the target water pressure monitoring point is any water pressure monitoring point on the slope section; Determine the target displacement monitoring point that matches the target water pressure monitoring point, and extract the displacement rate sequence of the target displacement monitoring point from the displacement collaborative analysis results; Based on the water pressure value sequence and the displacement rate sequence, determine the response delay and response gain of the target water pressure monitoring point; Based on the response delay and response gain of all water pressure monitoring points on the slope section, the coupling mode, water pressure sensitivity coefficient and stability trend are determined. The coupling mode includes shallow slippage mode and deep burrowing mode. The coupling mode, the water pressure sensitivity coefficient, and the stability trend constitute the coupling analysis results.

4. The method for monitoring high slope deformation according to claim 3, characterized in that, The determination of the response delay and response gain of the target water pressure monitoring point based on the water pressure value sequence and the displacement rate sequence includes: Identify the peak water pressure time of the water pressure value sequence and the peak displacement rate time of the displacement rate sequence, and calculate the response delay between the peak displacement rate time and the peak water pressure time; Identify peak water pressure and background water pressure values ​​from the water pressure value sequence, and calculate the water pressure increment based on the peak water pressure and the background water pressure values; Identify the peak displacement rate and background displacement rate value from the displacement rate sequence of the target displacement monitoring point, and calculate the displacement rate increment based on the peak displacement rate and the background displacement rate value; The response gain is calculated based on the increment of the water pressure value and the increment of the displacement rate.

5. The method for monitoring high slope deformation according to claim 1, characterized in that, The horizontal displacement data includes the coordinate data of each fiber grating sensor on the fiber grating inclinometer at each monitoring moment; The generation of slip surface analysis results based on the horizontal displacement data includes: Determine the depth data for each fiber Bragg grating sensor, construct a displacement rate-depth curve based on the depth data and the horizontal displacement data, and identify the slip surface depth from the displacement rate-depth curve; The equivalent shear modulus of the slope is retrieved, and a strain energy density depth curve is constructed based on the displacement rate depth curve and the equivalent shear modulus. The cumulative strain energy is obtained by integrating the strain energy density depth curve. The strain energy release rate is calculated based on the cumulative strain energy at each monitoring moment; The slip surface depth, the cumulative strain energy, and the strain energy release rate constitute the slip surface analysis results.

6. The method for monitoring deformation of high slopes according to claim 1, characterized in that, The process of performing parameter inversion based on the displacement data to obtain slope stability parameters includes: Construct an objective function, which characterizes the difference between the displacement predicted by the model and the actual monitored displacement; An optimization algorithm is used to update the equivalent internal friction angle and equivalent cohesion in each iteration. Displacement simulation is performed using the preset slope simulation model, and the function value of the objective function is calculated. When the function value of the objective function meets the preset optimization target or reaches the maximum number of iterations, the iteration stops, and the slope stability parameters obtained by the inversion of the preset slope simulation model are received. The slope stability parameters include the equivalent internal friction angle and the equivalent cohesion.

7. A high slope deformation monitoring system, characterized in that, include: Each slope section is equipped with a CCD micro-deformation monitoring instrument, displacement monitoring pile, GPS monitoring device, fiber optic inclinometer, pore water pressure gauge and electronic equipment. The slope sections are arranged at first preset distances along the route. The CCD micro-deformation monitoring instrument is installed on the slope surface to collect the first displacement data of the slope. The displacement monitoring pile is buried at a second preset distance outside the slope line of the slope section to provide a displacement monitoring benchmark. The GPS monitoring device is installed at the GPS monitoring point on the slope section to collect the second displacement data of the GPS monitoring point relative to the displacement monitoring pile; The fiber optic inclinometer is installed at the top of the slope section to collect horizontal displacement data of the slope depth. The pore water pressure gauge is buried in the soil below the slope section and is used to collect water pressure data. The electronic device is used to perform the high slope deformation monitoring method according to any one of claims 1-6.

8. The high slope deformation monitoring system according to claim 7, characterized in that, The electronic device includes: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, said at least one application being configured to: perform the high slope deformation monitoring method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed in the computer, the computer is instructed to perform the high slope deformation monitoring method according to any one of claims 1-6.

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