High slope stability performance quantity mutation monitoring and panoramic early warning method and system

Abstract

The application discloses a high-slope stability energy mutation monitoring and panoramic early warning method and system. The method comprises the following steps: establishing a unified space reference framework of a target high slope, constructing a numerical analysis model and a panoramic real scene model based on the framework, and associating monitoring data to the numerical analysis model; gradually reducing rock-soil strength parameters and tracking energy response parameter values of characteristic discrete units; when the energy response parameter value change rate exceeds a threshold value, the corresponding reduction value is taken as a stability criterion value; when the stability criterion value is lower than a safety threshold value, a region where yield units form a continuous through zone and shear strain exceeds a threshold value is identified as a potential slip zone according to mechanical response data; and the spatial position information of the potential slip zone is superimposed on the panoramic real scene model space to generate a risk-identified early warning panorama and interactively display. The application realizes a closed loop from energy mutation analysis to panoramic early warning, and improves the accuracy and intuitiveness of slope early warning.

Description

Technical Field

[0001] This invention belongs to the field of geotechnical engineering slope stability monitoring and early warning technology, specifically involving a method and system for monitoring and panoramic early warning of energy mutation in high slope stability, which can be used for stability analysis and early warning of instability disasters of high slopes in fields such as hydropower engineering, highway construction, and mining. Background Technology

[0002] Currently, the stability of high slopes in water conservancy and hydropower projects, highway construction, and mining operations is directly related to the safe operation of these projects. Slope instability can lead to serious disasters, often triggering landslides, debris flows, and other geological hazards, posing a severe threat to engineering construction and the ecological environment. Therefore, in-depth research on slope stability and its instability and disaster evolution mechanisms is of great significance for ensuring engineering safety and reducing disaster losses.

[0003] Existing slope stability analysis methods mainly suffer from the following technical shortcomings: Instability criteria are greatly influenced by human factors and lack accuracy. Traditional slope stability analysis methods mainly include the limit equilibrium method and the strength reduction method. The limit equilibrium method requires pre-assuming the location of the sliding surface, limiting its applicability to high slopes under complex geological conditions. Although the strength reduction method can automatically determine the safety factor, its instability criteria often rely on traditional indicators such as abrupt displacement, plastic zone penetration, or calculation non-convergence. These criteria are greatly affected by human factors such as grid density and boundary conditions, resulting in discrepancies in calculation results and a lack of a unified and objective standard for determining instability.

[0004] Existing energy-based criteria lack a complete monitoring and early warning loop. In recent years, the theory of energy catastrophe has gradually gained attention in slope stability analysis, providing a new approach to stability evaluation by analyzing the energy changes during slope instability. However, existing energy-based research mostly remains at the numerical analysis level, only outputting abstract indicators such as safety factors, failing to intuitively map the analysis results to the engineering site, and lacking a complete technical chain from "analysis and judgment" to "visualized early warning".

[0005] The monitoring data is presented in a simplistic way, lacking intuitive spatial positioning methods. Existing slope monitoring data is mostly presented in two-dimensional charts or numerical cloud maps, with spatial location information of risk areas presented as coordinate data or color blocks. This makes it difficult for on-site personnel to quickly correlate the data with the actual terrain, hindering the rapid and accurate understanding of the overall slope stability and the engineering positioning of risk areas.

[0006] Multi-source data lacks a unified spatial benchmark. Monitoring data, numerical analysis models, and on-site images belong to different coordinate spaces. The lack of a unified spatial reference framework for data fusion results in monitoring data not being able to be directly used to drive numerical analysis models, and analysis results not being able to be directly superimposed onto real-world displays, creating data silos between different stages.

[0007] Therefore, providing a method and system for monitoring and providing panoramic early warning of energy mutations in the stability of high slopes that can objectify instability criteria, visualize analysis results, and complete data chains is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0008] To address the aforementioned technical problems, this invention provides a method and system for monitoring and providing panoramic early warning of energy mutations in the stability of high slopes, thereby overcoming the technical deficiencies in existing technologies, such as the instability criteria being greatly affected by human factors, the lack of intuitive means of displaying analysis results, and incomplete data chains.

[0009] This invention constructs a "unified spatial reference frame" as a data fusion benchmark, places the numerical analysis model and the panoramic real-scene model in the same spatial coordinate system, and uses "energy mutation" as an objective criterion for slope instability, thus realizing a complete closed loop from monitoring data collection, numerical analysis, instability identification to panoramic early warning display.

[0010] The system adopts a modular architecture, consisting of a unified spatial reference frame module, a model building module, a data association module, an energy tracking and mutation determination module, an instability identification module, and a panoramic early warning display module. The modules work together to form a complete closed-loop system.

[0011] Specifically, this invention establishes a unified spatial reference framework for the target high slope, and constructs a numerical analysis model and a panoramic real-scene model based on this framework, allowing the two models to share the same spatial coordinate system. After linking the monitoring data to the numerical analysis model, the strength parameters of the soil and rock are progressively reduced using a strength reduction method to track the energy response parameters (kinetic energy and gravitational potential energy) of the characteristic discrete units. When a sudden change occurs in the energy response parameters, a stability criterion value is locked. When the criterion value is lower than the safety threshold, mechanical response data is extracted to identify potential landslide zones. Finally, the spatial location information of the potential landslide zones is mapped onto the panoramic real-scene model to generate a warning panorama with risk indicators, which is then interactively displayed via a mobile terminal.

[0012] Thus, this invention realizes a complete closed loop from spatial benchmark establishment, dual-mode construction, data association, energy tracking, mutation determination, instability identification to panoramic early warning, significantly improving the objectivity, accuracy and intuitiveness of high slope stability analysis and early warning information.

[0013] According to one aspect of the present invention, a method for monitoring and providing panoramic early warning of energy mutations in the stability of high slopes is provided, comprising the following steps: A unified spatial reference framework for the target high slope is established; based on the unified spatial reference framework, a numerical analysis model and a panoramic real-scene model of the target high slope are constructed respectively. The numerical analysis model consists of multiple discrete units, and each discrete unit has unique spatial location information; the monitoring data of the target high slope is associated with the corresponding discrete unit in the numerical analysis model. The soil and rock strength parameters of the numerical analysis model are reduced step by step, and the energy response parameter values ​​of multiple characteristic discrete units in the numerical analysis model are tracked after each reduction. When the rate of change of the energy response parameter value of at least one of the characteristic discrete units exceeds a preset rate of change threshold after any level of reduction, the reduction value corresponding to the level of reduction that has changed will be used as the stability criterion value of the high slope. When the stability criterion value is lower than a preset safety threshold, the mechanical response data output by the numerical analysis model after the change at that level is extracted. The mechanical response data includes at least the yield state identifier of each discrete element and the shear strain value of each discrete element. Based on the mechanical response data, all discrete elements whose yield state identifier is yielded are marked as yielding elements. If each yielding element forms a continuous through zone in space, and the shear strain value of each yielding element in the continuous through zone exceeds the preset shear strain threshold, then the spatial region where the continuous through zone is located is identified as a potential slip zone, and the spatial location information of the potential slip zone is obtained. According to the unified spatial reference framework, the spatial location information of the potential slip zone is spatially superimposed with the corresponding spatial location in the panoramic real-scene model to generate a warning panorama with risk indicators, and the warning panorama is interactively displayed through a mobile terminal.

[0014] Another aspect of the present invention provides a high slope stability energy mutation monitoring and panoramic early warning system, which includes: The Unified Spatial Reference Frame module is used to establish a unified spatial reference frame for the target high slope. The model building module is used to build a numerical analysis model and a panoramic real-scene model of the target high slope based on the unified spatial reference frame. The numerical analysis model is composed of multiple discrete units, and each discrete unit has unique spatial location information. The data association module is used to associate the monitoring data of the target high slope with the corresponding discrete unit in the numerical analysis model; The energy tracking and mutation determination module is used to progressively reduce the soil and rock strength parameters of the numerical analysis model and track the energy response parameter values ​​of multiple feature discrete units in the numerical analysis model after each reduction. When the rate of change of the energy response parameter value of at least one feature discrete unit exceeds a preset rate of change threshold after any reduction, the reduction value corresponding to the reduction at that level is used as the stability criterion value of the high slope. The instability identification module is used to extract the mechanical response data output by the numerical analysis model after the change in the corresponding level when the stability criterion value is lower than a preset safety threshold. The mechanical response data includes at least the yield state identifier of each discrete element and the shear strain value of each discrete element. Based on the mechanical response data, all discrete elements with yield state identifiers indicating yielding are marked as yielding elements. If each yielding element forms a continuous through-zone in spatial location, and the shear strain value of each yielding element within the continuous through-zone exceeds a preset shear strain threshold, then the spatial region where the continuous through-zone is located is identified as a potential slip zone, and the spatial location information of the potential slip zone is obtained. The panoramic early warning display module is used to spatially overlay the spatial location information of the potential slip zone with the corresponding spatial location in the panoramic real-scene model according to the unified spatial reference framework, generate an early warning panorama with risk indicators, and display the early warning panorama interactively through a mobile terminal.

[0015] Compared with the prior art, the present invention has the following beneficial effects: The instability criterion is made objective, eliminating the influence of human factors. This invention uses energy mutation (a sharp increase in kinetic energy and a sharp decrease in gravitational potential energy) as the criterion for determining slope instability, replacing the traditional method's reliance on grid density and boundary conditions for displacement mutations or non-convergence calculations. The rate of change threshold of the energy response parameters is an objective quantitative indicator, and the judgment result does not change with the model discretization method, significantly improving the accuracy and consistency of stability analysis.

[0016] This invention achieves a complete technological closed loop from "numerical analysis" to "panoramic early warning." Existing energy-based judgment methods only output numerical results such as safety factors. This invention places the numerical analysis model and the panoramic real-scene model under the same spatial reference frame through a unified spatial reference frame. It directly maps the analysis results (spatial location information of potential slip zones) to the real-scene model, generating a panoramic early warning system with risk indicators, thus filling the technological gap between analysis and judgment and visual early warning.

[0017] The spatial positioning of risk areas is intuitive, significantly improving on-site decision-making efficiency. This invention overlays the spatial location information of potential slip zones onto a panoramic real-world model via coordinate mapping, generating risk markers in a display method distinct from the background. On-site engineers can directly and intuitively locate the spatial distribution of risk areas within the panoramic scene without needing to consult coordinate data or cloud maps, greatly shortening the decision-making time from data interpretation to on-site handling.

[0018] This invention unifies spatial references across multiple data sources, eliminating data silos. By establishing a unified spatial reference framework, monitoring data, numerical analysis models, and panoramic reality models share the same coordinate system. This enables a complete data chain where monitoring data directly drives numerical analysis, and analysis results are directly mapped to the reality display, with seamless connections between each stage. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the overall architecture of the high slope stability energy mutation monitoring and panoramic early warning system provided in this embodiment of the invention, showing six core modules and their interrelationships: unified spatial reference frame module, model building module, data association module, energy tracking and mutation judgment module, instability identification module, and panoramic early warning display module. Figure 2 The flowchart of the high slope stability energy mutation monitoring and panoramic early warning method provided in the embodiment of the present invention shows the complete process from the establishment of a unified spatial reference frame, the construction of numerical analysis model and panoramic real scene model, the correlation of monitoring data, energy tracking and mutation judgment, instability identification to panoramic early warning display. Figure 3 This is a graph showing the variation of energy response parameters of the characteristic discrete unit with the reduction coefficient in an embodiment of the present invention. Specifically: (a) is the kinetic energy-reduction coefficient relationship curve for characteristic unit A, (b) is the kinetic energy-reduction coefficient relationship curve for characteristic unit B, and (c) is the gravitational potential energy-reduction coefficient relationship curve for characteristic unit A. When the reduction coefficient increases from 2.11 to 2.12, the kinetic energy of each characteristic unit shows a sharp increase, and the gravitational potential energy simultaneously shows a sharp decrease. Therefore, the reduction coefficient of 2.11 is determined as the stability criterion value. Figure 4 This is a comparison of the maximum shear strain increment cloud maps of the slope under the natural stable state and the critical instability state provided in the embodiments of the present invention. Wherein: (a) is the natural stable state (reduction factor) (a) shows the maximum shear strain increment contour map, with the bottom accumulation concentration area having only a very small amount of plastic zone at the junction of the slope angle and the ground; (b) shows the critical instability state (reduction factor). Figure (a) shows the maximum shear strain increment cloud map, with a large area of ​​plastic zone appearing in the middle and upper local concentrated area, forming a continuous through zone from the top of the slope to the bottom of the slope; (c) shows the curves of failure volume, shear volume and tensile volume changing with the calculation step, with a sudden change in failure volume between stage F=1.0 and stage F=2.12. Figure (a) and Figure (b) show the evolution process of the plastic zone from discrete to continuous. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] The embodiments of this invention are written in a progressive manner.

[0023] Terminology Explanation To facilitate understanding of the technical solution of this invention, some technical terms appearing in the specification are explained as follows: FLAC3D (Fast Lagrangian Analysis of Continua in 3 Dimensions) is a three-dimensional numerical analysis software based on the finite difference method. It is widely used in geotechnical engineering for simulation and analysis of problems such as slope stability, underground excavation, and foundation settlement. This software divides the computational domain into grid cells and uses an explicit time-stepping algorithm to solve the equations of motion, making it suitable for large deformation and nonlinear analysis of soil and rock masses.

[0024] Fish (FLAC3D's built-in scripting language) is a scripting programming language built into the FLAC3D software. Users can write Fish functions to customize and control the calculation process, including custom operations such as parameter reduction, data extraction, and energy calculation.

[0025] The strength reduction method is a numerical analysis method that refers to the method of gradually reducing the shear strength parameters (cohesion and internal friction angle) of the soil and rock mass until the slope reaches the critical instability state, and then using the reduction coefficient at this point as the slope stability safety factor.

[0026] The Mohr-Coulomb yield criterion is the most widely used strength theory in geotechnical mechanics. It states that when the shear stress on a cross-section of a material reaches its shear strength, determined by cohesion and normal stress, the material undergoes shear yielding. This criterion utilizes cohesion... and internal friction angle Two parameters describe the shear strength characteristics of soil and rock masses.

[0027] Principal stresses are the normal stresses on a cross section of an object where the shear stress is zero at a given point. The three principal stresses, ordered by magnitude, are: the maximum principal stress... Intermediate principal stress and minimum principal stress ( > > (with compressive stress as positive).

[0028] The plastic zone (yield zone) refers to the stress state in rock and soil that has reached the yield condition. In the region of a slope, the material undergoes irreversible plastic deformation. When the plastic zone forms a continuous, penetrating band within the slope, it usually signifies the beginning of overall slope instability.

[0029] Shear strain refers to the change in shape of a rock or soil mass under shear stress. The maximum shear strain increment is an important indicator for identifying areas of concentrated shear deformation.

[0030] A panoramic real-scene model refers to a three-dimensional real-scene display model that can be viewed from all angles by stitching and fusion of real-scene images taken from multiple angles.

[0031] Mobile terminals refer to portable electronic devices such as smartphones and tablets that have QR code scanning and panoramic browsing functions.

[0032] The terms used above are only for explaining specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Those skilled in the art will understand that other existing technologies with the same or similar functions can be employed without departing from the concept of the present invention.

[0033] Example 1: System Architecture like Figure 1 As shown, this invention provides a high slope stability energy mutation monitoring and panoramic early warning system. Its core lies in establishing a unified spatial reference framework, enabling the numerical analysis model and the panoramic real-world model to share the same spatial coordinate system, thus achieving a complete closed loop from monitoring data acquisition, numerical analysis, instability identification to panoramic early warning display. The system adopts a modular architecture, consisting of six core modules that work collaboratively to achieve the above functions.

[0034] Specifically, the system includes the following functional modules: The Unified Spatial Reference Frame module is used to establish a unified spatial reference frame for the target high slope. This module establishes a Cartesian three-dimensional coordinate system with a point at the toe of the slope as the origin, defines the coordinate axis directions (e.g., the x-axis coincides with the tailrace tunnel axis, the y-axis is perpendicular to the tailrace tunnel axis, and the z-axis coincides with the geodetic coordinate system with upward orientation) and length units, providing a consistent spatial benchmark for all subsequent models and data.

[0035] The model building module is used to construct a numerical analysis model and a panoramic real-scene model of the target high slope based on the unified spatial reference frame. The numerical analysis model is built in finite difference / finite element software such as FLAC3D or ABAQUS, and consists of multiple discrete elements, each with unique spatial location information (three-dimensional coordinates). The panoramic real-scene model is stitched together from panoramic images taken from multiple angles, using an 8mm fisheye lens, taking one image every 60°, for a total of six images.

[0036] The data association module is used to associate the monitoring data of the target high slope with the corresponding discrete elements in the numerical analysis model. This module sets up multiple monitoring points at different elevations on the target high slope (e.g., characteristic monitoring points A, B, and C, with elevations of 1082m, 949m, and 771m respectively), collects displacement and stress monitoring data, and assigns the monitoring data to the discrete elements corresponding to the spatial location information in the numerical analysis model according to the spatial location information of each monitoring point within a unified spatial reference frame, for subsequent strength reduction analysis.

[0037] The energy tracking and mutation determination module is used to progressively reduce the soil and rock strength parameters of the numerical analysis model, and to track the energy response parameter values ​​of multiple characteristic discrete units in the numerical analysis model after each reduction. This module uses the strength reduction method, according to the formula... Gradually reduce cohesion according to the formula The internal friction angle is reduced step by step, where, For cohesion, It is the internal friction angle. This is the current reduction value. To reduce the cohesive force, The internal friction angle after reduction. After each reduction stage, the kinetic energy and gravitational potential energy values ​​of each characteristic discrete unit are recorded, forming the kinetic energy value sequence and gravitational potential energy value sequence of each characteristic discrete unit under the reduction sequence. When, after any reduction stage, the kinetic energy value increase factor between two adjacent reduction stages in the kinetic energy value sequence of at least one characteristic discrete unit exceeds a preset kinetic energy increase factor threshold, and the gravitational potential energy value decrease between two adjacent reduction stages in the gravitational potential energy value sequence of the same characteristic discrete unit exceeds a preset gravitational potential energy decrease threshold, the reduction value corresponding to the changed reduction stage is used as the stability criterion value of the high slope.

[0038] The instability identification module is used to extract the mechanical response data output by the numerical analysis model after the change in that level of reduction when the stability criterion value is lower than a preset safety threshold. The mechanical response data includes at least the yield state identifier and the shear strain value of each discrete element. The yield state identifier is determined according to the Mohr-Coulomb yield function: when the maximum principal stress of the discrete element... and minimum principal stress satisfy When the discrete element yields, its yield state is identified as yielded, where... The yield function value is used. Based on the mechanical response data, all discrete elements that have yielded are marked as yielding elements. The spatial location information of each yielding element within a unified spatial reference frame is obtained. Spatial adjacency analysis is used to determine whether there is a spatial adjacency relationship between the yielding elements. If so, the yielding elements with spatial adjacency are marked as the same connected region. When the yielding elements within any connected region extend continuously from the slope crest boundary to the slope toe boundary of the numerical analysis model, the connected region is determined to be a continuous zone. If the yielding elements form a continuous zone in spatial location, and the shear strain value of each yielding element within the continuous zone exceeds a preset shear strain threshold, the spatial region where the continuous zone is located is identified as a potential slip zone. The spatial location information of the potential slip zone is obtained and output to the panoramic early warning display module.

[0039] The panoramic early warning display module is used to spatially overlay the spatial location information of the potential slip zone with the corresponding spatial location in the panoramic real-scene model according to the unified spatial reference framework, generating an early warning panorama with risk indicators, and displaying it interactively via a mobile terminal. This module establishes a spatial coordinate mapping relationship between the numerical analysis model and the panoramic real-scene model based on the unified spatial reference framework, converting the spatial location information of the numerical analysis model into scene coordinates of the panoramic real-scene model. According to this mapping relationship, the spatial location information of the potential slip zone is mapped to the scene coordinate system of the panoramic real-scene model to obtain the corresponding scene coordinate region. Risk indicators are generated on the scene coordinate region in a display manner distinct from the background. Further, risk information of the potential slip zone (including at least the stability criterion value and the spatial location information of the potential slip zone) is obtained. The risk level of the potential slip zone is determined based on the risk information. Risk indicators are then layered and overlaid on the panoramic real-scene model according to the risk level and the corresponding display style to generate the early warning panorama. The risk indicators are dynamically updated as the stability criterion value changes.

[0040] The six functional modules mentioned above work together to form a complete closed-loop system. The unified spatial reference frame module provides a spatial benchmark for the model building module; the model building module establishes both the numerical analysis model and the panoramic real-scene model; the data association module associates the monitoring data with the numerical analysis model; the energy tracking and mutation determination module completes intensity reduction and energy mutation analysis and outputs stability criterion values; the instability identification module extracts mechanical response data and identifies potential slip zones when the criterion value is lower than the safety threshold; and the panoramic early warning display module maps the identification results to the panoramic real-scene model for visualization.

[0041] All modules communicate with each other through well-defined data interfaces, ensuring the scalability and stability of the system.

[0042] Example 2: General Process like Figure 2 As shown, this invention provides a method for monitoring and providing panoramic early warning of energy mutations in the stability of high slopes, comprising the following steps S1 to S5: S1: Establishment of a unified spatial reference frame, construction of dual models, and data association This step is performed by the Unified Spatial Reference Frame module, the Model Building module, and the Data Association module.

[0043] First, establish a unified spatial reference framework for the target high slope. Establish a Cartesian three-dimensional coordinate system with a point at the toe of the slope as the origin, defining the direction and unit of length for the coordinate axes. For example, with the center point of the high diversion tunnel outlet as the origin, the x-axis coincides with the tailrace tunnel axis and points towards the outlet (positive), the y-axis is perpendicular to the tailrace tunnel axis, and the z-axis coincides with the geodetic coordinate system and points upwards (positive).

[0044] Then, based on a unified spatial reference frame, a numerical analysis model and a panoramic real-scene model of the target high slope were constructed. The numerical analysis model was built in FLAC3D and consists of multiple discrete elements (e.g., divided into 47,665 elements and 51,202 nodes), each with unique spatial location information (i.e., three-dimensional coordinates). The panoramic real-scene model was constructed as follows: using an 8mm fisheye lens, six multi-angle panoramic images were taken at 60° intervals, and the images were stitched together to generate a panoramic real-scene model that can be viewed in 360°.

[0045] Finally, the monitoring data of the target high slope are correlated to the corresponding discrete elements in the numerical analysis model. Monitoring points are set up at different elevations of the target high slope (e.g., 1082m, 949m, 771m) to collect displacement and stress monitoring data. According to the spatial location information of each monitoring point within a unified spatial reference frame, the displacement and stress monitoring data are assigned to the discrete elements corresponding to the spatial location information in the numerical analysis model.

[0046] S2: Energy Tracking This step is performed by the energy tracing and mutation determination module.

[0047] The soil and rock strength parameters of the numerical analysis model are reduced step by step. These parameters include cohesion and internal friction angle, and are reduced step by step according to the following formula: ; ; in, For cohesion, It is the internal friction angle. This is the current reduction value. To reduce the cohesive force, This is the reduced internal friction angle.

[0048] After each reduction stage, the energy response parameters of multiple characteristic discrete units in the numerical analysis model are tracked. These energy response parameters include kinetic energy and gravitational potential energy. After each reduction stage, the kinetic energy and gravitational potential energy values ​​of each characteristic discrete unit are recorded, forming a sequence of kinetic energy and gravitational potential energy values ​​for each characteristic discrete unit under the reduction sequence.

[0049] Taking a high slope near the dam area of ​​a hydropower project as an example, characteristic units A, B, and C were selected at different elevations (1082m, 949m, and 771m) on the slope. Energy data was recorded using the Zextra unit storage function in FLAC3D via Fish programming. The reduction factor F started at 1.0 and increased gradually in increments of 0.01 until the critical value.

[0050] S3: Energy Mutation Determination and Stability Criterion Value Locking This step is performed by the energy tracing and mutation determination module.

[0051] When the rate of change of the energy response parameter value of at least one characteristic discrete unit exceeds a preset rate of change threshold after any level of reduction, the reduction value corresponding to the level of reduction that has changed will be used as the stability criterion value of the high slope.

[0052] Specifically, in the kinetic energy value sequence of the same characteristic discrete unit, when the growth factor of the kinetic energy value between two adjacent reduction levels exceeds a preset kinetic energy growth factor threshold, and in the gravitational potential energy value sequence of the same characteristic discrete unit, when the decrease in the gravitational potential energy value between two adjacent reduction levels exceeds a preset gravitational potential energy decrease threshold, an energy mutation is determined to have occurred.

[0053] For example, taking characteristic unit A as an example, the reduction coefficient When the value increases from 2.11 to 2.12, the kinetic energy value changes from... Leap to The growth rate was 9.6 times, exceeding the preset kinetic energy growth rate threshold (e.g., 3 times); the gravitational potential energy value increased from... Down to The decrease exceeds the preset threshold for the decrease in gravitational potential energy. At this point, an energy mutation is determined, and the energy level of that stage will be reduced accordingly (…). The corresponding reduction value of 2.11 is used as the stability criterion value for the high slope.

[0054] If the energy mutation points of multiple discrete characteristic units occur at different reduction coefficients, the reduction coefficient at which the energy mutation occurs first shall be used as the stability criterion value; if the energy mutation points of multiple discrete characteristic units occur at the same reduction coefficient, the reduction coefficient shall be jointly identified as the stability criterion value.

[0055] S4: Instability Identification and Potential Slip Zone Determination This step is performed by the instability identification module.

[0056] When the stability criterion value is lower than the preset safety threshold, the mechanical response data output by the numerical analysis model after reduction at that stage of change is extracted. The preset safety threshold is determined with reference to the provisions on slope stability safety factors in the national standard "Technical Specification for Building Slope Engineering" (GB50330-2013). Depending on the slope engineering grade and working conditions (e.g., a first-grade slope under self-weight conditions), the standard value of the safety factor is typically between 1.25 and 1.35. In this embodiment, the preset safety threshold is 1.30. It should be noted that this value is only one implementation method of the present invention; those skilled in the art can determine the corresponding safety threshold based on the above specifications according to different engineering grades and geological conditions.

[0057] The mechanical response data includes at least the yield state identifier and the shear strain value of each discrete element.

[0058] The yield state is determined according to the Mohr-Coulomb yield function. This is based on the maximum principal stress of the discrete element. and minimum principal stress The discrete element is identified as having yielded when the following equation is satisfied: For the yield function value: ; Based on the mechanical response data, all discrete elements that have yielded are marked as yielded elements.

[0059] If each yielding element forms a continuous through zone in space, and the shear strain value of each yielding element within the continuous through zone exceeds a preset shear strain threshold, then the spatial region where the continuous through zone is located is identified as a potential slip zone, and the spatial location information of the potential slip zone is obtained.

[0060] The method for determining a continuous zone is as follows: The spatial location information of each yielding element within a unified spatial reference frame is obtained. A spatial adjacency analysis method (such as eight-neighborhood or twenty-six-neighborhood connectivity detection) is used to determine whether spatial adjacency exists between the yielding elements. If it exists, the yielding elements with spatial adjacency are marked as the same connected region. When yielding elements within any connected region continuously extend from the slope crest boundary to the slope toe boundary of the numerical analysis model, the connected region is determined to be a continuous zone.

[0061] Taking a high slope in a hydropower project as an example, the natural stable state ( There is only a very small plastic zone at the junction of the slope angle and the ground, which has no effect on the slope stability; the critical instability state ( Under these conditions, a large plastic zone appears in the upper and middle parts of the slope, extending from the top boundary to the toe boundary to form a continuous band, and the shear strain value within the continuous band exceeds a preset threshold (e.g., ...). ~ (At the scale of), the spatial region where the continuous passage is located is identified as a potential slip zone.

[0062] S5: Panoramic Overlay and Early Warning Display This step is performed by the panoramic early warning display module.

[0063] Following a unified spatial reference framework, the spatial location information of potential slip zones is spatially overlaid with the corresponding spatial location in the panoramic real-scene model to generate a warning panorama with risk indicators, which is then interactively displayed via mobile terminals.

[0064] Specifically, a spatial coordinate mapping relationship is established between the numerical analysis model and the panoramic reality model based on a unified spatial reference frame. This mapping relationship can be established using either the calibration point registration method or the direct coordinate matching method. According to the spatial coordinate mapping relationship, the spatial location information of the potential slip zone is mapped to the scene coordinate system of the panoramic reality model, obtaining the corresponding scene coordinate region. Risk markers are then generated on this scene coordinate region in a display manner distinct from the background. These risk markers can be dynamic, including one or more of the following: color-highlighted markers, flashing markers, or boundary wireframe markers, and / or displayed as overlaid semi-transparent color blocks.

[0065] Further, risk information about potential slip zones (including at least stability criterion values ​​and spatial location information of the potential slip zones) is acquired, and the risk level of the potential slip zones is determined based on this information. The risk level is determined by comparing the stability criterion value with a preset safety threshold; the smaller the difference, the higher the risk level. Specifically, when the stability criterion value is lower than the preset safety threshold and the difference is less than the preset low-risk threshold, it is classified as a low-risk level; when the difference is between the preset low-risk threshold and the preset high-risk threshold, it is classified as a medium-risk level; and when the difference is greater than the preset high-risk threshold, it is classified as a high-risk level. Different risk levels correspond to different display styles; for example, low-risk levels are indicated by a yellow boundary frame, medium-risk levels by an orange semi-transparent block, and high-risk levels by a bright red flashing indicator. According to the risk level, the risk indicators are layered and overlaid on the panoramic real-world model according to their corresponding display styles to generate a warning panorama. The risk indicators are dynamically updated as the stability criterion value changes.

[0066] The early warning panorama can be interactively displayed on mobile terminals in the following ways: the early warning panorama with risk labels is encoded into an interactive electronic link, the electronic link is converted into a QR code, and the electronic link is accessed by scanning the QR code with a mobile terminal. The early warning panorama is then displayed on the mobile terminal screen, and users can rotate, zoom, and click to view risk information.

[0067] Example 3: Stability Analysis and Early Warning Application of High Slopes Near Dam Area in Hydropower Projects This embodiment uses the high slope on the left bank of the stilling basin near the dam area of ​​a hydropower project as an application example to provide a detailed description of the high slope stability energy mutation monitoring and panoramic early warning method of the present invention. The rock mass of this slope is mainly composed of thin-layered limestone and medium-thick-layered limestone strata. The surface layer of the slope has strong unloading zones and weak unloading zones. The rock mass material parameters are relatively poor, and there is a potential risk of instability.

[0068] Step 1: Establishing a unified spatial reference frame, constructing a dual-model system, and associating data. A Cartesian three-dimensional coordinate system was established with a point at the toe of the slope as the origin. The x-axis, coinciding with the tailrace tunnel axis and pointing towards the outlet, was positive; the y-axis, perpendicular to the tailrace tunnel axis, was positive; and the z-axis, coinciding with the geodetic coordinate system, was positive upwards. Based on this framework, a numerical analysis model was built in FLAC3D. The model's dimensions were 268.18m × 230.90m × 339.00m (x × y × z), divided into 47,665 elements and 51,202 nodes. The model included structures such as the tailrace outlet slope, the tailrace tunnel, and the high diversion tunnel, and was simulated in 11 phases.

[0069] The numerical analysis model was established based on the engineering geological survey data of the target high slope. Rock mechanics parameters were obtained through laboratory rock mechanics tests on rock samples collected on-site from the target high slope. The deformation modulus was determined using the secant modulus at 50% compressive strength in a uniaxial compression test, while cohesion and internal friction angle were determined through triaxial shear tests or direct shear tests. The mechanical parameters of each rock layer and unloading zone are shown in Table 1.

[0070] Table 1. Values ​​of Rock Mass Mechanical Parameters

[0071] The significant differences in deformation modulus among different lithologies in Table 1 objectively reflect the engineering geological conditions of different rock strata. Among them, It is a thin-layered limestone with a deformation modulus of 6 GPa in the strong unloading zone, 14 GPa in the weak unloading zone, and 15 GPa in the fresh rock mass. It is a medium-thick layer of limestone, with the fresh rock mass being the most intact. The deformation modulus reaches 27 GPa, the strong unloading zone drops to 9.5 GPa, and the weak unloading zone is 21.5 GPa. The rock is a medium-thick layer of limestone. The deformation modulus of the fresh rock mass is 20 GPa, decreasing to 7 GPa in the strongly unloaded zone and 18 GPa in the weakly unloaded zone. Due to the unloading relaxation effect, the deformation modulus and shear strength parameters of the rock mass in the unloaded zone are lower than those of the corresponding fresh rock mass. The above parameters are derived from the geological survey and test report of the target project and are directly used as input parameters for the numerical analysis model.

[0072] Feature measuring points A, B, and C were set up at different elevations (1082m, 949m, and 771m) on the slope to collect displacement and stress monitoring data. Based on the spatial location information of each measuring point within a unified spatial reference frame, the monitoring data were assigned to the discrete elements corresponding to the spatial location information in the numerical analysis model.

[0073] Using a Canon 60D camera with an 8mm fisheye lens, multiple collection points were selected around the slope, and six multi-angle panoramic images were taken at 60° intervals. These images were then stitched together using Photoshop and Dreamweaver software to generate a panoramic real-world model.

[0074] Step Two: Energy Tracking and Mutation Determination The soil and rock strength parameters of the numerical analysis model are reduced step by step. Reduction factor. Starting from 1.0, the value is increased incrementally in increments of 0.01. Automatic reduction and energy tracking are implemented using Fish programming language. After each reduction level, the kinetic and gravitational potential energy values ​​of characteristic unit cells A, B, and C are recorded.

[0075] like Figure 3 As shown, the kinetic energy-reduction coefficient relationship curve of characteristic unit A is as follows: From version 1.0 to 2.11, the growth in momentum was slow, remaining at a certain level. Magnitude; From stage 2.11 to 2.12, the kinetic energy from Leap to The growth rate was 9.6 times, exceeding the preset kinetic energy growth rate threshold (3 times). Meanwhile, the gravitational potential energy-reduction coefficient relationship curve shows that from F = 2.11 to 2.12, the gravitational potential energy decreased from... Down to The decrease exceeded the preset threshold for the decrease in gravitational potential energy. Characteristic unit B exhibits the same pattern, with kinetic energy decreasing from... Leap to .

[0076] Because in A sudden energy change (a sharp increase in kinetic energy and a sharp decrease in gravitational potential energy) occurred between 2.12 and 2.11, the reduction value corresponding to this change, was taken as the stability criterion value for the high slope.

[0077] Step 3: Instability Identification and Potential Slip Zone Determination Stability criterion value The value is compared with a preset safety threshold. The preset safety threshold is determined with reference to the provisions regarding the slope stability safety factor in the national standard "Technical Specification for Building Slope Engineering" (GB 50330-2013). Depending on the slope engineering grade and working conditions (e.g., a Class I slope under its own weight), the standard value of the safety factor is typically taken as 1.25 to 1.35. In this embodiment, the preset safety threshold is 1.30. This indicates that the slope is stable under natural conditions. To demonstrate the characteristics of the critical instability state, the slope is further reduced to... .

[0078] extract (Natural stable state) and Mechanical response data under two states (critical instability state), including the yield state identifier and shear strain value of each discrete element. The yield state identifier is determined according to the Mohr-Coulomb yield function: when the maximum principal stress of the discrete element... and minimum principal stress satisfy When the yielding state of the discrete unit is reached, it is marked as yielded.

[0079] Based on the mechanical response data, all discrete elements that have yielded are marked as yielded elements. For example... Figure 4 As shown, At that time, there is only a very small plastic zone at the junction of the slope angle and the ground, and the total yield volume is very small; At that time, large plastic zones appeared in the upper and middle parts of the slope, and the shear failure volume increased sharply. Spatial location information of each yield element was obtained within a unified spatial reference frame, and spatial adjacency analysis was used to determine whether spatial adjacency relationships existed between the yield elements. If such relationships existed, the yield elements with spatial adjacency relationships were marked as the same connected region. When yield elements within any connected region continuously extend from the slope crest boundary to the slope toe boundary in the numerical analysis model, the connected region is determined to be a continuous zone.

[0080] In this embodiment, The yielding element forms a continuous zone from the slope crest boundary to the slope toe boundary, and the shear strain value of each yielding element within the continuous zone exceeds the preset shear strain threshold. (At the scale of) satisfying the instability conditions, the spatial region where the continuous through-strip is located is identified as a potential slip zone, and its spatial location information is obtained.

[0081] Step 4: Panoramic Overlay and Early Warning Display Following a unified spatial reference framework, the spatial location information of potential slip zones is spatially overlaid with the corresponding spatial location in the panoramic real-scene model to generate a warning panorama with risk indicators, which is then interactively displayed via mobile terminals.

[0082] First, a spatial coordinate mapping relationship is established between the numerical analysis model and the panoramic real-scene model based on a unified spatial reference frame. This spatial coordinate mapping relationship is used to convert the spatial location information of the numerical analysis model into scene coordinates in the panoramic real-scene model. In this embodiment, the calibration point registration method is used to establish this mapping relationship: several control points with known spatial locations are selected on the target high slope, and the coordinates of each control point are marked in both the numerical analysis model and the panoramic real-scene model. The mapping relationship is then established through a coordinate transformation matrix.

[0083] Based on the spatial coordinate mapping relationship, the spatial location information of the potential slip zone is mapped to the scene coordinate system of the panoramic real-scene model to obtain the corresponding scene coordinate region. A risk marker is then generated on the scene coordinate region in a display manner distinct from the background. In this embodiment, the risk marker is displayed as a superimposed red semi-transparent block, supplemented by a boundary frame.

[0084] Then, risk information about the potential slip zone is obtained, including at least a stability criterion value and the spatial location information of the potential slip zone. The risk level of the potential slip zone is determined based on the risk information. In this embodiment, since... The slope is in a stable state and no warning is triggered. If the F value is lower than the preset safety threshold, the risk level is determined based on the difference between the stability criterion value and the preset safety threshold: when the difference is less than the preset low-risk threshold, it is classified as low-risk and marked with a yellow boundary frame; when the difference is between the preset low-risk threshold and the preset high-risk threshold, it is classified as medium-risk and marked with an orange semi-transparent block; when the difference is greater than the preset high-risk threshold, it is classified as high-risk and marked with a bright red flashing indicator. The preset low-risk threshold and the preset high-risk threshold are preset according to the engineering safety level requirements.

[0085] Based on risk levels, risk indicators are layered and overlaid on the panoramic real-world model according to their corresponding display styles to generate a warning panorama. The risk indicators are dynamically updated as the stability criterion value changes.

[0086] The panoramic view of the warning, marked with risk indicators, is encoded into an interactive electronic link, which is then converted into a QR code. On-site management personnel can scan the QR code with a mobile device to access the electronic link, displaying the panoramic view on their mobile screen. Users can also rotate, zoom, and click to view risk information. In this way, on-site personnel can intuitively locate the spatial distribution of risk areas within the panoramic view without needing to consult coordinate data or numerical cloud maps, quickly grasping the overall stability of the slope and the engineering location of potential landslide zones.

[0087] One or more embodiments in this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of this application. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of one or more embodiments in this application should be included within the protection scope of this application.

[0088] If flowcharts are used in this application, they are used to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these flows, or one or more steps can be removed from these flows.

[0089] The above provides a detailed description of the method and system for monitoring and providing panoramic early warning of energy mutations in high slope stability provided in this application. The above description of the disclosed embodiments enables those skilled in the art to implement or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for monitoring and providing panoramic early warning of energy mutations in the stability of high slopes, characterized in that, include: Establish a unified spatial reference framework for the target high slope; Based on the unified spatial reference framework, a numerical analysis model and a panoramic real-scene model of the target high slope are constructed respectively. The numerical analysis model consists of multiple discrete units, each of which has unique spatial location information. The monitoring data of the target high slope is associated with the corresponding discrete unit in the numerical analysis model. The soil and rock strength parameters of the numerical analysis model are reduced step by step, and the energy response parameter values ​​of multiple characteristic discrete units in the numerical analysis model are tracked after each reduction. When the rate of change of the energy response parameter value of at least one of the characteristic discrete units exceeds a preset rate of change threshold after any level of reduction, the reduction value corresponding to the level of reduction that has changed will be used as the stability criterion value of the high slope. When the stability criterion value is lower than a preset safety threshold, the mechanical response data output by the numerical analysis model after the change at that level is extracted. The mechanical response data includes at least the yield state identifier of each discrete element and the shear strain value of each discrete element. Based on the mechanical response data, all discrete elements whose yield state identifier is yielded are marked as yielding elements. If each yielding element forms a continuous through zone in space, and the shear strain value of each yielding element in the continuous through zone exceeds the preset shear strain threshold, then the spatial region where the continuous through zone is located is identified as a potential slip zone, and the spatial location information of the potential slip zone is obtained. According to the unified spatial reference framework, the spatial location information of the potential slip zone is spatially superimposed with the corresponding spatial location in the panoramic real-scene model to generate a warning panorama with risk indicators, and the warning panorama is interactively displayed through a mobile terminal.

2. The method for monitoring and panoramic early warning of energy mutation in high slope stability according to claim 1, characterized in that, The monitoring data for the target high slope includes displacement monitoring data and stress monitoring data; The step of associating the monitoring data of the target high slope with the corresponding discrete unit in the numerical analysis model specifically involves: Based on the spatial location information of the monitoring data of the target high slope under the unified spatial reference frame, the displacement monitoring data and the stress monitoring data are assigned to the discrete units corresponding to the spatial location information in the numerical analysis model.

3. The method for monitoring and panoramic early warning of energy mutation in high slope stability according to claim 1, characterized in that, The energy response parameters include kinetic energy and gravitational potential energy; The tracking of energy response parameter values ​​of multiple characteristic discrete units in the numerical analysis model specifically involves: After each reduction stage, the kinetic energy value and gravitational potential energy value of each of the characteristic discrete units are recorded to form the kinetic energy value sequence and gravitational potential energy value sequence of each of the characteristic discrete units under the reduction sequence.

4. The method for monitoring and panoramic early warning of energy mutation in high slope stability according to claim 3, characterized in that, The rate of change of the energy response parameter value exceeds a preset rate of change threshold, specifically: In the kinetic energy value sequence of the same feature discrete unit, the growth factor of the kinetic energy value between two adjacent reduction levels exceeds a preset kinetic energy growth factor threshold, and in the gravitational potential energy value sequence of the same feature discrete unit, the decrease in the gravitational potential energy value between two adjacent reduction levels exceeds a preset gravitational potential energy decrease threshold.

5. The method for monitoring and panoramic early warning of energy mutation in high slope stability according to claim 1, characterized in that, The soil and rock strength parameters include cohesion and internal friction angle; The stepwise reduction of the soil and rock strength parameters of the numerical analysis model is specifically as follows: The cohesive force is reduced stepwise according to the following formula: ； The internal friction angle is reduced step by step according to the following formula: ； in, For cohesion, It is the internal friction angle. This is the current reduction value. To reduce the cohesive force, This is the reduced internal friction angle.

6. The method for monitoring and panoramic early warning of energy mutation in high slope stability according to claim 5, characterized in that, The yield state indicator is determined according to the Mohr-Coulomb yield function: When the maximum principal stress of the discrete element and minimum principal stress The discrete element is identified as yielded when the following equation is satisfied: ； in, The yield function value, For the maximum principal stress, It is the minimum principal stress.

7. The method for monitoring and panoramic early warning of energy mutation in high slope stability according to claim 1, characterized in that, If each of the yielding units forms a continuous through-band in spatial position, specifically: Obtain the spatial position information of each yielding element within the unified spatial reference frame; A spatial adjacency analysis method is used to determine whether there is a spatial adjacency relationship between the yielding elements based on their spatial location information. If they exist, then each of the yielding units that have a spatial adjacency relationship is marked as the same connected region; When the yielding unit in any of the connected regions extends continuously from the top boundary of the slope to the bottom boundary of the slope in the numerical analysis model, the connected region is determined to be a continuous through zone.

8. The method for monitoring and panoramic early warning of energy mutation in high slope stability according to claim 1, characterized in that, The step of spatially overlaying the spatial location information of the potential slip zone with the corresponding spatial location in the panoramic real-world model specifically involves: Based on the unified spatial reference framework, a spatial coordinate mapping relationship is established between the numerical analysis model and the panoramic real-scene model. The spatial coordinate mapping relationship is used to convert the spatial position information of the numerical analysis model into the scene coordinates of the panoramic real-scene model. Based on the spatial coordinate mapping relationship, the spatial location information of the potential slip zone is mapped to the scene coordinate system of the panoramic real scene model to obtain the corresponding scene coordinate region; A risk marker is generated on the scene coordinate area in a display manner that is distinct from the background.

9. The method for monitoring and panoramic early warning of energy mutation in high slope stability according to claim 8, characterized in that, The generation of the early warning panorama with risk indicators specifically includes: Obtain risk information of the potential slip zone, wherein the risk information includes at least the stability criterion value and the spatial location information of the potential slip zone; The risk level of the potential slip zone is determined based on the risk information. According to the risk level, the risk markers are layered and superimposed on the panoramic real-scene model according to the corresponding display style to generate the early warning panorama; The risk indicator is dynamically updated as the stability criterion value changes.

10. A high slope stability energy mutation monitoring and panoramic early warning system, characterized in that, include: The Unified Spatial Reference Frame module is used to establish a unified spatial reference frame for the target high slope. The model building module is used to build a numerical analysis model and a panoramic real-scene model of the target high slope based on the unified spatial reference frame. The numerical analysis model is composed of multiple discrete units, and each discrete unit has unique spatial location information. The data association module is used to associate the monitoring data of the target high slope with the corresponding discrete unit in the numerical analysis model; The energy tracking and mutation determination module is used to progressively reduce the geotechnical strength parameters of the numerical analysis model and track the energy response parameter values ​​of multiple characteristic discrete units in the numerical analysis model after each reduction. When the rate of change of the energy response parameter value of at least one of the characteristic discrete units exceeds a preset rate of change threshold after any level of reduction, the reduction value corresponding to the level of reduction that has changed will be used as the stability criterion value of the high slope. The instability identification module is used to extract the mechanical response data output by the numerical analysis model after the change in the corresponding level when the stability criterion value is lower than a preset safety threshold. The mechanical response data includes at least the yield state identifier of each discrete element and the shear strain value of each discrete element. Based on the mechanical response data, all discrete elements with yield state identifiers indicating yielding are marked as yielding elements. If each yielding element forms a continuous through-zone in spatial location, and the shear strain value of each yielding element within the continuous through-zone exceeds a preset shear strain threshold, then the spatial region where the continuous through-zone is located is identified as a potential slip zone, and the spatial location information of the potential slip zone is obtained. The panoramic early warning display module is used to spatially overlay the spatial location information of the potential slip zone with the corresponding spatial location in the panoramic real-scene model according to the unified spatial reference framework, generate an early warning panorama with risk indicators, and display the early warning panorama interactively through a mobile terminal.

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