Landslide monitoring and early warning method and system based on digital twinborn technology

Abstract

The invention discloses a landslide monitoring and early warning method and system based on a digital twinborn technology, and belongs to the technical field of geological disaster monitoring and early warning, and the method specifically comprises the steps: collecting the geographic information data of a landslide in real time; constructing a dynamically updated multi-source spatial database; the method comprises the following steps: constructing a landslide simulation model, performing mesh generation on the landslide simulation model, introducing a stress field and seepage field numerical coupling algorithm on the basis of a numerical analysis method, establishing a landslide mass hydraulic coupling model, performing solution on the basis of the landslide mass hydraulic coupling model, and accurately analyzing the existing state of the landslide mass. Acquiring the safety coefficient of the landslide mass in real time by adopting a strength reduction method; and establishing a disaster analysis model, if the safety coefficient reaches a preset alarm threshold, deducing a landslide disaster forming range, calculating a disaster risk index, evaluating a risk level according to the disaster risk index, and if the risk level is higher than a preset level, carrying out early warning on the landslide disaster. According to the invention, accurate landslide monitoring and intelligent safety early warning are realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of geological disaster monitoring and early warning, and specifically relates to a landslide monitoring and early warning method and system based on digital twin technology. Background Art

[0002] Landslide is a geological disaster, which is often caused by the combined effects of multiple factors such as geology, meteorology and hydrology. Traditional landslide monitoring and early warning systems usually rely on limited sensor data and local monitoring methods, and have problems such as low monitoring accuracy, untimely data processing and poor real-time performance.

[0003] In recent years, intelligent monitoring technology has developed rapidly and can obtain more detailed geographic information data in a variety of ways. However, the existing landslide monitoring and early warning methods and systems have not correspondingly improved the integration and analysis capabilities of geographic information data. There is still much room for improvement in the accuracy, intelligence and overall effectiveness of landslide monitoring and early warning. Summary of the invention

[0004] In view of the shortcomings of the existing technology, the present invention proposes a landslide monitoring and early warning method based on digital twin technology, which integrates digital twin technology and intelligent monitoring technology to improve the integration and analysis capabilities of geographic information data. Through digital twin technology, the landslide body is simulated and analyzed, the safety status of the landslide body is judged in real time and potential disasters are predicted, thereby realizing accurate monitoring of landslides and intelligent safety early warning.

[0005] Another object of the present invention is to provide a landslide monitoring and early warning system based on digital twin technology, which has the ability to obtain detailed surface information, high sensitivity and multi-parameter monitoring capabilities, and simulation and analysis capabilities that highly restore geological structures, hydrological characteristics and other factors, thereby improving the real-time, reliability and intelligence of landslide monitoring and early warning.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A landslide monitoring and early warning method based on digital twin technology, comprising:

[0008] Collect geographic information data of landslides in real time;

[0009] Standardizing the geographic information data of the landslide to construct a dynamically updated multi-source spatial database;

[0010] Building a landslide simulation model based on the multi-source spatial database, meshing the landslide simulation model, building a hydraulic coupling model of the landslide body based on a numerical analysis method and introducing a numerical coupling algorithm of a stress field and a seepage field, solving the hydraulic coupling model of the landslide body as a basis, accurately analyzing the existing state of the landslide body, and using a strength reduction method to obtain a safety factor of the landslide body in real time;

[0011] A disaster analysis model is established. If the safety factor reaches the preset warning threshold, the scope of the landslide disaster is deduced, the disaster risk index is calculated, and the risk level is evaluated based on the disaster risk index. If the risk level is higher than the preset level, an early warning of the landslide disaster is issued.

[0012] Specifically, the geographic information data of the landslide include: orthophotos and surface digital elevation data, stratigraphic distribution data, soil internal data including temperature, strain, moisture content and pore water pressure, soil displacement data, groundwater level change data, surface displacement data and site rainfall data.

[0013] Specifically, based on the numerical analysis method and introducing the numerical coupling algorithm of stress field and seepage field, the mathematical model of stress field affecting seepage field is:

[0014]

[0015] H(x,y,z)=H1(x,y,z),(x,y,z)∈Π3,

[0016] Where H represents the head distribution, represents the permeability coefficient, Ω1 represents the seepage calculation area, Π1 represents the known flow boundary, Π2 represents the known free boundary, Π3 represents the known head boundary, n2 represents the normal direction of the known free boundary, n3 represents the normal direction of the known head boundary, represents the partial derivative function, (x, y, z) represents the spatial coordinates, q(x, y, z) represents the flow at the coordinates (x, y, z), H(x, y, z) represents the head distribution at the coordinates (x, y, z), H1(x, y, z) represents the given head distribution at the coordinates (x, y, z), i, j, k are used to represent different directions in space, corresponding to the x, y, z directions of the three-dimensional spatial coordinates, and are used to distinguish components and operations in different directions in tensor operations and partial differential equations.

[0017] Specifically, based on the numerical analysis method and introducing the numerical coupling algorithm of stress field and seepage field, the mathematical model of the seepage field affecting the stress field is:

[0018] σ ijk,j +f i =0,(x,y,z)∈Ω2,

[0019]

[0020] Among them, f i represents the penetration volume force, σ ijk,j , σ ijk represents the stress tensor, u ijk 、u jki and u kij represents the displacement field, ε ijk represents the strain tensor, Ω2 represents the stress field area, ε v represents the volume strain, λ represents the elastic constant of the soil, It represents the shear modulus of soil, reflecting the ability of soil to resist shear deformation. ijk (H) represents the known body force distribution, It represents the average volume force distribution, reflecting the overall average level of volume stress in the landslide area. σ represents the known body force boundary, n j represents the cosine of the direction of the normal line of the known body force boundary, S u represents the known displacement boundary, u i represents the known displacement distribution on the known displacement boundary, It represents the average displacement distribution on the displacement boundary, reflecting the overall displacement trend of the structure or object where the displacement boundary is located at the boundary.

[0021] Specifically, the use of the strength reduction method to obtain the safety factor of the landslide body in real time includes:

[0022] Define the safety factor, the specific formula is:

[0023]

[0024] Wherein, c' represents the reduced cohesion, F' represents the reduction coefficient, φ' represents the reduced internal friction angle, φ represents the internal friction angle, arctan() represents the inverse trigonometric function, and tan() represents the tangent function;

[0025] Adjust cohesion and internal friction angle to conduct stability analysis on landslide;

[0026] Increase the reduction factor and continue the calculation until the landslide reaches the limit equilibrium state. The reduction factor at this time is the safety factor.

[0027] Specifically, the calculation of the disaster risk index includes: the disaster risk index includes an economic loss index, a regional correlation expansion index and an additional disaster risk index;

[0028] The economic loss index is used to reflect the economic losses of building changes after disaster deduction. The specific formula is:

[0029]

[0030] Where ELI stands for Economic Loss Index, A stands for the number of loss types, and W a represents the weight of the a-th loss type, L a Indicates the loss degree of the a-th loss type, C a represents the economic cost of the ath loss type, T a represents the time value adjustment factor for the ath type of loss, TV represents the total area value, total output value or total building value;

[0031] The regional correlation expansion index is used to reflect the expansion loss impact caused by the correlation impact during the deduction process. The specific formula is:

[0032]

[0033] Where RCEI represents the regional correlation expansion index, B represents the number of parameters, and W b represents the weight of the i-th parameter, P b Indicates the value of the i-th parameter, including diffusion area, landslide volume, kinetic energy, maximum speed, duration, etc. b represents the impact factor associated with the i-th parameter, reflecting its extended impact on different aspects;

[0034] The additional disaster risk index is used to reflect the subsequent exclusive disaster risk caused by disaster simulation. The specific formula is:

[0035]

[0036] Among them, AHEI represents the additional disaster risk index, E represents the number of additional disaster types, and Fz e represents the occurrence frequency of the e-th additional disaster, Rz e represents the impact range of the e-th additional disaster, Sz e Indicates the severity of the e-th additional disaster.

[0037] Specifically, the construction of the landslide simulation model based on the multi-source spatial database includes: performing three-dimensional surround modeling of the landslide, retaining the physical characteristics of the topography, geological structure and soil properties of the target simulation area, and retaining the hydrological characteristics of the groundwater, pore water pressure and moisture content in the target simulation area.

[0038] Specifically, the construction of a dynamically updated multi-source spatial database includes: using ArcGIS software to perform spatial modeling, simulate different geological scenarios, and visualize the real-time monitoring data.

[0039] A landslide monitoring and early warning system based on digital twin technology, used to implement a landslide monitoring and early warning method based on digital twin technology, comprising:

[0040] An information collection unit, used to collect geographic information data of landslides in real time;

[0041] A digital information unit, used to standardize the geographic information data and construct a dynamically updated multi-source spatial database;

[0042] A digital twin unit is used to construct a landslide simulation model based on the multi-source spatial database, mesh the landslide simulation model, establish a hydraulic coupling model of the landslide body based on a numerical analysis method and by introducing a numerical coupling algorithm of a stress field and a seepage field, solve the hydraulic coupling model of the landslide body based on the hydraulic coupling model of the landslide body, accurately analyze the existing state of the landslide body, and obtain the safety factor of the landslide body in real time by using a strength reduction method; and to establish a disaster analysis model, and if the safety factor reaches a preset alarm threshold, deduce the scope of the landslide disaster;

[0043] The safety warning unit is used to calculate the disaster risk index, evaluate the risk level with the disaster risk index, and issue a warning for landslide disaster if the risk level is higher than a preset level.

[0044] Specifically, the information collection unit includes:

[0045] The drone module is used to perform three-dimensional oblique photogrammetry operations to obtain orthophotos and surface digital elevation data;

[0046] The drilling sampling module is used to drill at geological disaster risk points and typical slopes to obtain stratum distribution data.

[0047] Seismic array module, used to obtain the detailed distribution of the sediment thickness and site amplification effect of the landslide using the horizontal and vertical spectrum ratio method;

[0048] The optical fiber sensing module is used to collect the temperature, strain, moisture content and pore water pressure inside the landslide soil through the ultra-weak reflection optical fiber grating sensing method;

[0049] Fixed inclinometer module for collecting soil displacement data;

[0050] Digital water level meter module, used to collect groundwater level change data;

[0051] Beidou remote displacement measurement module, used to collect surface displacement data;

[0052] Rain gauge module, used to collect rainfall data in the field.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] 1. The present invention proposes a landslide monitoring and early warning method and system based on digital twin technology, which realizes the comprehensive collection of multi-source geographic information, more accurately grasps the data of each landslide area, obtains more comprehensive and accurate monitoring data, and improves the integration and analysis capabilities of multi-source geographic information data. Through the digital twin technology, the landslide body is simulated and analyzed, the current safety status of the landslide body is accurately judged, and simulation analysis of potential disasters and disaster damage ranges is performed to realize accurate monitoring of landslides and intelligent safety early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A flow chart of a landslide monitoring and early warning method based on digital twin technology provided by the present invention;

[0056] Figure 2 A flowchart of constructing a dynamically updated multi-source spatial database provided by the present invention;

[0057] Figure 3 A flow chart of constructing a landslide simulation model based on a multi-source spatial database provided by the present invention;

[0058] Figure 4 A flow chart for early warning of landslide disasters provided by the present invention;

[0059] Figure 5 A structural diagram of a landslide monitoring and early warning system based on digital twin technology provided by the present invention;

[0060] Figure 6 A schematic diagram of a hydraulic coupling model of a landslide provided by the present invention;

[0061] Figure 7 A schematic diagram of a disaster analysis model provided by the present invention;

[0062] Figure 8 This is a structural schematic diagram of the information acquisition unit provided by the present invention. DETAILED DESCRIPTION

[0063] The present application is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present application, but do not limit the present application in any form. It should be noted that, for those of ordinary skill in the art, several variations and improvements can also be made without departing from the concept of the present application. These all belong to the protection scope of the present application.

[0064] In the present invention, unless otherwise specified, all parts and percentages are weight units, and the equipment and raw materials used can be purchased from the market or are commonly used in the art. The methods in the following embodiments, unless otherwise specified, are conventional methods in the art. The components or equipment in the following embodiments, unless otherwise specified, are universal standard parts or components known to those skilled in the art, and their structures and principles are known to those skilled in the art through technical manuals or conventional experimental methods.

[0065] The embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present invention. However, one or more embodiments may also be implemented by those skilled in the art without these specific details.

[0066] Example 1

[0067] See also Figure 1-Figure 4 , an embodiment of the present invention provides a method, comprising the following specific steps:

[0068] Step S1: real-time collection of geographic information data of landslide;

[0069] The collection of geographic information data of landslides specifically includes:

[0070] Use drones with real-time dynamic differential positioning (RTK) measurement systems to perform three-dimensional oblique photogrammetry to obtain orthophotos and surface digital elevation (DEM) data;

[0071] By drilling at important geological hazard risk points and typical slopes, stratigraphic distribution data are obtained, and the horizontal and vertical spectrum ratio method is used to obtain the detailed distribution of the sedimentary layer thickness and site amplification effect of the landslide;

[0072] The temperature, strain, moisture content and pore water pressure inside the landslide soil are collected by ultra-weak reflection fiber Bragg grating sensing method;

[0073] Collect soil displacement data, groundwater level change data, surface displacement data and site rainfall data.

[0074] In this embodiment, a topographic map of a slope with an area of ​​2.2 km2 was collected. The DJI Mavic 3 Industrial Edition of the DJI UAV was used with RTK technology to perform two 3D laser scans to obtain orthophotos and surface DEM data.

[0075] Drilling and sampling were carried out on three typical landslides in the site, and a total of 20 boreholes were constructed to obtain stratum distribution data. At the same time, in order to obtain the physical and hydrological information of each soil layer, 135 samples were taken, including 102 original soil samples and 133 rock samples. A total of 1,415 geotechnical tests were completed, mainly including natural density, gravity, natural water content, specific gravity, liquid limit, plastic limit, compression and strength (shear) indicators, permeability coefficient, free expansion rate, etc.

[0076] In order to obtain the distribution of the thickness of the sedimentary layer of the landslide body, a dense seismic array consisting of 8 northwest-southeast seismic survey lines was planned within the landslide body according to the detection work objectives. The survey line spacing is 75 meters, and each survey line has 12 observation points, with a spacing of 75 meters between observation points, which basically covers the landslide body. In order to obtain a more detailed internal structure of the landslide body, a dense survey line with a point spacing of 25 meters was also designed within the dense array. A total of 132 observation points were planned for the 9 survey lines.

[0077] In order to monitor the strain, pore water pressure and moisture content inside the soil, two boreholes were selected along the main sliding direction of the landslide, at the bottom and middle of the landslide, respectively, and a total of four deep boreholes were laid to install optical fiber sensing cables. Two of the boreholes were laid with ultra-weak reflection fiber Bragg grating sensing cables, and the other two were laid with distributed sensing cables for parallel monitoring. A strain sensing cable and a moisture sensing cable were laid in the sensing cables. A 16-channel NZS-DDS-A01 cabinet-type dense distributed optical fiber demodulator was used, equipped with an automated heating module, a control module and a wireless transmission module to form a new optical fiber neural perception system based on UWFBG technology.

[0078] In order to monitor soil displacement and groundwater level, 8 surface displacement monitoring points, 6 deep displacement monitoring points, 4 groundwater level monitoring points and 3 pore water pressure monitoring points were arranged to monitor the changes of relevant displacement and water level data in the field in real time. In addition, Beidou displacement monitoring points were used to record surface displacement, and rain gauges were used to record rainfall in the field.

[0079] The above multi-source geographic information data is finally transmitted to the collection box through optical fiber. The collection box transmits the relevant signals collected in the field to the GIS digital information storage module, i.e., the digital information unit, installed indoors through the wireless network Zigbee.

[0080] like Figure 2 As shown in the figure, through the GIS digital information storage module, the various geographic information data, including topographic, geological, hydrological, meteorological and other data, are processed, the geographic information data from different sources are standardized, and data cleaning, format conversion and geographic coordinate system unification are performed. After that, data visualization, analysis and spatial modeling are performed, ArcGIS software is used for spatial modeling, different geological scenarios are simulated, and real-time monitoring data is visualized.

[0081] Step S2: standardizing the geographic information data, performing data visualization, analysis and spatial modeling, and constructing a dynamically updated multi-source spatial database;

[0082] ArcGIS software is used for data visualization, analysis and spatial modeling, and multi-source geographic information data are integrated into the GIS digital information storage module based on three-dimensional GIS. Among them, tools such as Model Builder (component of ArcGIS Desktop) and Python scripts are used for spatial modeling to simulate different geological scenarios. Tools such as ArcGIS Dashboards and ArcGIS Online Web App Builder are used to visualize real-time monitoring data and create dashboards, including dynamic maps, charts and indicators, to monitor the status of the landslide area in real time.

[0083] Step S3: constructing a landslide simulation model based on the multi-source spatial database, meshing the landslide simulation model, establishing a hydraulic coupling model of the landslide body based on a numerical analysis method and introducing a numerical coupling algorithm of a stress field and a seepage field, solving the hydraulic coupling model of the landslide body as a basis, accurately analyzing the existing state of the landslide body, and obtaining the safety factor of the landslide body in real time by using a strength reduction method;

[0084] like Figure 3 As shown in the figure, the construction of landslide simulation model based on multi-source spatial database specifically includes: using mechanical simulation software to perform three-dimensional surround modeling of landslide, retaining the physical characteristics of the target deduction area such as topography, geological structure and soil properties, and retaining the hydrological characteristics of the target deduction area such as groundwater, pore water pressure and water content. After that, GID is used for grid division, and based on the numerical analysis method, the numerical coupling algorithm of stress field and seepage field is introduced, and the hydraulic coupling model is established in GDEM. Based on the hydraulic coupling model of the landslide body, the mechanical simulation software GDEM is used to solve it, accurately analyze the current state of the landslide body, and obtain the safety factor of the landslide body in real time based on the strength reduction method.

[0085] Among them, the mathematical model of stress field affecting seepage field is:

[0086]

[0087] H(x,y,z)=H1(x,y,z),(x,y,z)∈Π3,

[0088] Where H represents the head distribution, represents the permeability coefficient, Ω1 represents the seepage calculation area, Π1 represents the known flow boundary, Π2 represents the known free boundary, Π3 represents the known head boundary, n2 represents the normal direction of the known free boundary, n3 represents the normal direction of the known head boundary, represents the partial derivative function, (x, y, z) represents the spatial coordinates, q(x, y, z) represents the flow at the coordinates (x, y, z), H(x, y, z) represents the head distribution at the coordinates (x, y, z), H1(x, y, z) represents the given head distribution at the coordinates (x, y, z), i, j, k are used to represent different directions in space, corresponding to the x, y, z directions of the three-dimensional spatial coordinates, and are used to distinguish components and operations in different directions in tensor operations and partial differential equations.

[0089] In this embodiment, the first formula is a three-dimensional partial differential equation, which indicates that in the seepage calculation area Ω1, the distribution of the water head H satisfies certain continuity conditions, and describes the water head distribution law of the seepage field in the absence of a source or sink; the second formula indicates that on the known flow boundary Π1, the derivative of the water head H along the boundary normal direction n2 is related to the permeability coefficient The product of is equal to the given flow q(x,y,z), which is a flow boundary condition used to determine the flow information on the boundary; the third formula indicates that on the known free boundary Π2, the head H is equal to the z coordinate value, and the derivative of the head H along the boundary normal direction n3 is equal to the permeability coefficient The product of is 0, which is usually used to describe boundary conditions such as free water surface; the fourth formula indicates that on the known head boundary Π3, the head H is equal to the given function H1(x, y, z), which is a head boundary condition that directly gives the head value on the boundary.

[0090] Among them, the mathematical model of the seepage field affecting the stress field is:

[0091] σ ijk,j +f i =0,(x,y,z)∈Ω2,

[0092]

[0093] Among them, f i represents the penetration volume force, σ ijk,j , σ ijk represents the stress tensor, u ijk 、u jki and u kij represents the displacement field, ε ijk represents the strain tensor, Ω2 represents the stress field area, which is the same as the seepage field area, and ε v represents the volume strain, λ represents the elastic constant of the soil, It represents the shear modulus of the landslide soil, reflecting the ability of the soil to resist shear deformation. ijk (H) represents the known body force distribution, It represents the average volume force distribution, reflecting the overall average level of volume stress in the landslide area. σ represents the known body force boundary, n j represents the cosine of the direction of the normal line of the known body force boundary, S u represents the known displacement boundary, u i represents the known displacement distribution on the known displacement boundary, It represents the average displacement distribution on the displacement boundary, reflecting the overall displacement trend of the structure or object where the displacement boundary is located at the boundary.

[0094] Water is the main factor affecting slope stability. The pores inside the landslide rock and soil are channels for water to exist and transmit. When a head difference is generated inside the pores, water will seep and form dynamic water pressure. The dynamic water pressure acts on the rock and soil in the slope, which will cause changes in the stress field, thereby causing changes in the spatial position of the rock and soil. This affects the volume of the pores inside the rock and soil, and the change in the pore volume affects the permeability coefficient. In other words, the seepage field affects the stress field by changing the dynamic water pressure of the rock and soil, and the stress field affects the seepage field by changing the pore characteristics and distribution of the rock and soil. Therefore, since the landslide simulation model constructed in the landslide monitoring and early warning method takes into account the seepage-stress coupling process, compared with traditional slope stability analysis methods (such as graphical methods, limit equilibrium methods, etc.), the analysis dimension is improved, and the influence of hydrological conditions such as groundwater, rainfall and reservoir water level changes on the slope can be integrated, which helps to more accurately evaluate the stability of the landslide rock and soil.

[0095] The strength reduction method is usually used to calculate the safety factor of landslides. It gradually reduces the strength parameters of the landslide material, so that the landslide enters a critical failure state to solve the safety factor. The use of the strength reduction method to obtain the safety factor of the landslide in real time specifically includes:

[0096] The safety factor is defined using the following mathematical expression:

[0097]

[0098] Wherein, c' represents the reduced cohesion, F' represents the reduction coefficient, φ' represents the reduced internal friction angle, φ represents the internal friction angle, arctan() represents the inverse trigonometric function, and tan() represents the tangent function;

[0099] By continuously adjusting the cohesion and internal friction angle, the stability analysis of the landslide is carried out;

[0100] By continuously increasing the reduction factor, calculations are performed until the landslide body reaches a limit equilibrium state. The reduction factor at this time is the safety factor.

[0101] Step S4: Establish a disaster analysis model. If the safety factor reaches the preset warning threshold, deduce the scope of landslide disaster, calculate the disaster risk index, and evaluate the risk level with the disaster risk index. If the risk level is higher than the preset level, issue an early warning for the landslide disaster.

[0102] In this embodiment, if Figure 4 As shown in Figure 2, the early warning process of landslide disasters is as follows:

[0103] Establish a decision support system integrated with GIS and digital twins. The system uses GIS to display the on-site situation of the slope globally, compares and analyzes the collected data, and sets the alarm threshold. When the collected data reaches the threshold, the system applies the digital twin to establish a disaster analysis model based on the hidden danger area, and deduce the scope of the landslide disaster. The deduced results include parameters such as the location of the landslide, the volume of the landslide, the diffusion area, the kinetic energy, the maximum speed, and the duration. There may be surface collapse and slope collapse, mudslides, house damage, etc. After that, the deduced data of the digital twin is counted and the disaster risk index is calculated. Finally, the nearest emergency resources are matched according to the geographical location, and the emergency plan is activated, the emergency tasks are automatically issued, and the disposal plan is formed to release geological warning information to government departments and emergency management departments.

[0104] The calculation of disaster risk index specifically includes:

[0105] The definition of disaster risk index includes economic loss index, regional correlation expansion index and additional disaster risk index. The economic loss index is used to reflect the economic loss of the building changes after the disaster simulation. The regional correlation expansion index is used to reflect the extended loss impact caused by the correlation impact during the simulation process. The additional disaster risk index is used to reflect the subsequent exclusive disaster risk caused by the disaster simulation.

[0106] The economic loss index is calculated using the following mathematical expression:

[0107]

[0108] Where ELI stands for Economic Loss Index, A stands for the number of loss types, and W a represents the weight of the a-th loss type, L a Indicates the loss degree of the a-th loss type, C a represents the economic cost of the ath loss type, T a represents the time value adjustment factor for the ath type of loss, TV represents the total area value, total output value or total building value;

[0109] The regional association expansion index is calculated using the following mathematical expression:

[0110]

[0111] Where RCEI represents the regional correlation expansion index, B represents the number of parameters, and W b represents the weight of the i-th parameter, P b Indicates the value of the i-th parameter, including diffusion area, landslide volume, kinetic energy, maximum speed, duration, etc. b represents the impact factor associated with the i-th parameter, reflecting its extended impact on different aspects;

[0112] The additional disaster risk index is calculated using the following mathematical expression:

[0113]

[0114] Among them, AHEI represents the additional disaster risk index, E represents the number of additional disaster types, and Fz e represents the occurrence frequency of the e-th additional disaster, Rz e represents the impact range of the e-th additional disaster, Sz e Indicates the severity of the e-th additional disaster.

[0115] Step S5: By integrating digital twin technology and intelligent monitoring technology, the ability to integrate and analyze geographic information data is improved. Through digital twin technology, the landslide body is simulated and analyzed, the safety status of the landslide body is judged in real time and potential disasters are predicted, so as to achieve accurate monitoring of landslides and intelligent safety warnings.

[0116] In this embodiment, the landslide monitoring and early warning method of the present invention realizes the comprehensive collection of multi-source geographic information through the combination of traditional monitoring methods and new fiber optic neural perception monitoring methods, and can more accurately grasp the data of each area, making the monitoring data more comprehensive and accurate. The method realizes three-dimensional visualization of traditional data through GIS digital information processing, and globally displays the landslide site situation, while making data interaction more intelligent, and improving the comprehensive understanding of the landslide area situation. Through the digital twin, the method can accurately judge the existing safety status of the landslide body, and conduct simulation analysis of potential disasters and disaster damage ranges. By combining GIS digital information processing methods and digital twins, the landslide disaster is predicted intelligently, and the landslide disaster predicted by the digital twin is converted into a risk index, and decision feedback is made accordingly, which provides protection and scheduling decisions for the prevention of landslide disasters.

[0117] Example 2

[0118] See also Figure 5, another embodiment provided by the present invention: a system, comprising: an information acquisition unit, a digitized information unit, a digital twin unit and a safety warning unit connected in communication by wired and / or wireless means;

[0119] The information collection unit is used to collect geographic information data of landslide in real time, and the information collection unit includes a hydrological information collection module and a physical information collection module;

[0120] The digital information unit is used to standardize geographic information data, perform data visualization, analysis and spatial modeling, and build a dynamically updated multi-source spatial database;

[0121] The digital twin unit is used to build a landslide simulation model based on a multi-source spatial database, mesh the landslide simulation model, and introduce a numerical coupling algorithm of stress field and seepage field based on numerical analysis methods to establish a landslide simulation model. Figure 6 The hydraulic coupling model of the landslide shown in the figure is solved based on the hydraulic coupling model of the landslide, accurately analyzes the existing state of the landslide, and uses the strength reduction method to obtain the safety factor of the landslide in real time; and is used to establish Figure 7 The disaster analysis model shown in the figure can deduce the scope of landslide disaster if the safety factor reaches the preset warning threshold;

[0122] The safety warning unit is used to calculate a disaster risk index, and to assess the risk level with the disaster risk index. If the risk level is higher than a preset level, a landslide disaster warning is issued.

[0123] like Figure 8 As shown, the information collection unit includes a drone module, a drilling sampling module, a seismic array module, a fiber optic sensor module, a fixed inclinometer module, a digital water level meter module, a Beidou remote displacement measurement module and a rain gauge module;

[0124] The drone module is used to perform three-dimensional oblique photogrammetry operations to obtain orthophotos and surface digital elevation data;

[0125] The drilling sampling module is used to drill at important geological disaster risk points and typical slopes to obtain stratum distribution data;

[0126] The seismic array module is used to obtain the detailed distribution of the sediment thickness and site amplification effect of the landslide using the horizontal and vertical spectrum ratio method;

[0127] The optical fiber sensing module is used to collect the temperature, strain, moisture content and pore water pressure inside the landslide soil through the ultra-weak reflection optical fiber Bragg grating sensing method;

[0128] The fixed inclinometer module is used to collect soil displacement data;

[0129] The digital water level meter module is used to collect groundwater level change data;

[0130] Beidou remote displacement measurement module is used to collect surface displacement data;

[0131] The rain gauge module is used to collect rainfall data in the field;

[0132] The information collected by the above modules is summarized in the data collection box.

[0133] The landslide monitoring and early warning system integrates digital information units and digital twin units to collect geological data, plan seismic lines, arrange UWFBG systems, and conduct multi-point monitoring in a multi-dimensional manner. It transmits data in real time, evaluates landslide stability in real time, and provides early warning for potential landslide hazards. It then comprehensively statistically deduces data, calculates disaster risk indexes, automatically activates emergency plans, and issues geological early warning information.

[0134] In addition, the parts of the above-mentioned technical solutions provided in the embodiments of the present application that are consistent with the implementation principles of the corresponding technical solutions in the prior art are not described in detail to avoid excessive redundancy.

[0135] The specific implementation modes as described above further describe the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation mode of the present invention and is not intended to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A landslide monitoring and early warning method based on digital twin technology, characterized in that: include: Collect geographic information data of landslides in real time; Standardizing the geographic information data of the landslide to construct a dynamically updated multi-source spatial database; Building a landslide simulation model based on the multi-source spatial database, meshing the landslide simulation model, building a hydraulic coupling model of the landslide body based on a numerical analysis method and introducing a numerical coupling algorithm of a stress field and a seepage field, solving the hydraulic coupling model of the landslide body as a basis, accurately analyzing the existing state of the landslide body, and using a strength reduction method to obtain a safety factor of the landslide body in real time; A disaster analysis model is established. If the safety factor reaches the preset warning threshold, the scope of the landslide disaster is deduced, the disaster risk index is calculated, and the risk level is evaluated based on the disaster risk index. If the risk level is higher than the preset level, an early warning of the landslide disaster is issued.

2. A landslide monitoring and early warning method based on digital twin technology as claimed in claim 1, characterized in that: The geographic information data of the landslide include: orthophotos and surface digital elevation data, stratum distribution data, soil internal data including temperature, strain, moisture content and pore water pressure, soil displacement data, groundwater level change data, surface displacement data and site rainfall data.

3. The landslide monitoring and early warning method based on digital twin technology according to claim 1 is characterized in that: Based on the numerical analysis method and the introduction of the numerical coupling algorithm of stress field and seepage field, the mathematical model of stress field affecting seepage field is: H(x,y,z)=H1(x,y,z),(x,y,z)∈Π3, Where H represents the head distribution, represents the permeability coefficient, Ω1 represents the seepage calculation area, Π1 represents the known flow boundary, Π2 represents the known free boundary, Π3 represents the known head boundary, n2 represents the normal direction of the known free boundary, n3 represents the normal direction of the known head boundary, represents the partial derivative function, (x, y, z) represents the spatial coordinates, q(x, y, z) represents the flow rate at the coordinates (x, y, z), H(x, y, z) represents the head distribution at the coordinates (x, y, z), H1(x, y, z) represents the given head distribution at the coordinates (x, y, z), and i, j, and k are used to represent different directions in space.

4. The landslide monitoring and early warning method based on digital twin technology according to claim 1 is characterized in that: Based on the numerical analysis method and the introduction of the numerical coupling algorithm of the stress field and the seepage field, the mathematical model of the seepage field affecting the stress field is: σ ijk,j +f i =0,(x,y,z)∈Ω2, Among them, f i represents the penetration volume force, σ ijk,j , σ ijk represents the stress tensor, u ijk 、u jki and u kij represents the displacement field, ε ijk represents the strain tensor, Ω2 represents the stress field area, ε v represents volume strain, λ represents the elastic constant of soil, G εijk represents the shear modulus of the landslide soil, t ijk (H) represents the known volume force distribution, represents the average volume force distribution, S σ represents the known body force boundary, n j represents the cosine of the direction of the normal line of the known body force boundary, S u represents the known displacement boundary, u i represents the known displacement distribution on the known displacement boundary, represents the average displacement distribution on the displacement boundary.

5. The landslide monitoring and early warning method based on digital twin technology according to claim 1, characterized in that: The method of using the strength reduction method to obtain the safety factor of the landslide body in real time includes: Define the safety factor, the specific formula is: Wherein, c' represents the reduced cohesion, F' represents the reduction coefficient, φ' represents the reduced internal friction angle, φ represents the internal friction angle, arctan() represents the inverse trigonometric function, and tan() represents the tangent function; Adjust cohesion and internal friction angle to conduct stability analysis on landslide; Increase the reduction factor and continue the calculation until the landslide reaches the limit equilibrium state. The reduction factor at this time is the safety factor.

6. The landslide monitoring and early warning method based on digital twin technology according to claim 1 is characterized in that: The calculation of the disaster risk index includes: the disaster risk index includes an economic loss index, a regional correlation expansion index and an additional disaster risk index; The economic loss index is used to reflect the economic losses of building changes after disaster deduction. The specific formula is: Where ELI stands for Economic Loss Index, A stands for the number of loss types, and W a represents the weight of the a-th loss type, L a Indicates the loss degree of the a-th loss type, C a represents the economic cost of the ath loss type, T a represents the time value adjustment factor for the ath type of loss, TV represents the total area value, total output value or total building value; The regional correlation expansion index is used to reflect the expansion loss impact caused by the correlation impact during the deduction process. The specific formula is: Where RCEI represents the regional correlation expansion index, B represents the number of parameters, and W b represents the weight of the i-th parameter, P b Indicates the value of the i-th parameter, including diffusion area, landslide volume, kinetic energy, maximum speed, duration, etc. b represents the impact factor associated with the i-th parameter, reflecting its extended impact on different aspects; The additional disaster risk index is used to reflect the subsequent exclusive disaster risk caused by disaster simulation. The specific formula is: Among them, AHEI represents the additional disaster risk index, E represents the number of additional disaster types, and Fz e represents the occurrence frequency of the e-th additional disaster, Rz e represents the impact range of the e-th additional disaster, Sz e Indicates the severity of the e-th additional disaster.

7. The landslide monitoring and early warning method based on digital twin technology according to claim 1, characterized in that: The landslide simulation model is constructed based on a multi-source spatial database, including: performing three-dimensional surround modeling of the landslide, retaining the topography, geological structure and physical characteristics of soil properties in the target deduction area, and retaining the hydrological characteristics of groundwater, pore water pressure and water content in the target deduction area.

8. The landslide monitoring and early warning method based on digital twin technology according to claim 1, characterized in that: The construction of the dynamically updated multi-source spatial database includes: using ArcGIS software to perform spatial modeling, simulating different geological scenarios, and visually displaying real-time monitoring data.

9. A landslide monitoring and early warning system based on digital twin technology, used to implement a landslide monitoring and early warning method based on digital twin technology as claimed in any one of claims 1 to 8, characterized in that: include: An information collection unit, used to collect geographic information data of landslides in real time; A digital information unit, used to standardize the geographic information data and construct a dynamically updated multi-source spatial database; A digital twin unit is used to construct a landslide simulation model based on the multi-source spatial database, mesh the landslide simulation model, establish a hydraulic coupling model of the landslide body based on a numerical analysis method and by introducing a numerical coupling algorithm of a stress field and a seepage field, solve the hydraulic coupling model of the landslide body based on the hydraulic coupling model of the landslide body, accurately analyze the existing state of the landslide body, and obtain the safety factor of the landslide body in real time by using a strength reduction method; It is also used to establish a disaster analysis model. If the safety factor reaches the preset warning threshold, the scope of the landslide disaster can be deduced; The safety warning unit is used to calculate the disaster risk index, evaluate the risk level with the disaster risk index, and issue a warning for landslide disaster if the risk level is higher than a preset level.

10. A landslide monitoring and early warning system based on digital twin technology as claimed in claim 9, characterized in that: The information collection unit comprises: The drone module is used to perform three-dimensional oblique photogrammetry operations to obtain orthophotos and surface digital elevation data; The drilling sampling module is used to drill at geological disaster risk points and typical slopes to obtain stratum distribution data. Seismic array module, used to obtain the detailed distribution of the sediment thickness and site amplification effect of the landslide using the horizontal and vertical spectrum ratio method; The optical fiber sensing module is used to collect the temperature, strain, moisture content and pore water pressure inside the landslide soil through the ultra-weak reflection optical fiber grating sensing method; Fixed inclinometer module for collecting soil displacement data; Digital water level meter module, used to collect groundwater level change data; Beidou remote displacement measurement module, used to collect surface displacement data; Rain gauge module, used to collect rainfall data in the field.

Images