653 results about "Slope stability" patented technology

The invention provides an intelligent ecological restoration system, method and device for a high and steep slope of a strip mine in an arid region. Comprising a data acquisition layer which realizes real-time acquisition of multi-dimensional environmental data through InSAR satellite remote sensing, a ground sensor network and unmanned aerial vehicle multispectral imaging; the transmission layer adopts LoRa and 5G hybrid networking; the platform layer is used for constructing a slope stability prediction and restoration scheme optimization platform based on a digital twinborn model and a deep learning algorithm; and the application layer is used for remotely controlling the repairing device through a mobile terminal and a Web terminal and monitoring the repairing progress in real time. The problems that a traditional restoration technology is poor in adaptability, low in vegetation survival rate, high in ecological restoration cost, insufficient in monitoring technology application, insufficient in monitoring feedback mechanism, insufficient in intelligence, long in ecological restoration period and the like are solved.

The invention discloses a slope geological disaster multi-mode early warning method and system, and relates to the technical field of slope monitoring, and the method comprises the steps: laying a distributed sensor network, and collecting slope multi-source monitoring data; the multi-source monitoring data comprises displacement data, stress data and vibration frequency data; feature extraction is performed on the multi-source monitoring data by using a graph neural network, and the feature extraction comprises capturing spatial correlation among sensor nodes and identifying an abnormal mode, identifying a potential instability area of the slope according to the abnormal mode, and outputting features of the potential instability area; and generating a slope stability risk grade assessment report based on the characteristics of the potential instability region and a disaster evolution graph constructed by combining historical disaster data. According to the invention, the comprehensive monitoring of the slope from the outside to the inside and from the static state to the dynamic state can be realized, the abnormal mode and the potential instability area can be accurately identified, and the accurate assessment and timely early warning of the slope risk can be realized based on the historical data.

The invention belongs to the technical field of road deformation monitoring, and discloses a road slope deformation monitoring system and method, and the system comprises a fixed point monitoring mechanism which monitors the displacement, strain, underground water level and inclination parameters of a slope in real time at key points and key positions of the road slope; the route planning module plans the flight route of the unmanned aerial vehicle; the cruise monitoring mechanism is used for monitoring the side slope in all directions; the weather data acquisition module is used for acquiring local weather data; the three-dimensional laser scanner data analysis module is used for identifying abnormal conditions on the side slope; the image analysis module is used for identifying abnormal conditions on the slope; the comprehensive evaluation module is used for comprehensively evaluating the stability of the slope by utilizing a comprehensive evaluation model; and the alarm module comprises an alarm. According to the invention, the fixed-point monitoring mechanism and the cruise monitoring mechanism are combined to monitor the slope in all directions, the comprehensive evaluation module fuses data of various monitoring means, and the comprehensive evaluation model is utilized to comprehensively evaluate the slope stability.

The invention relates to the technical field of geological disaster prevention and control, in particular to a rock engineering slope stability classification method. According to the technical scheme, the method comprises the following steps: obtaining spatial distribution characteristics of a slope structural plane through combined detection of three-dimensional laser scanning and a geological radar, and establishing a quantitative index system containing occurrence, density and connectivity of the structural plane; the method comprises the following steps: acquiring a fracture signal in a slope in real time by adopting a micro-seismic monitoring system, and extracting a micro-seismic event energy release rate, a dominant frequency offset and a seismic source mechanism parameter through time-frequency analysis; and constructing a geologic structure evolution inversion model, reconstructing a geologic structure evolution process based on the regional geologic database and the field drilling data, and calculating the distribution characteristics of the residual stress field of the structure. According to the method, comprehensive, accurate and real-time monitoring and classified evaluation of the rock engineering slope stability are realized, potential risks can be effectively predicted, a scientific and accurate decision basis is provided for slope support and treatment, and the safety and stability of the rock engineering slope are greatly guaranteed.

The invention provides a road slope stability prediction method and device, a storage medium and electronic equipment, and the method comprises the steps: collecting the multi-dimensional environmental parameters of a road slope in real time, and forming an original parameter set; based on a Granger causal test algorithm, analyzing the original parameter set, determining a causal influence relationship among the parameters, constructing a parameter causal network, and screening out key parameters; calculating the similarity of each key parameter in time and space dimensions through a dynamic time warping algorithm, and generating a space-time incidence matrix; based on the space-time incidence matrix, performing weighted fusion on the key parameters to obtain fusion parameters; inputting the fusion parameters into a pre-trained slope stability prediction model to obtain a predicted value of the slope stability; and when the predicted value exceeds a dynamically updated early warning threshold value, outputting slope instability early warning information. According to the method, the defects of inaccurate prediction and data redundancy of a current road slope stability prediction method are overcome.

The invention relates to the technical field of slope stability data identification, and particularly provides a multi-sensor fusion slope stability intelligent analysis system and an edge calculation method.The system comprises an environment sensing subsystem, a data processing subsystem and an edge calculation subsystem, the environment sensing subsystem monitors the change of the soil moisture content through a soil humidity sensor, and micro movement data of a slope are obtained through a displacement sensor; using a pressure sensor to sense the change of the ground pressure; meanwhile, pre-screening out abnormal data to form a fused data set; the data analysis subsystem is used for converting abnormal data of the fusion data set into a quantitative index of slope stability, and deducing a potential sliding risk of the slope by analyzing the relevance of the soil water content, the tiny movement data or the ground pressure; and the decision support subsystem provides specific reinforcement countermeasures according to the analysis result of the potential sliding risk. According to the method, the potential sliding risk of the side slope is comprehensively deduced by analyzing the relevance of the soil water content, the tiny movement data and the ground pressure.

The invention relates to the field of monitoring and early warning, in particular to a dynamic beam radar monitoring and linkage early warning method and system for a layered side slope of an expressway, and the method comprises the steps: carrying out the layered scanning of a layered geologic structure of the side slope, synchronously obtaining a phase coherent echo signal, carrying out the multi-threshold scattering point extraction, and carrying out the multi-threshold scattering point extraction; through analysis of a prior constraint model and a geological vegetation recognition network, interference signals caused by vehicle passing are eliminated to obtain a space-time coherent scattering point set, the space-time coherent scattering point set is input to a deformation calculation assembly line, differential interference measurement, adaptive atmospheric disturbance correction and slope structure parameter inversion are executed, and a displacement data stream is generated. And carrying out space-time correlation analysis on the layered inclination angle time sequence data and the meteorological and hydrological data, updating a slope stability evaluation index through a dynamic baseline, and generating an early warning instruction. According to the invention, a technical system from interference suppression and precise calculation to decision closed loop is formed, high reliability of road slope monitoring results is ensured, and intelligent support is provided for traffic safety and emergency management and control.

The invention discloses a grouting method and system for enhancing strip mine slope stability, and belongs to the technical field of slope protection. The grouting method comprises the steps that early-stage data are pre-collected, and an analysis model is established; grouting is designed according to a model analysis result; a pressure-resistant grouting pipe is installed and connected with a grouting pump; grouting parameters are adjusted in real time according to feedback of the sensor; after grouting, all data in the grouting holes are analyzed; outputting a slurry permeation three-dimensional cloud picture, a stress change curve and a stability evaluation index; and storing all monitoring data and model parameters. A cyclic self-adaptive system is formed, it is ensured that the grouting process is efficient and accurate, the overall stability is improved for heterogeneous rock mass, dependence on a static geological report is reduced, and therefore the problem that grouting parameters depend on engineering experience or conservative of the static report is avoided.

The invention relates to the technical field of slope engineering, in particular to a settlement deformation prediction method and system for a reinforced soil slope building structure. The method comprises the following steps: acquiring a soil body infiltration line position parameter of a reinforced soil slope, an interface friction coefficient of a reinforced material and a soil body, a soil body grain grading curve and environment temperature and humidity duration information, and obtaining initial characteristic data of a slope system state; constructing a heat-force-water multi-field coupling monitoring network in the soil-reinforced material interface area according to the initial characteristic data of the slope system state, and obtaining the interface shear stress, the interface normal strain, the pore water pressure gradient and the temperature gradient of each monitoring point to obtain interface action characteristic data. According to the method, the environment disturbance probability density model based on the temperature fluctuation and the sudden change of the water content is constructed, the influence of a complex environment on the slope stability can be quantitatively described, and the robustness of the model is improved.

The invention discloses a road slope modeling method based on an unmanned aerial vehicle inspection route, and relates to the technical field of unmanned aerial vehicle inspection. The method comprises the following steps: measuring the road slope length, the landform and the geological complexity, and selecting an adaptive unmanned aerial vehicle type and sensor combination according to the road slope length, the landform and the geological complexity; planning unmanned aerial vehicle surface inspection and shallow geological exploration routes, ensuring space matching, and synchronously obtaining high-resolution images and ground penetrating radar data; and processing image data through a photogrammetry technology, generating a digital elevation model and an orthophoto map, and combining to construct a three-dimensional model of the earth surface. Geophysical inversion is carried out on the ground penetrating radar data, reflection features are extracted and projected to the ground surface three-dimensional model, and space correlation between the ground surface and a shallow layer structure is established; the reflection features are digitalized and geometrically reconstructed into three-dimensional surface elements, the three-dimensional surface elements are embedded into an earth surface model to form a three-dimensional geologic body model, time dimensions are introduced, and a dynamic evolution model is constructed. According to the dynamic evolution model, the dynamic analysis of the slope stability is realized.

The invention relates to the technical field of slope protection, in particular to a slope stability assessment method and system applied to mine ecological restoration, and the method comprises the steps: collecting basic geological data and dynamic monitoring data of a slope in an assessment region based on a set data collection frequency; performing space-time division according to a preset time window and a space grid to obtain a plurality of space-time window units, and calculating to obtain a multi-dimensional stability evaluation index according to the basic geological data and the dynamic monitoring data corresponding to each space-time window unit; based on the multi-dimensional stability evaluation indexes corresponding to different space-time window units, constructing a space-time serialized slope stability characteristic matrix; inputting the dynamic stability data into a preset multi-dimensional stability evaluation model to obtain a dynamic stability index; correcting the dynamic stability index by considering the obtained real-time environmental load interference data to obtain a corrected stability index; and a preset slope stability threshold value is utilized to perform early warning judgment.

The invention relates to the technical field of geotechnical engineering safety monitoring, in particular to a river valley area bedding slope stability monitoring method and related products, and the method comprises the steps: building a three-dimensional geology-mechanics numerical model of a slope; acquiring monitoring data of the slope state in real time; dynamically correcting mechanical parameters in the three-dimensional geology-mechanical numerical model through inversion calculation; evaluating the stability of the slope and outputting early warning information; according to the method, multi-source monitoring data are fused into the numerical model in real time, dynamic inversion and tracking of internal mechanical parameters of the slope are achieved, comprehensive indexes such as the real-time safety coefficient, the main sliding direction deviation angle and the damage evolution rate are calculated, graded early warning is triggered according to the indexes, and the perspectiveness and reliability of early warning are improved.

The invention discloses a high cut slope stability evaluation method based on multi-source data fusion, and particularly relates to the technical field of data analysis. By integrating topographic data, geological exploration data, remote sensing images, monitoring sensor data and geophysical detection data, an inversion algorithm is adopted to automatically extract abnormal structure features such as shear wave velocity sudden change and resistivity valley, the abnormal structure features and geological profiles are subjected to cross validation to generate an underground structure risk map layer, and a fusion model is combined with machine learning and a mechanical algorithm to obtain an underground structure risk map layer. According to the method, slope stability indexes including the safety coefficient and the sliding probability are comprehensively output, intelligent identification and grading of potential sliding dangerous areas are achieved, finally, an evaluation result is visually displayed in a three-dimensional GIS platform in a layer superposition mode, the identification precision and evaluation scientificity of slope hidden risks are remarkably improved, and the method is suitable for popularization and application. And a more reliable decision basis is provided for early warning and disposal of a high-risk slope.

The invention relates to the field of highway engineering safety monitoring, in particular to a highway slope stability image monitoring and risk early warning system which comprises an image acquisition module, a slope parameterization representation module, a multi-scale curvature flow analysis module, a Riemannian manifold learning module and a risk early warning module. Differential features are extracted by calculating a measurement tensor and a curvature tensor of the curved surface; constructing multi-scale representation of the slope curved surface by applying a curvature flow theory, and identifying deformation characteristics under different scales; according to the method, riemannian manifold learning and a geodesic convolutional network are utilized to extract advanced features, geological disaster precursors such as landslide, collapse and debris flow are accurately identified, the system has a self-adaptive monitoring frequency adjustment function, monitoring modes are automatically switched according to risk levels, the slope disaster risk is greatly reduced, and a powerful guarantee is provided for safe operation of roads.

The invention provides a high earth and rockfill dam digital twinborn model construction method, and belongs to the technical field of high earth and rockfill dam health monitoring, and the method comprises the steps: constructing a measuring point monitoring model based on sensor monitoring data; constructing a mapping model, and constructing a mapping model dynamic monitoring loss function for adversarial training by adopting a domain adaptive method; inputting predicted values of deformation monitoring effect quantity and osmotic pressure monitoring quantity of the measuring point monitoring model on the seepage process and the deformation process of the high earth and rockfill dam into the mapping model to obtain a digital twinborn model, and constructing an extreme working condition digital twinborn model based on the digital twinborn model; knowledge graph reasoning is combined with a dam slope stability coefficient to realize interaction of an extreme working condition digital twinning model and a solid model, and the high earth and rockfill dam deformation-seepage digital twinning framework is proposed for the first time on the basis of deep learning and finite element methods so as to realize a more economical, efficient and reliable monitoring scheme. And technical support is provided for health monitoring of the high earth and rockfill dam structure in the future.

The invention discloses a loess slope stability intelligent monitoring method and system, and the method comprises the steps: carrying out the regional differentiation modeling of multi-source data of a target region, and outputting slope change data; according to the period-by-period displacement time sequence data, a slope deformation trend is obtained through prediction based on an LSTM algorithm; and inputting the slope change data, the slope deformation trend and the meteorological rainfall data into a slope stability evaluation model to predict a safety coefficient, and if the safety coefficient is lower than a preset threshold value, issuing early warning information. According to the loess slope stability intelligent monitoring method and system provided by the invention, data such as gradient change and deformation trend are accurately extracted, multi-source data and meteorological rainfall data are fused by means of cross-modal attention, a random forest model is used for learning a multi-factor coupling rule, and finally multi-factor data prediction is integrated to obtain a safety coefficient for early warning. The problem of low early warning reliability caused by difficulty in accurately evaluating the slope stability by fusing multiple factors such as gradient, deformation and meteorological rainfall can be solved.

The invention discloses a side slope stability intelligent monitoring and supporting optimization method based on digital twinning, which comprises the following steps: extracting gradient, curvature and geological layering characteristics from a holographic terrain model, calculating a preliminary change trend of stress distribution of a rock-soil body in combination with a finite element analysis method, and determining spatial position distribution of a potential sliding surface of a side slope; according to the space coordinate set of the real-time monitoring point position, the data acquisition frequency of the sensor is adjusted through a time sequence analysis method, and a high-frequency monitoring data set reflecting dynamic changes of stress and underground water is obtained; extracting stress peak values and underground water level fluctuation characteristics from the high-frequency monitoring data set, and generating a multi-dimensional information matrix containing terrain, stress and water dynamics by combining spatial characteristics of the holographic terrain model and adopting a data fusion algorithm; according to the state parameters of the digital twinborn body, if it is judged that the stress distribution exceeds a preset threshold value, the stress distribution of the supporting structure is recalculated through finite element analysis, and an adjusted slope supporting design scheme is obtained.

The invention relates to the technical field of side slope monitoring, and particularly discloses a side slope monitoring data fusion method and system based on multiple sensors, and the method comprises the steps: collecting various physical parameters of a side slope through a plurality of side slope monitoring sensors, and further constructing an evidence body of each physical parameter; the basic probability distribution of each evidence body to different propositions is determined in combination with statistical analysis and expert experience, then all the evidence bodies are gradually fused by adopting a D-S evidence synthesis rule to obtain multi-sensor fusion representation, and then, based on the multi-sensor fusion representation, according to a maximum credibility decision rule, the probability distribution of each evidence body to different propositions is determined. And the final stability state of the slope is determined, and corresponding early warning measures are taken. In this way, multi-source heterogeneous data can be utilized more comprehensively, the accuracy and comprehensiveness of slope stability evaluation are improved, and a powerful guarantee is provided for engineering safety.

The invention provides a slope displacement monitoring data processing system based on an unmanned aerial vehicle laser radar, and relates to the technical field of data processing, and the system comprises the steps: carrying out the spatial interpolation processing of a topographic feature data set, and constructing a digital topographic surface model; the displacement field calculation module is used for performing iterative optimization based on a digital terrain surface model through spatial similarity analysis and fusion with a gradient descent algorithm, calculating a slope surface displacement vector field, identifying a potential sliding surface and a deformation abnormal region, and generating a displacement field calculation result; and the evaluation module is used for inputting a displacement field calculation result into a risk evaluation model and carrying out slope stability quantitative evaluation through a multi-source data fusion analysis platform. According to the invention, the practicability and operability of the monitoring result are improved.

The invention discloses a near-slope foundation bearing capacity estimation method and system considering slope body stability, and the method comprises the steps: collecting geological data and environmental data of a target region, constructing a target region simulation model, and carrying out the simulation obtaining of the slope body parameter changes of the target region under different environments and load effects; determining a potential sliding surface based on the simulated slope parameter change, a preset sliding surface determination mode and a preset slope stability coefficient calculation method, and calculating a slope stability coefficient of the target area; determining a geological risk level of the target area, and when the geological risk level is greater than a preset risk level, selectively collecting a slope surface image of the target area, and calculating a soil parameter adjustment value; and correcting the foundation bearing capacity formula by using the slope stability coefficient or the slope stability coefficient recalculated according to the soil parameter adjustment value, and outputting an estimated value of the foundation bearing capacity. According to the method, the slope stability can be considered under the complex terrain condition, and the bearing capacity estimated value of the near-slope foundation can be obtained more accurately.

The invention relates to the technical field of rainfall slope evaluation, in particular to a rainfall slope stability evaluation method based on a physical certainty coupling model. The method comprises the following steps: acquiring digital elevation model data, engineering geological survey data and historical rainfall data of a target area; extracting topographic features from the digital elevation model data to obtain basic topographic parameters; the method comprises the following steps: carrying out longitudinal layering division on a rock-soil body based on engineering geological survey data, and carrying out physical and mechanical parameter setting on each layered rock-soil body to obtain a rock-soil body layering parameter set; and performing frequency analysis on the historical rainfall data to obtain an extreme rainfall intensity sequence. According to the method, by fusing the multi-source data and the three-dimensional physical coupling model, dynamic and accurate rainfall induced slope stability evaluation and risk early warning are realized, and the prediction precision is effectively improved.

The invention discloses a muck site landslide total probability risk quantitative evaluation method considering muck three-dimensional space variability, comprising the following steps: carrying out muck site drilling investigation to obtain muck site data; random field parameters representing the spatial variability of the muck are obtained; simulating three-dimensional space variation characteristics of the muck; based on a limit equilibrium method, carrying out three-dimensional slope stability evaluation and potential landslide volume estimation on the muck field; possible migration ranges under various landslide volumes are simulated; counting life and property data of a downstream disaster-bearing body, and estimating the vulnerability of the disaster-bearing body according to the landslide strength based on a building and personnel vulnerability evaluation formula; and establishing a muck site landslide total probability risk assessment formula, and carrying out landslide risk quantitative assessment and risk rating. According to the method, the unique spatial variation characteristic of the muck is considered, the stability and the potential slip position and quantity are analyzed from the three-dimensional perspective, and accurate risk assessment is realized in combination with a vulnerability quantitative assessment method.

The invention belongs to the technical field of civil engineering, and discloses and relates to an open pit coal mine slope multi-physical field action large-scale simulation platform which is used for simulating slope stability tests under various working conditions. Comprising a base, a plurality of box bodies are arranged in the middle of the base from left to right, and a first foundation pit and a second foundation pit are arranged at the bottom of each box body; the base is provided with a box rotating shaft located between the first foundation pit and the second foundation pit. A plurality of lateral overturning oil cylinders are arranged in the first foundation pit; the bottom of the front end of each box body is hinged to the tops of at least two lateral overturning oil cylinders, and the middle of each box body is connected with a rotating shaft fixed to the base. Wherein one box body comprises a forward overturning oil cylinder, a forward overturning base and a forward overturning box body; and the forward overturning oil cylinder is used for driving the forward overturning box body to overturn towards the adjacent box body. The device can realize loading of the open pit coal mine slope under various working conditions, and is reasonable in structure, convenient to operate and high in test precision.

The invention relates to the technical field of rainfall type loess side slope instability early warning methods, and discloses a rainfall type loess side slope instability early warning method and system based on multi-source data fusion, and the method comprises the steps: S1, arranging a sensor network on a side slope, and collecting rainfall capacity, surface displacement and soil pressure data in real time; s2, preprocessing the collected multi-source data, including data cleaning, missing value filling and data standardization; and S3, extracting characteristic indexes capable of reflecting the stability state of the slope from the preprocessed data. Environmental data of the loess slope, such as rainfall, evaporation capacity, temperature and humidity, are acquired by using a sensor network; the deformation data comprises earth surface displacement, deep displacement and crack width; the mechanical data comprises soil pressure, pore water pressure and soil moisture content; image data: a slope surface image and a crack development image are collected, an early warning model is constructed based on a machine learning algorithm, and data features can be automatically learned.

The invention provides a GNSS-based mountain area highway loess slope stability evaluation method and system, and relates to the technical field of loess slope stability evaluation.The method comprises the steps that firstly, a slope area is divided into grids, geologic feature data of each grid are obtained, super nodes are divided according to the geologic feature data, and the super nodes are divided into super nodes; monitoring points are determined, and the soil moisture content is monitored, so that the moisture content of the soil at different depths is analyzed; secondly, the original displacement is monitored through a GNSS, displacement correction is carried out based on the Fredld unsaturated soil shear strength theory, and the actual displacement is obtained; the influence of the accumulated rainfall on the soil body strength parameters is analyzed, and the soil body strength parameters are corrected in real time; coupling the corrected soil body strength parameter with the actual displacement, calculating a safety coefficient, and judging an early warning state according to the rainfall sensitivity coefficient; and finally, comprehensively judging the stability of the slope according to the early warning state. According to the method, through multi-parameter comprehensive analysis, the accuracy of slope stability evaluation is improved.

The embodiment of the invention discloses a hydrology-landslide coupling forecast and parameter optimization method, and the method comprises the steps: constructing a coupling model, the coupling model comprises a hydrology model and a landslide model, the hydrology model is used for simulating the spatial and temporal changes of water volume and energy flux in a watershed, and the landslide model is used for representing the stability of a slope; establishing an intelligent forecasting model of the coupling model through a machine learning algorithm; performing parameter optimization on the intelligent forecasting model by using an intelligent substitution model based on Gaussian process regression, and outputting an optimized parameter sample and a target function value thereof; the objective of simultaneously forecasting flood and landslide disasters in a research area can be achieved, and the precision and efficiency of model calculation are improved.

The invention discloses a slope anchor cable support optimization design method based on global sensitivity analysis, and belongs to the technical field of engineering geology. The method comprises the following steps: screening parameters by using a local sensitivity analysis method to determine parameter subsets; secondly, in the anchor cable anchoring force loss calculation model, verifying and calibrating the parallel connection mode of the anchor cable body and the West original rock-soil body rheological model, designing a plurality of sensitivity analysis schemes, and constructing a joint probability density function of uncertainty parameters; and finally, establishing an anchor cable layout and parameter optimization model by taking maximum slope stability reliability as an optimization target and considering constraint conditions such as engineering cost and construction difficulty, and formulating corresponding anchor cable anchoring force compensation measures according to changes of key uncertainty parameters. According to the scheme, the stability risks of the side slope under different working conditions are evaluated more accurately, the engineering cost is effectively reduced and the construction difficulty is reduced on the premise of guaranteeing the stability of the side slope, and the stability of the side slope is jointly improved by designing all links from design to construction.

The invention provides a slope stability double reverse parameter inversion early warning method and system, and relates to the technical field of slope early warning, and the method comprises the steps: obtaining slope multi-source data, and carrying out the preprocessing of the slope multi-source data, and obtaining a slope parameter database; performing side slope potential sliding surface screening and numerical modeling based on the side slope parameter database to obtain a multi-dimensional data set of the side slope potential sliding surface; constructing a double-reverse neural network model based on the multi-dimensional data set of the potential sliding surfaces of the side slope, and obtaining a double-reverse neural network model of multi-sliding-surface risk early warning; and processing slope displacement data monitored in real time based on the double-reverse neural network model for multi-sliding-surface risk early warning to obtain a prediction result of slope stability, and performing real-time early warning based on the prediction result. According to the invention, the efficiency and precision of landslide early warning are improved, and an intelligent solution is provided for slope engineering under complex geological conditions.

The present invention discloses a full - probability risk quantitative assessment method for the landslide of a muck yard considering the three - dimensional spatial variability of muck, which includes the following steps: conducting borehole exploration of the muck yard site to obtain muck yard data; obtaining random field parameters characterizing the spatial variability of muck; simulating the three - dimensional spatial variation characteristics of muck; based on the limit equilibrium method, conducting the three - dimensional slope stability assessment of the muck yard and estimating the potential landslide volume; simulating the possible migration ranges under various landslide volumes; statistically collecting the life and property data of downstream disaster - bearing bodies, and based on the vulnerability assessment formulas for buildings and personnel, estimating the vulnerability of disaster - bearing bodies according to the landslide intensity; establishing a full - probability risk assessment formula for the muck yard landslide, and conducting quantitative risk assessment and risk rating. The present invention considers the unique spatial variation characteristics of muck, analyzes the stability, potential sliding position and volume from a three - dimensional perspective, and combines with the quantitative vulnerability assessment method to achieve accurate risk assessment.