786 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 discloses a guidance planning method for ecological restoration of a side slope, and relates to the technical field of ecological restoration, and the main scheme is as follows: collecting multiple data of the side slope; calculating a slope stability index, and presetting a threshold value to judge whether the slope area is in a risk state; calculating a vegetation coverage area, and further calculating a plant suitability index; calculating a plant variety selection index, and further calculating a planting quantity; calculating the water and soil loss rate after restoration; calculating a plant adaptation comprehensive index; calculating an ecological restoration effect index and a vegetation density, and further obtaining a planting layout rationality index; calculating a soil stability index, further calculating a water and soil loss control index, and judging whether the soil loss control state is abnormal or not according to a preset threshold value; calculating a water and soil conservation effect index, further obtaining a vegetation growth comprehensive index, presetting a threshold value to judge the vegetation growth condition, and taking corresponding remediation measures; the method can effectively guarantee scientificity and effectiveness of ecological restoration of the side slope.

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 an ecological slope protection structure and a construction method thereof.The ecological slope protection structure comprises an ecological vegetation layer formed by splicing a plurality of units, and a vegetation planting groove is formed in each unit; the regulation and control layer comprises a honeycomb-shaped coarse aggregate layer, a corrugated plate laminated middle aggregate layer and a fractal tree-root-shaped fine aggregate layer of which the porosity decreases progressively from top to bottom; the drainage mechanism comprises a drainage channel in the ecological vegetation layer, a porous drainage framework and a water collecting well arranged at the slope bottom; the anchoring mechanism comprises a plurality of umbrella-shaped expansion anchor rods, and the lower end of each anchor rod is perpendicular to the slope surface and is inserted into the slope surface soil layer; the lower end of each anchor rod is provided with four sets of extensible 120-degree arc-shaped anchor flukes, and the surfaces of the anchor flukes are provided with bionic ground gripping grooves consistent with the anti-sliding ribs in trend. By innovatively designing the ecological vegetation layer, the regulation and control layer, the drainage mechanism and the anchoring mechanism, stability of the slope protection structure in mechanical property and sustainable development of the ecological environment are achieved, and coordination and unification of vegetation growth and slope stability are promoted.

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.

A slope safety and stability analysis method based on an integrated sensor and an intelligent algorithm comprises the following steps: acquiring initial values of geometric parameters (including height, gradient and width) of a slope and basic physical parameters (weight, internal friction angle and cohesive force) of a soil body through a method of combining in-situ static sounding and an indoor test; an improved integrated sensor slope state monitoring device is adopted to continuously obtain state parameters such as water content, matrix suction, internal three-way displacement, an inclination angle and soil pressure of a slope soil body, and multi-dimensional dynamic monitoring is achieved; basic physical parameters of a soil body are updated in real time based on data collected by a sensor, and the slope stability safety coefficient is predicted through a semi-supervised learning model; safety early warning is triggered in a grading mode according to prediction results, model prediction values and measured values are recorded and analyzed, and the system evaluates the long-term stability and applicability of the model; through multi-source data fusion and intelligent analysis, theoretical support and technical guarantee are provided for safety monitoring and early warning of the loess slope.

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 side slope monitoring and early warning, in particular to a mine site side slope remote online real-time monitoring and early warning system which comprises a multi-source data monitoring unit, a data processing and analyzing unit, a side slope instability judging unit, an instability grading early warning unit and an early warning verification pushing unit. The method comprises the following steps: collecting monitoring data of a plurality of data sources to obtain time sequence monitoring data of each data source, carrying out noise reduction on the time sequence monitoring data, then decomposing the time sequence monitoring data, calculating a time-frequency feature vector through an energy density function, and optimizing the time-frequency feature vector through feature screening; calculating a slope stability evaluation index by optimizing the time-frequency feature vector, constructing an instability risk index to judge a slope instability risk level, constructing an early warning index, and combining the early warning index with the slope instability risk level to establish a graded early warning mechanism to obtain a slope instability early warning level; and verifying the slope instability early warning grade, and performing early warning according to the slope instability early warning grade passing the verification. According to the invention, the false alarm rate of slope monitoring and early warning can be reduced.

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 relates to a slope structure stability safety monitoring method, which comprises the following steps of: acquiring characteristic data of geological conditions, stress states and potential instability modes of a slope, partitioning the slope according to the characteristic data, and acquiring a plurality of monitoring partitions; according to the weathering degree and structural surface development characteristics of the slope material in the monitoring subarea, obtaining a dominant deformation mode and key influence factors of the monitoring subarea; based on the dominant deformation mode and the key influence factors, obtaining a sensor optimization layout scheme in the monitoring subarea, and obtaining monitoring data of the monitoring subarea; and performing spatialization processing on the monitoring data, obtaining a spatial distribution diagram of the monitoring data, analyzing the spatial distribution diagram, identifying an abnormal region, evaluating the stability of the abnormal region, and obtaining the stable state of the slope. According to the invention, through zone monitoring and machine learning, the accuracy and pertinence of slope stability evaluation are improved, and a scientific basis is provided for making prevention and control measures and emergency plans.

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 slope stability test device and test method, and relates to the technical field of slope test.The slope stability test device comprises a test frame and further comprises a test adjusting device.A shielding frame is slidably installed on the inner wall of the test frame, a displacement sensor is fixedly installed on the front side of the shielding frame, and a slope model is arranged at the bottom of the inner wall of the test frame; a placing plate is fixedly installed on the inner wall of the test frame, the test adjusting device comprises hydraulic equipment, an L-shaped frame, an adjusting rod, a pressing plate, an adjusting gear, a U-shaped rod, a limiting frame and an elastic telescopic rod, and the pressing plate moves to make contact with the slope model and conducts a stability test on the slope model; meanwhile, the displacement sensor works to detect and record the displacement condition of the slope model in real time, external force mistaken touch is prevented through the elastic telescopic rod, it can be ensured that the angle of the pressing plate is kept stable in the test process, and therefore the real stability of the slope model is correctly reflected.

The invention discloses a slope stability evaluation method based on micro-seismic signal double-dominant-frequency mechanism characteristics, and relates to material analysis and application. The method is based on the objective principle that rock acoustic emission dominant frequency characteristics and micro-seismic signal dominant frequency characteristics have consistency and relevance, and the phenomenon of double dominant frequency characteristics existing in acoustic emission tests and micro-seismic monitoring. A rock sample dominant frequency characteristic rule obtained by an acoustic emission test is used for processing micro-seismic signal waveform data obtained by micro-seismic monitoring, so that a dominant frequency characteristic evolution rule of slope rock damage can be obtained through a micro-seismic signal, and the stress condition of the slope rock is more accurately judged based on the dominant frequency characteristic evolution rule; the stability of the slope is evaluated, so that the accuracy of an evaluation result is remarkably improved; the evaluation method combines an acoustic emission test and micro-seismic monitoring, has the advantages of high evaluation accuracy and good universality, and is suitable for large-scale application in monitoring and prevention of geological disasters such as landslide and the like.

The invention relates to the technical field of geological disaster model tests, in particular to a cold region soil engineering collapse monitoring device, system and method.The cold region soil engineering collapse monitoring device comprises an outer box, an inner box and a side slope model, the side slope model is arranged in the inner box, and the outer box is used for containing the inner box; the rainfall assembly is movably mounted on the inner box and is used for controllably and quantitatively spraying water or mist towards the inner box so as to simulate a rainfall or plum rain state; the vibration assembly is arranged at the bottom of the side slope model, the side slope model is adjustably installed on the vibration assembly, and the vibration assembly is used for enabling the side slope model to generate vibration so as to simulate the vibration state; the device further comprises an electromagnetic force loading assembly, and the electromagnetic force loading assembly is arranged on the outer side of the side slope model and used for applying loads in at least one direction to the side slope model. The device is used for simulating the slope stability of the cold region soil engineering under the multi-factor coupling effect.

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 discloses a slope stability prediction method based on deformation monitoring, and relates to the field of slope monitoring, and the method comprises the steps: obtaining a time sequence deformation field of a target slope through employing an InSAR; generating a time sequence Dn through differential interference processing; collecting rainfall data; generating a time sequence representing regional rainfall conditions; grey correlation analysis is adopted, and the correlation degree of Dn and Pn is calculated; constructing a slope slip prediction model based on InSAR displacement and rainfall factors; if the displacement time sequence has an acceleration trend or fluctuation, marking the corresponding slope unit as an early warning analysis object; obtaining rainfall forecast data in a future period of time, and calculating a displacement predicted value di '(N + 1) of the marked side slope unit at the (N + 1) th time point in the future; and comparing the displacement predicted value di '(N + 1) of the (N + 1) th time point with a threshold value, and if di' (N + 1) exceeds the threshold value, giving a slippage early warning level. Aiming at low precision of a rainfall-induced slope slippage early warning model in the prior art, the precision is improved.

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 relates to the technical field of geotechnical engineering, in particular to a bedding side slope stability judgment method and system, and the method comprises the following steps: scanning a target bedding side slope by using an ultrasonic sensor based on the position information of the bedding side slope, recording a three-dimensional geological structure image of the side slope, detecting the positions of cracks and cavities, and generating a bedding side slope structure image. According to the method, an ultrasonic sensor is used for scanning a slope, internal cracks and cavities are recognized, stability problems are found in the early stage, side slope rock and soil characteristics are recognized in combination with physical and chemical attribute measurement, a three-dimensional geologic model is constructed through terrain scanning, and interaction between soil particles and rocks in multiple scenes is simulated; according to the method, the behaviors of the slope under various natural and artificial conditions are analyzed, the instability behavior of the slope is identified, the influence of various factors on the stability of the slope is evaluated, the ability of taking precautionary measures for various risk factors is enhanced, and a decision maker is helped to make accurate maintenance and intervention decisions.

The invention discloses a mine high and steep slope landslide machine learning prediction method based on an unmanned aerial vehicle technology and multi-source data fusion. The method comprises the steps that a high-resolution digital surface model is shot by an unmanned aerial vehicle; removing non-topographic features from the digital surface model data in ArcGIS software, then converting the digital surface model data into digital elevation model data, obtaining a surface refining model of the surface mine in the digital elevation model, taking the surface refining model as a constraint to trim the surface of the three-dimensional geologic model, and fusing factors of ArcGIS software and three-dimensional geologic model analysis by using Python to obtain a three-dimensional geologic model surface refining model; complete slope data are constructed; inputting the fused complete side slope data into a machine learning algorithm training model, and generating a side slope landslide susceptibility prediction model; the optimized model is used for carrying out landslide susceptibility prediction on new slope data. According to the method, various factors influencing the slope stability can be comprehensively analyzed, high efficiency can be kept during large-scale data processing, and the slope stability in mine engineering can be evaluated more accurately.