949 results about "Slope gradient" patented technology

The invention provides a drainage basin digital twinning construction method and system based on multi-source data fusion. The method is applied to the technical field of drainage basin digital twinning construction, and comprises the following steps: acquiring water level monitoring data, surface flood routing path data, weather forecast rainfall data and terrain slope change data; rainfall and topographic slope data are fused to generate a runoff distribution relation, and a high-risk area is identified in combination with a water level sudden change amplitude. A digital twinning preliminary framework is established, and related characteristic parameters are generated by utilizing reverse feedback of a flood path and water level data. And inputting meteorological data, constructing a twinborn model based on the boundary condition of the catchment area, and simulating flood direction abnormity and flooding early warning signals. And according to the early warning space-time distribution and the terrain elevation data, generating emergency schemes such as flood dividing gate scheduling and flood storage and detention area starting, and realizing risk hierarchical management and control. According to the technical scheme provided by the invention, the flood inundation prediction precision and the emergency response efficiency are improved, and precise decision support is provided for flood control of a drainage basin.

The invention provides a water and soil loss dynamic monitoring method and system based on a remote sensing image, and the method comprises the steps: firstly obtaining a multi-temporal remote sensing image data set of a target region, which comprises a plurality of time period remote sensing image subsets and land surface coverage information, and then carrying out the land surface feature extraction of the multi-temporal remote sensing image data set, after vegetation coverage, terrain gradient and soil exposure features are obtained, a water and soil loss prediction model based on time-space correlation is constructed, the features are input for prediction, a water and soil loss grade distribution map is generated, a target loss risk area is identified according to the water and soil loss grade distribution map, and a treatment priority sequence and a vegetation recovery strategy are generated. And finally, the information is fed back to a monitoring platform to trigger regional governance task allocation operation, so that dynamic monitoring of water and soil loss is realized, and governance tasks are effectively planned.

The invention discloses a reservoir bank slope geological disaster risk identification method based on an unmanned aerial vehicle laser radar, and relates to the technical field of reservoir bank slope prevention and control, an unmanned aerial vehicle is used for carrying laser radar equipment, flight scanning is carried out on a reservoir bank slope area, and three-dimensional point cloud data is obtained. According to the reservoir bank slope identification method based on the unmanned aerial vehicle laser radar detection data, high-precision terrain and geological information of the reservoir bank slope is rapidly acquired in a non-contact manner by using the three-dimensional imaging capability of the unmanned aerial vehicle laser radar technology, so that the data acquisition efficiency and safety are greatly improved; the method also remarkably improves the precision and integrity of data, accurately captures key topographic factors such as topographic relief, gradient, slope direction and the like through laser radar scanning, and provides a solid foundation for the accurate recognition of bank slope types in combination with geological factors such as geological structures, lithology and the like, so that the prediction and evaluation of bank slope disasters are more accurate. Preventive measures can be taken in advance, and disaster risks are reduced.

The invention provides a multi-modal fusion sensing robot dog inspection slope disaster risk assessment method and device and a storage medium, and relates to the field of slope disaster assessment, and the method comprises the steps: obtaining multi-modal sensing data; performing space-time alignment processing on the multi-modal sensing data and then converting the multi-modal sensing data into a voxel coordinate system; performing feature extraction on the multi-modal sensing data after time-space alignment, and mapping each extracted feature to a unified voxel unit to form a three-dimensional voxel structure containing each extracted feature; constructing a three-dimensional multi-modal data fusion model; identifying disaster types based on the three-dimensional multi-modal data fusion model, wherein the disaster types comprise the ground surface crack length, the underground cavity volume, the water seepage point number, the local collapse and bulging area, the vegetation degradation area and the slope gradient; and calculating a risk index based on the identified disaster type in combination with the association degree of the disaster type. By adopting the evaluation method provided by the invention, rapid and efficient evaluation of slope disasters can be realized, and the method has relatively good accuracy.

The invention relates to the technical field of risk analysis, in particular to a safety engineering comprehensive management system which comprises a geological parameter dynamic monitoring module, a risk threshold early warning module, a stability weight evaluation module and a risk comprehensive management and control module. According to the method, lithology data are extracted through a drilling profile to calculate the layer thickness sudden change rate and the strength attenuation rate, a lithology abnormal area is positioned through a variable coefficient method, lithology sudden change marks are analyzed through spatial clustering, a dynamic trend is captured through sliding window mean value comparison, and gradient amplitude and slope direction dispersion are calculated through a digital elevation model. Fusing the abnormal point density to generate a terrain instability index; establishing a multi-dimensional quantitative evaluation framework; carrying out fuzzy comprehensive evaluation and cross validation on the instability index and an engineering parameter trend; generating a dynamic priority sequence, carrying out stake number interval matching to construct a risk measure table, carrying out analytic hierarchy process dynamic resource allocation support drainage scheme, and carrying out real-time monitoring and prediction closed-loop iteration. And adaptively adjusting the control strategy.

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 discloses a method for predicting the risk of a valley-type tailing pond being threatened by extra-small watershed flood, and the method comprises the steps: S1, obtaining the soil type, vegetation coverage and gradient of the extra-small watershed of the valley-type tailing pond, and the spatial distribution data of a valley, and building an underlying surface classification system; s2, non-linear key inducements in the rainfall-runoff process in the valley terrain extra-small watershed are extracted, dominant factors influencing runoff formation are recognized, and a non-linear confluence calculation numerical model is constructed; s3, constructing a distributed sensing monitoring network through a rainfall monitoring station and a runoff monitoring station; s4, constructing a layered three-dimensional hydrological hydrodynamic model of coupling rainfall runoff generation-slope confluence-shallow groundwater flow; and S5, establishing a risk assessment index system and a risk prediction model through a layered three-dimensional hydrological hydrodynamic model in combination with flood risk influence factors. According to the method, accurate prediction of the valley-type tailings pond under the flood threat in the extra-small watershed is realized, and the problem of poor predictability of the flood threat in the extra-small watershed is solved.

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 provides an intelligent early warning method and system for phosphorus tailing improved soil heavy metal migration, relates to the technical field of computers, and accurately predicts the main migration direction of heavy metal pollutants by combining factors such as terrain gradient, hydrological flow direction and soil structure heterogeneity. The method comprises the following steps: acquiring soil information of a to-be-detected area and soil potential information of a detection point in the to-be-detected area; determining heavy metal concentration information of the detection point according to the soil potential information; the heavy metal concentration information is used for reflecting heavy metal concentration distribution conditions corresponding to different soil depths of the detection points; determining migration direction information of the heavy metal at the detection point; the migration direction information is used for reflecting the corresponding heavy metal migration direction distribution condition of the heavy metal of the detection point in the three-dimensional space; and predicting a pollution diffusion area based on the migration direction information, the organic decomposition rate and the underground water level fluctuation information, and performing visual display.

The invention relates to the technical field of geological disaster detection, in particular to a geological disaster hidden danger point detection method and system. Comprising the following steps: S1, synchronously acquiring vegetation canopy penetration data, multispectral soil humidity spatial distribution data and lithology distribution data by adopting an unmanned aerial vehicle carried image data acquisition device and a multi-band laser radar, and generating an orthoimage and a three-dimensional point cloud data set; s2, fusing the orthoimage and the three-dimensional point cloud data through an aerial triangulation encryption algorithm to establish a three-dimensional model, loading the multispectral soil humidity spatial distribution data into the three-dimensional model to generate a dynamic digital elevation model, and generating a contour line topological structure through a TIN triangulation network algorithm; s3, extracting a slope factor, topographic relief, vegetation coverage, fracture distance and a lithologic factor based on the three-dimensional model to construct a geological disaster hidden danger system; according to the system, the geological disaster occurrence time can be estimated, and the rescue and protection treatment period can be effectively planned based on the geological disaster occurrence time.

The invention relates to the technical field of earthquakes, in particular to an optical remote sensing image feature landslide information extraction method. A double-time-phase NDVI time sequence analysis strategy is adopted, and landslide area recognition is achieved by constructing a vegetation index difference chart before and after an earthquake. A landslide mass area before an earthquake presents a high NDVI value due to complete vegetation coverage, and a vegetation index of the area in an image after a disaster is significantly attenuated due to surface disturbance, so that an obvious change response is formed. If the normalized vegetation index does not change, a non-landslide area can be determined, and the greater the change of the normalized vegetation index is, the greater the possibility of landslide occurrence is, and a landslide preselection area is determined; then Otsu threshold segmentation is carried out by combining cloud layer features and water body features, cloud layer and water body change parts are effectively eliminated, object-oriented geometric shape rule fine recognition is carried out on a preselected area, a DEM is adopted to calculate a slope value to constrain low-lying or flat earth surface changes, and efficient and accurate landslide information extraction is achieved.

A method, system, medium and program product for measuring a volume based on elevation measurement, the method comprising: determining historical topographic feature data; elevation values of all positions in the mining area in different time periods are extracted; calculating a topographic relief change rule according to the elevation value, and establishing a topographic evolution model according to the topographic relief change rule; extracting terrain boundary feature points and ponding area contour lines from the unmanned aerial vehicle inclined image data; dividing a plurality of local terrain units according to the terrain boundary feature points, and calculating an elevation difference to obtain a gradient change coefficient; determining a terrain prediction model of each local terrain unit; splicing and reconstructing the terrain prediction model of each local terrain unit to obtain underwater terrain estimation data of the ponding area; constructing a mining area terrain model according to the underwater terrain estimation data and the terrain data; and calculating the earthwork excavation volume in the mining area according to the mining area terrain model. According to the invention, the accuracy of mining volume measurement is improved.

The invention belongs to the technical field of bridge safety evaluation, and particularly discloses a method and a system for evaluating local scouring of a bridge pile foundation based on a flow velocity strain rate. A calculation model of a local scouring pit form and a maximum scouring depth of a river-sea crossing bridge pile foundation is established, and a Reynolds stress tensor is converted into a flow velocity strain rate scalar; the method comprises the following steps: providing an erosion-deposition model, analyzing an erosion-deposition rate, establishing a scouring depth relationship, utilizing a sediment transportation model of grid unit storage parameters, simulating dynamic response of a water-sediment mixture, and triggering sediment sliding and updating a riverbed terrain when the dip angle of a scouring pit is at a supercritical slope by virtue of a slump model. All the models cooperate to achieve efficient simulation of local scouring of the pile foundation. According to the method, the form evolution and the maximum scouring depth of the local scouring pit of the single pile and the pile group can be efficiently and accurately calculated, and support is provided for bridge pile foundation design and anti-scouring structure optimization.

The invention discloses a grating dam safety evaluation and design method and structure based on debris flow blocking degree. Wherein the safety assessment method comprises the following steps: S100, calculating the safety of the debris flow on the basis of the solid matter concentration of a debris flow susceptible area, the particle size value corresponding to the accumulated content of 95% in a full particle size grading curve, the channel average gradient, the channel average width and the primary debris flow scale in the section range of the grating dam, the minimum particle size value of the maximum boulder in the drainage basin and the opening width of the grating dam; calculating a critical blocking judgment coefficient according to the correlation value of the height of the grating dam, the angle of the wedge-shaped structure and 60 degrees and the correlation value of the total amount of debris flow solid substances and the reservoir capacity of the wedge-shaped beam type grating dam; and S200, evaluating the safety of the grating dam based on the critical blocking discrimination coefficient. The evaluation and design method and structure incorporate the relative relation between the debris flow scale and the dam body storage capacity, meanwhile, the influence on active structure parameters such as wedge-shaped flow guide is quantified, and the blocking state prediction accuracy of the grating dam in actual operation is improved to a certain degree.

The invention belongs to the technical field of mineral exploration, and particularly discloses a copper ore prospecting method based on three-dimensional geological modeling. The method comprises the following steps: acquiring geological data of a target area; after extreme values in the geological data are recognized and removed through a box plot, the geological data are mapped to an interval of [0, 1], and the geological data are divided into terrain data, stratum data and mineral resource data; adopting Kalman filtering to enable the data to form fusion data, and generating a thematic map comprising a geological map, a mineralization anomaly map and a topographic slope map; based on the data and the thematic map, constructing a three-dimensional geologic model by a finite element method, and performing mining path planning by adopting a specific path planning algorithm formula; exploring by the mining equipment according to the planned path, acquiring geological data, comparing the geological data with the predicted data, re-planning the path and continuing exploring if the path is blocked, the resource recovery is out of tolerance and new mineralization is abnormal, otherwise continuing exploring according to the planned path. The method has the advantages of being high in exploration efficiency and data precision, low in comprehensive cost and high in adaptability.

The invention relates to the technical field of marine surveying and mapping and submarine topography modeling, and discloses a submarine topography and landform construction method based on multi-source water depth data fusion, which comprises a multi-source data acquisition module, a data preprocessing module, a feature extraction module, a fusion algorithm matching module, a three-dimensional modeling module and an uncertainty evaluation module. A historical submarine topographic map is converted into grid data, namely, submarine topography is discretized into digital representation of regular grid units, water depths of other sources are converted into the grid data, the precision of the water depths of different sources is evaluated by adopting a superposition comparison method, and an error distribution model is established to reasonably correct and fuse the water depth data of various sources. The innovation of the method lies in that topographic feature parameters including the gradient, the curvature matrix and the bionic optimization algorithm are introduced, the defect that a single algorithm is preset in a traditional method is overcome, and the precision of coral reef and fault zone complex areas is improved.

The invention discloses an MT-InSAR deformation monitoring method in combination with reservoir bank landslide deformation spatial-temporal characteristics. The method comprises the following steps: S1, selecting SAR data; step S2, constructing small baseline set InSAR data, including SAR image registration, interferogram combination, differential interference processing, phase filtering, coherence estimation and interferogram optimization combination; s3, based on the dual-polarized SAR intensity image, performing earth surface classification in combination with random forest classification, gradient and direction constraint and a deep neural network; then adaptive homogeneous filtering is carried out on the interferometric phase based on a secondary classification result; s4, combining a plurality of Sigmoid functions and a linear creep and periodic function to obtain an adaptive deformation model of the reservoir bank landslide; s5, performing deformation parameter nonlinear search by using a genetic algorithm to determine an optimal parameter set; on the basis of low-frequency deformation, atmospheric delay and decoherence noise are separated through low-pass filtering of a space domain and high-pass filtering of a time domain, and finally a deformation time sequence and an average deformation rate are recovered.

The present invention relates to the technical field of ecological suitability evaluation of agricultural land, and disclosed is a method for evaluating the ecological suitability of agricultural land. The present invention comprises: determining values of indicators of agricultural land, wherein the values of the indicators of the agricultural land comprise slope, elevation, slope length, profile curvature, soil thickness, plan curvature, the minimum number of days of continuous flooding, the maximum number of days of continuous flooding, the cumulative number of days of flooding, the average number of days of continuous flooding, minimum flooding depth, maximum flooding depth, cumulative flooding depth, and average flooding depth. In the present invention, the natural ecology of agricultural land, i.e., whether regional water, soil and climate conditions meet the ecological requirements of the agricultural land, is evaluated, so that it is ensured that the agricultural land can guarantee the sustainability of an ecosystem and environment; the ecological status thereof can be quickly and accurately identified, weights of indicators in an element layer can be determined, and finally, a system for evaluating the ecological suitability of agricultural land is constructed; the method can reflect the ecological suitability of agricultural land in a timely, macroscopic, and dynamic manner.

The invention discloses an RCBAM model construction method for remote sensing inversion of river flow. The method comprises the following steps: 1) collecting remote sensing image data; (2) high-precision DEM production; 3) obtaining a central line of a river channel; 4) river width and gradient acquisition; 5) river section shape extraction; 6) calculating an open-current area; and 7) estimating the river flow. According to the method, the section shape of the river channel is obtained based on a high-precision digital elevation model (DEM), and the section area of the river channel is dynamically calculated by combining instantaneous water surface information obtained by a remote sensing image, so that the problem that defects exist due to the fact that the overflowing area is obtained by depending on an empirical formula in a traditional BAM flow model is effectively solved, and river flow estimation considering the shape characteristics of the river channel is realized. And efficient and accurate river flow remote sensing inversion can be realized.

The invention relates to the technical field of water conservancy projects, in particular to a water conservancy earthwork dynamic monitoring method and system based on multi-source point cloud data fusion, and the method comprises the steps: carrying out the identification and standardization processing of airborne LiDAR, ground scanning and oblique photography point clouds, and generating a standard point cloud data set with uniform spatial positions and balanced density; dividing an abrupt slope area, a gentle slope area and a flat area based on topographic gradients, and constructing a grid framework adaptive to topographic features; carrying out weighted fusion by combining the point cloud coverage rate and the normalized terrain gradient to generate high-precision grid elevation data; calculating an earthwork variation distribution matrix by comparing historical elevation models; dynamically analyzing the change trend of the excavation and filling area, and synchronously evaluating the construction progress deviation and the geological disaster risk. According to the method, the problems of insufficient multi-source point cloud fusion precision, poor terrain adaptability and dynamic evaluation splitting in the prior art can be solved, and the monitoring precision and the engineering safety early warning efficiency under the complex terrain condition are remarkably improved.

The invention relates to the technical field of environmental assessment, and provides a plateau region soil erosion attribution method, system, medium and equipment, and the method comprises the steps: calculating the soil erosion rate of each calculation unit in a research region through a soil erosion model based on multi-source geographic space data; the soil erosion rate is a product of a rainfall erosivity factor, a soil erodibility factor, a slope length gradient factor, a vegetation coverage management factor and a water and soil conservation measure factor; a rainfall erosivity factor, a soil erodibility factor, a slope length and gradient factor, a vegetation coverage management factor and / or a water and soil conservation measure factor are used as key driving factors, and the control degree of the key driving factors on the soil erosion rate change is calculated by adopting a logarithmic mean Dewei index method; wherein the control degree sets a weighting coefficient for each calculation unit in the calculation process, and the weighting coefficient is constructed based on the difference between each calculation unit and the preset reference region. And the independent contribution of each factor to the erosion change can be accurately separated.

The invention discloses a lower reservoir high slope landslide vibration monitoring and early warning system, belongs to the technical field of vibration monitoring, and aims to solve the problems that an existing monitoring and early warning system is poor in comprehensiveness and low in risk estimation accuracy. The system comprises a monitoring unit, a comprehensive coefficient calculation unit and a risk level judgment unit, and the comprehensive coefficient calculation unit comprises an index quantification module, a matrix construction and weight distribution module and a comprehensive coefficient calculation module. A plurality of factors such as stratum characteristics, side slope geological conditions, rock mass characteristics, rock mass structures, side slope heights and side slope gradients are comprehensively considered, a dynamic matrix is constructed, a comprehensive coefficient is calculated by adopting a scientific weight distribution method, and a risk grade division standard is automatically adjusted according to a risk index change trend after fusion. The system adapts to the dynamic change of slope stability, timely gives out accurate early warning, overcomes the problem that an existing monitoring and early warning system only pays attention to a single index or a few indexes, and improves the comprehensiveness of evaluation.

A system for predicting the fundamental period for reinforced concrete buildings on slopes, consisting of: a data input module configured to retrieve building and soil parameters from datasets, including building height, field width, number of fields, slope angle, and soil conditions; a modal analysis module configured to perform a modal analysis of the input parameters using finite element analysis software and to generate results for different slope angles, soil conditions, and building configurations; a soil-structure interaction (SSI) module that includes a foundation modeling component that applies spring stiffness to column foundations based on Gazetas' formulas and simulates soil conditions categorized as stiff, medium or soft, thus incorporating soil-structure interaction effects; a regression and machine learning prediction module configured for developing predictive models using multiple linear regression, random forest, and XGBoost algorithms; and an output module configured to output the predicted basic period of the building based on the trained prediction models.

The invention discloses a mountainous area wind field downscaling optimization method based on high-precision simulation, and relates to the technical field of meteorological numerical simulation, and the method comprises the steps: obtaining the terrain elevation data and meteorological monitoring data of a target mountainous area, recognizing slope abrupt change points, constructing a spiral sampling path, calculating a slope change value, determining the distance between sampling points, and generating target sampling data; performing orthogonal decomposition on the sampled data to obtain a frequency component, calculating a surface fluctuation coefficient, and constructing a boundary disturbance equation to obtain surface stress distribution; calculating an airflow motion state based on surface stress distribution, solving a vorticity equation to obtain vorticity characteristics of a leeward area, and calculating airflow motion correction parameters; and carrying out downscaling iterative operation on the corrected parameters and the meteorological monitoring data to generate target area wind field data with hectometer-magnitude spatial resolution. The simulation precision of the local wind field under the complex terrain condition is improved.

The invention relates to the technical field of slope simulation tests, in particular to a high and steep embankment slope soil engineering simulation test device and method.The high and steep embankment slope soil engineering simulation test device comprises a multi-degree-of-freedom vibration table, a slope assembly, an airflow assembly and a driving assembly, the slope assembly is installed on the multi-degree-of-freedom vibration table, and the airflow assembly is installed on the driving assembly; the airflow assembly is located above the side slope assembly, and the driving assembly is connected with the multi-degree-of-freedom vibration table, the side slope assembly and the airflow assembly; the shifting piece is connected with the frame unit and is used for driving the inclination of the frame unit to change; the data acquisition system is used for monitoring the motion characteristics and collapse deformation of the slope model in the simulation process in real time and collecting data information generated in the test process; the problems that a traditional slope test device cannot dynamically simulate gradient gradual change caused by earthquake collapse, and the multi-disaster coupling effect of rockfall impact and hydrological airflow disturbance is difficult to reproduce are solved.

The invention discloses a slope dangerous rock mass stability intelligent analysis system based on multi-source monitoring information fusion, and the system comprises a slope dangerous rock mass multi-source information monitoring sensor which receives a dangerous rock mass stability intelligent analysis instruction; the multi-source information acquisition sensor acquires slope gradient, form and rock strength information of slopes at different altitudes of each unit time slope and underground water level and surface water level data of a mountain body where each unit time slope is located, and stores and sends the acquired data to the big data intelligent supervision platform; the big data intelligent supervision platform judges whether the gradient, shape and rock strength information of the slopes at different altitudes and the underground water level and surface water level data are within a preset safety threshold range or not; and the information is fed back to the landslide probability analysis model of the mountain multi-source information monitoring point where the slope is located through the 5G network transmission base station. According to the invention, a slope dangerous rock landslide risk prompt signal can be sent in time, and the monitoring efficiency is improved.

The invention relates to the technical field of slope reinforcement, and discloses an anchoring device for preventing landslide geological disasters, the anchoring device is arranged on a slope surface, distributed in a grid shape and formed by splicing a plurality of anchoring units, each anchoring unit comprises an anchor rod support and four frames, the four frames are evenly distributed on the periphery of the anchor rod support, and the anchor rod support is arranged on the periphery of the anchor rod support. The anchor rod support is detachably connected with the frame; a center hole is formed in the anchor rod support, and an anchor rod inserted into a slope body is installed at the center hole. Every two adjacent frames are connected through a set of reinforcing mechanisms. The modular structural design is adopted, specifically, the detachable anchor rod supports and the frame are combined, the weight of a single node is small, carrying is convenient, manual carrying and rapid splicing are facilitated, a latticed splicing system formed by the scheme can adapt to terrains with different slopes, and the construction efficiency can be effectively improved.

The utility model relates to the technical field of hydraulic engineering construction machinery, and discloses a canal trench ditching device, which comprises a chassis structure, a trench digging mechanism, a trench digging mechanism, a trench digging mechanism, a trench digging mechanism, a trench digging mechanism and a trench digging mechanism, wherein the chassis structure is used for realizing operation on soft and hard alternate soil layers or undulating surfaces; the rotary tillage structure is mounted at the bottom of the chassis structure and used for crushing hard soil on the surface layer and removing weeds and broken stones to form a uniform and loose plough layer; the ditching structure is mounted at the bottom of the chassis structure, is positioned behind the rotary tillage structure and is used for realizing excavation of grooves with different depths; and the tamping structure is installed at the bottom of the chassis structure and located behind the ditching structure, comprises a soil shifting shovel for leveling soil discharged from the two sides of the ditching structure, and tamps the bottom of the groove and the side slope through vibration compaction of a plane tamping plate and a slope tamping plate. By integrating the self-adaptive terrain adjusting system and the combined type grooving mechanism, topographic relief and soil states can be monitored in real time, the ditching depth, gradient and section form can be dynamically adjusted, and one-time forming of a groove is ensured.