337 results about "Slope stability" patented technology

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 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 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 invention belongs to the technical field of geological disaster risk assessment, and particularly relates to a slope stability grade identification method and system based on multi-modal deep learning. Comprising the following steps: acquiring a remote sensing image and corresponding parameter data, and respectively preprocessing the remote sensing image and the corresponding parameter data to obtain a high-dimensional image feature vector and a parameter feature vector; performing dynamic fusion of multi-modal information on the high-dimensional image feature vector and the parameter feature vector through a modal-level gating and fine-grained weighting mechanism to obtain a fusion feature; and inputting the fusion features into a preset classifier to obtain probability distribution of slope stability levels, and outputting the class with the maximum probability as a stability level identification result. According to the method, through combined modeling of the image modality and the parameter modality and introduction of an improved gating attention mechanism in a feature fusion stage, a reliable explanatory basis can be provided while high-precision prediction is ensured, so that the engineering applicability and the popularization value of the model are enhanced.

The invention discloses a geotechnical engineering catastrophe dynamic real-time intelligent early warning method and system based on displacement monitoring, and the method comprises the steps: collecting the real-time displacement data and related parameters of a geotechnical engineering region through displacement monitoring equipment, and transmitting the real-time displacement data and related parameters to a bank slope stability evolution analysis platform to establish a multi-dimensional database; calling a fractured rock mass effective stress analysis model to calculate rock mass effective stress distribution characteristics, and inputting a multi-grid sliding surface stress calculation algorithm to obtain a potential sliding surface stress state and a critical threshold value; inputting the sliding surface stress parameters and the displacement data into a multi-field coupling analysis learning prediction model to obtain a displacement evolution trend and a catastrophe risk coefficient; and finally, real-time early warning information is generated and fed back through the catastrophe dynamic real-time intelligent early warning module. The method improves the real-time performance and accuracy of early warning, can effectively guarantee the safety of geotechnical engineering, and is suitable for catastrophe early warning scenes of geotechnical engineering such as bank slopes and foundation pits.

The invention provides a method and device for evaluating the stability of a soil slope in a man-made forest area and electronic equipment, and relates to the technical field of slope protection. In the method, a multi-field coupling numerical model not only considers a hydrological effect and a mechanical effect, but also considers the comprehensive effect of the hydrological effect and the mechanical effect; and the comprehensive influence of the artificial forest on the slope stability under the real environment load can be accurately quantified and verified.

The invention provides a method for analyzing deformation characteristics of an exit slope of a flood discharge building, which comprises the following steps of: firstly, collecting geotechnical parameters, hydraulic load parameters, GNSS displacement, pore water pressure and clinometer data of the slope; then, constitutive parameters of the slope stability model are dynamically corrected, GNSS displacement is decomposed into creep and elastic displacement components, and the time delay error of pore water pressure data is compensated; thirdly, seepage-stress coupling stability calculation is conducted in combination with the compensated pore water pressure and inclinometer data, and the slope stability safety coefficient is obtained. And finally, outputting the creep displacement, the elastic displacement and the stability safety coefficient to an early warning terminal. According to the invention, the accuracy and reliability of slope stability evaluation can be improved.

The invention discloses a landslide risk early warning method, device and equipment based on multi-source data fusion, relates to the technical field of natural disaster monitoring, and aims to solve the problem of low precision and timeliness of landslide risk early warning. The method comprises the following steps: collecting multi-source monitoring data of a target area in real time and constructing a multi-source parameter set, wherein the multi-source parameter set comprises rainfall characteristic data, soil hydrogeological parameters and slope morphological parameters; performing space-time discretization moisture migration simulation based on the multi-source parameter set, and generating space-time distribution data reflecting the dynamic change of the slope moisture field; calculating a slope stability index sequence according to the spatial and temporal distribution data to construct a prediction model reflecting a risk evolution trend; and setting a dynamic grading early warning threshold based on a prediction model output result, and triggering multi-grade early warning information when the risk grade reaches a preset condition.

The invention relates to a slope stability rechecking method combining a Sweden arc method and monitoring data, which specifically comprises the following steps of: looking up geological survey data of a target slope, acquiring initial rock-soil body strength parameters and a slope angle, arranging deformation sensors on the surface and underground of the slope, acquiring slope deformation data monitored in real time, and determining the slope stability of the target slope according to the deformation data. Determining a potential arc slip plane of the slope according to the three points with the maximum deformation; equally dividing the soil body within the range of the potential arc slip plane according to the fixed width, and directly calculating the center height and the vertical included angle of the ith soil strip through a geometric analysis method based on the geometric parameters and the slope angle of the potential arc slip plane; according to the initial rock-soil body strength parameter, the calculated soil strip height and the vertical included angle, limit equilibrium stability calculation is carried out, the stability coefficient of the potential arc slip plane is obtained, and the slope stability is rechecked. According to the method, a scientific decision basis is provided for slope safety management, preventive maintenance and precise treatment become possible, and disasters are effectively avoided.

The invention provides a slope seepage analysis method under a flood discharge atomization condition. The slope seepage analysis method comprises the following steps: S1, acquiring slope pore water pressure data and matrix suction data through a distributed sensor array; s2, the data fusion unit compares the pore water pressure data with a dynamic critical pressure threshold value, compares the matric suction data with a dynamic critical suction threshold value, and generates a seepage analysis trigger instruction when any data exceeds the limit; s3, starting a transient seepage field calculation model by the seepage calculation engine based on the fracture network topology data; s4, generating a slope stability control parameter set according to a seepage pressure distribution diagram output by the transient seepage field calculation model; and S5, the execution system regulates and controls the operation state of the drainage facility according to the slope stability control parameter set. The slope seepage pressure can be reduced, the slope stability is improved, and safe operation of a water conservancy project is guaranteed.

The invention relates to the technical field of slope stability prediction, in particular to a slope stability evolution prediction method of a main shock and aftershock sequence cumulative damage mechanism. The method comprises the following steps: determining an initial strength parameter of a slope sliding surface rock-soil body and a dynamic strength attenuation parameter under the action of a main shock and aftershock sequence through an indoor cyclic load test, and establishing a cumulative damage model; three-dimensional side slope geometric features are obtained, and the spatial orientation and the stress direction of a potential sliding surface are determined; calculating a dynamic sliding force in combination with seismic oscillation parameters, and updating an effective strength parameter and a dynamic anti-sliding force of the sliding surface in real time; and carrying out staged calculation and dynamic evolution analysis by adopting a limit equilibrium method or a strength reduction method. According to the method, by introducing a rock-soil body strength accumulated damage and progressive attenuation mechanism under the cyclic action of the main and aftershock sequences, the damage accumulation process and the stability evolution law of the slope stability along with the development of the main and aftershock sequences are described, so that the progressive instability process and the accumulated instability risk driven by the aftershock after the main shock is triggered can be identified.

The invention provides an intelligent landslide rainfall simulation system and method based on AI historical rainfall data driving, and belongs to the technical field of geological disaster monitoring and early warning. Dynamic coupling analysis and high-precision simulation of the rainfall process and slope stability are realized through automatic fusion of multi-source monitoring data and spatial-temporal feature extraction in combination with deep learning and physical mechanism modeling. The system can sense various types of data such as rainfall, soil moisture content and slope deformation in real time, intelligently identify landslide induced risks, output graded early warning information and support digital twinborn and adaptive risk optimization decisions. The landslide disaster risk assessment and early warning accuracy and response timeliness are remarkably improved, and the method has good intelligence, expansibility and practical application value and is widely applied to the fields of geological disaster prevention and control and engineering safety monitoring.

The invention relates to the technical field of computational mechanics, in particular to a DDDA-based circle-circle contact interface non-occlusion sliding numerical simulation method, which comprises the following steps: constructing a non-occlusion joint model; establishing a circular unit-non-occlusion joint initial correlation; establishing a DDDA total balance equation; applying a non-occlusion contact constitutive to the associated circle unit contact; and solving the model to obtain the non-occlusion sliding process of the circle-circle contact interface. According to the invention, the non-occlusion sliding process of the circle-circle contact interface is realized, so that the sliding simulation result of the structural surface better conforms to the real mechanical response of the structural surface, and a more convincing numerical analysis tool is provided for the sliding process analysis of slope stability, the slip instability prediction of underground engineering surrounding rock along a weak surface and other key engineering problems. And the method has great engineering application value.

The invention provides a comprehensive optimization method for blasting control in a complex geological environment, and the method comprises the steps: collecting rock mass characteristic data, including hardness and density distribution, in the complex geological environment through a field sensor, integrating multi-source information through a data fusion method, and obtaining a unified rock mass characteristic model; the soft rock disturbance degree is evaluated through slope stability influence indexes, a blasting time sequence is calculated through a particle swarm optimization algorithm, a delay interval is prolonged for a high disturbance area, and an accurate blasting time sequence scheme is determined; generating pre-fracture formation path prediction according to the accurate blasting time sequence scheme, and if the adaptation degree of the prediction path and the target geology is lower than a threshold value, iterating time sequence parameters to obtain a regular pre-fracture formation model; and deriving energy release distribution from the regular pre-crack formation model, integrating a time sequence scheme and a charging structure, and simulating the overall blasting efficiency to obtain final geological adaptive blasting control parameters.

The invention discloses a high and steep slope safety monitoring system and method, and relates to the field of high and steep slope safety monitoring, and the method comprises the steps: collecting sensing monitoring data of a target high and steep slope, an initial three-dimensional point cloud model, and the triaxial acceleration and angular velocity of a laser radar in a scanning process through deploying a multi-mode monitoring network; the point cloud configuration module generates a dynamic reference by using a laser radar and an IMU; the space-time alignment module realizes data fusion and feature extraction; the signal activation module triggers graded early warning based on stability evaluation; according to the application, data collected by different types of sensors are effectively integrated, key information reflecting the stability of the high and steep slope is extracted, the equipment layout is optimized, interference to monitoring equipment is reduced, and the accuracy and reliability of monitoring data are improved. And all-directional high-precision monitoring on the stability of the high and steep slope is realized.

The invention discloses a mine blasting design optimization method and device based on digital twinning and a medium, and relates to the technical field of digital twinning, and the method comprises the steps: collecting terrain three-dimensional point cloud, geological drilling records, joint and fracture distribution and rock mass mechanical parameters of a physical mine, and constructing an initial digital twinning body; through a deep reinforcement learning algorithm of a multi-target reward function, performing multiple rounds of interactive training in a digital twinborn simulation environment to obtain a deep reinforcement learning agent; implementing an optimal blasting scheme in the physical mine, acquiring blasting vibration signals, and inputting the blasting vibration signals into the vibration inversion neural network to obtain rock mass parameter correction values; the updated digital twinborn body is corrected based on the rock mass parameter correction value, a blasting simulation scene is reconstructed, blasting energy distribution, fragment granularity and slope stability are evaluated, and a blasting design optimization feedback data set is generated; a high-fidelity initial digital twinborn body fused with multi-source geological information is constructed, and the safety of mine blasting operation is effectively improved.

The invention discloses a rock stratum drilling in-situ identification method based on physical information machine learning and an application thereof, which are used for solving the technical problem of in-situ sensing of unknown rock mass properties in a drilling process. Multi-source signal parameters including drilling pressure, drilling rod torque, drilling rod rotating speed, drilling speed and drilling vibration and acoustic emission signals are collected in the drilling process, CEEMDAN-VMD combined denoising and feature extraction are carried out, and fused feature vectors are input into a physical information machine learning model; and outputting the strength prediction value of the drilled rock stratum and the prediction value of the rock mass category on line in real time. The method is applied to innovative combination of freeze-thaw environment simulation, rock drilling process test and lithology intelligent identification, an advanced means is provided for drillability evaluation of freeze-thaw rock mass, data support can be provided for blasting parameter intelligent design and slope stability early warning, and the method has good engineering applicability and popularization value.

The invention provides a mine geological disaster early warning method and system based on digital twinning and electronic equipment, and relates to the technical field of geological disaster monitoring and early warning. The method comprises the following steps: constructing a digital twinborn model corresponding to a target mine based on multi-dimensional geological data and rock physical and mechanical parameters; collecting multi-source heterogeneous monitoring data of the target mine in real time, and mapping the multi-source heterogeneous monitoring data to corresponding grid nodes of the digital twinborn body based on the spatial coordinate relationship so as to update state attributes of the digital twinborn model in real time; according to the rock mass physical and mechanical parameters of the grid nodes and the updated state attributes, a slope stability coefficient is calculated through a rock and soil mechanical model; calculating a displacement predicted value based on historical time sequence characteristics of the multi-source heterogeneous monitoring data by using a data driving model; and carrying out fusion calculation on the slope stability coefficient and the displacement prediction value to obtain a comprehensive early warning index, and when the comprehensive early warning index meets a preset geological disaster alarm condition, rendering a risk area in the digital twinborn body.

The invention provides an open-pit mine multi-step space-time cooperative efficient mining method, and relates to the technical field of open-pit mine mining, and the method comprises the following four steps: constructing a dynamic three-dimensional geologic model based on multi-source data, carrying out multi-step space-time cooperative pre-planning, carrying out multi-step dynamic scheduling and cross-operation cooperation, and carrying out multi-parameter coupling grading early warning. According to the method, real-time mapping of a physical mine and a virtual model is realized by integrating total element data of geology, equipment and environment through a digital twin platform, further, real-time problems such as equipment conflicts and road closing are solved through pre-planning and optimizing step space layout and time sequence and dynamic scheduling, efficient operation of main mining equipment can be guaranteed, and the real-time performance of the main mining equipment is improved. Then a multi-parameter coupling grading early warning mechanism is introduced, key indexes such as slope stability and dust concentration are monitored in real time, the accident risk is reduced through grading response, and multiple targets of improving the working efficiency, reducing the operation cost, controlling the safety risk and flexibly utilizing resources can be achieved.

The invention relates to the technical field of image processing, big data analysis and slope engineering, and discloses a tractor-ploughing road slope stability evaluation system based on image recognition and big data, and the system comprises the steps: obtaining a remote sensing image, geological parameters and real-time sensor data through a slope data collection module; the image multi-modal coding module performs hierarchical convolution and cross-modal association on the remote sensing image to form a multi-modal coding feature matrix; the geological data space-time coding module performs space-time sequence coding on the geological parameters to generate a space-time correlation feature matrix; the sensor data dynamic coding module extracts real-time sensor data dynamic characteristics and generates a coding characteristic matrix; and the multi-source data fusion module fuses the three types of matrixes to obtain a comprehensive feature matrix, and after stability feature enhancement and space attention correction, the three-dimensional thermodynamic diagram generation module outputs a three-dimensional stability thermodynamic diagram. The system realizes multi-source data deep fusion and spatial-temporal characteristic analysis, improves the evaluation accuracy and the visualization level, and is suitable for intelligent evaluation of the slope stability of the tractor-ploughing road.

The invention discloses a multi-source monitoring and early warning method for slope stability of a strip mine dump. The method comprises the steps that multi-source monitoring data of a target slope are acquired, and the multi-source monitoring data comprise radar monitoring data, GNSS monitoring data and deep displacement sensor data; a two-dimensional model of the central axis of the maximum deformation area of the target slope is established based on the numerical simulation technology, the model is generated according to slope design parameters and rock stratum physical and mechanical parameters, and the deformation rate and the accumulated displacement early warning threshold value are obtained by simulating the landslide process; and according to the slope surface deformation rate and the deep accumulated displacement, landslide risk early-warning grades are divided, and the surface early-warning grade and the deep early-warning grade are fused to output a final landslide risk early-warning result. The method is comprehensive and accurate in monitoring and early warning of the slope stability of the strip mine dumping site, and is suitable for monitoring and evolution of the slope stability of the strip mine dumping site.

The invention relates to the field of land reclamation engineering, in particular to a land reclamation engineering progress monitoring system based on time sequence image analysis, which comprises a data storage module, an engineering progress image recognition engine, an engineering quality detection module, a meteorological condition compensation module and an early warning module. A Riemannian geometric model of a terrain curved surface is constructed, a project progress is analyzed and quantified through a geodesic network, a project progress image recognition engine comprises an image registration module, a Riemannian geometric terrain modeling module and a geodesic analysis module, and the Riemannian geometric terrain modeling module constructs a terrain surface model through manifold parameterization and measurement tensor calculation. The geodesic analysis module quantifies engineering progress indexes such as the earthwork completion rate, the road hardening rate and the greening coverage rate based on geodesic network changes, the system further integrates quality evaluation functions such as slope stability detection and drainage system integrity detection, and the reliability of a monitoring result is improved through meteorological condition compensation.

The invention relates to the technical field of blasting construction, in particular to a slow slope hole-by-hole presplitting blasting method and system.The method comprises the following steps that engineering geological condition comprehensive information of a blasting area is obtained so as to determine the blast hole distance, the blast hole row distance, the blast hole depth and blasting delay; in the blasting area, RTK is used for paying off and measuring points, the coordinates of the blast holes are obtained in combination with the three-dimensional point cloud data, the distance between the blast holes and the row distance between the blast holes and used for positioning the blast holes and searching the holes, and drilling is completed according to the depth of the blast holes; charging explosives into the blast holes, checking the connection of a detonating network, detonating according to the sequence of the pre-split holes, the main blasting holes and the auxiliary holes, and performing hole-by-hole short-delay detonating on the pre-split holes according to the blasting delay; and field blasting is carried out in the blasting area, the vibration reduction rate of hole-by-hole presplitting blasting is calculated, the half-hole rate after hole-by-hole presplitting blasting is counted, and the damage degree of the surrounding rock is judged. According to the method, joint development during slow slope hole-by-hole presplitting blasting can be effectively reduced, the slope stability of fractured rock mass and surrounding buildings is improved, and the slope protection cost is saved.

The invention relates to the technical field of environmental governance and ecological restoration, and discloses a microbial grouting solidification system for mine restoration. Comprising a microorganism propagation and activation module, a cementing liquid preparation and supply module, a double-liquid precise mixing and filling module, a multi-channel distribution and injection module and a real-time monitoring and intelligent control module which are connected with one another, the microbial propagation and activation module comprises a first-stage seed tank, a second-stage propagation tank and an activation storage tank which are sequentially connected through pipelines, and a bacterial liquid activity online detector is arranged at an outlet of the activation storage tank; the cementing liquid preparation and supply module comprises a urea solution storage tank, a calcium salt solution storage tank, a solvent water storage tank and an online dilution and blending unit, and the urea solution storage tank, the calcium salt solution storage tank and the solvent water storage tank are all connected with the online dilution and blending unit through pipelines. According to the system, efficient solidification of a slope rock-soil body, heavy metal fixation and slope stability improvement are achieved, and meanwhile the repair cost is reduced.

The invention discloses an operation high-speed rail tunnel exit tall slope collapse rockfall construction method and system, relates to the technical field of rockfall protection, and is applied to an operation mountain with a structure denudation type high and steep high mountain and hill landform at an operation high-speed rail tunnel exit. The distribution and characteristics of the dangerous rock mass can be accurately presented; the model is subjected to region division to obtain a plurality of dangerous rock risk regions, so that detailed distinguishing of different risk regions can be realized; carrying out slope stability evaluation on each dangerous rock risk area and determining a risk level, so as to clearly quantify a risk condition; corresponding slope protection components are matched according to the risk levels, so that selection of the protection components is more targeted; and finally, scaffold platforms of all dangerous rock risk areas are built, operation is carried out through protection components, effective implementation of protection work is guaranteed, then pertinence and reliability of slope protection can be improved, and safety risks and resource waste caused by improper protection are avoided.

The invention provides an in-service slope inspection method and system based on machine vision, and the method comprises the steps: building a composite data set through obtaining the continuously collected visible light image data and the synchronously collected infrared thermal imaging data of an in-service slope, and the three-dimensional point cloud data, carrying out the multi-dimensional information extraction processing of the composite data set, and carrying out the inspection of the in-service slope. And obtaining the texture change sequence of the in-service slope surface and the temperature gradient distribution corresponding to the infrared thermal imaging data. And inputting the two into a pre-trained transfer learning model, adjusting and optimizing the model in combination with slope instability case data in a historical disaster database, and outputting instability risk probability distribution of the in-service slope. Performing space-time matching on the instability risk probability distribution and meteorological data acquired in real time, quantifying the influence weight of rainfall and temperature change on the stability of the in-service slope through a meteorological geological coupling model, updating a deformation prediction curve of the in-service slope, performing matching analysis with a disaster threshold library in a historical disaster database based on the deformation prediction curve, and determining the stability of the in-service slope. And generating a slope maintenance decision table.

The invention discloses a digital twin-driven slope stability evaluation method, and belongs to the field of geological engineering and civil engineering. According to the method, slope images and point cloud data are obtained through an unmanned aerial vehicle, sensors are arranged to collect physical field data, and geological exploration parameters are combined; after data preprocessing, constructing a training sample set, a digital twinborn body and a CNN model containing a multi-scale convolutional layer, and training the training sample set, the digital twinborn body and the CNN model; inputting the trained CNN model to predict a stability state by utilizing digital twin mapping real-time data, and outputting a probability value or category; and finally, early warning is triggered through dynamic threshold judgment, visual display is performed on a digital twin platform, and reinforcement decision support is provided. According to the method, multi-source data and a digital twinborn technology are fused, accurate capture of slope dynamic characteristics is realized, the real-time performance and accuracy of evaluation are improved, and a scientific basis is provided for engineering safety guarantee.

The invention provides a tunnel-slope system state information association mutual feedback model construction method and system, and relates to the technical field of geotechnical engineering monitoring, and the method comprises the steps: constructing a unified database through obtained target monitoring data, and analyzing an influence coefficient of a traffic load on slope stability in combination with a dynamic disturbance factor; on the basis of the coefficient, the geographic features and the stress data, completing unknown region data to form a complete data set; extracting a sensitive feature set, identifying a construction blasting and rainstorm rainfall interference section, and locking a side slope potential sliding surface and tunnel lining deformation collaborative feature interval; constructing a multi-index evaluation matrix, performing normalization and threshold dynamic adjustment, and screening an early warning index set; a dynamic model is established, and a tunnel-slope system state information association mutual feedback model is formed through a bidirectional feedback mechanism optimization model of slope displacement and tunnel excavation data. According to the invention, the accuracy and real-time regulation and control capability of tunnel-slope system state early warning are improved.

The invention provides a three-dimensional lithium battery mine visualization system based on digital twinning, and the system comprises a physical sensing layer which is disposed at a lithium battery mine site, and comprises a plurality of sensor networks used for collecting geologic bodies, production equipment, environment parameters, personnel positions, and vehicle states; and the data interaction layer comprises a data integration platform and an edge computing node, and is used for carrying out cleaning, fusion, protocol conversion and edge side preliminary analysis on the multi-source heterogeneous data uploaded by the physical sensing layer, and uploading the multi-source heterogeneous data to a cloud. By integrating the slope monitoring sensor and the professional analysis model, real-time evaluation and advanced early warning of the slope stability and the tailing pond safety are achieved, major accidents such as collapse and dam break are effectively prevented, meanwhile, the harmful element diffusion model is utilized, and the safety of the tailing pond is improved. Migration paths of fluoride dust, radioactive substances and potential leakage pollutants in the atmosphere and the water system are dynamically simulated, accurate decision support is provided for environmental risk emergency response, and the influence on surrounding ecology is reduced to the maximum extent.

The invention relates to the technical field of civil engineering, in particular to a red sandstone multi-bench combined mechanical cold excavation construction method which comprises the following steps: S1, generating a rock mass model by adopting three-dimensional laser scanning and AI geological analysis, and dynamically optimizing mechanical configuration and excavation parameters by combining a BIM numerical simulation rehearsal bench scheme; accurate rehearsal and parameter optimization of a stair flight scheme are achieved through three-dimensional laser scanning, AI geological analysis and BIM numerical simulation, a scientific basis is provided for construction, dynamic adaptation and process correction of excavation operation are achieved with the help of rock mass hardness sensing, intelligent parameter matching and particle size recognition technologies, the construction efficiency and the crushing quality are improved, and the construction cost is reduced. Real-time monitoring, trend prediction and grading response of slope stability are achieved through a multi-source sensing network, a digital twin model and edge calculation, construction safety is guaranteed, and the intelligent level, operation efficiency and safety controllability of red sandstone multi-bench mechanical cold excavation are remarkably improved.