124 results about "Earthquake risk" patented technology

The invention belongs to the technical field of seismic structure models, and discloses a seismic structure model construction method and system, and the method comprises the steps: constructing a database; constructing a three-dimensional digital elevation model; constructing a three-dimensional geological structure model; constructing an earthquake three-dimensional earthquake structure model; constructing a three-dimensional P-wave velocity structure model; and analyzing a pregnancy and earthquake environment. The three-dimensional seismic geologic model of the Changning seismic region is constructed by taking the Changning seismic region in southern Sichuan as a modeling object and integrating superficial geology, landform (DEM), seismic fine positioning data and main fracture distribution, a deep seismic detection result, a two-dimensional seismic reflection profile, drilling data and the like, the spatial distribution and structure of the three-dimensional seismic geologic model are finely determined, and the three-dimensional seismic geologic model of the Changning seismic region is constructed. Analysis of deep and shallow tectonic deformation characteristics and tectonic styles has important guiding significance for discussing the earthquake-pregnancy environment and evaluating the earthquake risk of the deep and shallow tectonic deformation.

The invention discloses an earthquake risk analysis method based on a regional fine geological structure. The method comprises the following steps: constructing a fine three-dimensional geoscience model; optimizing boundary conditions based on GNSS velocity field data; finite element numerical simulation; and earthquake risk analysis. According to the method, a fine three-dimensional geoscience model is constructed, a finite element numerical simulation method is utilized, historical seismic data and geologic structure characteristics are combined, non-uniform strain energy distribution caused by plate movement in a certain time is calculated, and depth and magnitude weighting processing is performed on magnitude risk values obtained through simulation, so that the magnitude risk values are obtained. And the actual condition of the earthquake damage effect is reflected. And finally, performing summation operation on the weighted strain energy data of the earthquakes with different depths and different earthquake magnitudes in the research area to obtain the overall earthquake risk distribution condition of the earth surface area. The method can break through the limitation of the existing seismological observation data, the seismic activity can be viewed from a wider view angle and time scale, and the periodicity, frequency and potential disaster risk of the earthquake can be deeply understood.

The invention discloses a water injection induced earthquake monitoring and fault activation detection system, and belongs to the field of earthquake monitoring and fault activation detection. The earthquake observation module is used for obtaining earthquake monitoring data; the seismic phase data extraction module is used for carrying out micro-seismic identification according to the seismic monitoring data to obtain seismic phase data; the earthquake initial positioning module is used for obtaining an earthquake directory of initial positioning; the earthquake fine positioning module is used for carrying out secondary positioning to obtain an earthquake directory of fine positioning; the fault and structure modeling module is used for integrating the finely positioned seismic catalog into a three-dimensional geologic structure model and carrying out spatial positioning and visualization of seismic activities; and the fault activation and earthquake risk analysis module is used for analyzing the earthquake activity time change trend, b value change, fault activation and earthquake risk according to the three-dimensional geologic structure model. The method solves the problem that an existing method lacks monitoring of fault activation and weakening of the shale gas development area and water injection induced earthquakes.

The invention provides a rock burst and mine earthquake collaborative treatment method based on regional fracturing, and the method comprises the following steps: selecting a working surface, determining a plurality of rock burst control layers with rock burst risks, then determining a plurality of mine earthquake control layers with mine earthquake risks, and determining a plurality of mine earthquake control layers with mine earthquake risks; performing main control layer analysis on all the rock burst control layers in the fissure zone preferentially to determine a multi-stage rock burst main control layer, performing main control layer analysis on all the mine earthquake control layers above the fissure zone to determine a multi-stage mine earthquake main control layer, and performing logging correction analysis; according to the length and width of the working face, the thickness of the rock burst control layer and the number of the mine earthquake control layers, the layout design of separate layer fracturing is determined, the treatment method achieves comprehensive prevention and control of the mine area risk, the treatment effect on the rock burst and the mine earthquake is remarkable, the disaster risk is reduced, and a powerful guarantee is provided for mine safety production.

The invention relates to the technical field of disaster early warning, in particular to an earthquake early warning method of an emergency early warning broadcast system, which comprises the following steps: acquiring latitude and longitude coordinates of a seismic source and earthquake monitoring data; according to the longitude and latitude coordinates of the seismic source, determining a broadcast station distribution area range which is represented by longitude and latitude; the method comprises the following steps: constructing an earthquake risk topological space based on historical earthquake data, and dividing earthquake risk grades in the topological space; according to the earthquake risk level, determining a corresponding broadcast emergency degree parameter, and generating a broadcast message code; and sending the broadcast message code to broadcast stations in the broadcast station distribution area through a power line carrier and a wireless communication network so as to trigger earthquake early warning broadcast, accurately determining an early warning range through a topological space mapping technology in combination with geological structure data, remarkably reducing early warning blind areas, and avoiding excessive early warning.

The invention relates to the field of seismic source monitoring, and discloses a double-bubble seismic source monitoring method based on water seismic exploration, which comprises the following steps: deploying a geophone array in a target sea area, recording seismic wave data generated by double bubbles by the geophone array, and taking frequency data of seismic waves as first target monitoring data; the seismic source identification module is used for identifying a seismic source, positioning the position of the seismic source by taking the propagation speed of the seismic wave as second target monitoring data and analyzing the time when the seismic wave reaches different detectors, respectively analyzing the amplitude attenuation characteristic change of the seismic wave in the propagation process and the propagation path of the seismic wave, and evaluating and analyzing the seismic scale; the earthquake risk level is evaluated, the earthquake occurrence probability is calculated based on the evaluated earthquake risk level, the accuracy of seismic source data acquisition is improved, the position of the seismic source can be accurately identified and positioned, and thus the accuracy of seismic probability prediction is improved.

The invention discloses a fault gas online monitoring system and method for seismic observation, and relates to the field of seismic monitoring, and the method comprises the steps: deploying a multi-parameter gas monitoring device near a fault zone, collecting gas concentration data at preset time intervals, building a historical gas concentration time sequence, and building a training feature set through preprocessing and feature extraction; an earthquake prediction model is built based on LSTM, model training is carried out with the training feature set as input and the earthquake occurrence probability as output until a loss function converges, and an optimized earthquake prediction model is obtained; acquiring gas concentration data in a certain time period before the current time node, and predicting an earthquake occurrence probability after the current time node through the optimized earthquake prediction model; when the earthquake occurrence probability exceeds a preset threshold value, early warning information is automatically generated and published to the public through multiple channels, and earthquake risks are prompted. According to the invention, early recognition and early warning of earthquake activities can be realized, and powerful support is provided for earthquake monitoring.

The invention provides an earthquake risk assessment method and system for a medium-strong earthquake region, and belongs to the technical field of earthquake risk assessment, and the method comprises the steps: carrying out the partitioning construction of an earthquake region, and obtaining a plurality of structural regions; fitting data of historical earthquakes and modern small and medium earthquakes in each structural area to obtain an earthquake magnitude-frequency relational expression, and calculating to obtain an incidence rate, an earthquake generation probability and a recurrence interval of any level of earthquake in each structural area; and for each structural area, a spatial smoothing method is used to distribute weights such as the occurrence rate, the earthquake generation probability and the recurrence interval of any grade of earthquake in each earthquake grade, and the like, to each fault zone. According to the method, the seismic activity model is established by using the spatial smoothing method, after smoothing processing, the earthquake risk is generally improved and is close to the historical earthquake occurrence situation, and for the areas with unclear earthquake-generating structures and weak seismic activities, the earthquake with large energy release occupies a more important position in distribution, so that the seismic activity is improved. And the potential danger of the earthquake activity can be reflected more accurately.

According to the urban earthquake disaster situation risk degree and loss big data evaluation platform, modeling is carried out from three aspects of earthquake disaster-inducing factor dangerousness, disaster-bearing body vulnerability and urban earthquake disaster situation response capability, and a big data analysis method based on multi-index decision is adopted to evaluate the earthquake risk degree of an earthquake-prone city. A GIS technology is integrated and combined with an earthquake damage loss matrix evaluation method based on historical big data, an earthquake disaster situation loss evaluation system is established, and the earthquake disaster situation loss condition in a region is evaluated and calculated. Before an earthquake occurs, the risk degree or probability that the region may suffer from the earthquake is analyzed and predicted, the government is helped to scientifically and effectively carry out urban development planning and disaster prevention and reduction decision making, the regional disaster prevention capability construction is improved, and the earthquake disaster situation loss is reduced; after an earthquake occurs, the emergency rescue and response capability is improved, the distribution and scheduling of disaster relief materials are facilitated, and the method has practical significance and effect on regional earthquake risk degree and loss assessment.

The invention discloses an earthquake risk evaluation method and system, and relates to the technical field of earthquake numerical simulation, and the method comprises the steps: receiving a three-dimensional geometric model of a grid fault, and setting an initial condition; constructing a simulation operation equation to solve a shear stress loading rate, a normal stress loading rate and a state variable, and constructing an ordinary differential equation system; based on the three-dimensional geometric model and the initial conditions, accelerated simulation operation of the shear stress loading rate, the normal stress loading rate and the state variables is achieved through the ordinary differential equation system, and the accelerated simulation operation method comprises the steps that accelerated simulation operation is achieved through the method of combining an H-matrix and MPI, comprising the steps that a layered matrix is obtained based on a Green function under the half-space condition in combination with an adaptive cross-approximation algorithm, the layered matrix comprises a normal stiffness H-matrix and a shear stiffness H-matrix, and MPI parallel operation matrix-vector multiplication is adopted. According to the invention, the hierarchical matrix is introduced and the MPI parallel computing framework is fused, so that the simulation period is greatly shortened.

The invention discloses a natural earthquake risk analysis method based on an artificial neural network, and the method comprises the steps: S1, obtaining a target analysis region, and dividing the target analysis region into a plurality of sub-regions; s2, acquiring a historical seismic data set corresponding to the target analysis area and preprocessing the historical seismic data set; s3, performing sub-region marking on the preprocessed data set to obtain a plurality of seismic source sub-regions and non-seismic source sub-regions; s4, acquiring data subsets corresponding to the seismic source sub-region and the non-seismic source sub-region, and inputting the data subsets into an artificial neural network for feature extraction; s5, calculating the similarity between the non-seismic source sub-region and the plurality of seismic source sub-regions; s6, training the convolutional neural network by using the historical seismic data set to obtain a seismic prediction model; and S7, inputting the data subsets of the different regions into the earthquake prediction model for prediction to obtain an earthquake prediction result, and outputting an earthquake risk analysis report according to the earthquake prediction result. According to the method, earthquake risk analysis of multiple areas and potential earthquake areas is realized.

The embodiment of the invention discloses an efficient response spectrum method for soil-structure interaction anti-seismic analysis. The efficient response spectrum method comprises the steps that a finite element model of a to-be-analyzed soil-structure system is obtained; performing modal analysis on the structure model under the rigid foundation, and calculating the effective inherent frequency and modal vector of each order of the soil-structure system; according to the effective inherent frequency and the modal vector of each order, calculating a modal participation coefficient of each effective modal and a cross correlation coefficient between the effective modals; a model bottom response spectrum is obtained according to earthquake risk analysis of a specific site, and for an engineering site without earthquake risk analysis of the specific site, the model bottom response spectrum is obtained through inversion of a ground surface design spectrum through an inversion method; and determining the peak response of the structure according to the bottom response spectrum of the model. According to the embodiment of the invention, soil-structure interaction is considered in the structural seismic analysis response spectrum method, and the execution efficiency is relatively high.

The invention provides a hot dry rock reservoir fracturing induced earthquake management and control system, which belongs to the field of hot dry rock development and supervision and comprises a fracturing construction monitoring subsystem, a microearthquake monitoring subsystem and a traffic light decision subsystem. The fracturing construction monitoring subsystem is used for monitoring fracturing construction data in the fracturing construction process and transmitting main construction parameters to the traffic light decision subsystem; the microseism monitoring subsystem is used for acquiring microseism waveform information, interpreting the microseism waveform information into microseism event data and transmitting the microseism event data to the traffic light decision subsystem; and the traffic light decision subsystem is used for comparing information parameters transmitted by the fracturing construction monitoring subsystem and the micro-earthquake monitoring subsystem with a plurality of set decision discrimination factors, judging and predicting the risk of inducing an earthquake event, carrying out graded early warning prompt on the earthquake risk through an indicator light, guiding the fracturing construction process in real time, and carrying out early warning on the earthquake risk. And the earthquake inducing risk is reduced.

The invention discloses a mine earthquake risk main control factor analysis method based on rock stratum macro-microscopic numerical simulation. The method comprises the following steps: firstly, collecting a rock sample and testing to obtain microscopic rock mechanical parameters; secondly, constructing a standard sample model based on discrete element numerical analysis software, and performing heterogeneity parameter assignment on the standard sample model by utilizing a Weibull function in combination with fractal dimensions and mesoscopic rock mechanical parameters, so as to realize accurate matching of rock mass mesoscopic-macroscopic mechanical properties; the mesoscopic rock mechanical parameters are converted into macroscopic rock mechanical parameters for discrete element analysis according to the conversion relation between the rock quality indexes and the rock strength, and high-fidelity reconstruction of a discrete element macroscopic model is achieved; and subsequently performing an orthogonal test and range analysis to quantify the macroscopic heterogeneous main control factors, thereby realizing priority ranking of each macroscopic heterogeneous main control factor as a key disaster-causing factor. Simulation can be carried out under the condition of considering the rock stratum heterogeneity, the result fits the actual rock stratum condition, and data support is provided for subsequent mine earthquake risk prevention and control treatment on the rock stratum.

The invention provides an early warning, prevention and control method and device for a hydrofracture-induced earthquake risk, and relates to the technical field of unconventional oil and gas development, and the method comprises the steps: collecting geological data of a target block, constructing a three-dimensional geomechanical model, classifying fracture surfaces in the block based on the three-dimensional geomechanical model, and recognizing fracture classification data. Fractured surface parameters are quantified; in the fracturing construction process, construction data and geological response data are collected; performing splitting and dimensionless processing on the crack classification data, the fracture surface parameters, the construction data and the geological response data to obtain sub-risk components, and inputting the sub-risk components into a multi-parameter weighting model based on an induced earthquake risk index system to obtain a comprehensive risk coefficient; determining early warning grading information corresponding to the comprehensive risk coefficient according to a preset early warning grading mechanism; and adopting a matched risk prevention and control strategy according to the early warning grading information in combination with well section features.

The invention provides a federated learning and privacy calculation-based cross-border earthquake risk assessment method, which solves the fundamental contradiction between data sovereignty and privacy security in cross-border data sharing by constructing a federated learning architecture fusing hierarchical desensitization and hybrid encryption. Through the multi-source data cooperative training and CNN-LSTM mixed disaster chain model, the problem that the assessment precision is insufficient due to the fact that a single country model cannot describe a complex cross-border disaster chain is solved; finally, a cross-border disaster scene is constructed, and the defect that a static evaluation tool is disjointed with an actual combat is overcome through a multi-agent dynamic policy simulation system; according to the method, the security collaboration under the condition that the data is not out of the scene is realized, the multi-country collaboration participation rate is improved by 60%, the risk assessment accuracy rate is improved to 92% or above, the policy assessment period is shortened from several months to several hours, a quantifiable scientific basis is provided for cross-border emergency decision making, and the joint prevention and joint control capability of regional earthquake disasters is effectively improved.

The invention provides a mine earthquake master control horizon determination method, which comprises the following steps of: establishing a mine area stratum model, and determining a plurality of key layers which are positioned above a fissure zone in the mine area stratum model and have mine earthquake risks as mine earthquake control layers according to a key layer theory; main control layer analysis is carried out on all the mine earthquake control layers, a step-by-step determination and governance analysis principle is formulated for the mine earthquake control layers, and multi-stage mine earthquake main control layers are determined from all the mine earthquake control layers; and performing logging correction analysis, and dynamically correcting the position of the target rock stratum of the multi-stage mine earthquake main control layer. According to the method, different mine earthquake disaster-causing conditions are analyzed, mine earthquake main control layers under the scene that mine earthquakes generate disaster-causing influence on the ground and under the scene that mine earthquakes generate disaster-causing influence on an underground mining working face are respectively determined, and the target rock layer position of the mine earthquake main control layers is dynamically corrected through logging analysis; and it is guaranteed that the target layer of the mine earthquake main control layer can be subjected to construction treatment.

The invention discloses a broadband seismic oscillation simulation method and system based on probabilistic seismic risk analysis, and relates to the technical field of field seismic oscillation, and the method comprises the steps: carrying out the seismic risk decoupling through employing a Chinese probabilistic seismic risk analysis method, determining a target potential source area corresponding to the maximum contribution degree with probability significance and a potential source magnitude and an epicentral distance of the target potential source area; calculating a fault size parameter of the target potential source area based on the potential source magnitude and a preset scaling rate; calculating fault distribution parameters of the target potential source area based on the fault size parameters and the mixed seismic source model; combining the three-dimensional longitudinal wave velocity model and the shallow structure model to construct a three-dimensional calculation model; and performing deterministic low-frequency simulation and deterministic high-frequency simulation on the three-dimensional calculation model based on a spectral element method and a three-way stochastic finite fault method respectively, and then performing broadband time program sequence synthesis to obtain a broadband seismic oscillation simulation result. The technical problem of low simulation result accuracy in the prior art is relieved.

The invention relates to the technical field of emergency management, and discloses an earthquake emergency cooperative command and dispatch system, which comprises a data sensing module used for collecting and preprocessing an earthquake basic data set and a rescue resource data set, the earthquake basic data set comprising earthquake condition parameter data, geographical environment data and secondary disaster data, and the rescue resource data set comprising earthquake condition parameter data, geographical environment data and secondary disaster data; the rescue resource data set comprises team configuration data, material reserve data and traffic path data; and the cooperative processing module is used for processing the seismic basic data set and the rescue resource data set to obtain emergency response indexes, and grading the emergency response indexes to obtain a rescue priority result. According to the invention, real-time acquisition and integration of multi-source seismic data and rescue resource data are realized through the data sensing module, and the problems of data dispersion and islanding in traditional emergency command are solved; an emergency response index can be dynamically generated based on the earthquake risk and the resource guarantee capability through a rescue priority grading model constructed by the cooperative processing module, and a scientific basis is provided for decision making.

This invention relates to the field of seismic source monitoring and discloses a dual-bubble seismic source monitoring method based on marine seismic detection. The method involves deploying a seismic detector array in a target sea area, recording seismic wave data generated by the dual bubbles, using the frequency data of the seismic waves as the first target monitoring data for seismic source identification, and using the propagation velocity of the seismic waves as the second target monitoring data. The method analyzes the arrival time of the seismic waves at different detectors to locate the seismic source. It also analyzes the amplitude attenuation characteristics and propagation path of the seismic waves during propagation to assess the earthquake magnitude and calculate the probability of earthquake occurrence based on the assessed earthquake risk level. This method improves the accuracy of seismic source data acquisition, enables accurate identification and location of the seismic source, and thus improves the accuracy of earthquake probability prediction.

The application provides a substation steel structure earthquake risk early warning method and device, equipment and medium, and the method comprises the steps of: constructing a foundation soil-substation steel structure model and a half-space site model; based on an indirect boundary element method, simulating the seismic response according to the half-space site model and the foundation soil-substation steel structure model to determine a risk grade early warning table; acquiring a target displacement response of the substation steel structure in real time; and analyzing the target displacement response and the risk grade early warning table to determine the seismic risk grade of the current substation steel structure. The application simulates and calculates the displacement response of the substation steel structure under different seismic risk grades based on the indirect boundary element method, the half-space site model and the foundation soil-substation steel structure model, can automatically meet the infinite boundary condition, reduces the problem dimension, improves the solving accuracy, thereby obtains more accurate seismic response of the substation steel structure, and can accurately monitor the risk grade of the substation steel structure.

The invention discloses a small sample mine earthquake risk identification method based on a physical information convolution-attention neural network, and belongs to the field of mine dynamic disaster prevention and control. According to the method, firstly, a correlation model of deformation localization and mine earthquakes is established, and mine earthquake occurrence conditions are defined from the angle of mechanical instability; secondly, micro-seismic signals are processed through a bilinear time-frequency feature extraction module, and cross-domain feature representation is optimized in combination with an interactive iterative learning strategy; secondly, learning spatial distribution of key physical parameters based on a physical information neural network so as to regularize a stress-strain response mechanism; and fusing the time-frequency features and the physical parameters by using a convolution-attention neural network, realizing mine earthquake risk identification, designing a physical-data mixed loss function, and integrating a feature extraction module and a physical parameter learning module through a collaborative optimization strategy to jointly optimize the network performance. According to the method, the mine earthquake risk can be identified and key physical parameters can be revealed under the small sample condition, and an effective technical path is provided for prediction and early warning of mine disasters.

The invention discloses a hot dry rock reservoir transformation mutual feedback multi-stage dynamic earthquake control method based on comprehensive prediction, and relates to the field of enhanced geothermal system development, and the method comprises the following steps: S1, dividing a limited earthquake magnitude into four stages according to a site earthquake control demand; s2, establishing an induced earthquake real-time monitoring system, and providing a real-time induced earthquake catalog; s3, comprehensively predicting and evaluating an induced earthquake risk; s4, according to the different limited earthquake magnitudes determined in the step S1 and the induced earthquake risk comprehensive analysis provided in the step S3, dynamically adjusting hierarchical management and control early warning conditions; s5, performing dynamic limitation on injection parameters by utilizing the earthquake risk analysis in the step S3; and S6, taking corresponding countermeasures according to different dynamic early warning conditions in the step S4 to realize prospective active earthquake control. And S7, through induced earthquake real-time monitoring in S2, mutual feedback type analysis in S3 and S5, dynamic injection limiting parameters are provided, dynamic early warning conditions are provided for S4 in combination with S3, prospective active earthquake control adjustment measures in S6 are realized, a real-time earthquake risk analysis and dynamic parameter adjustment mutual feedback type multi-stage earthquake control system is formed, and finally the purpose of safe earthquake control is achieved.

The invention discloses a complex terrain seismic oscillation amplification coefficient prediction and correction method and system based on a convolutional neural network model, and belongs to the application of a deep learning method in the field of seismic engineering. The method comprises the following steps: firstly, respectively establishing seismic oscillation databases of isolated terrains and regional complex terrains; training by using a BP neural network to obtain an isolated terrain seismic oscillation amplification coefficient prediction model, and training by using a convolutional neural network to obtain a regional terrain influence coefficient prediction model; and multiplying the isolated terrain prediction coefficient of the to-be-measured site by the regional terrain influence prediction coefficient to obtain an accurately corrected seismic oscillation amplification coefficient. The method overcomes the defect that an existing method neglects the regional terrain coupling effect, effectively improves the prediction precision of the seismic oscillation amplification coefficient under the complex terrain condition, and provides more reliable technical support for engineering aseismic design and seismic risk assessment.

This disclosure presents a method and apparatus for simulating landslide area generation in post-earthquake secondary disasters. One specific implementation of the method includes: acquiring panchromatic and multispectral image sets, and obtaining original images and elevation datasets; fusing the panchromatic image with each multispectral image in the multispectral image set to generate a fused image; identifying landslide areas on the fused image to generate an identification result; in response to the identification result indicating that the post-earthquake risk area includes landslide areas, performing landslide area edge detection based on the original image, elevation dataset, and fused image to generate a first edge coordinate sequence and a second edge coordinate sequence; and performing landslide area simulation processing based on the original image, fused image, first edge coordinate sequence, and second edge coordinate sequence to generate the landslide surface area and landslide coverage area. This implementation can improve the accuracy of the generated landslide surface area and landslide coverage area.

The invention relates to the technical field of anti-seismic safety of power systems and structures, and provides a multi-source data intelligent-driven power transmission line earthquake risk prediction method and system in order to solve the problems that in the prior art, a model is single in applicable object, cannot be dynamically updated and lacks risk closed-loop management. The multi-source data intelligent driving power transmission line earthquake risk prediction method comprises the steps of processing an actual earthquake wave time history by using a continuously updated mixed deep learning model, and predicting a top displacement time history of a power transmission line to serve as a power transmission line dynamic response index; comparing the predicted top displacement time history of the power transmission line with a known structural performance limit value of the power transmission line, judging a structural performance state of the power transmission line and a corresponding risk level of the structural performance state, and converting the predicted top displacement time history into occurrence probabilities of different structural performance states by using a vulnerability curve method; the method has the characteristics of high prediction precision and strong adaptability, and can realize real-time risk early warning.

The invention relates to the technical field of coal mine safety, and provides a deep well roadway surrounding rock blasting measure optimization design method and system. According to the determined residual mine earthquake energy of the migration of the key layer of each layer covering the target working face to the roadway supporting system and the theoretical impact resistance of the roadway supporting system of the target working face, determining a threat factor of the migration of the key layer of each layer to the roadway supporting system so as to identify a top plate blasting layer of the target working face; and then, a construction path and blasting parameters of target working face roof blasting are generated based on the recognized roof blasting position, and threat factors of migration of all key layers covering the target working face to a roadway supporting system are cyclically updated. Therefore, the impact resistance of a roadway support system is constrained, the'disaster-inducing-disaster-bearing 'matching of the blasting horizon is realized, the quantitative screening of the target blasting horizon is realized, the identification efficiency and accuracy are improved, and the rock burst and mine earthquake risks caused by misjudgment or missed judgment are reduced.

The present invention discloses a GNSS aseismic slip signal extraction method based on template matching and linear rate correction, which relates to the field of geodetic surveying and geophysical monitoring technology, including: decomposing the mixed noise in the GNSS / InSAR time series and extracting the denoised residual signal; using masking technology to separate transient and non-transient signal segments, dynamically correcting the linear trend error based on the variance-weighted average rate of the non-transient data before and after the transient segment, and achieving millimeter-level amplitude extraction of transient signals through iterative optimization; constructing an exponential decay and cosine-type transient signal template library, calculating the full sequence cross-correlation by sliding the template along the residual sequence, and accurately identifying the signal amplitude, duration, and spatial distribution. The present invention breaks through the bottleneck of linear rate interference and multi-signal superposition technology, provides high-precision data support for fault slip behavior, aseismic slip identification, and earthquake risk assessment, and significantly enhances the engineering application value of GNSS / InSAR technology in geophysical research and disaster warning.

The invention discloses a landslide seismic signal precursor identification and early warning method based on machine learning. The method comprises the following steps: acquiring original seismic signal waveform data to generate seismic signal waveform data; judging a potential seismic phase arrival time point based on the seismic signal waveform, and generating a preliminary seismic phase arrival time sequence; acquiring position coordinate estimation of the landslide event based on the initial seismic phase arrival time sequence; original seismic oscillation signal waveform data are screened, landslide seismic scale classification is carried out, and seismic risk levels are output; if the earthquake risk level is a high level, original earthquake signal waveform data, geological displacement and rainfall data are extracted, the earthquake risk level and position coordinate estimation of the landslide event are integrated, and a landslide early warning signal is obtained and output. According to the technical scheme, signal purity can be improved, noise interference can be reduced, manual subjective errors can be reduced, accuracy and real-time performance of landslide position estimation can be improved, rapid risk assessment can be realized, reliability and response speed of landslide early warning can be improved, and effective support can be provided for disaster prevention and control.

The invention belongs to the technical field of potential earthquake risk prediction analysis, and discloses an earthquake risk analysis method considering historical earthquake energy release, which comprises the following steps: constructing a strain energy three-dimensional grid of a research area; calculating historical earthquake energy release and a release range; calculating accumulated strain energy of each grid; calculating residual strain energy and identifying a potential earthquake generation area; and earthquake risk analysis. According to the method, an original analysis method of a numerical simulation result is broken through, energy release of historical earthquakes and energy accumulation between earthquakes are considered from a new perspective and method, and a new thought for carrying out earthquake risk analysis based on the numerical simulation result is provided.