2250 results about "Seismic wave" patented technology

The invention belongs to the technical field of earthquake disaster scene recognition, and discloses an earthquake disaster scene recognition method based on deep learning. The method comprises the following specific steps: S1, data acquisition and preprocessing; S1.1, multi-source heterogeneous data acquisition and establishment of a comprehensive database containing seismic waveform data, surface deformation data, building structure data, geographic information data and historical disaster record data; through fusion of a 3D convolutional network, a graph attention mechanism, a space-time LSTM and an adaptive cross-modal attention fusion technology, combined modeling of a seismic waveform space-time evolution law, an earth surface deformation space distribution characteristic, a building group topology vulnerability and disaster chain time sequence association is realized, the characterization capability of a complex nonlinear disaster mode is effectively improved, and the method has the advantages of high adaptability and high reliability. And disaster assessment response time is shortened to a sub-second level through mixed precision quantification and edge computing deployment, and high recognition accuracy is still kept in a scene with strong noise and data missing in combination with a multi-task classifier and a physical constraint verification mechanism.

The invention discloses an Internet of Things multichannel earthquake early warning emergency linkage system, belongs to the technical field of earthquake early warning, and aims to solve the problems of insufficient real-time performance, reliability, scene coverage and safety in the prior art. The sensing layer collects data cooperatively through various sensors, eliminates environmental interference and ensures high-precision seismic wave detection, the edge calculation layer filters noise in real time by adopting an advanced algorithm, and confirms seismic events through multi-dimensional comparison, so that the local processing efficiency is remarkably improved, the cloud load is greatly reduced, a cloud platform fuses multi-source data, and the seismic detection efficiency is improved. A machine learning model is combined to dynamically optimize an early warning threshold value, the accuracy of earthquake type classification and intensity prediction is improved, full-link optimization from data acquisition to intelligent decision making is realized, a multi-channel distribution module is designed, instructions are transmitted according to priority levels, and urban and rural full-scene coverage is ensured through multiple communication technologies.

According to the goaf detection method based on transient electromagnetic and seismic wave field joint inversion, data acquisition and joint inversion are carried out on the goaf through the combination of the transient electromagnetic detection system and the reflection seismic detection system, the complementary advantages of the two detection methods are played, the bottlenecks of a single method in the aspects of resolution and signal-to-noise ratio are broken through, and the goaf detection method based on transient electromagnetic and seismic wave field joint inversion is realized. Fine characterization of the structure, the physical property and the stability of the goaf is realized; a machine learning classification algorithm is introduced to analyze a goaf multi-attribute feature data set, and intelligent discrimination of the type, scale and stability of the goaf under complex geological conditions is realized; establishing a quantitative response relationship between goaf physical property parameters and goaf electrical and elastic difference characteristic parameters, constructing a goaf transient electromagnetic and seismic wave field joint forward modeling numerical model, and constructing an electromagnetic-seismic joint inversion objective function; and calculating and solving to obtain goaf resistivity, seismic wave velocity three-dimensional distribution and uncertainty quantitative evaluation results, and reducing blind areas of goaf judgment.

The invention discloses a shield tunnel active and passive source combined geological detection method and system. The method comprises the following steps: acquiring an active source seismic wave reflection signal and a passive source acoustic wave reflection signal; according to the active source seismic wave reflection signal, obtaining an active source geological detection imaging result by adopting a longitudinal and transverse wave combined imaging principle; according to the passive source sound wave reflection signal, a frequency dispersion extraction-shear wave velocity inversion method fusing spatial autocorrelation and a half-wavelength model is adopted to obtain a passive source geological exploration imaging result; and taking an active source geological detection imaging result as a main result, taking a passive source geological detection imaging result as an auxiliary result, and combining adaptive adjustment coefficients between the two results to obtain an unfavorable geological risk level of the to-be-detected area. Shield tunneling vibration noise with high energy and wide frequency band is introduced as a passive detection source, the detection depth and resolution are improved, and support is provided for accurate geological imaging.

The invention discloses a tunnel deep-buried drainage ditch rapid blasting excavation method based on vertical drilling, which comprises the following steps: step 1, detecting the geology in front of a tunnel by using vertical drilling coring, geological radar and TSP seismic wave technology, and constructing a three-dimensional model; 2, generating an asymmetric hole net layout based on a geological model and AI, and setting a drilling-free vibration isolation belt; the design of dense inside and sparse outside is adopted, and vibration propagation is blocked; thirdly, a three-stage air spacer is arranged at the bottom of the blast hole, segmented charging is implemented, the explosive energy release time is prolonged, and the single-segment explosive quantity peak value is reduced; fourthly, an electronic detonator is adopted for millisecond detonation, and peak vibration is weakened through the waveform superposition offset effect; 5, arranging fiber grating sensors in the tunnel, collecting data in real time and transmitting the data to the cloud AI platform; dynamically adjusting parameters based on the monitoring data; and 6, evaluating a blasting effect through a three-dimensional laser scanner, generating an evaluation report in combination with data, updating a BIM model database, and continuously optimizing an AI algorithm.

The invention discloses a vibration table test device and a test method for seismic dynamic response of a fault-crossing mountain tunnel. The test device comprises an earthquake simulation vibration table, a laminated shear model box, surrounding rock, a fault fracture zone, a tunnel model and a monitoring and measuring system. Wherein the earthquake simulation vibration table inputs earthquake waves and provides earthquake power; the bottom of the laminated shear model box is fixed on the earthquake simulation vibration table, and the laminated shear model box is filled with surrounding rocks and fault fracture zones; the fault dip angle is 90 degrees, and left and right surrounding rock elevations are inconsistent; the tunnel model comprises a non-shock-absorption layer and a shock-absorption layer which are buried in the surrounding rock in the model box in parallel and perpendicularly intersect with a fault fracture zone. The monitoring and measuring system is used for measuring tunnel acceleration and strain, surrounding rock acceleration, fault acceleration and the like in the seismic oscillation process. The test device can simulate the dynamic response process of the fault-crossing mountain tunnel under the action of an earthquake, and time evolution and spatial distribution characteristics of tunnel earthquake response are determined.

The invention provides a tunnel construction structure health on-line monitoring method and system, and the method comprises the steps: obtaining stress data, crack images and seismic wave signals of tunnel construction, and carrying out the preprocessing; obtaining and constructing stress-crack joint representation mapping, generating a first joint feature vector, and predicting a lining health state of a future # imgabs0 # time step; generating a second joint feature vector, and determining a stratum stress field of the future # imgabs1 # time step according to the second joint feature vector; constructing a tunnel lining damage probability model according to the stress data and the crack image, and determining an overall construction risk score; and dividing the construction risks into a plurality of grades. According to the method, data multi-modal fusion, structure-stratum joint modeling and AI enhanced prediction and early warning are achieved, the defects in the prior art are effectively overcome, the method can be widely applied to engineering scenes such as tunnel construction, subway construction and underground space development, and the construction safety and the structure health monitoring capacity are remarkably improved.

The invention discloses a seismic data constrained direct current method three-dimensional inversion method, which relates to the field of geophysical exploration and comprises the steps of processing seismic data and performing inversion processing on resistivity data. The seismic wave layer velocity information is used for constraining high-density electrical method inversion, so that a supplement effect to a certain degree can be achieved, three-dimensional seismic image information can be used for supplementing the resolution ratio of resistivity inversion, the boundary of an underground electrical anomalous body is reflected, and meanwhile, through the comprehensive geological-geophysical information, the electrical anomalous body can be accurately determined. And boundary features of the anomalous body can be further depicted. Seismic data constraints are applied to three-dimensional resistivity inversion, numerical simulation and inversion processing are performed on electrical method data under rugged topography according to finite volume method numerical simulation and a Gaussian-Newton inversion method, and meanwhile, seismic anisotropic velocity tensor constraints are introduced to perform inversion, so that the problem of multiplicity of solutions of inversion of a single method is reduced, and the inversion accuracy is improved. A more accurate three-dimensional underground electrical structure is obtained, and the resolution of inversion to a longitudinal boundary is improved.

The invention discloses a road protection multi-scene coupling simulation method and system based on digital twinning, and relates to the field of electric digital data processing, and the method comprises the steps: collecting dynamic response data (strain, acceleration and displacement) of a traffic protection facility through multiple sensors, and building a scene feature library containing vehicle collision, wind load and seismic waves; and projecting response data to a unified time axis, identifying a multi-scene overlapping interval, and determining an action sequence and duration. Primary and secondary scenes are judged according to scene action parameters, and mechanical correction values and standard response parameters are extracted. And establishing a digital twinborn model for coupling simulation to obtain a stress distribution condition, evaluating a structural damage level and generating a safety performance report. By implementing the method, the deviation between the mechanical property simulation result of the protection facility and the actual working condition can be reduced.

The invention relates to the technical field of building information, and discloses an ancient building anti-seismic performance analysis and evaluation system based on BIM modeling, and the system comprises a building parameter obtaining module which is used for dynamically collecting component material attributes, structure connection states and historical damage parameters, recognizing structure weak links, and triggering a collaborative evaluation instruction; the modal feature analysis module and the seismic response simulation module are used for respectively extracting vibration modal feature parameters and seismic wave energy distribution parameters to obtain modal feature integrity indexes and dynamic stability evaluation values; the multi-source fusion judgment module synthesizes the indexes to generate a structure reinforcing or component repairing signal; the optimization parameter generation module is matched with the anti-seismic optimization strategy and generates structure reinforcement and node connection repair parameters; the system further comprises a damage coupling analysis module and a model iteration updating module, and monitoring of historical damage evolution and closed-loop updating of the BIM model are achieved. According to the system, precise evaluation and dynamic optimization of the anti-seismic performance of the historic building are realized.

The invention discloses a BIM-based high-speed rail overhead line system elastic sling and electric connection prefabrication processing method, and relates to the field of elastic sling processing, and the method comprises the steps: building a knowledge base, and building an initial elastic sling BIM model of a target project through parametric modeling; establishing an initial finite element analysis model of the target project through grid division and material attribute mapping; calculating the internal force and deformation of the elastic sling under the action of the static load by adopting an incremental iteration method; carrying out dynamic time-history analysis by adopting a direct integration method to obtain time-history curves of the elastic sling under different seismic waves; according to static and dynamic analysis results, stress-strain response of the elastic sling is extracted, and the initial elastic sling BIM model is optimized by adopting a topological optimization method with the minimum strain of the elastic sling as the target and the stress constraint of the elastic sling as the condition; and updating the finite element analysis model by using the optimized elastic sling BIM model. According to the method, the parameterized design degree of the elastic sling is improved.

The present application relates to the technical field of seismic data imaging and migration in geophysical prospecting for petroleum. Provided are a multi-wave migration imaging method and apparatus based on an iterative deconvolutional imaging condition. The method comprises: acquiring a seismic wave forward wave field and a seismic wave reverse wave field; using a deconvolutional imaging condition to perform multi-wave imaging on the seismic wave forward wave field and the seismic wave reverse wave field so as to obtain an initial imaging result; taking the seismic wave forward wave field, the seismic wave reverse wave field and the initial imaging result as inputs, using an iterative deconvolutional imaging method to perform multi-wave imaging, so as to obtain an iterative deconvolutional multi-wave imaging result; during the multi-wave imaging, determining an objective function value of the deconvolutional imaging; if the objective function value does not meet a preset condition, iterating the imaging result until the objective function value of the deconvolutional imaging meets the preset condition, and generating a final iterative deconvolutional multi-wave imaging result according to an imaging result obtained after iteration.

The invention relates to the technical field of earthquake monitoring, in particular to a geological disaster early warning device based on earthquake waveform recognition, which comprises an earthquake data receiving module, an earthquake wave type analysis module, a disaster mode recognition module, an early warning signal construction module, a risk judgment module and an early warning information issuing module. According to the invention, through identifying and analyzing the seismic waveform data, the characteristics of the earthquake and the type of the caused disaster, such as landslide, rock collapse, debris flow, ground fissure, surface collapse and the like, are rapidly judged, and through comprehensively evaluating the emergency and the influence range of the earthquake event, the targeted early warning information is generated and issued in time. The geological disaster response speed and efficiency can be remarkably improved, earthquake monitoring is not limited to recording of earthquake activities, disaster risks can be evaluated in real time, more accurate disaster prediction and early warning can be provided, for areas where geological disasters frequently occur, the early warning accuracy and timeliness can be remarkably improved, casualties and property losses can be reduced, and the economic benefit is improved. And the method has extremely high practical value and social significance.

The invention provides a single-station earthquake positioning system and method combining multi-source features and collaborative loss, and relates to the technical field of earthquake positioning, and the single-station earthquake positioning system comprises a data preprocessing module, a model training module, and a single seismic source positioning model. Inputting three-component waveform data into a data preprocessing module by querying seismic directory information, inputting the preprocessed seismic waveform data into a single seismic source positioning model, training each network module to obtain a single-station seismic positioning system, and outputting a time sequence feature tensor, a time frequency feature tensor and a station information feature tensor; the trained seismic positioning system is used for predicting the seismic source depth and the epicentral distance, seismic waveform data collected by the station are input into the data preprocessing module to obtain standardized waveform data, the standardized waveform data are input into the seismic source positioning module, and prediction results of the seismic source depth and the epicentral distance of the station are output.

The invention discloses a data center seismic isolation performance detection method based on AI intelligence, and particularly relates to the technical field of seismic isolation performance detection. Earthquake vibration characteristic data are collected in real time on a data center building and equipment, earthquake input characteristics are extracted in combination with a historical earthquake wave database, a seismic isolation performance prediction model is constructed and trained, a foundation shear wave velocity gradient abnormal value and a seismic isolation layer dynamic displacement response deviation ratio are further extracted, a deviation index is comprehensively calculated, and a seismic isolation performance prediction model is constructed and trained. And classification processing is carried out according to the deviation level, especially under the condition of a middle deviation level, foundation physical parameters are dynamically updated, and the model is optimized, so that the accuracy of the prediction model and the self-adaptive capability of the system are remarkably improved, and the shock isolation safety and the continuous operation capability of the data center in a strong shock environment are effectively guaranteed.

The invention provides a rainfall and earthquake coupled slope simulation method and system. The method comprises the following steps: constructing a coupling numerical model through multi-physics field data of a slope; the dynamic coupling effect of rainfall and earthquake is simulated by initializing a seepage field and loading earthquake power; the stability of the simulation result is comprehensively evaluated through iteration of a strength reduction method, and whole-process coupling from seepage to dynamic response of the slope is achieved. SeismoSignal is used for processing seismic waves, and the problem that the value of kinematics parameters is not zero when the seismic action is finished is avoided; the allowable maximum negative pore water pressure boundary is assigned to the slope surface of the side slope, the actual steady-state seepage field of the side slope is restored, and the seepage field in the side slope under different rainfall conditions is accurately calculated; by adopting an unsaturated soil dynamic seepage model for a seepage field, Rayleigh damping is introduced and an earthquake load is applied, so that cross-time scale coupling is realized. The method is simple and convenient to operate, high in calculation efficiency and accurate in calculation result, and has practical significance and value in research of the problem in the rock-soil field.

The invention relates to the technical field, in particular to a geothermal resource favorable area prediction method and system, and the method comprises the following steps: collecting electromagnetic and seismic wave data of a plurality of positions of a target area through a sensor based on regional position data, carrying out the correlation of the data and position information, and generating a geological exploration data set through the combination of data cleaning and standardization. According to the method, electromagnetic and seismic wave data of multiple positions are collected and associated with geographic position information, the practicability and reliability of the data are improved, the data quality is optimized in combination with data filtering, the accuracy of stratum structure prediction is improved, a three-dimensional geologic model is constructed and combined with actual drilling data, and the practicability and accuracy of the model are verified; the method improves the accuracy and credibility of model prediction, optimizes the precision and practicability of resource prediction by analyzing the correlation between a geologic structure and geothermal resources, provides scientific decision support for geothermal development, and supports the effective utilization of renewable energy sources and the realization of a sustainable development target.

The invention relates to the technical field of petroleum and natural gas engineering, and discloses an oil and gas reservoir optimized mining method based on multi-modal data, which comprises the following steps: constructing an oil and gas reservoir multi-modal data acquisition system, seismic wave field data, logging interpretation data, production dynamic data, micro-seismic monitoring data, underground temperature and pressure time sequence data and shaft structure parameter data are obtained through the acquisition system; and performing space-time alignment processing on the acquired multi-modal data, establishing a unified geological coordinate system and a time reference, and eliminating data isomerism caused by different acquisition frequencies and spatial resolutions. A six-dimensional heterogeneous data acquisition system covering a seismic wave field, well logging interpretation, production dynamics, micro-seismic monitoring, an underground temperature and pressure time sequence and shaft structure parameters is constructed, so that the depiction precision of a reservoir porosity field, a permeability field, a saturation field and a pressure field is essentially improved.

The embodiment of the invention provides a seismic wave detection method and system, electronic equipment and a storage medium, and belongs to the field of seismic wave engineering detection. The method comprises the steps that seismic sources and detectors are arranged in advance according to actual working conditions, seismic waves are excited at the positions of the seismic sources, and seismic wave data are collected through the detectors; based on seismic wave data, solving a time fractional order viscoelastic acoustic wave equation by using a short memory fast algorithm so as to simulate the propagation behavior of seismic waves in a real stratum medium; and performing Bayesian full waveform inversion and reverse time migration imaging based on the seismic wave data to obtain a stratum structure and stratum characteristics. The memory effect of a time fractional order viscoacoustic wave equation is reasonably simplified through a short memory fast algorithm, so that the storage requirement for wave field historical data is reduced, efficient numerical solution is achieved, on the premise that precision is guaranteed, memory occupation is greatly reduced, and the cost is reduced. And the time fractional order viscoelastic acoustic wave equation has higher operability and calculation efficiency in engineering application.

A method for monitoring a rock burst in ultra-thin coal seams, which method belongs to the technical field of fully mechanized coal mining in ultra-thin coal seams. The method comprises: respectively recording the acquired propagation times and propagation velocities of attenuated seismic waves from artificial seismic sources and the acquired propagation time and propagation velocity of a rock burst, and comparing different seismic wave signals and real-time rock burst signals passing through a mining area; converting the different seismic wave signals and the real-time rock burst signals into digital signals, and determining via comparison whether the digital signals have waveforms during the rock burst; when the digital signals have waveforms during the rock burst, identifying the waveforms of micro-seismic events, and determining the energy intensity of the rock burst; locating rock burst sources, and obtaining an intersection area of the rock burst sources, so as to obtain a seismic source position after a delineated range is reduced; and on the basis of acquired real-time pressure data in underground rock or coal seams, obtaining the positions of the maximum pressure and maximum pressure changes of a seismic source, and the numerical values thereof by means of analyzing a real-time pressure value and a real-time strain change rate. By means of the method, potential hazardous areas can be monitored. The present invention further relates to a system for monitoring a rock burst in ultra-thin coal seams.

The invention relates to the technical field of geophysical exploration, in particular to an exploration surveying and mapping method based on remote sensing and a surveying and mapping instrument thereof. The exploration surveying and mapping method based on remote sensing comprises the following steps: step 1, multi-platform collaborative data dynamic acquisition; step 2, multi-modal data fusion and feature enhancement: vegetation noise filtering is performed on the laser radar point cloud data, and a surface terrain model under vegetation coverage is reconstructed; seismic wave speed data and ground penetrating radar dielectric constant data are combined to construct an underground medium physical property combined distribution model; associating the reflectivity characteristics of the multispectral image with the underground physical property parameters, and identifying a geological abnormal region; and step 3, hidden geologic body dynamic modeling and risk assessment. By means of the method, real-time monitoring and risk assessment of the complex geologic body can be achieved, and the geological disaster prediction and prevention and control capacity is greatly improved.

The invention discloses a semi-supervised seismic wave impedance inversion method and system based on Swin Transform iterative gradient correction, and belongs to the technical field of earthquakes in geophysical exploration. According to the method, the impedance gradient is iteratively corrected in the model space through the deep neural network, and complex nonlinear prior information is captured; and each anisotropic structure direction regularization item is established, and constraint is carried out along the direction of the stratum structure, so that the space consistency of the prediction result is ensured. Meanwhile, the USTNet network designed by the invention combines the advantages of the local feature capture capability of the convolutional neural network and the global modeling capability of Transform, and reduces the non-uniqueness of solutions. The network is used for inverting synthetic data and actual data, and the effectiveness of the method is verified.

The invention discloses a deep learning seismic source mechanism inversion system and method based on physical driving. The system is characterized in that a seismic wave acquisition module is used for acquiring an actually measured seismic wave waveform; the data preprocessing module preprocesses the data; the data feature extractor is used for extracting seismic waveform data features; the physical constraint optimizer is used for constructing a comprehensive loss item function; the model training module is used for training the seismic source mechanism prediction model; the seismic source mechanism prediction module is used for result inversion; the method comprises the following steps: simulating and generating a synthetic seismic waveform, and extracting spectrum features; preprocessing the data; extracting multi-level enhanced features from actually measured and synthesized seismic waveforms by using a data feature extractor; introducing the fault physical mechanism, the stress tensor conservation and the seismic source tensor constraint into a loss function to form a comprehensive loss item, and constructing a seismic source mechanism prediction model; and performing inversion of an actual seismic event by using the seismic source mechanism prediction model. According to the system and the method, efficient and accurate seismic source mechanism inversion can be carried out on unknown seismic events.

The invention provides a three-dimensional seismic exploration analysis method, which comprises the following steps: S1, exploration design: determining a three-dimensional seismic exploration range and a target horizon, and designing an observation system; s2, acquiring data, including staking out in survey, exciting seismic waves and receiving seismic signals; s3, data processing: preprocessing the collected seismic data, removing noise and interference signals, and improving the signal-to-noise ratio, resolution and precision of the seismic data; and S4, geological interpretation: according to the processed seismic data, interpreting the geological structure and coal seam distribution of the coal mine area in combination with geological and geophysical prospecting data. According to the method, richer and more accurate underground geological information can be provided, the detection precision and reliability of coal mine underground geological structures and coal seam distribution are improved, noise and interference signals can be effectively removed, the signal-to-noise ratio and resolution of seismic data are improved, and the method is suitable for exploration and development of coal mines of different scales.

The invention discloses an urban karst water guide channel detection system and method based on earthquake Krauklis waves. The urban karst water guide channel detection system comprises a piezoelectric type vibroseis, an array type earthquake receiving system and a multi-wave seismograph. The piezoelectric vibroseis is used for exciting seismic waves; and the multi-wave seismograph is used for acquiring seismic data acquired by each seismic acceleration sensor in the array type seismic receiving system. The structure can ensure the precision of seismic wave data acquisition each time; separating and extracting Krauklis waves from the acquired seismic wave data by adopting an energy-frequency double-selection method; then, based on the frequency dispersion characteristic of Krauklis waves, a mapping model of crack opening and wave field response is established; and finally, determining the opening degree of the urban karst water guide channel according to the mapping model, and performing inversion to obtain the dynamic flow of the urban karst water guide channel. Through treatment in the mode, the opening degree and the dynamic flow of the urban karst water guiding channel can be monitored, and finally prevention and control over hidden geological disasters are effectively improved.

The invention discloses a three-dimensional crustal stress field visualization construction method under a complex geological structure condition, and relates to the technical field of crustal stress field analysis. Comprising the following steps: in a to-be-analyzed area, obtaining characteristic data such as density and Poisson ratio of a surface rock-soil layer, a sedimentary layer, a parent material layer and a bedrock layer through well drilling; applying seismic waves, acquiring longitudinal wave and transverse wave speeds of each rock-soil layer by using a geophone, and calculating a shear modulus and a bulk modulus; and establishing a finite element model to analyze the strain tensor under the load, and calculating the stress tensor in combination with the modulus. Calculating pore water pressure, and correcting the stress tensor to obtain effective stress. Fault feature information is obtained through a geological report, and the stress tensor is further corrected to obtain accurate and effective stress. And constructing a three-dimensional geologic model and dividing grids, mapping accurate and effective stress to each grid unit, and completing visual construction of the crustal stress field by utilizing visual software. Safety and economic benefits are effectively improved, and risks caused by geological factors are reduced.

The invention discloses an earthquake monitoring linkage triggering device, and the device comprises an earthquake intensity instrument which is used for collecting an earthquake signal and outputting earthquake intensity; the sensor is used for collecting seismic activity data; the data acquisition host is used for processing the seismic intensity and the seismic activity data and transmitting the seismic intensity and the seismic activity data to the upper computer; and the upper computer is used for receiving, analyzing and displaying the seismic data. According to the invention, high-performance modular hardware is utilized, efficient and flexible software is combined to complete various testing work, signals of acquisition equipment are displayed and stored through the upper computer, seismic wave acquisition information is fused, data analysis and judgment are carried out, and earthquake monitoring can be comprehensively and automatically realized.

According to the micro-seismic source intelligent positioning method and the model training method and system, physical laws such as a seismic wave equation are integrated, physical loss and data loss are comprehensively considered, the adaptability of the model to a complex geological environment is improved, micro-seismic source positioning challenges in the complex geological environment can be effectively dealt with, and the positioning accuracy of the micro-seismic source in the complex geological environment is improved. Noise immunity and positioning precision are improved, and more reliable technical support is provided for safety monitoring of underground engineering.

The invention relates to the technical field of roadway surrounding rock danger identification, and discloses a roadway surrounding rock danger identification model construction method, which comprises the steps of collecting multi-modal data, and generating preprocessed data through synchronous calibration and denoising; extracting a seismic wave frequency domain and image texture features, and generating a multi-modal feature matrix; in combination with a geological prior clustering mining abnormal mode, generating a labeled sample data set; generating a danger identification model based on a transfer learning and feature fusion training network; and the edge deployment model performs real-time reasoning, and generates an early warning result through an adaptive algorithm. According to the method, the frequency domain features of the seismic fluctuation signals and the depth texture features of the surrounding rock images are fused, the multi-modal feature matrix is constructed, abnormal mode mining is carried out in combination with geological prior knowledge, and early weak abnormal signals such as hidden fault slippage or asymmetric microfracture extension which are difficult to find by a single monitoring means can be effectively recognized.

The invention relates to the technical field of seismic exploration, and discloses a Beidou short message communication node type seismograph based on efficient edge data compression, and the seismograph comprises a main control module which is responsible for controlling other modules and cooperating with the other modules to achieve the functions of the other modules; the vibration acquisition module is responsible for acquiring seismic data; the data storage module is used for storing seismic data and configuration parameters during acquisition; and the data compression module is used for compressing the seismic data before the seismic data is transmitted to the satellite. The Beidou short message communication module is used for transmitting the compressed seismic data to a satellite through a Beidou short message; and the power supply module is used for supplying power to other modules. According to the invention, Beidou short message communication and edge data compression are combined, so that the seismograph can realize high-sampling-rate seismic waveform data quasi-real-time transmission in areas without coverage of wireless communication networks such as Wifi and 4G, and therefore, the seismograph can be applied to more complex layout environments and meet the timeliness requirements of seismic monitoring and analysis.