336 results about "Microseism" patented technology

The invention relates to the technical field of geophysical exploration, and particularly discloses a tunnel surrounding rock stability automatic monitoring and early warning method and system. The method comprises the steps that surrounding rock microseismic signals, convergence displacement and osmotic pressure data are collected through a space-time synchronization array to generate a multi-source fusion data set; based on a dynamic constitutive model separation frequency dispersion effect, extracting correlation characteristics of a microseismic event rate and a displacement rate; generating an instability energy density index; dynamically switching impact or creep damage criteria according to the deformation behavior of the surrounding rock; inputting the indexes into corresponding criteria to generate a damage state result; and if the result exceeds the threshold value, verifying the spatial focusing property of the micro-seismic event cluster, and outputting an early warning instruction when the focusing degree exceeds the critical value. Through multi-source fusion and a dynamic criterion mechanism, the accuracy of tunnel surrounding rock instability early warning is remarkably improved.

The invention discloses a self-adaptive grouting control plugging method based on mining-induced fracture real-time monitoring, and relates to the technical field of mine safety engineering and hydrogeology. Through cooperative work of the grouting mechanism, the data monitoring system, the data collecting and processing module and the self-adaptive control module, automation and intellectualization of grouting protection can be achieved, and through introduction of the fracture roughness coefficient and the time-dependent viscosity, rough fracture flow resistance and grout rheology and time-varying characteristics are quantified, and the grout diffusion radius calculation error is reduced. The data weight is dynamically adjusted through a micro-seismic travel time residual error and sound wave velocity field joint inversion algorithm in combination with a weighted robust LM algorithm, and accurate fracture positioning is achieved. And a PID gain compensation and saturation function mechanism is adopted, so that self-adaptive safe and efficient grouting is realized. The fracture dynamic state is monitored in real time through the multi-source data fusion technology, grouting parameters are dynamically optimized in combination with an intelligent algorithm, complex geological interference is effectively restrained, slurry waste is reduced, and efficient and accurate plugging of mining-induced fractures is achieved.

The invention relates to the technical field of coal mine water disaster prevention and control, and particularly discloses a hidden structure detection system for mine water disaster intelligent monitoring, early warning and prevention, which is used for solving the problems of low mine hidden structure detection precision, mine water disaster early warning lag and large seismic wave propagation path simulation error. Comprising a multi-source data comprehensive detection module, a real-time imaging module, a micro-seismic multi-scale intelligent analysis module, a seismic wave signal identification module, a regional difference analysis module and an intelligent data processing module. According to the invention, through fusion of multi-source data, real-time imaging, micro-seismic analysis, seismic wave identification and intelligent data processing technologies, precise detection of a mine hidden structure, high-precision prediction of mine earthquakes and water disasters and real-time risk early warning are realized, and timeliness and accuracy of mine water disaster prevention and control are improved.

The invention discloses a rock burst global monitoring and dynamic and static far and near field cooperative early warning method and system, and the early warning method comprises the steps: determining a stope space key monitoring region and a stress wave type based on a dynamic load stress wave far field generation and propagation mechanism, delineating a working face surrounding rock high-stress region, and analyzing the structural characteristics of a rock stratum. Arranging a micro-seismic sensor in a far-field key area, and obtaining parameters such as seismic source fracture size, energy and magnitude through waveform inversion; an acoustoelectric system is arranged in a near-field high-stress area, coal rock fracture characteristics are dynamically monitored, and the static load energy storage state of surrounding rock is quantitatively analyzed. And in combination with a stress wave propagation attenuation coefficient, a far and near field fusion early warning criterion under the action of dynamic and static energy superposition is established, and advanced accurate early warning of the rock burst is realized through collaborative analysis of multi-source monitoring data. The disaster-pregnant space global monitoring technology fusing earthquake, sound and electricity is provided, the chain evolution disaster-causing process of dynamic load generation, cross-space propagation and working face surrounding rock damage is considered, and the accuracy of rock burst early warning can be remarkably improved.

The invention discloses a coal and rock mass fracture seismic source and stress field joint inversion method and system, and the method comprises the following steps: arranging a multi-channel sonic sensor in a coal and rock mass, and collecting original acoustic emission / microseismic signal data; the head wave arrival time / amplitude of the filtered effective waveform data is automatically picked up through an improved AIC (Akaike Information Code), quantitative evaluation is carried out on the quality of a picked-up result, and high-precision positioning is carried out on waveform signals with a high signal-to-noise ratio and a low signal-to-noise ratio; constructing a tension fracture seismic source model based on a displacement discontinuous tensor, obtaining a moment tensor component of a fracture event, and calculating to obtain a spatial orientation, a tension-shear attribute, a deviation angle alpha, energy release and a moment magnitude of the fracture; establishing a stress field inversion model of the tension-shear fracture seismic source, and realizing the inversion of the stress direction and size of the tension-shear fracture seismic source; and a slip direction included angle minimization objective function is established for iteration until convergence conditions are met, and joint iteration inversion of the fracture and the stress field is realized.

The invention discloses a dynamic short-term and temporary intelligent forecasting system for mine time-delay rockburst, and belongs to the field of short-term and temporary forecasting of rockburst disasters. The system comprises a deep well three-dimensional micro-seismic field global sensing module, a micro-seismic characteristic parameter extraction module, a rockburst catastrophe evolution data set construction module, a data preprocessing module, a deep learning prediction module, an interpretability analysis module and a dynamic short-term and temporary intelligent forecasting module. A dynamic tracking type micro-seismic sensing network is constructed through a three-level annular nested layout strategy, micro-seismic event data are collected in real time, spatial-temporal characteristic parameters are extracted, a rockburst time sequence data set is constructed in combination with a sliding time window method, and the occurrence probability and intensity level of rockburst are predicted. The system adopts a grey wolf-simulated annealing hybrid algorithm to optimize model parameters, and improves the credibility of a prediction result through SHAP value analysis. The system can realize dynamic short-term and temporary early warning of rockburst disasters, and provides scientific decision support for mine safety management.

The invention provides an ionic type rare earth ore bed rock crack detection method and system, and the method comprises the steps: laying an active seismic source at a preset position of a target detection region, and enabling the active seismic source to emit an elastic wave with a preset frequency and a preset amplitude; a micro-seismic sensor network arranged in a target detection area collects sound wave signals which are emitted by the active seismic source and are scattered and polarized by the crack; extracting a plurality of crack characteristic parameters related to the bedrock crack from the bedrock crack microseismic sound wave signal, and performing preliminary analysis to obtain a possible crack region and preliminary key parameter information of the crack; based on the multiple fracture characteristic parameters, a multi-parameter joint inversion method is adopted to construct a fracture model containing fracture geometric parameters and physical parameters, and regularization optimization is carried out on the fracture model; and finally, based on the optimized crack model, carrying out inversion to obtain key parameters of high-precision spatial positions and distribution of the cracks. On the basis that the ore body is not damaged, the bedrock crack detection precision can be improved.

The invention relates to the technical field of safety management, in particular to a mine safety production risk prevention and control method based on multi-source data fusion, and the method comprises the following steps: constructing a coupling parameter set through a micro-seismic sensor and a temperature and humidity sensor, detecting and extracting displacement points through Bayesian regression, and drawing a deformation diagram; determining a displacement area, counting an airflow velocity gradient, extracting a main fracture direction, generating an airflow path diagram, calculating a curvature change rate, positioning a sudden change area, extracting a thermal strain rate and an axial strain rate, generating a smooth curve, identifying a risk point, and expanding a boundary when the overlapping rate exceeds 60%, and redrawing a mine thermal-mechanical coupling risk map. According to the method, a multi-parameter analysis framework is constructed through micro-seismic and temperature and humidity data coupling to extract a deformation active band, difference statistics airflow velocity gradient is combined with a crack direction to correct an airflow path, a sudden change area is positioned based on a curvature change rate mean threshold, and thermal strain and axial strain are extracted to screen risk points. And constructing thermal variable amplitude mapping to represent the rock mass instability risk.

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 provides a coal mine water inrush risk early warning method and system under multi-source information, and relates to the technical field of risk early warning, and the method comprises the steps: employing a multi-source information collection module to regularly collect geological structure data, hydrological data, microseismic signals and environment monitoring data in a coal mine operation area, and constructing a multi-source information database; performing data preprocessing to obtain a standard multi-source information database; carrying out multi-source data fusion, and constructing a water inrush risk comprehensive evaluation model in combination with a geological model, a hydrological model and a micro-seismic analysis model; analyzing the water inrush risk index in real time, and generating water inrush risk early warning information when the model output value is higher than a preset risk threshold value; and performing visual display of the water inrush risk early warning information through a visual interface. The technical problem that the prior art depends on a single data source and cannot comprehensively reflect complex condition changes in a coal mine operation area, so that accuracy of water inrush risk assessment is insufficient, and then early warning of the water inrush risk is missed is solved.

The invention relates to the technical field of side slope geological disaster monitoring and early warning, and discloses a Beidou-based side slope geological disaster monitoring and early warning method and system.The Beidou-based side slope geological disaster monitoring and early warning method comprises the steps that multi-scale geological signals based on Beidou system time service are acquired, the multi-scale geological signals comprise environmental noise signals, acoustic emission signals and micro-seismic signals; processing the multi-scale geological signals, and extracting environmental noise interference characteristics representing the change of a microstructure in the slope, acoustic emission signal characteristics representing the microscopic damage process of a material and micro-seismic signal characteristics representing the deformation of a macrostructure; based on the environmental noise interference features, the acoustic emission features and the micro-seismic features, constructing a slope instability risk assessment model, and outputting a risk assessment result; performing early warning according to a risk assessment result; according to the invention, high-precision, low-cost and full-coverage monitoring and early warning can be realized.

The invention provides a sandy stratum tunnel water burst risk prediction method. The method comprises the steps that a radar instantaneous energy spectrum in front of tunneling is obtained through a geological radar, a micro-seismic spectrum is obtained through a micro-seismic array, and a residual distance is obtained through laser ranging; aligning and coupling the two spectrums to obtain a water inrush risk index, inputting the water inrush risk index and the residual distance into a self-adaptive threshold comparator, and if the water inrush risk index and the residual distance exceed the limit, dynamically adjusting the rotating speed of a cutter head, propulsive force, the rotating speed of a screw conveyor and grouting pressure, and generating a risk avoidance path; and calling a water inrush risk model library constructed by LSTM-Attention, inputting a risk index sequence, a residual distance, cutterhead torque, a soil pressure gradient, a current change rate and other auxiliary variables, and outputting a future multi-step risk level. According to the method, accurate prediction and real-time avoidance of the water gushing risk of the sandy stratum tunnel can be realized, and the safety and efficiency of tunnel construction are improved.

The invention provides a landslide monitoring and early warning method based on air-sky-earthquake integration, and belongs to the technical field of landslide disaster monitoring. Air-sky-ground-earthquake monitoring data are integrated, multi-dimensional parameters such as surface deformation, topographic change, internal strain, crack propagation, rainfall intensity and micro-earthquake activity are covered, the limitation of a single monitoring means is solved, and a space-time complementary three-dimensional monitoring system is formed. According to a data analysis processing result, an early warning response rule is set, an early warning model is constructed through a multi-source data fusion technology in combination with an optimal weighted random forest method and a comprehensive scoring model, real-time evaluation and early warning grade judgment of landslide risks are realized, and visual display of monitoring data is realized. The model is iteratively trained by introducing reward and punishment factors, and weight distribution of different data sources is dynamically adjusted, so that the early warning model has adaptive ability, early warning requirements of long-term slow deformation and short-term accelerated deformation are considered, and the early warning accuracy of the model is improved.

The invention relates to the technical field of mine safety and geological environment evaluation, in particular to a mine goaf geological environment dynamic evaluation method based on digital twinning. The method comprises the following steps: constructing a digital twinborn model of a mine goaf, designing a data structure and a virtual-real mapping rule, collecting multi-source heterogeneous data, and performing spatio-temporal data indexing processing to form a spatio-temporal associated data stream; microseismic travel time data are extracted from the space-time associated data stream; performing parallel ray tracing and rapid inversion on the microseismic travel time data to obtain a wave velocity distribution initial value; carrying out wave velocity field self-adaptive grid refinement on the micro-seismic travel time data by utilizing the wave velocity distribution initial value to obtain a multi-resolution wave velocity field; and carrying out wave velocity change rate analysis on the multi-resolution wave velocity field to obtain a wave velocity variability tensor. According to the method, the abstract energy transfer process is concrete into a data field capable of being quantitatively analyzed, so that the geological environment of the goaf is accurately and dynamically evaluated.

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 relates to the technical field of mine coal and rock dynamic disaster prevention and control, in particular to a micro-seismic-based deep coal and rock mass instability dynamic multi-parameter evaluation method. The method comprises the following steps: acquiring waveform data of each micro-seismic event of a deep coal and rock mass through a mine micro-seismic system; according to the waveform data, acquiring a micro-seismic characteristic index set of each micro-seismic event; according to the seismic source position and the micro-seismic characteristic index set of each micro-seismic event, acquiring an energy-based micro-seismic magnitude; according to the micro-seismic magnitude, obtaining a micro-seismic b value corresponding to a preset duration, and according to the micro-seismic characteristic index set, obtaining a micro-fracture type and change trend information of accumulated energy of each micro-seismic event; and according to the micro-seismic energy, the change trend information of the accumulated energy, the frequency, the ringing count, the micro-fracture type and the micro-seismic b value, the dynamic instability fracture risk information of the deep coal and rock mass is obtained. According to the invention, the determination accuracy and efficiency of the instability and fracture risk information can be improved.

The invention provides a hydraulic fracture growth visualization method and device based on microseismic point cloud. The method comprises the steps that first point cloud data of a real micro-seismic event is obtained based on observation data of a micro-seismic monitoring system, and the micro-seismic monitoring system is used for collecting data of the micro-seismic event generated when hydraulic fracturing operation is conducted on a target reservoir; real fracturing curve parameters associated with the hydraulic fracturing operation are obtained; based on the first point cloud data of the real micro-seismic event, constructing a first micro-seismic density field on a continuous time sequence; based on the first micro-seismic density field and the real fracturing curve parameters, adopting a pre-trained multi-source fusion neural network model to perform predictive reasoning to obtain fracture probability distribution output by the multi-source fusion neural network model; and determining a crack boundary and an extension form based on the crack probability distribution, and overlapping the crack boundary and the extension form on the reference underlying structure or the actual well position profile for display. According to the invention, the accuracy and timeliness of crack identification can be improved.

The invention provides a fusion geological prediction method, system and device, a storage medium and a program product, and relates to the technical field of tunnel advanced geological prediction. The method comprises the following steps: an upper computer receives multiple groups of seismic data and acquisition time of each group of seismic data sent by a data acquisition instrument; the upper computer determines the type of seismic data according to the acquisition time, the pre-recorded working time period of the heading machine and the vibration time period of the seismic source; the upper computer extracts micro-seismic analysis data, active source analysis data and passive source analysis data from the multiple sets of seismic data according to the data types; the upper computer generates rockburst risk data according to the micro-seismic analysis data, and generates geological risk data according to the active source analysis data and the passive source analysis data; and reconstructing and displaying a three-dimensional visual image according to the rockburst risk data and the geological risk data. The problems that in the prior art, due to the fact that sensors are arranged repeatedly, equipment layout is disordered, construction streamlines are blocked, and construction efficiency and equipment safety are seriously affected are solved.

The invention discloses a coal rock instability precursor identification method and system based on fracture topological parameters, and the method comprises the steps: obtaining sound wave data through micro-seismic monitoring, and extracting coal rock fracture core parameters in combination with seismic source positioning and seismic source mechanism inversion; building a fracture network topology model based on a graph theory method by considering the geometric dimension and direction characteristics of the fracture, and obtaining fracture space-time topology evolution parameters to build a multivariable time sequence topology characteristic data set; introducing a multivariable time sequence graph model MTAD-GAT, dynamically capturing a structural dependency relationship among topological parameters by using a graph attention mechanism, mining collaborative anomaly characteristics of the structural dependency relationship, and capturing an evolution trend of the structural dependency relationship in combination with a time sequence modeling module; and fusing the prediction error and the reconstruction error to form an abnormal score as an instability precursor index, extracting covariant features and evolution trends of a plurality of key topological indexes in the precursor stage, and assisting in distinguishing an instability critical state, thereby realizing unsupervised automatic identification and intelligent early warning of the topological precursor.

The invention discloses a micro-seismic event identification method, device and equipment and a storage medium, the disclosed micro-seismic event identification method is applied to a graph neural network, and the graph neural network is composed of a plurality of mutually connected nodes. According to the application, the response result of each sensor node is obtained by responding to the stress signal of the signal node through each sensor node, and the response result at least comprises waveform data and audio data; inputting each waveform data into a preset waveform prediction model to obtain an original waveform probability vector corresponding to each sensor node; inputting each piece of audio data into a preset audio prediction model to obtain an original audio probability vector corresponding to each sensor node; and according to each original waveform probability vector and each original audio probability vector, determining the probability that the stress signal is triggered by the preset micro-seismic event, thereby realizing automatic identification of the micro-seismic event without depending on artificial experience, effectively improving the identification speed of the micro-seismic event, and further improving the timeliness of micro-seismic early warning.

The invention relates to the technical field of earthquake monitoring, and discloses a mining area micro-earthquake monitoring method and system based on multi-parameter fusion, and the method comprises the steps: collecting time-space synchronization data of a mining area through employing a preset sensor array, and the time-space synchronization data comprise gravity data and seismic wave data; performing mixed noise reduction on the gravity data to obtain noise reduction data of the gravity data; extracting a gravity anomaly index of the mining area based on the noise reduction data; extracting a seismic wave energy ratio of the seismic wave data; based on the gravity anomaly index and the seismic wave energy ratio, establishing a joint criterion model of the mining area; and performing micro-seismic early warning on the mining area based on the combined criterion value of the combined criterion model and a preset early warning threshold value. The micro-seismic monitoring efficiency of the mining area can be improved.

The invention relates to the technical field of tunnel engineering, in particular to a tunnel rockburst risk assessment method and prevention method, and the assessment method comprises the steps: installing a plurality of first micro-seismic sensors in the circumferential direction of a tunnel wall within a preset distance range behind a tunnel face, determining an initial rockburst range based on the micro-seismic data collected by the first micro-seismic sensor; and a plurality of second micro-seismic sensors are annularly installed on the tunnel wall corresponding to the initial rockburst range, the monitoring precision of the second micro-seismic sensors is higher than that of the first micro-seismic sensors, and the final rockburst position is determined based on micro-seismic data collected by the second micro-seismic sensors. The tunnel rock burst occurrence position can be finely determined, and hydraulic slotting pressure relief is guided.

The invention discloses a deep rock mass fracture imaging method and system based on micro-seismic monitoring, and belongs to the technical field of geophysical exploration, and the method comprises the steps: collecting multi-channel micro-seismic event waveform data, obtaining a main seismic phase direct waveform and a scattering tail waveform through wave field separation, and carrying out the imaging of a deep rock mass fracture. Determining a three-dimensional space coordinate and an energy distribution form of the seismic source through joint inversion, carrying out clustering analysis, and constructing an initial three-dimensional space distribution form; each seismic source is regarded as an active excitation source, a scattering tail wave waveform is regarded as a reflection signal, scatterer three-dimensional point cloud data is generated through reverse time migration processing, analysis is carried out in combination with an initial three-dimensional space distribution form, and an enhanced fracture structure is formed; and finally, through topology analysis and orientation clustering, discrete scatterers are eliminated, and a fracture development map is generated. According to the method, a technical path of combining a main seismic phase direct wave inversion seismic source and a scattering tail wave inversion scatterer is adopted, high-precision and high-fidelity imaging of a deep rock mass movable fracture can be realized, and physical activity is revealed.

The invention discloses a tunnel micro-seismic enhanced positioning method and system based on a DAS and a blasting active source signal. The method comprises the steps that firstly, optical fibers are arranged on the surface of a tunnel wall and in a drill hole; blasting the tunnel face to generate a blasting active source signal with known time and space; then, a blasting active source signal is collected through a DAS system, and P wave arrival time of each monitoring point on the optical fiber is recorded; establishing and optimizing a wave velocity field partition model according to the spatio-temporal information of the blasting active source signal and P wave arrival time of each monitoring point on the optical fiber; and when a micro-seismic event occurs in the surrounding rock, the optimized wave velocity field partition model and P wave arrival time measured at each monitoring point on the optical fiber are utilized, a geometric algorithm is combined to invert and position the micro-seismic event, and a positioning result is output. The system comprises a signal acquisition system, an optical fiber network and a DAS system. The method has the advantages that the wave velocity field model is optimized and dynamically updated by using the tunnel face blasting signal, and the distributed sensing is performed by using the DAS system, so that the capability of monitoring and evaluating the micro-seismic event of the tunnel is remarkably enhanced.

The invention provides an early warning method based on microseismic energy accumulation tendency, and belongs to the field of seismic data processing. The method comprises the following steps: acquiring a historical micro-seismic log set of an earthquake monitoring sensor array in a coal mine area; performing staged processing in combination with a timestamp to obtain a micro-seismic energy characteristic sub-sequence set; executing a first-order difference operation, and constructing a difference energy characteristic subsequence set; performing trend correlation analysis by using a space-time guiding module to obtain a trend feature set; constructing an energy accumulation tendency analyzer based on the trend feature set; and obtaining a real-time micro-seismic log, carrying out abnormity identification by combining with an analyzer, and triggering an early warning instruction. The technical problem that in the prior art, the dynamic change trend of the micro-seismic energy cannot be accurately captured, so that the early warning accuracy of the energy accumulation is insufficient is solved, and the technical effect of improving the early warning accuracy and timeliness of the micro-seismic energy accumulation through differential energy feature analysis and space-time trend association is achieved.

The invention discloses a rock hydraulics-based high-position separation water monitoring and drainage control method, which comprises the following steps of: determining a separation water development position according to an early-stage exploration result; a monitoring drill hole and a drainage drill hole which are communicated with the separation water are constructed on the ground surface above the development position of the separation water; a water pressure sensor is arranged at the bottom in the monitoring drill hole; a water suction pump is arranged in the drainage drill hole; a plurality of micro-seismic sensors are arranged in a roof rock stratum of the working face at set intervals, and the development height of the water flowing fractured zone is determined according to micro-seismic signals collected by the micro-seismic sensors; determining the thickness of a separation layer water-resisting layer according to the development height of the water flowing fractured zone; determining an abscission water warning water head according to the thickness of the abscission water water-resisting layer; determining a warning water level according to the separation water warning water head and the separation water bottom plate elevation obtained through early-stage exploration, and setting the determined separation water warning water level as an early warning water level; the water level data in the monitoring drill hole are collected in real time, the real-time water level is obtained, when the real-time water head exceeds the early warning water level, the water suction pump is started to pump separation water, and separation water level control is achieved.

The invention discloses a method and a system for identifying a micro-seismic signal mode of a surrounding rock rockburst risk, particularly relates to the technical field of deep underground engineering rockburst monitoring, and is used for solving the problem that an existing micro-seismic early warning model lags in identifying a rock mass damage evolution critical state. The method comprises the following steps: collecting a surrounding rock micro-seismic event signal in real time, intercepting an event sequence based on a sliding time window, and calculating a space-time fractal dimension; extracting an event space density field in the window to calculate an energy gradient, and marking a strong interaction cluster of which the energy gradient exceeds a threshold value; storing the fractal dimension change sequence in real time; performing characteristic frequency band filtering on the signals in the window, calculating a ratio of an energy ratio entropy descent rate to a fractal dimension descent rate, and determining a damage acceleration state when the ratio is a supercritical coefficient; generating a rockburst high-risk instruction when the strong interaction cluster and the damage acceleration state coexist and the fractal dimension descent rate is supercritical threshold; the multi-dimensional collaborative identification of the rockburst precursor is realized, and the early warning accuracy and timeliness are remarkably improved.

The invention relates to a regional fracturing influence range monitoring method based on distributed optical fiber sound wave sensing, and the method comprises the steps: pre-arranging a DAS monitoring system in a fracturing region, and collecting an original signal of the fracturing region through the DAS monitoring system; identifying the original signal, and obtaining a micro-seismic signal and first arrival time of a longitudinal wave in the micro-seismic signal; based on the first arrival time of longitudinal waves in the micro-seismic signals, the distribution position of micro-seismic events in the fracturing area is determined; according to the distribution position of the micro-seismic event in the fracturing area, the hydraulic fracturing influence range in the fracturing area is determined, the original signal of the fracturing area is collected through the DAS monitoring system, the distribution position of the micro-seismic event in the fracturing area is determined by processing the original signal, accurate characterization of the hydraulic fracturing crack propagation form is achieved, and the hydraulic fracturing influence range in the fracturing area is determined. The accuracy and efficiency of determining the effective influence range of hydraulic fracturing are improved, reference can be provided for optimization of a hydraulic fracturing scheme, the hydraulic fracturing pressure relief effect is improved, and the production safety of a coal mine is guaranteed.

The invention discloses an all-terrain ad hoc network high-speed data transmission method and system for microseism acquisition, and relates to the technical field of data transmission, and the method comprises the steps: constructing a layered network architecture, a first-layer central backbone network is provided with a Mesh chain communication structure, and a second-layer star acquisition network is provided with a star connection architecture; after being powered on, the seismic acquisition terminal acquires seismic signal data and accesses the seismic signal data to the target relay node; and the target relay node selects an optimal Mesh routing path according to a built-in path evaluation processor, forwards the seismic signal data to a preset master control node hop by hop, and uploads the seismic signal data to a seismic data processing server through a local communication module after receiving the seismic signal data, thereby completing centralized data processing. According to the invention, the technical problem of poor seismic signal data transmission stability due to dependence on fixed communication infrastructures in a complex field environment in the prior art is solved, and the technical effects of improving data transmission reliability, reducing network failure rate and overcoming unsmooth communication under a complex field surface condition are achieved.

The invention discloses a test device and a test method for a vibration and dislocation double-input lower span tilting-sliding fault tunnel. The test device comprises a test box body, a hydraulic actuator, a loading unit, a covering layer soil body, a tunnel physical model and a sensor monitoring system, wherein the test box body consists of a movable steel plate and a fixed steel plate; the loading unit consists of an angle adjusting module and a hydraulic control system; a bed rock model, a covering layer soil body and a tunnel model are arranged through a modular construction method, and data are collected in real time through soil pressure, microseismic and strain sensors and displacement meters. According to the invention, the failure mechanism of the cross-fault tunnel under the coupling action of bed rock dislocation and pulse seismic oscillation can be accurately simulated, the damage rule of the combined action of fault dislocation and seismic waves to the tunnel structure is revealed by qualitatively and quantitatively analyzing the strain, displacement, soil pressure and seismic oscillation response of the tunnel, and a test basis is provided for the aseismic design of the cross-fault tunnel.