708 results about "Rock burst" patented technology

The invention discloses a data-mechanism dual-drive-based rock burst early warning method and system, and the method comprises the following steps: deploying a multi-modal sensor network to collect coal and rock stratum data, building a rock burst disaster precursor information sample database, providing a rock burst disaster multi-modal data precursor feature recognition algorithm, and carrying out the recognition of rock burst disaster multi-modal data precursor features. Mining the relevance between the multi-modal data and disaster-causing key risk indexes, and establishing a rock burst disaster multi-modal data prediction model; establishing a three-dimensional geological geometric model, fusing a multi-field coupling dynamics constitutive model and a catastrophe criterion, constructing a PINN physical information neural network prediction model of the rock burst disaster, and obtaining a time-space evolution rule of an energy field of a target area; providing a loss function coupling calculation method of a multi-modal data driving sample error and a physical driving control equation residual error, dynamic data and mechanism prediction result weight, comprehensively calculating a risk score, and accurately judging a top disaster danger level.

The invention discloses a deep well rock burst early warning system and method based on multi-dimensional monitoring, and belongs to the technical field of deep well rock burst early warning. According to the method, multi-dimensional data such as stress, strain and microseism are collected through a monitoring network, and an aligned multi-source data set is obtained through space-time registration; after dynamic noise suppression processing matched with physical characteristics is adopted, strong correlation characteristics are screened through mutual information entropy; frequency domain, time domain and time-frequency domain features are extracted through principal component extraction and phase-space reconstruction, and a multi-dimensional state space data set is formed; and inputting the prediction model to obtain a danger level and trigger a corresponding early warning signal, and finally dynamically adjusting the monitoring network layout and prevention and control measures based on the early warning signal. According to the method, the early warning accuracy and real-time performance are improved, and effective technical support is provided for deep well rock burst prevention and control.

An intelligent design method for a support scheme of a rock burst section in a TBM tunnel, relating to the field of tunnel engineering. The intelligent design method for the support scheme of the rock burst section in the TBM tunnel comprises: determining a surrounding rock class on the basis of TBM mainframe operation data, surrounding rock feedback evaluation, and a tunnel engineering geological survey report, and using a rock burst intensity assessment method to predict a rock burst grade; and on the basis of the surrounding rock class and the rock burst grade, using a computer deep learning technology to determine an initial surrounding rock support method. The method effectively avoids the impact of subjective factors, actively utilizes TBM mainframe operation data and surrounding rock feedback evaluation, utilizes big data processing and an artificial intelligence technology to propose an intelligently designed support scheme for a rock burst section in a TBM tunnel, and can provide an efficient support scheme for field construction workers for a rock burst section in a tunnel.

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 an underground-ground-sky combined rock burst and earth surface deformation early warning method, which comprises the following steps of: S1, arranging an underground monitoring system, and acquiring underground monitoring data; s2, setting a ground monitoring system, and collecting ground monitoring data; s3, setting a sky monitoring system, and collecting sky monitoring data; s4, calibrating the time scale difference of the underground monitoring data, the ground monitoring data and the sky monitoring data through a multi-scale time alignment algorithm; and S5, constructing a multi-stage joint probability assessment framework to carry out mining area rock burst and earth surface deformation risk assessment. According to the method, multi-source monitoring data are integrated through a multi-scale space-time fusion framework, and a full-chain association model of'microcosmic fracture-mesoscopic deformation-macroscopic accumulation 'is constructed. And on the basis of cross-scale time sequence alignment, spatial heterogeneity is optimized and eliminated, a multi-stage joint probability assessment framework quantifies a cross-scale collaborative risk, full-period intelligent management and control of'monitoring-early warning-feedback-optimization 'is realized, and early warning accuracy and timeliness are improved.

The invention provides a multi-physics field cooperative regulation and control method in coal mine rock burst prevention and control, and relates to the technical field of coal mine rock burst prevention and control, and the method comprises the steps: synchronously collecting stress field, fracture field and vibration wave field data in real time through a distributed optical fiber sensor network and a micro-seismic monitoring system, and constructing a dynamically updated three-dimensional geomechanical model; based on an adaptive Kalman filtering algorithm, noise reduction multi-source data are fused, a dynamic stress concentration factor and an energy accumulation critical index are extracted, and a rock burst risk probability model is established; a multi-objective optimization algorithm is adopted to generate graded regulation and control instructions of grouting reinforcement, mining speed adjustment and pressure relief drilling, and the graded regulation and control instructions are executed in real time; and iteratively optimizing the model weight by using a transfer learning algorithm in combination with a historical case library to form a closed-loop feedback adaptive prevention and control system. According to the method, the analysis precision of rock mass fracture evolution under complex geological conditions is improved through multi-physics field collaborative perception and dynamic modeling, and risk quantification and real-time regulation and control are realized through multi-algorithm coupling analysis.

The invention discloses a coal mine rock burst risk assessment system which comprises a data acquisition module, an energy accumulation rate calculation module, a roadway network modeling module, a risk assessment module and an early warning regulation and control module. The method comprises the following steps of: firstly, calculating an energy accumulation rate of a roadway, then constructing a roadway network diagram, identifying a high stress conduction path, calculating a dynamic risk index and delimiting a risk area by integrating factors such as a historical impact event and an energy index, and automatically triggering corresponding early warning and regulation measures by a system according to a risk level so as to realize accurate early warning and dynamic regulation. And mine operation decision making and accident prevention are assisted.

The invention belongs to the field of surrounding rock rockburst early warning, and provides a rockburst early warning method and system based on micro-seismic energy and support stress coupling monitoring, which are used for carrying out deep gold mine roadway surrounding rock micro-seismic monitoring and anchor rod support stress monitoring. Establishing a micro-seismic energy data set, and carrying out statistical analysis to obtain a micro-seismic energy early warning index; the anchor rod supporting stress is analyzed, and then an anchor rod stress early warning index is determined; and carrying out information fusion on the micro-seismic energy early-warning index and the anchor rod stress early-warning index, establishing a combined early-warning method based on micro-seismic energy and support stress, and carrying out evaluation and early-warning on the rock burst grade of the surrounding rock. Rockburst occurrence risks can be effectively reduced, and safety of constructors and mechanical equipment is guaranteed.

The invention relates to the technical field of coal mine safety, in particular to a water inrush and rock burst composite disaster risk multi-source judgment method which comprises the steps that four fields of original data of a target underground area are collected in real time, and the four fields comprise a stress field, a vibration field, an energy field and a seepage field; extracting multivariate feature indexes from the four-field original data to obtain four-field multivariate indexes; constructing a core composite index based on the four-field multi-element indexes, quantifying the coupling strength of water inrush and rock burst, and judging a disaster dominant type; and calculating a comprehensive risk index based on the four-field multi-element indexes and the disaster dominant type, and judging the risk level of the water inrush and rock burst composite disaster according to the comprehensive risk index. According to the invention, accurate identification and graded prevention and control of composite disasters are realized, and the accuracy and timeliness of early warning of mine disasters are significantly improved.

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 discloses a hydraulic fracture monitoring system and method based on an underground micro-seismic sensor network, and belongs to the field of coal mining, and the system comprises a plurality of micro-seismic sensors which are used for collecting micro-seismic signals generated by rock fracture; the plurality of data acquisition substations are used for receiving and processing the micro-seismic signals; the data transmission substation is used for converting the micro-seismic signal processed by the data acquisition substation into an optical signal; the micro-seismic server performs micro-seismic event analysis according to the optical signal; the mining network switch is connected with the data transmission substation and the micro-seismic server and is used for network data exchange; the in-mine ring main unit is connected with the mining network switch and the micro-seismic server to form a communication network of the system; in order to solve the problem that hydraulic fracture detection precision is low due to the fact that micro-seismic signals generated by hydraulic fracture and coal mining activities are difficult to accurately distinguish in a complex underground environment, the hydraulic fracture detection method and device distinguish the micro-seismic signals generated by hydraulic fracture and coal mining activities by dividing a fracture area and a mining area, and the real-time monitoring precision of hydraulic fracture expansion is improved.

The invention provides a mining area catastrophe early warning method, device and equipment based on a rock mass multi-dimensional quantitative characterization model, and the method comprises the steps: inputting the collected multi-field data of a stress field, a rock mass damage field and a penetration field into a multi-field co-evolution model to obtain a corresponding multi-field evolution coefficient, and updating the output of a catastrophe early warning model through the evolution coefficient. A stress-rock mass damage-permeation co-evolution mechanism is constructed, the prediction precision of disasters such as rockburst and water and mud inrush is guaranteed, and advanced early warning and active control of catastrophe are achieved.

The invention discloses a high gas impact ground pressure mine island working face blasting pre-pressure-relief scour prevention method which comprises the steps that a scour inducing key layer in a top plate above an island working face is determined, a top plate pre-splitting pressure relief roadway with specific construction parameters is arranged in the scour inducing key layer, and by means of the mode, elastic deformation accumulated in the scour inducing key layer can be effectively reduced, and one-time pressure relief can be achieved; then, a plurality of blast holes with specific parameters are constructed from the roof presplitting pressure relief roadway to the inducing key layer, finally, the blast holes are sectioned according to the hole depth and sequentially blasted, energy release of each time of blasting is accurately controlled through sectioned blasting, meanwhile, continuous pressure relief is achieved in time and space through sectioned blasting, and the blasting efficiency is improved. The stress of the inducing key layer is effectively released to realize secondary pressure relief; through mutual cooperation of primary pressure relief of the roof presplitting pressure relief roadway and secondary pressure relief of segmented blasting of the blast hole, the mine roof type impact risk facing high gas, an island working face and mining rock burst is effectively reduced, and subsequent safe mining of the island working face is guaranteed.

The invention discloses a coal mining rock burst prevention and early warning system which comprises a data acquisition system, and the data acquisition system comprises a sensor network, a self-adaptive sensor layout module, a signal sending module and a power supply module. The sensor network comprises a stress sensor, a displacement sensor and a vibration sensor which are arranged in a coal mine tunnel; the signal sending module is used for sending data acquired by the sensor; the power module is used for supplying power to the sensor network and the signal sending module. The coal mining rock burst prevention and early warning system is compatible with three kinds of sensing data of a stress sensor, a displacement sensor and a vibration sensor, and the positions and density of the sensors in a high-risk area are dynamically adjusted. And establishing a coal seam rock burst risk evaluation expert system by using the monitored result, and evaluating the early warning result. The sensor layout strategy of the coal mining rock burst prevention and early warning system is optimized, the monitoring capability of a high-risk area is improved, and the rock burst danger early warning level can be improved.

The invention belongs to the field of coal mine rock burst and gas control, and relates to a high-gas coal seam mining method with cooperation of hydraulic fracturing pressure relief and high drainage roadway, which comprises the following steps: constructing a trend high drainage roadway, and constructing a hydraulic fracturing drill hole and fracturing in an air return crossheading; constructing layer-crossing drilling holes from the trend high drainage roadway to the air return crossheading; tunneling an air return crossheading and ventilating; performing hydraulic fracturing drilling and fracturing in the open-off cut; constructing a layer-penetrating hole from the end part of the trend high drainage roadway to the open-off cut; tunneling a cut hole and ventilating; the air return crossheading is connected with the air return main roadway; bedding drilling and fracturing are carried out in self-air-return crossheading construction; and hydraulic fracturing drilling and fracturing are conducted on the transportation crossheading, the transportation crossheading is tunneled and ventilated, and working face stoping is conducted. Pressure relief is carried out before roadway tunneling, a smooth air flow path can be formed before roadway tunneling and in the tunneling process to extract gas, newly generated gas on a tunnel face can be rapidly extracted, gas extraction can be continuously carried out during stoping, and safety of the whole production process is guaranteed.

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 discloses an intelligent rock burst early warning and prevention system and method based on a large language model, and the system is characterized in that a rock burst monitoring and early warning module comprises a high-precision sensor group, a rock burst prediction module and a rock burst danger level grading module, and is used for obtaining a grading result of a rock burst danger level; the anti-scour pressure relief measure self-adaptive optimization decision module is used for outputting optimal pressure relief measures and pressure relief parameters; the man-machine interaction module based on the large language model is used for performing engineering interpretation and man-machine interaction; the method comprises the following steps: predicting a rock burst danger early warning result by using the rock burst prediction module based on preorder multi-mode monitoring data; obtaining a grading result of an impact danger grade by utilizing a rock burst danger grade grading module; outputting an optimal pressure relief measure and a pressure relief parameter by using an anti-scour pressure relief measure self-adaptive optimization decision module; and a man-machine intelligent interaction module based on a large language model is used for providing intelligent decision support. According to the system and the method, the rock burst prevention and control scheme can be accurately and intelligently realized in advance.

The invention relates to the field of surrounding rock supporting, and provides an aging cracking and multi-source dynamic response self-adaptive supporting system and method in order to improve the supporting reliability, and the state of surrounding rock is sensed in real time through a multi-source sensing module; the aging damage model can comprehensively and dynamically evaluate the damage state of the surrounding rock of the mixed rock, and progressive instability accidents such as hysteresis rock burst can be effectively prevented; the dynamic disturbance model can analyze the damage effect of dynamic loads such as TBM tunneling and blasting on mixed rock surrounding rock in real time, a millisecond-level dynamic risk assessment result is provided for a self-adaptive support system, and instant instability accidents are effectively restrained. The self-adaptive support of the dynamic execution module is realized by combining the parallel decision of the aging damage model and the dynamic disturbance model, the problem that the traditional support depends on static geological data and is difficult to adapt to the dynamic damage change of the surrounding rock is solved, the stability and reliability of the support system are remarkably improved, and the engineering cost and the safety risk are reduced.

The invention relates to the technical field of coal mine safety, in particular to a mine rock burst early warning, prevention and control method, device and equipment and a medium, and the method comprises the steps: obtaining multi-source monitoring data based on a high-precision positioning method; performing feature extraction on the multi-source monitoring data to obtain deep feature data; constructing a network prediction model, and training the network prediction model by using the deep feature data to obtain a trained network prediction model; and constructing a three-dimensional cellular automaton model of the coal and rock mass fracture process, and simulating a prevention and control strategy by using the three-dimensional cellular automaton model of the coal and rock mass fracture process to obtain a final prevention and control strategy. By integrating multi-source data such as coal and rock mass microstructure parameters, geological conditions and mining processes and combining machine learning and dynamic weight distribution technologies, accurate prediction and active prevention and control of rock burst risks are realized, and the problems of low early warning precision, poor real-time performance and weak adaptability in the prior art are solved.

The invention discloses a combined well spacing method for a ground vertical well and an underground horizontal well, which comprises the following steps of: determining estimated fracturing information of the vertical well and estimated fracturing information of the horizontal well according to acquired fracturing construction information of a surrounding mine; the width of the to-be-mined working face and the lateral mining-induced fracture range of the mined working face are obtained, vertical well construction information is determined according to the width of the to-be-mined working face, the lateral mining-induced fracture range and vertical well estimated fracturing information, fracturing construction is conducted on the thick and hard roof based on the vertical well construction information, and the vertical well fracturing range of a ground vertical well is obtained; and horizontal well construction information is determined according to the horizontal well estimated fracturing information and the vertical well fracturing range, and fracturing construction is conducted on the impact main control rock stratum based on the horizontal well construction information. According to the combined well spacing method for the ground vertical well and the underground horizontal well, the well spacing scheme that the ground vertical well and the underground horizontal well are matched with each other is adopted, sufficient fracturing and pressure relief can be conducted on a thick and hard top plate, and cooperative prevention and control over rock burst and mine earthquake disasters are achieved.

The invention provides a deep tunnel time-delay rockburst comprehensive early warning method based on an acoustoelectric technology. The method is applied to the technical field of tunnel and underground engineering disaster early warning and comprises the steps that a micro-seismic sensor array is arranged in a deep tunnel rock engineering target area, and a micro-seismic monitoring system is built; positioning a micro-seismic event and seismic source parameter information for the collected micro-seismic signals, and determining a key monitoring area of a rock mass fracture damage area; carrying out point location monitoring on the key monitoring area of the rock mass fracture damage area by using an electromagnetic radiation monitoring instrument; establishing a time-delay rockburst early warning index system; a comprehensive early warning model is established, and fuzzy mathematics comprehensive evaluation is conducted on the time-delay rockburst; obtaining a rockburst main control factor membership degree function according to a micro-seismic and electromagnetic radiation monitoring data statistical result; obtaining a fuzzy matrix R of the time-delay rockburst according to the membership function of the main control factors of the rockburst; and outputting an early warning result. In this way, the accuracy of rockburst early warning can be improved.

The invention relates to a rock burst multi-level monitoring and early warning method and device based on coal mine tunnel deformation. The method comprises the following steps: acquiring three-dimensional coordinate data and historical data of a to-be-monitored coal mine tunnel surrounding rock at a current time node, and generating a contour model of the to-be-monitored coal mine tunnel surrounding rock at the current time node by using the three-dimensional coordinate data; the three-dimensional coordinate data and the historical data are utilized to determine the time change imbalance degree and the space change discordance degree of energy corresponding to each grid in the contour model; determining a rock burst danger coefficient by using the imbalance degree and the discordance degree corresponding to the grids, and outputting early warning information based on the rock burst danger coefficient; and under the condition that the rock burst danger coefficient of the grid does not meet a first preset condition, performing hierarchical grid division processing on the grid, and returning to execute the step of obtaining the three-dimensional coordinate data of the surrounding rock of the coal mine tunnel to be monitored and the calculation step. According to the scheme, the accuracy and timeliness of rock burst early warning are improved.

The invention discloses an accurate coal mine rock burst intelligent monitoring and early warning method. The method comprises the following steps that a plurality of micro-seismic monitoring sensors are arranged on a coal mine working face to form a monitoring network; microseismic signal data are collected in real time; the collected micro-seismic signals are preprocessed; a developed redundancy time difference set hyperboloid interpolation positioning method is used to accurately position the micro-seismic source; and based on the micro-seismic signal features and the positioning result, establishing a rock burst early warning model, determining a potential region where rock burst occurs, and realizing dynamic early warning and forecasting. The accuracy, the real-time performance and the reliability of rock burst monitoring and early warning are remarkably improved, and important technical support is provided for coal mine safety production.

The invention provides a large cavern group design method for a hydropower station under an extremely high crustal stress condition. The method comprises the following steps: S1, analyzing a three-dimensional initial crustal stress field of a factory; s2, rock mass mechanical characteristic analysis; s3, underground powerhouse cavern group surrounding rock stability analysis; s4, carrying out design analysis on an anchor cable pre-tightening coefficient and a supporting opportunity; s5, performing micro-seismic early warning analysis on deformation and fracture of the surrounding rock of the cavern group of the underground powerhouse; and S6, providing underground powerhouse rockburst criteria in combination with measured rockburst data: providing underground powerhouse rockburst occurrence and evolution mechanisms based on rock mass characteristics, rockburst characteristics, micro-seismic data and monitoring results, analyzing surrounding rock stress release, relaxation and deformation characteristics, and evaluating surrounding rock stability. The design safety and reliability of the large cavern group of the hydropower station are improved, the construction risk and cost are remarkably reduced, and meanwhile the requirement for environmental protection is met. The improvement measures act together to ensure smooth implementation and long-term stable operation of an engineering project.

The invention provides a static blasting process optimization method and system based on digital twinning, and relates to the technical field of blasting process optimizing.The method comprises the steps that historical static blasting data are obtained, data before blasting and data during blasting are analyzed to obtain disturbance fluctuation characteristics and disturbance stress characteristics, and the disturbance fluctuation characteristics and the disturbance stress characteristics are analyzed; analyzing the disturbance fluctuation characteristics and the disturbance stress characteristics to obtain a disturbance fluctuation interference coefficient and a disturbance stress interference coefficient, and analyzing the disturbance fluctuation interference coefficient and the disturbance stress interference coefficient to obtain a rock burst occurrence coefficient; establishing a rock burst prediction model according to the pre-burst data and the rock burst occurrence coefficient, and calculating the rock burst occurrence coefficient by using the rock burst prediction model; the maximum rock burst generation coefficient is used as an optimization target, the genetic algorithm is used for optimizing the blasting setting data, and the group with the minimum rock burst generation coefficient is selected as the optimal blasting setting data; and the digital twin platform previews the blasting effect.

The invention relates to the technical field of mine safety, in particular to a rock burst prediction method based on dynamic frequency domain decomposition, relative event coding and dynamic sparse attention. According to the method, data decomposition of Fourier transform, adaptive frequency domain noise reduction, relative event coding and a dynamic sparse attention mechanism are combined, key features in micro-seismic data can be effectively extracted, and the accuracy and robustness of rock burst prediction are improved. The method is excellent in performance in rock burst prediction, the problems of noise interference, error accumulation and the like can be effectively solved, and reliable technical support is provided for accurate early warning of rock burst.

The invention provides a novel multi-source information and damage coupled coal mine rock burst prediction method. The method comprises the following steps that rock mass fracture signals, a three-dimensional stress field and acoustic emission parameters are collected in real time through a micro-seismic monitoring array, an optical fiber stress sensor and a rock sound probe; an LSTM-attention fusion module is adopted to carry out spatio-temporal feature extraction on the collected multi-source data, an attention weight coefficient is generated, and a weighted fusion feature vector is output; calculating the rock mass damage degree based on a statistical damage mechanics Weibull distribution theory; based on the law of conservation of energy and the damage mechanics theory, a dynamic energy threshold function is constructed, the mining time effect and the rock mass damage state are incorporated into a quantitative evaluation system, and a dynamic energy accumulation rate threshold function is established by introducing a time accumulation effect and a damage coupling term; when the real-time energy accumulation rate is larger than or equal to the energy accumulation rate threshold value and the time derivative of the energy accumulation rate is larger than the sudden change threshold value, third-level early warning is triggered. According to the invention, advanced accurate early warning of the rock burst can be realized.

The invention discloses a multi-source information real-time identification and positioning method for a coal mine rock burst risk area. The method comprises the following steps: integrating a micro-seismic system, a rock noise system, a stress system and a geological system to construct an acquisition network; extracting multi-source characteristic indexes and carrying out space-time unification; establishing a dynamic weighted risk fusion model to calculate a comprehensive risk index RI of a three-dimensional grid unit, wherein the weight of the comprehensive risk index RI is dynamically and adaptively adjusted along with mining; based on the RI value, a high-risk area is identified and positioned through three-dimensional visualization, and graded early warning information is generated; according to the invention, a time-space synchronous multi-source information acquisition network is constructed, and uniform preprocessing and feature extraction are carried out on four types of data of microseism, rock noise, stress and geologic structure, so that deep fusion and collaborative analysis of multi-source information are realized, and an information island phenomenon existing in traditional monitoring is overcome; and the judgment on the rock burst risk is more comprehensive.

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 discloses an advanced blasting pressure relief method based on rock burst prediction, and the method achieves the precise recognition and efficient intervention of rock burst risks through the combination of a micro-seismic monitoring technology, energy thermodynamic diagram modeling and an intelligent algorithm. According to the method, micro-seismic data is deeply analyzed, an abnormal activity area is identified, an energy thermodynamic diagram is constructed, a stress concentration situation is visually displayed, and risk level prediction is carried out in combination with historical data, so that early warning accuracy and response timeliness are improved, an optimal blast hole position in a high-risk area is automatically identified by adopting a density-based clustering algorithm, and the early warning efficiency is improved. Classification and directional blasting pressure relief are implemented according to risk levels, local stress is effectively released, the occurrence probability of rock burst is reduced, the overall process is highly automatic, monitoring, prediction, decision making and intervention are integrated, and the method is suitable for various complex coal mine geological environments.