367 results about "Rock burst" patented technology

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 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 a rock burst ultra-deep hole blasting unloading wave absorption coupling prevention method for a steeply inclined coal seam, and belongs to the technical field of coal mining, and the method comprises the following steps: step 1, determining an unloading target rock stratum where a working face top plate and / or bottom plate stress concentration area is located in the steeply inclined coal seam; 2, determining a wave absorbing target rock stratum between the unloading target rock stratum and a roadway on the corresponding side of the working face of the steeply inclined coal seam; 3, arranging a plurality of unloading blast hole groups in the roadway; step 4, arranging a wave absorbing blast hole group at the position where the unloading blast hole group is arranged in the roadway; 5, all the wave absorbing blast holes are detonated, and all the unloading blast holes are detonated; and 6, after blasting is completed, the near-surface surrounding rock of the roadway on the corresponding side subjected to blasting serves as a supporting bearing layer for combined supporting. According to the invention, a three-level cooperative control mechanism of source unloading, propagation weakening and terminal bearing is realized, and steeply inclined coal seam clamping type roof and floor rock burst disasters are prevented fundamentally.

The invention provides a coal mine rock burst dynamic early warning method and device based on microseism. According to the method, dynamic prediction and real-time early warning of the rock burst risk can be realized, the adaptability of the early warning model to the mining process and the geological condition change is improved, the prediction hysteresis is effectively reduced, and the early warning accuracy is improved.

The utility model relates to a constant-resistance yield anchor rod and anchor cable, and belongs to the technical field of civil engineering, rock and soil slope treatment and mining engineering supporting. The anchor rod comprises a yield pipe, a rod body, an extrusion head and a force transmission system, the yield pipe is a straight circular steel pipe, periodic indentation lines are arranged on the middle section of the outer wall of the yield pipe, and constant-resistance energy absorption is achieved through gradual buckling deformation of the indentation lines; the rod body penetrates through an inner cavity of the yield pipe, an extrusion head with hardness higher than that of the pipe wall is fixed at the near end, and a birdcage-shaped expanding device is arranged at the far end to enhance anchoring; the force transmission system ensures the load transmission efficiency through a supporting base plate and a force transmission ring. According to the utility model, the contradiction between material strength and ductility is converted into controllable buckling deformation through structural collaborative design, and the controllable buckling deformation anchor rod has the advantages of low cost, long displacement energy absorption (millimeter-meter level), controllable bearing capacity level (yield pipe > extrusion head > rod body), multi-scene adaptation and the like, and is suitable for rock-soil body support under the conditions of earthquake, rock burst and large deformation of surrounding rock.

The invention belongs to the field of coal mine underground goaf filling methods, and particularly relates to an ultra-long working face goaf inclined strip filling method. According to the method, a plurality of working faces are taken as a group, and fracturing roadways are arranged outside all the working faces. An inclined fracturing roof cutting area is constructed in the basic roof through the fracturing roadway, and the fracturing roof cutting area is constructed into a caving rock mass with fracturing broken waste rock on the two sides, a roof cutting block in the middle and the two inclined sides adjacent to a complete rock stratum. Then, the top cutting block bodies are used as a grouting diffusion face to conduct grouting on the fracturing broken waste rocks around the top cutting block bodies, and a plurality of inclined supporting strips which have high supporting capacity and are formed by mixing the broken waste rocks, the top cutting block bodies and slurry are formed; and the subsidence of the overlying sandstone group is controlled, and rock burst is prevented. Afterwards, the remaining fracturing drill holes, the remaining top cutting drill holes and the remaining grouting drill holes are used for conducting goaf filling on the follow-up working face in sequence, and therefore the problem that the construction work amount of long drill holes of the ultra-long working face is large is solved.

The invention discloses a deep mine rockburst risk dynamic assessment and active prevention and control system, and relates to the technical field of rockburst risk assessment and prevention and control. Comprising a data acquisition module, a preprocessing module, a dynamic evaluation module, an active prevention and control decision module, a prevention and control execution module, a system monitoring and feedback module and a data storage and authority management module, is interacted through a mining intrinsic safety type communication network, adapts to underground working conditions and supports 24-hour operation; the data acquisition module deploys multiple types of monitoring equipment, and dynamically adjusts frequency encryption transmission; the preprocessing module filters noise and interpolates to ensure data integrity; the dynamic evaluation module updates the risk level in combination with indexes and algorithms; the decision-making module matches the prevention and control scheme and needs to be audited; the execution module is in butt joint with equipment control parameters; the monitoring module measures the state calculation effect; and the storage and authority module performs dual-backup, and performs hierarchical authorization trace leaving. According to the method, the problems of lag and low efficiency of traditional rockburst prevention and control are solved, evaluation accuracy and prevention and control efficiency are improved, risk closed-loop management is realized, safety and cost are balanced, and mining safety is guaranteed.

The invention provides a method for predicting an underground rock fracture risk in a carbon dioxide sequestration project, and the method comprises the steps: obtaining carbon dioxide time sequence pressure data of a plurality of monitoring points in a carbon dioxide sequestration region; performing feature analysis on the carbon dioxide time sequence pressure data to obtain spatial features and time features; fusing the spatial features and the time features to obtain space-time fusion features; geological parameters and rock fracture historical data of the carbon dioxide sequestration area are obtained; performing characteristic engineering processing on the geological parameters and the rock fracture historical data to obtain geomechanical characteristics; inputting the space-time fusion features and the geomechanical features into a pre-trained rock fracture prediction model to obtain rock fracture prediction data; wherein the rock fracture prediction model is a CNN-LSTM hybrid model. According to the technical scheme, the underground rock fracture risk in the carbon dioxide sequestration project can be accurately predicted.

The invention discloses a method for controlling rock burst through staged fracturing of a coal mine ground horizontal well. The method comprises the steps that 1, the applicability of controlling the rock burst through staged fracturing of the ground horizontal well is judged; 2, calculating a fracturing anti-impact efficiency index, and obtaining the position of an optimal fracturing target rock stratum; 3, fracturing construction parameters are calculated theoretically; 4, pressure test experiment inspection is conducted, the fracturing construction parameters obtained in the step 3 are optimized, a pump injection pressure-displacement curve of the fractured target rock stratum is obtained, and the displacement under the minimum pump injection pressure is determined through fitting calculation; 5, a numerical model is constructed according to the coal seam and stratum structure, different fracturing parameters are set, a fracturing numerical simulation test is conducted on the target fracturing horizon, and the optimal total liquid quantity parameters corresponding to different fracturing degrees and meeting the expected rock burst prevention and control requirement are obtained; and 6, drilling well fracturing construction is conducted according to the determined fracturing construction parameters. The method is particularly suitable for pressure relief and scour prevention by adopting an L-shaped horizontal well to carry out staged fracturing on a thick and hard roof target rock stratum on the ground.

The invention discloses a rock burst multi-source monitoring intelligent early warning system and method based on edge cloud collaboration. According to the system, a source monitoring module comprises a microseismic sensor, a stress sensor and a displacement sensor; the edge computing node is connected with the multi-source monitoring module; the cloud platform is connected with the edge computing node; the early warning module is connected with the cloud platform and the edge computing node. The method comprises the following steps: arranging the multi-source monitoring module and acquiring original monitoring data; the offset of the sensor is calibrated to obtain accurate multi-source monitoring data; performing feature extraction on the calibrated multi-source monitoring data, and calculating a comprehensive risk index; a dynamic early warning threshold value is set, the comprehensive risk index is compared with the dynamic early warning threshold value, at the moment, an early warning mechanism is triggered, an early warning module is controlled to execute an early warning action, and reminding information is sent to a monitoring terminal. According to the invention, low-delay and high-precision rock burst monitoring can be realized, the mine safety can be effectively improved, and the data transmission delay is reduced.

The invention provides a force-seismic partition comprehensive rock burst monitoring and early warning method. The method comprises the following steps that all statics early warning index critical values and danger levels of areas, 100 meters ahead of a working face, are determined; carrying out weight distribution of similar statics early warning indexes within 100 meters ahead of the working face; determining vibration early warning indexes of the free roadway and the solid coal roadway; dividing the danger level of each vibration early warning index; carrying out weight distribution on each vibration early warning index; evaluating the comprehensive danger level of the mine earthquake precursor index; determining a force-earthquake partition comprehensive danger coefficient according to the weight distribution of the statics early warning index and the mine earthquake precursor index; and evaluating the comprehensive danger level of the force-earthquake partition and preventing and treating countermeasures. According to the method, through double-source disaster-inducing mechanism modeling, partition grading dynamic early warning and a multi-source data fusion system, accurate dynamic grading early warning of rock burst danger grades is finally achieved.

The present application belongs to the field of rock burst risk assessment of deep rock engineering, and particularly relates to a quantitative evaluation method for rock burst tendency of surrounding rock under multiple disturbances, which comprises the following steps: obtaining the distribution depth of excavation damage zone through acoustic testing, and obtaining the average wave velocity of rock mass in the range of original rock zone; obtaining the geological strength index and disturbance factor through the average wave velocity; further obtaining the residual elastic energy of surrounding rock based on the geological strength index and disturbance factor, and evaluating the rock burst tendency of surrounding rock through the residual elastic energy of surrounding rock; the acoustic testing points of surrounding rock are unchanged, and the rock burst tendency of surrounding rock is evaluated after each excavation footage of the working face is completed, until the distribution characteristics of rock burst tendency no longer change obviously, which is taken as the long-term evaluation result of rock burst tendency of surrounding rock. The quantitative evaluation formula of rock burst tendency of surrounding rock considers the rock mass structure effect, which is reflected in the geological strength index, and considers the excavation disturbance effect, which is consistent with the actual situation of engineering construction process, and has strong practicability.

The invention discloses a spatial structure instability rock burst prediction method based on a graph neural network. A plurality of multi-source monitoring sensors are arranged at a plurality of key monitoring nodes; collecting multi-source monitoring data to obtain original monitoring data; preprocessing the original monitoring data to obtain processed multi-source monitoring data; regarding each key monitoring node as a node in a graph, and constructing an edge based on a spatial distance or geological association to form a graph structure; wherein the monitoring data of each key monitoring node is used as a node embedding vector; constructing and training a GCN network, and obtaining a GNN prediction model after training; inputting real-time multi-source monitoring data into the graph structure to obtain a node embedding vector; inputting the node embedding vector into a GNN prediction model for risk prediction, and outputting the risk probability at the current moment; and when the risk probability of any node exceeds the limit, the early warning module is controlled to scan and alarm. According to the system and the method, high-precision and low-cost prediction of the rock burst can be realized, and the mine safety is improved.

The invention relates to the technical field of coal mine rock burst monitoring and early warning, in particular to a rock burst mine micro-seismic data b value calculation method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining original micro-seismic time sequence data of a target monitoring area; preprocessing the original micro-seismic time sequence data to obtain preprocessed micro-seismic time sequence data; performing normalization processing on the preprocessed micro-seismic time sequence data to obtain standardized micro-seismic time sequence data; performing wavelet multi-scale decomposition to obtain a low-frequency approximate component and a high-frequency detail component; carrying out linear fitting by utilizing a Guyden-Ricker law to obtain a multi-scale b-value data set; and constructing and training a long-short-term memory network model, and obtaining a multi-scale b value fusion result as a final b value. Through a wavelet multi-scale decomposition technology, micro-seismic data is adaptively decomposed into components reflecting different time scales, and the limitation of manually setting a single sliding window is eliminated.

The invention relates to a mining overlying strata separation layer fracture ground self-adaptive grouting method, and belongs to the technical field of coal mine rock burst prevention and green coal mining, and the method comprises the following steps: S1, determining the spatial positions of an overlying strata key layer and a subkey layer where the overlying strata generates a separation layer fracture according to the thickness, the physical and mechanical properties and the position of the overlying strata; s2, according to the coal mining thickness and speed, the spatial change rate and distribution of separation fractures of a main key layer and a sub-key layer of the overlying strata are determined, the layer position where ground grouting holes are distributed is pre-judged in advance, and corresponding grouting holes are constructed; s3, the grouting rate is determined according to the spatial change rate of the separation fractures, and the minimum stress of splitting damage of rock stratums adjacent to the separation fractures is calculated in sequence to determine the maximum grouting pressure; and S4, the overall pressure and flow are adjusted in a self-adaptive mode according to the real-time feedback of the pressure and flow of the multiple grouting holes, and the separation layer space is filled in real time.

The invention discloses an underground mine deep mining rockburst monitoring and early warning system, which relates to the technical field of mining, and comprises a sensing module, the output end of the sensing module is communicated with the input end of a wireless network module, the output end of the wireless network module is communicated with the input end of a data acquisition module, and the output end of the data acquisition module is communicated with the input end of a data processing module. The output end of the data acquisition module is communicated with the input end of the Ethernet module, and the output end of the Ethernet module is respectively communicated with the input ends of the terminal display module, the communication module and the early warning decision module. According to the invention, through the sensing module, the data acquisition module and the early warning decision module, real-time acquisition of rock mass multi-dimensional parameters, adaptive coverage monitoring and interference signal filtering are realized, rock burst precursor features are accurately identified, the problems of many monitoring blind areas, large data interference and low identification precision of a traditional fixed sensor network are effectively solved, and the method is suitable for popularization and application. And the real-time performance and the accuracy of deep mining rock burst early warning are obviously improved.

The invention provides a rockburst intelligent early warning method based on cross-modal fusion of while-drilling sensing data and micro-seismic monitoring data, and belongs to the technical field of tunnel and underground engineering safety and disaster prevention and control. The rockburst intelligent early warning method comprises the steps that while-drilling parameters are acquired in real time, and drilling three-dimensional track coordinates are recorded; microseismic event signals induced by drilling disturbance are collected in real time, and seismic source parameters are inverted; preprocessing and time-space alignment are carried out on the collected while-drilling parameters and the microseismic event signals, and an aligned multi-modal feature sequence is generated; inputting the aligned multi-modal feature sequence into a trained rockburst risk prediction model, and outputting a rockburst risk grade probability distributed along the axis of each drilling track; and performing spatial interpolation on the rockburst risk level probability distributed along the axis of each drilling track, generating a three-dimensional rockburst risk probability field in front of the tunnel face, performing three-dimensional visual reconstruction on the three-dimensional rockburst risk probability field, performing risk level judgment according to a three-dimensional risk cloud picture in front of the tunnel face, and automatically issuing a corresponding early warning signal.

The invention discloses a method for predicting rock burst in a remaining coal pillar area based on monitoring data, and the method comprises the steps: constructing a synchronized and denoised basic data layer through the space-time interpolation completion of multiple types of monitoring data and a dual-channel noise suppression mechanism, and achieving the classification response of a sudden change signal and a progressive risk in combination with an adaptive risk weighting strategy, thereby achieving the prediction of the rock burst in the remaining coal pillar area. And meanwhile, by constructing a dynamic graph structure evolved along with time and combining a graph convolutional network and a circulating unit, combined modeling of a space coupling relationship and an evolution trend is realized, and the identification capability of the weak chain risk is improved while the prediction stability is guaranteed.

The invention relates to the technical field of underground engineering monitoring, in particular to an underground cavern monitoring and early warning method and system based on machine learning. The method comprises the following steps: acquiring stratum rock mass parameters and geological structure labels of a target cavern; generating a virtual geological disaster scene data set by using the generative adversarial network; a combined feature tensor of InSAR point cloud phase fluctuation, anchor rod stress meter reading and composite electrode potential gradient is extracted through a time sequence convolution layer; the fusion weight is optimized, and a pre-training strategy network is output; a model independent element learning adapter is adopted, and actual cavern monitoring data are utilized to carry out fine tuning on the pre-training network to obtain a disaster response model; and finally, the potential gradient of the composite electrode is monitored in real time, a displacement and stress cooperative control instruction is generated through the model, and a rockburst risk grade instruction and a target reinforcement area coordinate are issued. According to the method, the physical rationality of the virtual data and the geological adaptation capability and interpretability of the model are effectively improved.

The present application relates to a kind of potential rock burst pit depth quantitative estimation method considering structural plane and excavation disturbance effect, obtain the initial maximum principal stress and rock uniaxial compressive strength of the region to be estimated, preliminary evaluation whether it has the potential to occur rock burst;Surrounding rock is estimated to estimate the scope of excavation damage zone by sound wave test;According to the sound wave test data, the disturbance factor at different depths is estimated;According to the change characteristics of disturbance factor, the height damage zone and weak damage zone range of surrounding rock in excavation damage zone are estimated;Estimate the potential rock burst pit depth of surrounding rock.The present application not only considers rock strength and stress condition, but also considers the influence of structural plane and excavation disturbance on potential rock burst pit depth, uses high-precision, low-cost and convenient sound wave test technology and a small amount of rock indoor strength test can be realized, with greater innovation, practicality, economy and feasibility.

The invention belongs to the field of rock burst prevention and control coal mining methods, and particularly relates to a roof-cutting pressure-relief coal mining method under the stratum condition of a deeply-buried sandstone group. Comprising the following steps: respectively constructing detection drill holes inside and outside a first mining working face, and checking an interface in a stratum in a hydraulic pressure test mode so as to accurately determine a key layer. On the basis, on the basis of gob-side entry retaining, roof cutting drill holes are creatively constructed in a roof cutting special roadway and a transportation roadway correspondingly, so that roof cutting work is conducted on key layers in a bent sinking zone rock stratum, a water flowing fissure zone and a caving zone rock stratum in a roof; therefore, the suspended roof length of a part of the water flowing fractured zone rock stratum and the caving zone rock stratum is reduced but still reserved, the supporting force needing to be borne by the gob-side entry retaining is reduced, and a sheltering space is provided for the gob-side entry retaining. The bent sinking zone rock stratum is subjected to vertical drilling top cutting, and a top cutting transition area is reserved, so that superposition of fracture of the bent sinking zone rock stratum and fracture of the water flowing fissure zone rock stratum can be reduced, and the stratum pressure needing to be borne by gob-side entry retaining is reduced to the maximum extent.

The invention discloses a coal mine rock burst real-time monitoring and early warning system based on multi-source information, and the system comprises a multi-source information collection module which is used for collecting multi-source data; the data transmission and storage module is used for transmitting the data to a ground center for processing and storage; the dynamic risk assessment module is used for generating a comprehensive risk index; the early warning decision and release module is used for dividing early warning levels according to the indexes and releasing the early warning levels; the feedback control interface module is used for automatically linking underground prevention and treatment equipment to execute pressure relief or support measures during high-level early warning; according to the method, the dynamic risk assessment model containing the multi-stage fusion unit is constructed, deep analysis and fusion of multi-source information such as microseism, rock noise, electromagnetic radiation, stress and geologic structure are realized, and multi-element precursor characteristics shown in the rock burst inoculation process can be comprehensively captured, so that the comprehensiveness and accuracy of risk identification are improved, and the risk identification efficiency is improved. The problems of missing report and false report caused by information island and single early warning index of the existing system are solved.

The invention discloses a rock burst intelligent early warning and decision making system and method based on large language model driving. The system is characterized in that a data acquisition module, a data preprocessing module, a domain self-adaption large model module and a multi-agent early warning and decision making module are connected in sequence; the multi-agent early-warning and decision-making module comprises five agents including a seismic source mechanism intelligent analysis early-warning agent, an impact danger early-warning analysis daily report, a rock burst knowledge question and answer agent, a rock burst risk special event analysis agent and a rock burst early-warning and prevention and control auxiliary decision-making agent, and a knowledge database; and the user input module is connected with the rock burst knowledge question-answer agent. The method comprises the following steps: collecting multi-source monitoring data; extracting feature data; carrying out deep semantic understanding and professional reasoning by utilizing a domain self-adaptive large model module; and based on the input data, the multi-agent early warning and decision module outputs result data through a multi-agent communication and negotiation mechanism. According to the invention, accurate early warning and intelligent decision-making of the rock burst risk can be realized.

A rock burst risk dynamic assessment method based on a Bayesian method comprises the steps that a stope working face is divided into M * M regular grids, and each grid serves as an independent assessment unit; collecting geological and mining data, selecting a plurality of influence factors based on historical data and expert knowledge, and quantifying the plurality of influence factors by adopting a static evaluation model; determining weights of a plurality of influence factors by using an analytic hierarchy process, and calculating an initial risk score of each evaluation unit by using a comprehensive index method; normalizing the initial dangerousness score into prior distribution by adopting an S-type function, and constructing an initial dangerousness prior probability field; a power law attenuation model is introduced to calculate influence weights among the evaluation units, and an influence weight matrix is constructed; real-time monitoring data are obtained through a micro-seismic monitoring system, the risk probability of each evaluation unit is updated in real time based on the Bayesian theorem, and dynamic evaluation and evaluation result output are achieved. According to the method, the accuracy and the real-time performance of rock burst risk assessment can be effectively improved.

The invention provides a rockburst risk grading prediction method based on an improved LSTM neural network. The rockburst risk grading prediction method comprises the following steps: S1, collecting rockburst influence factor data; s2, preprocessing the rock burst influence factor data; s3, constructing an improved LSTM, residual connection and SVR collaborative fusion neural network model; s4, performing model training and hyper-parameter optimization; s5, performing double-label coding on the rockburst risk level; s6, performing model performance evaluation and optimization; and S7, performing rockburst risk grading prediction application. According to the method, accurate, efficient and dynamic grading prediction of the rockburst risk can be achieved, the method is suitable for rockburst risk grading prediction of deep underground engineering such as tunnels, mine pits and underground workshops, accurate technical support can be provided for construction safety decision making and protective measure making, and casualties and property losses caused by rockburst disasters are effectively reduced.

The invention relates to the technical field of tunnel and underground engineering safety construction, in particular to a deeply-buried hard rock tunnel micro-seismic monitoring and segmented advanced blasting collaborative pressure relief method which comprises the steps that a pre-constructed micro-seismic monitoring system is arranged along the tunnel wall so as to collect and analyze seismic source parameters of a micro-seismic event; whether a preset early warning threshold value is exceeded is judged according to the judgment result; if yes, segmented advanced blasting pressure relief design is carried out based on the seismic source parameters of the micro-seismic event, so that blasting parameters are obtained; according to the blasting parameters, drilling wall protection and charging blasting are conducted on the tunnel hole wall, so that the blasted tunnel hole wall is obtained; the current surrounding rock response of the tunnel wall after blasting is observed, whether the current surrounding rock response exceeds a preset early warning threshold value or not is judged, if yes, it is judged that pressure relief is effective and tunneling is normal, and if not, blasting parameters are adjusted or pressure relief is supplemented in the next cycle. Therefore, the problems of passive rock burst risk early warning, poor pressure relief effect, extensive parameter control and the like under the high ground stress condition in drilling and blasting method construction of the deeply-buried hard rock tunnel are solved.