440 results about "Blasting vibration" patented technology

The invention discloses a safety risk assessment system based on slope construction, relates to the technical field of slope construction, constructs a complete system composed of a data acquisition module, a dynamic disturbance identification module, a risk assessment module and an intelligent early warning and decision-making module, and acquires multi-source data such as displacement, cracks, pore water pressure, seismic disturbance and blasting vibration at high frequency. The time sequence analysis and disturbance feature extraction algorithm is combined to realize the rapid identification of the sudden disturbance event; risk score prediction is further carried out based on a polynomial regression model, and multi-level early warning is generated through comparison with a set threshold value; and finally, by combining the construction state, the support parameters and the disturbance intensity, a safety control suggestion is dynamically generated, so that the response speed and prediction precision of the system to the sudden slope instability risk are effectively improved, and real-time perception and intelligent management and control of the risk in the slope construction process are realized.

The invention belongs to the technical field of intelligent tunnel engineering, and discloses a tunnel blasting vibration velocity prediction method and system fusing multi-factor intelligent optimization. The method comprises the following steps: acquiring blasting parameters and historical vibration monitoring data; the method comprises the following steps: constructing a data set containing multi-factor characteristics, initializing XGBoost hyper-parameters, carrying out iterative optimization on the XGBoost hyper-parameters by using an SSA algorithm, inputting training set data to train an optimized SSA-XGBoost model, verifying model performance by using a test set, and predicting the performance by comparing with a traditional model; and dynamically adjusting single-section explosive quantity parameters in real time according to the predicted value, generating risk early warning in combination with a safety threshold, and realizing closed-loop optimization of blasting design. According to the method, real-time risk early warning is generated in combination with the safety threshold value and the SSA-XGBoost model, closed-loop optimization of blasting design is achieved by dynamically adjusting blasting parameters, and construction efficiency is improved while construction safety is ensured.

The invention relates to the technical field of artificial intelligence and data processing, in particular to a method for predicting the influence of tunneling blasting on surface building vibration, which specifically comprises the following steps of: collecting a vibration signal generated by blasting operation in a tunneling process and denoising the vibration signal as a sample; according to the energy distribution characteristics of the signals, a spectral clustering algorithm is adopted to generate meta-tasks; performing feature extraction on samples in each meta-task through a neural network model; a hierarchical attention mechanism is adopted to capture time response characteristics of the vibration signals in different time durations, key characteristics of all stages are obtained and fused, a classification feature vector is obtained, and then a classification prediction result of the influence of blasting on surface building vibration is determined according to the classification feature vector; and optimizing the classification prediction process. According to the method, the tunneling blasting vibration data is processed based on the neural network model of the improved meta-learning strategy, and the accuracy of the vibration influence on the surface building and the construction safety can be improved.

The invention provides an experimental system of a hot water force coupling landslide model, which is characterized in that on the basis of a large freezing and thawing environment test box, an artificially manufactured slope model is placed in the large freezing and thawing environment test box, and meanwhile, a rainfall and snowfall system, a slide rail system, a water level control system, a servo loading system, a medium strain rate disturbance system and a data acquisition system are integrated; a complete slope landslide model indoor experiment device under the combined action of freeze thawing-load-seepage is formed and used for simulating slope landslide caused by rainfall and snowfall, blasting vibration, slope body water level change and other conditions, and multi-source heterogeneous data of the whole process of the landslide from the unstable factor accumulation stage, the temporary sliding stage, the sliding stage and the stable stage are obtained.

The invention relates to the technical field of tunnel construction, in particular to a tunnel blasting quality evaluation method based on multi-source data fusion, which comprises the following steps: synchronously acquiring multi-source data such as blasting vibration waveform, shock wave overpressure, dust concentration time sequence and excavation face image through a sensor network and image acquisition equipment arranged in a tunnel; performing preprocessing and time sequence alignment on the data to form a standardized data sample set; multi-dimensional feature vectors representing the blasting effect are extracted from the multi-dimensional feature vectors respectively; fusing various features into a high-dimensional feature vector, training a machine learning model by using historical data and quality grade labels evaluated by experts to establish a mapping relationship between the features and quality grades, and constructing an intelligent evaluation model; and online automatic evaluation and visual result output of the new blasting event are realized. According to the invention, automation, objectization and systematization of blasting quality evaluation are realized, and an efficient and reliable data-driven solution is provided for tunnel construction quality control.

The invention provides a blast vibration peak velocity prediction model generation method, a blast vibration peak velocity prediction method, a blast vibration peak velocity prediction device and blast vibration peak velocity prediction equipment, and belongs to the technical field of engineering blasting. Loss functions of the first physical information neural network model comprise a physical information neural network prediction loss function and an empirical formula prediction loss function, and the empirical formula prediction loss function is used for calculating a mean square error between a prediction value of a preset empirical formula and a preset training set actual value; training the first physical information neural network model based on a preset training set; optimizing and training the complete first physical information neural network model based on a particle swarm optimization algorithm to obtain a second physical information neural network model; and training the second physical information neural network model based on the training set to obtain a blasting vibration peak velocity prediction model. The technical problem that a prediction model generated in the prior art seriously depends on the number of data is effectively solved.

The invention discloses an S-wave seismic phase first arrival identification method based on actually measured blasting-induced particle vibration signals, and relates to the field of negative effect monitoring and safety evaluation of blasting vibration induced by rock blasting excavation, and the method comprises the steps: determining a blasting scheme based on a scanning result; arranging a blasting vibration sensor; acquiring actual measurement waveforms of blasting vibration at different blasting center distances; constructing an S-wave seismic phase first arrival recognition function; and obtaining the first arrival moments of the S-wave seismic phases of the actually measured vibration waveforms at different explosion center distances. Compared with the prior art that the recognition precision of the S wave of the blasting vibration signal under the engineering scale is low and the like, by comprehensively utilizing the differences of the S wave, a noise signal, a P wave and a P wave tail wave in the aspects of energy, frequency, polarization characteristics and the like, recognition parameters such as the ratio of transverse energy to total energy, the polarization degree and the deflection angle are introduced, and the transverse energy serves as a weight coefficient; an S-wave recognition function suitable for actual measurement of blasting vibration is provided, and the technology has the advantages of small recognition error, high efficiency and the like.

The invention provides a shallow-buried tunnel blasting surface vibration waveform prediction method and system, and relates to the technical field of surface vibration waveform prediction, and the method comprises the steps: collecting geological, blasting and environmental parameters of historical and current blasting, and forming a standardized parameter set through three-stage index storage, abnormal value screening and standardization processing; establishing a mapping relation between blasting parameters and a vibration waveform time domain sequence based on an LSTM neural network, and predicting a current blasting vibration waveform; fusing the geological condition influence factors, the environmental sensitivity influence factors and the predicted waveform features to generate a comprehensive safety assessment index; and according to a matching result of the index and a multi-level safety threshold value, the risk is divided into four levels of safety, low risk, medium risk and high risk, and differential management and control are executed, so that accurate prediction and dynamic regulation and control of the blasting vibration risk are realized. According to the invention, the vibration wave propagation process in the shallow tunnel blasting construction can be accurately simulated, so that the influence of blasting can be better evaluated.

The invention discloses a blasting vibration test-based rock mass wave velocity field measurement method, which is applied to a blasting operation area, is consistent with a tunnel blasting propulsion direction, does not need to independently open up a test area, and can obtain rock mass vibration data of a measurement point corresponding to a vibration measurement instrument after blasting only by arranging the vibration measurement instrument on an excavated tunnel bottom plate. According to the method, the rock mass average wave velocity can be rapidly and accurately calculated by combining the pre-measured error time of the vibration measurement instrument, the limitation of the arrangement distance of the vibration measurement instrument is broken through, the measurement range is remarkably expanded, the cost and difficulty of rock mass wave velocity measurement are effectively reduced, wave velocity measurement is completed under the condition that the original property of the rock mass is kept, and the rock mass average wave velocity is calculated. The actual rock mass condition of the blasting construction area is fed back in time, high adaptability to different rock mass properties is achieved, a scientific basis is provided for engineering design and construction, and safety and efficiency of construction are guaranteed.

The invention discloses a rock mass strength parameter identification method and device based on a blasting vibration signal. The method comprises the following steps: acquiring an initial blasting vibration signal; performing preprocessing to obtain a preprocessed blasting vibration signal; component evaluation indexes are calculated through empirical mode decomposition; calculating a strong correlation component signal and a weak correlation component signal; constructing a target blasting vibration signal; calculating a time domain feature vector; calculating a frequency domain feature vector; calculating a time-frequency domain feature vector; constructing an initial joint multi-domain feature vector; performing mutual information principal component analysis on the initial joint multi-domain feature vector to obtain a target joint multi-domain feature vector; constructing a feature information data set; optimizing the random forest model by using a particle swarm optimization algorithm to obtain a rock mass strength parameter identification model; and performing rock mass strength parameter identification by using the rock mass strength parameter identification model. According to the method, rock mass strength parameter identification is realized, the efficiency is improved, and the cost is reduced. The method can be widely applied to the technical field of engineering blasting.

The invention relates to the technical field of tunnel construction, in particular to a blasting vibration signal noise reduction method, computer equipment and a medium, and the noise reduction method comprises the steps: carrying out the adaptive optimization of key parameters of a VMD through a frost ice optimization algorithm, and obtaining an optimized VMD; using the optimized VMD to decompose the actually measured signal of the tunnel blasting vibration to obtain a plurality of intrinsic mode components; calculating the variance contribution rate of each intrinsic mode component, and removing the components of which the variance contribution rates do not exceed 1%; using a wavelet threshold to carry out noise reduction on the residual intrinsic mode components; and reconstructing the intrinsic mode component after noise reduction to obtain a tunnel blasting vibration signal after noise reduction. According to the method, the VMD parameters are optimized through the frost ice optimization algorithm, the tunnel blasting vibration signals are subjected to noise reduction in combination with the wavelet threshold value, the good signal noise reduction effect is achieved, meanwhile, the modal aliasing phenomenon during signal decomposition is effectively restrained, and the problem that key parameters need to be valued depending on experience in the VMD is solved.

The invention relates to the technical field of monitoring and intelligent decision analysis, and discloses a monitoring and intelligent decision system for the influence of holographic blasting vibration on slope stability, and the system comprises a data collection module, a data processing module, an intelligent decision module, and a feedback control module. The method comprises the following steps: dynamically deploying a three-dimensional vibration sensor array based on topographic features; collecting and preprocessing blasting vibration signals and geological data; fusing the physical model and the data driving model to predict vibration propagation; calculating a dynamic safety coefficient and generating a multi-objective optimization scheme; and outputting an early warning instruction and feeding back and adjusting the sensor network configuration. Through a three-dimensional dynamic monitoring network, real-time data processing, a hybrid drive prediction model, multi-target quantitative evaluation and hierarchical early warning regulation and control, the problems of incomplete sensor coverage, early warning delay, prediction deviation, evaluation deficiency and poor scene adaptability are solved, and accurate monitoring and intelligent decision making of blasting vibration influence are realized.

The invention discloses a double-row medium-length hole blasting method for a filling stope. According to the method, a theoretical value range of each blasting parameter is deduced according to field engineering practice, an ore rock blasting crushing mechanism and a blasting parameter theoretical formula. The method comprises the following steps of: constructing a stope blasting model with different hole bottom distances, explosive unit consumption and resistance line combinations by using ANSYS numerical simulation software in combination with physical and mechanical properties of ore rocks and field explosive performance parameters, and preferably selecting double-row medium-length hole blasting parameters according to a chamber effective stress distribution rule and a roof area vibration velocity peak value of the ANSYS blasting model. According to the method, by selecting the double-row optimal medium-length hole blasting parameters, it is guaranteed that ore rocks in the chamber are fully crushed, the effective stress invading the roof and the blasting vibration velocity peak value are reduced, and the roof is prevented from being damaged. And meanwhile, the explosive loading amount is reduced, the economic cost is reduced, and the production efficiency of a mine is improved.

The invention provides a mine slope risk assessment method and system based on multi-source data space-time fusion, and relates to the technical field of mine monitoring, and the method comprises the steps: obtaining geological and engineering data, and constructing a basic model representing a slope three-dimensional space structure; collecting multi-source heterogeneous monitoring data on a mine slope field, and aligning and fusing the multi-source heterogeneous monitoring data with the basic model in a space-time dimension to generate a continuous dynamic parameter field; and setting a data fusion model, and taking the basic model and the dynamic parameter field as input to obtain a four-dimensional space-time fusion risk field. According to the method, the basic model representing the three-dimensional space structure of the slope is constructed, and a unified space-time bearing base is provided for all heterogeneous monitoring data, so that originally isolated data such as GNSS displacement, deep displacement, blasting vibration and underground water level can be fused in a unified coordinate system; the problem of data splitting in the prior art is fundamentally solved, and integral and integrated expression of slope engineering and geological conditions is formed.

The invention provides a grouting curtain parameter design method for structure protection under the blasting vibration effect, and relates to the technical field of underground engineering and blasting engineering, and the grouting curtain parameter design method comprises the following steps: S1, determining main factors influencing the vibration velocity of a protection structure, and constructing a vibration velocity prediction model containing an undetermined coefficient by adopting a dimension analysis white golden-han theorem; s2, establishing a finite element blasting numerical model, and obtaining structural vibration velocity data under different parameter combinations; s3, fitting the structural vibration velocity data by using the vibration velocity prediction model, and determining an undetermined coefficient in the vibration velocity prediction model; and S4, a relational expression between the structural vibration velocity and stress is established, and grouting curtain design parameters meeting structural safety requirements are determined in combination with engineering conditions. By means of the method, the problem that the grouting curtain damping effect and grouting curtain parameters are difficult to determine in actual engineering is solved, the blasting vibration peak value of the protection structure under the blasting vibration effect is effectively reduced, and a guarantee is provided for underground and ground structure protection and blasting engineering safety construction.

The invention provides a method for analyzing the dynamic stability of a slope containing a mining cavern group under the action of dynamic and static loads, and belongs to the technical field of analysis of the dynamic stability of the slope containing the mining cavern group. In order to solve the technical problem that complex mechanical behaviors of a slope containing a mining cave group under the dynamic and static load coupling effect are difficult to accurately consider because most of existing slope stability analysis aims at single static load or dynamic load working conditions, the technical scheme adopted by the invention comprises the following steps: collecting end slope mining coal pillars and rock samples of rock stratums overlying the end slope mining coal pillars, and testing physical and mechanical parameters of the rock samples; the physical and mechanical parameters of all the rock stratums are finally selected in combination with related production materials of the mining area; calculating a shear strength parameter of the rock mass after the rock is damaged under the action of cyclic blasting vibration; calculating shear strength parameters of the end slope mining area-evolved weak layer under the action of blasting vibration; the stability of the slope containing the mining cavern group under the blasting vibration effect is calculated; the method is applied to the stability analysis of the power of the slope containing the mining cavern group.

The invention relates to a blasting vibration rule prediction method and device, electronic equipment and a storage medium. Comprising the following steps: determining main factors influencing the blasting vibration speed and dimensions thereof based on monitoring data of a target blasting site; based on the main factors and the dimensions of the main factors, analyzing a Sadgowski formula by using a dimension analysis principle to determine target factors influencing the blasting vibration speed in the Sadgowski formula; constructing a function form of a blasting vibration rule, and taking the target factors as basic dimensions to obtain a common form of a Sadgowski formula; and based on a common form of a Sadgowski formula, fitting and constructing a new-form blasting vibration law prediction model so as to predict a propagation law of blasting vibration speeds in different directions. Therefore, the method solves the problems that a traditional Sadgowski formula cannot be suitable for complex engineering projects with consideration of influence factors such as a charging structure and a free surface, and cannot guide blasting near-area construction, and improves the effectiveness of blasting vibration prediction.

The invention discloses a comprehensive blasting method for controlling muck pile lumpiness and vibration in surface mine blasting, which comprises the following steps: S1, early-stage preparation and parameter calculation: investigating the geological condition of a mine in detail, and obtaining such information as rock physical and mechanical properties and joint fissure distribution; according to rock properties and mining requirements, blast hole parameters are determined; calculating initial delay detonation time according to a delay blasting rock breaking principle; s2, optimizing a charging structure: selecting a water medium interval charging structure, and determining the optimal unit consumption through theoretical analysis and field test; and based on the optimal unit consumption, establishing three-dimensional models of different water medium interval charging structures by adopting numerical simulation software, and selecting the optimal water medium interval charging structure. According to the method, the muck pile lumpiness is effectively controlled; the blasting vibration intensity is reduced; the blasting quality and the economic benefit are improved; the adaptability is high.

According to the method and device for predicting the blasting vibration waveform, the computer storage medium and the terminal, the random vibration prediction model constructed by modulating the white noise filtering model is used for testing each blast hole to obtain the single-hole waveform of the blast hole, the rock mass characteristics and the charging condition characteristics can be reflected, and the blasting vibration waveform prediction accuracy is improved. The accuracy of the underground blasting vibration prediction result is ensured, the single-hole blasting vibration waveform of related parameters determined according to the single-hole waveform is used as the superposition wavelet, the superposition calculation of the porous blasting vibration is completed, the method can be suitable for different types of porous blasting vibration waveforms, and under the condition that the applicability of the underground blasting vibration prediction result is ensured, the accuracy of the underground blasting vibration prediction result is ensured. A prediction model capable of reflecting porous blasting vibration waveforms such as rock mass characteristics and charging conditions is established, a tool is provided for urban underground space blasting construction, and technical support is provided for urban underground space construction.

The invention belongs to the technical field of blasting vibration prediction, and particularly discloses a blasting vibration speed attenuation law prediction method based on regression analysis, and the method comprises the steps: laying monitoring points in multiple directions around a blasting source, synchronously collecting the geological parameters and mass point peak vibration speed of each point, and constructing a segmented propagation path; a single dominant propagation section is identified based on adjacent monitoring point data, independent influence of specific geological conditions on vibration attenuation is quantified by combining single-factor control regression analysis, decoupling modeling of geological factors and attenuation behaviors is realized, and meanwhile, a double-factor dominant propagation section is identified on the basis of quantizing the independent influence of the single geological conditions. And deducting a known effect through residual analysis to separate out an independent contribution of another geological parameter, and finally integrating a multi-factor influence function to construct a comprehensive attenuation model. Progressive modeling from single-factor decoupling to multi-factor collaboration is achieved, and the precision and physical interpretability of blasting vibration prediction in a complex heterogeneous stratum are remarkably improved.

The invention discloses a mine blasting safety monitoring and early warning system, which comprises a multi-source sensing module, an edge computing node, a dynamic risk assessment module, an intelligent early warning decision module and an emergency linkage execution module, and is characterized in that the multi-source sensing module acquires multi-dimensional data such as blasting vibration, shock waves and toxic gas through various sensors; edge computing nodes filter noise and extract time-frequency features; the dynamic risk assessment module inverts blasting energy based on vibration and shock wave data, and predicts secondary disasters in combination with a geological model and gas concentration; the intelligent early warning decision module dynamically adjusts an early warning threshold by using a deep learning model and fusing multi-modal data; the emergency linkage execution module executes instructions such as power failure and evacuation according to devices such as early warning level, linkage ventilation and personnel positioning, overcomes the defects of traditional single monitoring and lack of correlation models, realizes full-process and all-directional monitoring of blasting operation, and effectively improves the safety of mine blasting operation and the efficiency of emergency management.

The invention discloses a cracking blasting method for controlling blasting vibration of a large stone in a strip mine, which belongs to the technical field of blasting engineering and comprises the following steps: S1, determining a drilling position and depth between a main blasting area and a protection target according to geological conditions and blasting design requirements, and drilling based on the determined drilling position and depth; s2, coupling charge is carried out in each hole, and the charge structure is a single-hole single-sound explosion network; s3, the charging structure in each hole is sequentially detonated in a delayed mode, a rock fracturing belt with cracks distributed in a dendritic mode is formed, blasting vibration is attenuated after being reflected and refracted in the cracks of the rock fracturing belt and is difficult to spread to a protection target, and the purpose of protecting the protection target is achieved; according to the method, the blasting vibration isolation belt is arranged between the main blasting area and the protection target, a rock cracking belt is formed through drilling blasting, blasting vibration is effectively attenuated, the blasting effect is not affected, and the influence of blasting vibration on the protection target can be effectively controlled.

The utility model relates to the technical field of sensors, and discloses a vibration velocity sensor for a blasting vibration meter, which comprises an auxiliary mechanism, a protection mechanism and a testing mechanism, the protection mechanism is arranged at the top end of the auxiliary mechanism, and the testing mechanism is arranged on the surface of the protection mechanism; the auxiliary mechanism comprises a mounting plate, a mounting hole is formed in the middle of the mounting plate, a connecting plate is arranged at the bottom end of the mounting plate, and a connecting screw rod is fixedly connected to the middle of the connecting plate. According to the utility model, the adjusting screw sleeve is arranged, the connecting screw rod passes through the mounting hole of the mounting plate, after the X-axis direction of the indication coordinate points to an explosion source, the sensor is fixed on the ground by using the positioning column, and the adjusting screw sleeve is rotated to adjust the distance between the connecting screw rod and the positioning column so as to adjust the inclination angle of the sensor; after it is observed that a horizontal bubble in the leveling device is located in the center, the connecting plate and the mounting plate are fixed through the fixing nuts, leveling can be completed, and convenience during leveling is improved.

The invention provides a mine vibration safety detection method and system during mining blasting. The method comprises the following steps: acquiring three-component signals of explosion fluctuation at a plurality of sampling points in a warning range through an intelligent sensor network during mine blasting; decomposing each three-component signal into a plurality of attenuation waves, determining cross correlation coefficients of the attenuation waves in the same component direction among different sampling points, and performing reverse time back propagation on each sampling point according to all the cross correlation coefficients to obtain a reverse time wave field of blasting vibration at each sampling point; inputting all the reverse time wave fields into a pre-trained multi-seismic-source positioning model to obtain a plurality of explosion points; and determining the risk value of miss-fire of each blast hole in the detonation network according to the coordinate positions of all the explosion points, and performing explosion aftershock evaluation on the mine according to all the risk values. According to the scheme, the miss-fire risk of each blast hole can be evaluated after mine blasting.

The invention discloses a filling mining method based on stage reverse medium-length hole groove broaching, which relates to the technical field of mining, and comprises the following steps: stope structure parameter design, mining preparation engineering construction, cutting engineering, stoping process and filling process are carried out in sequence, the cutting project comprises the steps of cutting courtyard rapid forming, cutting groove broaching and cutting groove rapid penetrating; and the cutting courtyard is rapidly formed by adopting a laser pre-splitting auxiliary blasting process. According to the method, the cutting and groove broaching processes are deeply optimized, so that the overall efficiency of underground mining is remarkably improved. In the cutting courtyard forming stage, the laser presplitting auxiliary blasting technology is introduced, so that the rock integrity is reduced, the blasting energy is more concentrated, the effect is more accurate, the problems of perforation, rock slag squeezing and the like in the traditional process are effectively avoided, the explosive loading amount can be reduced, disturbance of blasting vibration to surrounding rock is reduced, and the blasting quality is improved. And a safer technical support is provided for high-stress ore body mining.

The invention provides an underground large block secondary crushing device and method based on a robot platform. The device comprises a robot and an expansion cartridge, the robot comprises a robot seat, a drilling mechanical arm, a clamp mechanical arm, a depth camera and a container bin, a drill bit is installed at the tail end of the drilling mechanical arm, a clamp is installed at the tail end of the clamp mechanical arm, and the drilling mechanical arm, the clamp mechanical arm and the depth camera are all connected with a robot platform. The expansion cartridge is stored in the container bin. The mechanical arm is controlled through the robot platform, it is guaranteed that large rock is stably crushed in the complex and changeable underground environment, manual operation is reduced, production safety is guaranteed, and production efficiency is improved; a depth camera is used for accurately positioning the position of a large rock, the position of a blast hole is accurately positioned, and the accuracy of drilling and charging is guaranteed; rock breaking work is carried out through the expansion cartridge, and negative influences of blasting vibration and blasting shock waves on surrounding rock are avoided.

The utility model discloses a surface mine high and steep slope monitoring device and belongs to the technical field of slope monitoring. The surface mine high and steep slope monitoring device comprises a base, the upper surface of the base is fixedly connected with a fixing rod in a penetrating mode, and the top end of the fixing rod is electrically connected with front-end data monitoring equipment. The front-end data monitoring device comprises a surface deformation monitoring device, a deep deformation monitoring device, a blasting vibration monitoring device, an underground water level monitoring device and a settlement monitoring device. Front-end data monitoring equipment is used for monitoring the deformation condition of the whole surface of a side slope, the inclination angle acceleration multifunctional instrument is installed on the side slope boulder outburst dangerous rock mass to monitor the stability condition of the side slope boulder dangerous rock mass, and the inclination angle acceleration multifunctional instrument assists in monitoring the development condition of side slope cracks and is arranged on the penetrating edge at certain intervals through deep clinometers. Monitoring the slippage condition of the fault zone in the drill hole of the potential fault zone of the slope, aiming at the surface mine slope subjected to blasting mining, mounting and arranging along a slope top platform according to a certain interval, and monitoring the overall damage degree of blasting operation to the mine slope.

The invention provides a tunnel blasting vibration reduction method and system based on asymmetric slotting, relates to the technical field of geotechnical engineering numerical simulation, and provides an integrated intelligent blasting vibration reduction system of asymmetric slotting structure optimization-quantum genetic algorithm collaborative optimization-model dynamic regulation. Triple fusion of a physical mechanism, a mathematical algorithm and an information technology of proximity tunnel blasting vibration control is creatively achieved, the bottleneck that a traditional method depends on experience trial and error, model static lag and vibration control and construction efficiency are difficult to consider at the same time is broken through, vibration speed control precision is improved, tunneling efficiency is improved, and meanwhile the construction efficiency is improved. The dynamic adaptability to complex geological conditions is remarkably enhanced, and a new generation of integrated solution is provided for safe, efficient and intelligent construction of the adjacent tunnel.

The invention relates to the technical field of tunnel engineering, in particular to a method and a system for optimizing design parameters based on unsymmetrical pressure tunnel blasting excavation dynamic response. The method comprises the following steps of obtaining geological parameters and construction parameters of surrounding rock of the bias tunnel, constructing a discontinuous structure equivalent damage model, and obtaining initial stress field distribution of a rock mass in combination with the discontinuous structure equivalent damage model, the geological parameters and the construction parameters; analyzing the time-varying modified dynamic mechanical parameters, and calculating through a stress wave propagation path and an energy dissipation rule to obtain a time travel curve of dynamic stress and vibration speed of each point of the surrounding rock in the blasting process; correcting a dynamic response index by using a self-adaptive artificial boundary condition to obtain a dynamic response state characteristic; and on the basis of the initial stress field distribution of the rock mass, the time history curve and the dynamic response state characteristics, optimal design parameters are obtained according to optimal design indexes. According to the method, the balance between the blasting vibration strength and the construction efficiency is realized by optimizing and adjusting the design parameters.

The invention provides a blasting vibration monitoring and influence range prediction method for a long and large tunnel in an environment sensitive area, and relates to the technical field of blasting safety monitoring and vibration control in tunnel engineering, and the method comprises the steps: constructing a three-dimensional dynamic monitoring network, collecting multi-source data based on the three-dimensional dynamic monitoring network, carrying out the preprocessing of the multi-source data, obtaining a blasting vibration feature matrix, and carrying out the prediction of the influence range. Building a prediction model based on the improved LSTM model, training the prediction model based on a preset blasting vibration characteristic matrix and blasting parameters and geological conditions corresponding to the preset blasting vibration characteristic matrix to obtain a trained prediction model, and inputting a to-be-detected blasting vibration characteristic matrix and blasting parameters and geological conditions corresponding to the to-be-detected blasting vibration characteristic matrix into the trained prediction model. And obtaining a prediction result. According to the method, the precision and the real-time performance of blasting vibration monitoring and prediction are remarkably improved, the vibration control problem in blasting construction of the long and large tunnel in the environment sensitive area is effectively solved, the prediction precision is high, the real-time performance is high, the adaptability is high, and the data utilization efficiency is high.