Tunnel blasting influence prediction analysis method and system based on machine vision

Abstract

The invention relates to the field of tunnel blasting influence prediction and analysis, and particularly discloses a tunnel blasting influence prediction and analysis method and system based on machine vision, and the method comprises the steps: collecting the related data of a tunnel blasting project, screening the historical similar blasting projects of the tunnel blasting project according to the related data of the tunnel blasting project, and carrying out the prediction and analysis of the tunnel blasting influence. Further acquiring blasting information of historical similar blasting projects; according to the related data of the tunnel blasting project, a numerical simulation three-dimensional model of the tunnel blasting project is constructed by utilizing numerical simulation software, tunnel blasting is simulated, and blasting information of blasting simulated by a tunnel blasting simulation model is obtained; according to blasting information of blasting simulated by historical similar blasting projects and a tunnel blasting simulation model, the influence of tunnel blasting on structure safety, ground deformation and the surrounding environment is predicted, and then an engineer is helped to optimize blasting design, so that the adverse influence is reduced, and the safety and efficiency of operation are ensured.

Description

Technical Field

[0001] The invention relates to the field of tunnel blasting impact prediction and analysis, and relates to a tunnel blasting impact prediction and analysis method and system based on machine vision. Background Art

[0002] With the acceleration of urbanization, the demand for infrastructure such as transportation networks, water supply systems, and power transmission is increasing. Tunnels are key channels connecting different geographical areas, and their importance is self-evident. Especially in mountainous areas, hills, or densely populated urban areas, ground construction may be restricted by terrain, environment, or space, while tunnels can effectively overcome these obstacles and provide straight-line connections. Tunnel blasting technology can effectively solve the problems in infrastructure construction and resource development, while taking into account economic benefits and environmental protection, which has led to the continuous expansion of its application scope.

[0003] Tunnel blasting impact prediction and analysis is crucial to ensuring project safety, protecting the environment, and controlling costs, and is an indispensable part of modern tunnel engineering.

[0004] However, the existing tunnel blasting impact prediction and analysis methods have some limitations and shortcomings in practical applications.

[0005] For example, the existing Chinese patent with the authorization announcement number CN118153461 B discloses a vibration effect prediction and analysis method and system for interlayer tunnel blasting, which includes the following steps: collecting blasting point data of interlayer tunnels, including the type, thickness and physical properties of geological layers, using blasting point data to simulate the response of the stratum to blasting, and establishing a correlation model between geology and blasting parameters. By collecting tunnel blasting point data and simulating the response of the stratum to blasting, a correlation model between geology and blasting parameters is constructed, and personalized prediction data analysis and model construction of vibration effects are realized, allowing the impact of different blasting schemes on surrounding geological structures to be evaluated, blasting parameters to be optimized, and environmental damage to be effectively reduced. The vibration threshold is adjusted according to the prediction results, and then the blasting design is corrected according to the actual blasting conditions to ensure that the vibration is controlled within the safety limit, thereby improving the accuracy and safety of blasting operations, reducing the impact on surrounding buildings, and optimizing resource utilization and engineering costs.

[0006] For example, the existing Chinese patent with the publication number CN117831655A discloses a method for predicting the range of cracks in surrounding rock blasting damage, including obtaining working condition parameters, constructing a prediction model for the range of cracks in surrounding rock blasting damage, and then obtaining the range of cracks in surrounding rock damage partitions based on the working condition parameters and the range of cracks in surrounding rock damage partitions. Taking into account the principal stress, initial geostress, initial damage, borehole cavity expansion, rock plastic damage and shear dilatancy characteristics in the surrounding rock, the influence mechanism of initial geostress and intermediate principal stress on the range of cracks in surrounding rock blasting damage can be revealed, which can improve the efficiency of blasting surrounding rock and effectively predict the range of cracks in the actual deep tunnel drilling and blasting engineering.

[0007] The above existing technologies have the following deficiencies: (1) When predicting the impact of tunnel blasting, most of them are predicted by constructing mathematical models. The prediction method is relatively simple and is not combined with other prediction methods for comprehensive analysis, such as historical data of similar tunnel blasting events, which makes the results of predicting the impact of tunnel blasting insufficiently reliable and accurate.

[0008] (2) When predicting the impact of tunnel blasting, most of the time, only one aspect of the impact of tunnel blasting is analyzed, such as the vibration effect of tunnel blasting or the scope of damage and cracks caused by tunnel blasting. However, the multi-faceted impacts of tunnel blasting, such as the impact of tunnel blasting on structural safety, the impact on ground deformation, and the impact on the surrounding environment, are not analyzed. As a result, it is impossible to fully understand the possible impacts of tunnel blasting, which is not conducive to optimizing blasting design to reduce adverse effects and ensure the safety and efficiency of operations. Summary of the invention

[0009] In view of this, in order to solve the problems raised in the above background technology, a method and system for predicting and analyzing the impact of tunnel blasting based on machine vision is proposed.

[0010] The technical solution adopted by the present invention to solve the technical problem is as follows: In the first aspect, the present invention provides a method for predicting and analyzing the impact of tunnel blasting based on machine vision, comprising the following steps:

[0011] Step 1: Collection of tunnel blasting related data: Collect relevant data of the tunnel blasting project, including geological and topographic information, boundary condition information and blasting design parameters.

[0012] Step 2. Acquisition of blasting information of similar blasting projects: Acquire relevant data of each historical tunnel blasting project, further screen historical similar blasting projects of the tunnel blasting project, and obtain blasting information of historical similar blasting projects, wherein the blasting information includes seismic effect information, vibration information, stress-strain information, tunnel structure damage information, flying rock fragment information, ground damage information, air shock wave information, sound wave information, and air quality information.

[0013] Step 3: Acquisition of blasting information of tunnel blasting model: Based on the geological and topographic information, boundary condition information and blasting design parameters of the tunnel blasting project, a numerical simulation three-dimensional model of the tunnel blasting project is constructed using numerical simulation software, the tunnel blasting is simulated, and the blasting information of the tunnel blasting simulation model is obtained.

[0014] Step 4. Prediction of the impact of blasting on structural safety: Based on historical similar blasting projects and the tunnel blasting simulation model, the seismic effect information, vibration information, stress-strain information, tunnel structure damage information, and flying rock fragments information of the blasting are simulated, the impact coefficient of the tunnel blasting project on structural safety is analyzed, and feedback is provided.

[0015] Step 5. Prediction of the impact of blasting on ground deformation: Based on the ground damage information of similar historical blasting projects and the tunnel blasting simulation model, the influence coefficient of the tunnel blasting project on ground deformation is analyzed and feedback is provided.

[0016] Step 6. Prediction of the impact of blasting on the surrounding environment: Based on historical similar blasting projects and the tunnel blasting simulation model, simulate the air shock wave information, sound wave information and air quality information of the blasting, analyze the impact coefficient of the tunnel blasting project on the surrounding environment, and provide feedback.

[0017] In a second aspect, the present invention also provides a machine vision-based tunnel blasting impact prediction and analysis system, including: a tunnel blasting related data collection module: used to collect relevant data of tunnel blasting projects, wherein the relevant data includes geological and topographic information, boundary condition information and blasting design parameters.

[0018] The module for acquiring blasting information of similar blasting projects is used to acquire relevant data of each historical tunnel blasting project, further screen the historical blasting projects similar to the tunnel blasting project, and acquire the blasting information of the historical similar blasting projects, wherein the blasting information includes seismic effect information, vibration information, stress-strain information, tunnel structure damage information, flying rock fragment information, ground damage information, air shock wave information, sound wave information, and air quality information.

[0019] Tunnel blasting model blasting information acquisition module: used to construct a numerical simulation three-dimensional model of the tunnel blasting project based on the geological and topographic information, boundary condition information and blasting design parameters of the tunnel blasting project using numerical simulation software, simulate the tunnel blasting, and obtain the blasting information of the tunnel blasting simulation model simulated blasting.

[0020] Blasting impact prediction module for structural safety: used to simulate the seismic effect information, vibration information, stress-strain information, tunnel structure damage information, and flying rock fragment information of blasting based on historical similar blasting projects and tunnel blasting simulation models, analyze the impact coefficient of tunnel blasting projects on structural safety, and provide feedback.

[0021] Blasting impact prediction module on ground deformation: used to simulate ground damage information caused by blasting based on historical similar blasting projects and tunnel blasting simulation models, analyze the impact coefficient of tunnel blasting projects on ground deformation, and provide feedback.

[0022] The module for predicting the impact of blasting on the surrounding environment is used to simulate the air shock wave information, sound wave information and air quality information of blasting based on historical similar blasting projects and tunnel blasting simulation models, analyze the impact coefficient of tunnel blasting projects on the surrounding environment, and provide feedback.

[0023] Database: used to store blasting operation records of various historical tunnel blasting projects.

[0024] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The present invention predicts and analyzes the impact of tunnel blasting by acquiring blasting information of similar historical blasting projects and blasting simulated by tunnel blasting simulation models, and can combine multiple prediction methods for comprehensive analysis, thereby improving the reliability and accuracy of the results of predicting the impact of tunnel blasting.

[0025] 2. The present invention predicts the impact of tunnel blasting on structural safety, ground deformation, surrounding environment and other aspects, which is conducive to comprehensively understanding the possible impacts of tunnel blasting, and further helps to optimize the blasting design to reduce adverse effects and ensure the safety and efficiency of operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0027] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0028] Figure 2 This is a system module connection diagram of the present invention.

[0029] Figure 3 This is a diagram of the tunnel blasting impact prediction and analysis architecture of the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] See also Figure 1 and Figure 3 As shown, the first aspect of the present invention provides a tunnel blasting impact prediction and analysis method based on machine vision, comprising the following steps: Step 1, tunnel blasting related data collection: collecting relevant data of the tunnel blasting project, wherein the relevant data includes geological and topographic information, boundary condition information and blasting design parameters.

[0032] As a preferred solution, the specific analysis process of step one is: obtaining a geological report, a topographic map and a real-life image of the tunnel blasting project area, and obtaining geological and topographic information and boundary condition information of the tunnel blasting project, wherein the geological and topographic information includes rock type, stratum structure, groundwater level, ground stress state, and soil type, and the boundary condition information includes geometric boundary conditions, mechanical boundary conditions, explosion boundary conditions, material properties, and time-related boundary conditions.

[0033] The blasting design parameters of the tunnel blasting project are obtained, wherein the blasting design parameters include the type of explosive, explosive performance, single hole charge, total charge, blasting hole layout, detonation sequence, and time interval. The explosive performance includes the density, explosion velocity, and explosion work of the explosive. The blasting hole layout includes the depth, hole diameter, hole spacing, and row spacing of the blasting holes.

[0034] As a preferred embodiment, the stratum structure includes features such as bedding, joints, and faults.

[0035] As a preferred solution, the ground stress state includes self-weight stress and tectonic stress.

[0036] In a specific embodiment, the geometric boundary condition is a free surface.

[0037] In a specific embodiment, the mechanical boundary conditions include fixed boundaries, stress boundaries, and displacement boundaries.

[0038] In a specific embodiment, the explosion boundary conditions are the location, energy and explosion type of the explosion source.

[0039] In a specific embodiment, the material properties include rock physical and mechanical properties and explosive characteristics, wherein the rock physical and mechanical properties include but are not limited to elastic modulus, Poisson's ratio, compressive strength, tensile strength, density, fracture toughness, etc.

[0040] In a specific embodiment, the time-dependent boundary condition is a dynamic load.

[0041] Step 2. Acquisition of blasting information of similar blasting projects: Acquire relevant data of each historical tunnel blasting project, further screen historical similar blasting projects of the tunnel blasting project, and obtain blasting information of historical similar blasting projects, wherein the blasting information includes seismic effect information, vibration information, stress-strain information, tunnel structure damage information, flying rock fragment information, ground damage information, air shock wave information, sound wave information, and air quality information.

[0042] Exemplarily, the specific analysis process of step 2 is: extracting the blasting operation records of each historical tunnel blasting project stored in the database to obtain relevant data and blasting information of each historical tunnel blasting project.

[0043] The relevant data of each historical tunnel blasting project is compared with the relevant data of the tunnel blasting project to obtain the number of matching sub-items between each historical tunnel blasting project and the tunnel blasting project in geological and topographic information, boundary condition information and blasting design parameters, and the similarity coefficient between each historical tunnel blasting project and the tunnel blasting project is analyzed.

[0044] As a preferred solution, the similarity coefficients of each historical tunnel blasting project and the tunnel blasting project are analyzed. The specific method is to obtain the number of matching sub-items between each historical tunnel blasting project and the tunnel blasting project in geological and topographic information, boundary condition information and blasting design parameters, and record them as a represents the number of the ath historical tunnel blasting project, a=1, 2, ..., b.

[0045] By analyzing the formula Get the similarity coefficient δ between each historical tunnel blasting project and the tunnel blasting project a ,in They respectively represent the influencing factors corresponding to the unit quantity matching sub-items in the preset geological and topographic information, boundary condition information and blasting design parameters. ε1, ε2, and ε3 respectively represent the weight factors of the preset geological and topographic information, boundary condition information and blasting design parameters, and ε1+ε2+ε3=1.

[0046] As a preferred solution, the weight factors of geological and topographic information, boundary condition information and blasting design parameters are set based on the similarity between the three and the similarity between the evaluated tunnel projects. In a specific embodiment, the weight factors of geological and topographic information, boundary condition information and blasting design parameters are 0.4, 0.2 and 0.4 respectively.

[0047] The similarity coefficients of each historical tunnel blasting project and the tunnel blasting project are compared with each other, and the historical tunnel blasting project corresponding to the maximum similarity coefficient is recorded as the historical similar blasting project of the tunnel blasting project.

[0048] According to the blasting information of each historical tunnel blasting project, the blasting information of similar historical blasting projects is screened and obtained.

[0049] As a preferred solution, if the sub-items are feature-type sub-items, such as rock type, explosive type, etc., the sub-items are considered to be matched if they are the same; if the sub-items are numerical sub-items, such as charge amount, blasting hole depth, etc., the sub-items are considered to be matched if the difference between them is less than the set threshold.

[0050] As a preferred option, blasting operation records of historical tunnel blasting projects can be obtained with the help of measuring equipment such as accelerometers, seismometers, sound level meters, pressure sensors and vibration monitors, as well as monitoring methods such as ground monitoring stations, GPS positioning systems, radar interferometry, laser scanning technology and traditional topographic surveying.

[0051] Step 3: Acquisition of blasting information of tunnel blasting model: Based on the geological and topographic information, boundary condition information and blasting design parameters of the tunnel blasting project, a numerical simulation three-dimensional model of the tunnel blasting project is constructed using numerical simulation software, the tunnel blasting is simulated, and the blasting information of the tunnel blasting simulation model is obtained.

[0052] In a specific embodiment, numerical simulation software, such as FLAC3D, is used to build a three-dimensional model of tunnel blasting to simulate the blasting process and its impact on surrounding structures. The numerical simulation methods involved include but are not limited to: finite element method, finite difference method, discrete element method, smoothed particle fluid dynamics, etc.

[0053] In another specific embodiment, a special blasting prediction software, such as BLAST, is used to perform simulations to obtain key data such as vibration, shock waves, and ground deformation of tunnel blasting.

[0054] As a preferred solution, using numerical simulation software to simulate tunnel blasting is an existing relatively mature technology and will not be described in detail here.

[0055] Step 4. Prediction of the impact of blasting on structural safety: Based on historical similar blasting projects and the tunnel blasting simulation model, the seismic effect information, vibration information, stress-strain information, tunnel structure damage information, and flying rock fragments information of the blasting are simulated, the impact coefficient of the tunnel blasting project on structural safety is analyzed, and feedback is provided.

[0056] For example, the specific analysis process of step 4 includes: according to the seismic effect information of similar blasting projects in history, the intensity, peak acceleration and peak velocity of seismic waves of similar blasting projects in history are obtained, which are recorded as c, d and v respectively, and the analysis formula is used to obtain the seismic effect information of similar blasting projects in history. The seismic effect influence factor φ1 of similar historical blasting projects is obtained, where represents the correction coefficient of the preset earthquake effect factor, c设 d 设 、v 设 They respectively represent the thresholds of the preset seismic wave intensity, peak acceleration and peak velocity.

[0057] As a preferred solution, the thresholds of seismic wave intensity, peak acceleration and peak velocity represent the limit values ​​that the tunnel can withstand in the tunnel blasting project. If the limit values ​​are exceeded, the tunnel will be in danger of collapse. The thresholds of seismic wave intensity, peak acceleration and peak velocity can be obtained through field surveys, simulation models, reference to similar tunnels or historical tunnel blasting experience, etc.

[0058] As a preferred solution, seismic effect information of similar historical blasting projects can be measured with the help of a seismograph.

[0059] According to the vibration information of similar blasting projects in the past, the vibration velocity, vibration frequency and surface acceleration caused by blasting of similar blasting projects in the past are obtained, which are recorded as v1, f and d1 respectively. The vibration impact factor φ2 of similar blasting projects in history is obtained, where Indicates the correction coefficient of the preset vibration influence factor, v 1设 、f 设 d 1设 They respectively represent the preset vibration velocity, vibration frequency, and threshold value of the ground acceleration caused by blasting.

[0060] As a preferred solution, the thresholds of vibration velocity, vibration frequency, and ground acceleration caused by blasting represent the limit values ​​that the tunnel can withstand in the tunnel blasting project. If the limit values ​​are exceeded, the tunnel will be in danger of collapse. The thresholds of vibration velocity, vibration frequency, and ground acceleration caused by blasting can be obtained through field surveys, simulation models, reference to similar tunnels or historical tunnel blasting experience, etc.

[0061] According to the stress-strain information of similar blasting projects in history, the maximum stress value and maximum strain value of similar blasting projects in history are obtained, which are recorded as F and s respectively. 变 , by analyzing the formula The stress-strain influence factor φ3 of similar blasting projects in history is obtained, where Represents the correction coefficient of the preset stress-strain influence factor, γ ΔF , γ′ Δs They respectively represent the influence factors corresponding to the preset unit stress value and unit strain value.

[0062] For example, the specific analysis process of step 4 further includes: obtaining the maximum crack length and deformation degree of the tunnel main structure and the tunnel support structure in the historical similar blasting projects according to the tunnel structure damage information of the historical similar blasting projects, and recording them as l1, l2. By analyzing the formula The tunnel structure damage impact factor φ4 of similar blasting projects in history is obtained, where represents the correction coefficient of the preset tunnel structure damage influencing factor, e represents the natural constant, l 1设 , l 2设 , They respectively represent the preset thresholds of crack length and deformation degree of the tunnel main structure and the thresholds of crack length and deformation degree of the tunnel support structure.

[0063] As a preferred solution, the thresholds of crack length and deformation degree of the tunnel main structure and the thresholds of crack length and deformation degree of the tunnel support structure represent the limit value that the tunnel can withstand in the tunnel blasting project. If the limit value is exceeded, the tunnel will be in danger of collapse. The thresholds of crack length and deformation degree of the tunnel main structure and the thresholds of crack length and deformation degree of the tunnel support structure can be obtained through field surveys, simulation models, reference to similar tunnels or historical tunnel blasting experience, etc.

[0064] As a preferred solution, in order to obtain the maximum crack length of the tunnel main structure and the tunnel support structure in similar historical blasting projects, the images of the tunnel main structure and the tunnel support structure before and after the blasting can be collected by a visual sensor, and the images of the tunnel main structure before and after the blasting and the images of the tunnel support structure before and after the blasting can be compared to obtain the maximum crack length of the tunnel main structure and the tunnel support structure in similar historical blasting projects.

[0065] As a preferred solution, the deformation degree of the main tunnel structure and the tunnel support structure in similar historical blasting projects can be obtained by obtaining the spatial models of the main tunnel structure and the tunnel support structure before and after the blasting, fitting the spatial model of the main tunnel structure before and after the blasting, and fitting the spatial model of the tunnel support structure before and after the blasting, and analyzing the overlap respectively, so as to further obtain the deformation degree of the main tunnel structure and the tunnel support structure in similar historical blasting projects.

[0066] As a preferred solution, the deformation of the tunnel structure includes tilting, displacement and twisting.

[0067] According to the information of flying rock fragments in similar blasting projects in the past, the average flying rock size, average particle size of fragments, blast pile volume, and flying area of ​​similar blasting projects in the past were obtained, and they were recorded as d 石均 d 片均 、V 堆 、s 散 .

[0068] By analyzing the formula The impact factor of flying rock fragments in similar blasting projects in history is obtained as φ5, where represents the correction factor of the preset flying rock debris impact factor, d′ 石均 , d′ 片均 , V′ 堆 , s′ 散 They respectively represent the thresholds of the preset flying rock size, fragment size, explosion pile volume, and flying area.

[0069] As a preferred solution, the thresholds of flying rock size, fragment size, blast pile volume, and flying area area represent the limit value that the tunnel can withstand in the tunnel blasting project. If the limit value is exceeded, the tunnel will be in danger of collapse. The thresholds of flying rock size, fragment size, blast pile volume, and flying area area can be obtained through field surveys, simulation models, reference to similar tunnels or historical tunnel blasting experience, etc.

[0070] As a preferred solution, the average size of the flying stones may be area, volume or particle size.

[0071] Exemplarily, the specific analysis process of step 4 also includes: by analyzing the formula The influence coefficient η of similar historical blasting projects on structural safety is obtained 历史 , where κ1, κ 2 , κ3, κ4, and κ5 respectively represent the weights of the preset earthquake effect influence factor, vibration influence factor, stress-strain influence factor, tunnel structure damage influence factor, and flying rock fragment influence factor, and κ1+κ2+κ3+κ4+κ5=1.

[0072] As a preferred solution, the weights of the earthquake effect influence factor, the vibration influence factor, the stress-strain influence factor, the tunnel structure damage influence factor and the flying rock fragment influence factor are set according to the degree of threat posed by the earthquake effect, vibration, stress-strain, tunnel structure damage and flying rock fragments to the tunnel structure safety. In a specific embodiment, the weights of the earthquake effect influence factor, the vibration influence factor, the stress-strain influence factor, the tunnel structure damage influence factor and the flying rock fragment influence factor are 0.2, 0.2, 0.2, 0.2, 0.2, respectively.

[0073] Analyze the influence coefficient of tunnel blasting simulation model on structural safety.

[0074] As a preferred solution, the method of analyzing the influence coefficient of blasting simulated by the tunnel blasting simulation model on the structural safety is based on the same principle as the method of analyzing the influence coefficient of similar historical blasting projects on the structural safety.

[0075] The weighted average of the impact coefficients of blasting on structural safety from similar historical blasting projects and tunnel blasting simulation models is calculated to obtain the impact coefficient of the tunnel blasting project on structural safety, and the coefficient is fed back to the construction supervision department of the tunnel blasting project.

[0076] As a preferred solution, the weights of the impact coefficients of blasting on structural safety simulated by historical similar blasting projects and tunnel blasting simulation models are set values, and the cumulative sum is 1.

[0077] Step 5. Prediction of the impact of blasting on ground deformation: Based on the ground damage information of similar historical blasting projects and the tunnel blasting simulation model, the influence coefficient of the tunnel blasting project on ground deformation is analyzed and feedback is provided.

[0078] Exemplarily, the specific analysis process of step five includes: obtaining ground displacement information, ground settlement information, and ground crack information of similar historical blasting projects based on ground damage information of similar historical blasting projects.

[0079] According to the ground displacement information of similar blasting projects in history, the horizontal and vertical displacements of the ground after blasting in similar blasting projects in history are obtained, and the influencing factors of ground displacement in similar blasting projects in history are analyzed.

[0080] As a preferred solution, the horizontal displacement and vertical displacement of the ground after blasting in similar historical blasting projects are substituted into the preset relationship function between the horizontal displacement and vertical displacement of the ground and the ground displacement influencing factor to obtain the ground displacement influencing factor of similar historical blasting projects.

[0081] According to the ground subsidence information of similar blasting projects in history, the ground subsidence depth, subsidence rate and subsidence area of ​​similar blasting projects in history are obtained, and the influencing factors of ground subsidence of similar blasting projects in history are analyzed.

[0082] As a preferred solution, the ground settlement depth, settlement rate and settlement area of ​​historical similar blasting projects are substituted into the preset relationship function between the ground settlement depth, settlement rate and settlement area and the ground settlement influence factor to obtain the ground settlement influence factor of historical similar blasting projects.

[0083] As a preferred solution, the ground settlement depth refers to the amount of ground drop relative to before blasting.

[0084] As a preferred solution, the subsidence rate refers to the speed at which the ground drops per unit time.

[0085] As a preferred solution, the settlement area refers to the area of ​​the surface area affected by the blasting.

[0086] According to the ground crack information of similar blasting projects in history, the maximum length, maximum width, maximum depth and density of ground cracks in similar blasting projects in history are obtained, and the influencing factors of ground cracks in similar blasting projects in history are analyzed.

[0087] As a preferred solution, the maximum length, maximum width, maximum depth and density of ground cracks in similar historical blasting projects are substituted into the preset relationship function between the maximum length, maximum width, maximum depth and density of ground cracks and the ground cracks influencing factor to obtain the ground cracks influencing factor of similar historical blasting projects.

[0088] As a preferred solution, the density of cracks refers to the number of cracks per unit area.

[0089] The weighted average of the ground displacement influencing factors, ground settlement influencing factors and ground crack influencing factors of similar historical blasting projects was calculated to obtain the influence coefficient of similar historical blasting projects on ground deformation.

[0090] As a preferred solution, the weights of the ground displacement influence factor, the ground settlement influence factor and the ground crack influence factor are set values, and the cumulative sum is 1.

[0091] Exemplarily, the specific analysis process of step five further includes: analyzing the influence coefficient of the tunnel blasting simulation model on the ground deformation caused by the simulated blasting.

[0092] As a preferred solution, the method of analyzing the influence coefficient of blasting simulated by the tunnel blasting simulation model on ground deformation is the same as the method of analyzing the influence coefficient of similar historical blasting projects on ground deformation, and the principle is the same.

[0093] The influence coefficient of blasting on ground deformation simulated by similar historical blasting projects and tunnel blasting simulation model was calculated by weighted average, and the influence coefficient of tunnel blasting project on ground deformation was obtained.

[0094] As a preferred solution, the weights of the influence coefficients of blasting on ground deformation simulated by similar historical blasting projects and the tunnel blasting simulation model are set values, and the cumulative sum is 1.

[0095] Step 6. Prediction of the impact of blasting on the surrounding environment: Based on historical similar blasting projects and the tunnel blasting simulation model, simulate the air shock wave information, sound wave information and air quality information of the blasting, analyze the impact coefficient of the tunnel blasting project on the surrounding environment, and provide feedback.

[0096] Exemplarily, the specific analysis process of step six includes: obtaining the overpressure and overpressure duration of the air shock waves of similar historical blasting projects based on the air shock wave information of similar historical blasting projects, and analyzing the air shock wave influencing factors of similar historical blasting projects.

[0097] As a preferred solution, the overpressure and overpressure duration of air shock waves in similar historical blasting projects are substituted into a preset relationship function between the overpressure, overpressure duration and air shock wave influencing factor of air shock waves to obtain the air shock wave influencing factor of similar historical blasting projects.

[0098] According to the sound wave information of similar blasting projects in history, the sound pressure level, frequency, duration, and sound level fluctuation of the sound waves of similar blasting projects in history are obtained, and the sound wave influencing factors of similar blasting projects in history are analyzed.

[0099] As a preferred solution, the sound pressure level, frequency, duration, and sound level fluctuation of sound waves from similar historical blasting projects are substituted into a preset relationship function between the sound pressure level, frequency, duration, sound level fluctuation and sound wave influencing factor to obtain the sound wave influencing factor of similar historical blasting projects.

[0100] Based on the air quality information of similar blasting projects in the past, the dust concentrations and emission concentrations of various harmful gases generated by blasting in similar blasting projects in the past were obtained, and the air quality influencing factors of similar blasting projects in the past were analyzed.

[0101] As a preferred solution, the dust concentration and various harmful gas emission concentrations generated by blasting in similar historical blasting projects are substituted into the preset relationship function between dust concentration, various harmful gas emission concentrations and air quality impact factors to obtain the air quality impact factors of similar historical blasting projects.

[0102] The weighted average of the air shock wave impact factor, sound wave impact factor, and air quality impact factor of similar historical blasting projects was calculated to obtain the impact coefficient of similar historical blasting projects on the surrounding environment.

[0103] As a preferred solution, the weights of the air shock wave influence factor, the sound wave influence factor, and the air quality influence factor are set values, and the cumulative sum is 1.

[0104] Exemplarily, the specific analysis process of step six also includes: analyzing the influence coefficient of the tunnel blasting simulation model on the surrounding environment.

[0105] As a preferred solution, the method of analyzing the influence coefficient of blasting simulated by the tunnel blasting simulation model on the surrounding environment is based on the same principle as the method of analyzing the influence coefficient of similar historical blasting projects on the surrounding environment.

[0106] The weighted average of the impact coefficients of similar historical blasting projects and tunnel blasting simulation models on the surrounding environment was calculated to obtain the impact coefficient of the tunnel blasting project on the surrounding environment.

[0107] As a preferred solution, the weights of the impact coefficients of blasting on the surrounding environment simulated by historical similar blasting projects and the tunnel blasting simulation model are set values, and the cumulative sum is 1.

[0108] In this embodiment, the present invention predicts and analyzes the impact of tunnel blasting by acquiring blasting information of similar historical blasting projects and blasting simulated by a tunnel blasting simulation model. It can combine multiple prediction methods for comprehensive analysis, thereby improving the reliability and accuracy of the results of predicting the impact of tunnel blasting.

[0109] In this embodiment, the present invention predicts the impact of tunnel blasting on structural safety, ground deformation, surrounding environment and other aspects, which is conducive to comprehensively understanding the possible impacts of tunnel blasting, and further helps to optimize the blasting design to reduce adverse effects and ensure the safety and efficiency of operations.

[0110] See also Figure 2 As shown, the second aspect of the present invention provides a tunnel blasting impact prediction and analysis system based on machine vision, including a tunnel blasting related data collection module, a blasting information acquisition module for similar blasting projects, a tunnel blasting model blasting information acquisition module, a blasting impact prediction module for structural safety, a blasting impact prediction module for ground deformation, a blasting impact prediction module for surrounding environment, and a database.

[0111] The blasting information acquisition module for similar blasting projects is respectively connected to the tunnel blasting related data collection module and the tunnel blasting model blasting information acquisition module, the tunnel blasting model blasting information acquisition module is respectively connected to the blasting impact prediction module on structural safety, the blasting impact prediction module on ground deformation and the blasting impact prediction module on surrounding environment, and the database is connected to the blasting information acquisition module for similar blasting projects.

[0112] The tunnel blasting related data collection module is used to collect relevant data of the tunnel blasting project, wherein the relevant data includes geological and topographic information, boundary condition information and blasting design parameters.

[0113] The blasting information acquisition module for similar blasting projects is used to obtain relevant data of each historical tunnel blasting project, further screen historical similar blasting projects of tunnel blasting projects, and obtain blasting information of historical similar blasting projects, wherein the blasting information includes seismic effect information, vibration information, stress and strain information, tunnel structure damage information, flying rock fragment information, ground damage information, air shock wave information, sound wave information, and air quality information.

[0114] The tunnel blasting model blasting information acquisition module is used to construct a numerical simulation three-dimensional model of the tunnel blasting project based on the geological and topographic information, boundary condition information and blasting design parameters of the tunnel blasting project using numerical simulation software, simulate the tunnel blasting, and obtain blasting information of the tunnel blasting simulation model simulated blasting.

[0115] The blasting impact prediction module for structural safety is used to simulate the seismic effect information, vibration information, stress-strain information, tunnel structure damage information, and flying rock fragment information of blasting based on historical similar blasting projects and tunnel blasting simulation models, analyze the impact coefficient of tunnel blasting projects on structural safety, and provide feedback.

[0116] The blasting impact on ground deformation prediction module is used to simulate ground damage information caused by blasting based on historical similar blasting projects and tunnel blasting simulation models, analyze the impact coefficient of the tunnel blasting project on ground deformation, and provide feedback.

[0117] The blasting impact prediction module on the surrounding environment is used to simulate the air shock wave information, sound wave information and air quality information of the blasting according to historical similar blasting projects and the tunnel blasting simulation model, analyze the impact coefficient of the tunnel blasting project on the surrounding environment, and provide feedback.

[0118] The database is used to store the blasting operation records of various historical tunnel blasting projects.

[0119] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A machine vision-based tunnel blasting impact prediction and analysis method, characterized in that: The steps include: Step 1: Tunnel blasting related data collection: Collect relevant data of the tunnel blasting project, including geological and topographic information, boundary condition information and blasting design parameters; Step 2: Acquisition of blasting information of similar blasting projects: Acquiring relevant data of each historical tunnel blasting project, further screening historical similar blasting projects of the tunnel blasting project, and acquiring blasting information of historical similar blasting projects, wherein the blasting information includes seismic effect information, vibration information, stress and strain information, tunnel structure damage information, flying rock fragment information, ground damage information, air shock wave information, sound wave information, and air quality information; Step 3: Acquisition of blasting information of tunnel blasting model: Based on the geological and topographic information, boundary condition information and blasting design parameters of the tunnel blasting project, a numerical simulation three-dimensional model of the tunnel blasting project is constructed using numerical simulation software, the tunnel blasting is simulated, and blasting information of the tunnel blasting simulation model is obtained; Step 4: Prediction of the impact of blasting on structural safety: Based on historical similar blasting projects and the tunnel blasting simulation model, the seismic effect information, vibration information, stress and strain information, tunnel structure damage information, and flying rock fragments information of the blasting are simulated, and the impact coefficient of the tunnel blasting project on structural safety is analyzed and feedback is provided; Step 5: Prediction of the impact of blasting on ground deformation: Based on the ground damage information of similar blasting projects in history and the tunnel blasting simulation model, the influence coefficient of the tunnel blasting project on ground deformation is analyzed and feedback is provided; Step 6. Prediction of the impact of blasting on the surrounding environment: Based on historical similar blasting projects and the tunnel blasting simulation model, simulate the air shock wave information, sound wave information and air quality information of the blasting, analyze the impact coefficient of the tunnel blasting project on the surrounding environment, and provide feedback.

2. The method for predicting and analyzing the impact of tunnel blasting based on machine vision according to claim 1, characterized in that: The specific analysis process of step 2 is as follows: Extract the blasting operation records of each historical tunnel blasting project stored in the database to obtain relevant data and blasting information of each historical tunnel blasting project; Compare the relevant data of each historical tunnel blasting project with the relevant data of the tunnel blasting project, obtain the number of matching sub-items between each historical tunnel blasting project and the tunnel blasting project in geological and topographic information, boundary condition information and blasting design parameters, and analyze the similarity coefficient between each historical tunnel blasting project and the tunnel blasting project; The similarity coefficients of each historical tunnel blasting project and the tunnel blasting project are compared with each other, and the historical tunnel blasting project corresponding to the maximum similarity coefficient is recorded as the historical similar blasting project of the tunnel blasting project; According to the blasting information of each historical tunnel blasting project, the blasting information of similar historical blasting projects is screened and obtained.

3. The method for predicting and analyzing the impact of tunnel blasting based on machine vision according to claim 1 is characterized in that: The specific analysis process of step 4 includes: According to the seismic effect information of similar blasting projects in history, the intensity, peak acceleration and peak velocity of seismic waves of similar blasting projects in history are obtained, which are recorded as c, d and v respectively. The seismic effect influence factor φ1 of similar historical blasting projects is obtained, where represents the correction coefficient of the preset earthquake effect factor, c 设 d 设 、v 设 Respectively represent the thresholds of the preset seismic wave intensity, peak acceleration and peak velocity; According to the vibration information of similar blasting projects in the past, the vibration velocity, vibration frequency and surface acceleration caused by blasting of similar blasting projects in the past are obtained, which are recorded as v1, f and d1 respectively. The vibration impact factor φ2 of similar blasting projects in history is obtained, where Indicates the correction coefficient of the preset vibration influence factor, v 1设 、f 设 d 1设 They represent respectively the preset vibration velocity, vibration frequency, and threshold value of ground acceleration caused by blasting; According to the stress-strain information of similar blasting projects in history, the maximum stress value and maximum strain value of similar blasting projects in history are obtained, which are recorded as F and s respectively. 变 , by analyzing the formula The stress-strain influence factor φ3 of similar blasting projects in history is obtained, where Represents the correction coefficient of the preset stress-strain influence factor, γ ΔF , γ′ Δs They respectively represent the influence factors corresponding to the preset unit stress value and unit strain value.

4. The method for predicting and analyzing the impact of tunnel blasting based on machine vision according to claim 3 is characterized by: The specific analysis process of step 4 also includes: According to the tunnel structure damage information of similar blasting projects in the past, the maximum crack length and deformation degree of the tunnel main structure and tunnel support structure in similar blasting projects in the past are obtained, which are recorded as l1, l2. By analyzing the formula The tunnel structure damage impact factor φ4 of similar blasting projects in history is obtained, where represents the correction coefficient of the preset tunnel structure damage influencing factor, e represents the natural constant, l 1设 , l 2设 , Respectively represent the threshold values ​​of the crack length and deformation degree of the tunnel main structure and the threshold values ​​of the crack length and deformation degree of the tunnel support structure; According to the information of flying rock fragments in similar blasting projects in the past, the average flying rock size, average particle size of fragments, blast pile volume, and flying area of ​​similar blasting projects in the past were obtained, and they were recorded as d 石均 d 片均 、V 堆 、s 散 ; By analyzing the formula The impact factor of flying rock fragments in similar blasting projects in history is obtained as φ5, where represents the correction factor of the preset flying rock debris impact factor, d′ 石均 , d′ 片均 、V 堆 ′、s′ 散 They respectively represent the thresholds of the preset flying rock size, fragment size, explosion pile volume, and flying area.

5. The method for predicting and analyzing the impact of tunnel blasting based on machine vision according to claim 4 is characterized in that: The specific analysis process of step 4 also includes: By analyzing the formula The influence coefficient η of similar historical blasting projects on structural safety is obtained 历史 , where κ1, κ2, κ3, κ4, and κ5 represent the weights of the preset earthquake effect influence factor, vibration influence factor, stress-strain influence factor, tunnel structure damage influence factor, and flying rock debris influence factor, respectively, and κ1+κ2+κ3+κ4+κ5=1; Analyze the influence coefficient of tunnel blasting simulation model on structural safety; The weighted average of the impact coefficients of blasting on structural safety from similar historical blasting projects and tunnel blasting simulation models is calculated to obtain the impact coefficient of the tunnel blasting project on structural safety, and the coefficient is fed back to the construction supervision department of the tunnel blasting project.

6. The method for predicting and analyzing the impact of tunnel blasting based on machine vision according to claim 1, characterized in that: The specific analysis process of step 5 includes: Based on the ground damage information of similar blasting projects in the past, the ground displacement information, ground settlement information, and ground crack information of similar blasting projects in the past are obtained; Based on the ground displacement information of similar blasting projects in the past, the horizontal and vertical displacements of the ground after blasting in similar blasting projects in the past are obtained, and the influencing factors of ground displacement in similar blasting projects in the past are analyzed; Based on the ground settlement information of similar blasting projects in the past, the ground settlement depth, settlement rate and settlement area of ​​similar blasting projects in the past are obtained, and the ground settlement influencing factors of similar blasting projects in the past are analyzed; Based on the ground crack information of similar blasting projects in the past, the maximum length, maximum width, maximum depth and density of ground cracks in similar blasting projects in the past are obtained, and the influencing factors of ground cracks in similar blasting projects in the past are analyzed; The weighted average of the ground displacement influencing factors, ground settlement influencing factors and ground crack influencing factors of similar historical blasting projects was calculated to obtain the influence coefficient of similar historical blasting projects on ground deformation.

7. The method for predicting and analyzing the impact of tunnel blasting based on machine vision according to claim 6 is characterized by: The specific analysis process of step 5 also includes: Analyze the influence coefficient of tunnel blasting simulation model on ground deformation; The influence coefficient of blasting on ground deformation simulated by similar historical blasting projects and tunnel blasting simulation model was calculated by weighted average, and the influence coefficient of tunnel blasting project on ground deformation was obtained.

8. The method for predicting and analyzing the impact of tunnel blasting based on machine vision according to claim 1 is characterized by: The specific analysis process of step six includes: Based on the air shock wave information of similar blasting projects in history, the overpressure and overpressure duration of the air shock wave of similar blasting projects in history are obtained, and the air shock wave influencing factors of similar blasting projects in history are analyzed; Based on the sound wave information of similar blasting projects in the past, the sound pressure level, frequency, duration, and sound level fluctuation of the sound waves of similar blasting projects in the past are obtained, and the sound wave influencing factors of similar blasting projects in the past are analyzed; Based on the air quality information of similar blasting projects in the past, the dust concentration and various harmful gas emission concentrations generated by blasting in similar blasting projects in the past were obtained, and the air quality influencing factors of similar blasting projects in the past were analyzed; The weighted average of the air shock wave impact factor, sound wave impact factor, and air quality impact factor of similar historical blasting projects was calculated to obtain the impact coefficient of similar historical blasting projects on the surrounding environment.

9. The method for predicting and analyzing the impact of tunnel blasting based on machine vision according to claim 8, characterized in that: The specific analysis process of step six also includes: Analyze the influence coefficient of tunnel blasting simulation model on the surrounding environment; The weighted average of the impact coefficients of similar historical blasting projects and tunnel blasting simulation models on the surrounding environment was calculated to obtain the impact coefficient of the tunnel blasting project on the surrounding environment.

10. A machine vision-based tunnel blasting impact prediction and analysis system, characterized in that: include: Tunnel blasting related data collection module: used to collect relevant data of tunnel blasting projects, including geological and topographic information, boundary condition information and blasting design parameters; The module for acquiring blasting information of similar blasting projects is used to acquire relevant data of each historical tunnel blasting project, further screen the historical similar blasting projects of the tunnel blasting project, and acquire the blasting information of the historical similar blasting projects, wherein the blasting information includes seismic effect information, vibration information, stress strain information, tunnel structure damage information, flying rock fragment information, ground damage information, air shock wave information, sound wave information, and air quality information; Tunnel blasting model blasting information acquisition module: used to construct a numerical simulation three-dimensional model of the tunnel blasting project based on the geological and topographic information, boundary condition information and blasting design parameters of the tunnel blasting project using numerical simulation software, simulate the tunnel blasting, and obtain the blasting information of the tunnel blasting simulation model; Blasting impact prediction module for structural safety: used to simulate the seismic effect information, vibration information, stress-strain information, tunnel structure damage information, and flying rock fragment information of blasting based on historical similar blasting projects and tunnel blasting simulation models, analyze the impact coefficient of tunnel blasting projects on structural safety, and provide feedback; Blasting impact prediction module on ground deformation: used to simulate ground damage information caused by blasting based on historical similar blasting projects and tunnel blasting simulation models, analyze the impact coefficient of tunnel blasting projects on ground deformation, and provide feedback; The module for predicting the impact of blasting on the surrounding environment is used to simulate the air shock wave information, sound wave information and air quality information of blasting based on historical similar blasting projects and tunnel blasting simulation models, analyze the impact coefficient of the tunnel blasting project on the surrounding environment, and provide feedback; Database: used to store blasting operation records of various historical tunnel blasting projects.

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