Detection device for blasting of surrounding rock of oil storage cave depot with ultra-large cross section

Abstract

The invention discloses a detection device for blasting of surrounding rock of an oil storage cave depot with a super-large section, and belongs to the technical field of blasting detection, the detection device comprises a device body and a blasting analysis system in an integrated controller, the system comprises a blasting environment analysis module, a blasting environment analysis module, a blasting environment analysis module and a blasting environment analysis module, outputting an environment state coefficient based on the vibration speed peak value and the dust concentration; the blasting damage analysis module outputs a damage coefficient based on the displacement, the gradient and the sound wave drop amplitude; the blasting damage prediction module is used for outputting a damage coefficient in combination with the environment and damage coefficient, the charge compactness and the pitch index; and the explosive quantity analysis module dynamically optimizes the target explosive quantity according to the damage coefficient. According to the invention, real-time evaluation of blasting damage and accurate control of explosive load are realized, and the stability of surrounding rocks is guaranteed.

Description

Technical Field

[0001] The present invention belongs to the technical field of blasting detection, and particularly relates to a detection device for surrounding rock blasting of an extra-large cross-section oil storage cavern. Background Technique

[0002] During the blasting construction of an extra-large cross-section oil storage cavern, the control of surrounding rock stability is of crucial importance. Traditional methods mainly rely on empirical formulas and static safety thresholds, and it is difficult to quantitatively analyze the synergistic effect of blasting damage and environmental risks in real time. Existing detection devices have the following limitations:

[0003] 1) It is unable to integrate multi-dimensional environmental parameters such as vibration velocity and dust concentration;

[0004] 2) It lacks a comprehensive damage assessment of borehole displacement, inclination, and acoustic wave reduction;

[0005] 3) The adjustment of charge amount lags behind, resulting in the risk of over-excavation or under-excavation of the surrounding rock.

[0006] Therefore, there is an urgent need for a detection device that can dynamically predict blasting damage and intelligently optimize the charge amount. Summary of the Invention

[0007] Aiming at the deficiencies of the existing technology, the present invention provides a detection device for surrounding rock blasting of an extra-large cross-section oil storage cavern, which solves the above problems.

[0008] To achieve the above objectives, the present invention is realized through the following technical solutions: A detection device for surrounding rock blasting of an extra-large cross-section oil storage cavern, including a device body, further including:

[0009] A blasting analysis system, integrally installed in a controller embedded in the upper cover of the device body, including:

[0010] A blasting environment analysis module, which constructs an environmental state model based on the peak value of blasting vibration velocity and dust concentration and outputs an environmental state coefficient;

[0011] A blasting damage analysis module, which constructs a blasting damage model based on the displacement at the deepest part of the borehole measured by a multi-point displacement meter, the borehole inclination, and the ultrasonic wave reduction of the borehole before and after blasting, and outputs a blasting damage coefficient;

[0012] A blasting failure prediction analysis module, which constructs a blasting failure model based on the current environmental state coefficient, blasting damage coefficient, single-point charge density, and blasting point spacing, and outputs a blasting failure coefficient;

[0013] A charge amount analysis module, which constructs a charge amount analysis model based on the blasting failure coefficient and the current single-point charge amount and outputs the target single-point charge amount.

[0014] Based on the above technical solutions, the present invention also provides the following optional technical solutions:

[0015] Further technical solution: The charge amount analysis model is expressed as:

[0016]

[0017] Wherein, represents the target charge amount, represents the current charge amount, represents the blasting damage prediction coefficient, represents the safety value of the blasting damage coefficient, represents the blasting damage coefficient, represents the warning value of the blasting damage coefficient, represents the over-width band.

[0018] Further technical solution: The steps of the blasting damage prediction and analysis module are as follows:

[0019] Perform a ratio process on the reference hole spacing and the current blasting point spacing to obtain the blasting point distance index, and perform a ratio process on the current single-point charge density and the maximum allowable charge density to obtain the charge density index;

[0020] Construct a blasting damage model based on the charge density index and the blasting point distance index under the current environmental state coefficient and the blasting damage coefficient, and output the blasting damage prediction coefficient;

[0021] The blasting damage model is expressed as:

[0022]

[0023] Wherein, represents the blasting damage prediction coefficient, represents the environmental state coefficient, represents the blasting damage coefficient, represents the charge density index, represents the blasting point distance index, represents the sensitivity coefficient, represents the hole spacing sensitivity index.

[0024] Further technical solution: The steps of the blasting environment analysis module are as follows:

[0025] Perform a ratio process on the obtained peak blasting vibration velocity and the maximum vibration safety value to obtain the vibration index;

[0026] Perform a ratio process on the obtained dust concentration and the maximum dust concentration value to obtain the dust concentration index;

[0027] Construct an environmental state model based on the vibration index and the dust concentration index, and output the environmental state coefficient;

[0028] The environmental state model is expressed as:

[0029]

[0030] Wherein, represents the environmental state coefficient, represents the vibration index, represents the dust concentration index, represents the weight coefficient and .

[0031] Further technical solution: The steps of the blasting damage analysis module are as follows:

[0032] Ratio process the displacement amount at the deepest part of the drill hole, the inclination angle, and the ultrasonic wave amplitude reduction respectively with the corresponding maximum values, so as to obtain the displacement index, the angular deviation index, and the wave velocity amplitude reduction index;

[0033] Construct a blasting damage model based on the displacement index (the most direct index for quantifying blasting damage), the angular deviation index (reflecting shear damage), and the wave velocity amplitude reduction index (reflecting the integrity of the rock mass) to output the blasting damage coefficient;

[0034] The blasting damage model is expressed as:

[0035]

[0036] Wherein, represents the blasting damage coefficient, represents the displacement index, represents the angular deviation index, represents the wave velocity amplitude reduction index, represents the damage sensitivity index, represents the weight coefficient and .

[0037] Further technical solution: It further includes:

[0038] A multi-point displacement meter, which can be disassembled and installed in the device body, and is used to quantify the deformation amount of the surrounding rock caused by blasting;

[0039] An inclinometer, which can be embedded and installed in the device body, and is used to measure the inclination of the drill hole after blasting;

[0040] An acoustic wave sensor, which can be embedded and installed in the device body, and is used to obtain the ultrasonic wave amplitude reduction in the drill hole before and after blasting.

[0041] Further technical solution: Slots A for placing the multi-point displacement meter, slot B for placing the inclinometer, and slot C for placing the acoustic wave sensor are provided on the device body

[0042] The present invention provides a detection device for surrounding rock blasting of an extra-large cross-section oil storage cavern, which has the following beneficial effects compared with the prior art:

[0043] 1. Through the coordination of the environmental state model (blasting vibration, dust) and the damage model (displacement, inclination, acoustic wave reduction), the present invention realizes the comprehensive quantification of the surrounding rock state. At the same time, based on the environmental state coefficient and the damage coefficient, combined with the charge density and the hole spacing index, a non-linear failure prediction model is constructed, significantly improving the prediction accuracy. Finally, through the charge amount analysis model, according to the failure prediction coefficient and the damage warning threshold, the safe charge amount is output in real time, reducing the risk of surrounding rock damage. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic flow diagram of the blasting analysis system of the present invention.

[0045] Figure 2 It is a three-dimensional structure schematic diagram of the device body of the present invention.

[0046] Annotation of reference numerals: 1. Device body; 101. Slot A; 102. Slot B; 103. Slot C; 2. Controller. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0048] The following describes the specific implementation of the present invention in detail with reference to specific embodiments.

[0049] Please refer to Figures 1 to 2 , a detection device for surrounding rock blasting of an extra-large cross-section oil storage cavern provided by an embodiment of the present invention, including a device body 1, and further including:

[0050] A multi-point displacement meter, which can be disassembled and installed in the slot A 101 opened in the device body 1, and is used to quantify the deformation amount of the surrounding rock caused by blasting;

[0051] An inclinometer, which can be embedded and installed in the slot B 102 opened in the device body 1, and is used to measure the inclination of the drilled hole after blasting;

[0052] An acoustic wave sensor, which can be embedded and installed in the slot C 103 opened in the device body 1, and is used to obtain the ultrasonic wave reduction in the drilled hole before and after blasting;

[0053] A blasting analysis system, which is integrally installed in the controller 2 embedded in the upper cover of the device body 1, and includes:

[0054] The blasting environment analysis module constructs an environmental state model based on the peak value of blasting vibration velocity and dust concentration and outputs an environmental state coefficient;

[0055] The blasting damage analysis module constructs a blasting damage model based on the displacement at the deepest part of the borehole measured by a multi-point displacement meter, the borehole inclination, and the ultrasonic wave reduction rate of the borehole before and after blasting, and outputs a blasting damage coefficient;

[0056] The blasting failure prediction and analysis module constructs a blasting failure model based on the single-point charge density and the blasting point spacing under the current environmental state coefficient and blasting damage coefficient, and outputs a blasting failure coefficient;

[0057] The charge amount analysis module constructs a charge amount analysis model based on the blasting failure coefficient and the current single-point charge amount, and outputs the target single-point charge amount.

[0058] Specifically, the blasting environment analysis module collects vibration velocity and dust concentration data in real time, normalizes the two with the preset safety threshold, and generates a comprehensive environmental state coefficient. The blasting damage analysis module synchronously obtains the measurement data of the multi-point displacement meter, inclinometer, and acoustic wave sensor, and generates a blasting damage coefficient by quantifying the coordinated changes in displacement, inclination angle, and acoustic wave reduction rate. The blasting failure prediction and analysis module inputs the environmental state coefficient and the blasting damage coefficient into a non-linear model, combines the current charge density and blasting point spacing parameters, and calculates the blasting failure prediction coefficient. The charge amount analysis module outputs the optimized target charge amount in real time through the model according to the dynamic relationship between the failure prediction coefficient and the current charge amount.

[0059] Compared with the prior art, the traditional method uses a single-parameter threshold warning mechanism and cannot handle the coupling effect of multiple factors. This solution realizes the multi-dimensional assessment of blasting risks by establishing a dynamic correlation model between the environmental state coefficient and the blasting damage coefficient. In the prior art, the adjustment of the charge amount depends on manual experience judgment. This solution forms an automatic feedback adjustment mechanism by constructing a mathematical relationship between the failure prediction coefficient and the charge amount. Each monitoring module of the traditional detection device operates independently. This solution integrates the multi-module analysis system through a controller, realizing real-time data interaction and collaborative processing.

[0060] Through the above technical solutions, this application solves the problem of multi-dimensional environmental parameter fusion, and avoids the risk of misjudgment of a single parameter through the environmental state model. It overcomes the problem of one-sidedness in traditional damage assessment, and realizes the comprehensive monitoring of the surrounding rock structure state through a multi-index fusion model. It eliminates the defect of lag in charge amount adjustment, and ensures the dynamic optimization of blasting parameters through a real-time feedback mechanism. Finally, it realizes the precision and intelligence of surrounding rock stability control, and effectively reduces the occurrence rate of over-excavation or under-excavation accidents.

[0061] Preferably, the steps of the blasting environment analysis module are as follows:

[0062] The peak value of the blasting vibration velocity obtained is processed by taking the ratio with the maximum vibration safety value to obtain the vibration index;

[0063] The dust concentration obtained is processed by taking the ratio with the maximum dust concentration value to obtain the dust concentration index;

[0064] An environmental state model is constructed based on the vibration index and the dust concentration index to output the environmental state coefficient;

[0065] The environmental state model is expressed as:

[0066]

[0067] Among them, represents the environmental state coefficient, represents the vibration index, represents the dust concentration index, represents the weight coefficient and .

[0068] Among them, the peak value of the blasting vibration velocity refers to the maximum vibration velocity value monitored during the blasting operation. Specifically, data can be collected in real time by a vibration sensor, and through ratio operation with the preset maximum vibration safety value, the impact degree of vibration on the surrounding rock is quantified.

[0069] Among them, the maximum dust concentration value refers to the preset dust concentration safety threshold. Specifically, the dust concentration in the blasting area can be measured by a dust concentration sensor, and through ratio operation with the safety threshold, the pollution risk of blasting dust to the working environment is reflected.

[0070] Among them, the weight coefficient refers to the contribution ratio of the vibration index and the dust concentration index in the environmental state model. Specifically, it can be an empirical value or dynamically adjusted based on historical data, and through normalization constraints, the balanced influence of different environmental parameters is ensured.

[0071] Specifically, the vibration index is generated by dividing the measured peak value of the vibration velocity by the safety threshold. The dust concentration index uses the same ratio processing method. The environmental state coefficient is calculated by a linear combination formula, where the weight coefficient can be dynamically allocated according to different working conditions. For example, in a dust-sensitive area, the dust concentration weight can be set to 0.6 and the vibration weight to 0.4. Through normalization constraints, the distortion of the evaluation caused by abnormal fluctuations of a single parameter is avoided, so as to realize the comprehensive quantification of vibration and dust pollution.

[0072] Compared with the prior art, traditional methods usually only use a single vibration velocity threshold to judge environmental risks, lack dynamic assessment of dust pollution, and the synergistic effects between parameters are not quantified. This solution constructs a linear weighted model by introducing the joint processing of dust concentration index and vibration index, which can reflect the dual impacts of blasting operations on surrounding rock stability and working environment simultaneously, and dynamically adjusts the contribution degrees of different parameters through weight coefficients.

[0073] Through the above technical solution, this application realizes the multi-dimensional environmental parameter fusion analysis of blasting vibration and dust pollution, and solves the problems that traditional methods rely on static thresholds and cannot dynamically quantify environmental synergistic risks. By introducing normalized weight coefficients, the balanced impacts of different environmental parameters on the comprehensive evaluation results are ensured, and the misjudgment risk caused by a single parameter dominating the evaluation results is avoided, thus providing an accurate environmental state input for subsequent charge amount optimization.

[0074] Preferably, the steps of the blasting damage analysis module are as follows:

[0075] The displacement at the deepest part of the borehole, the inclination angle, and the ultrasonic wave amplitude reduction are respectively processed by taking the ratio with the corresponding maximum values, and then the displacement index, the angular deviation index, and the wave velocity reduction index are obtained.

[0076] Based on the displacement index (the most direct index to quantify blasting damage), the angular deviation index (reflecting shear failure), and the wave velocity reduction index (reflecting the integrity of the rock mass), a blasting damage model is constructed to output the blasting damage coefficient.

[0077] The blasting damage model is expressed as:

[0078]

[0079] Wherein, represents the blasting damage coefficient, represents the displacement index, represents the angular deviation index, represents the wave velocity reduction index, represents the damage sensitivity index, represents the weight coefficient and .

[0080] Among them, the displacement at the deepest part of the borehole refers to the maximum deformation amount of the surrounding rock caused by blasting, which can be specifically measured by a multi-point displacement meter. The displacement index is generated through ratio processing to quantify the degree of compression or tensile deformation. The inclination angle refers to the angle between the borehole axis and the vertical direction, which can be specifically measured by an inclinometer. The non-linear influence of shear failure is highlighted through squaring operation. The ultrasonic wave amplitude reduction refers to the reduction amount of the acoustic wave propagation velocity before and after blasting, which can be specifically measured by an acoustic wave sensor. Combining with the damage sensitivity index Adjust the sensitivity of wave velocity change to rock mass integrity. The displacement index is the ratio of the displacement amount to the maximum allowable displacement, which is used to directly reflect the deformation degree of the surrounding rock. The angular offset index is the ratio of the inclination angle to the maximum allowable angle, which is used to characterize the shear failure risk. The wave velocity reduction index is the ratio of the ultrasonic wave velocity reduction to the maximum allowable reduction, which is used to evaluate the crack propagation state inside the rock mass. The weight coefficient is used to balance the contribution degrees of different damage mechanisms and ensure the physical meaning and calculation stability of the model.

[0081] Specifically, after obtaining the displacement amount at the deepest part of the borehole through a multi-point displacement meter, the displacement index is generated by processing the ratio with the preset maximum allowable displacement, which directly reflects the compression or tensile deformation degree of the surrounding rock. The angular offset index is generated by processing the ratio of the inclination angle measured by the inclinometer to the maximum allowable angle, and the nonlinear effect of shear failure is strengthened through squaring operation. The ultrasonic wave velocity data before and after blasting are collected by the acoustic wave sensor, and after calculating the reduction, the wave velocity reduction index is generated by processing the ratio with the maximum allowable reduction, and the sensitivity to the rock mass integrity is adjusted in combination with the damage sensitivity index α. The displacement index, the square term of the angular offset index, and the power function term of the wave velocity reduction index are weighted and superimposed to comprehensively reflect the compression deformation, shear failure, and crack propagation state of the surrounding rock. The weight coefficient ensures the reasonable distribution of the contribution degrees of different damage mechanisms through normalization constraint, and finally outputs the dynamic blasting damage coefficient.

[0082] Compared with the prior art, the traditional method only relies on a single index to evaluate the damage of the surrounding rock. For example, it only judges by the change of the displacement amount or the acoustic wave velocity, and cannot comprehensively reflect the synergistic effect of compression deformation, shear failure, and crack propagation. In the prior art, the inclination angle is not non-linearly processed, and the dynamic adjustment of the sensitivity to the wave velocity reduction is lacking, resulting in deviation in damage assessment.

[0083] Through the above technical solution, the present application can integrate three types of parameters: borehole displacement, inclination angle, and acoustic wave reduction, and accurately quantify the blasting damage degree of the surrounding rock through non-linear operation and dynamic weight distribution. This solution solves the limitation of the traditional method of single-index evaluation, avoids the evaluation error caused by ignoring the non-linear effect of shear failure and the wave velocity sensitivity difference, and provides a reliable damage coefficient input for the subsequent optimization of the charge amount.

[0084] Preferably, the steps of the blasting failure prediction and analysis module are as follows:

[0085] Process the ratio of the reference hole spacing to the current blasting point spacing to obtain the blasting point distance index, and process the ratio of the current single-point charge density to the maximum allowable charge density to obtain the charge density index;

[0086] Construct a blasting damage model based on the charge density index and the blasting point distance index under the current environmental state coefficient and the blasting damage coefficient, and output the blasting damage prediction coefficient;

[0087] The blasting damage model is expressed as:

[0088]

[0089] where represents the blasting damage prediction coefficient, represents the environmental state coefficient, represents the blasting damage coefficient, represents the charge density index, represents the blasting point distance index, represents the sensitivity coefficient (used to control the intensity of the synergistic effect between the environment and damage), represents the hole spacing sensitivity index.

[0090] Among them, the blasting point distance index refers to the ratio of the reference hole spacing to the current blasting point spacing. Specifically, it can be realized by measuring the actual hole spacing with a distance sensor and then performing a division operation with the preset reference value, which is used to reflect the degree of deviation of the actual hole spacing from the reference value. The charge density index refers to the ratio of the current single-point charge density to the maximum allowable charge density. Specifically, it can be realized by collecting charge density data with a density sensor, which is used to dynamically evaluate whether the charge density exceeds the safe range. The environmental state coefficient refers to the weighted parameter of the comprehensive vibration velocity and dust concentration, which is used to characterize the comprehensive risk level of the blasting operation environment. The blasting damage coefficient refers to the non-linear parameter of the comprehensive displacement, inclination and acoustic wave reduction, which is used to quantify the degree of damage to the integrity of the surrounding rock structure. The sensitivity coefficient refers to the adjustment factor of the superposition effect of the environmental and damage parameters. Specifically, it can be determined by experimental calibration or machine learning optimization, which is used to control the steepness of the non-linear response curve. The hole spacing sensitivity index refers to the influence weight of the blasting point distance on the damage prediction. Specifically, different power parameters can be set according to the differences in rock mass types, which is used to reflect the sensitivity characteristics of different geological conditions to the change of hole spacing.

[0091] Specifically, by collecting the ratio of the current blast point spacing to the reference hole spacing in real time, the degree of deviation of the actual hole spacing from the designed value can be dynamically monitored, avoiding uneven energy distribution caused by too large a spacing or stress concentration caused by too small a spacing. The charge density index can timely identify the risk of rock crushing caused by over-dense charging by monitoring the proportional relationship between the charging density and the maximum allowable value in real time. The environmental state coefficient and the blast damage coefficient are coupled and calculated in the form of an exponential function, strengthening the non-linear superposition effect of the two in the high-value region, and the sensitivity coefficient adjusts the response rate of this coupling effect. The power function relationship between the blast point distance index and the hole spacing sensitivity index can differentially adjust the influence weight of the change in hole spacing on the failure prediction according to the rock mass characteristics. For example, a higher γ value is set in soft rock formations to enhance the hole spacing sensitivity. The constructed blast failure model realizes multi-dimensional dynamic matching of environmental parameters, damage states, charging conditions, and geometric layouts.

[0092] Compared with the prior art, traditional methods only adopt fixed hole spacing thresholds and static charge density limits, and cannot reflect in real time the influence of the dynamic changes of hole spacing deviation and charge density during the blasting operation on the stability of the surrounding rock. In the prior art, the environmental parameters and damage parameters are calculated by a linear superposition method to obtain the damage coefficient, and it is difficult to accurately characterize the non-linear synergistic effect of the two under high-risk working conditions. This solution effectively captures the interaction between environmental risks and structural damage by introducing a coupling calculation term in the form of an exponential function, and combines the differential setting of the hole spacing sensitivity index, significantly improving the prediction accuracy under different geological conditions.

[0093] Through the above technical solutions, this application solves the problem that the traditional blasting detection method cannot dynamically predict the blast damage coefficient, resulting in a lag in the adjustment of the charge amount, and realizes the real-time calculation of the blast damage coefficient and the dynamic early warning of the stability risk of the surrounding rock. By dynamically quantifying the relative states of the blast point spacing and the charge density, combined with the non-linear coupling calculation of the environmental and damage parameters, it is possible to identify the hole spacing layout deviation and the risk of over-dense charging in real time during the charging operation, providing an accurate input of the failure prediction coefficient for the dynamic adjustment of the charge amount. Based on the parametric design of the sensitivity coefficient and the hole spacing sensitivity index, it can meet the customized requirements of different rock mass types and geological conditions for the blast damage model, effectively avoiding the occurrence of accidents such as over-excavation or under-excavation of the surrounding rock.

[0094] Preferably, the charge amount analysis model is expressed as:

[0095]

[0096] Wherein, represents the target charge amount, represents the current charge amount, represents the blast failure prediction coefficient, represents the safety value of the blast damage coefficient, denotes the blasting damage coefficient, denotes the early warning value of the blasting damage coefficient, denotes the excessive bandwidth (the floating value above and below the early warning value of the blasting damage coefficient).

[0097] Specifically, the model realizes the dynamic correlation between the damage prediction coefficient and the safety value through the exponential function term When the blasting damage prediction coefficient exceeds the safety value, the value of the exponential term decreases, thereby reducing the target charge amount and preventing over-excavation of the surrounding rock. The hyperbolic tangent function term is used to dynamically respond to the damage state. When the blasting damage coefficient approaches or exceeds the early warning value, the function value decays rapidly, forcing the charge amount to be reduced to avoid under-excavation. The excessive bandwidth parameter is the core safety buffer of the charge amount regulation model, and together with the early warning value constitutes a "soft threshold" together, replacing the traditional hard threshold alarm, realizing the dynamic progressive optimization of the charge amount, and being able to control the response speed of the charge amount adjustment by adjusting the slope of the hyperbolic tangent curve. For example, when the value is small, the charge amount adjustment is more sensitive to the change of the damage coefficient.

[0098] Compared with the prior art, the traditional method relies on a fixed safety threshold to adjust the charge amount and cannot distinguish the synergistic effect between the damage prediction coefficient and the damage coefficient. However, in this solution, through the combination of non-linear functions, the damage prediction coefficient and the damage early warning mechanism are fused and calculated, and the charge amount correction coefficient can be dynamically generated according to the real-time blasting data. In the prior art, the charge amount adjustment usually adopts linear proportional scaling, while this model realizes the non-linear adjustment of the charge amount with the change of the risk level through the combined action of the exponential function and the hyperbolic tangent function.

[0099] Through the above technical solution, this application solves the problems of over-excavation or under-excavation of the surrounding rock caused by the lag of traditional charge amount adjustment. During the blasting construction process, when it is monitored that the blasting damage coefficient approaches the early warning value, the model automatically reduces the target charge amount to avoid cumulative damage to the rock mass; when the blasting damage prediction coefficient exceeds the safety threshold, the exponential decay mechanism takes effect immediately to inhibit excessive charging. The model ensures that the charge amount is always within the safe construction range by dynamically balancing the dual constraints of damage prediction and damage early warning, thereby maintaining the stability of the surrounding rock structure.

[0100] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusively, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0101] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A detection device for the surrounding rock blasting of an ultra-large cross-section oil storage cavern, comprising a device body, characterized in that, It further includes: A blasting analysis system, which is integrally installed in a controller embedded in the upper cover of the device body, and includes: A blasting environment analysis module, which constructs an environmental state model based on the peak value of blasting vibration velocity and dust concentration and outputs an environmental state coefficient; A blasting damage analysis module, which constructs a blasting damage model based on the displacement amount at the deepest part of the borehole measured by a multi-point displacement meter, the borehole inclination, and the ultrasonic wave reduction amplitude of the borehole before and after blasting, and outputs a blasting damage coefficient; A blasting failure prediction analysis module, which constructs a blasting failure model based on the single-point charge density and the blasting point spacing under the current environmental state coefficient and blasting damage coefficient, and outputs a blasting failure coefficient; A charge amount analysis module, which constructs a charge amount analysis model based on the blasting failure coefficient and the current single-point charge amount, and outputs the target single-point charge amount.

2. The detection device for surrounding rock blasting of an ultra-large cross-section oil storage cavern as claimed in claim 1, wherein, The charge amount analysis model is expressed as: Among them, represents the target charge amount, represents the current charge amount, represents the blasting damage prediction coefficient, represents the safety value of the blasting damage coefficient, represents the blasting damage coefficient, represents the warning value of the blasting damage coefficient, represents the excessive bandwidth.

3. The detection device for surrounding rock blasting of an extra-large cross-section oil storage cavern according to claim 2, wherein, The steps of the blasting failure prediction analysis module are: Perform a ratio process on the reference hole distance and the current blasting point spacing to obtain a blasting point distance index, and perform a ratio process on the current single-point charge density and the maximum allowable charge density to obtain a charge density index; Construct a blasting failure model based on the charge density index and the blasting point distance index under the current environmental state coefficient and blasting damage coefficient, and output a blasting failure prediction coefficient; The blasting failure model is expressed as: Among them, represents the blasting damage prediction coefficient, represents the environmental state coefficient, represents the blasting damage coefficient, represents the charge density index, represents the blasting point distance index, represents the sensitivity coefficient, represents the hole spacing sensitivity index.

4. The detection device for surrounding rock blasting of ultra-large cross-section oil storage caverns according to claim 3, characterized in that, The steps of the blasting environment analysis module are: Perform a ratio process on the obtained peak value of blasting vibration velocity and the maximum vibration safety value to obtain a vibration index; Perform a ratio process on the obtained dust concentration and the maximum dust concentration value to obtain a dust concentration index; Construct an environmental state model based on the vibration index and the dust concentration index, and output an environmental state coefficient; The environmental state model is expressed as: Among them, represents the environmental status coefficient, represents the vibration index, represents the dust concentration index, represents the weight coefficient and .

5. The detection device for surrounding rock blasting of ultra-large cross-section oil storage caverns according to claim 3, wherein The steps of the blasting damage analysis module are: Perform a ratio process on the displacement amount at the deepest part of the borehole, the inclination angle, and the ultrasonic wave reduction amplitude with their respective maximum values to obtain a displacement index, an angular offset index, and a wave velocity reduction index; Construct a blasting damage model based on the displacement index, the angular offset index, and the wave velocity reduction index, and output a blasting damage coefficient; The blasting damage model is expressed as: Among them, represents the blasting damage coefficient, represents the displacement index, represents the angle deviation index, represents the wave velocity reduction index, represents the damage sensitivity index, represents the weight coefficient and .

6. The detection device for surrounding rock blasting of an extra-large cross-section oil storage cavern according to claim 1, characterized in that, It further includes: A multi-point displacement meter, which can be disassembled and installed in the device body, and is used to quantify the surrounding rock deformation caused by blasting; An inclinometer, which can be embedded and installed in the device body, and is used to measure the borehole inclination after blasting; An acoustic wave sensor, which can be embedded and installed in the device body, and is used to obtain the ultrasonic wave reduction amplitude in the borehole before and after blasting.

7. The detection device for surrounding rock blasting of super-large cross-section oil storage caverns according to claim 6, wherein, Slot A for placing the multi-point displacement meter, slot B for placing the inclinometer, and slot C for placing the acoustic wave sensor are provided on the device body.

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