A tunnel fracture zone depth testing method based on blasting vibration energy

Abstract

The application provides a tunnel rupture zone depth testing method based on blasting vibration energy, belongs to the technical field of tunnel engineering and engineering blasting safety monitoring, and comprises the following steps: arranging vibration sensors in tunnel surrounding rock; collecting and storing blasting vibration signals in the blasting construction process; pre-processing the blasting vibration signals and calculating particle peak vibration velocity; according to the particle peak vibration velocity, adopting a Hilbert-Huang transform digital signal analysis method, calculating the Hilbert total energy of the blasting vibration signals; inputting the Hilbert total energy of the blasting vibration signals into a pre-constructed mathematical model between the Hilbert total energy and the tunnel rupture zone depth, and obtaining the tunnel surrounding rock rupture zone depth. The method can reflect the energy characteristics of the blasting vibration signals and the rock mass rupture characteristics, and can establish a quantitative relationship between the blasting vibration energy and the rupture zone depth, thereby providing an important reference for safety control of tunnel construction and blasting parameter optimization.

Description

Technical Field

[0001] This invention belongs to the field of tunnel engineering and engineering blasting safety monitoring technology, specifically relating to a method for testing the depth of tunnel fracture zone based on blasting vibration energy. Background Technology

[0002] With the rapid development of transportation infrastructure construction, the drill-and-blast method has become the main construction method for mountain tunnel excavation due to its strong adaptability to geological conditions and significant economic benefits. However, during the blasting process, only a small portion of the enormous energy released instantaneously by the explosive is used to break the rock; most of the energy propagates to the surrounding rock in the form of blasting vibrations. This high-intensity dynamic disturbance causes the expansion of existing fissures within the surrounding rock or the generation of new microcracks, thus forming a fractured zone of a certain depth outside the tunnel outline. The existence of this fractured zone not only severely weakens the self-bearing capacity of the rock mass but also easily induces safety accidents such as tunnel spalling and collapse. Therefore, accurately and quickly determining the depth of the fractured zone in the surrounding rock is of significant engineering importance for optimizing blasting parameter design, determining a reasonable initial support scheme, and ensuring construction safety.

[0003] Existing methods for testing the depth of fractured zones in tunnel surrounding rock mainly rely on direct observation and geophysical testing. Direct observation methods, such as coring and multi-point displacement metering, provide intuitive and reliable results, but require drilling numerous observation holes in the surrounding rock. This is not only cumbersome and costly, but also severely disrupts normal construction progress and makes it difficult to perform measurements as drilling progresses. Geophysical testing primarily uses acoustic wave testing, which determines the depth of the fractured zone by detecting the attenuation of rock wave velocity. While this method offers relatively high accuracy, it suffers from significant data dispersion, long testing cycles, and susceptibility to interference from construction noise and hydrological conditions, making it difficult to meet the demands of modern tunnel construction for rapid feedback on the surrounding rock condition.

[0004] Besides field measurements, empirical formulas are often used for prediction in engineering. Traditional empirical formulas are often derived from statistical data fitting under specific geological conditions, resulting in poor universality. Furthermore, these formulas typically consider only peak particle velocity (PPV) as a single criterion, ignoring the complex spectral characteristics of blasting vibration signals (such as energy distribution), leading to limited prediction accuracy. At the signal processing level, blasting vibration signals exhibit typical nonlinear and non-stationary characteristics. Traditional Fourier transforms, based on the linear stationarity assumption, cannot accurately describe the time-varying spectral characteristics of blasting signals. While wavelet transforms possess multi-resolution analysis capabilities, they are limited by the fixed nature of wavelet basis functions and lack adaptability. In contrast, the Hilbert-Huang Transform (HHT), as an adaptive time-frequency analysis method for processing nonlinear and non-stationary signals, can decompose complex signals into several intrinsic mode functions (IMFs) and accurately extract the instantaneous frequency and Hilbert energy spectrum of the signal, demonstrating significant advantages in analyzing the energy distribution of blasting vibrations.

[0005] Although HHT has been applied in the field of blasting vibration signal analysis, existing research is mostly limited to describing the time-frequency characteristics of the signal itself. Few studies have applied HHT blasting vibration energy characteristic analysis to fracture zone identification, or established mathematical models reflecting the relationship between blasting vibration energy and fracture zone depth. Therefore, there is an urgent need to develop a method for calculating tunnel fracture zone depth that requires no additional drilling, does not take up construction time, and comprehensively considers the characteristics of blasting vibration energy. This would provide an important reference for safety control and blasting parameter optimization in tunnel construction. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this application proposes a method for testing the depth of the tunnel fracture zone based on blasting vibration energy. Using this method to monitor the surrounding rock of the tunnel can more conveniently, effectively, and economically calculate the depth of the fracture zone, providing technical support for the evaluation of tunnel surrounding rock stability and the optimization of support parameters.

[0007] In a first aspect, the present invention provides a method for testing the depth of a tunnel fracture zone based on blasting vibration energy, comprising:

[0008] Vibration sensors were installed in the surrounding rock of the tunnel.

[0009] Collect and store blasting vibration signals during blasting operations;

[0010] The peak vibration velocity of the particles was obtained by preprocessing the blasting vibration signal.

[0011] Based on the peak particle vibration velocity, the Hilbert-Huang transform digital signal analysis method is used to calculate the total Hilbert energy of the blasting vibration signal;

[0012] The Hilbert total energy of the blasting vibration signal is input into a pre-constructed mathematical model between the Hilbert total energy and the depth of the tunnel fracture zone to obtain the depth of the tunnel surrounding rock fracture zone. The pre-constructed mathematical model between the Hilbert total energy and the depth of the tunnel fracture zone is constructed by: constructing a relationship between key physical parameters with fitting coefficients and the Hilbert total energy, where the key physical parameters include the depth of the tunnel fracture zone, and fitting the fitting coefficients using measured historical data.

[0013] The installation of vibration sensors in the surrounding rock of the tunnel includes: along the tunnel axis, arranging monitoring points at different distances from the tunnel face on cross sections, with at least 7 monitoring points arranged on each cross section, covering the positions of the arch crown, left arch shoulder, right arch shoulder, left side wall, right side wall, left arch foot, and right arch foot, and the distance between adjacent monitoring points is not less than 2 meters.

[0014] The vibration sensor is installed by drilling a hole in the surrounding rock of the tunnel. The diameter of the hole is larger than the size of the vibration sensor. During installation, the vibration sensor is inserted into the hole and fixed to the surrounding rock with an adhesive. During installation, the positive X-axis of the vibration sensor points towards the blast center, and the Z-axis of the vibration sensor is perpendicular to the ground.

[0015] The calculation of the Hilbert total energy based on the peak particle vibration velocity using the Hilbert-Huang transform digital signal analysis method includes:

[0016] The peak vibration velocity of the particle is decomposed into intrinsic mode function components and a residual component using the modal decomposition method.

[0017] The instantaneous amplitude and instantaneous frequency are obtained by performing a Hilbert transform on the components of the intrinsic mode function;

[0018] Construct the Hilbert spectrum based on the instantaneous amplitude and instantaneous frequency;

[0019] Integrating the Hilbert spectrum over the time domain yields the Hilbert marginal energy spectrum;

[0020] The total Hilbert energy of the blasting vibration signal is calculated by integrating the Hilbert marginal energy spectrum within the effective frequency band.

[0021] The Hilbert spectrum is constructed based on the instantaneous amplitude and instantaneous frequency, and the expression is as follows:

[0022] ;

[0023] in, For Hilbert's spectrum, Re denotes taking the real part. Let be the instantaneous amplitude of the j-th mode decomposition component. Let be the instantaneous frequency of the j-th mode decomposition method component, n be the number of mode decomposition method components, and e be the natural logarithm. Let be the instantaneous velocity of the j-th modal component.

[0024] Integrating the Hilbert spectrum in the time domain yields the Hilbert marginal energy spectrum, expressed as follows:

[0025] ;

[0026] in, For Hilbert's marginal energy spectrum, Represents the instantaneous frequency, and T is the total duration of the blasting vibration signal. This is Hilbert's score.

[0027] The Hilbert marginal energy spectrum is integrated over the effective frequency band to calculate the total Hilbert energy of the blasting vibration signal, as shown in the following formula:

[0028] ;

[0029] Where E is the Hilbert total energy of the blast vibration signal. Represents the maximum value of the instantaneous frequency. For Hilbert's marginal energy spectrum, Represents instantaneous frequency.

[0030] The relationship between the key physical parameters with fitting coefficients and the total Hilbert energy is as follows:

[0031] ;

[0032] in, The first fitting coefficient, The second fitting coefficient, The third fitting coefficient, The fourth fitting coefficient, Q is the maximum charge per segment, R is the distance from the detonation center, ρ is the rock density, D is the charge length, and C is the detonation coefficient. p R represents the longitudinal wave velocity of the rock mass. e Where is the radius of the fracture zone. is the fitting constant.

[0033] The Hilbert total energy of the blasting vibration signal is input into a pre-constructed mathematical model relating the Hilbert total energy to the depth of the tunnel fracture zone, and the depth of the tunnel surrounding rock fracture zone is obtained. The calculation formula is as follows:

[0034] ;

[0035] in, The first fitting coefficient, The second fitting coefficient, The third fitting coefficient, The fourth fitting coefficient, Q is the maximum charge per segment, R is the distance from the detonation center, ρ is the rock density, D is the charge length, and C is the detonation coefficient. p R represents the longitudinal wave velocity of the rock mass. e The radius of the fracture zone is the same as the depth of the fracture zone in the surrounding rock of the tunnel. is the fitting constant.

[0036] Before performing Hilbert transform on the intrinsic mode function components, the following steps are taken: using the correlation coefficient method to remove invalid components from the intrinsic mode function components, and only retaining intrinsic mode function components whose correlation coefficient with the peak vibration velocity of the particle is greater than a set threshold.

[0037] Beneficial effects:

[0038] This application proposes a method for testing the depth of tunnel fracture zones based on blasting vibration energy. 1) Considering the problems of large interference with construction and long cycle of traditional monitoring methods, this application utilizes conventional blasting vibration monitoring data for inversion, which avoids the high cost and procedural conflicts of traditional methods and realizes real-time dynamic assessment of fracture zone depth; 2) The Hilbert-Huang transform is introduced to process the blasting vibration signal, overcoming the shortcomings of Fourier transform in processing transient signals, and realizing a refined characterization of the blasting vibration signal in the time-frequency-energy domain. In particular, calculating the fracture zone depth through blasting vibration energy can more realistically extract the effective energy characteristics that play a dominant role in surrounding rock damage; 3) Unlike purely empirical statistical formulas, this application derives a mathematical model based on dimensional analysis, including energy, charge, distance, and rock mass parameters, revealing the intrinsic relationship between various physical quantities. By regressing undetermined coefficients through measured data, this calculation method can be adapted to tunnel engineering under different geological conditions, has better engineering practical value, and provides a basis for tunnel construction safety. Attached Figure Description

[0039] Figure 1 This invention provides a method for testing the depth of a tunnel fracture zone based on blasting vibration energy.

[0040] Figure 2 This is a schematic diagram of the radial waveform of tunnel surrounding rock blasting vibration in an embodiment of the present invention;

[0041] Figure 3 This is a schematic diagram of the tangential waveform of blasting vibration in the surrounding rock of a tunnel, as shown in an embodiment of the present invention.

[0042] Figure 4 This is a schematic diagram of the vertical waveform of tunnel surrounding rock blasting vibration in an embodiment of the present invention;

[0043] Figure 5 This is a peak velocity diagram of particles in an embodiment of the present invention;

[0044] Figure 6 This is a Hilbert marginal energy spectrum calculation diagram of the blasting vibration signal in an embodiment of the present invention;

[0045] Figure 7 This is a schematic diagram of the depth of the tunnel fracture zone in an embodiment of the present invention. Detailed Implementation

[0046] The specific implementation methods of this application will be further described in detail below with reference to the accompanying drawings and embodiments.

[0047] Example 1:

[0048] This embodiment provides a method for testing the depth of tunnel fracture zones based on blasting vibration energy, such as... Figure 1 As shown, it includes:

[0049] Step S1: Install vibration sensors in the surrounding rock of the tunnel;

[0050] The method of deploying vibration sensors in the surrounding rock of the tunnel includes: along the tunnel axis, arranging monitoring points at different distances from the tunnel face on cross sections, with at least 7 monitoring points arranged on each cross section, covering the positions of the arch crown, left arch shoulder, right arch shoulder, left side wall, right side wall, left arch foot, and right arch foot, and the distance between adjacent monitoring points is not less than 2 meters, in order to obtain the vibration velocity attenuation law under different blast center distances.

[0051] The vibration sensor is installed by drilling a hole in the surrounding rock of the tunnel. The diameter of the hole is larger than the size of the vibration sensor. During installation, the vibration sensor is inserted into the hole and fixed to the surrounding rock with an adhesive. During installation, the positive X-axis of the vibration sensor points towards the blast center, and the Z-axis of the vibration sensor is perpendicular to the ground.

[0052] In this embodiment, the preferred model of the triaxial vibration sensor is a three-axis (X-axis, Y-axis, Z-axis) or equivalent sensor.

[0053] Specifically, in this embodiment, a deep-buried railway tunnel in a southwestern mountainous area was excavated using the drill-and-blast method. The tunnel is approximately 40 km long, with a horseshoe-shaped cross-section and excavation dimensions of 9.8m × 8.8m. The surrounding rock is classified as Class III, primarily composed of gneiss. The tunnel face blasting employed full-face smooth blasting technology with millisecond delay segmented detonation. Using the aforementioned method for calculating the depth of the tunnel fracture zone based on blasting vibration energy, the fracture zone depth of the Dyk1124+707 section of the tunnel was calculated. The specific steps are as follows: Figure 1 As shown.

[0054] (1) Blasting vibration sensors were installed on a section 45 m from the tunnel face, specifically at the tunnel arch crown, left abutment, left side wall, left arch foot, right abutment, right side wall, and right arch foot, for a total of seven sensors, to obtain the vibration response characteristics of the surrounding rock. The sensors were installed in the tunnel surrounding rock by drilling, with a borehole diameter of 200 mm and a drilling depth greater than the initial support shotcrete thickness, approximately 300 mm, to ensure close contact with the surrounding rock. Plaster sensors were rigidly fixed to the bottom of the hole, ensuring that the X-direction of the sensor was horizontally pointing towards the blast center and the Z-direction was perpendicular to the ground.

[0055] (2) On May 12, 2025, blasting operations were carried out at the tunnel face. Seven blasting vibration sensors were activated, the sampling frequency was set to be no less than 5 kHz, and a negative delay trigger mode was set. The trigger level was set to 0.05 cm / s based on the background noise at the site. After the blasting was completed, the stored vibration waveform data was exported.

[0056] (3) Preprocess the collected blasting vibration waveform data: First, remove the DC component and trend term, and then use a low-pass filter with a cutoff frequency of 200 Hz to eliminate high-frequency noise interference. For example... Figure 2 , Figure 3 , Figure 4 The blasting vibration velocity-time curves are obtained from a measuring point on the right wall at a distance of 35m from the blast center, showing the horizontal radial, horizontal tangential, and vertical directions. The triaxial velocity components at each measuring point are extracted, and the calculated PPV is 5.8 cm / s. Figure 5 As shown.

[0057] Step S2: Collect and store blasting vibration signals during the blasting operation;

[0058] In this embodiment, when collecting and storing waveform data of blasting vibration signals, the sampling frequency is set to be no less than 5kHz, and a negative delay trigger mode is set, with the trigger level set according to the on-site background noise threshold.

[0059] Step S3: Preprocess the blasting vibration signal and calculate the peak vibration velocity of the particles;

[0060] In this embodiment, the original waveform data of the blasting vibration signal is processed by removing the DC component, removing the trend term, and low-pass filtering to eliminate high-frequency noise interference; the synthesized peak particle velocity (PPV) is the maximum value of the sum of the three-axis velocity vectors, and the calculation formula is as follows:

[0061] ;

[0062] Among them, v x (t) represents the radial velocity component, v y (t) represents the tangential velocity component, vz (t) represents the vertical velocity component, and PPV represents the peak vibration velocity of the particle.

[0063] Step S4: Based on the peak particle vibration velocity, the Hilbert-Huang transform digital signal analysis method is used to calculate the total Hilbert energy of the blasting vibration signal;

[0064] The calculation of the Hilbert total energy based on the peak particle vibration velocity using the Hilbert-Huang transform digital signal analysis method includes:

[0065] Step S4.1: Using the Empirical Mode Decomposition (EMD) method, the peak vibration velocity of the particle is decomposed into an Intrinsic Mode Function (IMF) component and a residual component.

[0066] Step S4.2: Perform Hilbert transform on the intrinsic mode function components to obtain the instantaneous amplitude and instantaneous frequency;

[0067] In this embodiment, before performing Hilbert transform on the intrinsic mode function components, the method further includes: using the correlation coefficient method to remove invalid components from the intrinsic mode function components, and retaining only the intrinsic mode function components whose correlation coefficient with the peak vibration velocity of the particle is greater than a set threshold.

[0068] Step S4.3: Construct the Hilbert spectrum based on the instantaneous amplitude and instantaneous frequency, as shown in the following expression:

[0069] ;

[0070] in, For Hilbert's spectrum, Re denotes taking the real part. Let be the instantaneous amplitude of the j-th mode decomposition component. Let be the instantaneous frequency of the j-th mode decomposition method component, n be the number of mode decomposition method components, and e be the natural logarithm. Let be the instantaneous velocity of the j-th modal component. This can be understood as: The sum of the velocities in the X, Y, and Z directions constitutes the peak velocity of the particle. Based on this expression, the signal amplitude can be characterized as a function of time and instantaneous frequency.

[0071] Step S4.4: Integrate the Hilbert spectrum in the time domain to obtain the Hilbert marginal energy spectrum, as shown in the following expression:

[0072] ;

[0073] in, For Hilbert's marginal energy spectrum, Represents the instantaneous frequency, and T is the total duration of the blasting vibration signal. This is Hilbert's score. For Hilbert's marginal energy spectrum, such as Figure 6 As shown, it characterizes the cumulative energy contribution of the blasting signal with respect to frequency over the entire duration T.

[0074] Step S4.5: Integrate the Hilbert marginal energy spectrum within the effective frequency band to calculate the total Hilbert energy of the blasting vibration signal.

[0075] The Hilbert marginal energy spectrum is integrated over the effective frequency band to calculate the total Hilbert energy of the blasting vibration signal, as shown in the following formula:

[0076] ;

[0077] Where E is the Hilbert total energy of the blast vibration signal. Represents the maximum value of the instantaneous frequency. For Hilbert's marginal energy spectrum, Represents instantaneous frequency.

[0078] Specifically, in this embodiment, the Hilbert-Huang Transform (HHT) is used to analyze the preprocessed waveform data. The Empirical Mode Decomposition (EMD) method is used to decompose the acquired blasting vibration signal into eight Intrinsic Mode Function (IMF) components and one residual component. The Hilbert Transform is then applied to the selected main IMF components to construct the Hilbert spectrum. This allows us to obtain the Hilbert marginal spectrum ES. Integrating the Hilbert marginal spectrum over the effective frequency band yields the total Hilbert energy of the blast vibration at the monitoring point, E = 987.69 (cm / s). 2 Similarly, the energy values ​​at other measuring points were calculated.

[0079] Step S5: Input the total Hilbert energy of the blasting vibration signal into the pre-constructed mathematical model between the total Hilbert energy and the depth of the tunnel fracture zone to obtain the depth of the tunnel surrounding rock fracture zone. The pre-constructed mathematical model between the total Hilbert energy and the depth of the tunnel fracture zone is constructed by: constructing the relationship between key physical parameters with fitting coefficients and the total Hilbert energy. The key physical parameters include the depth of the tunnel fracture zone. The fitting coefficients are fitted using measured historical data.

[0080] In this embodiment, the key physical parameters selected include: maximum charge amount per segment Q, detonation center distance R, surrounding rock density ρ, charge length D, and longitudinal wave velocity of the rock mass C. p and the radius r of the fracture zone e ;according to Theorem yields the following relationship between the key physical parameters with fitting coefficients and the total Hilbert energy:

[0081] ;

[0082] in, The first fitting coefficient, The second fitting coefficient, The third fitting coefficient, The fourth fitting coefficient, Q is the maximum charge per segment, R is the distance from the detonation center, ρ is the rock density, D is the charge length, and C is the detonation coefficient. p R represents the longitudinal wave velocity of the rock mass. e The radius of the fracture zone is 1. is the fitting constant.

[0083] The Hilbert total energy of the blasting vibration signal is input into a pre-constructed mathematical model relating the Hilbert total energy to the depth of the tunnel fracture zone, and the depth of the tunnel surrounding rock fracture zone is obtained. The calculation formula is as follows:

[0084] ;

[0085] in, The first fitting coefficient, The second fitting coefficient, The third fitting coefficient, The fourth fitting coefficient, Q is the maximum charge per segment, R is the distance from the detonation center, ρ is the rock density, D is the charge length, and C is the detonation coefficient. p R represents the longitudinal wave velocity of the rock mass. e The radius of the fracture zone is the same as the depth of the fracture zone in the surrounding rock of the tunnel. is the fitting constant.

[0086] In this embodiment, regression analysis is performed using measured data to determine the fitting coefficients. This is achieved through multiple sets of historical measured data (including: maximum charge amount Q per segment, detonation center distance R, surrounding rock density ρ, charge length D, and longitudinal wave velocity C of the rock mass). p and the radius r of the fracture zone e The specific rupture zone depth is obtained by regression using the least squares method.

[0087] Specifically, in this embodiment, the key physical parameters selected include: maximum charge amount per segment Q, detonation center distance R, surrounding rock density ρ, charge length D, and longitudinal wave velocity C of the rock mass. p and the radius r of the fracture zone e According to Ba Jin Theorem, constructing relations The density of the rock mass is ρ = 2650 kg / m³. 3 On-site acoustic wave testing revealed that the longitudinal wave velocity C of the rock mass... p= 4500 m / s. Twenty sets of measured data from different explosions were selected, and regression fitting was performed using the least squares method. The fitting results show a correlation coefficient R0. 2 =0.89, and the undetermined coefficients are obtained as follows: C1=2.745, α1=2.283, α2=0.404, α3=-1.769, α4=0.012. The final calculation model is as follows:

[0088] ;

[0089] The functional relationship model of the broken region is simplified into a power function form:

[0090] ;

[0091] Substituting the data from the measuring points in this embodiment into the fitted model above for back-calculation, the calculated fracture zone depth r is obtained. e =2.73m. Comparing this calculated value with the actual measured sound wave value (2.65 m), the relative error is only 3.1%. Figure 7 This represents the depth of the fracture zone at different locations within the same cross-section. This indicates that, during the drill-and-blast excavation of deep-buried tunnels, the method proposed in this invention, based on HHT energy and dimensional analysis, can effectively overcome the limitations of traditional single-index PPV (Power Producer Value) methods, enabling accurate calculation of the fracture zone depth in the surrounding rock of the tunnel. This provides reliable data support for adjusting blasting parameters and strengthening support in the next cycle.

[0092] Example 2:

[0093] This embodiment proposes an electronic device, including: one or more processors, and a memory, wherein the memory is used to store instructions, and when the instructions are executed by the one or more processors, the one or more processors execute the aforementioned method for testing the depth of tunnel fracture zones based on blasting vibration energy.

[0094] The electronic device may be a mobile phone, computer, or tablet computer, etc., and includes a memory and a processor. The memory stores a computer program, which, when executed by the processor, implements a method for testing the depth of a tunnel fracture zone based on blasting vibration energy, as described in the embodiment. It is understood that the electronic device may also include an input / output (I / O) interface and communication components.

[0095] The processor is used to execute all or part of the steps in the tunnel fracture zone depth testing method based on blasting vibration energy as described in the above embodiments. The memory is used to store various types of data, which may include, for example, instructions for any application or method in the electronic device, as well as application-related data.

[0096] The processor can be implemented as an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a programmable logic device (PLD), a field-programmable gate array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components, and is used to execute the tunnel fracture zone depth testing method based on blasting vibration energy described in the above embodiments.

[0097] Example 3:

[0098] This embodiment proposes a computer-readable storage medium that stores executable instructions. When these instructions are executed, if they are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.

[0099] The computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the tunnel fracture zone depth testing method based on blasting vibration energy described in various embodiments of this application.

[0100] The aforementioned storage media include: flash memory, hard disk, multimedia card, card-type memory (e.g., SD (Secure Digital Memory Card) or DX (Memory Data Register, MDR) memory), random access memory (RAM), static random-access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic storage, disk, optical disk, server, APP (Application) application store, and other media capable of storing program verification codes. These media store computer programs, which, when executed by a processor, can implement the various steps of the aforementioned method for testing the depth of a tunnel fracture zone based on blasting vibration energy.

[0101] Example 4:

[0102] This embodiment proposes a computer program product, including a computer program or instructions, which, when executed by a processor, implements the aforementioned method for testing the depth of a tunnel fracture zone based on blasting vibration energy.

[0103] Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a computer program product.

[0104] The various embodiments in this application are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0105] The scope of protection of this application is not limited to the embodiments described above. Obviously, those skilled in the art can make various modifications and variations to this disclosure without departing from the scope and spirit of this disclosure. If such modifications and variations fall within the scope of equivalent technology of this disclosure, then the intent of this disclosure also includes such modifications and variations.

Claims

1. A method for testing the depth of a tunnel fracture zone based on blasting vibration energy, characterized in that, include: Vibration sensors were installed in the surrounding rock of the tunnel. Collect and store blasting vibration signals during blasting operations; The peak vibration velocity of the particles was obtained by preprocessing the blasting vibration signal. Based on the peak particle vibration velocity, the Hilbert-Huang transform digital signal analysis method is used to calculate the total Hilbert energy of the blasting vibration signal; The Hilbert total energy of the blasting vibration signal is input into a pre-constructed mathematical model between the Hilbert total energy and the depth of the tunnel fracture zone to obtain the depth of the tunnel surrounding rock fracture zone. The pre-constructed mathematical model between the Hilbert total energy and the depth of the tunnel fracture zone is constructed by: constructing a relationship between key physical parameters with fitting coefficients and the Hilbert total energy, where the key physical parameters include the depth of the tunnel fracture zone, and fitting the fitting coefficients using measured historical data.

2. The method for testing the depth of a tunnel fracture zone based on blasting vibration energy according to claim 1, characterized in that, The installation of vibration sensors in the surrounding rock of the tunnel includes: along the tunnel axis, arranging monitoring points at different distances from the tunnel face on cross sections, with at least 7 monitoring points arranged on each cross section, covering the positions of the arch crown, left arch shoulder, right arch shoulder, left side wall, right side wall, left arch foot, and right arch foot, and the distance between adjacent monitoring points is not less than 2 meters.

3. The method for testing the depth of a tunnel fracture zone based on blasting vibration energy according to claim 1, characterized in that, The vibration sensor is installed by drilling a hole in the surrounding rock of the tunnel. The diameter of the hole is larger than the size of the vibration sensor. During installation, the vibration sensor is inserted into the hole and fixed to the surrounding rock with an adhesive. During installation, the positive X-axis of the vibration sensor points towards the blast center, and the Z-axis of the vibration sensor is perpendicular to the ground.

4. The method for testing the depth of a tunnel fracture zone based on blasting vibration energy according to claim 1, characterized in that, The calculation of the Hilbert total energy based on the peak particle vibration velocity using the Hilbert-Huang transform digital signal analysis method includes: The peak vibration velocity of the particle is decomposed into intrinsic mode function components and a residual component using the modal decomposition method. The instantaneous amplitude and instantaneous frequency are obtained by performing a Hilbert transform on the components of the intrinsic mode function; Construct the Hilbert spectrum based on the instantaneous amplitude and instantaneous frequency; Integrating the Hilbert spectrum over the time domain yields the Hilbert marginal energy spectrum; The total Hilbert energy of the blasting vibration signal is calculated by integrating the Hilbert marginal energy spectrum within the effective frequency band.

5. The method for testing the depth of a tunnel fracture zone based on blasting vibration energy according to claim 4, characterized in that, The Hilbert spectrum is constructed based on the instantaneous amplitude and instantaneous frequency, and the expression is as follows: ； in, For Hilbert's spectrum, Re denotes taking the real part. Let be the instantaneous amplitude of the j-th mode decomposition component. Let be the instantaneous frequency of the j-th mode decomposition method component, n be the number of mode decomposition method components, and e be the natural logarithm. Let be the instantaneous velocity of the j-th modal component.

6. The method for testing the depth of a tunnel fracture zone based on blasting vibration energy according to claim 4, characterized in that, Integrating the Hilbert spectrum in the time domain yields the Hilbert marginal energy spectrum, expressed as follows: ； in, For Hilbert's marginal energy spectrum, Represents the instantaneous frequency, and T is the total duration of the blasting vibration signal. This is Hilbert's score.

7. The method for testing the depth of a tunnel fracture zone based on blasting vibration energy according to claim 4, characterized in that, The Hilbert marginal energy spectrum is integrated over the effective frequency band to calculate the total Hilbert energy of the blasting vibration signal, as shown in the following formula: ； Where E is the Hilbert total energy of the blast vibration signal. Represents the maximum value of the instantaneous frequency. For Hilbert's marginal energy spectrum, Represents instantaneous frequency.

8. The method for testing the depth of a tunnel fracture zone based on blasting vibration energy according to claim 1, characterized in that, The relationship between the key physical parameters with fitting coefficients and the total Hilbert energy is as follows: ； in, The first fitting coefficient, The second fitting coefficient, The third fitting coefficient, The fourth fitting coefficient, Q is the maximum charge per segment, R is the distance from the detonation center, ρ is the rock density, D is the charge length, and C is the detonation coefficient. p R represents the longitudinal wave velocity of the rock mass. e Where is the radius of the fracture zone. is the fitting constant.

9. The method for testing the depth of a tunnel fracture zone based on blasting vibration energy according to claim 1, characterized in that, The Hilbert total energy of the blasting vibration signal is input into a pre-constructed mathematical model relating the Hilbert total energy to the depth of the tunnel fracture zone, and the depth of the tunnel surrounding rock fracture zone is obtained. The calculation formula is as follows: ； in, The first fitting coefficient, The second fitting coefficient, The third fitting coefficient, The fourth fitting coefficient, Q is the maximum charge per segment, R is the distance from the detonation center, ρ is the rock density, D is the charge length, and C is the detonation coefficient. p R represents the longitudinal wave velocity of the rock mass. e The radius of the fracture zone is the same as the depth of the fracture zone in the surrounding rock of the tunnel. is the fitting constant.

10. A method for testing the depth of a tunnel fracture zone based on blasting vibration energy according to claim 4, characterized in that, Before performing Hilbert transform on the intrinsic mode function components, the following steps are taken: using the correlation coefficient method to remove invalid components from the intrinsic mode function components, and only retaining intrinsic mode function components whose correlation coefficient with the peak vibration velocity of the particle is greater than a set threshold.

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