Method and system for detecting cumulative damage of roadway rock mass based on acoustic wave method

Abstract

The present application belongs to the technical field of rock mass engineering detection, and particularly relates to a roadway rock mass cumulative damage detection method and system based on the acoustic wave method, which comprises the following steps: calculating a plurality of damage indexes of each monitoring point, obtaining a comprehensive damage index of each monitoring point according to the plurality of damage indexes of each monitoring point, converting the comprehensive damage index of all monitoring points into a two-dimensional damage function using a spatial interpolation algorithm, and calculating the spatial gradient of the two-dimensional damage function; obtaining the structural stability of each position, which is inversely proportional to the size of the comprehensive damage index and the spatial gradient; and performing risk zoning on the roadway surrounding rock according to the structural stability. The present application overcomes the limitations of single index and single monitoring point through multi-parameter fusion, and improves the accuracy and robustness of monitoring.

Description

Technical Field

[0001] This invention relates to the field of rock mass engineering testing technology. More specifically, this invention relates to a method and system for detecting cumulative damage in tunnel rock mass based on acoustic wave methods. Background Technology

[0002] Roadways are a crucial component of underground engineering projects such as mines, and the stability of their surrounding rock directly impacts production safety and the lives of personnel. During excavation and production, the surrounding rock of roadways suffers cumulative damage due to factors such as stress redistribution and blasting disturbances. This damage can lead to the initiation, propagation, and connection of micro-cracks, potentially triggering disasters such as rock bursts and roof collapses. Therefore, effective monitoring and assessment of the damage status of roadway rock masses is a critical step in ensuring the safety of underground engineering projects.

[0003] Acoustic wave testing, as a mature non-destructive testing technique, inverts the physical and mechanical properties of rock masses by analyzing the changes in parameters as sound waves propagate through them, and is applied to rock mass damage monitoring. Existing techniques typically evaluate the degree of damage by measuring certain specific parameters of the sound waves. For example, Chinese patent document CN113899811B discloses an acoustic wave testing system for cumulative damage in coal mine roadways. This system discloses a borehole layout for acoustic wave testing of cumulative damage in the roof rock mass of a coal mine roadway. It can achieve both single-hole planar refraction wave testing and repeated testing between pairs of boreholes, comprehensively reflecting the sound velocity of the rock mass within the three-hole area, thus reflecting the development of rock mass fractures. The differences in test results between the three boreholes can reflect the differences in fracture damage in different directions of the roof rock mass, thereby allowing for targeted design of support schemes.

[0004] However, rock mass damage is a complex physical process, and its impact on sound wave propagation is multidimensional. A single parameter often cannot fully reflect the damage state. For example, relying solely on P-wave velocity for assessment, while sensitive to macroscopic fractures, may be insensitive to damage caused by the development of diffuse microfractures, thus underestimating the risk and leading to erroneous monitoring results of cumulative rock mass damage in tunnels, affecting the judgment of underground engineering safety. Summary of the Invention

[0005] To address the technical problem of insufficient accuracy in detecting cumulative damage to roadway rock mass, the present invention provides solutions in the following aspects.

[0006] In a first aspect, the present invention provides a method for detecting cumulative damage in tunnel rock mass based on acoustic wave methods, comprising:

[0007] Acquire acoustic time-domain waveform signals from multiple monitoring points within the test area of ​​the roadway rock mass, including a reference monitoring point. Based on the time-domain waveform signals, calculate multiple damage indices for each monitoring point, including: a stiffness damage index based on P-wave velocity, a filtered damage index based on power spectral density sequence, and an energy dissipation damage index based on attenuation coefficient. Based on the multiple damage indices for each monitoring point, obtain a comprehensive damage index for each monitoring point. The calculation of the comprehensive damage index includes summing the multiple damage indices and multiplying by the consistency of the multiple damage indices. Use a spatial interpolation algorithm to transform the comprehensive damage index of all monitoring points into a two-dimensional damage function and calculate the spatial gradient of the two-dimensional damage function. Obtain the structural stability at each location, where the structural stability is inversely proportional to both the comprehensive damage index and the spatial gradient. Based on the structural stability, classify the roadway surrounding rock into risk zones.

[0008] This invention achieves a multi-dimensional and comprehensive characterization of rock mass damage by simultaneously extracting a stiffness damage index reflecting stiffness changes, a filtered damage index reflecting microcrack development, and an energy dissipation damage index from acoustic signals. By combining the magnitude of the damage index with the gradient of its spatial distribution to define structural stability, this invention not only identifies severely damaged areas but also identifies potentially unstable weak zones with drastic damage changes. This provides a more comprehensive and reliable basis for risk zoning, improving the accuracy of early warning systems for roadway surrounding rock hazards.

[0009] Preferably, the calculation of the stiffness damage index includes:

[0010] The square of the ratio of the P-wave velocity of the target monitoring point to that of the reference monitoring point is obtained and recorded as the first intermediate value. The first intermediate value is subtracted from 1 and normalized to obtain the stiffness damage index of the target monitoring point. The target monitoring point is any monitoring point in the area to be tested.

[0011] Preferably, the filter impairment index satisfies the expression:

[0012] ;

[0013] In the formula, This represents the filter damage index of the target monitoring point; This represents the number of frequencies in the power spectral density sequence; This represents the spectral energy loss value at the k-th frequency of the target monitoring point; This represents the difference in spectral energy loss between the k-th frequency and the previous frequency at the target monitoring point. Represents the normalization function; The difference is represented by the value of the kth frequency of the power spectral density sequence of the benchmark monitoring point and the target monitoring point.

[0014] This invention constructs an index that simultaneously reflects the intensity of acoustic energy attenuation and the frequency-selective attenuation characteristics by multiplying the total amount of spectral energy loss with the non-uniformity of energy loss distribution in the frequency band. This makes the index more sensitive to the attenuation of high-frequency components caused by microcrack scattering, thereby improving the ability to identify early diffuse damage.

[0015] Preferably, the calculation of the energy consumption damage index includes:

[0016] The difference between the attenuation coefficient of the target monitoring point and the attenuation coefficient of the rock mass in its intact state is recorded as the first difference; the difference between the attenuation coefficient of the target monitoring point and the attenuation coefficient of the rock mass in its completely destroyed state is recorded as the second difference; and the ratio of the first difference to the second difference is recorded as the energy consumption damage index of the target monitoring point.

[0017] This invention establishes a standardized energy consumption damage evaluation index by normalizing the attenuation coefficient measured on-site between two extreme benchmarks: intact state and completely destroyed state. This can eliminate systematic errors of instruments and environment, making the monitoring results at different times and locations comparable and improving the stability and reliability of the monitoring results.

[0018] Preferably, the rock mass attenuation coefficient in the intact state and the attenuation coefficient in the completely destroyed state are obtained by conducting indoor experimental tests on rock cores obtained from the area to be tested.

[0019] Preferably, the comprehensive damage index satisfies the expression:

[0020] ;

[0021] In the formula, This represents the overall damage index of the target monitoring point; , Represents the i-th and j-th damage indices of the target monitoring point; Represents the normalization function; This represents the natural exponential function.

[0022] This invention introduces a consistency product term, which automatically adjusts the weights based on the degree of consistency among multiple damage indices. When all indices point to similar damage states, the results are enhanced; when there is significant divergence among the indices, the results are suppressed. This avoids the subjectivity of manually setting weights, making the assessment results of the comprehensive damage index more objective and reliable.

[0023] Preferably, the structural stability satisfies the expression:

[0024] ;

[0025] In the formula, The coordinates of the two-dimensional damage field representing the region to be tested are: The structural stability of the location; The coordinates of the two-dimensional damage field representing the region to be tested are: The two-dimensional damage function value at the location; The coordinates of the two-dimensional damage field representing the region to be tested are: The spatial gradient vector of the location; This represents the natural exponential function.

[0026] This invention uses an exponential function to nonlinearly combine the damage function value with its spatial gradient, which reduces the structural stability of areas with high and large damage values. It can more effectively identify dangerous areas with stress concentration or damage localization, and has higher risk warning sensitivity compared to assessment methods that rely solely on damage values.

[0027] Preferably, the step of risk zoning of the surrounding rock of the roadway based on the structural stability includes:

[0028] A first risk threshold and a second risk threshold are preset, wherein the second risk threshold is greater than the first risk threshold; regions with structural stability greater than or equal to the second risk threshold are classified as relatively stable regions; regions with structural stability greater than or equal to the first risk threshold and less than the second risk threshold are classified as potential development regions; and regions with structural stability less than the first risk threshold are classified as high-risk instability regions.

[0029] Preferably, the acquisition of acoustic time-domain waveform signals from multiple monitoring points within the test area of ​​the tunnel rock mass includes: using a one-to-one transceiver method, placing the transducer on the same surface of the test area for acquisition, wherein the preset frequency of the transducer is 50-250kHz.

[0030] Secondly, the present invention provides a tunnel rock mass cumulative damage detection system based on acoustic wave method, including a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-mentioned tunnel rock mass cumulative damage detection method based on acoustic wave method is implemented.

[0031] By adopting the above technical solution, the above-mentioned method for detecting cumulative damage in tunnel rock mass based on acoustic wave method is generated into a computer program and stored in a memory so that it can be loaded and executed by a processor. A terminal device can then be made based on the memory and processor for convenient use.

[0032] The beneficial effects of this invention are as follows:

[0033] (1) This invention constructs a comprehensive evaluation model that integrates the damage index of three physical dimensions: stiffness, filtering, and energy consumption, and introduces the consistency between indicators as dynamic weights, which overcomes the one-sidedness of single parameter evaluation and the subjectivity of traditional weighting methods.

[0034] (2) This invention combines the magnitude of damage with its spatial gradient to establish a new structural stability model, which can more accurately identify weak areas with drastic damage changes.

[0035] (3) This invention realizes the assessment process of cumulative rock mass damage in roadways from multi-dimensional data fusion to precise risk zoning, and improves the comprehensiveness, reliability and early warning capability of rock mass damage detection. Attached Figure Description

[0036] Figure 1 This is a flowchart illustrating the cumulative damage detection method for tunnel rock mass based on acoustic wave method in this invention;

[0037] Figure 2 This is a schematic diagram illustrating a time-domain waveform signal;

[0038] Figure 3 This is a schematic diagram illustrating the risk zoning of the area to be tested. Detailed Implementation

[0039] This invention discloses a method for detecting cumulative damage in tunnel rock mass based on acoustic wave method, referring to... Figure 1 This includes steps S1-S4:

[0040] S1: Acquire acoustic data from multiple monitoring points within the test area of ​​the tunnel rock mass.

[0041] It should be noted that, considering the insufficient robustness of data analysis from a single monitoring point, this invention sets up a monitoring grid for the area to be monitored, thereby enabling overall monitoring and analysis, and improving monitoring accuracy and robustness.

[0042] Specifically, in the area to be tested in the tunnel rock mass, the rock surface is ground and a measurement grid is set up; each grid point of the measurement grid is recorded as a monitoring point; a monitoring point with intact structure is selected and recorded as a reference monitoring point; using a one-to-one transmission and reception method, an ultrasonic pulse transmitter / receiver, a transducer with a preset frequency and a data acquisition system are used to collect the time-domain waveform signal of the sound wave after propagation at a preset interval at each monitoring point.

[0043] It should be noted that the measurement grid can be set according to the detection accuracy requirements, for example, in a block rice On the tunnel wall area of ​​1 meter, there are 0.5-meter intervals between the installations. The measurement grid; the grinding process can be performed using a handheld angle grinder to create a smooth and flat area; the preset frequency of the transducer can be selected according to the rock mass characteristics and detection depth requirements, for example, 50-250kHz; the preset spacing can be set according to the site conditions, for example, setting the preset spacing to 0.2 meters; the sampling rate of the data acquisition system should satisfy the Nyquist sampling theorem, for example, a sampling rate of 5MS / s (megasamples per second); the one-to-one transmitting and receiving method refers to placing a transmitting transducer and a receiving transducer at a fixed preset spacing on the same surface of the rock mass to be measured for measurement. This method does not require operation on the opposite side of the rock mass, is suitable for single-sided contact environments such as tunnels, and can accurately measure surface wave velocity and calculate attenuation. Figure 2 This is a schematic diagram of a time-domain waveform signal.

[0044] At this point, the acoustic time-domain waveform signals of all monitoring points within the test area have been obtained.

[0045] S2: Calculate multiple damage indices for each monitoring point based on the time-domain waveform signal of the measurement grid.

[0046] It should be noted that rock mass damage is a complex process, and its impact on sound wave propagation is multi-dimensional. Therefore, a single acoustic parameter cannot fully reflect the damage state. For example, relying solely on the P-wave (primary wave) velocity for assessment is only sensitive to rock masses with a few macroscopic through-cracks, but for rock masses with a diffuse microfracture network, the velocity change may be small, leading to an underestimation of the damage severity. Considering that different damage mechanisms leave different damage conditions due to the different physical characteristics of sound waves, such as propagation time, energy dissipation, and frequency components, this invention decomposes and extracts multiple core physical features through comprehensive analysis of the original waveform.

[0047] It should be further explained that rock mass damage mainly affects sound wave propagation through the following physical mechanisms: the appearance of fissures alters the effective propagation path of sound waves, leading to a longer propagation time and thus a decrease in wave velocity; friction and scattering at the fissure surface under sound wave disturbance dissipate energy, affecting the attenuation of sound wave energy; small-sized micro-fissures scatter and absorb high-frequency sound waves more strongly than low-frequency sound waves, thus affecting the spectral morphology. This invention calculates the damage index for each monitoring point targeting these three physical mechanisms to achieve a comprehensive analysis of the damage state.

[0048] Specifically, for time-domain waveform signals acquired at any monitoring point, the P-wave propagation time is determined using an initial arrival picking algorithm, such as the short-long window averaging method (STA / LTA), and the P-wave velocity is calculated. The P-wave velocity is equal to a preset interval divided by the P-wave propagation time. It should be noted that the initial arrival picking algorithm is an existing method for automatically and accurately identifying the first arrival time of the P-wave from noisy waveform signals, and the short-long window averaging method is existing technology and will not be elaborated upon here.

[0049] For example, the benchmark monitoring point is denoted as The initial arrival time was obtained from the benchmark monitoring point. The calculated reference wave velocity is At the monitoring point Pick up the initial arrival time The wave velocity at that point was calculated. The It is obtained by rounding down to the nearest integer.

[0050] It should be noted that damage to the rock mass, i.e., the generation of microcracks, reduces the overall effective elastic modulus of the rock mass. According to elastic wave theory, the square of the P-wave velocity is proportional to the elastic modulus. Therefore, the relative reduction in wave velocity can be used to calculate the degree of loss of rock mass stiffness.

[0051] Preferably, the stiffness damage index of any monitoring point is calculated based on the relative decrease in P-wave velocity at the monitoring point, including:

[0052] Any monitoring point that is not a baseline monitoring point is recorded as a target monitoring point.

[0053] The stiffness damage index of the target monitoring point satisfies the following expression:

[0054] ;

[0055] In the formula, This represents the stiffness damage index of the target monitoring point; The P-wave velocity at the target monitoring point; The P-wave velocity at the reference monitoring point; This represents the normalization function.

[0056] For example, for monitoring points Its stiffness damage index is: The It is the result rounded to two decimal places.

[0057] The power spectral density sequence of the target monitoring point is obtained by processing the time-domain waveform signal of the target monitoring point using the time-frequency transformation method. ,in This refers to the index of the frequency point. The time-frequency transformation method, such as the Fast Fourier Transform, is existing technology and will not be described in detail here.

[0058] It should be noted that the attenuation of sound waves in damaged rock masses exhibits a strong frequency dependence. Due to the short wavelength of high-frequency sound waves, they are more sensitive to micro-fractures ranging from micrometers to millimeters, resulting in more severe attenuation of high-frequency components. Using only a single spectral characteristic, such as peak frequency or centroid frequency, is easily affected by noise interference and cannot comprehensively reflect the overall changes in the spectral morphology. Therefore, this invention simultaneously calculates the overall degree of spectral energy loss and the non-uniformity of the loss distribution at different frequencies. The overall energy loss reflects the intensity of attenuation, while the non-uniformity reflects the selectivity of attenuation through spectral distortion. Thus, this invention constructs a comprehensive assessment of the overall spectral attenuation and distortion by multiplying the cumulative amount of spectral energy loss by the volatility of the spectral energy loss distribution.

[0059] Preferably, the filter impairment index for any monitoring point is obtained based on the energy attenuation and morphological distortion of the power spectral density sequence at the monitoring point, including:

[0060] The filter damage index of the target monitoring point satisfies the following expression:

[0061] ;

[0062] ;

[0063] ;

[0064] In the formula, This represents the filter damage index of the target monitoring point; This represents the number of frequencies in the power spectral density sequence; , This represents the spectral energy loss value at the (k+1)th and kth frequencies of the target monitoring point; This represents the difference in spectral energy loss between the k-th frequency and the previous frequency at the target monitoring point. , This represents the value of the k-th frequency in the power spectral density sequence of the reference monitoring point and the target monitoring point; This represents the normalization function.

[0065] In the formula, The total energy attenuation caused by damage is reflected by summing up the absolute value of energy loss over the entire frequency band. The larger this value is, the greater the filter damage index of the target monitoring point. By accumulating the difference of spectral energy loss in the frequency domain, the selective attenuation characteristics of spectral energy loss to a specific frequency band and the degree of spectral distortion are reflected. The larger the value, the higher the degree of spectral distortion of the target monitoring point, thus indicating that the filter impairment index of the target monitoring point is greater.

[0066] For example, benchmark monitoring points The power spectral density sequence is Monitoring points The power spectral density sequence is Then the monitoring point The spectral energy loss sequence is , .

[0067] It should be noted that the sound wave attenuation coefficient directly reflects the degree of sound wave energy dissipation during propagation. Sound wave attenuation is mainly caused by friction and scattering of micro-cracks in the rock mass. By normalizing it between intact and damaged states, a standardized energy dissipation damage index can be obtained.

[0068] Preferably, the energy consumption damage index of each monitoring point is obtained based on the relative change of the attenuation coefficient of the power spectrum at each monitoring point, including:

[0069] The spectral ratio method is used to calculate the acoustic attenuation coefficient of the monitoring point by comparing the power spectrum of the monitoring point with that of the reference monitoring point.

[0070] For example, for monitoring points The attenuation coefficient was calculated. .

[0071] Indoor experiments were conducted to test rock cores obtained from the field, and the rock mass attenuation coefficients under intact and completely destroyed conditions were determined.

[0072] The energy consumption damage index of the target monitoring point satisfies the following expression:

[0073] ;

[0074] In the formula, This indicates the energy consumption damage index of the target monitoring point; The sound wave attenuation coefficient at the target monitoring point; and The rock mass attenuation coefficient represents the rock mass attenuation coefficient under intact and completely destroyed conditions. The rock mass attenuation coefficient is obtained by laboratory testing of rock cores obtained from the rock mass.

[0075] For example, the rock mass attenuation coefficient under intact conditions is obtained through indoor experimental calibration. Rock mass attenuation coefficient under complete failure state For monitoring points Its energy consumption and damage index is: .

[0076] Thus, the stiffness damage index, filter damage index, and energy consumption damage index of each monitoring point were obtained.

[0077] S3: Based on the stiffness damage index, filter damage index, energy dissipation damage index, and consistency of each damage index at each monitoring point, obtain the comprehensive damage index for each monitoring point.

[0078] It should be noted that, to obtain more robust and comprehensive evaluation indicators, it is necessary to effectively integrate the stiffness damage index and filtered damage index of monitoring points reflecting different physical mechanisms. Considering that existing linear weighted averaging methods rely on human experience for weight setting, are highly subjective, and fail to reflect the inherent consistency between different damage indicators, reliable evaluation results should not only consider the numerical values ​​of each indicator but also determine whether they point to the same conclusion. For example, the presence of a small number of macroscopically penetrating fractures in a rock mass may lead to a large stiffness damage index, but due to the limited total number of fractures and the finite total friction surface area, the energy dissipation damage index may only be moderate. In this case, differences exist between the indicators, and a simple weighted average would obscure this characteristic.

[0079] It should be further noted that when multiple independent damage indicators yield similar damage assessment values—for example, stiffness loss, energy dissipation, and filtering effects all exhibiting moderate levels—the confidence level of the assessment result is higher. Conversely, if the values ​​of each indicator differ significantly, such as a large change in wave velocity but a small attenuation, it suggests the possible existence of a specific damage mechanism or measurement noise, resulting in a lower confidence level for the assessment result. Therefore, this invention constructs a comprehensive damage index characterizing the multidimensional damage index of monitoring points and the consistency of multiple indicators.

[0080] Specifically, based on the stiffness damage index, filter damage index, energy dissipation damage index, and consistency of each damage index at each monitoring point, a comprehensive damage index for each monitoring point is obtained, including:

[0081] The stiffness damage index, filter damage index, and energy dissipation damage index of the target monitoring point are each recorded as a damage index of the target monitoring point, for a total of three damage indices for the target monitoring point.

[0082] The comprehensive damage index of the target monitoring point satisfies the expression:

[0083] ;

[0084] In the formula, This represents the overall damage index of the target monitoring point; , Represents the i-th and j-th damage indices of the target monitoring point; Represents the normalization function; This represents the natural exponential function.

[0085] In the formula, This represents the difference between any two different damage indices. This represents the sum of differences between all different damage indices. This value reflects the consistency between different damage indices. The larger the value, the smaller the consistency between different damage indices, and the lower the reliability of the damage at the target monitoring point, thus assigning a smaller weight to the damage at the target monitoring point. This represents the cumulative sum of damage indices at the target monitoring points. This value is the main effect term of the comprehensive damage index. The larger this value is, the greater the comprehensive damage index of the target monitoring points. By multiplying the main effect term with the consistency of different damage indices, the final comprehensive damage index is enhanced when multiple indicators synergistically point to the same damage state, and suppressed otherwise.

[0086] For example, monitoring points The overall damage index: the main effect term is: The dispersion of the consistency term is: Its unnormalized comprehensive damage index is: The It is the result rounded to two decimal places.

[0087] At this point, the comprehensive damage index of each monitoring point was obtained.

[0088] S4: Based on the comprehensive damage index of all monitoring points and combined with the structural gradient analysis of the damage field, the surrounding rock of the roadway is divided into risk zones.

[0089] It should be noted that the comprehensive damage index is a series of values ​​corresponding to discrete monitoring points. For practical engineering applications, such as guiding support design or delineating risk areas, discrete numerical points cannot provide intuitive and continuous spatial distribution information, nor can they clearly reveal the gradual process of the extent, shape, and severity of the damage area. Therefore, this invention transforms these discrete data points into a continuous and visualized damage field.

[0090] It should be further explained that traditional spatial interpolation methods, such as Kriging interpolation or inverse distance weighted interpolation, while transforming these discrete points into continuous, visualized damage maps, only show the magnitude of the damage and ignore the spatial morphological information of the damage. For rock mass stability, the distribution pattern of damage is as important as its magnitude. For example, areas with rapidly changing damage, even with a low damage index, can become weak points for structural instability due to stress concentration. Therefore, this invention calculates the rate of change of the comprehensive damage index in space, combining the comprehensive damage situation of the rock mass with the damage morphology to construct a structural stability that better reflects the true instability risk. Based on this structural stability, risk zoning is performed on the surrounding rock of the tunnel to achieve cumulative damage monitoring of the tunnel rock mass.

[0091] Specifically, based on the comprehensive damage index of all monitoring points and combined with the structural gradient analysis of the damage field, the surrounding rock of the roadway is divided into risk zones, including:

[0092] Using a spatial interpolation algorithm, the comprehensive damage index of all monitoring points is transformed into a two-dimensional damage function. All locations and their corresponding two-dimensional damage function values ​​constitute the two-dimensional damage field of the area to be tested. It should be noted that the spatial interpolation algorithm, such as Kriging interpolation, is existing technology and will not be elaborated upon here.

[0093] Calculate the spatial gradient vector of the two-dimensional damage function at each location and take its magnitude.

[0094] The structural stability at any location in the two-dimensional damage field of the region under test satisfies the expression:

[0095] ;

[0096] In the formula, The coordinates of the two-dimensional damage field representing the region to be tested are: The structural stability of the location; The coordinates of the two-dimensional damage field representing the region to be tested are: The two-dimensional damage function value at the location; The coordinates of the two-dimensional damage field representing the region to be tested are: The spatial gradient vector of the location; This represents the natural exponential function.

[0097] In the formula, The coordinates of the two-dimensional damage field representing the region to be tested are: The magnitude of the spatial gradient vector; This indicates that the coordinates of the two-dimensional damage field of the region to be tested are... The spatial gradient vector of the location is used as a weight to weight the two-dimensional damage function value. The larger the value, the higher the structural risk at the corresponding location. Simultaneously, if the two-dimensional damage function value at the corresponding location is larger, the coordinates of the two-dimensional damage field of the area to be tested are... The weaker the structural stability of a location.

[0098] For example, , , , , The gradient is approximated using the central difference method, with the grid spacing... , , .

[0099] It should be noted that, in order to intuitively reflect the structural stability of different areas, this invention performs visualization processing on the structural stability of the area to be tested. The area to be tested is divided by a preset threshold and different colors are applied, so that the damage to the tunnel rock mass can be transmitted in a timely and accurate manner, thereby enabling timely repair.

[0100] Preferably, a first risk threshold and a second risk threshold are preset, wherein the second risk threshold is greater than the first risk threshold; regions with structural stability greater than or equal to the second risk threshold are classified as relatively stable regions; regions with structural stability greater than or equal to the first risk threshold and less than the second risk threshold are classified as potential development regions; and regions with structural stability less than the first risk threshold are classified as high-risk instability regions. It should be noted that, as... Figure 3 This is a schematic diagram of the risk zoning of the area to be tested.

[0101] Thus, the assessment and zoning process of cumulative damage to the tunnel rock mass was completed, and the detection of cumulative damage to the tunnel rock mass was completed.

[0102] The present invention also discloses a tunnel rock mass cumulative damage detection system based on acoustic wave method, including a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, the tunnel rock mass cumulative damage detection method based on acoustic wave method according to the present invention is implemented.

[0103] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

[0104] While this specification has shown and described numerous embodiments of the invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many modifications, alterations, and alternatives will occur to those skilled in the art without departing from the spirit and essence of the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in the practice of this invention.

Claims

1. A method for detecting cumulative damage in tunnel rock mass based on acoustic wave method, characterized in that, include: Acquire acoustic time-domain waveform signals from multiple monitoring points within the test area of ​​the roadway rock mass, including a reference monitoring point; Based on the time-domain waveform signal, multiple damage indices are calculated for each monitoring point, including: stiffness damage index based on P-wave velocity, filtering damage index based on power spectral density sequence, and energy dissipation damage index based on attenuation coefficient. The calculation of the stiffness damage index includes: obtaining the square of the ratio of the P-wave velocity of the target monitoring point and the reference monitoring point, which is recorded as the first intermediate value; subtracting the first intermediate value from 1 and performing normalization processing to obtain the stiffness damage index of the target monitoring point; the target monitoring point is any monitoring point in the area to be measured. The filter impairment index satisfies: ； This represents the filter damage index of the target monitoring point; This represents the number of frequencies in the power spectral density sequence; This represents the spectral energy loss value at the k-th frequency of the target monitoring point; This represents the difference in spectral energy loss between the k-th frequency and the previous frequency at the target monitoring point. Represents the normalization function; The difference in the power spectral density sequence of the benchmark monitoring point and the target monitoring point is represented by the difference in the value of the kth frequency. The calculation of the energy consumption damage index includes: The difference between the attenuation coefficient of the target monitoring point and the attenuation coefficient of the rock mass in its intact state is recorded as the first difference; the difference between the attenuation coefficient of the target monitoring point and the attenuation coefficient of the rock mass in its completely destroyed state is recorded as the second difference; the ratio of the first difference and the second difference is recorded as the energy consumption damage index of the target monitoring point. Based on multiple damage indices at each monitoring point, a comprehensive damage index is obtained for each monitoring point. The calculation of the comprehensive damage index includes summing up the multiple damage indices and multiplying by the consistency of the multiple damage indices. The comprehensive damage index of all monitoring points is transformed into a two-dimensional damage function using a spatial interpolation algorithm, and the spatial gradient of the two-dimensional damage function is calculated. The structural stability at each location is obtained. The structural stability is inversely proportional to the magnitude of both the comprehensive damage index and the spatial gradient. The surrounding rock of the roadway is divided into risk zones based on the structural stability. Structural stability satisfies: ； , , The coordinates of the two-dimensional damage field in the region to be tested are respectively: The structural stability of the location, the two-dimensional damage function value, and the spatial gradient vector; This represents the natural exponential function.

2. The method for detecting cumulative damage in tunnel rock mass based on acoustic wave method according to claim 1, characterized in that, The attenuation coefficients of the rock mass in its intact state and in its completely destroyed state were obtained through indoor experimental testing of rock cores obtained from the area to be tested.

3. The method for detecting cumulative damage in tunnel rock mass based on acoustic wave method according to claim 1, characterized in that, The comprehensive damage index satisfies the expression: ； In the formula, This represents the overall damage index of the target monitoring point; , Represents the i-th and j-th damage indices of the target monitoring point; Represents the normalization function; This represents the natural exponential function.

4. The method for detecting cumulative damage in tunnel rock mass based on acoustic wave method according to claim 1, characterized in that, The risk zoning of the surrounding rock of the roadway based on the structural stability includes: A first risk threshold and a second risk threshold are preset, wherein the second risk threshold is greater than the first risk threshold; regions with structural stability greater than or equal to the second risk threshold are classified as relatively stable regions; regions with structural stability greater than or equal to the first risk threshold and less than the second risk threshold are classified as potential development regions; and regions with structural stability less than the first risk threshold are classified as high-risk instability regions.

5. The method for detecting cumulative damage in tunnel rock mass based on acoustic wave method according to claim 1, characterized in that, The acquisition of acoustic time-domain waveform signals from multiple monitoring points within the test area of ​​the tunnel rock mass includes: using a one-to-one transducer method, placing the transducer on the same surface of the test area for acquisition, wherein the preset frequency of the transducer is 50-250kHz.

6. A tunnel rock mass cumulative damage detection system based on acoustic wave method, characterized in that, include: A processor and a memory, the memory storing computer program instructions that, when executed by the processor, implement the method for detecting cumulative damage in tunnel rock mass based on acoustic wave method according to any one of claims 1-5.

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