High-precision space positioning method and device considering rock anisotropy degradation sound signal

Abstract

The invention provides a high-precision space positioning method and device considering rock anisotropy degradation sound signals, and relates to the technical field of geotechnical engineering. Aiming at the problems of heterogeneity of a rock mass structure and anisotropy in acoustic signal propagation in the prior art, a novel wave velocity attenuation model considering initial wave velocity anisotropy and anisotropy fracture process evolution is provided, so that more accurate acoustic emission space positioning is realized. According to the method, an acoustic emission sensor is arranged on a rock sample, seismic source waveform data are collected, a total stress-strain curve is obtained through a true triaxial experiment, and a function model of damage and wave velocity is established. And through an optimization algorithm, constructing a seismic source positioning objective function and carrying out iteration, and finally determining the position of a seismic source. According to the method, the energy and the damage mechanism of the acoustic emission signal can be analyzed, and the high-precision quantitative characterization of the damage position, the micromechanism and the released energy in the anisotropic rock mass fracture process is realized.

Description

Technical Field

[0001] The present invention relates to the field of geotechnical engineering technology, and in particular to a high-precision spatial positioning method and device for acoustic signals taking into account anisotropic degradation of rock masses. Background Art

[0002] Due to the heterogeneity of natural rock mass structure and the initial anisotropic characteristics caused by the inherent structural anisotropy of the rock mass, when the rock mass fractures under stress, the anisotropic evolution of wave velocity caused by the anisotropic damage mechanism causes the wave velocity of the sound wave to also have anisotropic characteristics during the propagation of the rock mass. The current use of a single velocity model does not take into account the anisotropy of wave velocity during rock mass propagation, making positioning less accurate. In the field of multi-physics field monitoring of rock mass fractures, signals in different frequency bands have significant characteristic differences: the sound signal (SS) mainly exhibits low-frequency characteristics, the microseismic signal (MS) exhibits medium- and low-frequency characteristics, and the acoustic signal (AE) covers the high-frequency range. Traditional monitoring methods are limited by the physical characteristics of single-band acquisition equipment and are often only able to obtain fracture information in a local frequency band, making it difficult to establish a complete fracture evolution characteristic spectrum.

[0003] Traditional moment tensor positioning methods have significant limitations in practical engineering applications. Accurate positioning requires at least six acoustic emission probes to simultaneously receive valid signals. However, due to complex on-site geological conditions and limited sensor deployment, the requirement for simultaneous multi-probe reception is often difficult to achieve. This significantly reduces positioning accuracy, and the method is prone to falling into local minima, being susceptible to the influence of individual sensors, exhibiting low stability, and lacks universal applicability. Therefore, further research is needed on earthquake source location algorithms and velocity models that consider anisotropic rock degradation.

[0004] In summary, current acoustic signal monitoring still has the following shortcomings: While existing velocity models can reflect the true wave velocity of rock masses, they cannot reflect the wave velocity attenuation pattern after rock degradation. Existing positioning algorithms require multiple acoustic emission probes, resulting in a large computational load and unstable positioning, significantly reducing positioning efficiency. Furthermore, the signal energy response received by each acoustic emission probe varies significantly, and a unified technical standard for determining energy response has not yet been established, making it difficult to ensure the reliability and comparability of energy calculation results. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a high-precision spatial positioning method and device for acoustic signals that take into account the anisotropic degradation of rock masses; specifically, an algorithm based on a small number of probe signals is proposed, which takes into account the initial anisotropy of the rock mass and the anisotropic wave velocity evolution of the fracture process. By innovatively optimizing the signal processing algorithm and positioning model, only a small amount of effective signals are required to accurately judge the rock fracture mechanism, which significantly improves the engineering applicability and positioning reliability of the method, and establishes a standardized energy response determination method based on multi-probe signals. By constructing an energy correction model and a standardized processing flow, the simultaneous and accurate identification of the fracture mechanism and energy characteristics is achieved.

[0006] On the one hand, a high-precision spatial positioning method for acoustic signals considering anisotropic degradation of rock mass includes the following steps:

[0007] Step S1: Deploy and bond full-band broadband sensors to the rock sample. Four full-band broadband sensors are used to collect low, medium, and high-frequency microseismic and acoustic emission signals. Four rectangular measurement areas are established for the sensors. The full-band broadband sensors collect source waveform data and calculate the arrival time difference between other full-band broadband sensors and a reference node.

[0008] In step S1, full-band broadband sensors are arranged on the edge of a rectangular measurement area of ​​the rock mass, and adhesive is applied during the arrangement to establish a measurement area in the shape of a rectangular parallelepiped. The full-band broadband sensors are used to collect acoustic emission source waveforms, and the time it takes for the source wave to travel from the source to the observation point is obtained. One of the full-band broadband sensors is selected as a reference node, and the arrival time difference between the other three full-band broadband sensors and the selected full-band broadband sensor is obtained by performing a difference calculation.

[0009] Step S2: Conduct true triaxial experiments at different stress levels, obtain stress-strain curves, and then establish a damage degradation equation. Then, simultaneously measure the wave velocity during the rock fracture process and establish a function of damage and wave velocity.

[0010] The details are as follows: when the rock is in its initial state, the wave velocity measurement function of the full-band broadband sensor is used. One of the full-band broadband sensors is selected as the reference node and the velocity is measured between the other three full-band broadband sensors in pairs to obtain the wave velocity in the three directions of the initial rock. Then, a true triaxial experiment of rock degradation under different stress conditions is carried out. During the experiment, measurements are made between the sensor and the reference node sensor to obtain the wave velocity and total stress-strain curve in the three directions during the rock failure process. The principal stress σ of the rock during the true triaxial experiment of rock degradation is i Anisotropic deformation modulus K in the direction i , the calculation formula is defined as:

[0011] ;

[0012] Among them, K i The axial stress increment dσ and the three elastic principal strain increments dε in each cyclic loading and unloading of the rock specimen are ie The absolute value of the ratio is determined according to the calculated K i Define the Young's modulus E in the three main directions i , i=1,2,3, assuming that the initial values ​​of Young's modulus E1, E2 and E3 in the three directions are the same, then E i The definition is as follows:

[0013] ;

[0014] Where μ1 and μ2 are the lateral Young's modulus proportional factors, defined as:

[0015] ;

[0016] where K 1,0 is the rock principal stress σ i Initial deformation modulus in the direction, K 2,0 and K 3,0 is the initial deformation modulus in the lateral direction;

[0017] According to the evolution law of mechanical parameters and nonlinear fitting method, E1, E2 and E3 are fitted with equivalent plastic strain ε p The evolution equation of the changing parameters:

[0018] ;

[0019] ;

[0020] ;

[0021] Among them, a i 、b i and c i are the fitting coefficients related to the second principal stress σ2 and the third principal stress σ3, i = 1, 2, 3, E i,0 is the initial elastic modulus, ε 1p , ε 2p and ε 3p are the maximum plastic principal strain, the intermediate plastic principal strain and the minimum plastic principal strain, respectively. 1i 、a 2i 、a 3i 、a 4i 、a 5i is the weight coefficient describing the evolution of the plastic strain component to the elastic modulus E, b 1i 、b 2i、b 3i 、b 4i 、b 5i To control the nonlinear influence coefficient of plastic strain on modulus decay or hardening, c 1i 、c 2i 、c 3i 、c 4i 、c 5i is the quadratic term or high-order correction coefficient of plastic strain on modulus evolution; wave velocity and Young's modulus E in three directions i The relationship is as follows:

[0022] ;

[0023] in, is Young's modulus, is the density, is the wave velocity, i =1,2,3, is the Kronecker function, P ij is a permutation matrix. The wave velocity decays as the rock deteriorates and its evolution equation is as follows:

[0024] ;

[0025] Where t is the propagation time, is the initial wave velocity, α is the attenuation coefficient;

[0026] Step S3: Based on the arrival time difference and taking into account the wave velocity attenuation law with rock degradation, the earthquake source location objective function is established, the earthquake source position is calculated by the sensor arrival time, and the residual formula is optimized using the L1 norm;

[0027] Specifically: Assume that there is a seismic source on a two-dimensional plane, and the source coordinates are P=[xy] T , the full-band broadband sensor is located at S j = [x j y j ], j = 1,2,3...n, n is the number of sensors; therefore, the time t for the P wave to be emitted from the earthquake source and received by the jth sensor is j for:

[0028] ;

[0029] Where v represents the propagation speed of P wave in the positioning model, d z represents the distance between the zth sensor and the earthquake source, (x0, y0) is the coordinate of the earthquake source;

[0030] If the full-band broadband sensor T1 is used as the reference node, the arrival time difference between the zth sensor and T1 is expressed as:

[0031] ;

[0032] When the measurement area is a three-dimensional space, the time when the i-th sensor receives the source signal relative to the reference node is expressed as:

[0033] ;

[0034] Where (x0, y0, z0) is the coordinate of the earthquake source in three-dimensional space, (x1, y1, z1) is the coordinate of the reference full-band broadband sensor in three-dimensional space, (x i ,y i , z i ) are the coordinates of other full-band broadband sensors in three-dimensional space.

[0035] make , ;

[0036] The residual formula f based on the time difference positioning model is obtained:

[0037] ;

[0038] where R i and R1 represent the source P to the full-band broadband sensor S i Distance from full-band broadband sensor S1, i=1,2,3...n, V i is the function of damage and wave velocity, k is the norm; according to the function of damage and wave velocity established previously; the v in its function is changed to the newly established function of damage and wave velocity V i , the obtained formula is as follows:

[0039] ;

[0040] When there is data with an error greater than the set threshold, the minimum absolute value method, that is, the L1 norm, is used to optimize the objective function. That is, the sum of the residual absolute values ​​of the time difference between each full-band wideband sensor and the reference full-band wideband sensor is used as the objective function f, that is, k is 1, as shown in the formula:

[0041] ;

[0042] The optimization algorithm is used to iteratively solve the minimum value of the objective function value f and obtain the source location (x0, y0, z0). When the objective function value f takes the minimum value, the solution (x0, y0, z0) is the optimal location of the source.

[0043] Step S4: Select four points around the full-band broadband sensor within a set threshold range from the center, establish an initial tetrahedron, calculate the residual, compare the residuals of the four vertices, eliminate the point with the largest residual, and optimize the tetrahedron through iterative stretching and shrinking operations until the residual value reaches the threshold;

[0044] In step S4, four points are randomly selected near the center of the sensor array to establish an initial tetrahedron in three-dimensional space. Based on the coordinates of each vertex of the initial tetrahedron, the initial wave velocity anisotropy and the wave velocity decay to time difference during the evolution of the anisotropic rupture process are considered. The residuals of the four vertices are calculated using the L1 norm optimization residual formula. The residual values ​​are calculated and compared to find the minimum point f of the residual function of the vertex of the initial tetrahedron. min and the maximum point f max , and calculate the length of each side of the initial tetrahedron, d, and then eliminate the point f with the largest residual difference max , and continuously stretch and shrink the tetrahedron, replace and add new vertices to construct a new simplex tetrahedron, and judge whether the minimum residual value f reaches the predetermined threshold of the function iteration. If not, continue to search and construct a new simplex tetrahedron. If the residual value of the positioning target function is less than the predetermined threshold, the coordinate value of the simplex vertex is the positioning coordinate point;

[0045] Step S5: When the residual value reaches the termination threshold, within the spatial range where the optimal value error is less than 1, use the random number generation command to randomly select hundreds of minimum spacing points and compare the optimal value residual value f k The residual value f with the random point i , if f k <f i , then it is the global optimal point; if there exists f i >f, then the point is the local optimal point, the calculation is exited, the initial point is reselected and the process jumps to step S4 for search calculation;

[0046] Step S6, obtaining the optimal location of the earthquake source by inversely calculating the earthquake source coordinate parameters corresponding to the minimum residual value;

[0047] Step S7: Based on the positioning event, each probe receives SS / MS / AE signal information to determine the microscopic damage type and positioning energy;

[0048] The details are as follows:

[0049] The SS / MS / AE wave signal information received by each full-band broadband sensor at the location event of the failure is recorded and stored in the computer system. The location event at the rock fracture location is subjected to inversion analysis, and the fracture types are classified into tension fracture, shear fracture and mixed tension-shear fracture. The failure type of the rock in different time periods is determined as follows;

[0050] RA = Duration / Amplitude;

[0051] AF = Ringing Count AE / Duration;

[0052] For the classification of RA and AF, the optimal boundary method is adopted. The slope of the dividing line AF / RA is defined as N. Signals with AF / RA < N are defined as tensile fracture signals, and signals with AF / RA > N are defined as shear fracture signals. By conducting pure tensile experiments and pure shear experiments on rocks, the slope of the dividing line N is determined;

[0053] The computer system determines the level of the positioning event energy. It is the set of SS, MS, and AE signals generated by the same fracture source received by the full-bandwidth broadband sensor. The positioning event energy is the area integral under the signal detection envelope during the time period from the start time of receiving the first signal to the end time of the last signal. The specific calculation is as follows:

[0054] ;

[0055] G5 = n1G1 + n2G2 + n3G3 + n4G4;<了

[0056] Where E is the positioning event energy, is the end time of the last signal, is the start time of the first signal, , , , are weighting coefficients, G1, G2, G3, G4, G5 are the signals received by the full-bandwidth broadband sensor, A ring [[ID=​​​​​​​​​​​Processing module: Based on the damage degradation data and wave velocity data in three directions, a damage-wave velocity function is constructed that takes into account the anisotropy of the initial wave velocity and the evolution of the anisotropic rupture process. A source location objective function is established based on the arrival time difference and taking into account the attenuation law of wave velocity with rock degradation. The SS / MS / AE acoustic signal information is trained, calculated, analyzed and tested. Based on the analysis and processing results, the location event is obtained, verified and reviewed, and the acoustic signal information is classified and stored as a single location event.

[0061] Reprocessing module: Calculate, analyze, optimize, extract and integrate the acoustic signal information of each positioning event, determine its microscopic damage type and positioning energy, verify and store it again;

[0062] Output module: Output rock fracture location events, micro-damage types, location energy calculation results and review results in the form of charts for users to view.

[0063] The beneficial effects of adopting the above technical solution are:

[0064] The present invention provides a high-precision spatial positioning method and device for acoustic signals taking into account anisotropic degradation of rock mass, which has the following beneficial effects:

[0065] 1. The present invention improves the L1 norm positioning model based on arrival time difference, solves the problem of inaccurate positioning caused by the initial anisotropy of natural rock mass and the anisotropy of wave velocity attenuation caused by rock mass damage and deterioration, and proposes a wave velocity attenuation model that takes into account the initial wave velocity anisotropy and the evolution of the anisotropic rupture process, which is more accurate than the single velocity model, making positioning more stable and accurate.

[0066] 2. The present invention improves the termination condition of the simplex spatial positioning iterative algorithm. Based on the wave velocity attenuation model that considers the anisotropy of the initial wave velocity and the evolution of the anisotropic rupture process, an improved simplex acoustic emission spatial positioning method is proposed. The method reduces the influence of individual discrete points, has good solution stability and high accuracy, and has improved positioning accuracy compared with the traditional time difference positioning algorithm based on a single velocity model. The number of sensors required can be reduced to 4 to achieve positioning.

[0067] 3. The present invention innovatively develops a full-band signal synchronous acquisition system, achieving a breakthrough in the collaborative perception of wide-band signals. By establishing an energy coupling model for multi-band signals, it successfully solves the technical difficulties of poor spatiotemporal correlation and difficult feature fusion of signals in different frequency bands, providing a new technical paradigm for the multi-scale characterization of the entire rock fracture process.

[0068] 4. This invention establishes a standardized method for determining energy response based on multi-probe signals. By constructing an energy correction model and a standardized processing flow, it achieves simultaneous and precise identification of fracture mechanisms and energy signatures. This method not only determines the energy released at each location during fracture but also allows for a simple assessment of this energy magnitude, accurately determining the fracture mechanism at each location. This method addresses the technical challenges of standardized energy response determination and significantly improves the accuracy and reliability of fracture mechanism analysis, providing a new technical approach for quantitatively characterizing rock fracture processes. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 This is a rectangular parallelepiped positioning model diagram of the high-precision spatial positioning method of acoustic signals considering anisotropic degradation of rock mass according to the present invention;

[0070] Figure 2 This is a two-dimensional acoustic signal to time difference method positioning model diagram of the high-precision spatial positioning method of acoustic signals considering anisotropic degradation of rock mass in the present invention;

[0071] Figure 3 A flowchart of a high-precision spatial positioning method for acoustic signals taking into account anisotropic degradation of rock masses provided by an embodiment of the present invention;

[0072] Figure 4 A schematic diagram of a cloud server device provided in an embodiment of the present invention;

[0073] Figure 5 This is a schematic structural diagram of a high-precision spatial positioning device for acoustic signals taking into account anisotropic degradation of rock masses provided in an embodiment of the present invention;

[0074] Figure 6 is the full stress-strain curve simulated by the three-dimensional degradation model under different σ2 and σ3 stresses in the embodiment of the present invention;

[0075] Figure 7 σ2 is the elastic modulus curve simulated by the three-dimensional degradation model under different σ3 stresses in the embodiment of the present invention;

[0076] Figure 8 Graph showing the acoustic signal and strain processing results of a true triaxial shear failure test on granite in a multi-stage disturbance according to an embodiment of the present invention;

[0077] Figure 9 This is a diagram showing the location of the positioning event and the positioning energy processing results of the granite multi-stage disturbance true triaxial shear failure test in an embodiment of the present invention;

[0078] Figure 10 This is a diagram showing the microscopic failure type processing results of the multi-stage disturbance true triaxial shear failure test on granite in an embodiment of the present invention. DETAILED DESCRIPTION

[0079] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0080] On the one hand, a high-precision spatial positioning method of acoustic signals considering the anisotropic degradation of rock mass, e.g. Figure 3 As shown, the following steps are included:

[0081] Step S1: Deploy and bond full-band broadband sensors to the rock sample. Four full-band broadband sensors are used to collect low, medium, and high-frequency microseismic and acoustic emission signals. Four rectangular measurement areas are established for the sensors. The full-band broadband sensors collect source waveform data and calculate the arrival time difference between other full-band broadband sensors and a reference node.

[0082] In step S1, full-band broadband sensors are arranged on the edge of a rectangular measurement area of ​​the rock mass, and adhesive is applied during the arrangement to establish a measurement area in the shape of a rectangular parallelepiped. The full-band broadband sensors are used to collect acoustic emission source waveforms, and the time it takes for the source wave to travel from the source to the observation point is obtained. One of the full-band broadband sensors is selected as a reference node, and the arrival time difference between the other three full-band broadband sensors and the selected full-band broadband sensor is obtained by performing a difference calculation.

[0083] The rock sample selected in this example is massive, homogeneous, medium-coarse-grained granite, which is further finely cut and polished into samples with a size of 100mm×100mm×100mm. Low, medium and high frequency sound signal SS / MS / AE broadband sensors are placed on the rock sample and glued together to establish its rectangular measurement area, such as Figure 1 As shown, sensor T1 is used as the reference node sensor, and a non-metallic ultrasonic detector is used to perform P-wave velocity measurement on the reference node sensor and the other three sensors. Each group of velocity is measured three times, and the average value is taken. The results are shown in Table 1 below.

[0084] Table 1 Wave velocity measured by the sensor in this example:

[0085]

[0086] Step S2: Conduct true triaxial experiments at different stress levels, obtain stress-strain curves, and then establish a damage degradation equation. Then, simultaneously measure the wave velocity during the rock fracture process and establish a function of damage and wave velocity.

[0087] The details are as follows: when the rock is in its initial state, the wave velocity measurement function of the full-band broadband sensor is used. One of the full-band broadband sensors is selected as the reference node and the velocity is measured between the other three full-band broadband sensors in pairs to obtain the wave velocity in the three directions of the initial rock. Then, a true triaxial experiment of rock degradation under different stress conditions is carried out. During the experiment, measurements are made between the sensor and the reference node sensor to obtain the wave velocity and total stress-strain curve in the three directions during the rock failure process. The principal stress σ of the rock during the true triaxial experiment of rock degradation is i Anisotropic deformation modulus K in the direction i , the calculation formula is defined as:

[0088] ;

[0089] Among them, K i The axial stress increment dσ and the three elastic principal strain increments dε in each cyclic loading and unloading of the rock specimen are ie The absolute value of the ratio is determined according to the calculated K i Define the Young's modulus E in the three main directions i , i=1,2,3, assuming that the initial values ​​of Young's modulus E1, E2 and E3 in the three directions are the same, then E i The definition is as follows:

[0090] ;

[0091] Where μ1 and μ2 are the lateral Young's modulus proportional factors, defined as:

[0092] ;

[0093] where K 1,0 is the rock principal stress σ i Initial deformation modulus in the direction, K 2,0 and K 3,0 is the initial deformation modulus in the lateral direction;

[0094] According to the evolution law of mechanical parameters and nonlinear fitting method, E1, E2 and E3 are fitted with equivalent plastic strain ε p The evolution equation of the changing parameters:

[0095] ;

[0096] ;

[0097] ;

[0098] Among them, a i 、b i and c iare the fitting coefficients related to the second principal stress σ2 and the third principal stress σ3, i = 1, 2, 3, E i,0 is the initial elastic modulus, ε 1p , ε 2p and ε 3p are the maximum plastic principal strain, the intermediate plastic principal strain and the minimum plastic principal strain, respectively. 1i 、a 2i 、a 3i 、a 4i 、a 5i is the weight coefficient describing the evolution of the plastic strain component to the elastic modulus E, b 1i 、b 2i 、b 3i 、b 4i 、b 5i To control the nonlinear influence coefficient of plastic strain on modulus decay or hardening, c 1i 、c 2i 、c 3i 、c 4i 、c 5i is the quadratic term or high-order correction coefficient of the plastic strain to modulus evolution, and the results are as follows: Figure 6 and Figure 7 As shown; wave velocity and Young's modulus E in three directions i The relationship is as follows:

[0099] ;

[0100] Among them, is Young's modulus, is the density, is the wave velocity, i =1,2,3, is the Kronecker function, P ij is a substitution matrix. Generally, the attenuation of wave velocity in rock mass may be affected by the microstructural changes of the medium, such as the development and expansion of cracks. The wave velocity attenuates as the rock deteriorates. Its evolution equation is as follows:

[0101] ;

[0102] Where t is the propagation time, is the initial wave velocity, which depends on the angle θ, and α is the attenuation coefficient, which depends on the rock material;

[0103] In this example, based on true triaxial compression tests on granite under different stresses, and by measuring the change in wave velocity during the granite failure process, the wave velocity and total stress-strain curves in three directions during the rock failure process were obtained. Table 2 below shows the experimental results:

[0104] Table 2 Wave velocity and total stress-strain data in three directions in this example:

[0105]

[0106] Based on the above experimental results and combined with the theory, the evolution equation of the wave velocity in this example, which decays with rock degradation, is as follows:

[0107] ;

[0108] Step S3: Based on the arrival time difference and considering the wave velocity attenuation law with rock degradation, establish the source location objective function, calculate the source position by the sensor arrival time, and the specific calculation model is referenced Figure 2 As shown, the L1 norm is used to optimize the residual formula;

[0109] Specifically: Assume that there is a seismic source on a two-dimensional plane, and the source coordinates are P=[xy] T , the full-band broadband sensor is located at S j = [x j y j ], j = 1,2,3...n, n is the number of sensors; therefore, the time t for the P wave to be emitted from the earthquake source and received by the jth sensor is j For:

[0110] ;

[0111] Where v represents the propagation speed of P wave in the positioning model, d z represents the distance between the zth sensor and the earthquake source, (x0, y0) is the coordinate of the earthquake source;

[0112] If the full-band broadband sensor T1 is used as the reference node, the arrival time difference between the zth sensor and T1 is expressed as:

[0113] ;

[0114] When the measurement area is a three-dimensional space, the time when the i-th sensor receives the source signal relative to the reference node is expressed as:

[0115] ;

[0116] Where (x0, y0, z0) is the coordinate of the earthquake source in three-dimensional space, (x1, y1, z1) is the coordinate of the reference full-band broadband sensor in three-dimensional space, (x i ,y i , z i ) are the coordinates of other full-band broadband sensors in three-dimensional space.

[0117] Order , ;

[0118] The residual formula f based on the time difference positioning model is obtained:

[0119] ;

[0120] where R i and R1 represent the source P to the full-band broadband sensor S i Distance from full-band broadband sensor S1, i=1,2,3...n, V i is the function of damage and wave velocity, k is the norm; according to the function of damage and wave velocity established previously; the v in its function is changed to the newly established function of damage and wave velocity V i , the obtained formula is as follows:

[0121] ;

[0122] When there is data with an error greater than the set threshold, the L2 norm solves the objective function in a square manner, that is, k=2, which will increase the discreteness of the results with large deviations. The L1 norm uses the sum of the absolute residual values ​​of each station as the objective function, and does not emphasize the role of any station in the positioning solution. Therefore, it effectively reduces the impact of a single outlier on the source calculation results. Therefore, it is more suitable for source location calculation. The minimum absolute value method, that is, the L1 norm, will be used to optimize the objective function. That is, the sum of the absolute values ​​of the residuals of the time difference between each full-band broadband sensor and the reference full-band broadband sensor is used as the objective function f, that is, k is 1, as shown in the formula:

[0123] ;

[0124] The optimization algorithm is used to iteratively solve the minimum value of the objective function value f and obtain the source location (x0, y0, z0). When the objective function value f reaches the minimum value, the solution (x0, y0, z0) is the optimal location of the source, and only four sensors are needed to achieve positioning.

[0125] Based on the above experimental results, this example divides the collected data into three categories according to the normal, lateral and shear directions, and corresponds the stress and strain. According to the above, a wave velocity attenuation model considering the initial wave velocity anisotropy and the evolution of the anisotropic rupture process is constructed, and combined with the relationship: By iteratively solving the minimum value of the function f through the optimization algorithm, the earthquake source location (x0, y0, z0) can be obtained. When the objective function value f takes the minimum value, the solution (x0, y0, z0) is the optimal location of the earthquake source, as shown in Table 3 below.

[0126] Table 3 Initial earthquake source coordinates:

[0127]

[0128] Step S4: Select four points around the full-band broadband sensor within a set threshold range from the center, establish an initial tetrahedron, calculate the residual, compare the residuals of the four vertices, eliminate the point with the largest residual, and optimize the tetrahedron through iterative stretching and shrinking operations until the residual value reaches the threshold;

[0129] In step S4, four points are randomly selected near the center of the sensor array to establish an initial tetrahedron in three-dimensional space. Based on the coordinates of each vertex of the initial tetrahedron, the initial wave velocity anisotropy and the wave velocity decay to time difference during the evolution of the anisotropic rupture process are considered. The residuals of the four vertices are calculated using the L1 norm optimization residual formula. The residual values ​​are calculated and compared to find the minimum point f of the residual function of the vertex of the initial tetrahedron. min and the maximum point f max , and calculate the length of each side of the initial tetrahedron, d, and then eliminate the point f with the largest residual difference max , and continuously stretch and shrink the tetrahedron, replace and add new vertices to construct a new simplex tetrahedron, and judge whether the minimum residual value f reaches the predetermined threshold of the function iteration. If not, continue to search and construct a new simplex tetrahedron. If the residual value of the positioning target function is less than the predetermined threshold, the coordinate value of the simplex vertex is the positioning coordinate point;

[0130] Step S5: When the residual value reaches the termination threshold, within the spatial range where the optimal value error is less than 1, use the random number generation command to randomly select hundreds of minimum spacing points and compare the optimal value residual value f k The residual value f with the random point i , if f k <f i , then it is the global optimal point; if there exists f i >f, then the point is the local optimal point, the calculation is exited, the initial point is reselected and the process jumps to step S4 for search calculation;

[0131] Step S6, obtaining the optimal location of the earthquake source by inversely calculating the earthquake source coordinate parameters corresponding to the minimum residual value;

[0132] In this embodiment, the optimal location of the earthquake source is obtained by back-calculating the minimum residual value corresponding to the earthquake source coordinate parameters, and a new location event coordinate point is obtained, as shown in Table 4 below;

[0133] Table 4 Updated earthquake source coordinates:

[0134]

[0135] Step S7: Based on the SS / MS / AE signal information received by each probe for the positioning event, determine the microscopic failure type and positioning energy;

[0136] Specifically as follows:

[0137] Record and store the SS / MS / AE wave signal information received by each full-band broadband sensor for the positioning event at the failure location in the computer system. Conduct inversion analysis for the positioning event at the rock fracture location, classify the fracture types into tensile fracture, shear fracture, and mixed tensile-shear fracture, and determine the failure types of the rock at different time periods. The specific determination is as follows;

[0138] RA = Duration / Amplitude;

[0139] AF = Ring count AE / Duration;

[0140] For the classification of RA and AF, the optimal boundary method is adopted. Define the slope of the dividing line AF / RA as N. Define the signal with AF / RA < N as the tensile fracture signal, and the signal with AF / RA > N as the tensile fracture signal. By conducting pure tensile experiments and pure shear experiments on the rock, determine the slope of the dividing line as N. The obtained results are as Figure 10 shown;

[0141] The computer system determines the level of the positioning event energy. Since each positioning event is a set of SS, MS, and AE signals generated by the same fracture source received by multiple full-band broadband sensors, the positioning event energy is the area integral under the signal detection envelope from the start time of receiving the first signal to the end time of the last signal. The specific calculation is as follows:

[0142] [[ID=​​​​​​​​​​​​​​​​​​​​​​​​​​​On the other hand, a high-precision spatial positioning device for acoustic signals considering anisotropic degradation of rock mass is proposed. Figure 4 The present invention proposes a cloud server device 10, which includes one or more processors 10-1, one or more storage devices 10-2, an input device 10-3 and an output device 10-4, and these components are interconnected via a bus system 10-5 and / or other forms of connection mechanisms. It should be noted that Figure 4 The components and structures of the cloud server device 10 shown are merely exemplary and non-restrictive. The cloud server device may also have other components and structures as needed.

[0146] The processor 10 - 1 may be a central processing unit or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the cloud server device 10 to perform desired functions.

[0147] Furthermore, the processor 10-1 can perform steps S2-S6 of the method of the present invention, including preprocessing and reprocessing of the original data of total stress and strain, wave velocity and acoustic signal, constructing a wave velocity attenuation model that takes into account the initial wave velocity anisotropy and the evolution of the anisotropic rupture process, establishing the source positioning objective function, and determining the micro-damage type and positioning energy.

[0148] The storage device 10-2 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory and / or cache memory. The non-volatile memory may include, for example, read-only memory, a hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 10-1 may execute the program instructions to implement the computer functions in the embodiments of the present invention described below and / or other desired functions. The computer-readable storage medium may also store various applications and various data, such as various data used and / or generated by the application.

[0149] The input device 10 - 3 may be a device for receiving instructions input by a user and collecting data, and its input method adopts a combination of wireless and wired transmission.

[0150] The output device 10-4 can output various information such as text data, images or sounds to the outside, and can include one or more of a display, a speaker, etc. The output of the present invention is image or text data.

[0151] Figure 5This is a schematic diagram of a high-precision spatial positioning device 20 for acoustic signals that considers anisotropic degradation of rock masses, provided in an example of the present invention. This device is used to acquire rock sample positioning events and analyze rock failure types and energy. This device is used to execute the method provided in the above example of the present invention. The device 20 includes:

[0152] The input module 20-1 is used to receive the collected raw data of the indoor rock experiment and obtain the initial raw sample set of the model. Figure 4 The cloud server device 10 shown in FIG. 1 includes an input device 10 - 3 for data collection, a processor 10 - 1 for data classification, and a storage device 10 - 2 for storing program instructions for execution, and can execute the corresponding parts of steps S1 to S3 of the high-precision spatial positioning method for acoustic signals considering anisotropic degradation of rock masses proposed in an embodiment of the present invention;

[0153] The classification and storage module 20-2 is used to classify, filter, extract, integrate and store the initial raw data to obtain the damage degradation data and the collection of SS / MS / AE acoustic signal information generated by the rupture source. Figure 4 The processor 10-1 in the cloud server device 10 shown runs the program instructions stored in the storage device 10-2 to implement and execute the corresponding parts of steps S2-S4 of the high-precision spatial positioning method of acoustic signals considering anisotropic degradation of rock mass of the present invention;

[0154] The processing module 20-3 is used to construct a velocity attenuation model that takes into account the initial velocity anisotropy and the evolution of the anisotropic rupture process based on the damage degradation and velocity data in three directions, and to establish a source location target function based on the arrival time difference and taking into account the law of velocity attenuation with rock degradation. The SS / MS / AE acoustic signal information is trained, calculated, analyzed and tested. Based on the results of the analysis and processing, the positioning event is obtained, and the acoustic signal information is verified and classified and stored as a single positioning event. The processing module 20-3 can be composed of Figure 4 The processor 10-1 in the cloud server device 10 shown here runs the program instructions stored in the storage device 10-2 to implement and execute the corresponding parts of steps S2-S6 of the high-precision spatial positioning method of acoustic signals considering anisotropic degradation of rock mass proposed in an embodiment of the present invention;

[0155] The reprocessing module 20-4 is used to calculate, analyze, optimize, extract and integrate the acoustic signal information contained in each positioning event, determine its microscopic damage type and positioning energy, and verify and store it again. Figure 4 The processor 10 - 1 in the cloud server device 10 shown runs the program instructions stored in the storage device 10 - 2 to implement and execute step S6 of the high-precision spatial positioning method for acoustic signals considering anisotropic degradation of rock masses proposed in an embodiment of the present invention.

[0156] The output module 20-5 is used to output the rock fracture location event, microscopic damage type and location energy calculation results and verification results in the form of charts for users to view. Figure 4 The output device 10 - 4 in the cloud server device 10 shown is implemented by running program instructions stored in the storage device 10 - 2 .

[0157] The above description is merely an illustration of the preferred embodiments of the present disclosure and the technical principles employed. Those skilled in the art should understand that the scope of the invention encompassed by the embodiments of the present disclosure is not limited to technical solutions formed by specific combinations of the aforementioned technical features. It also encompasses other technical solutions formed by any combination of the aforementioned technical features or their equivalents, without departing from the aforementioned inventive concept. For example, a technical solution formed by replacing the aforementioned features with (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A high-precision spatial positioning method for acoustic signals considering anisotropic degradation of rock mass, characterized by: The following steps are involved: Step S1: Deploy and bond full-band broadband sensors to the rock sample. Four full-band broadband sensors are used to collect low, medium, and high-frequency microseismic and acoustic emission signals. Four rectangular measurement areas are established for the sensors. The full-band broadband sensors collect source waveform data and calculate the arrival time difference between other full-band broadband sensors and a reference node. Step S2: Conduct true triaxial experiments at different stress levels, obtain stress-strain curves, and then establish a damage degradation equation. Then, simultaneously measure the wave velocity during the rock fracture process and establish a function of damage and wave velocity. Step S3: Based on the arrival time difference and taking into account the wave velocity attenuation law with rock degradation, the earthquake source location objective function is established, the earthquake source position is calculated by the sensor arrival time, and the residual formula is optimized using the L1 norm; Step S4: Select four points around the full-band broadband sensor within a set threshold range from the center, establish an initial tetrahedron, calculate the residual, compare the residuals of the four vertices, eliminate the point with the largest residual, and optimize the tetrahedron through iterative stretching and shrinking operations until the residual value reaches the threshold; Step S5: When the residual value reaches the termination threshold, within the spatial range where the optimal value error is less than 1, use the random number generation command to randomly select hundreds of minimum spacing points and compare the optimal value residual value f k The residual value f with the random point i , if f k < f i , then it is the global optimal point; if there exists f i >f, then the point is the local optimal point, the calculation is exited, the initial point is reselected and the process jumps to step S4 for search calculation; Step S6, obtaining the optimal location of the earthquake source by inversely calculating the earthquake source coordinate parameters corresponding to the minimum residual value; Step S7: Based on the positioning event, each probe receives SS / MS / AE signal information to determine the microscopic damage type and positioning energy.

2. The high-precision spatial positioning method for acoustic signals considering anisotropic degradation of rock mass according to claim 1 is characterized in that: In step S1, full-band broadband sensors are arranged on the edge of a rectangular measurement area of ​​the rock mass, and adhesive is applied during the arrangement to establish a measurement area in the shape of a rectangular parallelepiped. The acoustic emission source waveform is collected by the full-band broadband sensors, and the time it takes for the source wave to travel from the source to the observation point is obtained. One of the full-band broadband sensors is selected as a reference node, and the arrival time difference between the other three full-band broadband sensors and the selected full-band broadband sensor is obtained by performing a difference calculation.

3. The high-precision spatial positioning method for acoustic signals considering anisotropic degradation of rock mass according to claim 1 is characterized in that: The step S2 is specifically as follows: when the rock is in the initial state, the wave velocity measurement function of the full-band broadband sensor is used, one of the full-band broadband sensors is selected as the reference node, and velocity measurements are performed between each of the other three full-band broadband sensors to obtain the wave velocity in three directions of the initial rock, and then a true triaxial experiment of rock degradation under different stress conditions is performed. During the experiment, measurements are performed between the sensor and the reference node sensor to obtain the wave velocity and total stress-strain curve in three directions during the rock failure process. The principal stress σ of the rock during the true triaxial experiment of rock degradation is i Anisotropic deformation modulus K in the direction i , the calculation formula is defined as: Among them, K i The axial stress increment dσ and the three elastic principal strain increments dε in each cyclic loading and unloading of the rock specimen are ie The absolute value of the ratio is determined according to the calculated K i Define the Young's modulus E in the three main directions i , i=1,2,3, assuming that the initial values ​​of Young's modulus E1, E2 and E3 in the three directions are the same, then E i The definition is as follows: ; where μ1 and μ2 are the lateral Young's modulus proportional factors, defined as: ; where K 1,0 is the rock principal stress σ i Initial deformation modulus in the direction, K 2,0 and K 3,0 is the initial deformation modulus in the lateral direction; According to the evolution law of mechanical parameters and nonlinear fitting method, E1, E2 and E3 are fitted with equivalent plastic strain ε p The evolution equation of the changing parameters: ； ； ； Among them, a i 、b i and c i are the fitting coefficients related to the second principal stress σ2 and the third principal stress σ3, i=1,2,3, E i,0 is the initial elastic modulus, ε 1p , ε 2p and ε 3p are the maximum plastic principal strain, the intermediate plastic principal strain and the minimum plastic principal strain, respectively. 1i 、a 2i 、a 3i 、a 4i 、a 5i is the weight coefficient describing the evolution of the plastic strain component to the elastic modulus E, b 1i 、b 2i 、b 3i 、b 4i 、b 5i To control the nonlinear influence coefficient of plastic strain on modulus decay or hardening, c 1i 、c 2i 、c 3i 、c 4i 、c 5i is the quadratic term or high-order correction coefficient of plastic strain on modulus evolution; wave velocity and Young's modulus E in three directions i The relationship is as follows: ； in, is Young's modulus, is the density, is the wave velocity, i=1,2,3, is the Kronecker function, P ij is a permutation matrix. The wave velocity decays as the rock deteriorates and its evolution equation is as follows: ； Where t is the propagation time, is the initial wave velocity and α is the attenuation coefficient.

4. The high-precision spatial positioning method for acoustic signals considering anisotropic degradation of rock mass according to claim 1, characterized in that: Step S3 is as follows: Assume that there is a seismic source on a two-dimensional plane, and the seismic source coordinates are P = [xy] T , the full-band broadband sensor is located at S j = [x j y j ], j = 1,2,3...n, n is the number of sensors; Therefore, the P wave is emitted from the source point and received by the jth sensor at time t j for: ； Where v represents the propagation speed of P wave in the positioning model, d z represents the distance between the zth sensor and the earthquake source, (x0, y0) is the coordinate of the earthquake source; If the full-band broadband sensor T1 is used as the reference node, the arrival time difference between the zth sensor and T1 is expressed as: ； When the measurement area is a three-dimensional space, the time when the i-th sensor receives the source signal relative to the reference node is expressed as: ； Where (x0, y0, z0) is the coordinate of the earthquake source in three-dimensional space, (x1, y1, z1) is the coordinate of the reference full-band broadband sensor in three-dimensional space, (x i ,y i , z i ) are the coordinates of other full-band broadband sensors in three-dimensional space; make , ; The residual formula f based on the time difference positioning model is obtained: ； where R i and R1 represent the source P to the full-band broadband sensor S i Distance from full-band broadband sensor S1, i=1,2,3...n, V i is the function of damage and wave velocity, k is the norm; according to the function of damage and wave velocity established previously; the v in its function is changed to the newly established function of damage and wave velocity V i , the obtained formula is as follows: ； When there is data with an error greater than the set threshold, the minimum absolute value method, that is, the L1 norm, is used to optimize the objective function. That is, the sum of the residual absolute values ​​of the time difference between each full-band wideband sensor and the reference full-band wideband sensor is used as the objective function f, that is, k is 1, as shown in the formula: ； The minimum value of the objective function value f is solved iteratively through the optimization algorithm to obtain the source position (x0, y0, z0). When the objective function value f takes the minimum value, the solved (x0, y0, z0) is the optimal location of the source.

5. The high-precision spatial positioning method for acoustic signals considering anisotropic degradation of rock mass according to claim 1 is characterized in that: In step S4, four points are randomly selected near the center of the sensor array to establish an initial tetrahedron in three-dimensional space. Based on the coordinates of each vertex of the initial tetrahedron, the initial wave velocity anisotropy and the wave velocity decay to time difference during the evolution of the anisotropic rupture process are considered. The residuals of the four vertices are calculated using the L1 norm optimization residual formula. The residual values ​​are calculated and compared to find the minimum point f of the residual function of the vertex of the initial tetrahedron. min and the maximum point f max , and calculate the length of each side of the initial tetrahedron, d, and then eliminate the point f with the largest residual difference max , and continuously stretch and shrink the tetrahedron, replace and add new vertices to construct a new simplex tetrahedron, and judge whether the minimum residual value f reaches the predetermined threshold of function iteration. If not, continue to search and construct a new simplex tetrahedron. If the residual value of the positioning target function is less than the predetermined threshold, the coordinate value of the tetrahedron vertex is the positioning coordinate point.

6. The high-precision spatial positioning method for acoustic signals considering anisotropic degradation of rock mass according to claim 1, characterized in that: In step S7, the SS / MS / AE wave signal information received by each full-band broadband sensor at the location event of the failure is recorded and stored in the computer system. The location event at the rock fracture location is subjected to inversion analysis, and the fracture type is classified into tension fracture, shear fracture, and mixed tension-shear fracture. The failure type of the rock in different time periods is determined as follows: RA=duration / amplitude; AF=ring count AE / duration; For the classification of RA and AF, the best dividing line method is adopted. The slope of the dividing line AF / RA is defined as N. Signals with AF / RA < N are defined as tensile fracture signals, and signals with AF / RA > N are defined as shear fracture signals. By conducting pure tensile experiments and pure shear experiments on rocks, the slope of the dividing line N is determined. The computer system determines the level of the positioning event energy. It is the set of SS, MS, and AE signals generated by the same fracture source received by the full-frequency broadband sensor. The positioning event energy is the area integral under the signal detection envelope during the period from the start time of receiving the first signal to the end time of the last signal. The specific calculation is as follows: ； G5 = n1G1 + n2G2 + n3G3 + n4G4; Where E is the energy of the positioning event, is the end time of the last signal, is the start time of the first signal, 、 、 、 is the weighting coefficient, G1, G2, G3, G4, and G5 are the signals received by the full-band broadband sensor, and A ring To collect the amplitude of the sound signal, f collects the frequency of the sound signal; the computer system determines the energy level of the positioning event based on the above calculation. The higher the energy level, the larger the scatter point size and the darker the color.

7. A high-precision spatial positioning device for acoustic signals taking into account anisotropic degradation of rock mass, used to implement the high-precision spatial positioning method for acoustic signals taking into account anisotropic degradation of rock mass as claimed in claim 1, characterized in that: Specifically, it includes: Input module: Used to collect the original data of stress-strain data under true triaxial experiments at different stress levels and the SS, MS, and AE acoustic signal information of each positioning event at the rock failure location received by the full-frequency broadband sensor. Classification and storage module: Classify, screen, extract, integrate, and store the original data to obtain the set of damage deterioration data and the SS, MS, and AE acoustic signal information generated by the fracture source. Processing module: Based on the damage deterioration data and wave velocity data in three directions, construct a function of damage and wave velocity considering the initial wave velocity anisotropy and the evolution of anisotropic fracture process, and establish a source location objective function based on the time difference of arrival considering the attenuation law of wave velocity with rock deterioration. Train, calculate, and analyze and test the SS / MS / AE acoustic signal information. According to the analysis results, obtain the positioning event, and check and verify. Classify and store the acoustic signal information with a single positioning event. Re-processing module: Calculate, analyze, optimize, extract, and integrate the acoustic signal information included in each positioning event, determine its microscopic failure type and positioning energy, and check and verify and store again. Output module: Output the rock fracture positioning event, microscopic failure type, and the calculation results and verification results of the positioning energy in the form of charts for users to view.

Images