CN-120722284-B - High-precision space positioning method and device considering rock mass anisotropic degradation acoustic signals

Abstract

The invention provides a high-precision space positioning method and device considering rock mass anisotropic degradation acoustic signals, and relates to the technical field of geotechnical engineering. Aiming at the problems of the heterogeneity of a rock mass structure and the anisotropism in the propagation of acoustic signals in the prior art, a new wave velocity attenuation model considering the initial wave velocity anisotropism and the evolution of the anisotropism rupture process is provided so as to realize more accurate acoustic emission space positioning. According to the method, an acoustic emission sensor is arranged on a rock sample, seismic source waveform data are acquired, a full stress strain curve is acquired through a true triaxial experiment, and a function model of damage and wave velocity is established. And constructing a seismic source positioning objective function through an optimization algorithm, iterating, and finally determining the seismic source position. The method can also analyze the energy and the damage mechanism of the acoustic emission signal, and realize the high-precision quantitative characterization of the damage position, the microcosmic mechanism and the released energy in the process of the anisotropic rock mass fracture.

Inventors

• ZHENG ZHI
• JIANG DAFENG
• LI KUN
• WANG PENGFEI
• YANG BINLI
• ZHANG XIN
• WANG FENGYUN
• PAN RUI
• ZHANG ZHENHUA
• YAO HUAYAN
• HU XIAOCHUAN
• WU PING

Assignees

• 广西大学
• 广西壮族自治区建筑工程质量检测中心有限公司

Dates

Publication Date

20260505

Application Date

20250825

Claims (5)

1. 1. A high-precision spatial positioning method considering rock mass anisotropic degradation acoustic signals is characterized by comprising the following steps: Step S1, arranging and bonding all-frequency-band broadband sensors on a rock sample, wherein four all-frequency-band broadband sensors are used for collecting low-medium-high frequency microseismic and acoustic emission signals, establishing four sensor rectangular areas, acquiring seismic source waveform data by the all-frequency-band broadband sensors and calculating arrival time differences between other all-frequency-band broadband sensors and reference nodes; S2, carrying out true triaxial experiments with different stress levels, simultaneously obtaining stress-strain curves, then establishing a damage degradation equation, simultaneously measuring the wave speed of the rock cracking process, and establishing a function of damage and the wave speed; The step S2 is specifically as follows, when the rock is in an initial state, a function of measuring wave velocity in a full-frequency band broadband sensor is adopted, one full-frequency band broadband sensor is selected as a reference node, two-by-two speed measurement is carried out between the other three full-frequency band broadband sensors, the wave velocity of the wave velocity in three directions of the initial rock is obtained, then a rock degradation true triaxial experiment under different stress conditions is carried out, the measurement is carried out between the sensor and the reference node sensor in the experimental process, the wave velocity and the full-stress strain curve in the three directions in the rock breaking process are obtained, the anisotropic deformation modulus K i in the rock principal stress sigma i direction in the rock degradation true triaxial experimental process is defined by the calculation formula: Wherein K i is determined by the absolute value of the ratio of the axial stress increment dσ to the three elastic principal strain increments dε ie in each cycle of loading and unloading of the rock sample, and the calculated young's modulus in three principal directions, E i , i=1, 2,3, is defined based on K i , and assuming that the initial values of young's moduli in the three directions, E 1 、E 2 and E 3 , are the same, E i is defined as follows: wherein μ 1 、μ 2 is the lateral Young's modulus scaling factor, defined as: Wherein K 1,0 is the initial deformation modulus in the direction of rock principal stress sigma i , and K 2,0 and K 3,0 are the initial deformation moduli in the lateral direction; Fitting a parameter evolution equation of E 1 、E 2 and E 3 and equivalent plastic strain epsilon p change according to an evolution rule of mechanical parameters and a nonlinear fitting method: ; ; ; Wherein, a i 、b i and c i are fitting coefficients of the second main stress sigma 2 and the third main stress sigma 3 , i=1, 2,3, E i,0 are initial elastic modulus, epsilon 1p 、ε 2p and epsilon 3p are maximum plastic main strain, middle plastic main strain and minimum plastic main strain respectively, a 1i 、a 2i 、a 3i 、a 4i 、a 5i is a weight coefficient for describing evolution of plastic strain component to elastic modulus E, b 1i 、b 2i 、b 3i 、b 4i 、b 5i is a nonlinear influence coefficient for controlling attenuation or hardening of plastic strain to modulus, c 1i 、c 2i 、c 3i 、c 4i 、c 5i is a quadratic term or high-order correction coefficient of plastic strain to modulus evolution, and wave velocity is related to Young modulus E i in three directions as follows: ; Wherein, the Is the young's modulus, is the modulus, Is the density of the particles, which is the density, Is the wave velocity, i=1, 2,3, Is a kronecker function, P ij is a displacement matrix, and the wave velocity decays as the rock deteriorates with its evolution equation as follows: ; where t is the propagation time, and where, Is the initial wave velocity, α is the attenuation coefficient; s3, establishing a focus positioning objective function based on the arrival time difference and considering the attenuation law of the wave velocity along with the rock degradation, calculating the position of the focus through the arrival time of the sensor, and optimizing a residual error formula by using an L1 norm; The step S3 specifically includes that a seismic source exists on a two-dimensional plane, the coordinate of the seismic source is p= [ x y ] T , the full-band broadband sensor is located in S j = [x j y j , j=1, 2, 3..n, n is the number of sensors, and therefore the P wave is emitted from the seismic source point and received by the j-th sensor for a time t j : ; Wherein v represents the propagation speed of the P wave in the positioning model, d z represents the distance between the z-th sensor and the seismic source, and (x 0 ,y 0 ) is the coordinate of the seismic source; If the full-band wideband sensor T 1 is used as the reference node, the arrival time difference between the z-th sensor and T 1 is expressed as: ; when the zone is three-dimensional, then the time at which the ith sensor receives the source signal relative to the reference node is expressed as: ; Wherein (x 0 ,y 0 ,z 0 ) is the coordinate of the seismic source in the three-dimensional space, (x 1 ,y 1 ,z 1 ) is the coordinate of the reference full-frequency-band broadband sensor in the three-dimensional space, and (x i ,y i ,z i ) is the coordinate of other full-frequency-band broadband sensors in the three-dimensional space; Order the , ; Obtaining a residual error formula f based on the time difference positioning model: ; Wherein R i and R 1 represent distances from the source P to the full-band broadband sensor S i and the full-band broadband sensor S 1 , respectively, i=1, 2, 3..n, V i is a function of the damage and the wave velocity, k is a norm, according to the function of the damage and the wave velocity established previously, V in the function is changed to a function V i of the new damage and the wave velocity, and the obtained formula is as follows: ; When there is data with error greater than the set threshold, the minimum absolute value method, that is, L1 norm is used to optimize the objective function, that is, the sum of the absolute values of the residuals of the full-band broadband sensor and the reference full-band broadband sensor to the time difference is taken as the objective function f, that is, k takes 1, as shown in the formula: ; Iteratively solving the minimum value of the objective function value f through an optimization algorithm to obtain a seismic source position (x 0 , y 0 , z 0 ), and solving the obtained (x 0 , y 0 , z 0 ) to be the optimal position of the seismic source when the objective function value f takes the minimum value; s4, selecting four points within a set threshold range of the distance between the periphery of the full-band broadband sensor and the center, establishing an initial tetrahedron, calculating residual errors, comparing the residual errors of the four vertexes, eliminating the maximum residual error point, and optimizing the tetrahedron through iterative stretching and shrinking operation until the residual error value reaches the threshold; S5, after the residual value reaches a termination threshold, adopting a random number production command to randomly select hundreds of minimum interval points in a space range with an error of an optimal value less than 1, and comparing the residual value f k of the optimal value with the residual value f i of the random points, wherein if f k < f i is the global optimal point, if f i > f is present, the point is the local optimal point, skipping out calculation, reselecting the initial point and skipping to the step S4 to perform search calculation; s6, calculating the optimal position of the seismic source through reversely calculating the coordinate parameters of the seismic source corresponding to the minimum residual value; and S7, based on the positioning event, each probe receives the SS/MS/AE signal information, and the microscopic damage type and the positioning energy are determined.
2. 2. The method for high-precision spatial positioning of acoustic signals considering anisotropic degradation of a rock mass according to claim 1, wherein in the step S1, full-band broadband sensors are arranged on edges of a cuboid area of the rock mass, an adhesive is applied during arrangement, an area with a cuboid shape is established, acoustic emission source waveforms are collected through the full-band broadband sensors, the time for passing a source wave from a source to an observation point is obtained, one full-band broadband sensor 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 through difference calculation.
3. 3. The method according to claim 1, wherein in the step S4, four points are arbitrarily selected near the center of the sensor array, an initial tetrahedron is built in three-dimensional space, based on the coordinates of each vertex of the initial tetrahedron, the four vertices are subjected to residual calculation by using an L1 norm optimized residual formula in consideration of the initial wave velocity anisotropy and the wave velocity attenuation to time difference evolving in the anisotropic fracture process, the residual value is calculated, the residual values of the four vertices are compared, the minimum point f min and the maximum point f max of the initial tetrahedron residual function are found, the straight d of each side of the initial tetrahedron is calculated, then the point f max with the maximum residual value difference is eliminated, the tetrahedron is continuously stretched and shrunk, a new tetrahedron is built by replacing and supplementing the new vertex, whether the minimum residual value f reaches a predetermined threshold value of the function iteration is judged, if the minimum residual value f does not reach, the new simplex is continuously searched and built, and if the value of the positioning objective function is smaller than the predetermined threshold value, the residual value of the tetrahedron is the positioning point.
4. 4. The method for high-precision spatial localization of acoustic signals considering anisotropic degradation of rock mass according to claim 1, wherein in step S7, the full-band broadband sensors of the localization events under the breaking position receive SS/MS/AE wave signal information records and store the same in a computer system, perform inversion analysis for the localization events under the breaking position of the rock, divide the breaking types into tension breaking, shear breaking and hybrid tension-shear breaking, and determine the breaking types of the rock in different time periods, specifically determine as follows: RA = duration/amplitude; AF = ring count AE/duration; For classification of RA and AF, an optimal dividing line method is adopted, the slope of the dividing line AF/RA is defined as N, the signal of AF/RA < N is defined as a tensioning fracture signal, the signal of AF/RA > N is defined as a shearing fracture signal, and a pure pull experiment and a pure shearing experiment are carried out on the rock to determine that the slope of the dividing line is N; The computer system determines the level of the positioning event energy, namely the area integral under the signal detection envelope curve from the beginning time of receiving the first signal to the ending time of the last signal, and the set of SS, MS and AE signals generated by the same cracking source and received by the full-band broadband sensor, wherein the specific calculation is as follows: ; G 5 =n 1 G 1 + n 2 G 2 +n 3 G 3 + n 4 G 4 ; where E is the energy of the localization event, For the end time of the last signal, For the start time of the first signal, 、 、 、 The computer system determines the energy level of the positioning event according to the calculation, wherein the higher the energy level is, the larger the scattered spot size is, and the darker the color is.
5. 5. A high-precision spatial positioning device for a sound signal considering anisotropic degradation of a rock mass, for implementing the high-precision spatial positioning method for a sound signal considering anisotropic degradation of a rock mass according to claim 1, comprising: The input module is used for collecting stress strain data under true triaxial experiments of different stress levels and receiving original data of SS, MS and AE acoustic signal information by all-frequency-band broadband sensors of positioning events under rock breaking positions; the classifying and storing module is used for classifying, screening, extracting, integrating and storing the original data to obtain damage degradation data and a set of SS, MS and AE sound signal information generated by a cracking source; The processing module is used for constructing a function of damage and wave velocity considering initial wave velocity anisotropy and evolution of an anisotropic fracture process according to damage degradation data and wave velocity data in three directions, establishing a focus positioning objective function based on arrival time difference and considering attenuation rule of the wave velocity along with rock degradation, training, calculating and analyzing and testing SS/MS/AE acoustic signal information, acquiring a positioning event according to analysis processing results, checking and rechecking, and classifying and storing the acoustic signal information by using a single positioning event; The reprocessing module is used for calculating, analyzing, optimizing, extracting and integrating the acoustic signal information contained in each positioning event, determining the microscopic damage type and positioning energy of the positioning event, checking and rechecking the positioning event and storing the positioning event again; And the output module is used for outputting the rock fracture positioning event, the microscopic fracture type, the positioning energy calculation result and the rechecking result in a chart form for a user to check.

Description

High-precision space positioning method and device considering rock mass anisotropic degradation acoustic signals Technical Field The invention relates to the technical field of geotechnical engineering, in particular to a high-precision space positioning method and device for acoustic signals considering anisotropic degradation of rock mass. Background Due to the heterogeneity of the natural rock mass structure, the initial anisotropic characteristic caused by the inherent structural anisotropy of the rock mass, and the wave velocity anisotropic evolution characteristic caused by an anisotropic damage mechanism when the rock mass breaks under the action of stress, the wave velocity of the sound wave in the rock mass propagation process also has the anisotropic characteristic. The anisotropy of wave velocity in the rock mass propagation process is not considered by using a single velocity model at present, so that the positioning is inaccurate. In the field of rock mass fracture multi-physical field monitoring, signals in different frequency bands have obvious characteristic differences, wherein an acoustic signal (SS) mainly shows low-frequency characteristics, a Microseismic Signal (MS) shows medium-low frequency characteristics, and an acoustic signal (AE) covers a high-frequency range. Traditional monitoring methods are limited by the physical characteristics of single-band acquisition equipment, and often only can acquire the fracture information of local bands, so that a complete fracture evolution characteristic spectrum is difficult to establish. The traditional moment tensor positioning method has obvious limitation in practical engineering application, and at least 6 acoustic emission probes are required to simultaneously receive effective signals so as to realize accurate positioning. However, due to the factors of complex field geological conditions, limited sensor layout and the like, the requirement of synchronous receiving of multiple probes is often difficult to meet, the positioning precision is obviously reduced, the problems of easy sinking into a local minimum, easy influence of individual sensors, low stability and no general applicability of an algorithm are solved, and therefore, the seismic source positioning algorithm and a model considering the anisotropic degradation speed of a rock mass are further researched. In summary, the existing acoustic signal monitoring has the defects that the existing speed model can reflect the real wave speed of the rock mass, but cannot reflect the wave speed attenuation law after the rock is degraded, the existing positioning algorithm needs more acoustic emission probes, the calculated amount is extremely large, the positioning is not stable, and the positioning efficiency is greatly reduced. Meanwhile, the signal energy responses received by the acoustic emission probes have obvious differences, however, a unified technical standard is not established for the standardized determination method of the energy responses, so that the reliability and comparability of the energy calculation result are difficult to ensure. Disclosure of Invention Aiming at the defects of the prior art, the invention provides a high-precision space positioning method and device for acoustic signals considering the anisotropic degradation of a rock mass, and particularly provides a method and device for accurately determining the crack of the rock mass by innovatively optimizing a signal processing algorithm and a positioning model and only needing a small amount of effective signals on the basis of the wave velocity evolution of the initial anisotropy of the rock mass and the anisotropy of the crack process, which remarkably improves the engineering applicability and positioning reliability of the method, establishes an energy response standardized determination method based on multi-probe signals, and realizes the synchronous and accurate identification of the crack mechanism and energy characteristics by constructing an energy correction model and a standardized processing flow. In one aspect, a method for high-precision spatial localization of acoustic signals in consideration of anisotropic degradation of a rock mass includes the steps of: Step S1, arranging and bonding all-frequency-band broadband sensors on a rock sample, wherein four all-frequency-band broadband sensors are used for collecting low-medium-high frequency microseismic and acoustic emission signals, establishing four sensor rectangular areas, acquiring seismic source waveform data by the all-frequency-band broadband sensors and calculating arrival time differences between other all-frequency-band broadband sensors and reference nodes; in the step S1, full-band broadband sensors are arranged on the sides of a cuboid area of a rock mass, an adhesive is coated during arrangement, an area with a cuboid shape is established, acoustic emission source waveforms are acquired through the full-band broadband sens