Acoustic emission source positioning method and system based on grid search and simulated annealing

Abstract

The invention discloses an acoustic emission source positioning method and system based on grid search and simulated annealing, electronic equipment and a storage medium, and the method comprises the following steps: collecting an acoustic emission signal containing arrival time information, and carrying out the filtering processing of the acoustic emission signal; picking up the first arrival time of an acoustic emission event according to the acoustic emission signal after filtering processing; constructing a seismic source position objective function based on the picked first arrival time; carrying out global search by utilizing a grid search method through the constructed seismic source position target function, and solving a preliminary seismic source position; and taking the solved initial seismic source position as an initial iteration value of simulated annealing, and solving an accurate seismic source position. According to the method, the global search characteristic of the grid search method and the characteristics of enabling the model to jump out of the local optimal solution and global convergence of the simulated annealing method are utilized, the robustness of the positioning algorithm is improved, compared with an existing acoustic emission source positioning method, the calculation speed and stability of the positioning algorithm can be considered at the same time, and rapid and efficient positioning of the acoustic emission source is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of acoustic emission source positioning methods, and specifically relates to an acoustic emission source positioning method, system, electronic equipment and storage medium based on grid search and simulated annealing, which are used to process acoustic emission signals containing arrival time information and perform source inversion positioning. Background Art

[0002] Acoustic emission refers to the phenomenon that when the rock is deformed or cracked under the action of external force, the strain energy is quickly released in the form of instantaneous elastic waves. As an acoustic method to study rock loss and damage, acoustic emission technology infers the stress state and degree of damage of the rock by monitoring the acoustic emission signals generated by the rock under external loads. It is widely used in indoor rock experimental research and provides an important theoretical basis for guiding the design and construction of projects. Acoustic emission source positioning is an important step and key function of acoustic emission technology, and its positioning accuracy directly affects the application effect of acoustic emission technology.

[0003] At present, acoustic emission source positioning is mainly based on the traditional time difference positioning method, that is, it is achieved by searching for the minimum residual between the theoretical arrival time and the actual arrival time of the acoustic emission event at each station. The traditional time difference positioning method regards the internal wave velocity of the rock as a constant value, and represents the propagation distance between the source and the sensor as a straight line path, which does not fully consider the influence of the anisotropy of the rock and the internal irregular structure. In order to further improve the positioning accuracy, it is necessary to establish a more complex wave velocity model and recalculate the propagation path of elastic waves under the influence of structures such as holes and faults, which will inevitably increase the computational complexity of the positioning algorithm. In addition, with the increase in the sampling rate of the acoustic emission monitoring system and the increase in the number of sensors, the quality and processing difficulty of acoustic emission data are gradually increasing, which brings new challenges to the traditional positioning algorithm. How to quickly process large-scale data will become an inevitable problem. Grid search method and simulated annealing method are currently commonly used acoustic emission source positioning methods. The simulated annealing method can avoid the problem of the algorithm falling into the local optimum to a certain extent, but the global optimization will greatly increase the amount of calculation and calculation time, which is not conducive to the processing of large-scale acoustic emission data. The grid search method needs to divide the search area according to a certain grid density. The finer the grid division, the higher the positioning accuracy, but it will lead to a large number of positioning calculations. Although the above methods have their own characteristics, it is difficult to balance the calculation efficiency and stability, and they are not suitable for acoustic emission source positioning with high calculation complexity or large-scale acoustic emission data.

[0004] Therefore, it is necessary to improve the positioning algorithm and propose an acoustic emission source positioning algorithm that meets the requirements of computational efficiency and stability. Summary of the invention

[0005] In view of the technical problem that the traditional acoustic emission positioning algorithm based on time difference cannot take into account both the calculation speed and stability,

[0006] The purpose of the present invention is to provide an acoustic emission source positioning method, system, electronic device and storage medium based on grid search and simulated annealing, which can take into account both calculation speed and stability in the acoustic emission positioning algorithm, identify acoustic emission events and pick up the initial arrival time by adopting the STA / LTA-AIC method, the picked arrival time will be used as the actual arrival time to enter the positioning objective function, and then use the grid search method to obtain a preliminary result that is relatively close to the global optimal point, and finally use the output result of the grid search method as the initial value of the simulated annealing method to perform local search, continuously iterate the calculation nodes to obtain the global optimal point, and realize fast and efficient positioning of the acoustic emission source.

[0007] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0008] The first aspect of the present invention discloses a method for locating an acoustic emission source based on grid search and simulated annealing, comprising the following steps: S1, collecting an acoustic emission signal containing arrival time information, and filtering the acoustic emission signal; S2, picking up the first arrival time of the acoustic emission event according to the acoustic emission signal after filtering; S3, constructing a source position target function based on the picked first arrival time; S4, performing a global search using a grid search method through the constructed source position target function to solve a preliminary source position; S5, using the solved preliminary source position as an initial iteration value of simulated annealing to solve an accurate source position.

[0009] Based on the above disclosed steps, the present invention improves the robustness of the positioning algorithm by utilizing the global search characteristics of the grid search method and the characteristics of the simulated annealing method that enable the model to jump out of the local optimal solution and global convergence. Compared with the existing acoustic emission source positioning method, the present invention takes into account both the calculation speed and stability of the positioning algorithm, and can meet the needs in the technical field of acoustic emission source positioning methods.

[0010] And by identifying the acoustic emission events and picking the first arrival time, the picked arrival time will be used as the actual arrival time to enter the positioning objective function, and then the grid search method is used to obtain a preliminary result that is relatively close to the global optimal point. Finally, the output result of the grid search method is used as the initial value of the simulated annealing method for local search, and the calculation nodes are continuously iterated to obtain the global optimal point, thereby realizing fast and efficient positioning of the acoustic emission source.

[0011] In the acoustic emission source localization method based on grid search and simulated annealing disclosed according to the first aspect of the present invention, in step S2, picking up the first arrival time of the acoustic emission event includes:

[0012] The long-short time window ratio method STA / LTA is used to identify acoustic emission events;

[0013] The AIC method is used to pick the first arrival time.

[0014] In a preferred embodiment, in step S2, the long-short time window ratio method STA / LTA is used to identify acoustic emission events, and the sudden change of the ratio of STA to LTA is used as the judgment condition, wherein the short-time window STA represents the amplitude or energy of the microseismic signal, and the long-time window LTA represents the amplitude or energy of the background noise. When the STA / LTA ratio exceeds the set threshold, it means that an acoustic emission event has occurred; the square of the amplitude is used as the characteristic function of the long-short time window ratio method STA / LTA, and the calculation formula is as follows:

[0015]

[0016] In the formula, X(i) (i = 1, 2, ..., N) represents the amplitude of the microseismic waveform, STA(i) and LTA(i) are the short-term average and long-term average of the amplitude at time i, respectively, Nsta and Nlta represent the short-term window width and long-term window width, respectively, and the weighting coefficient α is the standard deviation of the signal amplitude in the short-term window (σ S ) and the standard deviation of the signal amplitude in the long time window (σ L ) to increase the sensitivity to signal changes.

[0017] Further, in step S2, after the long-short time window ratio method STA / LTA identifies an acoustic emission event, preferably, the AIC method is used to find the minimum value of the AIC function of the local waveform segment within a suitable time window, and the time corresponding to the minimum value is the first arrival time; the calculation formula of the AIC function is as follows:

[0018] AIC(k)=klog{var(X[1,k])}+(Nk-1)log{var(x[k+1,N])}

[0019] Where N is the total number of sampling points, k represents the sliding variable, and var(x[1,k]) and var(x[k+1,N]) represent the variance of the samples in two time periods, respectively.

[0020] In the present invention, in step S3, a source location objective function based on the sensor arrival time difference is constructed, and the acoustic emission source location based on the arrival time difference is realized by searching for the minimum residual between the theoretical arrival time and the actual arrival time. Assuming that the acoustic emission event occurs at time t0, after Δt i The duration of i To the i-th (i=1,2,…,n) sensor position, the residual θ between the theoretical arrival time and the actual arrival time of the i-th acoustic emission sensor is i It can be expressed as:

[0021] θ i =t i -Δt i -t0

[0022] In order to simplify the calculation process, it is usually assumed that the propagation medium has a uniform velocity, so the elastic wave velocity is a constant value, which can be expressed as the equivalent wave velocity c p Simple expression. Assume that the coordinates of the acoustic emission source are (x0, y0, z0), and the position coordinates of the i-th sensor are (x i ,y i ,z i ), l i is the distance between the ith station and the earthquake source. According to the distance formula between two points, the calculation of the ith sensor can be simplified to:

[0023]

[0024] In the case of only a single sensor, t0 cannot be obtained. In order to eliminate the influence of the earthquake occurrence time t0 on the positioning result, the relationship between multiple sensors can be used. The residual θ between the i-th sensor and the j-th sensor ij for:

[0025] θ ij =θ i -θ j =t i -Δt i -t0-(t j -Δt j -t0)=t i -t j -(Δt i -Δt j )

[0026] Under ideal conditions, the residual error θ between different sensors is ij = 0, but in practice, due to the influence of errors such as the first arrival time picking and theoretical arrival time calculation, θ ij Generally it is not 0. But compared with other points, the θ of the acoustic emission source ij The absolute value of is the smallest, and the source location error is the smallest. Therefore, the realization of acoustic emission source location can be achieved by searching the acoustic emission monitoring area so that the following objective function reaches the minimum value. The objective function is:

[0027]

[0028] Where (x, y, z) is the coordinate of any node in the acoustic emission monitoring area, and the source point (x0, y0, z0) should make the objective function reach the minimum value. i The first arrival time picked by AIC method can be obtained, Δt iIt can be simply calculated using the equivalent wave velocity and the distance between two points. However, for structural rocks containing holes, faults, etc., it is necessary to consider the changes in the elastic wave propagation path in order to accurately obtain the theoretical travel time of the elastic wave.

[0029] In the acoustic emission source location method based on grid search and simulated annealing disclosed in the first aspect of the present invention, in step S4, a global search is performed using a grid search method to solve a preliminary source location, including:

[0030] 1) Model building: According to the size of the rock specimen, the area where the acoustic emission event may occur is used as the search area. The search area is a three-dimensional space, and the search area is divided into a series of grid points. The density of the grid points determines the positioning accuracy. When the search area is large and the grid division is fine, the calculation amount of the grid search is large. Therefore, the search area and grid point density of the grid search should not be too large. In three-dimensional space, the coordinates of any grid point can be expressed as:

[0031]

[0032] Where n x , n y , n z are the number of grids on the X, Y, and Z axes, Δx, Δy, and Δz are the grid sizes on the three axes, and x is min ,y min ,z min They are the minimum values ​​of the coordinates on the X, Y, and Z axes respectively;

[0033] 2) Propagation time calculation: For each grid point, the theoretical propagation time from the point to each sensor is calculated, and the theoretical propagation time is compared with the actual monitored arrival time to obtain the time residual;

[0034] 3) Grid search: By constructing the earthquake source location objective function, calculate the objective function value of each grid point, and find the grid point that minimizes the objective function value. This point is the initial earthquake source location (x g ,y g ,z g ).

[0035] In the acoustic emission source localization method based on grid search and simulated annealing disclosed in the first aspect of the present invention, in step S5, the solved preliminary source position is used as the initial iteration value of simulated annealing to solve the precise source position, including:

[0036] 1) Initialization parameters: set the initial temperature T and the end temperature T min , temperature drop function and number of iterations, where T is generally 100, T minGenerally, it is set to 0.2, the temperature drop function is T = T·α, α is the temperature drop rate, and the value is 0<α<1, and the number of iterations is generally 300;

[0037] 2) Select the initial solution: The initial source location estimated by grid search is used as the initial solution of simulated annealing (x g ,y g ,z g );

[0038] 3) Cooling: lower the temperature T according to the set temperature drop function;

[0039] 4) Iteration process: Calculate the objective function value E at the current earthquake source position c , generate a new source position (x', y', z') by random perturbation of the current solution, and calculate the objective function E of the new source position n , update the current source location according to the following acceptance criteria: if E n <E c , accept the new solution; if E n >E c , then with a certain probability Accept the new solution, when the temperature T drops to T min Or when the set number of iterations is reached, the current solution is returned;

[0040] 5) Termination condition: Repeat the above steps until the termination condition is met, that is, the objective function value is less than 1×10 -6 When the final accurate source position (x s ,y s ,z s ) and the corresponding objective function value, otherwise, appropriately reduce the temperature drop rate or increase the number of iterations and perform re-iteration.

[0041] The second aspect of the present invention discloses an acoustic emission source localization system based on grid search and simulated annealing, comprising:

[0042] The acoustic emission signal acquisition and processing module is used to acquire the acoustic emission signal containing the arrival time information and perform filtering processing on the acoustic emission signal;

[0043] An acoustic emission event first arrival time picking module is used to pick up the first arrival time of the acoustic emission event according to the acoustic emission signal after filtering;

[0044] A source location objective function construction module is used to construct a source location objective function based on the picked first arrival times;

[0045] A preliminary earthquake source location solution module is used to solve the preliminary earthquake source location by global search using a grid search method based on the constructed earthquake source location objective function;

[0046] The module for solving the precise earthquake source position is used to solve the precise earthquake source position by taking the solved preliminary earthquake source position as the initial iteration value of simulated annealing.

[0047] The third aspect of the present invention discloses an electronic device, including a memory, a processor and a bus, wherein the memory stores a computer program executable by the processor. When the electronic device is running, the memory and the processor communicate through the bus, and the processor executes the computer program to execute the acoustic emission source localization method based on grid search and simulated annealing disclosed in the first aspect above.

[0048] The fourth aspect of the present invention discloses a storage medium storing computer program instructions, which, when executed by a processor, executes the acoustic emission source localization method based on grid search and simulated annealing disclosed in the first aspect.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] The present invention utilizes the global search characteristics of the grid search method and the characteristics of the simulated annealing method that the model jumps out of the local optimal solution and has global convergence in the acoustic emission source positioning method for the first time, thereby improving the robustness of the positioning algorithm. Compared with the acoustic emission source positioning method in the prior art, the present invention can take into account the calculation speed and stability of the positioning algorithm at the same time, and the calculation speed and stability are significantly improved, meeting the needs in the technical field of the acoustic emission source positioning method; secondly, the present invention adopts the STA / LTA-AIC method to identify the acoustic emission event and pick up the initial arrival time, and the picked arrival time is used as the actual arrival time to enter the positioning target function, and then the grid search method is used to obtain a preliminary result that is relatively close to the global optimal point, and finally the output result of the grid search method is used as the initial value of the simulated annealing method for local search, and the global optimal point is obtained by continuously iterating the calculation nodes, thereby avoiding the situation that the simulated annealing method causes the error to become larger due to improper selection of the initial value, and the simulated annealing has the characteristics of simple calculation and high efficiency, which improves the operation efficiency and accuracy in the iterative process, thereby realizing the rapid and efficient positioning of the acoustic emission source.

[0051] The following discloses in detail the acoustic emission source localization method, system, electronic device and storage medium based on grid search and simulated annealing of the present invention in conjunction with the embodiments shown in the accompanying drawings and the accompanying figure numerals. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A step diagram of an acoustic emission source localization method based on grid search and simulated annealing according to the present invention is shown;

[0053] Figure 2 The flowchart of the acoustic emission source localization system based on grid search and simulated annealing of the present invention is shown;

[0054] Figure 3 The present invention is a flowchart of specific steps for implementing the acoustic emission source localization system based on grid search and simulated annealing. DETAILED DESCRIPTION

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] It should be noted that, in the absence of conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. And it should be noted that the terms used here are only for describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0057] In addition, the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein, for example. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0058] like Figure 1 As shown, the present invention discloses an acoustic emission source positioning method based on grid search and simulated annealing, comprising the following steps: S1, collecting acoustic emission signals containing arrival time information, and filtering the acoustic emission signals; S2, picking up the first arrival time of the acoustic emission event according to the acoustic emission signals after filtering; S3, constructing a source position target function based on the picked first arrival time; S4, performing a global search using a grid search method through the constructed source position target function to solve a preliminary source position; S5, using the solved preliminary source position as an initial iteration value of simulated annealing to solve an accurate source position.

[0059] In the present invention, by identifying an acoustic emission event and picking up the initial arrival time, the picked arrival time is used as the actual arrival time to enter the positioning objective function, and then a preliminary result relatively close to the global optimal point is obtained by using the grid search method, and finally the output result of the grid search method is used as the initial value of the simulated annealing method for local search, and the calculation nodes are continuously iterated to obtain the global optimal point, so as to realize fast and efficient positioning of the acoustic emission source; and the global search characteristics of the grid search method and the simulated annealing method are used to make the model jump out of the local optimal solution and the global convergence, so as to improve the robustness of the positioning algorithm, and compared with the existing acoustic emission source positioning method, the calculation speed and stability of the positioning algorithm are taken into account at the same time, so as to meet the use requirements in the technical field of the acoustic emission source positioning method.

[0060] In the present invention, in step S1, the purpose of filtering the acoustic emission signal is to remove background noise, avoid interference with the acoustic emission source positioning algorithm, and affect the accuracy of the result.

[0061] In the embodiment of the present invention, in step S2, picking up the first arrival time of the acoustic emission event includes:

[0062] The long-short time window ratio method STA / LTA is used to identify acoustic emission events;

[0063] The AIC method is used to pick the first arrival time.

[0064] In a preferred embodiment, in step S2, the long-short time window ratio method STA / LTA is used to identify acoustic emission events, and the sudden change of the ratio of STA to LTA is used as the judgment condition, wherein the short-time window STA represents the amplitude or energy of the microseismic signal, and the long-time window LTA represents the amplitude or energy of the background noise. When the STA / LTA ratio exceeds the set threshold, it means that an acoustic emission event has occurred; the square of the amplitude is used as the characteristic function of the long-short time window ratio method STA / LTA, and the calculation formula is as follows:

[0065]

[0066]

[0067] In the formula, X(i) (i = 1, 2, ..., N) represents the amplitude of the microseismic waveform, STA(i) and LTA(i) are the short-term average and long-term average of the amplitude at time i, respectively, Nsta and Nlta represent the short-term window width and long-term window width, respectively, and the weighting coefficient α is the standard deviation of the signal amplitude in the short-term window (σ S ) and the standard deviation of the signal amplitude in the long time window (σ L ) to increase the sensitivity to signal changes.

[0068] In a preferred embodiment, in step S2, after the long-short time window ratio method STA / LTA identifies the acoustic emission event, the AIC method is used to find the minimum value of the AIC function of the local waveform segment within the appropriate time window, and the time corresponding to the minimum value is the first arrival time; the calculation formula of the AIC function is as follows:

[0069] AIC(k)=klog{var(X[1,k])}+(Nk-1)log{var(x[k+1,N])};

[0070] Where N is the total number of sampling points, k represents the sliding variable, and var(x[1,k]) and var(x[k+1,N]) represent the variance of the samples in two time periods, respectively.

[0071] In the embodiment of the present invention, in step S3, a source location objective function based on the sensor arrival time difference is constructed, wherein the acoustic emission source location based on the arrival time difference is realized by searching for the minimum residual between the theoretical arrival time and the actual arrival time. Assuming that the acoustic emission event occurs at time t0, after Δt i The duration of i To the i-th (i=1,2,…,n) sensor position, the residual θ between the theoretical arrival time and the actual arrival time of the i-th acoustic emission sensor is i It can be expressed as:

[0072] θ i =t i -Δt i -t0;

[0073] In order to simplify the calculation process, it is usually assumed that the propagation medium has a uniform velocity, so the elastic wave velocity is a constant value, which can be expressed as the equivalent wave velocity c p Simple expression. Assume that the coordinates of the acoustic emission source are (x0, y0, z0), and the position coordinates of the i-th sensor are (x i ,y i ,z i ), l i is the distance between the ith station and the earthquake source. According to the distance formula between two points, the calculation of the ith sensor can be simplified to:

[0074]

[0075] In the case of only a single sensor, t0 cannot be obtained. In order to eliminate the influence of the earthquake occurrence time t0 on the positioning result, the relationship between multiple sensors can be used. The residual θ between the i-th sensor and the j-th sensor ij for:

[0076] θ ij =θ i -θj =t i -Δt i -t0-(t j -Δt j -t0)=t i -t j -(Δt i -Δt j )

[0077] Under ideal conditions, the residual error θ between different sensors is ij = 0, but in practice, due to the influence of errors such as the first arrival time picking and theoretical arrival time calculation, θ ij Generally it is not 0. But compared with other points, the θ of the acoustic emission source ij The absolute value of is the smallest, and the source location error is the smallest. Therefore, the realization of acoustic emission source location can be achieved by searching the acoustic emission monitoring area so that the following objective function reaches the minimum value. The objective function is:

[0078]

[0079] Where (x, y, z) is the coordinate of any node in the acoustic emission monitoring area, and the source point (x0, y0, z0) should make the objective function reach the minimum value. i The first arrival time picked by AIC method can be obtained, Δt i It can be simply calculated using the equivalent wave speed and the distance between two points.

[0080] In a preferred embodiment, in step S4, a global search is performed using a grid search method to solve the preliminary source location. In this embodiment, first, in a given three-dimensional space area, all possible source locations are traversed according to a suitable grid density, the error between each location as the source and the monitored arrival data is calculated, and the location with the smallest error is found as a preliminary estimate of the source. The specific steps are as follows:

[0081] 1) Model building: According to the size of the rock specimen, the area where the acoustic emission event may occur is used as the search area. The search area is a three-dimensional space, and the search area is divided into a series of grid points. The density of the grid points determines the positioning accuracy. When the search area is large and the grid division is fine, the calculation amount of the grid search is large. Therefore, the search area and grid point density of the grid search should not be too large. In three-dimensional space, the coordinates of any grid point can be expressed as:

[0082]

[0083] Where n x , n y , n zare the number of grids on the X, Y, and Z axes, Δx, Δy, and Δz are the grid sizes on the three axes, and x is min ,y min ,z min They are the minimum values ​​of the coordinates on the X, Y, and Z axes respectively;

[0084] 2) Propagation time calculation: For each grid point, the theoretical propagation time from the point to each sensor is calculated, and the theoretical propagation time is compared with the actual monitored arrival time to obtain the time residual;

[0085] 3) Grid search: Based on the earthquake source location objective function constructed in step S3, the objective function value of each grid point is calculated, and the grid point that minimizes the objective function value is found. This point is the preliminary earthquake source location (x g ,y g ,z g ).

[0086] In a preferred embodiment, in step S5, the solved preliminary source position is used as the initial iteration value of simulated annealing to solve the precise source position. In this embodiment, after step S4, a rough position close to the real position is obtained, and the search range of the source point is controlled in a smaller area, and then the positioning result obtained by grid search is used as the initial iteration value of simulated annealing, and the simulated annealing method is used to accurately locate the location by jumping out of the local optimum and eventually tending to the global optimum. Simulated annealing is a heuristic global optimization algorithm that can continuously update the optimal solution with a certain probability during the optimization process, thereby jumping out of the local optimal solution and randomly searching for the global optimal solution of the objective function in the solution space. The specific steps are as follows:

[0087] 1) Initialization parameters: set the initial temperature T and the end temperature T min , temperature drop function and number of iterations. Where T is generally 100, T min Generally, it is set to 0.2, the temperature drop function is T = T·α, α is the temperature drop rate, and the value is 0<α<1, and the number of iterations is generally 300;

[0088] 2) Select the initial solution: Use the positioning result obtained by grid search as the initial solution of simulated annealing (x g ,y g ,z g );

[0089] 3) Cooling: lower the temperature T according to the set temperature drop function;

[0090] 4) Iteration process: Calculate the objective function value E at the current earthquake source position c, generate a new source position (x', y', z') by random perturbation of the current solution, and calculate the objective function E of the new source position n ;

[0091] Update the current source location according to the following acceptance criteria: If E n <E c , accept the new solution; if E n >E c , then with a certain probability Accept the new solution. When the temperature T drops to T min Or when the set number of iterations is reached, the current solution is returned;

[0092] 5) Termination condition: Repeat the above steps until the termination condition is met, that is, the objective function value is less than 1×10 -6 When the final accurate source position (x s ,y s ,z s ) and the corresponding objective function value. Otherwise, appropriately reduce the temperature drop rate or increase the number of iterations and perform re-iteration.

[0093] like Figure 2 As shown, the present invention also discloses an acoustic emission source positioning system based on grid search and simulated annealing, comprising:

[0094] The acoustic emission signal acquisition and processing module is used to acquire the acoustic emission signal containing the arrival time information and perform filtering processing on the acoustic emission signal;

[0095] An acoustic emission event first arrival time picking module is used to pick up the first arrival time of the acoustic emission event according to the acoustic emission signal after filtering;

[0096] A source location objective function construction module is used to construct a source location objective function based on the picked first arrival times;

[0097] A preliminary earthquake source location solution module is used to solve the preliminary earthquake source location by global search using a grid search method based on the constructed earthquake source location objective function;

[0098] The module for solving the precise earthquake source position is used to solve the precise earthquake source position by taking the solved preliminary earthquake source position as the initial iteration value of simulated annealing.

[0099] like Figure 3 As shown, when the acoustic emission source localization system based on grid search and simulated annealing of the present invention is implemented, the specific steps are as follows:

[0100] 1. Input the acoustic emission signal and perform filtering;

[0101] 2. Use the STA / LTA-ATC method to pick up the first arrival time of the acoustic emission event;

[0102] 3. Construct an objective function based on the time difference from sensor to sensor;

[0103] 4. Use the grid search method to perform a global search to solve the source location (x g ,y g ,z g );

[0104] 5. Set initialization parameters;

[0105] 6. Use the results obtained from the grid search as the initial solution for simulated annealing;

[0106] 7. Update the current optimal solution to obtain a more accurate earthquake source location (x s ,y s ,z s );

[0107] 8. Determine whether the termination condition is met. If the termination condition is met, output the result; if the termination condition is not met, return to step 5 and continue iterating until the termination condition is met.

[0108] The present invention also discloses an electronic device, including a memory, a processor and a bus, wherein the memory stores a computer program executable by the processor. When the electronic device is running, the memory and the processor communicate through the bus, and the processor executes the computer program to execute the acoustic emission source localization method based on grid search and simulated annealing disclosed in the first aspect of the present invention.

[0109] The present invention also discloses a storage medium storing computer program instructions, which are executed by a processor when running the method for locating acoustic emission sources based on grid search and simulated annealing disclosed in the first aspect of the invention.

[0110] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0111] In addition, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0112] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0113] The above description is only an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0114] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0115] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0116] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A method for locating acoustic emission sources based on grid search and simulated annealing, characterized in that: The steps include: S1, collecting acoustic emission signals containing arrival information and filtering the acoustic emission signals; S2, picking up the first arrival time of the acoustic emission event according to the acoustic emission signal after filtering; S3, constructing the hypocenter location objective function based on the picked first arrival times; S4, using the constructed earthquake source location objective function to perform a global search using the grid search method to solve the preliminary earthquake source location; S5, using the solved preliminary earthquake source position as the initial iteration value of simulated annealing to solve the precise earthquake source position.

2. The acoustic emission source localization method based on grid search and simulated annealing according to claim 1, characterized in that: In step S2, picking up the first arrival time of the acoustic emission event includes: The long-short time window ratio method STA / LTA is used to identify acoustic emission events; The AIC method is used to pick the first arrival time.

3. The acoustic emission source localization method based on grid search and simulated annealing according to claim 2, characterized in that: In step S2, the long-short time window ratio method STA / LTA is used to identify acoustic emission events, and the sudden change of the ratio of STA to LTA is used as the judgment condition, wherein the short-time window STA represents the amplitude or energy of the microseismic signal, and the long-time window LTA represents the amplitude or energy of the background noise. When the STA / LTA ratio exceeds the set threshold, it means that an acoustic emission event has occurred; the square of the amplitude is used as the characteristic function of the long-short time window ratio method STA / LTA, and the calculation formula is as follows: In the formula, X(i) (i = 1, 2, ..., N) represents the amplitude of the microseismic waveform, STA(i) and LTA(i) are the short-term average and long-term average of the amplitude at time i, respectively, Nsta and Nlta represent the short-term window width and long-term window width, respectively, and the weighting coefficient α is the standard deviation of the signal amplitude in the short-term window (σ S ) and the standard deviation of the signal amplitude in the long time window (σ L ) to increase the sensitivity to signal changes.

4. The acoustic emission source localization method based on grid search and simulated annealing according to claim 3, characterized in that: In step S2, after the AE event is identified by the long-short time window ratio method STA / LTA, the AIC method is used to find the minimum value of the AIC function of the local waveform segment within the appropriate time window. The time corresponding to the minimum value is the first arrival time. The calculation formula of the AIC function is as follows: AIC(k)=klog{var(X[1,k])}+(Nk-1)log{var(x[k+1,N])}; Where N is the total number of sampling points, k represents the sliding variable, and var(x[1,k]) and var(x[k+1,N]) represent the variance of the samples in two time periods, respectively.

5. The acoustic emission source localization method based on grid search and simulated annealing according to claim 1, characterized in that: In step S3, the earthquake source location objective function is constructed, and the calculation formula is as follows: Where (x, y, z) is the coordinate of any node in the acoustic emission monitoring area, θ ij is the residual between the ith acoustic emission sensor and the jth acoustic emission sensor, c p is the equivalent wave speed, l i is the distance between the ith station and the earthquake source, l j is the distance between the jth station and the earthquake source, t i is the time from the acoustic emission event to the i-th acoustic emission sensor, t j is the time when the acoustic emission event arrives at the jth acoustic emission sensor.

6. The method for locating acoustic emission sources based on grid search and simulated annealing according to claim 5, characterized in that: In step S4, a global search is performed using a grid search method to solve the preliminary earthquake source location, including: Steps to establish the model: According to the size of the rock specimen, the area where the acoustic emission event may occur is used as the search area. The search area is a three-dimensional space, and the search area is divided into a series of grid points. The density of the grid points determines the accuracy of positioning. When the search area is large and the grid division is fine, the calculation amount of the grid search is large. Therefore, the search area and grid point density of the grid search should not be too large. In three-dimensional space, the coordinates of any grid point can be expressed as: Where n x , n y , n z are the number of grids on the X, Y, and Z axes, Δx, Δy, and Δz are the grid sizes on the three axes, and x is min ,y min ,z min They are the minimum values ​​of the coordinates on the X, Y, and Z axes respectively; The steps of propagation time calculation are as follows: for each grid point, the theoretical propagation time from the point to each sensor is calculated, and the theoretical propagation time is compared with the actual monitored arrival time to obtain the time residual; Grid search steps: By constructing the earthquake source location objective function, calculate the objective function value of each grid point, and find the grid point that minimizes the objective function value. This point is the preliminary earthquake source location (x g ,y g ,z g ).

7. The method for locating acoustic emission sources based on grid search and simulated annealing according to claim 6, characterized in that: In step S5, the solved preliminary earthquake source position is used as the initial iteration value of simulated annealing to solve the precise earthquake source position, including: Steps for initializing parameters: set initial temperature T, end temperature T min , temperature drop function and number of iterations, where T is generally 100, T min Generally, it is set to 0.2, the temperature drop function is T = T·α, α is the temperature drop rate, and the value is 0<α<1, and the number of iterations is generally 300; Steps for selecting the initial solution: Use the preliminary source location estimated by grid search as the initial solution for simulated annealing (x g ,y g ,z g ); Cooling steps: lower the temperature T according to the set temperature drop function; Steps of the iterative process: Calculate the objective function value E at the current earthquake source position c , generate a new source position (x', y', z') by random perturbation of the current solution, and calculate the objective function E of the new source position n , update the current source location according to the following acceptance criteria: if E n <E c , accept the new solution; if E n >E c , then with a certain probability Accept the new solution, when the temperature T drops to T min Or when the set number of iterations is reached, the current solution is returned; Termination condition steps: Repeat the above steps until the termination condition is met, that is, the objective function value is less than 1×10 -6 When the final accurate source position (x s ,y s ,z s ) and the corresponding objective function value, otherwise, appropriately reduce the temperature drop rate or increase the number of iterations and perform re-iteration.

8. An acoustic emission source localization system based on grid search and simulated annealing, characterized in that: include: The acoustic emission signal acquisition and processing module is used to acquire the acoustic emission signal containing the arrival time information and filter the acoustic emission signal; An acoustic emission event first arrival time picking module is used to pick up the first arrival time of the acoustic emission event according to the acoustic emission signal after filtering; A source location objective function construction module is used to construct a source location objective function based on the picked first arrival times; A preliminary earthquake source location solution module is used to solve the preliminary earthquake source location by global search using a grid search method based on the constructed earthquake source location objective function; The module for solving the precise earthquake source position is used to solve the precise earthquake source position by taking the solved preliminary earthquake source position as the initial iteration value of simulated annealing.

9. An electronic device, characterized in that: The electronic device comprises a memory, a processor and a bus, wherein the memory stores a computer program executable by the processor, and when the electronic device is running, the memory and the processor communicate via the bus, and the processor executes the computer program to execute the acoustic emission source localization method based on grid search and simulated annealing according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores computer program instructions, and when the computer program instructions are executed by the processor, the method for locating an acoustic emission source based on grid search and simulated annealing according to any one of claims 1 to 7 is executed.

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