Acoustic emission positioning method and system for monitoring soil agglomeration and rupture sources

Abstract

The present invention provides an acoustic emission positioning method for monitoring soil agglomeration rupture sources, and the acoustic emission positioning method includes: synchronously collecting acoustic emission signals in the agglomeration load rupture process from several directions, and applying bandpass filtering to remove noise; obtaining the main rupture signal time point of each probe, and the rupture process signal energy value, and normalizing the energy value; assigning a positioning weight to each probe according to the energy value, and then establishing a weighted least squares objective function of the agglomeration rupture source according to the deployment position of each probe and the main rupture signal time point; solving the agglomeration rupture source objective function using the nonlinear least squares method to obtain the convergence position of the agglomeration rupture source; selecting agglomerations with known rupture positions and soil types as samples for acoustic emission positioning, and obtaining the optimal acoustic emission positioning parameters for the soil type agglomeration rupture positioning. Beneficial effects of the present invention: understanding the mechanical structure of soil agglomerates, and realizing high-precision positioning of rupture sources in complex soil environments.

Description

Technical Field

[0001] The invention belongs to the technical field of rock and soil structure detection, and in particular relates to an acoustic emission positioning method and system for monitoring soil agglomeration and rupture sources. Background Art

[0002] Soil agglomeration refers to the phenomenon that soil particles aggregate to form clumps due to moisture, pressure or other external factors. This not only affects the physical and mechanical properties of the soil, such as permeability, compressibility and shear strength, but also has a profound impact on agricultural production, construction engineering and environmental protection. In order to effectively monitor and evaluate the microscopic fractures and energy release in the process of soil agglomeration, acoustic emission (AE) technology is widely used in geotechnical engineering and soil monitoring. AE technology can provide non-destructive and continuous monitoring by capturing the high-frequency sound wave signals generated by the expansion of cracks or the rearrangement of particles inside the soil in real time. For example, AE technology has shown its unique advantages in slope stability analysis, underground structure construction monitoring and agricultural soil health assessment. However, the existing AE application has many limitations in actual operation, mainly including complex probe layout, serious signal noise interference and insufficient rupture source location accuracy. These problems limit the wide application and precise monitoring of AE technology in complex soil environments. Summary of the invention

[0003] In view of this, the present invention aims to propose an acoustic emission positioning method and system for monitoring soil agglomeration rupture sources, so as to understand the mechanical structure of soil agglomerates and achieve high-precision positioning of rupture sources in complex soil environments.

[0004] To achieve the above object, the technical solution of the present invention is achieved as follows:

[0005] Acoustic emission positioning method and system for monitoring soil agglomeration and rupture sources.

[0006] Furthermore, the mechanical structure of the soil is obtained according to the acoustic emission signal when the agglomerates are broken by the load, and the initial breaking point is located by combining the timing and energy of each acoustic emission probe signal. The acoustic emission positioning method includes:

[0007] T1. Signal acquisition: Acoustic emission signals during the agglomerate load rupture process are collected synchronously from several directions, and bandpass filtering is applied to remove noise;

[0008] T2. Data processing: obtaining the main rupture signal time point of each probe and the energy value of the rupture process signal, and normalizing the energy value;

[0009] T3, weighted positioning: assign positioning weights to each probe according to the energy value, and then establish a weighted least squares objective function of the agglomeration rupture source according to the deployment position of each probe and the time point of the main rupture signal;

[0010] T4, iterative solution: use the nonlinear least square method to solve the agglomeration rupture source objective function and obtain the convergence position of the agglomeration rupture source;

[0011] T5. Optimize positioning: Select the agglomerates with known rupture locations and soil types as samples for acoustic emission positioning. Compare the positioning results with the known rupture locations to adjust the probe deployment position and energy rights allocation method to obtain the best acoustic emission positioning parameters for the rupture positioning of agglomerates of this soil type.

[0012] Further, in said T1, at least four AE probes are arranged at known positions on the same plane of soil agglomeration, and the characteristics of the collected acoustic emission signals include but are not limited to the number of ringings and amplitude;

[0013] According to the physical characteristics of soil agglomeration, a multiple filtering strategy of low-pass and high-pass filters is used to remove noise in different frequency bands in stages.

[0014] Furthermore, the T2 signal energy value is the frequency domain signal energy. The signal energy is calculated by power spectrum density after the acoustic emission signal is converted to the frequency domain through time-frequency transformation. :

[0015] ;

[0016] In the formula, It emits a frequency domain signal for sound. , is the main frequency range of rupture;

[0017] The weight of each probe after energy normalization :

[0018] ;

[0019] In the formula, is the probe number, total A probe, is the normalized value of the probe energy.

[0020] Furthermore, in T3, the energy contribution of each probe is comprehensively considered to construct the objective function :

[0021] ;

[0022] ;

[0023] ;

[0024] In the formula, For the source and Probe distance, is the distance between the signal source and the reference probe, The arrival time difference of each probe relative to the reference probe 1, For the The time point when each probe receives the signal, , is the plane coordinate of the probe, is the speed of sound waves propagating in the soil.

[0025] Furthermore, in T4, the Gauss-Newton iteration method is used to minimize the error after weighting the arrival time difference and signal energy measured by all probes, and the rupture source position is obtained:

[0026] .

[0027] Further, Probe time difference By the original time difference Time scaling to improve positioning accuracy, based on reference probe 1 and probe The scaling factor is determined by the user's own position and the expected source direction. , and then scale the original time difference :

[0028] ;

[0029] ;

[0030] In the formula, For the original The difference between the time points when the probe and reference probe 1 receive the signal, is the amplification factor, and u is the expected source direction vector.

[0031] Furthermore, the starting point of the expected source direction vector u is probe location points, whose endpoints include but are not limited to the centroid of soil agglomeration and the geometric center point of all probes.

[0032] Further, a system for monitoring the source of soil caking and breaking, realizing the acoustic emission positioning method, comprises at least four acoustic emission probes and a load cell, the acoustic emission probes are all distributed around the caking soil caking, and all the acoustic emission probes are in the same plane;

[0033] The loading mode of the load unit includes but is not limited to distributed loading and multi-point loading, and the loading direction is perpendicular to the plane where the acoustic emission probe is located.

[0034] Furthermore, an electronic device includes a processor and a memory connected to the processor for storing executable instructions for the processor, wherein the processor is used to execute the acoustic emission positioning method for monitoring soil agglomeration and rupture sources.

[0035] Furthermore, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the acoustic emission positioning method for monitoring the source of soil agglomeration and rupture is implemented.

[0036] Compared with the prior art, the acoustic emission positioning method of the present invention has the following beneficial effects:

[0037] (1) The acoustic emission positioning method described in the present invention accurately measures the arrival time of the sound waves received at each monitoring point and introduces random noise to simulate the interference in the actual environment, thereby ensuring the applicability of the model under complex conditions;

[0038] (2) The acoustic emission positioning method described in the present invention uses normalized energy weights to perform weighted processing on the signals of different monitoring points, thereby enhancing the influence of high-energy signals, effectively suppressing the interference of low-energy noise, and improving the signal-to-noise ratio of the signal;

[0039] (3) The acoustic emission positioning method described in the present invention uses a weighted least squares optimization algorithm to accurately calculate the time difference, which significantly improves the accuracy and calculation efficiency of the rupture source position estimation. It comprehensively considers the energy weight and time difference deviation of each monitoring point, and realizes the precise positioning of the rupture source through numerical optimization.

[0040] (4) The acoustic emission positioning method described in the present invention uses time difference scaling technology to dynamically adjust and normalize the arrival time of the sound waves received at each monitoring point, effectively eliminating the time deviation caused by different detection paths and changes in propagation speed, thereby improving the consistency and reliability of time difference measurement. In this way, even in complex soil environments with uneven propagation conditions, the actual arrival time of the acoustic emission signal can be accurately captured. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0042] Figure 1 Schematic diagram of the arrangement of the acoustic emission probe and the load cell according to the embodiment of the present invention Figure 1 ;

[0043] Figure 2 Schematic diagram of the arrangement of the acoustic emission probe and the load cell according to the embodiment of the present invention Figure 2 ;

[0044] Figure 3 Schematic diagram of the expected information source position according to the embodiment of the present invention Figure 1 ;

[0045] Figure 4 Schematic diagram of the expected information source position according to the embodiment of the present invention Figure 2 ;

[0046] Figure 5 The figure is a flow chart of the acoustic emission positioning method according to an embodiment of the present invention.

[0047] Description of reference numerals:

[0048] 1-probe; 2-agglomeration; 3-loading area. DETAILED DESCRIPTION

[0049] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0050] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0051] A system for monitoring the source of soil caking and breaking, such as Figure 1-Figure 2 As shown, it includes at least four acoustic emission probes and load cells. The acoustic emission probes are distributed around the agglomerates of agglomerated soil, and all the acoustic emission probes are in the same plane; the load mode of the load cell includes but is not limited to distributed load and multi-point load, and the load direction is perpendicular to the plane where the acoustic emission probe is located. The monitoring principle is to use the load cell to apply load to the soil agglomerates, causing the defective structure in the heterogeneous soil agglomerates to rupture and collapse to generate sound waves, and the acoustic emission probes arranged around the agglomerates capture the sound waves as data for subsequent source (rupture point) positioning. The load unit includes equipment such as a texture analyzer and a mechanical load device. When a texture analyzer is used to apply load, there is a possibility that the rupture mainly occurs at the load application point, but the actual situation may be more complicated, especially in heterogeneous soil or materials with pre-defects. The rupture may not be limited to the load point, but may also occur at other locations. By applying loads at distributed or multi-points, the stress concentration at a single point is reduced, making it more likely that the rupture will occur at different locations, thereby improving the actual application effect of AE positioning.

[0052] The acoustic emission positioning method used to monitor the source of soil agglomeration rupture obtains the mechanical structure of the soil based on the acoustic emission signal when the agglomeration is broken by the load, and combines the timing and energy of each acoustic emission probe signal to locate the initial rupture point. The positioning principle is to use multiple acoustic emission probes to synchronously collect the acoustic signals generated by the rupture, analyze the arrival time difference and energy distribution of the signal, combine the weighted algorithm and iterative optimization technology, and integrate the information of each probe to accurately locate the rupture source of the soil agglomeration. Figure 5The acoustic emission positioning method shown includes the following steps:

[0053] T1. Signal acquisition: Acoustic emission signals during the agglomerate load rupture process are collected synchronously from several directions, and bandpass filtering is applied to remove noise;

[0054] T2. Data processing: obtaining the main rupture signal time point of each probe and the energy value of the rupture process signal, and normalizing the energy value;

[0055] T3, weighted positioning: assign positioning weights to each probe according to the energy value, and then establish a weighted least squares objective function of the agglomeration rupture source according to the deployment position of each probe and the time point of the main rupture signal;

[0056] T4, iterative solution: use the nonlinear least square method to solve the agglomeration rupture source objective function and obtain the convergence position of the agglomeration rupture source;

[0057] T5. Optimize positioning: Select the agglomerates with known rupture locations and soil types as samples for acoustic emission positioning. Compare the positioning results with the known rupture locations to adjust the probe deployment position and energy rights allocation method to obtain the best acoustic emission positioning parameters for the rupture positioning of agglomerates of this soil type.

[0058] Specifically, in the T1, at least four AE probes are arranged at known positions on the same plane of the soil agglomerate, and the characteristics of the collected acoustic emission signals include but are not limited to the number of ringings and amplitude, wherein the ringing threshold should be set according to the mechanical properties of the monitored soil agglomerate to remove background noise while capturing the maximum triggering ringing information as much as possible. According to the physical characteristics of soil agglomerates, a multiple filtering strategy combining low-pass and high-pass filters is used to remove noise in different frequency bands in stages to retain the acoustic wave signal when the soil agglomerate structure is broken.

[0059] Specifically, the T2 signal energy value is the frequency domain signal energy. Since the signal monitored by the existing acoustic emission equipment is usually a time domain signal, it is necessary to convert the acoustic emission signal to the frequency domain through time-frequency transformation (preferably FFT fast Fourier transform), and then calculate the signal energy through power spectrum density. :

[0060] ;

[0061] In the formula, It emits a frequency domain signal for sound. , is the main frequency range of the rupture. Since the actual acoustic emission signal is usually a discrete signal, its frequency domain energy can also be obtained by the discretization summation of the above formula.

[0062] Since the signal energy received by different probes may have different dimensions or orders of magnitude, normalization converts the energy value to a uniform range. Through normalization, it can be ensured that the sum of all weights is 1, so that the contribution of each probe is distributed proportionally, which helps prevent some probes from dominating the positioning process due to excessive energy, and ensures that the information of all probes is reasonably used. The weight of each probe after energy normalization is :

[0063] ;

[0064] In the formula, is the probe number, total A probe, is the normalized value of the probe energy.

[0065] Specifically, in T3, the energy contribution of each probe is comprehensively considered to construct the objective function :

[0066] ;

[0067] ;

[0068] ;

[0069] In the formula, For the source and Probe distance, is the distance between the signal source and the reference probe, The arrival time difference of each probe relative to the reference probe 1, For the The time point when each probe receives the signal, , is the plane coordinate of the probe, is the speed of sound waves propagating in the soil.

[0070] Specifically, in T4, the Gauss-Newton iteration method is used to minimize the error after weighting the arrival time difference and signal energy measured by all probes, and the rupture source position is obtained:

[0071] .

[0072] This embodiment takes eight acoustic emission probes as an example, assuming that the rupture source is located at the position (4,3) meters, and locates the position of the soil agglomeration rupture source by weighted least squares method:

[0073] ;

[0074] Its objective function is:

[0075]

[0076] The final rupture position is calculated by Gauss-Newton iteration method or steepest descent method. , error 0.012 meters.

[0077] Optionally, due to the limited size of soil agglomerates, the time difference of sound wave transmission between each probe is very close, so the time difference can be amplified based on the non-uniform time scaling of the probe position, thereby improving the measurement accuracy and enhancing the relative time difference. Probe time difference By the original time difference Time scaling to improve positioning accuracy, based on reference probe 1 and probe The scaling factor is determined by the user's own position and the expected source direction. , and then scale the original time difference :

[0078] ;

[0079] ;

[0080] In the formula, For the original The difference between the time points when the probe and reference probe 1 receive the signal, is the amplification factor, u is the expected source direction vector, and the time difference is recalculated in the time-scaled signal. Since the time difference is non-uniformly amplified, the sensitivity of the positioning algorithm to small time differences is increased, thereby improving the positioning accuracy. The starting point of the expected source direction vector u is probe location points, whose endpoints include but are not limited to the soil agglomeration center point, the geometric center point of all probes, Figure 3-Figure 4 shown.

[0081] Those of ordinary skill in the art will appreciate that the units and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0082] In the several embodiments provided in the present application, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the division of the units described above is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. The above-mentioned units may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

[0084] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An acoustic emission positioning method for monitoring soil agglomeration and rupture sources, characterized in that: The mechanical structure of the soil is obtained based on the acoustic emission signal when the agglomerate is broken by the load, and the initial breaking point is located by combining the timing and energy of each acoustic emission probe signal. The acoustic emission positioning method includes: T1. Signal acquisition: Acoustic emission signals during the agglomerate load rupture process are collected synchronously from several directions, and bandpass filtering is applied to remove noise; T2. Data processing: obtaining the main rupture signal time point of each probe and the energy value of the rupture process signal, and normalizing the energy value; T3, weighted positioning: assign positioning weights to each probe according to the energy value, and then establish a weighted least squares objective function of the agglomeration rupture source according to the deployment position of each probe and the time point of the main rupture signal; T4, iterative solution: use the nonlinear least square method to solve the agglomeration rupture source objective function and obtain the convergence position of the agglomeration rupture source; T5. Optimize positioning: Select known rupture locations and soil type agglomerates as samples for acoustic emission positioning. Compare the positioning results with the known rupture locations to adjust the probe deployment position and energy rights allocation method to obtain the best acoustic emission positioning parameters for the soil type agglomerate rupture positioning; The T2 signal energy value is the frequency domain signal energy. The acoustic emission signal is converted to the frequency domain through time-frequency transformation and the signal energy is calculated through the power spectrum density. : ； In the formula, It emits a frequency domain signal for sound. , is the main frequency range of rupture; The weight of each probe after energy normalization : ； In the formula, is the probe number, total A probe, is the normalized value of the probe energy; In T3, the energy contribution of each probe is comprehensively considered to construct the objective function : ； ； ； In the formula, For the source and Probe distance, is the distance between the signal source and the reference probe, The arrival time difference of each probe relative to the reference probe 1, For the The time point when each probe receives the signal, , is the plane coordinate of the probe, is the propagation speed of sound waves in the soil; No. Probe time difference By the original time difference Time scaling to improve positioning accuracy, based on reference probe 1 and probe Own location and expected source direction Determine the scaling factor , and then scale the original time difference : ； ； In the formula, For the original The difference between the time points when the probe and reference probe 1 receive the signal, is the magnification factor, is the expected source direction vector.

2. The acoustic emission positioning method for monitoring soil agglomeration and rupture sources according to claim 1 is characterized in that: In the T1, at least four AE probes are arranged at known positions on the same plane of soil agglomeration, and the characteristics of the collected acoustic emission signals include but are not limited to the number of ringings and amplitude; According to the physical characteristics of soil agglomeration, a multiple filtering strategy of low-pass and high-pass filters is used to remove noise in different frequency bands in stages.

3. The acoustic emission positioning method for monitoring soil agglomeration and rupture sources according to claim 1 is characterized in that: In T4, the Gauss-Newton iteration method is used to minimize the error after weighting the arrival time difference and signal energy measured by all probes, and the rupture source position is obtained: 。 4. The acoustic emission positioning method for monitoring soil agglomeration and rupture sources according to claim 1 is characterized in that: The expected source direction vector Starting point is probe location points, whose endpoints include but are not limited to the centroid of soil agglomeration and the geometric center point of all probes.

5. A system for monitoring soil agglomeration and rupture sources, implementing the acoustic emission positioning method as claimed in claim 1, characterized in that: It includes at least four acoustic emission probes and a load cell, wherein the acoustic emission probes are distributed around the agglomerated soil agglomerates, and all the acoustic emission probes are in the same plane; The loading mode of the load unit includes but is not limited to distributed loading and multi-point loading, and the loading direction is perpendicular to the plane where the acoustic emission probe is located.

6. An electronic device, comprising a processor and a memory connected to the processor for storing instructions executable by the processor, characterized in that: The processor is used to execute the acoustic emission positioning method for monitoring soil agglomeration and rupture sources as described in any one of claims 1 to 4 above.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the acoustic emission positioning method for monitoring soil agglomeration and rupture sources according to any one of claims 1 to 4 is implemented.

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