Soil engineering classification method based on acoustic emission characteristic information

Abstract

The invention relates to the technical field of geotechnical engineering and acoustics, in particular to a soil engineering classification method based on acoustic emission characteristic information. The soil engineering classification method comprises the following steps: placing a prefabricated soil sample on a base in a triaxial loading device, and connecting an acoustic emission sensor in an acoustic emission measurement system to the outer wall of the soil sample; controlling a confining pressure system and a loading system in the triaxial loading device to carry out shear failure at a constant axial loading rate on the soil sample, and stopping the failure until the axial strain of the soil sample is 30%; an original acoustic emission time domain electric signal generated in the shear failure process of the soil sample is obtained in the whole process through an acoustic emission measurement system; processing and analyzing the obtained original acoustic emission time-domain electric signal, and extracting an acoustic emission characteristic parameter from the original acoustic emission time-domain electric signal; the acoustic emission characteristic parameters are peak frequency, acoustic emission event rate and acoustic emission energy rate; dividing the dominant frequency response in the loading process of the triaxial loading device into a low frequency, an intermediate frequency and a high frequency through a Chebyshev filter; extracting low-frequency,-intermediate-frequency and high-frequency information in the acoustic emission event rate and the acoustic emission energy rate; and based on the characteristic information response difference of the AE average event rate and the AE average energy rate, dividing soil classes. A cylindrical soil sample is placed on a bottom base in a triaxial device, an acoustic emission measurement system is mounted on the side wall of the sample, and a confining pressure system and a loading system of the triaxial device are controlled to shear and damage the soil sample; original acoustic emission time domain electric signals generated in the shear failure process of the sample are obtained in the whole process through an acoustic emission measurement system; processing and analyzing an acoustic emission original time domain electric signal, and extracting acoustic emission characteristic parameter dominant frequency response, an acoustic emission event rate and an acoustic emission energy rate; the soil samples are classified according to the acoustic emission characteristic information of different soil samples in the shearing process, and the accuracy and universality of soil body classification are improved.

Description

Technical Field

[0001] The invention relates to the field of geotechnical engineering and acoustic technology, and in particular to a geotechnical engineering classification method based on acoustic emission characteristic information. Background Art

[0002] In geotechnical engineering, soil is often used as a material for foundations or geotechnical structures (such as embankments, roadbeds, and earth-rock dams). When designing foundations or geotechnical structures, it is first necessary to understand the engineering properties of soil. To make a preliminary qualitative evaluation of the properties of soil, the first thing to do is to classify the engineering of soil, which is the basic work of all geotechnical engineering designs. However, the structure of soil is complex and difficult to classify effectively. Different periods and regions have different classification systems, which brings great challenges to practical work.

[0003] At present, there is no completely unified basis for soil classification in my country. There are roughly three types of soil classification systems in China: the first type is based on the "Engineering Classification Standard for Soil", which classifies coarse-grained soil according to particle size composition and fine-grained soil according to plasticity diagram. The second type is based on the "Geotechnical Engineering Investigation Code" which is the most widely used in engineering construction in my country, which classifies coarse-grained soil according to particle size composition and fine-grained soil according to plasticity index. The third type is based on the "Railway Engineering Geotechnical Classification Standard", which is similar to the second type in the classification of coarse-grained soil, but the classification of fine-grained soil adopts the same plasticity diagram classification as the first type. There are basically two major systems for engineering classification of soil abroad. One is the unified classification method adopted by the United States, Britain, Japan and other countries, that is, coarse-grained soil is classified according to particle size and gradation, and fine-grained soil is classified according to plasticity index, which is the Casagrande plasticity diagram classification method. The other system is the classification of coarse-grained soil according to particle size composition and fine-grained soil according to plasticity index. These traditional soil engineering classification methods often obtain soil physical parameters (such as particle size, liquid limit, plasticity index, etc.) and mechanical parameters (such as compressive strength, shear strength, etc.) through indoor tests. However, these parameters often require destructive testing of soil samples when obtaining them and cannot fully reflect the complex behavior of soil types. At the same time, these methods rely on manual operation and recording, which are easily affected by the operator's level and test conditions, resulting in measurement errors and inconsistent results, limiting the accuracy and reliability of soil engineering classification.

[0004] Considering the aforementioned challenges, a measurement method is still needed to classify soils. One potential solution is to apply acoustic emission (AE) technology, which is an advanced non-destructive testing method. Acoustic emission refers to elastic body waves generated when the strain energy stored inside the stressed material is suddenly released, which is caused by irreversible changes such as crack formation and propagation, plastic deformation, or external mechanical forces. In the context of granular soils, particle interactions including particle rearrangement and particle crushing are the main sources of acoustic emission. Extracting and interpreting valuable information from acoustic emission waveforms is expected to achieve accurate classification of soils.

[0005] In view of this, the present invention proposes a soil engineering classification method based on acoustic emission characteristic information to solve the above-mentioned problems. Summary of the invention

[0006] The object of the present invention is to provide a soil engineering classification method based on acoustic emission characteristic information to solve any of the problems arising in the above-mentioned prior art.

[0007] The present invention adopts the following technical solution:

[0008] The present invention discloses a soil engineering classification method based on acoustic emission characteristic information. In the classification method, soil samples are subjected to a loading test by a triaxial loading device combined with an acoustic emission measurement system. The soil engineering classification steps based on the test are as follows:

[0009] S1. Place the prefabricated soil sample on the base inside the triaxial loading device, and connect the acoustic emission sensor in the acoustic emission measurement system to the outer wall of the soil sample;

[0010] S2, controlling the confining pressure system and the loading system in the triaxial loading device to perform shear failure on the soil sample at a constant axial loading rate until the axial strain of the soil sample reaches 30%, and then stopping the failure;

[0011] S3, using the acoustic emission measurement system to obtain the original acoustic emission time-domain electrical signal generated by the soil sample during the shear failure process;

[0012] S4, processing and analyzing the original acoustic emission time-domain electrical signal obtained in step S3, and extracting acoustic emission characteristic parameters from the original acoustic emission time-domain electrical signal;

[0013] The acoustic emission characteristic parameters are: peak frequency, acoustic emission event rate, and acoustic emission energy rate;

[0014] S5. The main frequency response of the triaxial loading device during loading is divided into low frequency, medium frequency and high frequency through Chebyshev filter; and the low frequency, medium frequency and high frequency information of acoustic emission event rate and acoustic emission energy rate are extracted; based on the characteristic information response differences of AE average event rate and AE average energy rate, the soil types are divided.

[0015] The invention discloses a soil engineering classification method based on acoustic emission characteristic information. The acoustic emission measurement system comprises an acoustic emission sensor, an acoustic emission signal amplifier, a data acquisition instrument and a calculator which are connected in sequence. An aluminum plate with a size of 10 mm×10 mm×1 mm is attached to the head of the acoustic emission sensor. The model of the acoustic emission sensor is R-cast:M304A produced by Fuji Ceramics Co., Ltd. of Japan. The model of the acoustic emission signal amplifier is A1201 produced by Fuji Ceramics Co., Ltd. of Japan. The model of the data acquisition instrument is PXIe-6366 produced by National Instruments of the United States.

[0016] In the soil engineering classification method based on acoustic emission characteristic information described in the present invention, in step 2, under saturated conditions, the target confining stress is applied to the soil sample, and then isotropic compression consolidation is performed for 30 minutes, and shear failure is started after the consolidation drainage volume is stable.

[0017] The soil engineering classification method based on acoustic emission characteristic information described in the present invention divides the main frequency response of AE into three components: low, medium and high frequency:

[0018] The low-frequency component has a main frequency of 0 to 100kHz;

[0019] The intermediate frequency component is mainly at 100-300kHz;

[0020] The high frequency component has a main frequency of 300kHz to 600kHz.

[0021] In the soil engineering classification method based on acoustic emission characteristic information described in the present invention, in step 4, the main frequency response during the loading process is divided into low frequency, medium frequency and high frequency through a Chebyshev filter.

[0022] The present invention discloses a soil engineering classification method based on acoustic emission characteristic information. In step 5, a main frequency response-shear displacement curve diagram, an AE average event rate-soil type diagram, and an AE average energy rate-soil type diagram are drawn. The soil type is determined by the AE average event rate and energy rate of different soil types and the distribution of low frequency, medium frequency, and high frequency during loading.

[0023] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0024] The invention discloses a soil engineering classification method based on acoustic emission characteristic information, which relates to the fields of geotechnical engineering and acoustic technology. The method places a cylindrical soil sample on a bottom base in a triaxial device, installs an acoustic emission measurement system on the side wall of the sample, controls the confining pressure system and the loading system of the triaxial device to shear the soil sample, and obtains the original acoustic emission time-domain electrical signal generated by the sample during the shearing failure process through the acoustic emission measurement system throughout the whole process; processes and analyzes the original acoustic emission time-domain electrical signal, extracts the acoustic emission characteristic parameters of the main frequency response, the acoustic emission event rate, and the acoustic emission energy rate; and classifies the soil samples according to the acoustic emission characteristic information of different soil samples during the shearing process, thereby improving the accuracy and versatility of soil classification. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A schematic diagram of a soil classification method based on acoustic emission characteristic information of the present invention;

[0026] Figure 2 Schematic diagram of a triaxial loading device and a high-precision acoustic emission measurement system in an embodiment of the present invention;

[0027] Figure 3 Schematic diagram of typical acoustic emission signals and related AE parameters in an embodiment of the present invention;

[0028] Among them, (a) is a typical AE waveform and related parameters, (b) is the time domain diagram of the AE signal and the frequency domain diagram after FFT conversion;

[0029] Figure 4 is a schematic diagram of the frequency response of acoustic emission generated by sliding between particles in an embodiment of the present invention;

[0030] Figure 5 is a schematic diagram of the frequency response of acoustic emission generated by the crushing of a single particle in an embodiment of the present invention;

[0031] Figure 6 Schematic diagram of the evolution of the AE average event rate and the AE average energy rate with the change of soil type in an embodiment of the present invention;

[0032] Figure 7 Schematic diagram of the evolution of the AE average event rate and the AE average energy rate of sand with the increase of confining pressure in an embodiment of the present invention;

[0033] Figure 8 Schematic diagram of the main frequency response of different soil types during shear failure in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] In order to more clearly illustrate the technical problems, technical solutions and advantages to be solved by the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0035] See also Figure 1-Figure 8 The present invention provides a soil engineering classification method based on acoustic emission characteristic information, which comprises the following steps:

[0036] S1. placing the prefabricated soil sample on the base inside the triaxial loading device, and connecting the acoustic emission sensor in the acoustic emission measurement system to the outer wall of the soil sample;

[0037] S2. Control the confining pressure system and the loading system in the triaxial loading device to perform shear failure on the soil sample at a constant axial loading rate until the axial strain of the soil sample reaches 30%, and then stop the failure;

[0038] S3. Using the acoustic emission measurement system to obtain the original acoustic emission time-domain electrical signal generated by the soil sample during the shear failure process;

[0039] S4. Processing and analyzing the original acoustic emission time-domain electrical signal obtained in step 3, extracting the acoustic emission characteristic parameters peak frequency, acoustic emission event rate, and acoustic emission energy rate;

[0040] The main frequency response during the loading process is divided into low frequency, medium frequency and high frequency through the Chebyshev filter, and the AE average event rate and AE average energy rate after the test loading is completed are calculated through the acoustic emission signal processing program.

[0041] S5. Establish the AE characteristic information response difference that is different from soil type and state conditions, and classify the soil types;

[0042] The main frequency response-shear displacement curve, AE average event rate-soil type diagram, and AE average energy rate-soil type diagram were drawn. The mathematical relationships between the AE average event rate, energy rate and effective confining pressure were established through fitting analysis. The AE average event rate and AE average energy rate were normalized based on the established mathematical relationships to eliminate the influence of confining pressure on the AE average event rate and AE average energy rate.

[0043] Example 1

[0044] The soil samples tested in this embodiment are cylindrical clay, silt, and silica sand (medium sand, fine sand) samples. The samples are prepared by compaction method. The size of the cylindrical soil sample is: diameter 50mm*height 100mm, and a rubber film with a thickness of 0.3mm is wrapped on the side wall of the cylindrical soil sample.

[0045] Control the initial dry density of different types of soil samples to a certain value, such as ρ d = about 1.5;

[0046] The negative pressure method was used to place the cylindrical soil samples in a saturated state before shear failure, and three shear tests were performed on each type of sample.

[0047] Combination Figure 2 The triaxial loading device includes: a base, a permeable stone, a loading rod, a top pressure plate, a load sensor, a plexiglass cylinder, a limit device, a loading piston, an axial linear displacement sensor, a horizontal linear displacement sensor and a locking device.

[0048] The base and the top pressure plate are used as fixed pressure heads. The base and the top pressure plate are made of metal materials, but are not limited to metal materials. Those skilled in the art can make appropriate choices according to actual needs.

[0049] During the loading process, the macroscopic mechanical parameters, including the applied axial load, axial displacement, confining pressure, and volume variables, were measured by axial linear displacement sensors, pressure sensors, and low-capacity differential pressure sensors, respectively.

[0050] The acoustic emission measurement system includes: eight piezoelectric ceramic AE sensors, four amplifiers, a data recorder and a computer (PC). An aluminum plate with a size of 10mm×10mm×1mm is attached to the head of the acoustic emission sensor. The signal amplifier, high-performance data acquisition instrument and data storage device are used to process, analyze and store the collected data.

[0051] Among them, the acoustic emission sensor (model: R-cast M304A) is a piezoelectric ceramic sensor produced by Fuji Ceramics of Japan. The probe has a built-in FET preamplifier. The sensor operating frequency is 10kHz-5MHz (resonant frequency is 300kHz) and the sensitivity is 115±3dB (reference: 0dB=1V / m / s); the acoustic emission signal amplifier (model: A1201) is a signal amplifier produced by Fuji Ceramics of Japan, and its gain is 53±3dB; the data acquisition instrument (model: PXIe-6366) is produced by NI of the United States, and its maximum sampling rate is 2MS / s.

[0052] The acoustic emission signal amplifier is connected to the acoustic emission sensor to further amplify the received acoustic emission signal and improve the signal-to-noise ratio of the signal; the data acquisition instrument is connected to the acoustic emission signal amplifier to continuously record the original time domain electrical signal of the acoustic emission; the data storage device is connected to the data acquisition instrument to continuously store the original time domain point signal of the acoustic emission.

[0053] The working principle is as follows: under saturated conditions, the target confining pressure stress is applied to the specimen, and then isotropic compression consolidation is carried out for 30 minutes. After stabilization, shear failure begins. The deviatoric stress applied to the target specimen by the loading test device is obtained through a pressure sensor, and the axial strain generated when the target specimen is destroyed during loading is obtained through an external displacement sensor. The original acoustic emission time domain signal generated by the target specimen during the destruction process is obtained through a high-performance acoustic emission measurement system.

[0054] S1. Place the prefabricated clay / silt / silica sand sample on the base inside the triaxial loading device, install the sampling parts of the acoustic emission measurement system on the side wall of the sample, and wait for the shear test; the sampling parts are the acoustic emission sensor and the aluminum plate, and the aluminum plate on the acoustic emission sensor is glued to the rubber membrane on the side wall of the cylindrical sample.

[0055] S2. Control the confining pressure system and loading system of the triaxial device to shear the sample in S1; the sample is consolidated in an isotropic manner, and the confining pressure level is set to 100kPa, 200kPa, 400kPa, 800kPa, 1000kPa, and 1600kPa. During the test, the loading system of the triaxial device is controlled by an AC servo motor, and the loading rate is controlled to 1mm / min. When the axial strain of the triaxial compression test is about 30%, the loading is stopped.

[0056] S3. Obtain the deviatoric stress applied to the sample by the loading device during the whole loading process, obtain the axial strain generated by the sample during the whole loading process, and obtain the original acoustic emission time-domain electrical signal generated by the sample during the destruction process through the acoustic emission measurement system.

[0057] The deviatoric stress q can be calculated by dividing the current axial load measured by the load cell by the current cross-sectional area, which can be corrected by dividing the constant sample volume by the current sample height.

[0058] Its calculation formula is:

[0059] Where: F is the axial load; A is the cross-sectional area of ​​the specimen; V0 is the initial volume of the specimen; ΔV is the change in the volume of the specimen during the test; H0 is the initial height of the specimen; ΔH is the change in the height of the specimen during the test.

[0060] The axial strain can be calculated from the axial displacement. The axial strain is calculated by dividing the axial displacement by the original height of the specimen.

[0061] The sampling frequency of the load sensor of the loading device is set to 1S / s, the sampling frequency of the external displacement sensor is set to 1S / s, and the sampling frequency of the acoustic emission measurement system is set to 2MS / s; the original acoustic emission time domain signal collected is as follows Figure 3 As shown in the figure, the main sources of the collected acoustic emission signals are particle sliding, particle friction, particle crushing, etc. Figure 4 , Figure 5 Schematic diagrams of the acoustic emission frequency responses caused by inter-particle sliding and single particle breakage.

[0062] S4. Processing and analyzing the original acoustic emission time-domain electrical signal obtained in step 3, extracting the acoustic emission characteristic parameters peak frequency, acoustic emission event rate, and acoustic emission energy rate;

[0063] Figure 3 (a) and (b) show the typical acoustic emission signals and related AE parameters in this embodiment. In order to distinguish the signals, a threshold of 0.03V (i.e. 29.5dB, reference value 0dB = 1V / m / s) is first set based on the voltage level caused by electrical and environmental noise. Once the signal exceeds the threshold, it is identified as an AE signal and defined as an acoustic emission event (AE hit). The peak voltage of the signal is designated as the AE amplitude. In order to analyze the frequency dependence of the AE signal, a fast Fourier transform (FFT) is applied to convert the signal from the time domain to the frequency domain, and the frequency component corresponding to the peak amplitude in the spectrum is regarded as the dominant frequency. For the emission event rate R H AE Analyze and interpret, where the acoustic emission event rate refers to the sum of the number of accumulated acoustic emission events per unit time. AE energy refers to the area under the signal detection envelope, the integral of the amplitude of the AE event and its duration corresponds to the AE energy, and the AE energy rate is the sum of the AE energy per unit time.

[0064] S5. Establish the AE characteristic information response difference that is different from soil type and state conditions, and classify soil types

[0065] Draw the main frequency response diagram of different soil types during shearing, such as Figure 8As shown. The frequency bandwidth of the AE signal generated by clay during the shearing process is relatively narrow, and they are all low-frequency signals below 100kHz; the frequency bandwidth of the AE signal generated by silt during the shearing process is in the middle, and in addition to the low-frequency signals below 100kHz, a large number of medium-frequency signals (100-300kHz) appear; the frequency bandwidth of the AE signal generated by silica sand, whether it is medium sand or fine sand, during the shearing process is the widest, and in addition to the low-frequency, medium-high frequency signals, a large number of high-frequency signals (300-600kHz) appear. Based on the main frequency response results during the shearing process, the AE main frequency response of different soil types is divided into three components of low, medium and high frequencies: Among them:

[0066] The low-frequency component is an AE signal with a main frequency of 0 to 100kHz;

[0067] The intermediate frequency component is an AE signal with a main frequency of 100 to 300kHz;

[0068] The high frequency component is an AE signal with a main frequency of 300kHz to 600kHz;

[0069] Based on this, different soil types can be preliminarily divided. Plot the effective confining pressure and the average AE event rate and the average AE energy rate (taking medium sand as an example), and establish the mathematical relationship between the average AE event rate, energy rate and effective confining pressure through fitting analysis, such as Figure 7 As shown, the AE average event rate and the AE average energy rate are normalized based on the established mathematical relationship to eliminate the influence of confining pressure on the AE average event rate and the AE average energy rate.

[0070] The construction of mathematical relationship between AE average event rate, energy rate and effective confining pressure,

[0071]

[0072] Where: is the average AE event rate; is the average energy rate of AE; σ3' is the effective confining pressure; R 2 is the correlation coefficient; A, B, C, D, E are the fitting coefficients.

[0073] The AE average event rate and the AE average energy rate are normalized based on the established mathematical relationship, and the characteristic is that the ratio of the AE average event rate, the AE average energy rate and the confining pressure is linearly transformed to eliminate the influence of the confining pressure on the AE average event rate and the AE average energy rate.

[0074] Draw the relationship curve between different soil types and the average AE event rate and the average AE energy rate after normalization, such as Figure 8 shown.

[0075] The average AE event rate and average AE energy rate of clay during shearing are low, with the average AE event rate being less than 50,000 and the average AE energy rate being less than 0.4;

[0076] The AE average event rate and AE average energy rate of silt during shearing are in the middle, with the AE average event rate ranging from 50000 to 100000 and the AE average energy rate ranging from 0.4 to 0.6;

[0077] The average AE event rate and average AE energy rate generated by silica sand during shearing are higher regardless of whether it is medium sand or fine sand;

[0078] The average AE event rate of fine sand is between 100,000 and 300,000, and the average AE energy rate is between 0.6 and 1.0;

[0079] The average AE event rate of medium sand is between 300000 and 350000, and the average AE energy rate is between 1.0 and 1.4. The AE characteristic information of different soil types is quite different, and the same soil type also has different AE characteristic information at different particle sizes. Based on this, different soil types can be subdivided.

[0080] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. 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. A soil engineering classification method based on acoustic emission feature information, Features: The soil samples in this classification method are subjected to loading tests using a triaxial loading device combined with an acoustic emission measurement system. The steps for soil engineering classification based on this test are as follows: S1. Place the prefabricated soil sample on the base inside the triaxial loading device, and connect the acoustic emission sensor in the acoustic emission measurement system to the outer wall of the soil sample; S2, controlling the confining pressure system and the loading system in the triaxial loading device to perform shear failure on the soil sample at a constant axial loading rate until the axial strain of the soil sample reaches 30%, and then stopping the failure; S3, using the acoustic emission measurement system to obtain the original acoustic emission time-domain electrical signal generated by the soil sample during the shear failure process; S4, processing and analyzing the original acoustic emission time-domain electrical signal obtained in step S3, and extracting acoustic emission characteristic parameters from the original acoustic emission time-domain electrical signal; The acoustic emission characteristic parameters are: peak frequency, acoustic emission event rate, and acoustic emission energy rate; S5. The main frequency response of the triaxial loading device during loading is divided into low frequency, medium frequency and high frequency through Chebyshev filter; and the low frequency, medium frequency and high frequency information of acoustic emission event rate and acoustic emission energy rate are extracted; based on the characteristic information response differences of AE average event rate and AE average energy rate, the soil types are divided.

2. The soil engineering classification method based on acoustic emission characteristic information according to claim 1, It is characterized in that In step S2, the target confining stress is applied to the soil sample under saturated conditions, and isotropic compression consolidation is carried out for 30 minutes. Shear failure begins after the consolidation drainage volume stabilizes.

3. The soil engineering classification method based on acoustic emission characteristic information according to claim 1, Features: The division of the three components of low frequency, medium frequency and high frequency in step S4 is as follows: The low-frequency component has a main frequency of 0kHz to 100kHz; The intermediate frequency component is mainly between 100kHz and 300kHz; The high frequency component has a main frequency of 300kHz to 600kHz.

4. The soil engineering classification method based on acoustic emission characteristic information according to claim 1, Features: In the step S5, a main frequency response-shear displacement curve, an acoustic emission average event rate-soil type diagram, and an acoustic emission average energy rate-soil type diagram are drawn; mathematical relationships between the AE average event rate, energy rate, and effective confining pressure are established through fitting analysis, and the AE average event rate and AE average energy rate are normalized based on the established mathematical relationships to eliminate the influence of confining pressure on the AE average event rate and AE average energy rate; The mathematical relationship between the average AE event rate, the average AE energy rate and the effective confining pressure is constructed as follows: Average AE event rate: AE average energy rate: Where: is the average AE event rate; is the average energy rate of AE; σ 3 ' is the effective confining pressure; R 2 is the correlation coefficient; A, B, C, D, E are the fitting coefficients.

5. The soil engineering classification method based on acoustic emission characteristic information according to claim 4, Features: The average AE event rate of clay during shearing is less than 50,000, and the average AE energy rate is less than 0.4; The average AE event rate of silt during shearing is between 50,000 and 100,000, and the average AE energy rate is between 0.4 and 0.6; The average AE event rate of fine sand is between 100,000 and 300,000, and the average AE energy rate is between 0.6 and 1.

0. The average AE event rate in Zhongsha is between 300,000 and 350,000, and the average AE energy rate is between 1.0 and 1.4.

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