Rock mechanics test acoustic emission signal collection device and positioning method

Abstract

The application discloses a kind of rock mechanics test in the collection device of acoustic emission signal, including computer, measurement and control and signal processing equipment, distributed acoustic wave sensing equipment and collection probe: the collection probe is composed of single-mode optical fiber and probe skeleton, single-mode optical fiber is fixed around probe skeleton, when testing, collection probe is fixed on the surface of rock sample for testing;The measurement and control and signal processing equipment include: radio frequency amplifier, digital-to-analog conversion module, analog-to-digital conversion module, filter amplifier, field programmable logic gate array and CPU-GPU data processing module;The distributed acoustic sensing equipment includes narrow linewidth laser, fiber coupler, acoustooptic modulator, erbium-doped fiber amplifier, circulator, polarization diversity receiver, first balanced photodetector and second balanced photodetector;Collection signal band is wide, can be conveniently installed on any rock sample.Collecting main frequency is lower, collection probe is connected closely with rock sample, coupling is good, without additional smearing coupling agent.

Description

Technical Field

[0001] This invention belongs to the field of rock mechanics testing technology, specifically relating to a device for acquiring acoustic emission signals and a positioning method for rock mechanics testing. Background Technology

[0002] Research on mine dynamic disaster prediction requires not only extensive and in-depth observation and research on a large number of disaster phenomena, but also laboratory simulation of the mechanical state of rocks under artificial disturbance and high pressure in the construction and production environment of mines. This research studies the various physical and mechanical properties of rocks and the evolution law of dynamic disasters, and compares this data with actual data observed at the disaster site in order to understand the evolution process of mine dynamic disasters and explore the causes and precursors of mine dynamic disasters.

[0003] Rock mechanics is a discipline that studies the mechanical properties of rocks and their changes under various environmental conditions. In recent years, with the increasing depth of mining, the connection between rock mechanics and mine dynamic disaster prediction research has become increasingly close, making it an important direction in mine dynamic disaster prediction research. Mine construction and production both hope that rock mechanics can solve the problems of stability monitoring and instability prediction. To study the stability of rocks or rock masses, researchers have conducted numerous experiments on the physical and mechanical properties of rocks in laboratories and in the field to understand the changes in their physical and mechanical properties before rock failure. Because sound emission propagates quickly, is less affected by external interference, is easy to propagate and receive, and can directly reflect changes in rock structure, it is widely used in observing and analyzing rock stability.

[0004] When a rock is subjected to stress and deformation, stress concentration and higher strain energy occur around existing or newly formed cracks. When the external force increases to a certain level, the rock undergoes microscopic yielding or deformation in the cracked defect area, causing the cracks to propagate. This leads to stress relaxation, and a portion of the stored energy is released in the form of elastic waves. This is the phenomenon of acoustic emission, also known as elastic wave emission. Acoustic emission technology is an experimental method that uses the sound emitted by rocks to investigate their internal state and mechanical properties. By observing and analyzing the sounds emitted by rocks, we can understand their internal state and mechanical properties, allowing us to understand the current state, formation history, and development trend of rock defects.

[0005] The frequencies of acoustic emission in rock mechanics range from the 20 Hz to 20 kHz frequencies audible to the human ear, as well as ultrasonic and infrasound waves. Generally, the larger the object under study, the lower the main measurable frequencies of rock acoustic emission. For example, the acoustic emission frequency of natural earthquakes can be as low as 0.01 Hz, while the acoustic emission frequencies of standard rock samples (Φ50×100mm) in the laboratory are mainly concentrated in the tens to hundreds of kHz.

[0006] With the continuous development of laboratory experimental equipment, larger-sized rock samples and similar material rock samples are increasingly being used to study the changes in the physical and mechanical properties of rocks before failure, and thus to study the evolution of dynamic disasters in mines. Compared with standard rock samples, the measurable dominant frequency of acoustic emission from larger-sized rock samples and similar material rock samples is lower, and the frequency band is wider.

[0007] However, current sensors for acquiring acoustic emission signals from rocks generally use piezoelectric transducers, which have very high output impedance and output voltage signals ranging from tens of microvolts to several millivolts. Therefore, a preamplifier with high input impedance and low noise is required. To avoid various interferences, the signal amplified by the preamplifier first needs to pass through a narrowband filter before being amplified again and sent to the data acquisition and display system. The entire acquisition device has a relatively narrow bandwidth, typically between 5kHz and 300kHz for smaller samples. This cannot meet the requirements for acquiring and locating acoustic emission signals from larger rock samples and similar materials in the laboratory. The main shortcomings of existing acoustic emission acquisition devices used in rock mechanics for large rock samples and similar materials are:

[0008] (1) The existing acoustic emission signal acquisition signal has a narrow bandwidth; the test frequency is too high. In the acoustic emission test of larger rock samples and similar material rock samples, only some higher frequency acoustic emission signals can be acquired, and the lower frequency acoustic emission signals are severely lost.

[0009] (2) The installation remains unchanged. The contact surface between the probe and the rock of the existing rock acoustic emission acquisition device is generally a plane or a fixed curved surface designed specifically for standard rock samples, and there are strict requirements on the diameter of the rock sample cylinder.

[0010] (3) High coupling requirements: When testing the probe of the existing rock acoustic emission acquisition device, sufficient petroleum jelly or honey coupling agent must be applied to couple the acoustic emission of the rock sample to the probe, which brings inconvenience to the test. Summary of the Invention

[0011] To address the technical problems of acoustic emission signal acquisition and localization in existing acoustic emission systems for mechanical experiments on larger rock samples or similar simulated material rock samples, the present invention aims to provide an acoustic emission signal acquisition device and method for rock mechanics experiments on larger rock samples or similar simulated material rock samples.

[0012] To achieve the above objectives, the present invention employs the following technical solution:

[0013] A device for acquiring acoustic emission signals in rock mechanics experiments includes a computer, a measurement and control and signal processing device, a distributed acoustic wave sensing device, and an acquisition probe. The computer and the measurement and control and signal processing device are connected via a network cable; the measurement and control and signal processing device and the distributed acoustic wave sensing device are connected via three coaxial cables; and the distributed acoustic wave sensing device is connected to the acquisition probe via a PC / APC fiber optic connector.

[0014] The acquisition probe consists of a single-mode optical fiber and a probe frame. The single-mode optical fiber is fixed around the probe frame. During testing, the acquisition probe is fixed on the surface of the test rock sample.

[0015] The measurement, control, and signal processing equipment includes: a radio frequency amplifier, a digital-to-analog converter module, an analog-to-digital converter module, a filter amplifier, a field-programmable gate array (FPGA), and a CPU-GPU data processing module. The CPU-GPU data processing module is connected to both the computer and the FPGA. The output of the FPGA is connected to the radio frequency amplifier via the digital-to-analog converter module. The input of the FPGA is connected to the filter amplifier via the analog-to-digital converter module.

[0016] The distributed acoustic sensing device includes a narrow-linewidth laser, an optical fiber coupler, an acousto-optic modulator, an erbium-doped fiber amplifier, a circulator, a polarization diversity receiver, a first balanced photodetector, and a second balanced photodetector. The output of the narrow-linewidth laser is connected to the input of the optical fiber coupler. The first output of the optical fiber coupler is connected to the first input of the polarization diversity receiver. The second output of the optical fiber coupler is connected to the acousto-optic modulator, which is connected to the circulator via the erbium-doped fiber amplifier. The circulator is connected to the single-mode optical fibers of the polarization diversity receiver and the acquisition probe. The output of the polarization diversity receiver is connected to the filter amplifier of the measurement and control and signal processing equipment via the first and second balanced photodetectors. The acousto-optic modulator is connected to the radio frequency amplifier of the measurement and control and signal processing equipment.

[0017] The method for locating the acoustic emission signal acquisition device in the above-mentioned rock mechanics test is characterized by comprising the following steps:

[0018] Step 1: Fix the acquisition probe to the surface of the rock sample and connect it to the acoustic emission signal acquisition device in the rock mechanics test;

[0019] Step two: Stress or hydraulic loading is applied to the rock sample, and acoustic emission signals are acquired simultaneously;

[0020] A narrow-linewidth laser emits light waves, which are coupled to generate coupled light waves via an optical fiber coupler. A portion of the coupled light waves is then transmitted to a polarization diversity receiver.

[0021] The other part of the coupled light wave is transmitted to the acousto-optic modulator; the field-programmable logic gate array emits a sweep pulse sequence, which is converted into a sweep continuous wave by a digital-to-analog converter module, and the sweep continuous wave is converted into an amplified sweep continuous wave by an RF amplifier, and the amplified sweep continuous wave is transmitted to the acousto-optic modulator.

[0022] The other part of the coupled light wave is modulated into a linear sweep light pulse in the acousto-optic modulator. The linear sweep light pulse is enhanced in optical power by an erbium-doped fiber amplifier and then injected into the single-mode fiber of the acquisition probe through a circulator. The backscattered Rayleigh signal generated after the enhanced linear sweep light pulse is transmitted in the single-mode fiber of the acquisition probe is transmitted to the polarization diversity receiver through the circulator.

[0023] A portion of the coupled light wave and the backscattered Rayleigh signal beat in the polarization diversity receiver to generate an optical signal; the optical signal is converted into a current signal by the first balanced photodetector and the second balanced photodetector; the current signal is converted into a digital signal by the filter amplifier and the analog-to-digital converter module; the digital signal contains acoustic emission information emitted by the rock sample during the rock sample loading process.

[0024] Step 3: Obtain differential phase information

[0025] The field-programmable gate array (FPGA) performs digital pulse compression on the digital signal obtained in step two to obtain a Rayleigh scattering digital signal; the FPGA then performs noise reduction processing on the Rayleigh scattering digital signal, and the GPU-CPU data processing module performs phase space difference operation on the noise-reduced Rayleigh scattering digital signal to obtain differential phase information.

[0026] Step four: After filtering and amplifying the obtained differential phase information, the required differential phase information is obtained.

[0027] Step 5: Obtain multiple differential phase information

[0028] Repeat steps two through four until the rock sample mechanical test is completed, and obtain multiple differential phase information; the digital signal contains acoustic emission information emitted by the rock sample during the rock sample loading process;

[0029] Step 6: Select acoustic emission signals with high similarity based on DTW distance clustering analysis.

[0030] Based on the properties and size of the rock samples, the GPU-CPU data processing module performs cluster analysis based on DTW distance on the multiple differential phase information obtained in step five, and selects acoustic emission signals with high similarity.

[0031] (1) Data normalization:

[0032] x n (t)=x(t) / mat(x(t)) (1)

[0033] Where mat(x(t)) is the maximum value of x(t);

[0034] (2) Dynamic time warping

[0035] To obtain the dynamic time-warped distance between two sequences, a distance matrix is ​​constructed:

[0036] d(x i ,y i )=(x i ,y i ) 2 (2)

[0037] Find a path through the matrix that minimizes the cumulative distance between time series:

[0038]

[0039] Among them, w k It is the k-th element of the normalized path matrix;

[0040] The regularized path is subject to the following constraints:

[0041] Boundary conditions: w1 = (1,1), w k = (m,n); the path must start from point (1,1) and end at the last point of both sequences;

[0042] Continuity: when w k = (a, b) and w k-1 =(a',b'), there are a-a'≤1, b-b'≤1;

[0043] Monotonicity: when w k = (a, b) and w k-1 =(a',b'), there are a-a'≤0, b-b'≤0;

[0044] Based on the above constraints, a regular path can be found by applying the following recursive property:

[0045] γ(i,j)=d(x i ,y j )+min(γ(i-1,j-1)),γ(i-1,j),γ(i,j-1)) (4)

[0046] In the formula, d(x) i ,y j ) represents the distance to the current cell, γ(x)i ,y j ) is d(x i ,y j The distance between γ(x) and the minimum cumulative distance between three adjacent units; i ,y j Signals with smaller distance values ​​indicate higher similarity and are more likely to originate from the same acoustic emission source.

[0047] (3) Similarity analysis of acoustic emission signals

[0048] Based on the dynamic regularization distance γ(x) i ,y j The similarity of acoustic emission signals is analyzed by the shortest distance method in hierarchical clustering. Signals with higher similarity are more likely to come from the same acoustic emission source.

[0049] Step 8: Use a direct localization algorithm to locate the acoustic emission source from similar signals.

[0050] The acoustic emission start time can be accurately selected from similar signals, so there is no need for iteration and optimization. The Inglada localization algorithm is used to directly locate the acoustic emission source.

[0051] Step nine: Analyze the rock fracture evolution process using acoustic emission localization technology.

[0052] According to the present invention, in step two, the sampling frequency of the ADC in the field-programmable gate array is set to 4 to 200 kHz based on the size and wave velocity parameters of the rock sample and similar materials.

[0053] The acoustic emission signal acquisition device and positioning method for rock mechanics experiments of the present invention have the following beneficial technical effects compared with the prior art:

[0054] (1) The acquisition signal bandwidth is wide and the main frequency can be wider and lower than that of traditional magnetic compression probes, making it more suitable for the acquisition of acoustic emission signals in rock mechanics experiments of large-sized rock samples or similar material rock samples.

[0055] (2) The test probe can be installed on any rock sample, making installation convenient.

[0056] (3) The acquisition frequency can be lower, and the acquisition probe is tightly connected to the rock sample with good coupling. No additional coupling agent is needed when acquiring signals. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the overall structure of the acoustic emission signal acquisition device in the rock mechanics test of the present invention.

[0058] Figure 2This is a schematic diagram illustrating the signal transmission relationship between measurement and control equipment and distributed acoustic wave sensing equipment.

[0059] Figure 3 This is a schematic diagram of the probe skeleton structure.

[0060] The markings in the diagram represent: 1. Computer, 2. Measurement and control and signal processing equipment, 3. Distributed acoustic wave sensing equipment, 4. Acquisition probe, 5. Single-mode optical fiber, 6. Experimental chamber, 7. Rock sample;

[0061] 21. RF amplifier; 22. Digital-to-analog converter module; 23. Analog-to-digital converter module; 24. Filter amplifier; 25. Field-programmable gate array; 26. CPU-GPU data processing module.

[0062] 31. Narrow linewidth laser; 32. Fiber optic coupler; 33. Acousto-optic modulator; 34. Erbium-doped fiber amplifier; 35. Circulator; 36. Polarization diversity receiver; 37. First balanced photodetector; 38. Second balanced photodetector.

[0063] 41. Probe mounting hole; 42. Other sensor through holes; 43. Probe frame;

[0064] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Detailed Implementation

[0065] See Figures 1 to 3 This embodiment provides a device for acquiring acoustic emission signals in rock mechanics experiments, including a computer 1, a measurement and control and signal processing device 2, a distributed acoustic wave sensing device 3, and an acquisition probe 4. The computer 1 is connected to the measurement and control and signal processing device 2 via a network cable. The measurement and control and signal processing device 2 is connected to the distributed acoustic wave sensing device 3 via three coaxial cables. The distributed acoustic wave sensing device 3 is connected to the acquisition probe 4 via a PC / APC fiber optic connector.

[0066] The acquisition probe 4 consists of a single-mode optical fiber 5 and a probe frame 42. The single-mode optical fiber 5 is fixed around the probe frame 42. The probe frame 42 also has a probe fixing hole 41 and other sensor through holes 42. Figure 3 During the test, the acquisition probe 4 is fixed to the surface of the test rock sample 7;

[0067] The measurement, control, and signal processing equipment 2 includes: a radio frequency amplifier 21, a digital-to-analog converter module 22, an analog-to-digital converter module 23, a filter amplifier 24, a field-programmable gate array (FPGA) 25, and a CPU-GPU data processing module 26. The CPU-GPU data processing module 26 is connected to both the computer 1 and the FPGA 25. The output of the FPGA 25 is connected to the radio frequency amplifier 21 via the digital-to-analog converter module 22. The input of the FPGA 25 is connected to the filter amplifier 24 via the analog-to-digital converter module 23.

[0068] The distributed acoustic sensing device 3 includes: a narrow-linewidth laser 31, an optical fiber coupler 32, an acousto-optic modulator 33, an erbium-doped fiber amplifier 34, a circulator 35, a polarization diversity receiver 36, a first balanced photodetector 37, and a second balanced photodetector 38; wherein, the output end of the narrow-linewidth laser 31 is connected to the input end of the optical fiber coupler 32; the first output end of the optical fiber coupler 32 is connected to the first input end of the polarization diversity receiver 36; the second output end of the optical fiber coupler 32 is connected to the acousto-optic modulator 33, the acousto-optic modulator 33 is connected to the circulator 35 through the erbium-doped fiber amplifier 34, and the circulator 35 is connected to the polarization diversity receiver 36 and the single-mode fiber 5 of the acquisition probe 4 respectively; the output end of the polarization diversity receiver 36 is connected to the filter amplifier 24 of the measurement and control and signal processing device 2 through the first balanced photodetector 37 and the second balanced photodetector 38 respectively; the acousto-optic modulator 33 is connected to the radio frequency amplifier 21 of the measurement and control and signal processing device 2.

[0069] The positioning method using the acoustic emission signal acquisition device in the above-mentioned rock mechanics test specifically includes the following steps:

[0070] Step 1: Fix the acquisition probe 4 on the surface of the rock sample and connect it to the acoustic emission signal acquisition device in the rock mechanics test;

[0071] Step 2: Apply stress or hydraulic loading to rock sample 7 according to the rock mechanics test loading scheme designed in the experiment, and acquire acoustic emission signals at the same time;

[0072] In step one, the narrow linewidth laser 31 emits light waves, which are coupled to generate coupled light waves via an optical fiber coupler. A portion of the coupled light waves are transmitted to the polarization diversity receiver 36.

[0073] The other part of the coupled light wave is transmitted to the acousto-optic modulator 33; a sweep pulse sequence is emitted by the field-programmable logic gate array 25, the sweep pulse sequence is converted into a sweep continuous wave by the digital-to-analog conversion module 22, the sweep continuous wave is converted into an amplified sweep continuous wave by the radio frequency amplifier 21, and the amplified sweep continuous wave is transmitted to the acousto-optic modulator 33.

[0074] The other part of the coupled light wave is modulated into a linear sweep frequency optical pulse in the acousto-optic modulator 33. The linear sweep frequency optical pulse is enhanced in optical power by the erbium-doped fiber amplifier 34 and then injected into the single-mode fiber 5 of the acquisition probe 4 through the circulator 35. The backscattered Rayleigh signal generated after the enhanced linear sweep frequency optical pulse is transmitted in the single-mode fiber 5 of the acquisition probe 4 is transmitted to the polarization diversity receiver 36 via the circulator 35.

[0075] The coupled light wave and the back Rayleigh scattering signal beat in the polarization diversity receiver 36 to generate an optical signal; the optical signal is converted into a current signal by the first balanced photodetector 37 and the second balanced photodetector 38; the current signal is converted into a digital signal by the filter amplifier 24 and the analog-to-digital conversion module 23; the digital signal contains acoustic emission information emitted by the rock sample during the rock sample loading process.

[0076] Step 3: Obtain differential phase information;

[0077] The field-programmable gate array 25 performs digital pulse compression on the digital signal obtained in step two to obtain a Rayleigh scattering digital signal; the field-programmable gate array 25 performs noise reduction processing on the Rayleigh scattering digital signal, and then the GPU-CPU data processing module 26 performs phase space difference operation on the noise-reduced Rayleigh scattering digital signal to obtain differential phase information.

[0078] Step four: After the obtained differential phase information is filtered and amplified by filter amplifier 24, the required differential phase information is obtained.

[0079] Step 5: Obtain multiple differential phase information

[0080] Repeat steps two through four until the rock sample mechanical test is completed, and obtain multiple differential phase information; the digital signal contains acoustic emission information emitted by the rock sample during the rock sample loading process;

[0081] Step 6: Select acoustic emission signals with high similarity based on DTW distance clustering analysis.

[0082] Based on the properties and size of the rock samples, the GPU-CPU data processing module 26 performs cluster analysis based on DTW distance on the multiple differential phase information obtained in step five, and selects acoustic emission signals with high similarity.

[0083] (1) Data normalization:

[0084] x n (t)=x(t) / mat(x(t)) (1)

[0085] Where mat(x(t)) is the maximum value of x(t);

[0086] (2) Dynamic time warping

[0087] To obtain the dynamic time-warped distance between two sequences, a distance matrix is ​​constructed:

[0088] d(x i ,y i )=(x i ,y i ) 2 (2)

[0089] Find a path through the matrix that minimizes the cumulative distance between time series:

[0090]

[0091] Among them, w k It is the k-th element of the regularized path matrix.

[0092] The regularized path is subject to the following constraints:

[0093] Boundary conditions: w1 = (1,1), w k = (m,n); the path must start from point (1,1) and end at the last point of both sequences;

[0094] Continuity: when w k = (a, b) and w k-1 =(a',b'), there are a-a'≤1, b-b'≤1;

[0095] Monotonicity: when w k = (a, b) and w k-1 =(a',b'), there are a-a'≤0, b-b'≤0.

[0096] Based on the above constraints, a regular path can be found by applying the following recursive property:

[0097] γ(i,j)=d(x i ,y j )+min(γ(i-1,j-1)),γ(i-1,j),γ(i,j-1)) (4)

[0098] In the formula, d(x) i ,y j ) represents the distance to the current cell, γ(x) i ,y j ) is d(x i ,y j The distance of γ(x) to the minimum cumulative distance between three adjacent units.i ,y j Signals with smaller distance values ​​indicate higher similarity and are more likely to come from the same acoustic emission source.

[0099] (3) Similarity analysis of acoustic emission signals

[0100] Based on the dynamic regularization distance γ(x) i ,y j The similarity of acoustic emission signals is analyzed by the shortest distance method in hierarchical clustering. Signals with higher similarity are more likely to come from the same acoustic emission source.

[0101] Step 8: Use a direct localization algorithm to locate the acoustic emission source from similar signals.

[0102] The acoustic emission start time can be accurately selected from similar signals, so there is no need for iteration and optimization. This scheme uses the Inglada localization algorithm to directly locate the acoustic emission source. This method has no divergence problem and is high-speed and reliable.

[0103] Step nine: Analyze the rock fracture evolution process using acoustic emission localization technology;

[0104] In this embodiment, in step two, the sampling frequency of the ADC in the field-programmable gate array is set to 4-200KHz based on parameters such as the size and wave velocity of the rock sample and similar materials.

[0105] The acoustic emission signal acquisition device and positioning method for rock mechanics experiments given in this embodiment have the following beneficial technical effects:

[0106] (1) The acquisition signal bandwidth is wide and the main frequency can be lower than that of traditional magnetic compression probes, making it more suitable for the acquisition of acoustic emission signals in rock mechanics experiments of large-sized rock samples or similar material rock samples.

[0107] (2) The test probe can be installed on any rock sample, making installation convenient.

[0108] (3) The acquisition frequency can be lower, and the acquisition probe is tightly connected to the rock sample with good coupling. No additional coupling agent is needed when acquiring signals.

Claims

1. A device for acquiring acoustic emission signals in rock mechanics experiments, comprising a computer (1), measurement and control and signal processing equipment (2), distributed acoustic wave sensing equipment (3), and acquisition probes (4), characterized in that, The computer (1) is connected to the measurement and control and signal processing equipment (2) via a network cable. The measurement and control and signal processing equipment (2) is connected to the distributed acoustic wave sensing device (3) via three coaxial cables. The distributed acoustic wave sensing device (3) is connected to a data acquisition probe (4) via a PC / APC fiber optic connector. The acquisition probe (4) consists of a single-mode optical fiber (5) and a probe frame (42). The single-mode optical fiber (5) is fixed around the probe frame (42). During the test, the acquisition probe (4) is fixed on the surface of the test rock sample (7). The measurement and control and signal processing equipment (2) includes: a radio frequency amplifier (21), a digital-to-analog conversion module (22), an analog-to-digital conversion module (23), a filter amplifier (24), a field-programmable gate array (25), and a CPU-GPU data processing module (26); wherein, the CPU-GPU data processing module (26) is connected to the computer (1) and the field-programmable gate array (25) respectively, the output of the field-programmable gate array (25) is connected to the radio frequency amplifier (21) through the digital-to-analog conversion module (22), and the input of the field-programmable gate array (25) is connected to the filter amplifier (24) through the analog-to-digital conversion module (23); The distributed acoustic sensing device (3) includes a narrow-linewidth laser (31), an optical fiber coupler (32), an acousto-optic modulator (33), an erbium-doped fiber amplifier (34), a circulator (35), a polarization diversity receiver (36), a first balanced photodetector (37), and a second balanced photodetector (38); wherein, the output end of the narrow-linewidth laser (31) is connected to the input end of the optical fiber coupler (32); the first output end of the optical fiber coupler (32) is connected to the first input end of the polarization diversity receiver (36); the second output end of the optical fiber coupler (32) is connected to the first input end of the polarization diversity receiver (36); The output end is connected to the acousto-optic modulator (33), which is connected to the circulator (35) through the erbium-doped fiber amplifier (34). The circulator (35) is connected to the polarization diversity receiver (36) and the single-mode fiber (5) of the acquisition probe (4), respectively. The output end of the polarization diversity receiver (36) is connected to the filter amplifier (24) of the measurement and control and signal processing equipment (2) through the first balanced photodetector (37) and the second balanced photodetector (38), respectively. The acousto-optic modulator (33) is connected to the radio frequency amplifier (21) of the measurement and control and signal processing equipment (2).

2. The positioning method of the acoustic emission signal acquisition device in rock mechanics testing as described in claim 1, characterized in that, Specifically, the steps include the following: Step 1: Fix the acquisition probe to the surface of the rock sample and connect it to the acoustic emission signal acquisition device in the rock mechanics test; Step two: Stress or hydraulic loading is applied to the rock sample, and acoustic emission signals are acquired simultaneously; A narrow-linewidth laser emits light waves, which are coupled to generate coupled light waves via an optical fiber coupler. A portion of the coupled light waves is then transmitted to a polarization diversity receiver. The other part of the coupled light wave is transmitted to the acousto-optic modulator; A field-programmable gate array emits a sweep pulse sequence, which is converted into a sweep continuous wave by a digital-to-analog converter module. The sweep continuous wave is then converted into an amplified sweep continuous wave by an RF amplifier and transmitted to an acousto-optic modulator. The other part of the coupled light wave is modulated into a linear sweep light pulse in the acousto-optic modulator. The linear sweep light pulse is enhanced in optical power by an erbium-doped fiber amplifier and then injected into the single-mode fiber of the acquisition probe through a circulator. The backscattered Rayleigh signal generated after the enhanced linear sweep light pulse is transmitted in the single-mode fiber of the acquisition probe is transmitted to the polarization diversity receiver through the circulator. A portion of the coupled light wave and the backscattered Rayleigh signal beat in the polarization diversity receiver to generate an optical signal; the optical signal is converted into a current signal by the first balanced photodetector and the second balanced photodetector; the current signal is converted into a digital signal by the filter amplifier and the analog-to-digital converter module; the digital signal contains acoustic emission information emitted by the rock sample during the rock sample loading process. Step 3: Obtain differential phase information The field-programmable gate array (FPGA) performs digital pulse compression on the digital signal obtained in step two to obtain a Rayleigh scattering digital signal; the FPGA then performs noise reduction processing on the Rayleigh scattering digital signal, and the GPU-CPU data processing module performs phase space difference operation on the noise-reduced Rayleigh scattering digital signal to obtain differential phase information. Step four: After filtering and amplifying the obtained differential phase information, the required differential phase information is obtained. Step 5: Obtain multiple differential phase information Repeat steps two through four until the rock sample mechanical test is completed, and obtain multiple differential phase information; the digital signal contains acoustic emission information emitted by the rock sample during the rock sample loading process; Step 6: Select acoustic emission signals with high similarity based on DTW distance clustering analysis. Based on the properties and size of the rock samples, the GPU-CPU data processing module performs cluster analysis based on DTW distance on the multiple differential phase information obtained in step five, and selects acoustic emission signals with high similarity. (1) Data normalization: x n (t)=x(t) / mat(x(t)) (1) Where mat(x(t)) is the maximum value of x(t); (2) Dynamic time warping To obtain the dynamic time-warped distance between two sequences, a distance matrix is ​​constructed: d(x i ,y i )=(x i ,y i ) 2 (2) Find a path through the matrix that minimizes the cumulative distance between time series: Among them, w k It is the k-th element of the normalized path matrix; The regularized path is subject to the following constraints: Boundary conditions: w1 = (1,1), w k = (m,n); the path must start from point (1,1) and end at the last point of both sequences; Continuity: when w k = (a, b) and w k-1 =(a',b'), there are a-a'≤1, b-b'≤1; Monotonicity: when w k = (a, b) and w k-1 =(a',b'), there are a-a'≤0, b-b'≤0; Based on the above constraints, a regular path can be found by applying the following recursive property: γ(i,j)=d(x i ,y j )+min(γ(i-1,j-1)),γ(i-1,j),γ(i,j-1)) (4) In the formula, d(x) i ,y j ) represents the distance to the current cell, γ(x) i ,y j ) is d(x i ,y j The distance between γ(x) and the minimum cumulative distance between three adjacent units; i ,y j Signals with smaller distance values ​​indicate higher similarity and are more likely to originate from the same acoustic emission source. (3) Similarity analysis of acoustic emission signals Based on the dynamic regularization distance γ(x) i ,y j The similarity of acoustic emission signals is analyzed by the shortest distance method in hierarchical clustering. Signals with higher similarity are more likely to come from the same acoustic emission source. Step 8: Use a direct localization algorithm to locate the acoustic emission source from similar signals. The acoustic emission start time can be accurately selected from similar signals, so there is no need for iteration and optimization. The Inglada localization algorithm is used to directly locate the acoustic emission source. Step nine: Analyze the rock fracture evolution process using acoustic emission localization technology.

3. The method as described in claim 2, characterized in that, In step two, based on the size and wave velocity parameters of the rock sample and similar materials, the sampling frequency of the ADC in the field-editable gate array is set to 4–200 kHz.

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