Ultrasonic spatial array sensing method for rockburst initiation process in large 3D physical model

Abstract

A large-scale three-dimensional physical model rockburst incubation process ultrasonic spatial array sensing method, belonging to active detection, is based on true triaxial stress and ultrasonic correlation characteristics to identify rock damage and invert stress field changes. It mainly uses the principle that ultrasonic waves will reflect when encountering fractures and slip interfaces with different acoustic impedances when propagating inside the object being measured. It is equivalent to the inverse process of the traditional microseismic method. The position of the excitation point is known, and the relative position of the excitation point to any array point in space is known. The wave velocity is determined according to the ultrasonic propagation time, and the degree of stress concentration in the potential rockburst area can be effectively sensed. The ultrasonic spatial array is a combination of piezoelectric ceramic crystals of ultrasonic probes, which are distributed and arranged in a spatial array, and then each piezoelectric chip is excited one by one according to a predetermined delay time, so that the ultrasonic waves emitted by all piezoelectric chips form an overall wavefront, and the wavefront shape and direction are controlled to achieve ultrasonic beam scanning, deflection and focusing.

Description

Technical Field

[0001] The invention belongs to the technical field of rock mechanics experiments, and in particular relates to an ultrasonic spatial array sensing method for a rockburst incubation process of a large three-dimensional physical model. Background Art

[0002] With the increasing demand for deep-earth resources, energy and deep infrastructure, underground projects in the fields of hydraulic engineering, mining, roads, railways, etc. are all developing in depth. In addition, the high-altitude stress environment has brought many deep engineering disasters, among which rock burst hazards are the most prominent.

[0003] Rockburst is a phenomenon in which the elastic deformation potential accumulated in the rock mass under high stress conditions is suddenly and violently released, causing the rock to burst and eject. Under the action of strong dynamic disturbance, the frequency and intensity of dynamic disasters in the surrounding rock of deep underground caverns have increased significantly. Rockburst and dynamic instability of surrounding rock are major safety hazards in deep underground engineering construction, and have become a key disaster problem restricting the safety of deep engineering construction.

[0004] In order to deeply study the rockburst failure characteristics of deeply buried high-altitude stress tunnels and better solve the problem of surrounding rock stability during underground engineering construction, large-scale three-dimensional physical simulation test technology for the entire process of multi-type rockburst incubation in deep engineering is an extremely important research method.

[0005] At present, for the characteristic perception of rockburst in deep engineering, microseismic monitoring technology is mainly used on site, and acoustic emission monitoring is mainly used for indoor rock compression tests. Although the research based on microseismic monitoring, analysis and early warning has promoted the progress of dynamic control methods for deep rock engineering, due to the low repeatability of rockburst, rockburst monitoring and field investigation research are mostly a posteriori analysis, and the data acquisition capability and resolution of the whole process of multi-type rockburst incubation are limited. Acoustic emission is a phenomenon in which local sources in rocks release energy rapidly to produce transient elastic waves. Piezoelectric ceramic sensors with different spectral characteristics are used to receive such signals. Due to their signal spectral characteristics, they are mostly suitable for monitoring the fracture signals of rock specimens. Therefore, the existing monitoring methods of rock fracture signals are mostly passive monitoring, that is, the fracture signal must first appear inside the rock before the acoustic information can be obtained. It is usually impossible to actively obtain the spatial and temporal changes of high-energy-density rock mass under the action of complex load-induced stress concentration, and this change process is precisely the basis of the rockburst incubation mechanism. Summary of the invention

[0006] In view of the problems existing in the prior art, the present invention provides a large-scale three-dimensional physical model rock burst incubation process ultrasonic spatial array sensing method, which belongs to active detection. The method is based on the true triaxial stress and ultrasonic correlation characteristics to identify rock damage and invert stress field changes. It mainly utilizes the principle that when ultrasonic waves propagate inside the measured object, they will reflect when encountering ruptures and slip interfaces with different acoustic impedances. It is equivalent to the inverse process of the traditional microseismic method. The position of the excitation point is known, and the relative position from the excitation point to any array point in space is known. Therefore, the wave velocity is determined according to the ultrasonic propagation time, and the degree of stress concentration in the potential rock burst area can be effectively sensed. The ultrasonic spatial array is a combination of piezoelectric ceramic crystals of ultrasonic probes. Multiple piezoelectric chips are distributed and arranged according to a set rule, and then each piezoelectric chip is excited one by one according to a predetermined delay time, so that the ultrasonic waves emitted by all chips form an overall wavefront, which can effectively control the shape and direction of the emitted ultrasonic beam (wavefront), thereby realizing the beam scanning, deflection and focusing of the ultrasonic wave.

[0007] In order to achieve the above object, the present invention adopts the following technical solution: a large-scale three-dimensional physical model rockburst incubation process ultrasonic spatial array sensing method, comprising the following steps:

[0008] Step 1: preparing a large-scale three-dimensional physical model specimen, during which a plurality of piezoelectric chips are pre-embedded, and the plurality of piezoelectric chips are distributed and arranged in a spatial array;

[0009] Step 2: Select a piezoelectric chip from the spatial array, send an ultrasonic excitation signal to the piezoelectric chip, and the piezoelectric chip sends ultrasonic waves to the surface of the large three-dimensional physical model sample, and the remaining piezoelectric chips in the spatial array are used to receive ultrasonic echo signals;

[0010] Step 3: Select another piezoelectric chip from the spatial array, send an ultrasonic excitation signal to the piezoelectric chip, and the piezoelectric chip transmits ultrasonic waves to the surface of the large three-dimensional physical model sample. The remaining piezoelectric chips in the spatial array are used to receive ultrasonic echo signals; and so on, until all the piezoelectric chips in the spatial array complete an ultrasonic transmission process;

[0011] Step 4: Conduct true triaxial loading tests on large-scale three-dimensional physical model specimens, excavate micro-tunnels on large-scale three-dimensional physical model specimens during the true triaxial loading process, collect and organize various single ultrasonic signals and mixed ultrasonic signals during the micro-tunnel excavation process, and then compile them into a characteristic wave signal database;

[0012] Step 5: Analyze the characteristic wave signal data to form a static analytical mathematical model in the acoustic domain, a dynamic response iterative model and a constrained optimization correction model;

[0013] Step 6: Generate an acoustic pressure distribution map based on the constraint optimization correction model in the acoustic number domain, determine the position and size of the three-dimensional volume element model of the rockburst incubation location, arbitrarily adjust the angle of the section, scanning depth and scanning angle, dynamically capture the focal position where the rockburst may occur, and adjust the scanning speed according to the ultrasonic echo signal and motion characteristics of the rockburst incubation location during scanning to sense the formation of microcracks and sections, and track the incubation status of the rockburst in real time;

[0014] Step 7: Display the ultrasonic echo signals collected by different piezoelectric chips in grayscale to form a two-dimensional dynamic real-time image of the rockburst breeding location, and obtain continuous two-dimensional cross-sectional images;

[0015] Step 8: Generate a three-dimensional image database through the continuous two-dimensional cross-sectional images obtained to supplement the correction model in the acoustic-numerical domain, and then form a noise + structure model in the image domain, so as to grasp the rockburst incubation process inside the large-scale three-dimensional physical model specimen in real time, realize the identification of the surrounding rock energy accumulation, dissipation and release process, perceive the degree of stress accumulation in the potential rockburst area, and realize high-resolution perception of the rockburst incubation process.

[0016] In step one, the selected piezoelectric chip needs to match the material acoustic impedance characteristics of the large 3D physical model specimen.

[0017] In step 2, the ultrasonic excitation signal sent to the piezoelectric chip includes amplitude, waveform, frequency, amplification factor and bandpass filter frequency. The ultrasonic excitation signal needs to be amplified before being sent to the piezoelectric chip.

[0018] In step three, when all the piezoelectric chips in the spatial array complete an ultrasonic emission process, the ultrasonic waves emitted by all the piezoelectric chips form an overall wavefront, which is used to achieve ultrasonic beam scanning, deflection and focusing by controlling the shape and direction of the wavefront.

[0019] In step 4, various single ultrasonic signals and mixed ultrasonic signals generated during the micro-tunnel excavation process have different characteristics of ultrasonic signals generated by rock crack damage, stone fragments and rolling, seepage and water droplets, rock bursts, excavation stone fragments and construction noise of personnel.

[0020] In step five, before forming the static analytical mathematical model, dynamic response iterative model and constrained optimization correction model in the acoustic domain, it is necessary to first establish the frequency, amplitude, phase and wave velocity of various ultrasonic signals as input parameters, then interpret and resynthesize the mixed signal, and adjust the appropriate filter function to filter out various noise signals until the signal features useful for rockburst identification and the behavioral characteristics of excavated gravel in the ultrasonic frequency band are extracted.

[0021] In step six, the acoustic pressure distribution diagram is used to characterize the severity of rockburst initiation.

[0022] In step seven, continuous two-dimensional cross-sectional images are obtained by moving the scanning plane.

[0023] In step eight, after the three-dimensional image database is generated, when a reference section is selected to cut and observe the three-dimensional image database in any direction, the three-dimensional reconstruction and display of the rockburst incubation location can be completed.

[0024] Beneficial effects of the present invention:

[0025] The ultrasonic spatial array sensing method for the rockburst incubation process of a large three-dimensional physical model of the present invention belongs to active detection. The method is based on the true triaxial stress and ultrasonic correlation characteristics to identify rock damage and invert stress field changes. It mainly utilizes the principle that when ultrasonic waves propagate inside the object being measured, they will reflect when encountering ruptures and slip interfaces with different acoustic impedances. It is equivalent to the inverse process of the traditional microseismic method. The position of the excitation point is known, and the relative position of the excitation point to any array point in space is known. Therefore, the wave velocity is determined according to the ultrasonic propagation time, and the degree of stress concentration in the potential rockburst area can be effectively sensed. The ultrasonic spatial array is a combination of piezoelectric ceramic crystals of an ultrasonic probe, which is distributed and arranged in a spatial array manner by multiple piezoelectric chips, and then each piezoelectric chip is excited one by one according to a predetermined delay time, so that the ultrasonic waves emitted by all piezoelectric chips form an overall wavefront, which can effectively control the shape and direction of the emitted ultrasonic beam (wavefront), thereby realizing the beam scanning, deflection and focusing of the ultrasonic wave. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the implementation principle of the ultrasonic spatial array sensing method for the rockburst incubation process of a large three-dimensional physical model of the present invention;

[0027] In the figure, 1 is a large three-dimensional physical model specimen, 2 is a piezoelectric chip, and 3 is a micro tunnel. DETAILED DESCRIPTION

[0028] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0029] A method for ultrasonic spatial array sensing of a rockburst incubation process in a large three-dimensional physical model comprises the following steps:

[0030] Step 1: Prepare a large three-dimensional physical model sample 1. During the preparation of the large three-dimensional physical model sample 1, a plurality of piezoelectric chips 2 are pre-embedded. The plurality of piezoelectric chips 2 are distributed and arranged in a spatial array, such as Figure 1 As shown; the selected piezoelectric chip 1 needs to match the material acoustic impedance characteristics of the large three-dimensional physical model sample 1;

[0031] Step 2: Select a piezoelectric chip 2 from the spatial array, send an ultrasonic excitation signal to the piezoelectric chip 2, and the piezoelectric chip 2 sends ultrasonic waves to the surface of the large three-dimensional physical model sample 1. The remaining piezoelectric chips 2 in the spatial array are used to receive ultrasonic echo signals; the ultrasonic excitation signal sent to the piezoelectric chip 2 includes amplitude, waveform, frequency, amplification factor and bandpass filter frequency, and the ultrasonic excitation signal needs to be amplified before being sent to the piezoelectric chip 2;

[0032] Step 3: Select another piezoelectric chip 2 from the spatial array, send an ultrasonic excitation signal to the piezoelectric chip 2, and the piezoelectric chip 2 transmits ultrasonic waves to the surface of the large three-dimensional physical model sample 1, and the remaining piezoelectric chips 2 in the spatial array are used to receive ultrasonic echo signals; and so on, until all the piezoelectric chips 2 in the spatial array have completed an ultrasonic transmission process; when all the piezoelectric chips 2 in the spatial array have completed an ultrasonic transmission process, the ultrasonic waves emitted by all the piezoelectric chips 2 form an overall wavefront, which is used to achieve ultrasonic beam scanning, deflection and focusing by controlling the shape and direction of the wavefront;

[0033] Step 4: Carry out a true triaxial loading test on the large three-dimensional physical model sample 1, excavate a micro-tunnel 3 on the large three-dimensional physical model sample 1 during the true triaxial loading process, collect and organize various single ultrasonic signals and mixed ultrasonic signals during the excavation of the micro-tunnel 3, and then compile them into a characteristic wave signal database; various single ultrasonic signals and mixed ultrasonic signals generated during the excavation of the micro-tunnel 3 have different characteristics of ultrasonic signals generated by rock crack damage, gravel and rolling, seepage and water droplets, rock bursts, excavation gravel sound and construction noise of personnel;

[0034] Step 5: Analyze the characteristic wave signal data to form a static analytical mathematical model, a dynamic response iterative model and a constrained optimization correction model in the acoustic-numerical domain; before forming the static analytical mathematical model, the dynamic response iterative model and the constrained optimization correction model in the acoustic-numerical domain, it is necessary to first establish the frequency, amplitude, phase and wave velocity of various ultrasonic signals as input parameters, then interpret and resynthesize the mixed signal, and adjust the appropriate filter function to filter out various noise signals until the signal features useful for rockburst identification and the behavioral features of excavated gravel in the ultrasonic frequency band are extracted;

[0035] Step 6: Generate an acoustic pressure distribution map based on the constraint optimization correction model in the acoustic number domain, determine the position and size of the three-dimensional volume element model of the rockburst incubation location, arbitrarily adjust the angle of the section, scanning depth and scanning angle, dynamically capture the focal position where the rockburst may occur, and adjust the scanning speed according to the ultrasonic echo signal and motion characteristics of the rockburst incubation location during scanning to sense the formation of microcracks and sections, and track the incubation status of the rockburst in real time; the acoustic pressure distribution map is used to characterize the severity of the rockburst incubation;

[0036] Step 7: Display the ultrasonic echo signals collected by different piezoelectric chips 2 in grayscale to form a two-dimensional dynamic real-time image of the rockburst breeding location, and obtain continuous two-dimensional cross-sectional images; the continuous two-dimensional cross-sectional images are obtained by moving the scanning plane;

[0037] Step 8: Generate a three-dimensional image database through the continuous two-dimensional cross-section images obtained to supplement the correction model in the acoustic-numerical domain, and then form a noise + structure model in the image domain, so as to grasp the rockburst incubation process inside the large three-dimensional physical model sample 1 in real time, realize the identification of the surrounding rock energy accumulation, dissipation and release process, perceive the stress accumulation degree in the potential rockburst area, and realize high-resolution perception of the rockburst incubation process; after the three-dimensional image database is generated, when a reference section is selected to cut and observe the three-dimensional image database in any direction, the three-dimensional reconstruction and display of the rockburst incubation position can be completed.

[0038] The solutions in the embodiments are not intended to limit the patent protection scope of the present invention. All equivalent implementations or changes that do not deviate from the present invention are included in the patent scope of this case.

Claims

1. A method for ultrasonic spatial array sensing of rockburst incubation process in a large three-dimensional physical model, characterized in that The steps include: Step 1: preparing a large-scale three-dimensional physical model specimen, during which a plurality of piezoelectric chips are pre-embedded, and the plurality of piezoelectric chips are distributed and arranged in a spatial array; Step 2: Select a piezoelectric chip from the spatial array, send an ultrasonic excitation signal to the piezoelectric chip, and the piezoelectric chip sends ultrasonic waves to the surface of the large three-dimensional physical model sample, and the remaining piezoelectric chips in the spatial array are used to receive ultrasonic echo signals; Step 3: Select another piezoelectric chip from the spatial array, send an ultrasonic excitation signal to the piezoelectric chip, and the piezoelectric chip transmits ultrasonic waves to the surface of the large three-dimensional physical model sample. The remaining piezoelectric chips in the spatial array are used to receive ultrasonic echo signals; and so on, until all the piezoelectric chips in the spatial array complete an ultrasonic transmission process; Step 4: Conduct true triaxial loading tests on large-scale three-dimensional physical model specimens, simulate tunnel hole excavation on large-scale three-dimensional physical model specimens during true triaxial loading, collect and organize various single ultrasonic signals and mixed ultrasonic signals during the simulated tunnel hole excavation process, and then compile them into a characteristic wave signal database; Step 5: Analyze the characteristic wave signal data to form a static analytical mathematical model in the acoustic domain, a dynamic response iterative model and a constrained optimization correction model; Step 6: Generate an acoustic pressure distribution map based on the constraint optimization correction model in the acoustic number domain, determine the position and size of the three-dimensional volume element model of the rockburst incubation location, arbitrarily adjust the angle of the section, scanning depth and scanning angle, dynamically capture the focal position where the rockburst may occur, and adjust the scanning speed according to the ultrasonic echo signal and motion characteristics of the rockburst incubation location during scanning to sense the formation of microcracks and sections, and track the incubation status of the rockburst in real time; Step 7: Display the ultrasonic echo signals collected by different piezoelectric chips in grayscale to form a two-dimensional dynamic real-time image of the rockburst breeding location, and obtain continuous two-dimensional cross-sectional images; Step 8: Generate a three-dimensional image database through the continuous two-dimensional cross-sectional images obtained to supplement the correction model in the acoustic-numerical domain, and then form a noise + structure model in the image domain, so as to grasp the rockburst incubation process inside the large-scale three-dimensional physical model specimen in real time, realize the identification of the surrounding rock energy accumulation, dissipation and release process, perceive the degree of stress accumulation in the potential rockburst area, and realize high-resolution perception of the rockburst incubation process.

2. The ultrasonic spatial array sensing method for the rockburst incubation process of a large-scale three-dimensional physical model according to claim 1 is characterized by: In step one, the selected piezoelectric chip needs to match the material acoustic impedance characteristics of the large 3D physical model specimen.

3. The ultrasonic spatial array sensing method for the rockburst incubation process of a large-scale three-dimensional physical model according to claim 1 is characterized by: In step 2, the ultrasonic excitation signal sent to the piezoelectric chip includes amplitude, waveform, frequency, amplification factor and bandpass filter frequency. The ultrasonic excitation signal needs to be amplified before being sent to the piezoelectric chip.

4. The ultrasonic spatial array sensing method for the rockburst incubation process of a large-scale three-dimensional physical model according to claim 1 is characterized by: In step three, when all the piezoelectric chips in the spatial array complete an ultrasonic emission process, the ultrasonic waves emitted by all the piezoelectric chips form an overall wavefront, which is used to achieve ultrasonic beam scanning, deflection and focusing by controlling the shape and direction of the wavefront.

5. The ultrasonic spatial array sensing method for the rockburst incubation process of a large-scale three-dimensional physical model according to claim 1 is characterized by: In step 4, various single ultrasonic signals and mixed ultrasonic signals generated during the tunnel hole excavation process are simulated, and the different characteristics of ultrasonic signals are generated by rock crack damage, stone fragments and rolling, seepage and water droplets, rock bursts, excavation stone fragments and construction noise.

6. The ultrasonic spatial array sensing method for the rockburst incubation process of a large-scale three-dimensional physical model according to claim 1 is characterized by: In step five, before forming the static analytical mathematical model, dynamic response iterative model and constrained optimization correction model in the acoustic domain, it is necessary to first establish the frequency, amplitude, phase and wave velocity of various ultrasonic signals as input parameters, then interpret and resynthesize the mixed signal, and adjust the appropriate filter function to filter out various noise signals until the signal features useful for rockburst identification and the behavioral characteristics of excavated gravel in the ultrasonic frequency band are extracted.

7. The ultrasonic spatial array sensing method for the rockburst incubation process of a large-scale three-dimensional physical model according to claim 1 is characterized by: In step six, the acoustic pressure distribution diagram is used to characterize the severity of rockburst initiation.

8. The ultrasonic spatial array sensing method for the rockburst incubation process of a large-scale three-dimensional physical model according to claim 1 is characterized by: In step seven, continuous two-dimensional cross-sectional images are obtained by moving the scanning plane.

9. The ultrasonic spatial array sensing method for the rockburst incubation process of a large-scale three-dimensional physical model according to claim 1 is characterized by: In step eight, after the three-dimensional image database is generated, when a reference section is selected to cut and observe the three-dimensional image database in any direction, the three-dimensional reconstruction and display of the rockburst incubation location can be completed.

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