CN116299708B - Visualization method and related equipment for tunnel surrounding rock loose ring evolution process - Google Patents
Visualization method and related equipment for tunnel surrounding rock loose ring evolution process Download PDFInfo
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Abstract
The invention discloses a visualization method and related equipment for a loose ring evolution process of tunnel surrounding rock, relates to the field of geotechnical mechanics, and mainly aims to solve the problem that a method for accurately monitoring the loose ring evolution process of the tunnel surrounding rock for a long time is lacking at present. The method comprises the following steps: acquiring noise signals of at least two detectors in surrounding rock; determining a corresponding surrounding rock loosening ring transverse wave speed curve at a target detector based on a noise signal of the target detector, wherein the surrounding rock loosening ring transverse wave speed curve is related to depth change; determining a surrounding rock loose coil transverse wave speed model based on surrounding rock loose coil transverse wave speed curves corresponding to the at least two detectors; and acquiring the surrounding rock loose coil transverse wave speed model in a preset period to determine the evolution process of the surrounding rock loose coil. The method is used for the visualization process of the loose ring evolution process of the tunnel surrounding rock.
Description
Technical Field
The invention relates to the field of geotechnical mechanics, in particular to a tunnel surrounding rock loose ring evolution process visualization method and related equipment.
Background
The radial stress of surrounding rock is reduced to zero after tunnel excavation, so that the strength of the surrounding rock is reduced, and the stress concentration in the surrounding rock is caused. When the stress exceeds the strength of the surrounding rock, the damage of the surrounding rock of the tunnel gradually expands from the outside to the inside until the three-dimensional stress balance is obtained again after a certain depth, and usually the scholars define the loose broken zone generated in the surrounding rock as the loose ring of the surrounding rock, which is called as the loose ring for short. The relevant scholars in foreign countries divide the tunnel surrounding rock loosening ring into a damage area, a damage area and a disturbance area, and can divide the excavation disturbance area into an excavation damage area, a non-saturation area and a stress distribution area. Domestic scholars generally divide the excavation disturbance zone into an unloading damage zone, an unloading influence zone and a slight disturbance zone, and tunnel excavation disturbance zones can be divided into three types as a whole.
The current in-situ testing and observation technology for disturbance areas is mainly focused on borehole optical observation and acoustic testing. However, the optical observation of the drilling is completely dependent on the observation holes on the surrounding rock wall of the tunnel to observe images through equipment such as a drilling television, so that the defect of one hole exists, the loose circle condition of surrounding rock around the drilling cannot be known, the accuracy of the observation depends on the number and the intensity of the drilling holes, the observation of a long-term evolution process is difficult, the drilling of the surrounding rock of the tunnel, especially the horizontal holes and the declining holes, easily have the problems of hole collapse, water seepage and the like, and the difficulty of long-term protection of the drilling holes brings a large amount of extra cost. Traditional sound wave test needs drilling and water filling, obtains the sound wave velocity that is between sound wave transmitting transducer and the tunnel surface receiving transducer in the drilling, lacks the regional test of the regional district of tunnel country rock loose coil, if need observe long-term evolution to same observation area, need carry out artifical repeated observation, and consuming time is big and test repeatability is low. Therefore, a method for visually testing the evolution process of the loose ring of the surrounding rock of the tunnel, which can evolve for a long time, is lacking in the current engineering.
Disclosure of Invention
In view of the above problems, the invention provides a method for visualizing the evolution process of a loose ring of a tunnel surrounding rock and related equipment, and mainly aims to solve the problem that a method for accurately monitoring the evolution process of the loose ring of the tunnel surrounding rock for a long time is lacking at present.
To solve at least one of the above technical problems, in a first aspect, the present invention provides a method for visualizing a loose loop evolution process of a tunnel surrounding rock, the method comprising:
Acquiring noise signals of at least two detectors in surrounding rock;
Determining a corresponding surrounding rock loosening ring transverse wave speed curve at a target detector based on a noise signal of the target detector, wherein the surrounding rock loosening ring transverse wave speed curve is related to depth change;
determining a surrounding rock loose coil transverse wave speed model based on surrounding rock loose coil transverse wave speed curves corresponding to the at least two detectors;
And acquiring the surrounding rock loose coil transverse wave velocity model in a preset period to determine the evolution process of the surrounding rock loose coil.
Optionally, the method further comprises:
determining a spatial autocorrelation coefficient based on the noise signal of the target detector and the noise signals of the other detectors;
And determining a dispersion curve based on the spatial autocorrelation coefficient, wherein the dispersion curve is used for representing the dispersion change process of the surface wave propagating along the tunnel side wall.
Optionally, the determining the dispersion curve based on the spatial autocorrelation coefficient includes:
determining a first zero-order Bessel function based on the spatial autocorrelation coefficients;
And determining the dispersion curve based on the first zero-order Bezier function, wherein the dispersion curve is used for representing the transverse wave speed of the tunnel surrounding rock.
Optionally, the method further comprises:
Determining propagation speeds of Rayleigh waves at different frequencies along a tunnel side wall based on the first zero-order Bessel function;
And determining a dispersion curve based on the propagation speed of the Rayleigh waves at different frequencies along the side wall of the tunnel.
Optionally, the determining, based on the noise signal of the target detector, a corresponding surrounding rock loose coil transverse wave velocity curve at the target detector includes:
And determining a surrounding rock loose coil transverse wave speed curve at the target detector through a least square method and constraint information based on the dispersion curve.
Optionally, the determining the surrounding rock loose coil transverse wave velocity curve at the target detector based on the dispersion curve through a least square method and constraint information includes:
and determining a surrounding rock loose coil transverse wave speed curve at the target detector through a least square method and constraint information based on the dispersion curve and the number of surrounding rock transverse wave speed model layers, wherein the number of transverse wave speed model layers is three based on loose coil layering characteristics.
Optionally, the method further comprises:
acquiring an optical image of the surrounding rock based on the drilling optical camera to determine RMIBT values;
And determining the constraint condition based on the change of RMIBT values at different moments, wherein the constraint condition is the positive and negative directions of the update quantity of the surrounding rock loose coil transverse wave velocity model.
In a second aspect, an embodiment of the present invention further provides a device for visualizing a loose loop evolution process of a tunnel surrounding rock, including:
the acquisition unit is used for acquiring noise signals of at least two detectors in the surrounding rock;
A first determining unit, configured to determine a corresponding surrounding rock loose coil shear wave velocity curve at a target detector based on a noise signal of the target detector, where the surrounding rock loose coil shear wave velocity curve is related to a depth change;
the second determining unit is used for determining a surrounding rock loosening ring transverse wave speed model based on surrounding rock loosening ring transverse wave speed curves corresponding to the at least two detectors;
and the third determining unit is used for acquiring the surrounding rock loose coil transverse wave speed model in a preset period to determine the evolution process of the surrounding rock loose coil.
To achieve the above object, according to a third aspect of the present invention, there is provided a computer readable storage medium including a stored program, wherein the steps of the above-mentioned tunnel surrounding rock loose-loop evolution process visualization method are implemented when the program is executed by a processor.
In order to achieve the above object, according to a fourth aspect of the present invention, there is provided an electronic device including at least one processor, and at least one memory connected to the processor; the processor is used for calling the program instructions in the memory and executing the steps of the tunnel surrounding rock loose ring evolution process visualization method.
By means of the technical scheme, the visualization method and the relevant equipment for the loose ring evolution process of the tunnel surrounding rock are used for solving the problem that a method for accurately monitoring the loose ring evolution process of the tunnel surrounding rock for a long time is lacking at present; determining a corresponding surrounding rock loosening ring transverse wave speed curve at a target detector based on a noise signal of the target detector, wherein the surrounding rock loosening ring transverse wave speed curve is related to depth change; determining a surrounding rock loose coil transverse wave speed model based on surrounding rock loose coil transverse wave speed curves corresponding to the at least two detectors; and acquiring the surrounding rock loose coil transverse wave velocity model in a preset period to determine the evolution process of the surrounding rock loose coil. In the scheme, typical noises of different periods of a tunnel, such as blasting noises in a construction period and traffic noises in an operation period, are effectively utilized, inversion transverse wave speed profiles are extracted through dispersion curves of the noises, a three-dimensional transverse wave speed model of surrounding rocks of the tunnel can be obtained through transverse wave speed profile results of a plurality of measuring lines, transverse wave speeds of a plurality of measuring lines are obtained through inversion of environmental noise signals, a range of a loose coil is determined through the size of the transverse wave speeds, regional large-size test and evaluation can be realized, and due to a periodic acquisition model, the inversion of the transverse wave speeds of signals in a selective interception period can be carried out through long-term monitoring of background noises, and a near continuous loose coil evolution process at different moments can be obtained.
Correspondingly, the tunnel surrounding rock loose-loop evolution process visualization device, the tunnel surrounding rock loose-loop evolution process visualization equipment and the tunnel surrounding rock loose-loop evolution process visualization computer-readable storage medium have the technical effects.
The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present invention more readily apparent.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
Fig. 1 shows a flow diagram of a visualization method for a loose loop evolution process of a tunnel surrounding rock according to an embodiment of the present invention;
Fig. 2 shows a schematic layout plan view of a visual test device for the long-term evolution of a loose ring of a tunnel surrounding rock according to an embodiment of the present invention;
fig. 3 shows an arrangement view schematic diagram of a visual testing device for the long-term evolution of a loose ring of a tunnel surrounding rock, which is provided by the embodiment of the invention;
fig. 4 is a schematic front view showing the arrangement of a visual testing device for the long-term evolution of the loose ring of the surrounding rock of the tunnel, which is provided by the embodiment of the invention;
fig. 5 shows a schematic structural diagram of a visual test device for long-time evolution of a loose ring of a tunnel surrounding rock, which is provided by the embodiment of the invention;
fig. 6 shows a schematic diagram of a visual test analysis host structure for long-term evolution of a loose ring of a tunnel surrounding rock, which is provided by the embodiment of the invention;
FIG. 7 is a schematic diagram illustrating background noise monitoring of a detector environment according to an embodiment of the present invention;
FIG. 8 shows a typical three-layered schematic of a tunnel surrounding rock loose coil provided by an embodiment of the present invention;
FIG. 9 shows a schematic diagram of a transverse wave velocity inversion at 11 detectors on a line of a loose circle of tunnel surrounding rock provided by an embodiment of the present invention;
FIG. 10 shows a schematic diagram of transverse wave velocity inversion of a plurality of detectors of a loose ring of a tunnel surrounding rock according to an embodiment of the present invention;
FIG. 11 shows a schematic representation of a small borehole optical observation calculation RMIBT constraint inversion provided by an embodiment of the present invention;
fig. 12 is a schematic block diagram illustrating a visualization device for the evolution process of a loose ring of a tunnel surrounding rock according to an embodiment of the present invention;
Fig. 13 is a schematic block diagram of a visual electronic device for the evolution process of a loose ring of a tunnel surrounding rock according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
In order to solve the problem that a method for accurately monitoring the evolution process of the loose ring of the surrounding rock of a tunnel for a long time is lacking at present, the embodiment of the invention provides a visualization method for the evolution process of the loose ring of the surrounding rock of the tunnel, as shown in fig. 1, the method comprises the following steps:
S101, acquiring noise signals of at least two detectors in surrounding rock;
As shown in fig. 2, 3 and 4, an arrangement plan view, a side view and a front view of a tunnel surrounding rock loose coil long-time evolution visual testing device of the method are provided, wherein the testing device mainly comprises a testing device 1 and a field analysis host 2. The testing device 1 mainly comprises a high-frequency seismic wave detector 1.1 and a drilling optical camera 1.5. The high-frequency geophone is connected with the field analysis host through wireless communication, and the drilling optical camera is connected with the field analysis host through a wired communication cable. The high-frequency geophones are horizontally and equidistantly arranged on the tunnel side wall along the axis direction of the tunnel, and the drilling optical cameras are arranged in a small number of observation holes on the tunnel side wall. Due to the dominant frequency characteristics (about 10Hz to 300 Hz) and the depth range (about 25m range) of the loose coil of the background noise (construction blast, normal construction noise, vehicle noise, etc.) of the tunnel environment, the pitch of the high-frequency geophones can be set to 10m in this method, the bandwidth and sampling rate of which correspond to the background noise band. According to the actual field requirement, the distance between a small number of observation holes can be 100m, and the depth of the observation holes is more than 10m so as to achieve the purpose of constrained noise inversion. Observing the drilled holes is mostly upward inclined holes so as to prevent the drilled holes from collapsing. If necessary, a detector measuring line can be added at the top of the tunnel so as to realize transverse wave velocity profile inversion of the high-density tunnel surrounding rock loose coil.
As shown in fig. 5, the field host 2 includes a host communication module 2.1, a man-machine interaction device 2.2, a central processing unit 2.3, a storage module 2.4, an independent power supply module 2.5, an environmental noise signal processing module 2.6, a surrounding rock loose coil inversion module 2.7, a drilling optical image analysis module 2.8, a surrounding rock loose coil three-dimensional visualization module 2.9, and a mobile analysis terminal 2.10. The host communication module 2.1 is used as an interface to connect the field analysis host 2 with the testing device 1, the human-computer interaction device 2.2 can be a device such as a touch screen or an optical rotary button, the central processing unit 2.3 is used for processing control of signal transmission, storage, calculation and other instructions, the storage module 2.4 is used for storing acquired and processed information, the independent power supply module 2.5 is used for independently supplying power, the environmental noise signal processing module 2.6 is used for carrying out signal processing on a noise signal tested for a long time and extracting a dispersion curve, the surrounding rock loose coil inversion module 2.7 is used for inverting the dispersion curve to obtain the transverse wave speed of the surrounding rock loose coil at the high-frequency geophone 1.1, the drilling optical image analysis module 2.8 is used for calculating parameters such as image processing, RMIBT and the like, and guiding a model for transverse wave speed inversion to update the gradient direction. The surrounding rock loose coil three-dimensional visualization module 2.9 converts the 1D transverse wave speed curve of each detector point line into a 2D transverse wave speed profile of each measuring line, and a 3D transverse wave speed model is generated by utilizing the 2D transverse wave speed profiles of a plurality of measuring lines.
As shown in fig. 6, the test device 1 specifically includes a high-frequency geophone 1.1, a pre-signal amplifying filter 1.2, an a/D conversion module 1.3, a data transmission wireless communication module 1.4, a borehole optical pickup probe 1.5, a pre-image data processor 1.6, an image data digitizing module 1.7, and a data transmission line communication module 1.8. The high-frequency geophone 1.1 is provided with a self-powered module, can be installed on the side wall of a surrounding rock of a tunnel to be tested for a long time for continuous sampling, acquires a tunnel environment noise signal, further selects an effective signal frequency band through a preposed signal amplifying filter 1.2, converts an electric signal into a digital signal through an A/D conversion module 1.3, transmits the signal to a field analysis host 2 through a host communication module 2.1 in a real-time wireless manner through a data transmission wireless communication module 1.4, and a drilling optical camera probe 1.5 is connected with the field analysis host 2 through a wired cable and realizes power supply. The drilling optical camera probe 1.5 is only placed in an observation drilling hole when testing is needed, the drilling optical camera probe conducts preliminary noise filtering on rock mass images of the wall of the observation drilling hole through the front-end image data processor 1.6, the rock mass images are digitized through the image data digitizing module 1.7, and finally the drilling optical camera probe is connected with a site analysis host through the host communication module 2.1 through the data transmission wired communication module 1.8.
As shown in fig. 7, the method collects noise signals of tunnel construction and operation period through a high-frequency geophone 1.1 (abbreviated as a geophone in the scheme), wherein the noise signals can be blasting and construction noise of further tunnel construction or vehicle noise in the tunnel of operation period, and are not particularly limited herein. The method solves the problems that in the prior art, test analysis of a long-time evolution process is required to be realized, detection is needed once at intervals, acquired data are discrete, time and labor are wasted, and the method can obtain a near-continuous loose-loop evolution process at different moments by carrying out inversion of transverse wave speed on signals in a selectable interception time period through long-term monitoring of background noise.
S102, determining a corresponding surrounding rock loose coil transverse wave speed curve at a target detector based on a noise signal of the target detector, wherein the surrounding rock loose coil transverse wave speed curve is related to depth change;
By way of example, the method uniformly segments the collected data according to time-frequency, and as far as possible, the larger the signal-to-noise ratio is, the smaller the noise mixed in the signal is, the higher the sound quality of sound playback is, so that the part with low signal-to-noise ratio in the collected data segment is removed, each data short is processed by using narrow-band-pass filters with different center frequencies, and the part with high signal-to-noise ratio is substituted into the later signal processing to determine the corresponding surrounding rock loose ring transverse wave speed curve at the target detector.
S103, determining a surrounding rock loose coil transverse wave speed model based on surrounding rock loose coil transverse wave speed curves corresponding to the at least two detectors;
By way of example, the same transverse wave speed inversion method is adopted for different detector center points, inversion steps are repeated, surrounding rock loose ring transverse wave speed curves at a plurality of detector point positions can be obtained, and two-dimensional transverse wave speed profiles of detector measuring lines can be obtained through linear interpolation of transverse wave speed curves at different positions.
S104, acquiring the surrounding rock loose coil transverse wave velocity model in a preset period to determine the evolution process of the surrounding rock loose coil.
By way of example, at different time points, the inversion method can be repeated to obtain transverse wave velocity models of the loose rings of the tunnel surrounding rocks at different time points, and then the long-term evolution process of the loose rings of the tunnel surrounding rocks can be obtained. The time interval for analysis can be selected according to specific engineering requirements, for example, the time interval can be analyzed in days when a tunnel is excavated, and the operation period of the tunnel can be analyzed in months. The transverse wave speeds of a plurality of measuring lines are obtained through inversion of the environmental noise signals, and the range of the loose ring is determined through the transverse wave speeds, so that the detection of the long-time evolution process of the loose ring of the tunnel surrounding rock is realized, and the regional large-scale test and evaluation of the loose ring of the tunnel surrounding rock are realized.
By means of the method and the device, the number of layers in the process of inverting the transverse wave speed is fixed according to the characteristics of the loose rings of the surrounding rocks of the tunnel, the inversion speed can be effectively increased, and the inversion accuracy is improved. The definition and classification of tunnel surrounding rock loose rings are different, but are divided into three areas as a whole, and the three areas have obvious differences in transverse wave speed.
By means of the technical scheme, the visualization method for the loose ring evolution process of the tunnel surrounding rock provided by the invention is used for solving the problem that a method for accurately monitoring the loose ring evolution process of the tunnel surrounding rock for a long time is lacking at present; determining a corresponding surrounding rock loosening ring transverse wave speed curve at a target detector based on a noise signal of the target detector, wherein the surrounding rock loosening ring transverse wave speed curve is related to depth change; determining a surrounding rock loose coil transverse wave speed model based on surrounding rock loose coil transverse wave speed curves corresponding to the at least two detectors; and acquiring the surrounding rock loose coil transverse wave velocity model in a preset period to determine the evolution process of the surrounding rock loose coil. In the scheme, typical noises of different periods of a tunnel, such as blasting noises in a construction period and traffic noises in an operation period, are effectively utilized, inversion transverse wave speed profiles are extracted through dispersion curves of the noises, a three-dimensional transverse wave speed model of surrounding rocks of the tunnel can be obtained through transverse wave speed profile results of a plurality of measuring lines, transverse wave speeds of a plurality of measuring lines are obtained through inversion of environmental noise signals, a range of a loose coil is determined through the size of the transverse wave speeds, regional large-size test and evaluation can be realized, and due to a periodic acquisition model, the inversion of the transverse wave speeds of signals in a selective interception period can be carried out through long-term monitoring of background noises, and a near continuous loose coil evolution process at different moments can be obtained.
In one embodiment, the method further comprises:
determining a spatial autocorrelation coefficient based on the noise signal of the target detector and the noise signals of the other detectors;
And determining a dispersion curve based on the spatial autocorrelation coefficient, wherein the dispersion curve is used for representing the dispersion change process of the surface wave propagating along the tunnel side wall.
For example, spatial autocorrelation coefficients are often used to quantitatively describe the spatial dependence of things, and can be used to measure the spatial distribution characteristics of physical or ecological variables and their extent of impact on the field. The dispersion curve is a curve showing the relationship between the period (or wavelength, frequency) and the wave velocity of the dispersion wave.
In one embodiment, the determining the dispersion curve based on the spatial autocorrelation coefficients includes:
determining a first zero-order Bessel function based on the spatial autocorrelation coefficients;
And determining the dispersion curve based on the first zero-order Bezier function, wherein the dispersion curve is used for representing the transverse wave speed of the tunnel surrounding rock.
Illustratively, the method first calculates the spatial autocorrelation coefficients between the target detector and the other detector points to fit a first class zero-order Bessel function as follows:
Where W a (ω) is the power spectrum of the center point of the detector's observation array and W b (ω, r, θ) is the cross power spectrum seen by the adjacent detectors. Omega is the signal frequency, r is the equivalent spacing seen by the detector, and θ is the azimuth angle. Re is the real part of the power spectrum.
Illustratively, the propagation velocity C (ω) is calculated by a zero-order bessel function of the first type, thereby picking up the dispersion curve:
in one embodiment, the method further comprises:
Determining propagation speeds of Rayleigh waves at different frequencies along a tunnel side wall based on the first zero-order Bessel function;
And determining a dispersion curve based on the propagation speed of the Rayleigh waves at different frequencies along the side wall of the tunnel.
Illustratively, the propagation speed C (omega) of the Rayleigh wave along the tunnel side wall under different frequencies is calculated through a first zero-order Bessel function, so that the propagation speed of the Rayleigh wave along the tunnel side wall under different frequencies is picked up to determine a dispersion curve.
In one embodiment, the determining the corresponding surrounding rock loose coil shear wave velocity profile at the target detector based on the noise signal of the target detector includes:
And determining a surrounding rock loose coil transverse wave speed curve at the target detector through a least square method and constraint information based on the dispersion curve.
Illustratively, the least square method defines an objective function as a dispersion curve J (r, w), namely an observation value G, and the method inverts an acoustic wave velocity structure layer of a surrounding rock loosening zone of a tunnel through the least square method and constraint information to determine a surrounding rock loosening zone transverse wave velocity curve at a target detector.
In one embodiment, the determining the surrounding rock loose coil transverse wave velocity curve at the target detector through a least square method and constraint information based on the dispersion curve includes:
and determining a surrounding rock loose coil transverse wave speed curve at the target detector through a least square method and constraint information based on the dispersion curve and the number of surrounding rock transverse wave speed model layers, wherein the number of transverse wave speed model layers is three based on loose coil layering characteristics.
For example, as shown in fig. 8, the speed model is divided into three layers (disturbance area, damage area) as a whole, the acoustic speed structure layer of the tunnel surrounding rock loose ring is inverted by a least square method, the least square method defines an objective function as a dispersion curve J (r, w), namely, observed values g= [ G1, G2, G3 … Gm ], model parameters x= [ X1, X2, X3 … Xm ], and X takes a transverse wave speed model of the 3-layer tunnel surrounding rock, and the least square method defines the objective function as a least square of G and a forward result M of X:
in the method, m is 3, taylor expansion is carried out on the objective function, and the minimum value is taken after secondary and higher terms are omitted:
in the above equation, a is a jacobian matrix for the first partial derivative of the model parameters. Let g=a T|G―X(0) |, the update amount of the model at each time can be obtained:
ΔX＝(ATA)―1g
The graph shows curves corresponding to an initial model, a real model and an inversion result respectively, wherein the initial model is an inverted initial model, the real model is a real speed model, inversion is completed when the model is updated to a target function smaller than a preset threshold value through multiple iterations, an inversion result is obtained, and a curve of a transverse wave changing along with the depth is obtained, as shown in fig. 10, in a transverse wave speed inversion schematic diagram formed by a plurality of detectors of a tunnel surrounding rock loose ring, the transverse coordinate is a horizontal axis, the unit is m, the ordinate is depth, the higher the numerical value is, the closer the tunnel is, the unit is m, and a right color legend represents the surrounding rock loose ring transverse wave speed.
By way of example, when the least square inversion is used, the speed model can be integrally divided into three layers (disturbance area, damage area and damage area) according to the characteristics of the tunnel surrounding rock loose ring, the same speed representation can be approximately adopted in the same layer, the thickness and the speed change of the layer can be obtained through long-time monitoring inversion, and the visualization process of the tunnel surrounding rock loose ring of the whole monitoring field along with the time change can be obtained through analysis.
In one embodiment, the method further comprises:
acquiring an optical image of the surrounding rock based on the drilling optical camera to determine RMIBT values;
And determining the constraint condition based on the change of RMIBT values at different moments, wherein the constraint condition is the positive and negative directions of the update quantity of the surrounding rock loose coil transverse wave velocity model.
The inversion of the least square method requires more priori information, is very sensitive to an initial model and parameter setting of the inversion, and needs to define the initial model of the inversion to a certain extent through a small number of optical observation drilling holes of a tunnel at the moment, so that the inversion result is solved in the correct direction.
For example, a new deep Rock integrity evaluation method-RMIBT method (Rock MASS INTEGRITY Index Based on High-definition Digital Borehole Televiewer) is provided based on high-definition digital drilling camera shooting test results, a RMIBT value is obtained by measuring the weight proportion occupied by the Rock length without macroscopic cracks in the wall of a drilling hole, the method is suitable for deep Rock integrity evaluation under the conditions of deep Rock core cake formation, spatial combination characteristics of structural surfaces in different directions with the drilling hole and high-stress coring and crushing, and is applied to a plurality of deep projects to prove the effectiveness of the deep Rock integrity evaluation, RMIBT can dynamically evaluate the crack evolution of macroscopic Rock integrity and a loosening range, and provides basis for engineering Rock evaluation and support.
The method is exemplified by determining the weight proportion occupied by the length of the complete rock mass in the wall of the borehole by using RMIBT values through observing the optical image of the borehole by a small amount of optics of the tunnel, wherein the calculation formula is as follows:
The formula: l is the total length of the evaluation section, and the unit is m; l1, l2, l3, l4 and l5 are respectively the lengths of the rock mass without macroscopic cracks in the evaluation section of 0.1-0.3 m, 0.3-0.5 m, 0.5-0.75 m, 0.75-1 m and the interval length larger than 1m, and the division of li is the division condition according to the recommended joint spacing grading standard of the international society of rock mechanics, domestic and foreign engineering practice and related specifications; ai is the coefficient of the i-th interval, where a1=0.19, a2=0.41, a3=0.63, a4=0.77, a5=1; lij is the rock mass length in the ith section; ni is the number of rock mass segments in the ith interval.
For ease of understanding, fig. 11 shows a schematic diagram of a constraint inversion of a small borehole optical observation calculation RMIBT provided by an embodiment of the present invention, RMIBT of this section may be calculated as follows:
RMIBT＝(0.19×l1+0.41×l2+0.63×l3+0.77×l4+l5)/L＝(0.19×0.7+0.41×1.07+0.77×0.91)/3＝0.45
illustratively, the method constrains the update amount deltax direction of the transverse wave velocity model at the moment by observing the change of RMIBT values of the borehole optical image at different moments, if RMIBT values become smaller, the forced constraint of deltax is negative, otherwise, if RMIBT values become larger, the forced constraint of deltax is positive. Therefore, the transverse wave speed inversion of the large field area can be effectively limited through a small amount of drilling information, and the stability and accuracy of inversion are improved.
By means of the method, the transverse wave speed inversion process is restrained through an optical-acoustic combination method, the multi-solution of transverse wave speed inversion can be improved to a great extent, and the inversion stability is improved. According to the scheme, the drilling optical observation is carried out by introducing a very small quantity of drilling holes, the direction of the gradient is updated by restraining the transverse wave speed model through the optical information of the wall of the drilling holes, the false update of transverse wave speed parameters in the inversion process can be avoided, the inversion is prevented from being trapped into a local optimal solution, the inversion is enabled to approach to a global optimal solution as much as possible, and the stability of the inversion is enhanced.
Furthermore, the key step of the scheme is to extract a dispersion curve from the collected noise surface wave data, and according to the arrangement mode of the inner detectors of the tunnel, the scheme can extract the data of noise signals by adopting a space autocorrelation method, and inversion of the transverse wave speed of the loose circle of the surrounding rock of the tunnel is carried out under the constraint condition of a small quantity of optical observation drilling holes. The method is realized by the following steps:
Step 1: noise signals of tunnel construction and operation period are collected through the detectors, and the noise source signals can be blasting and construction noise of further tunnel construction or vehicle noise in the tunnel of operation period.
Step 2: the collected data are uniformly segmented according to time-frequency, the parts with larger noise are distinguished as far as possible, the parts with low signal-to-noise ratio in the collected data segments are removed, each data short is processed by narrow-band-pass filters with different center frequencies, and the parts with high signal-to-noise ratio are substituted into the signal processing in the later stage.
Step 3: the spatial autocorrelation coefficients between the detector center point and other detector points are calculated to fit a first class of zero-order Bessel functions as follows:
Where W a (ω) is the power spectrum of the center point of the detector's observation array and W b (ω, r, θ) is the cross power spectrum seen by the adjacent detectors. Omega is the signal frequency, r is the equivalent spacing seen by the detector, and θ is the azimuth angle. Re is the real part of the power spectrum.
Step 4: calculating propagation speeds C (omega) of Rayleigh waves at different frequencies along the tunnel side wall through a first zero-order Bessel function, so as to pick up a dispersion curve:
Step 5: inverting the acoustic velocity structure layer of the loose ring of the tunnel surrounding rock by a least square method, wherein the least square method defines an objective function as a least square of a dispersion curve J (r, w), namely observed values G, G= [ G1, G2, G3 … Gm ] and model parameters (transverse wave velocity model of the 3-layer tunnel surrounding rock) X= [ X1, X2, X3 … Xm ] forward modeling result M, wherein the least square is as follows:
taylor expansion is carried out on the objective function, and the minimum value is taken after secondary and higher order items are omitted:
in the above equation, a is a jacobian matrix for the first partial derivative of the model parameters. Let g=a T|G―X(0) |, the update amount of the model at each time can be obtained:
ΔX＝(ATA)―1g
and when the model is updated to the state that the objective function is smaller than the preset threshold value after multiple iterations, ending inversion, and obtaining a curve of the transverse wave along with the depth change.
Certain limitation is needed to be carried out on the inverted initial model through a small amount of optical observation drilling holes of the tunnel, so that an inversion result is solved in the correct direction:
The optical image of the drilling hole is observed optically by a small amount of tunnels, the weight proportion occupied by the length of the complete rock mass in the wall of the drilling hole is determined by RMIBT values, and the calculation formula is as follows:
Wherein: l is the total length of the evaluation section, and the unit is m; l1, l2, l3, l4 and l5 are respectively the lengths of the rock mass without macroscopic cracks in the evaluation section of 0.1-0.3 m, 0.3-0.5 m, 0.5-0.75 m, 0.75-1 m and the interval length larger than 1m, and the division of li is the division condition according to the recommended joint spacing grading standard of the international society of rock mechanics, domestic and foreign engineering practice and related specifications; ai is the coefficient of the i-th interval, where a1=0.19, a2=0.41, a3=0.63, a4=0.77, a5=1; lij is the rock mass length in the ith section; ni is the number of rock mass segments in the ith interval.
By observing the change of RMIBT values at the beginning of the statistics of the optical image of the drilling at different moments, the updating quantity delta X direction of the transverse wave speed model at the moment is restrained, if RMIBT is smaller, the forced restraint of delta X is negative, otherwise, when RMIBT value is larger, the forced restraint of delta X is positive.
Step 6: and (3) adopting the same transverse wave speed inversion method for different detector center points, repeating the steps 1 to 5 to obtain transverse wave speed curves of surrounding rock loose rings at a plurality of detector point positions, obtaining two-dimensional transverse wave speed profiles of detector measuring lines by carrying out linear interpolation on the transverse wave speed curves at different positions, and obtaining a transverse wave speed three-dimensional model of the surrounding rock loose rings of the tunnel at the current moment by analyzing different measuring lines and repeating the steps 1 to 6.
Step 7: and (3) repeating the steps 1 to 6 at different time points to obtain transverse wave speed models of the loose ring of the tunnel surrounding rock at different moments, and obtaining the long-time evolution process of the loose ring of the tunnel surrounding rock. The time interval for analysis can be selected according to specific engineering requirements, for example, the time interval can be analyzed in days when a tunnel is excavated, and the operation period of the tunnel can be analyzed in months. According to the characteristics of the tunnel surrounding rock loosening ring, the speed model is integrally divided into three layers, the same speed representation can be approximately adopted in the same layer, the layer thickness and the speed change are obtained through long-time monitoring inversion, and the visualization process of the tunnel surrounding rock loosening ring along with the time change of the whole monitoring field is obtained through analysis.
By means of the technical scheme, the tunnel surrounding rock loose ring evolution process visualization method provided by the invention has the following advantages compared with the prior art:
(1) The method has the advantages that regional large-scale tunnel surrounding rock loosening ring test and evaluation are realized, the surrounding rock loosening ring is evaluated by the verification of observing hole wall rock by drilling optical imaging through a single drilling hole or longitudinal wave velocity test of the single drilling hole in the prior art, the problem that the surrounding rock loosening ring range cannot be judged in the area outside the test drilling hole exists in the test method. According to the method, the transverse wave speeds of a plurality of measuring lines are obtained through inversion of the environmental noise signals, the range of the loose coil is determined through the transverse wave speeds, and regional large-size testing and evaluation can be achieved.
(2) The method realizes the detection of the long-time evolution process of the loose ring of the tunnel surrounding rock, the test analysis of the long-time evolution process is realized in the prior art, the detection is needed once at intervals, and the acquired data are discrete, time-consuming and labor-consuming. According to the method, by monitoring the background noise for a long time, signals in a time period can be selectively intercepted to invert the transverse wave speed, and a near continuous loose loop evolution process at different moments can be obtained.
(3) Three-dimensional imaging can be realized through observation of different measuring lines of environmental noise, typical noise of tunnels in different periods, such as blasting noise in construction period and traffic noise in operation period, can be effectively utilized, inversion transverse wave velocity profiles can be extracted through dispersion curves of the noise, and a three-dimensional transverse wave velocity model of surrounding rock of the tunnel can be obtained through transverse wave velocity profile results of a plurality of measuring lines.
(4) The transverse wave speed inversion process is restrained by an optical-acoustic combination method, so that the multi-solution property of transverse wave speed inversion can be improved to a great extent, and the inversion stability is improved. According to the method, the drilling optical observation is carried out by introducing a very small amount of drilling holes, the direction of the gradient is updated by restraining the transverse wave speed model through the optical information of the wall of the drilling holes, the false update of transverse wave speed parameters in the inversion process can be avoided, the inversion is prevented from being trapped into a local optimal solution, the inversion is enabled to approach to a global optimal solution as much as possible, and the stability of the inversion is enhanced.
(5) According to the characteristics of the loose rings of the surrounding rocks of the tunnel, the number of layers in the process of inverting the transverse wave speed is fixed, the inversion speed can be effectively accelerated, and the inversion precision is improved. The definition and classification of the tunnel surrounding rock loose rings are different, but are divided into three areas as a whole, and the three areas have obvious differences in transverse wave speed.
Further, as an implementation of the method shown in fig. 1, the embodiment of the invention further provides a visualization device for the evolution process of the loose coil of the surrounding rock of the tunnel, which is used for implementing the method shown in fig. 1. The embodiment of the device corresponds to the embodiment of the method, and for convenience of reading, details of the embodiment of the method are not repeated one by one, but it should be clear that the device in the embodiment can correspondingly realize all the details of the embodiment of the method. As shown in fig. 12, the apparatus includes: an acquisition unit 21, a first determination unit 22, a second determination unit 23, and a third determination unit 24, wherein
An acquisition unit 21 for acquiring noise signals of at least two detectors in the surrounding rock;
A first determining unit 22, configured to determine a corresponding surrounding rock loose coil shear wave velocity curve at a target detector based on a noise signal of the target detector, where the surrounding rock loose coil shear wave velocity curve is related to a depth change;
a second determining unit 23, configured to determine a surrounding rock loose coil shear wave velocity model based on the surrounding rock loose coil shear wave velocity curves corresponding to the at least two detectors;
And a third determining unit 24, configured to acquire the surrounding rock loose coil transverse wave velocity model at a preset period to determine a surrounding rock loose coil evolution process.
Illustratively, the above unit is further configured to:
determining a spatial autocorrelation coefficient based on the noise signal of the target detector and the noise signals of the other detectors;
And determining a dispersion curve based on the spatial autocorrelation coefficient, wherein the dispersion curve is used for representing the dispersion change process of the surface wave propagating along the tunnel side wall.
Illustratively, the determining the dispersion curve based on the spatial autocorrelation coefficients includes:
determining a first zero-order Bessel function based on the spatial autocorrelation coefficients;
And determining the dispersion curve based on the first zero-order Bezier function, wherein the dispersion curve is used for representing the transverse wave speed of the tunnel surrounding rock.
Illustratively, the above unit is further configured to:
Determining propagation speeds of Rayleigh waves at different frequencies along a tunnel side wall based on the first zero-order Bessel function;
And determining a dispersion curve based on the propagation speed of the Rayleigh waves at different frequencies along the side wall of the tunnel.
Illustratively, the determining, based on the noise signal of the target detector, a corresponding surrounding rock trip transverse wave velocity profile at the target detector includes:
And determining a surrounding rock loose coil transverse wave speed curve at the target detector through a least square method and constraint information based on the dispersion curve.
Illustratively, determining the surrounding rock loose coil shear wave velocity curve at the target detector through a least square method and constraint information based on the dispersion curve comprises:
and determining a surrounding rock loose coil transverse wave speed curve at the target detector through a least square method and constraint information based on the dispersion curve and the number of surrounding rock transverse wave speed model layers, wherein the number of transverse wave speed model layers is three based on loose coil layering characteristics.
Illustratively, the above unit is further configured to:
acquiring an optical image of the surrounding rock based on the drilling optical camera to determine RMIBT values;
And determining the constraint condition based on the change of RMIBT values at different moments, wherein the constraint condition is the positive and negative directions of the update quantity of the surrounding rock loose coil transverse wave velocity model.
By means of the technical scheme, the visualization device for the loose ring evolution process of the tunnel surrounding rock provided by the invention solves the problem that a method for accurately monitoring the loose ring evolution process of the tunnel surrounding rock for a long time is lacking at present, and noise signals of at least two detectors in the surrounding rock are obtained; determining a corresponding surrounding rock loosening ring transverse wave speed curve at a target detector based on a noise signal of the target detector, wherein the surrounding rock loosening ring transverse wave speed curve is related to depth change; determining a surrounding rock loose coil transverse wave speed model based on surrounding rock loose coil transverse wave speed curves corresponding to the at least two detectors; and acquiring the surrounding rock loose coil transverse wave velocity model in a preset period to determine the evolution process of the surrounding rock loose coil. In the scheme, typical noises of different periods of a tunnel, such as blasting noises in a construction period and traffic noises in an operation period, are effectively utilized, inversion transverse wave speed profiles are extracted through dispersion curves of the noises, a three-dimensional transverse wave speed model of surrounding rocks of the tunnel can be obtained through transverse wave speed profile results of a plurality of measuring lines, transverse wave speeds of a plurality of measuring lines are obtained through inversion of environmental noise signals, a range of a loose coil is determined through the size of the transverse wave speeds, regional large-size test and evaluation can be realized, and due to a periodic acquisition model, the inversion of the transverse wave speeds of signals in a selective interception period can be carried out through long-term monitoring of background noises, and a near continuous loose coil evolution process at different moments can be obtained.
The processor includes a kernel, and the kernel fetches the corresponding program unit from the memory. The inner core can be provided with one or more than one, and the inner core parameter is adjusted to realize a visualization method of the loose ring evolution process of the tunnel surrounding rock, so that the problem that a method for accurately monitoring the loose ring evolution process of the tunnel surrounding rock for a long time is lacking at present can be solved.
The embodiment of the invention provides a computer readable storage medium, which comprises a stored program, and the program is executed by a processor to realize the visualization method of the tunnel surrounding rock loose-loop evolution process.
The embodiment of the invention provides a processor which is used for running a program, wherein the visualization method for the loose ring evolution process of the tunnel surrounding rock is executed when the program runs.
The embodiment of the invention provides electronic equipment, which comprises at least one processor and at least one memory connected with the processor; the processor is used for calling the program instructions in the memory and executing the tunnel surrounding rock loose-loop evolution process visualization method
An embodiment of the present invention provides an electronic device 30, as shown in fig. 13, where the electronic device includes at least one processor 301, and at least one memory 302 and a bus 303 connected to the processor; wherein, the processor 301 and the memory 302 complete communication with each other through the bus 303; the processor 301 is configured to call the program instructions in the memory to perform the above-mentioned visualization method for the loose-loop evolution process of the tunnel surrounding rock.
The intelligent electronic device herein may be a PC, PAD, cell phone, etc.
The application also provides a computer program product adapted to perform, when executed on a flow management electronic device, a program initialized with the method steps of:
Acquiring noise signals of at least two detectors in surrounding rock;
Determining a corresponding surrounding rock loosening ring transverse wave speed curve at a target detector based on a noise signal of the target detector, wherein the surrounding rock loosening ring transverse wave speed curve is related to depth change;
determining a surrounding rock loose coil transverse wave speed model based on surrounding rock loose coil transverse wave speed curves corresponding to the at least two detectors;
And acquiring the surrounding rock loose coil transverse wave velocity model in a preset period to determine the evolution process of the surrounding rock loose coil.
Further, the method further comprises the following steps:
determining a spatial autocorrelation coefficient based on the noise signal of the target detector and the noise signals of the other detectors;
And determining a dispersion curve based on the spatial autocorrelation coefficient, wherein the dispersion curve is used for representing the dispersion change process of the surface wave propagating along the tunnel side wall.
Further, the determining the dispersion curve based on the spatial autocorrelation coefficient includes:
determining a first zero-order Bessel function based on the spatial autocorrelation coefficients;
And determining the dispersion curve based on the first zero-order Bezier function, wherein the dispersion curve is used for representing the transverse wave speed of the tunnel surrounding rock.
Further, the method further comprises the following steps:
Determining propagation speeds of Rayleigh waves at different frequencies along a tunnel side wall based on the first zero-order Bessel function;
And determining a dispersion curve based on the propagation speed of the Rayleigh waves at different frequencies along the side wall of the tunnel.
Further, the determining, based on the noise signal of the target detector, a corresponding surrounding rock loose coil transverse wave velocity curve at the target detector includes:
And determining a surrounding rock loose coil transverse wave speed curve at the target detector through a least square method and constraint information based on the dispersion curve.
Further, the determining the surrounding rock loose coil transverse wave velocity curve at the target detector through a least square method and constraint information based on the dispersion curve includes:
and determining a surrounding rock loose coil transverse wave speed curve at the target detector through a least square method and constraint information based on the dispersion curve and the number of surrounding rock transverse wave speed model layers, wherein the number of transverse wave speed model layers is three based on loose coil layering characteristics.
Further, the method further comprises the following steps:
acquiring an optical image of the surrounding rock based on the drilling optical camera to determine RMIBT values;
And determining the constraint condition based on the change of RMIBT values at different moments, wherein the constraint condition is the positive and negative directions of the update quantity of the surrounding rock loose coil transverse wave velocity model.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, electronic devices (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable flow management electronic device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable flow management electronic device, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, the electronic device includes one or more processors (CPUs), memory, and a bus. The electronic device may also include input/output interfaces, network interfaces, and the like.
The memory may include volatile memory, random Access Memory (RAM), and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM), among other forms in computer readable media, the memory including at least one memory chip. Memory is an example of a computer-readable medium.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer-readable storage media for a computer include, but are not limited to, phase-change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage electronic devices, or any other non-transmission medium which can be used to store information that can be accessed by the computing electronic device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or electronic device that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or electronic device. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article of manufacture, or electronic device comprising the element.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the application may take the form of a computer program product embodied on one or more computer-usable computer-readable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (4)
1. The method for visualizing the evolution process of the loose rings of the surrounding rocks of the tunnel is characterized by comprising the following steps:
Acquiring noise signals of at least two detectors in surrounding rock;
determining a corresponding surrounding rock loosening ring transverse wave speed curve at a target detector based on a noise signal of the target detector, wherein the surrounding rock loosening ring transverse wave speed curve is related to depth change;
Determining a surrounding rock loose coil transverse wave speed model based on surrounding rock loose coil transverse wave speed curves corresponding to the at least two detectors;
acquiring the surrounding rock loose coil transverse wave velocity model in a preset period to determine the evolution process of the surrounding rock loose coil;
determining a spatial autocorrelation coefficient based on the noise signal of the target detector and the noise signals of the other detectors;
Determining a dispersion curve based on the spatial autocorrelation coefficient, wherein the dispersion curve is used for representing a dispersion change process of the surface wave propagating along the tunnel side wall;
determining a first class of zero-order Bessel functions based on the spatial autocorrelation coefficients;
Determining the dispersion curve based on the first zero-order Bezier function, wherein the dispersion curve is used for representing the transverse wave speed of the tunnel surrounding rock;
Determining propagation speeds of Rayleigh waves at different frequencies along a tunnel side wall based on the first zero-order Bessel function;
determining a dispersion curve based on the propagation speed of the Rayleigh waves at different frequencies along the tunnel side wall;
Determining a surrounding rock loose coil transverse wave speed curve at a target detector through a least square method and constraint information based on the dispersion curve;
Determining a surrounding rock loose coil transverse wave speed curve at a target detector through a least square method and constraint information based on the frequency dispersion curve and the number of surrounding rock transverse wave speed model layers, wherein the number of transverse wave speed model layers is three based on loose coil layering characteristics;
acquiring an optical image of the surrounding rock based on the drilling optical camera to determine RMIBT values;
and determining the constraint condition based on the change of RMIBT values at different moments, wherein the constraint condition is the positive and negative directions of the update quantity of the surrounding rock loose coil transverse wave speed model.
2. A tunnel surrounding rock loose coil evolution process visualization device is characterized in that,
The acquisition unit is used for acquiring noise signals of at least two detectors in the surrounding rock;
The device comprises a first determining unit, a second determining unit and a third determining unit, wherein the first determining unit is used for determining a corresponding surrounding rock loose coil transverse wave speed curve at a target detector based on a noise signal of the target detector, and the surrounding rock loose coil transverse wave speed curve is related to depth change;
the second determining unit is used for determining a surrounding rock loosening ring transverse wave speed model based on the surrounding rock loosening ring transverse wave speed curves corresponding to the at least two detectors;
the third determining unit is used for acquiring the surrounding rock loose coil transverse wave speed model in a preset period to determine the surrounding rock loose coil evolution process;
determining a spatial autocorrelation coefficient based on the noise signal of the target detector and the noise signals of the other detectors;
Determining a dispersion curve based on the spatial autocorrelation coefficient, wherein the dispersion curve is used for representing a dispersion change process of the surface wave propagating along the tunnel side wall;
determining a first class of zero-order Bessel functions based on the spatial autocorrelation coefficients;
Determining the dispersion curve based on the first zero-order Bezier function, wherein the dispersion curve is used for representing the transverse wave speed of the tunnel surrounding rock;
Determining propagation speeds of Rayleigh waves at different frequencies along a tunnel side wall based on the first zero-order Bessel function;
determining a dispersion curve based on the propagation speed of the Rayleigh waves at different frequencies along the tunnel side wall;
Determining a surrounding rock loose coil transverse wave speed curve at a target detector through a least square method and constraint information based on the dispersion curve;
Determining a surrounding rock loose coil transverse wave speed curve at a target detector through a least square method and constraint information based on the frequency dispersion curve and the number of surrounding rock transverse wave speed model layers, wherein the number of transverse wave speed model layers is three based on loose coil layering characteristics;
acquiring an optical image of the surrounding rock based on the drilling optical camera to determine RMIBT values;
and determining the constraint condition based on the change of RMIBT values at different moments, wherein the constraint condition is the positive and negative directions of the update quantity of the surrounding rock loose coil transverse wave speed model.
3. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored program, wherein the steps of visualizing the tunnel surrounding rock loose-loop evolution process as claimed in claim 1 are implemented when the program is executed by a processor.
4. An electronic device comprising at least one processor and at least one memory coupled to the processor; wherein the processor is configured to invoke program instructions in the memory to perform the step of visualizing the tunnel surrounding rock loose-loop evolution process as described in claim 1.
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