Tunnel Advanced Geological Prediction Methods, Terminals and Storage Media

Abstract

This invention provides a method, terminal, and storage medium for tunnel advanced geological prediction. The method includes: acquiring direct and reflected waves generated by excavation blasting at the tunnel face, detected by fiber optic microseismic sensors deployed in the secondary lining section; determining the time accuracy of direct P-waves and direct S-waves based on time-frequency analysis; determining the time accuracy of reflected P-waves and reflected S-waves based on time-frequency analysis; determining the first location of an abnormal geological structure based on the time accuracy of direct and reflected P-waves; determining the second location of the abnormal geological structure based on the time accuracy of direct and reflected S-waves; verifying the first location based on the second location; and outputting the target location of the abnormal geological structure. This invention utilizes tunnel face excavation blasting as the excitation source, combined with P-waves and S-waves, effectively improving the accuracy of tunnel advanced prediction, increasing the prediction frequency, and reducing prediction costs.

Description

Technical Field

[0001] This invention relates to the field of geological exploration, and in particular to a method, terminal and storage medium for advanced geological prediction of tunnels. Background Technology

[0002] Advanced geological forecasting for tunnels involves predicting, during tunnel excavation, the interfaces of lithological changes in the surrounding rock in front of and around the tunnel face (mainly railway tunnels), structural fracture zones, karst and karst development zones, etc., to provide safety assurance for tunnel construction.

[0003] In existing technologies, it is usually necessary to drill holes and blast at the initial support rock to generate an excitation source, and then use various methods such as HSP, TSP, TGP, TRT, TST, negative apparent velocity, etc. for tunnel advanced geological prediction. This is costly, takes up construction time, is inefficient, and has low accuracy. Summary of the Invention

[0004] This invention provides a method, terminal, and storage medium for advanced geological prediction of tunnels, in order to solve the problems of high cost, construction time, low efficiency, and low accuracy in the prior art of geological prediction by drilling and blasting in the initial support surrounding rock.

[0005] In a first aspect, embodiments of the present invention provide a method for advanced geological prediction of tunnels, including:

[0006] The direct and reflected waves generated by the excavation blasting at the tunnel face are obtained by fiber optic microseismic sensors deployed in the secondary lining section; the direct waves include direct P-waves and direct S-waves; the reflected waves include reflected P-waves and reflected S-waves.

[0007] Based on time-frequency analysis, the direct P-wave and direct S-wave are determined to be accurate to the hour based on the direct wave; based on time-frequency analysis, the reflected P-wave and reflected S-wave are determined to be accurate to the hour based on the reflected wave.

[0008] The first location of the anomalous geological structure is determined based on the time accuracy of the direct P-wave and the time accuracy of the reflected P-wave; and the second location of the anomalous geological structure is determined based on the time accuracy of the direct S-wave and the time accuracy of the reflected S-wave.

[0009] The first position is verified based on the second position, and the target location of the abnormal geological structure is output.

[0010] Secondly, embodiments of the present invention provide a terminal device, including a processor and a memory. The memory is used to store computer programs, and the processor is used to call and run the computer programs stored in the memory to perform the steps of the tunnel advanced geological prediction method provided in the first aspect of the present invention.

[0011] Thirdly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the tunnel advanced geological prediction method provided in the first aspect or any possible implementation of the first aspect.

[0012] This invention provides a method, terminal, and storage medium for advanced geological prediction of tunnels. The method includes: acquiring direct and reflected waves generated by excavation blasting at the tunnel face, detected by fiber optic microseismic sensors deployed in the secondary lining section; wherein the direct waves include direct P-waves and direct S-waves; and the reflected waves include reflected P-waves and reflected S-waves; based on time-frequency analysis, determining the time accuracy of the direct P-wave and the direct S-wave; based on time-frequency analysis, determining the time accuracy of the reflected P-wave and the reflected S-wave; determining the first location of an abnormal geological structure based on the time accuracy of the direct P-wave and the reflected P-wave; and determining the second location of the abnormal geological structure based on the time accuracy of the direct S-wave and the reflected S-wave; verifying the first location based on the second location, and outputting the target location of the abnormal geological structure. This invention utilizes tunnel face excavation blasting as the excitation source, eliminating the need for drilling and blasting in the initial support section, thus saving time and space in the tunnel face section where personnel and equipment are concentrated, reducing prediction costs, and improving tunnel construction efficiency and safety. Simultaneously, advanced geological forecasting can be conducted for each construction blast, increasing the frequency of forecasts. Furthermore, this embodiment of the invention combines P-waves and S-waves, effectively improving the accuracy of tunnel advance forecasting. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a flowchart illustrating the implementation of a tunnel advanced geological prediction method provided in an embodiment of the present invention.

[0015] Figure 2 This is a schematic diagram of the arrangement position of the fiber optic microseismic sensor provided in an embodiment of the present invention;

[0016] Figure 3 This is a schematic diagram of the tunnel advanced geological prediction device provided in an embodiment of the present invention;

[0017] Figure 4 This is a schematic diagram of a terminal device provided in an embodiment of the present invention. Detailed Implementation

[0018] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0019] To make the objectives, technical solutions, and advantages of the present invention clearer, specific embodiments will be described below in conjunction with the accompanying drawings.

[0020] See Figure 1 The flowchart illustrating the implementation of the tunnel advanced geological prediction method provided in this embodiment of the invention is shown below:

[0021] The above methods include:

[0022] S101: Acquire the direct and reflected waves generated by the excavation blasting at the tunnel face, detected by fiber optic microseismic sensors deployed in the secondary lining section; wherein, the direct waves include: direct P-waves and direct S-waves; and the reflected waves include: reflected P-waves and reflected S-waves.

[0023] In this embodiment of the invention, the fiber optic microseismic sensor is arranged in the secondary lining section, with reference to... Figure 2 The secondary lining section has been completed. Fiber optic microseismic sensors will be deployed at the tunnel face where construction equipment is densely concentrated and at the branch construction section. Since there is less equipment in the secondary lining section, it is easier to deploy fiber optic microseismic sensors.

[0024] The signal waves generated by blasting during excavation at the tunnel face are directly received by the fiber optic microseismic sensor to the left, and are thus called direct waves. During their propagation through the surrounding rock, P-waves and S-waves encounter anomalous geological structures (interfaces of geological lithological changes, structural fracture zones, karst, and karst development zones, etc.) and are reflected. The signal waves generated by blasting at the tunnel face then travel to the right, reach the anomalous geological structure, are reflected, and are then received by the fiber optic microseismic sensor, and are thus called reflected waves. The direct and reflected waves travel a path twice the distance between the tunnel face and the anomalous geological structure. Therefore, the location of the anomalous geological structure can be determined by using the time difference and wave velocity between the direct and reflected waves, thereby achieving advanced geological prediction.

[0025] Fiber optic microseismic sensors can simultaneously measure P-waves and S-waves. The sensor's optical signal enters an unbalanced Mach-Zehnder interferometer, where the wavelength change is converted into a phase change. After photoelectric conversion, this change is demodulated using PGC. To achieve phase carrier modulation, a high-frequency sinusoidal modulation signal is generated by a signal generator to drive the piezoelectric ceramics on the interferometer arms, thus modulating the phase of the interference signal.

[0026] It should be noted that, for the corresponding fiber optic microseismic sensor, a fiber optic demodulator and an optical cable connecting the microseismic sensor and the demodulator should also be provided.

[0027] S102: Based on time-frequency analysis, determine the direct P-wave and direct S-wave to the time accuracy according to the direct wave; based on time-frequency analysis, determine the reflected P-wave and reflected S-wave to the time accuracy according to the reflected wave.

[0028] S103: Determine the first location of the anomalous geological structure based on the time accuracy of the direct P-wave and the time accuracy of the reflected P-wave; and determine the second location of the anomalous geological structure based on the time accuracy of the direct S-wave and the time accuracy of the reflected S-wave.

[0029] In this embodiment of the invention, the location of abnormal geological structures is determined based on the time difference between direct waves and reflected waves. Therefore, the accurate acquisition of the arrival times of P-waves and S-waves is an important prerequisite for geological prediction. In this embodiment of the invention, the precise arrival times of direct waves and reflected waves are accurately determined based on time-frequency analysis.

[0030] Based on the above, the distance between the abnormal geological structure and the working face can be determined by the time difference between the direct P-wave and the reflected P-wave, which is also the first location of the geological structure.

[0031] In one possible implementation, S103 may include:

[0032] The first position is determined by combining the time accuracy of the direct P-wave and the time accuracy of the reflected P-wave with the second formula.

[0033] The second formula can be:

[0034]

[0035] Δt P =t p2 -t p1

[0036] Among them, L p For the first position; t p2 To reflect P-waves accurately to the hour, t p1 For direct P-waves accurate to the hour, Δt P v is the time interval between the reflected P-wave and the direct P-wave. P This represents the propagation speed of the P-wave.

[0037] Similarly, S103 may also include: determining the second position based on the time accuracy of the direct S-wave and the time accuracy of the reflected S-wave, combined with the third formula;

[0038] The third formula can be:

[0039]

[0040] Δt s =t s2 -t s1

[0041] Among them, L s For the second position; t s2 To reflect the S-wave accurately to the hour, t s1 For direct S-wave accurate to the hour, Δt s v is the time interval between the reflected S-wave and the direct S-wave. s This represents the propagation speed of the S-wave.

[0042] In one possible implementation, prior to S103, the method further includes:

[0043] S105: Obtain the propagation speed of the S-wave and the P-wave.

[0044] For example, the fiber optic microseismic sensor can be a linear array of multiple fiber optic microseismic sensors with a spacing of l; the P-wave and S-wave generated by tunnel construction blasting can be used as test waves, and the wave velocities of the P-wave and S-wave can be obtained by the fiber optic microseismic sensor array deployed in the secondary lining section.

[0045] The propagation velocities of P-waves and S-waves can be obtained by utilizing the spacing *l* between fiber optic microseismic sensors and the time difference between the signals received by different sensors. The specific calculation formulas are as follows:

[0046] v P =l / Δt Pd

[0047] v S =l / Δt Sd

[0048] Where, Δt Pd Let Δt be the time difference between the P-waves received by two fiber optic microseismic sensors spaced l apart. Sd Let be the time difference between the S-waves received by two fiber optic microseismic sensors with a distance of l.

[0049] S104: Verify the first position based on the second position and output the target position of the abnormal geological structure.

[0050] In this embodiment of the invention, the second position is used to verify the first position, and the prediction results of P-wave and S-wave are fused to obtain the final position of the abnormal geological structure, which has higher accuracy.

[0051] Based on the above, this embodiment of the invention utilizes face excavation blasting as the excitation source, eliminating the need for drilling and blasting in the initial support section. This avoids occupying tunnel construction time and space in the densely populated face section, reducing forecasting costs and improving tunnel construction efficiency and safety. Simultaneously, each blast can be used for advanced geological forecasting, increasing forecasting frequency. Furthermore, this embodiment employs time-frequency analysis, accurately picking the arrival times of P-waves and S-waves, improving forecast accuracy. The combined forecasting of P-waves and S-waves further enhances forecast accuracy.

[0052] In one possible implementation, S102 may include:

[0053] S1021: Perform a short-time Fourier transform on the direct wave to obtain the initial power density spectrum, and obtain multiple dominant frequencies of the direct wave based on the initial power density spectrum;

[0054] S1022: Filter the direct wave based on the multiple main frequencies and the preset frequency to obtain the filtered direct wave;

[0055] The seismic signal generated by blasting at the tunnel face is usually at a preset frequency, but the direct and reflected waves detected by fiber optic microseismic sensors always contain noise. Therefore, in this embodiment of the invention, a short-time Fourier transform is performed on the direct wave to obtain multiple dominant frequencies. The dominant frequencies that are far from the preset frequency can be considered noise. Based on this, in this embodiment of the invention, a preset frequency range can be set with the preset frequency as the center to filter out clutter noise outside the preset frequency range, thus improving the accuracy of the signal. The specific filtering method is a conventional technique in the art and will not be described in detail here.

[0056] S1023: The time corresponding to the maximum extreme point of the amplitude in the filtered direct wave is taken as the direct S-wave accurate to the hour;

[0057] S1024: Using the amplitude of the direct S-wave accurate to the hour in the filtered direct wave as the initial value, the direct P-wave accurate to the hour is obtained by iteratively solving forward.

[0058] Because the power and amplitude of the S-wave are greater than those of the P-wave, picking up the S-wave is relatively simple. However, the wave velocity of the P-wave is greater than that of the S-wave, so the P-wave must be received by the fiber optic micro-vibration sensor before the S-wave. Therefore, from a waveform perspective, the P-wave precedes the S-wave, and their waveforms overlap. Therefore, this embodiment of the invention first extracts the peak of the S-wave, that is, the point of maximum amplitude extremum in the filtered direct wave. Then, the precise arrival time of the P-wave is found.

[0059] In one possible implementation, S1024 may include:

[0060] 1. The amplitude of the direct S-wave, accurate to the hour, in the filtered direct wave is taken as the first amplitude, and the amplitude of the wavelet at the moment preceding the first amplitude is taken as the second amplitude.

[0061] 2. Determine whether the first and second amplitudes meet the target conditions;

[0062] 3. If the conditions are met, the time corresponding to the second amplitude in the filtered direct wave is taken as the direct P-wave accurate to the hour.

[0063] 4. If it does not meet the requirements, the current second amplitude is taken as the new first amplitude, and the wavelet amplitude of the previous moment of the current second amplitude is taken as the new second amplitude. Then, the process jumps to the step of determining whether the first amplitude and the second amplitude meet the target conditions and continues to execute.

[0064] In one possible implementation, the target condition can be:

[0065] A1>0∧A2>0

[0066] |A1-A2| <k / 10

[0067] (A1+A2) / 2 <k

[0068] Where A1 is the first amplitude, A2 is the second amplitude, and k is the mathematical expectation of the full wavelet amplitude of the filtered direct wave.

[0069] In this embodiment of the invention, an iterative comparison method is used to sequentially compare the amplitude corresponding to the S-wave peak with the amplitude of the signal wavelet at the previous moment, thereby finding the P-wave peak.

[0070] Furthermore, in this embodiment of the invention, the same method can be used to determine the time accuracy of the reflected P-wave and the time accuracy of the reflected S-wave based on S1021 to S1024, and the specific details will not be repeated here.

[0071] In one possible implementation, S104 includes:

[0072] S1041: Calculate the difference between the first position and the second position;

[0073] S1042: If the difference is not greater than the preset threshold, obtain the joint weight, and determine the target position based on the joint weight, the first position and the second position;

[0074] S1043: If the difference is greater than the preset threshold, output a message indicating that the result is incorrect.

[0075] In this embodiment of the invention, the difference between the first position and the second position is first calculated. If the difference is too large, it indicates that one of the results has a large error. If the difference is small, it indicates that the calculation results of the first position and the second position are relatively accurate. Then, the joint weight is used to determine the target position, which improves the accuracy of the forecast.

[0076] In one possible implementation, S1042 may include:

[0077] The target position is determined based on the joint weight, the first position, the second position, and the first formula.

[0078] The first formula can be:

[0079]

[0080] Among them, L m Let w be the target position, and L be the joint weight. pi L represents the first position corresponding to the i-th explosive source. si The second position corresponding to the i-th blast source, M is the preset quantity.

[0081] Since the blasting points are all located at the working face, the locations of multiple blasts are basically consistent. Therefore, in this embodiment of the invention, P-wave and S-wave predictions are combined, along with the prediction results of multiple blasts, to comprehensively determine the target location, resulting in higher accuracy and more precise calculation results.

[0082] It should be noted that each blast in the face blasting operation involves multiple boreholes blasting simultaneously and continuously. Because the time intervals between multiple borehole blasts in a single blast are small, signals are prone to aliasing. Therefore, in this embodiment of the invention, the first blast (cut-out blast) in each blast can be used as the blast source to determine the first and second positions.

[0083] For example, the direct and reflected waves generated by the cut-hole blast in the first blast are obtained to determine the first and second positions of the first group; the direct and reflected waves generated by the cut-hole blast in the second blast are obtained to determine the first and second positions of the second group; and so on, to obtain multiple groups of first and second positions corresponding to the cut-hole blasts in multiple blasts, and then the target position is obtained by combining with the first formula.

[0084] In one possible implementation, the above method may further include:

[0085] S106: The sliding window method is used to sequentially obtain the first and second positions corresponding to a preset number of blasting sources, and the target positions are obtained by repeated calculations.

[0086] The length of the sliding window is a preset number.

[0087] In this embodiment of the invention, a sliding window can also be set to obtain a preset number of adjacent first and second positions, and the target position is obtained by using joint weights. Because the sliding window method is used, a single blast can calculate a target position, without affecting the prediction frequency.

[0088] It should be noted that the spatial distance accuracy D of geological advance prediction is related to the sampling frequency of the fiber optic microseismic sensor:

[0089]

[0090] Where f is the sampling frequency of the fiber optic microseismic sensor.

[0091] In this embodiment of the invention, the first blast (cut-hole blast) in each blasting operation is used as the blasting source for advanced geological prediction. To avoid interference from the second blast on the signal of the first blast, a certain time interval Δt is required between the first blast (cut-hole blast) and the second blast in each blasting operation. i The longest distance L for advanced geological prediction maxP and L maxS for:

[0092] L maxP =Δt i ·v P

[0093] L maxS =Δt i ·v S

[0094] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0095] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0096] Figure 3 A schematic diagram of the tunnel advanced geological prediction device provided in an embodiment of the present invention is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown, and are described in detail below:

[0097] like Figure 3 As shown, the tunnel advanced geological prediction device includes:

[0098] The parameter acquisition module 21 is used to acquire the direct and reflected waves generated by the excavation blasting at the tunnel face, as detected by the fiber optic microseismic sensors arranged in the secondary lining section; wherein, the direct waves include: direct P-waves and direct S-waves; and the reflected waves include: reflected P-waves and reflected S-waves.

[0099] The time accuracy determination module 22 is used to determine the time accuracy of direct P-wave and direct S-wave based on time-frequency analysis; and to determine the time accuracy of reflected P-wave and reflected S-wave based on reflected waves.

[0100] The first location determination module 23 is used to determine the first location of the anomalous geological structure based on the time accuracy of the direct P-wave and the time accuracy of the reflected P-wave; and to determine the second location of the anomalous geological structure based on the time accuracy of the direct S-wave and the time accuracy of the reflected S-wave.

[0101] The second location determination module 24 is used to verify the first location based on the second location and output the target location of the abnormal geological structure.

[0102] In one possible implementation, the time-accuracy determination module 22 may include:

[0103] The power spectrum transformation unit is used to perform short-time Fourier transform on the direct wave to obtain the initial power density spectrum, and to obtain multiple dominant frequencies of the direct wave based on the initial power density spectrum.

[0104] The filtering unit is used to filter the direct wave based on multiple main frequencies and preset frequencies to obtain the filtered direct wave.

[0105] The first time determination unit is used to determine the time corresponding to the maximum extreme point of the amplitude in the filtered direct wave as the accurate time of the direct S-wave.

[0106] The second time determination unit is used to iteratively solve for the accurate time of the direct S-wave by taking the amplitude of the direct S-wave in the filtered direct wave as the initial value.

[0107] In one possible implementation, the second time-determining unit may specifically be used for:

[0108] 1. The amplitude of the direct S-wave, accurate to the hour, in the filtered direct wave is taken as the first amplitude, and the amplitude of the wavelet at the moment preceding the first amplitude is taken as the second amplitude.

[0109] 2. Determine whether the first and second amplitudes meet the target conditions;

[0110] 3. If the conditions are met, the time corresponding to the second amplitude in the filtered direct wave is taken as the direct P-wave accurate to the hour.

[0111] 4. If it does not meet the requirements, the current second amplitude is taken as the new first amplitude, and the wavelet amplitude of the previous moment of the current second amplitude is taken as the new second amplitude. Then, the process jumps to the step of determining whether the first amplitude and the second amplitude meet the target conditions and continues to execute.

[0112] In one possible implementation, the target condition can be:

[0113] A1>0∧A2>0

[0114] |A1-A2| <k / 10

[0115] (A1+A2) / 2 <k

[0116] Where A1 is the first amplitude, A2 is the second amplitude, and k is the mathematical expectation of the full wavelet amplitude of the filtered direct wave.

[0117] In one possible implementation, the second position determination module 24 may include:

[0118] The difference calculation unit is used to calculate the difference between the first position and the second position.

[0119] The first judgment unit is used to obtain the joint weight if the difference is not greater than a preset threshold, and determine the target position based on the joint weight, the first position and the second position.

[0120] The second judgment unit is used to output information indicating that the result is incorrect if the difference is greater than a preset threshold.

[0121] In one possible implementation, the first determination unit may include:

[0122] The target position is determined based on the joint weight, the first position, the second position, and the first formula.

[0123] The first formula can be:

[0124]

[0125] Among them, L m Let w be the target position, and L be the joint weight. pi L represents the first position corresponding to the i-th explosive source. si The second position corresponding to the i-th blast source, M is the preset quantity.

[0126] In one possible implementation, the above-described apparatus may further include:

[0127] The sliding window module is used to sequentially obtain the first and second positions corresponding to a preset number of blasting sources using the sliding window method, and repeatedly calculates to obtain the position of each target.

[0128] The length of the sliding window is a preset number.

[0129] In one possible implementation, the first position determination module 23 may be specifically used for:

[0130] The first position is determined by combining the time accuracy of the direct P-wave and the time accuracy of the reflected P-wave with the second formula; the second formula can be:

[0131]

[0132] Δt P =t p2 -t p1

[0133] Among them, L p For the first position; t p2 To reflect P-waves accurately to the hour, t p1 For direct P-waves accurate to the hour, Δt P v is the time interval between the reflected P-wave and the direct P-wave. P This represents the propagation speed of the P-wave.

[0134] Figure 4 This is a schematic diagram of the terminal device 3 provided in an embodiment of the present invention. Figure 4 As shown, the terminal device 3 in this embodiment includes a processor 30 and a memory 31. The memory 31 is used to store a computer program 32, and the processor 30 is used to call and run the computer program 32 stored in the memory 31 to execute the steps in the various tunnel advanced geological prediction method embodiments described above, for example... Figure 1 The steps S101 to S104 are shown. Alternatively, the processor 30 is used to call and run the computer program 32 stored in the memory 31 to implement the functions of each module / unit in the above-described device embodiments, for example... Figure 3 The functions of modules 21 to 24 are shown.

[0135] For example, computer program 32 can be divided into one or more modules / units, one or more of which are stored in memory 31 and executed by processor 30 to complete the present invention. One or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 32 in terminal device 3. For example, computer program 32 can be divided into... Figure 3 Modules / units 21 to 24 are shown.

[0136] Terminal device 3 can be a computing device such as a desktop computer, laptop, handheld computer, or cloud server. Terminal device 3 may include, but is not limited to, processor 30 and memory 31. Those skilled in the art will understand that... Figure 4 This is merely an example of terminal device 3 and does not constitute a limitation on terminal device 3. It may include more or fewer components than shown, or combine certain components, or different components. For example, the terminal may also include input / output devices, network access devices, buses, etc.

[0137] The processor 30 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0138] The memory 31 can be an internal storage unit of the terminal device 3, such as a hard disk or RAM of the terminal device 3. The memory 31 can also be an external storage device of the terminal device 3, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the terminal device 3. Furthermore, the memory 31 can include both internal and external storage units of the terminal device 3. The memory 31 is used to store computer programs and other programs and data required by the terminal. The memory 31 can also be used to temporarily store data that has been output or will be output.

[0139] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0140] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0141] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0142] In the embodiments provided by this invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0143] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0144] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0145] If an integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0146] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method of tunnel advance geological prediction, characterized in that, The method comprises: obtaining direct waves and reflected waves generated by excavation blasting of a working face, wherein the direct waves comprise direct P waves and direct S waves, and the reflected waves comprise reflected P waves and reflected S waves; determining the direct P wave arrival time and the direct S wave arrival time based on time-frequency analysis of the direct waves, and determining the reflected P wave arrival time and the reflected S wave arrival time based on time-frequency analysis of the reflected waves; determining a first position of an abnormal geological structure based on the direct P wave arrival time and the reflected P wave arrival time, and determining a second position of the abnormal geological structure based on the direct S wave arrival time and the reflected S wave arrival time; verifying the first position based on the second position, and outputting a target position of the abnormal geological structure; the verifying the first position based on the second position, and outputting a target position of the abnormal geological structure, comprises: calculating a difference between the first position and the second position; if the difference is not greater than a preset threshold, obtaining a joint weight, and determining the target position based on the joint weight, the first position and the second position; if the difference is greater than the preset threshold, outputting information that the result is incorrect; the determining the target position based on the joint weight, the first position and the second position, comprises: determining the target position based on the joint weight, the first position and the second position, and a first formula; the first formula is: in, For the target location, For the joint weight, For the first The first position corresponding to each explosive source No. The second position corresponding to each explosive source For preset quantity; obtaining the first position and the second position corresponding to the preset number of blasting sources in turn by using a sliding window method, and repeatedly calculating to obtain each target position; wherein the length of the sliding window is the preset number.

2. The tunnel advance geological prediction method according to claim 1, characterized in that, the determining the direct P wave arrival time and the direct S wave arrival time based on time-frequency analysis of the direct waves, comprises: performing short-time Fourier transform on the direct waves to obtain an initial power density spectrum, and obtaining a plurality of main frequencies of the direct waves based on the initial power density spectrum; filtering the direct waves based on the plurality of main frequencies and a preset frequency to obtain filtered direct waves; taking the time corresponding to the maximum extreme point of the amplitude in the filtered direct waves as the direct S wave arrival time; taking the amplitude of the direct S wave arrival time in the filtered direct waves as an initial value, and iteratively solving forward to obtain the direct P wave arrival time.

3. The tunnel advance geological prediction method according to claim 2, characterized in that, the taking the amplitude of the direct S wave arrival time in the filtered direct waves as an initial value, and iteratively solving forward to obtain the direct P wave arrival time, comprises: taking the amplitude of the direct S wave arrival time in the filtered direct waves as a first amplitude, and taking the wavelet amplitude at the time point one time before the first amplitude as a second amplitude; determining whether the first amplitude and the second amplitude meet a target condition; if yes, taking the time corresponding to the second amplitude in the filtered direct waves as the direct P wave arrival time. If not, the current second amplitude is taken as a new first amplitude, and a wavelet amplitude at a previous time of the current second amplitude is taken as a new second amplitude, and the step of determining whether the first amplitude and the second amplitude meet the target condition is continued.

4. The tunnel advance geological prediction method according to claim 3, characterized in that, The target condition is: wherein is the first amplitude, is the second amplitude, is the mathematical expectation of the filtered direct wave full wavelet amplitudes.

5. The tunnel advance geological prediction method according to claim 1, characterized in that, The first position of the abnormal geological structure is determined according to the direct P-wave arrival time and the reflected P-wave arrival time, comprising: The first position is determined according to the direct P-wave arrival time and the reflected P-wave arrival time in combination with a second formula. The second formula is: wherein, is the first location; is the reflected P-wave arrival time, is the direct P-wave arrival time, is the time interval between the reflected P-wave and the direct P-wave, is the P-wave propagation velocity.

6. A terminal device, characterized by comprising: The tunnel advance geological prediction method comprises a processor and a memory, the memory is used for storing a computer program, and the processor is used for calling and running the computer program stored in the memory to execute the steps of the tunnel advance geological prediction method according to any one of claims 1 to 5.

7. A computer-readable storage medium storing a computer program, wherein the computer program comprises the following steps of: receiving a request for a resource from a client; determining whether the client is authorized to access the resource; and if the client is authorized to access the resource, providing the resource to the client. The computer program is executed by the processor to implement the steps of the tunnel advance geological prediction method according to any one of claims 1 to 5.

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