Comprehensive advanced forecasting and intelligent interpretation method and system for moraine stratum

Abstract

The invention belongs to the technical field of tunnel construction, and discloses a comprehensive advanced forecasting and intelligent interpretation method and system for moraine stratum.The method comprises the steps that a large-depth radar is used for detecting the geological condition of a certain depth underground of an unexcavated section, and a high-risk area is delineated; in the excavation process, a seismic wave method and a geological radar method are adopted for detecting the area within a certain range in front of the tunnel face, and a block stone enrichment area is delineated; adopting an induced polarization method to carry out moraine water-abundance detection on an area in a certain range in front of the tunnel face, and judging the water-abundance of a moraine stratum; based on the detection result, parameter distribution is obtained, the parameter distribution is integrated, and comprehensive interpretation of the moraine body structure and the water yield property is achieved through the weight coefficient. According to the method, comprehensive detection is carried out by utilizing multiple detection methods, parameter quantitative characterization of an advanced geological forecast result is realized, intelligent interpretation of a moraine stratum structure and a water yield property is realized, and a powerful support is provided for safe construction of a moraine stratum tunnel.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel construction, and in particular to a comprehensive advance prediction and intelligent interpretation method and system for moraine strata. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Moraine is a special rock and soil body formed by the accumulation of a large amount of debris transported by glaciers. It is widely distributed in the western plateau area of ​​my country and has become a geological problem that must be faced in the construction of plateau transportation trunk lines, especially tunnel construction. The freeze-thaw action of moraine in the plateau area brings disaster risks and safety challenges to the construction of tunnels, especially the entrance section. The construction of moraine tunnels mainly faces serious problems such as landslides, water and mud gushing.

[0004] The moraine strata are mainly composed of moraine breccia soil, crushed stone soil with blocks and boulders, with uneven structure and obvious anisotropic mechanical characteristics. Due to the poor self-stability of the surrounding rock after the stratum disturbance, there are risks such as poor cementation of the rock and soil, disintegration when exposed to water, and collapse. These characteristics have a great impact on the stability of tunnel construction and subsequent projects, and corresponding prevention and reinforcement measures need to be taken during the construction process.

[0005] In terms of early detection and treatment of moraine strata, commonly used detection methods for tunnel construction include seismic wave reflection method, transient electromagnetic method and engineering geological drilling method. Although these methods have been applied to a certain extent in tunnels, they still have problems such as insufficient resolution, unclear characterization of moraine rock-soil-water coupling characteristics, and lack of effective solutions for multi-means comprehensive detection and multi-parameter interpretation. The interpretation methods for the degree of fragmentation and water-richness of moraine strata mostly rely on human experience, and often lead to many problems such as improper advanced prediction methods, misreporting and omissions, and failure to identify water-rich risks in advance, which bring about a series of problems such as increased construction safety risks, delayed construction period, and increased investment costs. Summary of the invention

[0006] In order to solve the above problems, the present invention proposes a comprehensive advanced prediction and intelligent interpretation method and system for moraine strata, which uses a variety of complementary detection methods for comprehensive detection, realizes parameter quantitative characterization of advanced geological prediction results, and uses the parameter quantitative characterization results to realize intelligent interpretation of the structure and water-richness of the moraine strata, providing strong support for the safe construction of tunnels in moraine strata.

[0007] In order to achieve the above object, the present invention adopts the following technical solution: In a first aspect, the present invention provides a comprehensive advance prediction and intelligent interpretation method for moraine strata, comprising the following steps: Before or during tunnel excavation, use deep-depth radar to detect the geological conditions at a certain depth underground in the unexcavated section along the tunnel excavation axis to delineate high-risk areas in moraine strata; During tunnel excavation, seismic wave method and geological radar method are used to detect the area within a certain range in front of the tunnel face to delineate the rock-rich area; The induced polarization method is used to detect the water content of the moraine in a certain range in front of the tunnel face to determine the water content of the moraine strata; Based on the above detection results, the parameter distribution of the detection results is obtained, and the parameter distribution of the detection results is integrated to achieve a comprehensive interpretation of the moraine structure and water-richness using the weight coefficient.

[0008] As an optional implementation, the deep-depth radar uses a full waveform inversion method to conduct a long-distance general survey of the unexcavated section near the tunnel entrance, and the detection area is 30 to 50 meters underground; The induced polarization method adopts a multi-scale, multi-parameter inversion method to detect the water-richness of the moraine in front of the tunnel face every 30 to 40 meters to determine the water content of the moraine strata.

[0009] As an optional implementation, the seismic wave method uses a full waveform inversion method to perform long-distance prediction of the geological conditions ahead of the tunnel face every 100-120 m; The geological radar method uses a full waveform inversion method to perform high-resolution prediction of the geological conditions in front of the tunnel face every 30±5m, and to review and refine the long-distance prediction results.

[0010] As an optional implementation, the parameter distribution of the detection result is obtained, specifically: Process the detection data of deep-depth radar and geological radar respectively to obtain the electromagnetic wave reflection coefficient and relative dielectric constant of the detection area; Process the seismic wave detection data to obtain the seismic reflection coefficient, longitudinal wave velocity, shear wave velocity and density of the detection area; The induced polarization detection data is processed to obtain the resistivity and polarizability of the detection area.

[0011] As an optional implementation method, weight coefficients are used to achieve comprehensive interpretation of moraine structure, specifically: The geological radar method and seismic wave method are combined to interpret the moraine structure, and the comprehensive judgment value is Areas with a value greater than the set threshold are considered to have loose, weathered, poor quality, and high construction risk. Areas below the set threshold are considered to have hard, dense, good quality surrounding rocks and low construction risk;

[0012] in, For deep-depth radar detection of electromagnetic wave reflection coefficient, Relative dielectric constant for deep-depth radar detection, The seismic wave method is used to detect the seismic wave reflection coefficient. The seismic wave method is used to detect the longitudinal velocity of seismic waves. The seismic wave method is used to detect the shear wave velocity of seismic waves. To detect seismic wave density using the seismic wave method, The electromagnetic wave reflection coefficient detected by geological radar, Detect relative dielectric constant for geological radar.

[0013] As an optional implementation method, a weight coefficient is used to achieve a comprehensive interpretation of the water-richness of the moraine, specifically: The water-richness of moraine is determined by combining geological radar and induced polarization methods. Areas with a value greater than the set threshold are considered to have high water content and a high risk of water inrush. Areas below the set threshold are considered to have low water content and low risk of water inrush;

[0014] in, For deep-depth radar detection of electromagnetic wave reflection coefficient, Relative dielectric constant for deep-depth radar detection, The electromagnetic wave reflection coefficient detected by geological radar, To detect the relative dielectric constant of the geological radar, To detect resistivity using the induced polarization method, To detect the polarizability using the intracavity induced polarization method.

[0015] In a second aspect, the present invention provides a comprehensive advance prediction and intelligent interpretation system for moraine strata, comprising: The deep-depth radar detection module is configured to: before or during tunnel excavation, use the deep-depth radar to detect the geological conditions of a certain depth underground in the unexcavated section along the tunnel excavation axis to delineate high-risk areas of moraine strata; The seismic wave and geological radar detection module is configured to: during tunnel excavation, use the seismic wave method and the geological radar method to detect the area within a certain range in front of the tunnel face, and delineate the rock-rich area; The induced polarization detection module is configured to: use the induced polarization method to detect the water-richness of the moraine in a certain range in front of the tunnel face, and determine the water content of the moraine strata; The comprehensive interpretation module is configured to: based on the above detection results, obtain the parameter distribution of the detection results, integrate the parameter distribution of the detection results, and use the weight coefficient to achieve a comprehensive interpretation of the moraine structure and water richness.

[0016] In a third aspect, the present invention provides an electronic device comprising a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the method described in the first aspect is performed.

[0017] In a fourth aspect, the present invention provides a computer-readable storage medium for storing computer instructions, wherein when the computer instructions are executed by a processor, the method described in the first aspect is performed.

[0018] In a fifth aspect, the present invention provides a computer program product, comprising a computer program, which, when executed by a processor, implements the method described in the first aspect.

[0019] Compared with the prior art, the present invention has the following beneficial effects: The specific detection methods in the comprehensive advance prediction and intelligent interpretation method of moraine strata provided by the present invention have clear relationships with each other and are reasonably designed, the detection results of various methods complement each other, the connection between each step is properly arranged, the overall design is reasonable, the operation is simple, and the comprehensive detection effect is good.

[0020] The present invention abandons the original method of interpreting the advanced forecast results that relies on manual experience, realizes the parameter quantitative characterization of the advanced geological forecast results, and provides a quantitative parameter basis for further interpreting the risk of tunnel construction in moraine strata.

[0021] The comprehensive advance prediction and intelligent interpretation method of moraine strata provided by the present invention realizes intelligent interpretation of moraine strata structure and water-richness by comprehensive application of parameter quantitative characterization results. The interpretation results are reliable and provide strong support for the safe construction of moraine strata tunnels.

[0022] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0024] Figure 1 A flow chart of the comprehensive advance prediction and intelligent interpretation method of moraine strata provided in Example 1 of the present invention; Figure 2A schematic diagram of surface deep-depth radar detection provided by Example 1 of the present invention; Figure 3 A schematic diagram of in-cave seismic wave detection provided by Example 1 of the present invention; Figure 4 A schematic diagram of in-tunnel geological radar detection provided by Example 1 of the present invention; Figure 5 Schematic diagram of in-hole induced polarization detection provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0025] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0026] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0027] It should be noted that the terms used herein are only for describing specific embodiments, and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that the terms "include" and "have" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0029] Example 1 like Figure 1 As shown, this embodiment provides a comprehensive advance prediction and intelligent interpretation method for moraine strata, comprising the following steps: S1. Before or during tunnel excavation, use deep-depth radar to detect the geological conditions at a certain depth underground in the unexcavated section along the tunnel excavation axis to delineate high-risk areas in moraine strata; S2. During tunnel excavation, the seismic wave method and geological radar method are used to detect the area within a certain range in front of the tunnel face to delineate the rock-rich area; S3. Use the induced polarization method to detect the water content of the moraine in a certain range in front of the tunnel face to determine the water content of the moraine strata; S4. Based on the above detection results, the parameter distribution of the detection results is obtained, the parameter distribution of the detection results is integrated, and the weight coefficient is used to realize the comprehensive interpretation of the moraine structure and water richness.

[0030] Surface deep-depth radar detection, such as Figure 2 As shown in the figure, before or during the excavation of a tunnel in the moraine stratum, a large-depth geological radar is used with a full waveform inversion method in the tunnel excavation area, especially above the tunnel entrance, to detect the geological conditions 30 to 50 meters underground in the unexcavated section along the tunnel excavation axis. A long-distance general survey of the geological conditions along the tunnel entrance with the greatest danger is carried out to delineate high-risk areas in the moraine stratum that require special attention.

[0031] Long-distance detection by seismic wave method in caves, such as Figure 3 As shown in the figure, during the construction process in the moraine stratum, the seismic wave method was used to conduct long-distance detection of the area within 100~120m in front of the tunnel face to delineate the rock-rich area.

[0032] High-resolution geological radar detection in caves, such as Figure 4 As shown in the figure, during the construction process in the moraine stratum, the geological radar method was used to conduct high-resolution detection of the area within 30±5m in front of the tunnel face, and the prediction results of the seismic wave method were reviewed and refined.

[0033] Induced polarization water-rich detection in caves, such as Figure 5 As shown in the figure, during the construction process of moraine strata, the induced polarization method is used to detect the water-richness of the moraine in the area within 30 to 40 meters in front of the tunnel face to determine the water content of the moraine strata.

[0034] Based on the original detection data of deep-depth radar, seismic wave method, geological radar method and induced polarization method, full waveform inversion, multi-scale inversion and other methods are used to obtain the distribution of parameters such as seismic wave velocity, relative dielectric constant, resistivity, polarizability, etc., to achieve parametric characterization of the forecast results.

[0035] The parameterized representation of the forecast results is specifically: The full waveform inversion method of geological radar is used to process the detection data of surface deep-depth radar and in-cave geological radar to obtain the electromagnetic wave reflection coefficient and relative dielectric constant of the detection area.

[0036] The seismic wave full waveform inversion method is used to process the in-tunnel seismic wave detection data to obtain the seismic reflection coefficient, longitudinal wave velocity, shear wave velocity and density of the detection area.

[0037] The induced polarization multi-scale inversion method is used to process the in-hole induced polarization detection data to obtain the resistivity and polarizability of the detection area.

[0038] The distribution of parameters such as seismic wave velocity, relative dielectric constant, resistivity, polarizability, etc. is integrated, and weight coefficients are used to achieve a comprehensive interpretation of the till structure and water content.

[0039] Intelligent interpretation of moraine structure, specifically: The structure is interpreted by combining geological radar and seismic wave methods, and the comprehensive judgment value is Areas with a value greater than 0.5 are considered to have loose, weathered, poor quality, and high construction risk. Areas with a value less than 0.5 are considered to have hard, dense, good quality, and low construction risk.

[0040]

[0041] in, : The electromagnetic wave reflection coefficient of the surface deep-depth radar detection is 1 when it is ≥ 0.3, otherwise it is 0; : When the relative dielectric constant of the surface deep-depth radar detection is less than 2 or greater than 30, it is 1, otherwise it is 0; : When the seismic wave reflection coefficient detected by the in-tunnel seismic wave method is ≥ 0.3, it is 1, otherwise it is 0; : When the longitudinal wave velocity of seismic waves detected by the in-tunnel seismic wave method is less than 2000m / s, it is 1, otherwise it is 0; : When the shear wave velocity of seismic waves detected by the in-tunnel seismic wave method is less than 700 m / s, it is 1, otherwise it is 0; : When the seismic wave density detected by the in-cave seismic wave method is less than 2.0 g / cm³, it is 1, otherwise it is 0; : The reflection coefficient of electromagnetic waves detected by geological radar in the cave is 1 when it is ≥ 0.3, otherwise it is 0; :When the relative dielectric constant detected by geological radar in the cave is <2 or >30, it is 1, otherwise it is 0.

[0042] Intelligent interpretation of water-richness of moraine, specifically: The structure is interpreted by combining the geological radar method and the induced polarization method, and the comprehensive judgment value is Areas with a value greater than 0.5 are considered to have high water content and a high risk of water inrush. Areas with a value less than 0.5 are considered to have low water content and a low risk of water inrush.

[0043]

[0044] in, : The reflection coefficient of electromagnetic waves detected by deep-surface radar is 1 when it is ≥ 0.3, otherwise it is 0; : When the relative dielectric constant of the surface deep-depth radar detection is greater than 30, it is 1, otherwise it is 0; : The reflection coefficient of electromagnetic waves detected by geological radar in the cave is 1 when it is ≥ 0.3, otherwise it is 0; : The relative dielectric constant of the geological radar detection in the cave is 1 when it is greater than 30, otherwise it is 0; : When the resistivity detected by the in-hole induced polarization method is ≤50Ω·m, it is 1, otherwise it is 0; :When the polarization rate detected by the in-hole induced polarization method is ≥ 0.1, it is 1, otherwise it is 0.

[0045] Example 2 This embodiment provides a comprehensive advance prediction and intelligent interpretation system for moraine strata, including: The deep-depth radar detection module is configured to: before or during tunnel excavation, use the deep-depth radar to detect the geological conditions of a certain depth underground in the unexcavated section along the tunnel excavation axis to delineate high-risk areas of moraine strata; The seismic wave and geological radar detection module is configured to: during tunnel excavation, use the seismic wave method and the geological radar method to detect the area within a certain range in front of the tunnel face, and delineate the rock-rich area; The induced polarization detection module is configured to: use the induced polarization method to detect the water-richness of the moraine in a certain range in front of the tunnel face, and determine the water content of the moraine strata; The comprehensive interpretation module is configured to: based on the above detection results, obtain the parameter distribution of the detection results, integrate the parameter distribution of the detection results, and use the weight coefficient to achieve a comprehensive interpretation of the moraine structure and water richness.

[0046] It should be noted that the above modules correspond to the steps described in Example 1, and the examples and application scenarios implemented by the above modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above Example 1. It should be noted that the above modules, as part of the system, can be executed in a computer system such as a set of computer executable instructions.

[0047] In further embodiments, there is also provided: An electronic device includes a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the method described in Embodiment 1 is performed. For the sake of brevity, it will not be described in detail here.

[0048] It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general-purpose processors, digital signal processors DSP, application-specific integrated circuits ASIC, off-the-shelf programmable gate arrays FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0049] The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.

[0050] A computer-readable storage medium is used to store computer instructions, and when the computer instructions are executed by a processor, the method described in Example 1 is completed.

[0051] The method in Example 1 can be directly embodied as a hardware processor, or a combination of hardware and software modules in the processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware. To avoid repetition, it is not described in detail here.

[0052] A computer program product includes a computer program, and when the computer program is executed by a processor, the method described in embodiment 1 is implemented.

[0053] The present invention also provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer executable instructions, such as instructions included in a program module, which are executed in a device on a real or virtual processor of the target to perform the process / method as described above. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc. that perform specific tasks or implement specific abstract data types. In various embodiments, the functions of program modules can be combined or divided between program modules as needed. Machine executable instructions for program modules can be executed in local or distributed devices. In distributed devices, program modules can be located in local and remote storage media.

[0054] The computer program code for implementing the method of the present invention can be written in one or more programming languages. These computer program codes can be provided to the processor of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the computer or other programmable data processing device, causes the function / operation specified in the flow chart and / or block diagram to be implemented. The program code can be executed completely on a computer, partially on a computer, as an independent software package, partially on a computer and partially on a remote computer or completely on a remote computer or server.

[0055] In the context of the present invention, computer program codes or related data may be carried by any appropriate carrier to enable a device, apparatus or processor to perform the various processes and operations described above. Examples of carriers include signals, computer readable media, and the like. Examples of signals may include electrical, optical, radio, acoustic or other forms of propagation signals, such as carrier waves, infrared signals, and the like.

[0056] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with this embodiment can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0057] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A comprehensive advance prediction and intelligent interpretation method for moraine strata, characterized in that: The following steps are involved: Before or during tunnel excavation, use deep-depth radar to detect the geological conditions at a certain depth underground in the unexcavated section along the tunnel excavation axis to delineate high-risk areas in moraine strata; During tunnel excavation, seismic wave method and geological radar method are used to detect the area within a certain range in front of the tunnel face to delineate the rock-rich area; The induced polarization method is used to detect the water content of the moraine in a certain range in front of the tunnel face to determine the water content of the moraine strata; Based on the above detection results, the parameter distribution of the detection results is obtained, and the parameter distribution of the detection results is integrated to achieve a comprehensive interpretation of the moraine structure and water-richness using the weight coefficient.

2. The method for comprehensive advance prediction and intelligent interpretation of moraine strata according to claim 1, characterized in that: The deep-depth radar uses the full waveform inversion method to conduct long-distance general surveys of the unexcavated section near the tunnel entrance, with the detection area covering 30 to 50 meters underground. The induced polarization method adopts a multi-scale, multi-parameter inversion method to detect the water-richness of the moraine in front of the tunnel face every 30 to 40 meters to determine the water content of the moraine strata.

3. The method for comprehensive advance prediction and intelligent interpretation of moraine strata according to claim 1, characterized in that: The seismic wave method uses a full waveform inversion method to perform long-distance prediction of the geological conditions ahead of the tunnel face every 100 to 120 meters; The geological radar method uses a full waveform inversion method to perform high-resolution prediction of the geological conditions in front of the tunnel face every 30±5m, and to review and refine the long-distance prediction results.

4. The method for comprehensive advance prediction and intelligent interpretation of moraine strata according to claim 1, characterized in that: Get the parameter distribution of the detection results, specifically: Process the detection data of deep-depth radar and geological radar respectively to obtain the electromagnetic wave reflection coefficient and relative dielectric constant of the detection area; Process the seismic wave detection data to obtain the seismic reflection coefficient, longitudinal wave velocity, shear wave velocity and density of the detection area; The induced polarization detection data is processed to obtain the resistivity and polarizability of the detection area.

5. The method for comprehensive advance prediction and intelligent interpretation of moraine strata according to claim 1, characterized in that: The weight coefficient is used to realize the comprehensive interpretation of moraine structure, specifically: The geological radar method and seismic wave method are combined to interpret the moraine structure, and the comprehensive judgment value is Areas with a value greater than the set threshold are considered to have loose, weathered, poor quality, and high construction risk. Areas below the set threshold are considered to have hard, dense, good quality surrounding rocks and low construction risk; in, For deep-depth radar detection of electromagnetic wave reflection coefficient, Relative dielectric constant for deep-depth radar detection, The seismic wave method is used to detect the seismic wave reflection coefficient. The seismic wave method is used to detect the longitudinal velocity of seismic waves. The seismic wave method is used to detect the shear wave velocity of seismic waves. To detect seismic wave density using the seismic wave method, The electromagnetic wave reflection coefficient detected by geological radar, Detect relative dielectric constant for geological radar.

6. The method for comprehensive advance prediction and intelligent interpretation of moraine strata according to claim 1, characterized in that: The weight coefficient is used to realize the comprehensive interpretation of the water-richness of moraine, specifically: The water-richness of moraine is determined by combining geological radar and induced polarization methods. Areas with a value greater than the set threshold are considered to have high water content and a high risk of water inrush. Areas below the set threshold are considered to have low water content and low risk of water inrush; in, For deep-depth radar detection of electromagnetic wave reflection coefficient, Relative dielectric constant for deep-depth radar detection, The electromagnetic wave reflection coefficient detected by geological radar, To detect the relative dielectric constant of the geological radar, To detect resistivity using the induced polarization method, To detect the polarizability using the intracavity induced polarization method.

7. A comprehensive advance prediction and intelligent interpretation system for moraine strata, characterized in that: include: The deep-depth radar detection module is configured to: before or during tunnel excavation, use the deep-depth radar to detect the geological conditions of a certain depth underground in the unexcavated section along the tunnel excavation axis to delineate high-risk areas of moraine strata; The seismic wave and geological radar detection module is configured to: during tunnel excavation, use the seismic wave method and the geological radar method to detect the area within a certain range in front of the tunnel face, and delineate the rock-rich area; The induced polarization detection module is configured to: use the induced polarization method to detect the water-richness of the moraine in a certain range in front of the tunnel face, and determine the water content of the moraine strata; The comprehensive interpretation module is configured to: based on the above detection results, obtain the parameter distribution of the detection results, integrate the parameter distribution of the detection results, and use the weight coefficient to achieve a comprehensive interpretation of the moraine structure and water richness.

8. An electronic device, characterized in that: The method comprises a memory and a processor and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the method according to any one of claims 1 to 6 is completed.

9. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, complete the method described in any one of claims 1 to 6.

10. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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