Tunnel face geological risk prediction method, device, equipment, system and medium

Abstract

The invention relates to a tunnel face geological risk prediction method, a device, equipment, a system and a medium, in particular to the technical field of geological forecast. A known geological data sample is composed of geological survey data of a tunnel, a geological longitudinal section diagram and a cross section diagram of the tunnel and a design drawing of the tunnel; the method comprises the following steps: determining a current geological grade of a tunnel face, scanning a geological body in front of the tunnel face according to the current geological grade to obtain scanning data of the tunnel face, obtaining a scanning image of the tunnel face according to the scanning data, and processing the scanning image to determine dryness and humidity data of the tunnel face, and performing geological risk prediction on the tunnel face according to the dryness and humidity data to obtain a geological risk prediction result, so that the method has a function of performing geological risk prediction on the tunnel face. The tunnel face can be subjected to multi-region simultaneous prediction, and the prediction efficiency is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of geological prediction, and in particular to a method, device, equipment, system and medium for predicting geological risks of a tunnel face. Background Art

[0002] In the field of highway tunnel construction, the complexity of the geological environment and the uncertainty of construction conditions have always been major challenges to engineering safety and efficiency. With the development of technology, tunnel face risk prediction technology has emerged, aiming to predict and avoid potential geological risks through analysis of geological sketches and intelligent evaluation. The development path of this technology has gradually shifted from relying on the experience and qualitative analysis of geological experts to quantitative analysis using a large amount of data collected by geological exploration technology.

[0003] At present, the risk prediction technology of tunnel face has made some progress. The continuous improvement of geological data collection and recording technology has enabled the systematic collection of key geological information such as rock type, structure, groundwater level, soil moisture, etc. On this basis, some geological risk assessment methods have begun to try to apply statistical analysis and machine learning algorithms to assist prediction. These methods have shown certain effectiveness in specific data types or geological environments, but they still face the challenges of data complexity and environmental variability.

[0004] Although the existing tunnel face risk prediction technology has made progress in some aspects, it still has obvious shortcomings. In the existing technology, when performing risk prediction, usually only one risk is predicted, which affects the prediction efficiency. Summary of the invention

[0005] The main purpose of the present invention is to propose a method, device, equipment, system and medium for predicting geological risks of a tunnel face, aiming to solve the technical problem that when performing risk prediction, related technologies usually only predict one of the risks, which affects the prediction efficiency.

[0006] To achieve the above object, the present invention proposes a method for predicting geological risks of a tunnel face, comprising:

[0007] Determine the current geological grade of the tunnel face according to the acquired known geological data samples of the tunnel; wherein the known geological data samples include geological survey data of the tunnel, geological longitudinal and cross-sectional views of the tunnel, and design drawings of the tunnel;

[0008] Scanning the geological body in front of the tunnel face according to the current geological level to obtain scanning data of the tunnel face;

[0009] Acquiring a scanning image of the tunnel face according to the scanning data;

[0010] Processing the scanned image to determine dryness and wetness data of the tunnel face;

[0011] According to the dryness and wetness data, a geological risk prediction is performed on the tunnel face to obtain the geological risk prediction result.

[0012] In one embodiment, the step of performing geological risk prediction on the tunnel face according to the dryness and humidity data to obtain the geological risk prediction result includes:

[0013] According to the dryness and humidity data, regional division is performed to determine a dry area and a wet area; wherein the dry area is a tunnel face with a moisture content lower than 0.1%, and the wet area is a tunnel face with a moisture content higher than 1%;

[0014] The dry area and the wet area are surveyed respectively, and the geological risk prediction is performed on the tunnel face to obtain the geological risk prediction result.

[0015] In one embodiment, the step of respectively surveying the dry area and the wet area, predicting the geological risk of the tunnel face, and obtaining the geological risk prediction result comprises:

[0016] Use geological radar to survey the dry area and the wet area respectively to obtain geological radar scanning results of the dry area;

[0017] According to the geological radar scanning results, a geological risk prediction is performed on the tunnel face to obtain the geological risk prediction result.

[0018] In one embodiment, the step of performing regional division according to the dryness and humidity data to determine the dry area and the wetness area includes:

[0019] According to the dryness and humidity data, the area with a moisture content lower than 0.1% is taken as the dry area, and the area with a moisture content higher than 1% is taken as the dry area, so as to determine the dry area and the humidity area.

[0020] In one embodiment, the step of processing the scanned image to determine the dryness and wetness data of the tunnel face includes:

[0021] The scanned image is processed using a convolutional neural network to determine the dryness and wetness data of the tunnel face.

[0022] In one embodiment, the step of scanning the geological body in front of the tunnel face according to the current geological level to obtain scanning data of the tunnel face includes:

[0023] According to the current geological level, a geological radar is used to scan the geological body in front of the tunnel face to obtain scanning data of the tunnel face.

[0024] Based on the same technical concept, in a second aspect, the present invention also proposes a tunnel face geological risk prediction device, comprising:

[0025] A geological grade classification module, used to determine the current geological grade of the tunnel face according to the acquired known geological data samples of the tunnel; wherein the known geological data samples include geological survey data of the tunnel, geological longitudinal and cross-sectional views of the tunnel, and design drawings of the tunnel;

[0026] A scanning module, used for scanning the geological body in front of the tunnel face according to the current geological level, so as to obtain scanning data of the tunnel face;

[0027] An image acquisition module, used for acquiring a scanning image of the tunnel face according to the scanning data;

[0028] A data output module, used for processing the scanned image to determine the dryness and wetness data of the tunnel face;

[0029] The prediction module is used to perform geological risk prediction on the tunnel face according to the dryness and wetness data to obtain the geological risk prediction result.

[0030] Based on the same technical concept, in the third aspect, the present invention also proposes a tunnel face geological risk prediction device, which includes a processor and a memory, and a tunnel face geological risk prediction program is stored in the memory. When the tunnel face geological risk prediction program is executed by the processor, the tunnel face geological risk prediction method described in the first aspect is implemented.

[0031] Based on the same technical concept, in a fourth aspect, the present invention also proposes a tunnel face geological risk prediction system, comprising:

[0032] The tunnel face geological risk prediction device according to the third aspect; and

[0033] A scanning device is communicatively connected to the tunnel face geological risk prediction device.

[0034] Based on the same technical concept, in the fifth aspect, the present invention also proposes a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by one or more processors, the method for predicting geological risks of the tunnel face described in the first aspect is implemented.

[0035] Technical solution of the present invention The present invention determines the current geological grade of the tunnel face through a known geological data sample consisting of the tunnel geological survey data, the tunnel geological longitudinal section and cross-section diagram, and the tunnel design drawing. According to the current geological grade, the geological body in front of the tunnel face is scanned to obtain the scanning data of the tunnel face. According to the scanning data, a scanning image of the tunnel face is obtained, and the scanning image is processed to determine the dryness and humidity data of the tunnel face. According to the dryness and humidity data, the geological risk of the tunnel face is predicted to obtain the geological risk prediction result, so that the present invention can perform the function of geological risk prediction for the tunnel face. At the same time, the tunnel face is analyzed according to the dryness and humidity conditions of the tunnel face, so that when the present invention is used, it can perform the function of simultaneous prediction of multiple regions of the tunnel face, ensuring the prediction efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0037] Figure 1 A flow chart of a method for predicting geological risks of a tunnel face provided by the present invention;

[0038] Figure 2 for Figure 1 Flow chart of step S500 in the example;

[0039] Figure 3 for Figure 2 Flow chart of step S520 in the example;

[0040] Figure 4 The figure is a schematic diagram of the structure of a tunnel face geological risk prediction device according to an example of the present invention.

[0041] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components in a certain specific posture. If the specific posture changes, the directional indication will also change accordingly.

[0044] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features limited to "first" and "second" may explicitly or implicitly include at least one of the features. In addition, if "and / or" or "and / or" appears in the full text, its meaning includes three parallel solutions. Taking "A and / or B" as an example, it includes solution A, solution B, or solutions that satisfy both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in this field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0045] The invention provides a method for predicting geological risks of a tunnel face.

[0046] See also Figures 1 to 4 In one embodiment of the present invention, the method for predicting geological risks of a tunnel face includes:

[0047] S100, determining the current geological grade of the tunnel face according to the acquired known geological data samples of the tunnel; wherein the known geological data samples include geological survey data of the tunnel, geological longitudinal section and cross section of the tunnel, and design drawings of the tunnel;

[0048] S200, scanning the geological body in front of the tunnel face according to the current geological level to obtain scanning data of the tunnel face;

[0049] In this embodiment, the current geological level is exemplified as the surrounding rock level, and the surrounding rock levels are exemplified as primary surrounding rock, secondary surrounding rock, tertiary surrounding rock, quaternary surrounding rock, and fifth surrounding rock.

[0050] S300, acquiring a scanning image of the tunnel face according to the scanning data;

[0051] In this embodiment, the exemplary tunnel face scanning image is a grayscale image or an RGB color image of the tunnel face.

[0052] S400, processing the scanned image to determine the dryness and wetness data of the tunnel face;

[0053] S500: Perform geological risk prediction on the tunnel face according to the dryness and humidity data to obtain the geological risk prediction result.

[0054] In this embodiment, the current geological grade of the tunnel face is determined by using a known geological data sample consisting of the geological survey data of the tunnel, the geological longitudinal section and cross-section of the tunnel, and the design drawing of the tunnel. According to the current geological grade, the geological body in front of the tunnel face is scanned to obtain the scanning data of the tunnel face. According to the scanning data, a scanning image of the tunnel face is obtained. The scanning image is processed to determine the dryness and humidity data of the tunnel face. According to the dryness and humidity data, the geological risk of the tunnel face is predicted to obtain the geological risk prediction result, so that the present invention can perform the function of geological risk prediction for the tunnel face. At the same time, the tunnel face is analyzed according to the dryness and humidity of the tunnel face, so that the present invention can perform the function of simultaneous prediction of multiple regions of the tunnel face when used, ensuring the prediction efficiency.

[0055] In one embodiment, step S500 includes:

[0056] S510, performing regional division according to the dryness and humidity data to determine a dry area and a wet area; wherein the dry area is a tunnel face with a moisture content lower than 0.1%, and the wet area is a tunnel face with a moisture content higher than 1%;

[0057] S520, respectively conducting survey operations on the dry area and the wet area, performing geological risk prediction on the tunnel face, and obtaining the geological risk prediction result.

[0058] In one embodiment, step S520 includes:

[0059] S521, using geological radar to perform survey operations on the dry area and the wet area respectively, so as to obtain geological radar scanning results of the dry area;

[0060] S522. According to the geological radar scanning result, a geological risk prediction is performed on the tunnel face to obtain the geological risk prediction result.

[0061] In one embodiment, the step of performing regional division according to the dryness and humidity data to determine the dry area and the wetness area includes:

[0062] According to the dryness and humidity data, the area with a moisture content lower than 0.1% is taken as the dry area, and the area with a moisture content higher than 1% is taken as the dry area, so as to determine the dry area and the humidity area.

[0063] In one embodiment, the step of processing the scanned image to determine the dryness and wetness data of the tunnel face includes:

[0064] The scanned image is processed using a convolutional neural network to determine the dryness and wetness data of the tunnel face.

[0065] In this embodiment, the technology of using convolutional neural network to process images is an existing technology. This embodiment is only applied and will not be described in detail here.

[0066] In one embodiment, the step of scanning the geological body in front of the tunnel face according to the current geological level to obtain scanning data of the tunnel face includes:

[0067] According to the current geological level, a geological radar is used to scan the geological body in front of the tunnel face to obtain scanning data of the tunnel face.

[0068] In this embodiment, the two-end geological radar is the existing technology and will not be described in detail here.

[0069] Based on the same technical concept, in a second aspect, the present invention also proposes a tunnel face geological risk prediction device, comprising:

[0070] A geological grade classification module, used to determine the current geological grade of the tunnel face according to the acquired known geological data samples of the tunnel; wherein the known geological data samples include geological survey data of the tunnel, geological longitudinal and cross-sectional views of the tunnel, and design drawings of the tunnel;

[0071] A scanning module, used for scanning the geological body in front of the tunnel face according to the current geological level, so as to obtain scanning data of the tunnel face;

[0072] An image acquisition module, used to acquire a scanning image of the tunnel face according to the scanning data;

[0073] A data output module, used for processing the scanned image to determine the dryness and wetness data of the tunnel face;

[0074] The prediction module is used to perform geological risk prediction on the tunnel face according to the dryness and wetness data to obtain the geological risk prediction result.

[0075] The tunnel face geological risk prediction device provided in the embodiment of the present application adopts the tunnel face geological risk prediction method in the above embodiment, which can solve the technical problem that when performing risk prediction, usually only one of the risks is predicted, which affects the prediction efficiency. Compared with the prior art, the beneficial effects of the tunnel face geological risk prediction device provided in the embodiment of the present application are the same as the beneficial effects of the tunnel face geological risk prediction method provided in the above embodiment, and the other technical features of the tunnel face geological risk prediction device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0076] Based on the same technical concept, in the third aspect, the present invention also proposes a tunnel face geological risk prediction device, which includes a processor and a memory, and a tunnel face geological risk prediction program is stored in the memory. When the tunnel face geological risk prediction program is executed by the processor, the tunnel face geological risk prediction method described in the first aspect is implemented.

[0077] The tunnel face geological risk prediction equipment in the embodiments of the present application may include but is not limited to mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted control terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc.

[0078] The tunnel face geological risk prediction device may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM) 1004. Various programs and data required for the operation of the tunnel face geological risk prediction device are also stored in RAM 1004. The processing device 1001, ROM 1002, and RAM 1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the tunnel face geological risk prediction device to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a tunnel face geological risk prediction device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0079] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0080] The tunnel face geological risk prediction device provided by the present application adopts the tunnel face geological risk prediction method in the above-mentioned embodiment, which can solve the technical problem that when performing risk prediction, usually only one of the risks is predicted, which affects the prediction efficiency. Compared with the prior art, the beneficial effects of the tunnel face geological risk prediction device provided by the present application are the same as the beneficial effects of the tunnel face geological risk prediction method provided by the above-mentioned embodiment, and the other technical features of the tunnel face geological risk prediction device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0081] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0082] In addition, the tunnel face geological risk prediction device provided in the embodiment of the present application can solve the technical problem that when performing risk prediction, usually only one of the risks is predicted, which affects the prediction efficiency. Compared with the prior art, the beneficial effects of the tunnel face geological risk prediction device provided in the embodiment of the present application are the same as the beneficial effects of the tunnel face geological risk prediction method provided in the above embodiment, and the other technical features of the tunnel face geological risk prediction device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0083] Based on the same technical concept, in a fourth aspect, the present invention also proposes a tunnel face geological risk prediction system, comprising:

[0084] The tunnel face geological risk prediction device according to the third aspect; and

[0085] A scanning device is communicatively connected to the tunnel face geological risk prediction device.

[0086] In addition, the tunnel face geological risk prediction system provided in the embodiment of the present application can solve the technical problem that when performing risk prediction, usually only one of the risks is predicted, which affects the prediction efficiency. Compared with the prior art, the beneficial effects of the tunnel face geological risk prediction system provided in the embodiment of the present application are the same as the beneficial effects of the tunnel face geological risk prediction method provided in the above embodiment, and the other technical features of the tunnel face geological risk prediction system are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0087] Based on the same technical concept, in the fifth aspect, the present invention also proposes a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by one or more processors, the method for predicting geological risks of the tunnel face described in the first aspect is implemented.

[0088] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0089] The computer-readable storage medium may be included in the tunnel face geological risk prediction device; or may exist independently without being assembled into the tunnel face geological risk prediction device.

[0090] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the tunnel face geological risk prediction device, the tunnel face geological risk prediction device can implement the tunnel face geological risk prediction method described above.

[0091] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0092] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0093] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0094] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned tunnel face geological risk prediction method, and can solve the technical problem that when performing risk prediction, only one of the risks is usually predicted, which affects the prediction efficiency. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the tunnel face geological risk prediction method provided in the above-mentioned embodiment, and will not be repeated here.

[0095] Therefore, all the beneficial effects brought by the technical solutions of at least the above embodiments are not described one by one here. The above description is only an exemplary implementation of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the technical concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A method for predicting geological risks of a tunnel face, characterized in that: include: Determine the current geological grade of the tunnel face according to the acquired known geological data samples of the tunnel; wherein the known geological data samples include geological survey data of the tunnel, geological longitudinal and cross-sectional views of the tunnel, and design drawings of the tunnel; Scanning the geological body in front of the tunnel face according to the current geological level to obtain scanning data of the tunnel face; Acquiring a scanning image of the tunnel face according to the scanning data; Processing the scanned image to determine dryness and wetness data of the tunnel face; According to the dryness and wetness data, a geological risk prediction is performed on the tunnel face to obtain the geological risk prediction result.

2. The method for predicting geological risks of a tunnel face according to claim 1, characterized in that: The step of performing geological risk prediction on the tunnel face according to the dryness and humidity data to obtain the geological risk prediction result comprises: According to the dryness and humidity data, regional division is performed to determine a dry area and a wet area; wherein the dry area is a tunnel face with a moisture content lower than 0.1%, and the wet area is a tunnel face with a moisture content higher than 1%; The dry area and the wet area are surveyed respectively, and the geological risk prediction is performed on the tunnel face to obtain the geological risk prediction result.

3. The method for predicting geological risks of a tunnel face according to claim 2, characterized in that: The step of respectively surveying the dry area and the wet area, predicting the geological risk of the tunnel face, and obtaining the geological risk prediction result comprises: Use geological radar to survey the dry area and the wet area respectively to obtain geological radar scanning results of the dry area; According to the geological radar scanning results, a geological risk prediction is performed on the tunnel face to obtain the geological risk prediction result.

4. The method for predicting geological risks of a tunnel face according to claim 2, characterized in that: The step of dividing the regions according to the dryness and humidity data to determine the dry region and the wetness region comprises: According to the dryness and humidity data, the area with a moisture content lower than 0.1% is taken as the dry area, and the area with a moisture content higher than 1% is taken as the dry area, so as to determine the dry area and the humidity area.

5. The method for predicting geological risks of a tunnel face according to claim 2, characterized in that: The step of processing the scanned image to determine the dryness and wetness data of the tunnel face includes: The scanned image is processed using a convolutional neural network to determine the dryness and wetness data of the tunnel face.

6. The method for predicting geological risks of a tunnel face according to claim 2, characterized in that: The step of scanning the geological body in front of the tunnel face according to the current geological level to obtain scanning data of the tunnel face includes: According to the current geological level, a geological radar is used to scan the geological body in front of the tunnel face to obtain scanning data of the tunnel face.

7. A tunnel face geological risk prediction device, characterized in that: include: A geological grade classification module, used to determine the current geological grade of the tunnel face according to the acquired known geological data samples of the tunnel; wherein the known geological data samples include geological survey data of the tunnel, geological longitudinal and cross-sectional views of the tunnel, and design drawings of the tunnel; A scanning module, used for scanning the geological body in front of the tunnel face according to the current geological level, so as to obtain scanning data of the tunnel face; An image acquisition module, used to acquire a scanning image of the tunnel face according to the scanning data; A data output module, used for processing the scanned image to determine the dryness and wetness data of the tunnel face; The prediction module is used to perform geological risk prediction on the tunnel face according to the dryness and wetness data to obtain the geological risk prediction result.

8. A tunnel face geological risk prediction device, characterized in that: The tunnel face geological risk prediction device includes a processor and a memory, wherein a tunnel face geological risk prediction program is stored in the memory, and when the tunnel face geological risk prediction program is executed by the processor, the tunnel face geological risk prediction method according to any one of claims 1 to 5 is implemented.

9. A tunnel face geological risk prediction system, characterized in that: include: The tunnel face geological risk prediction device according to claim 8; as well as, A scanning device is communicatively connected to the tunnel face geological risk prediction device.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by one or more processors, the method for predicting geological risks of a tunnel face according to any one of claims 1 to 5 is implemented.

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