Tunnel excavation face surrounding rock deformation monitoring and early warning method, device and system

Abstract

The invention relates to the technical field of tunnel construction, in particular to a tunnel excavation face surrounding rock deformation monitoring and early warning method, device and system, the system comprises a laser radar and terminal equipment, the laser radar is fixedly arranged at the position, needing safety monitoring, of a tunnel and is used for emitting laser beams to the peripheral surface of the tunnel to collect point cloud data; the terminal equipment is used for segmenting the point cloud data so as to screen out target point cloud data for the surrounding rock of the excavation face, and analyzing the target point cloud data according to a preset condition to obtain an evaluation template; when the laser radar collects real-time point cloud data of surrounding rocks of the same excavation face in the subsequent monitoring process, the real-time point cloud data and the evaluation template can be directly subjected to distance calculation one by one, if the distance values of the real-time point cloud data exceeding the threshold number are all larger than the preset threshold value, it shows that the current excavation face has the rockfall risk, and if the distance values of the real-time point cloud data exceeding the threshold number are all larger than the preset threshold value, it shows that the current excavation face has the rockfall risk. And risk early warning reminding needs to be carried out.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel construction, and in particular to a method, device and system for monitoring and early warning of deformation of surrounding rock of tunnel excavation face. Background Art

[0002] In recent years, tunnel and underground engineering construction has ushered in great development opportunities. Drilling and blasting is a common construction method for railway tunnels. The tunnel excavation surface formed is complex and high-risk, making this area the main area for sudden disasters during tunnel construction. Especially in railway tunnels with complex geology such as high altitude, high-intensity earthquake zones, deep burial depth and ultra-long tunnels, there are rock disasters such as surrounding rock extrusion deformation (soft rock sections) and local block falling (hard rock sections), which not only increase the difficulty of on-site construction, but also seriously endanger the safety of construction workers.

[0003] At present, the safety hazard inspection of tunnel excavation sites mostly uses traditional instruments such as displacement meters, compasses, strain gauges, and convergence rulers. Not only are there limitations such as reliance on manual monitoring, inability to monitor continuously and as a whole, but also the deployment of sensors on the excavation face has a high safety risk. Commonly used advanced geological prediction methods and equipment such as seismic wave method, electrical method, and magnetic method are difficult to monitor the safety status of the face after excavation and provide early warning, and cannot meet the needs of on-site safety monitoring. Summary of the invention

[0004] The purpose of the present invention is to provide a method, device and system for monitoring and early warning of surrounding rock deformation of a tunnel excavation face, so as to realize fast, accurate and intelligent safety monitoring and early warning of the tunnel excavation face.

[0005] In order to achieve the above purpose, the technical solution adopted by the embodiment of the present invention is as follows:

[0006] In the first aspect, an embodiment of the present invention provides a method for monitoring and warning deformation of surrounding rock of a tunnel excavation face, the method comprising: receiving point cloud data collected by a laser radar emitting a laser beam to the surface around the tunnel; segmenting the point cloud data to filter out target point cloud data for the surrounding rock of the excavation face; analyzing the target point cloud data according to predetermined conditions to obtain an evaluation template; collecting real-time point cloud data of the surrounding rock of the same excavation face through the laser radar, and calculating the distance between the real-time point cloud data and the evaluation template one by one, and if there are more than a threshold number of real-time point cloud data with a distance value greater than a predetermined threshold, a risk early warning reminder of the surrounding rock of the excavation face is issued.

[0007] In the second aspect, an embodiment of the present invention further provides a tunnel excavation face surrounding rock deformation monitoring and early warning device, the device comprising: a receiving module, used to receive point cloud data collected by a laser radar emitting a laser beam to the surface around the tunnel; a segmentation module, used to segment the point cloud data to filter out target point cloud data for the excavation face surrounding rock; an analysis module, used to analyze the target point cloud data according to predetermined conditions to obtain an evaluation template; a calculation module, used to collect real-time point cloud data of the same excavation face surrounding rock through the laser radar, and calculate the distance between the real-time point cloud data and the evaluation template one by one. If there are more than a threshold number of real-time point cloud data with a distance value greater than a predetermined threshold, an excavation face surrounding rock risk early warning reminder is issued.

[0008] In the third aspect, an embodiment of the present invention further provides a tunnel excavation face surrounding rock deformation monitoring and early warning system, the system comprising a laser radar and a terminal device, the laser radar being used to emit laser beams to the surfaces around the tunnel to collect point cloud data, and sending the collected point cloud data to the terminal device; the terminal device being used to segment the point cloud data to filter out target point cloud data for the excavation face surrounding rock, and analyzing the target point cloud data according to predetermined conditions to obtain an evaluation template; when the laser radar collects real-time point cloud data of the same excavation face surrounding rock, the distance between the real-time point cloud data and the evaluation template is calculated one by one, if there are more than a threshold number of real-time point cloud data whose distance values ​​are greater than a predetermined threshold, an excavation face surrounding rock risk early warning reminder is issued.

[0009] A method, device and system for monitoring and warning deformation of surrounding rock of a tunnel excavation face provided by an embodiment of the present invention, the system includes a laser radar and a terminal device, the laser radar is fixedly arranged at a position where the tunnel needs to be safely monitored, and is used to emit laser beams to the surface around the tunnel to collect point cloud data; the terminal device is used to segment the point cloud data to filter out target point cloud data for the surrounding rock of the excavation face, and analyze the target point cloud data according to predetermined conditions to obtain an evaluation template; when the laser radar collects real-time point cloud data for the surrounding rock of the same excavation face in the subsequent monitoring process, the distance between the real-time point cloud data and the evaluation template can be directly calculated one by one. If there are real-time point cloud data with a distance value greater than a predetermined threshold that exceeds a threshold, it indicates that there is a risk of falling rocks on the current excavation face, and a risk warning reminder is required.

[0010] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A structural schematic diagram of a tunnel excavation face surrounding rock deformation monitoring and early warning system provided by an embodiment of the present invention is shown.

[0013] Figure 2 A schematic flow chart of a tunnel excavation face surrounding rock deformation monitoring and early warning method provided by an embodiment of the present invention is shown.

[0014] Figure 3 A schematic diagram of point cloud data provided by an embodiment of the present invention is shown.

[0015] Figure 4 A schematic diagram of an evaluation template provided by an embodiment of the present invention is shown.

[0016] Figure 5 A schematic diagram of functional modules of a tunnel excavation face surrounding rock deformation monitoring and early warning device provided by an embodiment of the present invention is shown.

[0017] Diagram:

[0018] 100 - tunnel excavation face surrounding rock deformation monitoring and early warning system; 110 - laser radar; 120 - terminal equipment; 200 - tunnel excavation face surrounding rock deformation monitoring and early warning device; 210 - receiving module; 220 - segmentation module; 230 - analysis module; 240 - calculation module. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present invention.

[0020] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0021] Please refer to Figure 1 , is a structural schematic diagram of a tunnel excavation face surrounding rock deformation monitoring and early warning system 100 provided in an embodiment of the present invention. The system includes a laser radar 110 and a terminal device 120. The laser radar 110 and the terminal device 120 are connected via a wired or wireless method.

[0022] During monitoring, the laser radar 110 is fixed at the position to be monitored in the tunnel, and a transmitting module and a receiving module are arranged inside it. Both the transmitting module and the receiving module can be driven by a motor to rotate 360 ​​degrees, and then the transmitting module rotates the transmitting head continuously at a predetermined frequency to emit a laser beam toward the surface of the tunnel to achieve dynamic scanning; the receiving module also rotates at the same frequency to synchronously receive the scanning data. The frequency of the scanning data is 10 frames per second, and each frame of data is composed of point cloud data collected by a petal-shaped laser beam, which is combined through continuous dynamic rotation to form a complete point cloud data. It should be noted that the total number of point cloud data in one rotation cycle is generally 479,554. By collecting a large range of point cloud data, the later monitoring effect can be made more accurate.

[0023] The terminal device 120 is used to receive the point cloud data collected by the laser radar 110, and analyze and process the point cloud data to achieve real-time monitoring and early warning of the deformation of the surrounding rock of the tunnel excavation face. Specifically, the terminal device 120 is used to segment the point cloud data to screen out the target point cloud data for the surrounding rock of the excavation face, and analyze the target point cloud data according to the predetermined conditions to obtain an evaluation template; when the subsequent laser radar collects the real-time point cloud data of the surrounding rock of the same excavation face, the real-time point cloud data and the evaluation template can be directly calculated one by one. If there is a distance value of more than a threshold number of real-time point cloud data greater than the predetermined threshold, it means that there is a risk of rockfall on the current excavation face, and a risk warning reminder is given in time to ensure the life safety of the construction personnel. It is easy to understand that the terminal device 120 can be, but not limited to, electronic devices with data processing capabilities such as desktop computers, laptops, tablets, and mobile phones. In addition, the terminal device 120 can also be integrated with an acoustic and light alarm device, or an external acoustic and light alarm device can be connected to facilitate timely alarm. The acoustic and light alarm device can be, but not limited to, an integration of a speaker and a flashing light.

[0024] A tunnel excavation face surrounding rock deformation monitoring and early warning method provided by an embodiment of the present invention is applied to the terminal device 120, please refer to Figure 2 , is a flow chart of a method for monitoring and early warning deformation of surrounding rock of tunnel excavation face provided by an embodiment of the present invention, the method comprising:

[0025] S110, receiving point cloud data collected by the laser radar emitting laser beams to the surrounding surfaces of the tunnel.

[0026] Specifically, the laser radar 110 is fixed at a place in the tunnel when working, and collects point cloud data by emitting laser beams toward the surface around the tunnel. The collected point cloud data is as follows: Figure 3 As shown, and are all sent to the terminal device 120.

[0027] S120, segmenting the point cloud data to filter out target point cloud data for the surrounding rock of the excavation surface.

[0028] Specifically, during the tunnel excavation process, as the excavation goes deeper, an arched structure gradually forms around the tunnel entrance. The arched structure is relatively strong. In the real-time monitoring system for tunnel excavation surface surrounding rock disasters, it is not necessary to monitor the side walls of the tunnel with an arched structure, but only to focus on the excavation surface to be excavated with a greater excavation risk in front. Since the laser radar 110 collects point cloud data of the surface around the tunnel, there is some useless data in the point cloud data, so it is necessary to segment the point cloud data to filter out the target point cloud data for the excavation surface surrounding rock, that is, the target point cloud data is the point cloud data that only includes the excavation surface surrounding rock in front of the tunnel entrance.

[0029] S130, analyzing the target point cloud data according to predetermined conditions to obtain an evaluation template.

[0030] Specifically, although the target point cloud data is the point cloud data of the surrounding rock of the excavation surface, since it is usually accumulated for a rotation cycle of the laser radar 110, the target point cloud data is still a large amount of data. In order to facilitate subsequent monitoring and analysis, the target point cloud data needs to be further screened, which specifically includes:

[0031] From the target point cloud data, a predetermined number of continuous frames without moving objects or obstructions are selected as evaluation point cloud data. In other words, in order to achieve a long-term stable monitoring effect, 40 consecutive frames without moving objects or obstructions are generally selected as evaluation point cloud data (the specific number of frames can be changed according to demand). Since there are no objects and no obstructions in the 40 consecutive frames, the state is relatively stable, which can be used as an effective reference for the subsequent changes in the state of the surrounding rock of the excavation surface. That is to say, the state of the surrounding rock of the excavation surface in the 40 consecutive frames is used as a benchmark to compare with the subsequent state, and then analyze what specific changes have occurred in the surrounding rock of the excavation surface in the subsequent state, such as whether there is rockfall, etc., in order to facilitate risk warning.

[0032] The evaluation point cloud data is then divided into multiple blocks, and the specific number of blocks can be set as needed, such as 9 blocks, 10 blocks, 20 blocks, etc. The more blocks are divided, the more accurate the subsequent monitoring and comparison will be.

[0033] Finally, the evaluation point cloud data in each block is reconstructed to obtain an evaluation template. Specifically, the evaluation point cloud data in each block is reconstructed using Poisson reconstruction, and the 3D grid corresponding to each block is output. The 3D grid data set formed by all blocks forms an evaluation template. The evaluation template is as follows: Figure 4 As shown, Figure 4 The dot representation of the evaluation template is shown in , and the effect of the block division is reflected. It can be found that the closer the evaluation template is to the center area of ​​the laser radar 110, the denser its points are. The Poisson reconstruction is an implicit surface reconstruction scheme, which inputs a set of directed point clouds on the surface of the object and outputs a three-dimensional mesh of the surface of the object. Compared with direct mesh reconstruction such as Delaunay, the main difference is that the vertices of the output mesh do not need to come from the original point cloud, the result is smoother, and due to the global solution, the watertightness of the mesh can be guaranteed.

[0034] S140, collecting real-time point cloud data of the surrounding rock of the same excavation face through the laser radar, and calculating the distance between the real-time point cloud data and the evaluation template one by one. If there are more than a threshold number of real-time point cloud data with distance values ​​greater than a predetermined threshold, an excavation face surrounding rock risk warning reminder is issued.

[0035] Specifically, after obtaining the evaluation template, the laser radar 110 is continued to monitor the surrounding rock of the same excavation face, that is, real-time point cloud data is continued to be collected. The real-time point cloud data collected subsequently will be calculated one by one with the evaluation template, and the calculation method is as follows: the real-time point cloud data is divided into the same number of blocks as the evaluation template, and the distance between the corresponding real-time point cloud data and the three-dimensional grid is calculated one by one according to each block. If the distance between the point and the evaluation template exceeds a predetermined threshold (such as the predetermined threshold can be 1cm), the point will be regarded as an offset point. However, considering that the offset point may be caused by errors, it is determined that the distance value of the real-time point cloud data exceeding the threshold number is greater than the predetermined threshold. At this time, there may be a high probability of surrounding rock offset or rockfall, so an early warning reminder of the risk of surrounding rock of the excavation face should be issued in time. In addition, it is also possible that multiple rays in one frame may be offset suddenly. In order to exclude such error frames, time continuity is required. The offset areas of adjacent rounds are compared, and an alarm is issued if an offset area is found at the same position for three consecutive rounds.

[0036] It should be noted that, since the laser radar 110 needs to remain stationary when emitting laser beams to the surface around the tunnel to collect point cloud data, if it is moved by humans or other objects, it will cause the laser radar 110 to measure inaccurately or even misjudge. Therefore, it is necessary to monitor the movement state of the laser radar 110. If the laser radar 110 is in a moving state, the monitoring of the deformation of the surrounding rock of the tunnel excavation surface should be stopped. Specifically:

[0037] The laser radar 110 is integrated with an IMU (Inertial measurement unit), an accelerometer, a mass block, and a spring. The IMU unit is used to collect the three-axis acceleration of the laser radar 110. In addition, under the influence of gravity, the mass block in the accelerometer will compress the spring in the vertical direction, equivalently recording the acceleration in one direction vertically upward, and decomposing the acceleration into the three-axis acceleration according to the posture of the IMU unit in space to obtain the three-axis acceleration after removing the gravity acceleration. And monitor whether the laser radar 110 moves based on the acceleration data after removing the gravity acceleration from the three-axis acceleration.

[0038] Therefore, the tunnel excavation face surrounding rock deformation monitoring and early warning method provided by the embodiment of the present invention can achieve at least the following beneficial effects:

[0039] 1. A more accurate evaluation template is constructed based on the accumulated point cloud data over a period of time through surface reconstruction. In this way, when the evaluation template has been obtained, each input monitoring point cloud only needs to quickly evaluate the evaluation template without the need to reconstruct the surface each time, meeting the real-time requirements.

[0040] 2. Drilling and blasting is a common construction method for railway tunnels. The tunnel excavation surface formed by the drilling and blasting method is complex and high-risk, making this area the main area for sudden disasters during tunnel construction. This is especially true for railway tunnels with complex geology such as high altitude, high-intensity earthquake zones, deep burial depths and long tunnels. The tunnel excavation surface surrounding rock deformation monitoring and early warning method has adapted to the complex tunnel environment and greatly protected the lives of construction workers.

[0041] Please refer to Figure 5 , is a functional module diagram of a tunnel excavation face surrounding rock deformation monitoring and early warning device 200 provided in an embodiment of the present invention, the device is applied to a terminal device 120, and the device includes:

[0042] The receiving module 210 is used to receive point cloud data collected by the laser radar by emitting laser beams to the surrounding surfaces of the tunnel.

[0043] In the embodiment of the present invention, S110 may be executed by the receiving module 210 .

[0044] The segmentation module 220 is used to segment the point cloud data to filter out target point cloud data for the surrounding rock of the excavation surface.

[0045] In the embodiment of the present invention, S120 may be performed by the segmentation module 220 .

[0046] The analysis module 230 is used to analyze the target point cloud data according to predetermined conditions to obtain an evaluation template.

[0047] In the embodiment of the present invention, S130 may be executed by the analysis module 230 .

[0048] The calculation module 240 is used to collect real-time point cloud data of the surrounding rock of the same excavation face through the laser radar, and calculate the distance between the real-time point cloud data and the evaluation template one by one. If there are more than a threshold number of real-time point cloud data with distance values ​​greater than a predetermined threshold, an excavation face surrounding rock risk warning reminder is issued.

[0049] In the embodiment of the present invention, S140 may be executed by the calculation module 240 .

[0050] Since the monitoring and early warning method of surrounding rock deformation at the tunnel excavation face has been described in detail, it will not be repeated here.

[0051] In summary, an embodiment of the present invention provides a method, device and system for monitoring and early warning of deformation of surrounding rock of a tunnel excavation face. The system includes a laser radar and a terminal device. The laser radar is fixedly arranged at a position where the tunnel needs to be safely monitored, and is used to emit laser beams to the surface around the tunnel to collect point cloud data; the terminal device is used to segment the point cloud data to filter out target point cloud data for the surrounding rock of the excavation face, and analyze the target point cloud data according to predetermined conditions to obtain an evaluation template; when the laser radar collects real-time point cloud data for the surrounding rock of the same excavation face in the subsequent monitoring process, the distance between the real-time point cloud data and the evaluation template can be directly calculated one by one. If there are more than a threshold number of real-time point cloud data whose distance values ​​are all greater than a predetermined threshold, it means that there is a risk of falling rocks on the current excavation face, and a risk early warning reminder is required.

[0052] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes 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 box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0053] In addition, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0054] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. It should be noted that, in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0055] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention. It should be noted that similar numbers and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0056] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for monitoring and early warning of surrounding rock deformation of tunnel excavation face, characterized in that: The method comprises: Receive point cloud data collected by laser radar emitting laser beams to the surface around the tunnel; Segmenting the point cloud data to filter out target point cloud data for the surrounding rock of the excavation surface; Analyzing the target point cloud data according to predetermined conditions to obtain an evaluation template; The laser radar is used to collect real-time point cloud data of the surrounding rock of the same excavation face, and the distance between the real-time point cloud data and the evaluation template is calculated one by one. If there are more than a threshold number of real-time point cloud data with distance values ​​greater than a predetermined threshold, an excavation face surrounding rock risk warning reminder is issued.

2. The tunnel excavation face surrounding rock deformation monitoring and early warning method according to claim 1, characterized in that: The step of analyzing the target point cloud data according to predetermined conditions to obtain an evaluation template comprises: From the target point cloud data, a predetermined number of continuous frames without moving objects or occluders are selected as evaluation point cloud data; Dividing the evaluation point cloud data into a plurality of blocks; The evaluation point cloud data in each block is reconstructed to obtain an evaluation template.

3. The tunnel excavation face surrounding rock deformation monitoring and early warning method according to claim 2, characterized in that: The step of reconstructing the evaluation point cloud data in each block to obtain an evaluation template comprises: The evaluation point cloud data in each block is reconstructed using Poisson reconstruction, and the three-dimensional grid corresponding to each block is output. The three-dimensional grid data set formed by all blocks forms an evaluation template.

4. The tunnel excavation face surrounding rock deformation monitoring and early warning method according to claim 3, characterized in that: The step of calculating the distance between the real-time point cloud data and the evaluation template one by one comprises: Dividing the real-time point cloud data into the same number of blocks as the evaluation template; The distance between the corresponding real-time point cloud data and the three-dimensional grid is calculated one by one according to each block.

5. The tunnel excavation face surrounding rock deformation monitoring and early warning method according to claim 1, characterized in that: The method further comprises: The moving state of the laser radar is monitored. If the laser radar is in a moving state, the monitoring of the deformation of the surrounding rock of the tunnel excavation face is stopped.

6. The tunnel excavation face surrounding rock deformation monitoring and early warning method according to claim 5, characterized in that: The step of monitoring the movement state of the laser radar includes: Receiving the three-axis acceleration collected by the IMU unit provided in the laser radar; Whether the laser radar moves is monitored based on acceleration data obtained by removing gravity acceleration from the three-axis acceleration.

7. A tunnel excavation face surrounding rock deformation monitoring and early warning device, characterized in that: The device comprises: A receiving module is used to receive point cloud data collected by the laser radar emitting laser beams to the surface around the tunnel; A segmentation module, used to segment the point cloud data to filter out target point cloud data for the surrounding rock of the excavation surface; An analysis module, used for analyzing the target point cloud data according to predetermined conditions to obtain an evaluation template; A calculation module is used to collect real-time point cloud data of the surrounding rock of the same excavation face through the laser radar, and calculate the distance between the real-time point cloud data and the evaluation template one by one. If there are more than a threshold number of real-time point cloud data with distance values ​​greater than a predetermined threshold, an excavation face surrounding rock risk warning reminder is issued.

8. A tunnel excavation face surrounding rock deformation monitoring and early warning system, characterized in that: The system includes a laser radar and a terminal device. The laser radar is used to emit laser beams to the surface around the tunnel to collect point cloud data, and send the collected point cloud data to the terminal device; The terminal device is used to segment the point cloud data to filter out target point cloud data for the surrounding rock of the excavation surface, and analyze the target point cloud data according to predetermined conditions to obtain an evaluation template; when the laser radar collects real-time point cloud data of the surrounding rock of the same excavation surface, the distance between the real-time point cloud data and the evaluation template is calculated one by one. If there are more than a threshold number of real-time point cloud data with distance values ​​greater than a predetermined threshold, an excavation surface surrounding rock risk warning reminder is issued.

9. The tunnel excavation face surrounding rock deformation monitoring and early warning system according to claim 8, characterized in that: The laser radar includes a transmitting module and a receiving module. The transmitting module rotates at a predetermined frequency and emits a laser beam toward the surface of the tunnel. The receiving module is used to collect point cloud data.

10. The tunnel excavation face surrounding rock deformation monitoring and early warning system according to claim 8, characterized in that: The terminal device is integrated or externally connected with an acoustic and visual alarm device, which is used to emit sound and / or light to alarm in the event of a risk warning of surrounding rock on the excavation face.

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