An intelligent monitoring system for soft surrounding rock deformation in shallow large-section tunnels

Abstract

The present invention belongs to the field of tunnel deformation monitoring, relates to data processing technology, and is used to solve the problem that the existing intelligent monitoring system for surrounding rock deformation cannot combine the surrounding rock deformation amount with the cross-sectional distribution state for analysis. Specifically, it is an intelligent monitoring system for deformation of soft surrounding rocks in shallow buried large-section tunnels, comprising an intelligent monitoring platform, wherein the intelligent monitoring platform is communicatively connected with a tunnel segmentation module, a cross-sectional analysis module, a distribution analysis module, a comprehensive monitoring module and a storage module; the tunnel is segmented at a length value of L1 meters on one side of the tunnel to obtain a plurality of segmented areas, and the segmented areas are numbered according to the order of division; the present invention can perform cross-sectional analysis on the segmented areas, obtain the cross-sectional coefficient by performing comprehensive analysis and calculation on a plurality of deformation parameters in the cross-section, and provide data support for the cross-sectional distribution analysis while providing feedback on the cross-sectional coverage range within the segmented areas.

Description

Technical Field

[0001] The invention belongs to the field of shallow buried large-section tunnels and relates to data processing technology, in particular to an intelligent monitoring system for deformation of soft surrounding rocks of shallow buried large-section tunnels. Background Art

[0002] Shallow buried large-section tunnels with soft surrounding rock have large single excavation space and poor mechanical properties of the surrounding rock. Under the concentrated stress after excavation disturbance, the soft surrounding rock is prone to large deformation, which seriously affects the safe and efficient construction of the tunnel. Understanding the occurrence and development process of surrounding rock deformation of this type of tunnel is of great significance to the support design and safe construction of this type of tunnel.

[0003] The existing intelligent monitoring system for surrounding rock deformation can only monitor and analyze the surrounding rock deformation inside the tunnel, but lacks the function of analyzing the cross-sectional distribution. As a result, it is impossible to combine the surrounding rock deformation with the cross-sectional distribution status for analysis, resulting in low accuracy of deformation monitoring results.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent monitoring system for deformation of weak surrounding rock in shallow-buried large-section tunnels, which is used to solve the problem that the existing intelligent monitoring system for surrounding rock deformation cannot combine the surrounding rock deformation with the cross-section distribution state for analysis;

[0006] The technical problem to be solved by the present invention is: how to provide an intelligent monitoring system for deformation of weak surrounding rocks in shallow-buried large-section tunnels, which can combine the deformation of surrounding rocks with the cross-section distribution state for analysis.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] An intelligent monitoring system for soft surrounding rock deformation of shallow-buried large-section tunnels, comprising an intelligent monitoring platform, wherein the intelligent monitoring platform is communicatively connected with a tunnel segmentation module, a section analysis module, a distribution analysis module, a comprehensive monitoring module and a storage module;

[0009] The tunnel segmentation module is used to segment the tunnel into regions: the tunnel is segmented at one side of the tunnel by a length value of L1 meters to obtain a plurality of segmented regions, and the segmented regions are numbered according to the segmentation order;

[0010] The section analysis module is used to perform section analysis on the segmented area: obtain the section quantity data DL and section volume data DJ of the segmented area, the section quantity data DL is the number of sections in the segmented area, and the section volume data DJ is the sum of the area values ​​of all sections in the segmented area; send the section quantity data DL and section volume data DJ of the segmented area to the comprehensive monitoring module through the intelligent monitoring platform; obtain the area data MJ, pressure data YL and displacement data WY of the section in the segmented area, perform numerical calculations on the area data MJ, pressure data YL and displacement data WY to obtain the section coefficient DM of the section in the segmented area; mark the section with the largest value of the section coefficient DM in the segmented area as the main section of the segmented area, send all the main sections in the segmented area to the intelligent monitoring platform, and the intelligent monitoring platform sends the main section to the distribution analysis module after receiving the main section;

[0011] The distribution analysis module is used to analyze the cross-sectional distribution state of the tunnel after receiving the main cross-section and obtain the distribution characteristics of the main cross-section of the segmented area, and send the distribution characteristics of all segmented areas to the comprehensive monitoring module through the intelligent monitoring platform; the number of segmented areas with safe, fuzzy and dangerous distribution characteristics in the tunnel is marked as a safety value AS, a modulus value MS and a danger value WS respectively, and a distribution coefficient FB is obtained by numerical calculation, and whether the cross-sectional distribution state of the tunnel meets the requirements is judged by the numerical value of the distribution coefficient FB;

[0012] The comprehensive monitoring module is used to conduct comprehensive monitoring and analysis on the deformation risk of the tunnel and obtain the deformation coefficient BX, and to determine whether the deformation state of the segmented area meets the requirements according to the value of the deformation coefficient BX.

[0013] As a preferred embodiment of the present invention, the area data MJ of the section in the divided area is the area value of the section, and the process of obtaining the pressure data YL includes: randomly selecting L2 representative detection points in the section, measuring the surrounding rock pressure at the representative detection points and obtaining L2 pressure detection values, and marking the pressure detection value with the largest value as the pressure data YL; the process of obtaining the displacement data WY includes: measuring the surrounding rock displacement value at the representative detection points using a multi-point displacement meter and obtaining L2 detection displacement values, and marking the detection displacement value with the largest value as the displacement data WY.

[0014] As a preferred embodiment of the present invention, the process of acquiring the distribution characteristics of the segmented area includes: acquiring the center point of the main section, making a segmentation line in the middle position of the segmented area, the segmentation line dividing the segmented area into a starting area and an ending area, the starting area is close to the starting position of the tunnel segmentation direction, and the ending area is close to the extension position of the tunnel segmentation direction. If the center point of the main section is located in the starting area, the distribution value of the main section is marked as 0; if the center point of the main section is located at the ending position, the distribution value of the main section is marked as 1; performing distribution analysis on the main section in the segmented area and marking the distribution characteristics of the segmented area as safe, fuzzy or dangerous.

[0015] As a preferred embodiment of the present invention, the specific process of performing distribution analysis on the main section within the segmented area includes: forming an area group from two adjacent segmented areas, marking the segmented area with the smallest serial number in the area group as element A of the area group, and marking the segmented area with the largest serial number in the area group as element B of the area group; if the distribution value of element A is 0 and the distribution value of element B is 1, then the distribution feature of the segmented area corresponding to element A is marked as safe; if the distribution value of element A is 1 and the distribution value of element B is 0, then the distribution feature of the segmented area corresponding to element A is marked as dangerous; otherwise, the distribution feature of the segmented area corresponding to element A is marked as fuzzy.

[0016] As a preferred embodiment of the present invention, the specific process of determining whether the cross-sectional distribution state of the tunnel meets the requirements includes: obtaining the distribution threshold value FB through the storage module max , the tunnel distribution coefficient FB and the distribution threshold FB max Compare: If the distribution coefficient FB is less than the distribution threshold FB max , then it is determined that the cross-sectional distribution state of the tunnel meets the requirements; if the distribution coefficient FB is greater than or equal to the distribution threshold FB max , it is determined that the cross-sectional distribution state of the tunnel does not meet the requirements, a distribution abnormality signal is generated and the distribution abnormality signal is sent to the mobile terminal of the manager through the intelligent monitoring platform.

[0017] As a preferred embodiment of the present invention, the specific process of the comprehensive monitoring module for comprehensive monitoring and analysis of the deformation risk of the tunnel includes: obtaining the deformation coefficient BX of the segmented area through the formula BX=t1*(γ1*DL+γ2*DJ), wherein γ1 and γ2 are both proportional coefficients, and γ1>γ2>1, and t1 is the correction factor; obtaining the deformation threshold BX through the storage module max , the deformation coefficient BX and the deformation threshold BX max Compare: If the deformation coefficient BX is less than the deformation threshold BX max , then the deformation state of the segmented area meets the requirements; if the deformation coefficient BX is greater than or equal to the deformation threshold BX max, it is determined that the deformation state of the segmented area does not meet the requirements, and the comprehensive monitoring module sends a deformation warning signal to the intelligent monitoring platform. After receiving the deformation warning signal, the intelligent monitoring platform sends the deformation warning signal to the mobile phone terminal of the manager.

[0018] As a preferred embodiment of the present invention, the process of taking the value of t1 includes: if the distribution characteristic of the segmented area is safe, then t1=0.85; if the distribution characteristic of the segmented area is fuzzy, then t1=1; if the distribution characteristic of the segmented area is dangerous, then t1=1.15.

[0019] As a preferred embodiment of the present invention, the working method of the intelligent monitoring system for soft surrounding rock deformation of shallow buried large-section tunnels comprises the following steps:

[0020] Step 1: Segment the tunnel into regions. Segment the tunnel into regions with a length of L1 meters on one side of the tunnel and obtain a number of segmented regions.

[0021] Step 2: Perform cross-sectional analysis on the segmented area and obtain the cross-sectional coefficient of each cross-sectional area, and mark the main cross-sectional area by the value of the cross-sectional coefficient;

[0022] Step 3: Analyze the cross-sectional distribution state of the tunnel and obtain the distribution coefficient of the tunnel, and determine whether the cross-sectional distribution state of the tunnel meets the requirements according to the value of the distribution coefficient;

[0023] Step 4: Conduct comprehensive monitoring and analysis on the deformation risk of the tunnel and obtain the deformation coefficient of the segmented area. Determine whether the deformation state of the segmented area meets the requirements based on the numerical value of the deformation coefficient.

[0024] The present invention has the following beneficial effects:

[0025] 1. The cross-section analysis module can be used to perform cross-section analysis on the segmented area. The cross-section coefficient is calculated by comprehensively analyzing multiple deformation parameters in the cross-section. The cross-section coefficient is used to provide feedback on the deformation risk level in the cross-section, and the main cross-section in the segmented area is marked by the value of the cross-section coefficient. While providing feedback on the cross-section coverage within the segmented area, data support is provided for cross-section distribution analysis.

[0026] 2. The distribution analysis module can be used to analyze the cross-sectional distribution of the tunnel. By dividing the main section, the starting area and the ending area, the distribution characteristics of each segmented area are marked, and then the distribution coefficient is obtained by numerical calculation of the distribution characteristic marking results. The distribution coefficient is used to determine whether there is a risk in the cross-sectional distribution of the tunnel, and feedback is provided on the deformation risk of the tunnel surrounding rock as a whole.

[0027] 3. The comprehensive monitoring module can be used to conduct comprehensive monitoring and analysis of the deformation risk of the tunnel. The deformation coefficient of the segmented area can be obtained by comprehensively analyzing the cross-sectional parameters and distribution feature marking results in the segmented area. The deformation coefficient can then be used to provide feedback on the explicit deformation risk and invisible distribution risk in the segmented area to improve the accuracy of deformation monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] 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 these drawings without paying creative work.

[0029] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0030] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0031] The technical scheme of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than 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.

[0032] Embodiment 1

[0033] like Figure 1 As shown, an intelligent monitoring system for deformation of soft surrounding rock in shallow buried large-section tunnels includes an intelligent monitoring platform, which is communicatively connected to a tunnel segmentation module, a section analysis module, a distribution analysis module, a comprehensive monitoring module and a storage module.

[0034] The tunnel segmentation module is used to segment the tunnel into regions: the tunnel is segmented on one side of the tunnel with a length of L1 meters and several segmented regions are obtained. L1 is a numerical constant and the specific value of L1 is set by the management personnel. The segmented regions are numbered in the order of segmentation:

[0035] The section analysis module is used to perform section analysis on the segmented area: obtain the fault quantity data DL and fault volume data DJ of the segmented area, the fault quantity data DL is the number of sections in the segmented area, and the fault volume data DJ is the sum of the area values ​​of all sections in the segmented area; send the fault quantity data DL and fault volume data DJ of the segmented area to the comprehensive monitoring module through the intelligent monitoring platform; obtain the area data MJ, pressure data YL and displacement data WY of the sections in the segmented area, the area data MJ of the sections in the segmented area is the area value of the sections, and the pressure data YL acquisition process includes: randomly selecting L2 representative detection points in the section, and the selection process of the representative detection points includes: 1 at the middle position of the tunnel top, 1 at each of the two shoulder positions of the tunnel top, and 1 at the tunnel top. One point at each of the two bottom corners of the road floor; measure the surrounding rock pressure at the representative detection point and obtain L2 pressure detection values, L2 is a numerical constant, and the specific value of L2 is set by the management personnel; mark the pressure detection value with the largest value as pressure data YL; the process of obtaining displacement data WY includes: using a multi-point displacement meter to measure the surrounding rock displacement value at the representative detection point and obtain L2 displacement values. The multi-point displacement meter is also called a roof delamination meter. The roof delamination meter is a special monitoring instrument for monitoring the movement of the roof rock layer, which can effectively ensure the safe production of coal mines. In addition, a digital roof delamination meter and an online monitoring roof delamination meter have also been developed; mark the displacement value with the largest value as displacement data WY, through the formula DM=α1*MJ+α2*YL+α3*WY e The section coefficient DM of the section in the segmented area is obtained. The section coefficient is a value that reflects the coverage range and deformation degree of the surrounding rock section. The larger the value of the section coefficient, the larger the coverage range of the surrounding rock section and the higher the deformation degree. Among them, α1, α2 and α3 are all proportional coefficients, and α1>α2>α3>1, e is a natural constant, and the value of e is 2.718. The section with the largest value of the section coefficient DM in the segmented area is marked as the main section of the segmented area, and all the main sections in the segmented area are sent to the intelligent monitoring platform. After receiving the main section, the intelligent monitoring platform sends the main section to the distribution analysis module; the segmented area is analyzed, and the section coefficient is obtained by comprehensive analysis and calculation of multiple deformation parameters in the section. The deformation risk degree in the section is fed back through the section coefficient, and the main section in the segmented area is marked by the numerical value of the section coefficient. While feeding back the section coverage inside the segmented area, data support is provided for the section distribution analysis.

[0036] The distribution analysis module is used to analyze the cross-sectional distribution status of the tunnel after receiving the main section: obtain the center point of the main section, make a dividing line in the middle position of the segmentation area, and the dividing line divides the segmentation area into a starting area and an ending area. The starting area is close to the starting position of the tunnel segmentation direction, and the ending area is close to the extension position of the tunnel segmentation direction. If the center point of the main section is located in the starting area, the distribution value of the main section is marked as 0; if the center point of the main section is located at the ending position, the distribution value of the main section is marked as 1; perform distribution analysis on the main section in the segmentation area: two adjacent segmentation areas form an area group, mark the segmentation area with the smallest serial number in the area group as element A of the area group, and mark the segmentation area with the largest serial number in the area group as element B of the area group; if the distribution value of element A is 0 and the distribution value of element B is 1, the distribution characteristics of the segmentation area corresponding to element A are marked as safe; if the distribution value of element A is is 1 and the distribution value of element B is 0, then the distribution characteristics of the segmented area corresponding to element A are marked as dangerous; otherwise, the distribution characteristics of the segmented area corresponding to element A are marked as fuzzy; the distribution characteristics of all segmented areas are sent to the comprehensive monitoring module through the intelligent monitoring platform; the number of segmented areas with safe, fuzzy and dangerous distribution characteristics in the tunnel are marked as safety value AS, modulus value MS and danger value WS respectively, and the distribution coefficient FB of the tunnel is obtained by the formula FB=β1*AS+β2*MS+β3*WS. The distribution coefficient is a value reflecting the concentration degree of the section in the tunnel. The larger the value of the distribution coefficient, the higher the concentration degree of the section in the tunnel; β1, β2 and β3 are all proportional coefficients, and β3>β2>β1>1; the distribution threshold FBmax is obtained through the storage module, and the distribution coefficient FB of the tunnel is compared with the distribution threshold FBmax: if the distribution coefficient FB is less than the distribution threshold FB max , then it is determined that the cross-sectional distribution state of the tunnel meets the requirements; if the distribution coefficient FB is greater than or equal to the distribution threshold FB max , it is determined that the cross-sectional distribution state of the tunnel does not meet the requirements, and a distribution anomaly signal is generated and sent to the mobile terminal of the manager through the intelligent monitoring platform; the cross-sectional distribution state of the tunnel is analyzed, and the distribution characteristics of each segmented area are marked by dividing the main section, the starting area and the ending area, and then the distribution characteristic marking results are numerically calculated to obtain the distribution coefficient. The distribution coefficient is used to determine whether there is a risk in the cross-sectional distribution state in the tunnel, and feedback is given to the deformation risk of the tunnel surrounding rock as a whole.

[0037] The comprehensive monitoring module is used to conduct comprehensive monitoring and analysis of the deformation risk of the tunnel: the deformation coefficient BX of the segmented area is obtained by the formula BX=t1*(γ1*DL+γ2*DJ), where γ1 and γ2 are both proportional coefficients, and γ1>γ2>1, t1 is the correction factor, and the value-taking process of t1 includes: if the distribution characteristics of the segmented area are safe, then t1=0.85; if the distribution characteristics of the segmented area are fuzzy, then t1=1; if the distribution characteristics of the segmented area are dangerous, then t1=1.15; the deformation threshold BX is obtained through the storage module. max , the deformation coefficient BX and the deformation threshold BX max Compare: If the deformation coefficient BX is less than the deformation threshold BX max , then the deformation state of the segmented area meets the requirements; if the deformation coefficient BX is greater than or equal to the deformation threshold BX max , it is determined that the deformation state of the segmented area does not meet the requirements, and the comprehensive monitoring module sends a deformation warning signal to the intelligent monitoring platform. After receiving the deformation warning signal, the intelligent monitoring platform sends the deformation warning signal to the mobile terminal of the manager; the deformation risk of the tunnel is comprehensively monitored and analyzed, and the deformation coefficient of the segmented area is obtained by comprehensively analyzing the cross-sectional parameters and distribution feature marking results in the segmented area. Then, the deformation coefficient is used to feedback the explicit deformation risk and invisible distribution risk in the segmented area to improve the accuracy of deformation monitoring.

[0038] Embodiment 2

[0039] like Figure 2 As shown, an intelligent monitoring method for deformation of soft surrounding rock of shallow buried large-section tunnels includes the following steps:

[0040] Step 1: Segment the tunnel into regions. Segment the tunnel into regions with a length of L1 meters on one side of the tunnel and obtain a number of segmented regions.

[0041] Step 2: Perform cross-section analysis on the segmented area and obtain the cross-section coefficient of each cross-section. Mark the main cross-section of the segmented area by the value of the cross-section coefficient, and provide data support for cross-section distribution analysis while providing feedback on the cross-section coverage within the segmented area.

[0042] Step 3: Analyze the cross-sectional distribution of the tunnel and obtain the distribution coefficient of the tunnel. Use the value of the distribution coefficient to determine whether the cross-sectional distribution of the tunnel meets the requirements. Use the distribution coefficient to determine whether there is a risk in the cross-sectional distribution of the tunnel, and provide feedback on the deformation risk of the tunnel surrounding rock as a whole.

[0043] Step 4: Conduct comprehensive monitoring and analysis on the deformation risk of the tunnel and obtain the deformation coefficient of the segmented area. Determine whether the deformation state of the segmented area meets the requirements based on the numerical value of the deformation coefficient. Use the deformation coefficient to provide feedback on the explicit deformation risk and invisible distribution risk in the segmented area to improve the accuracy of deformation monitoring.

[0044] An intelligent monitoring system for deformation of soft surrounding rocks in shallow-buried large-section tunnels. When working, the tunnel is divided into several divided areas at a length value of L1 meters on one side of the tunnel; the divided areas are cross-sectionally analyzed to obtain the section coefficients of each section, and the main sections of the divided areas are marked by the values ​​of the section coefficients; the cross-sectional distribution state of the tunnel is analyzed to obtain the distribution coefficient of the tunnel, and whether the cross-sectional distribution state of the tunnel meets the requirements is determined by the value of the distribution coefficient; the deformation risk of the tunnel is comprehensively monitored and analyzed to obtain the deformation coefficients of the divided areas, and whether the deformation state of the divided areas meets the requirements is determined by the numerical values ​​of the deformation coefficients.

[0045] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0046] The above formulas are obtained by collecting a large amount of data and performing software simulation to select a formula close to the actual value. The coefficients in the formula are set by technicians in this field according to actual conditions; for example: Formula DM = α1*MJ+α2*YL+α3*WY e ; A technician in this field collects multiple groups of sample data and sets a corresponding section coefficient for each group of sample data; Substitute the set section coefficient and the collected sample data into the formula, any three formulas constitute a three-variable linear equation system, screen the calculated coefficients and take the average, and obtain the values ​​of α1, α2 and α3 as 5.47, 3.52 and 2.67 respectively;

[0047] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding cross-sectional coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the cross-sectional coefficient is proportional to the value of the area data.

[0048] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0049] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent monitoring system for deformation of soft surrounding rock in shallow large-section tunnels, characterized in that: It includes an intelligent monitoring platform, which is communicatively connected with a tunnel segmentation module, a section analysis module, a distribution analysis module, a comprehensive monitoring module and a storage module; The tunnel segmentation module is used to segment the tunnel into regions: the tunnel is segmented at one side of the tunnel by a length value of L1 meters to obtain a plurality of segmented regions, and the segmented regions are numbered according to the segmentation order; The section analysis module is used to perform section analysis on the segmented area: obtain the section quantity data DL and section volume data DJ of the segmented area, the section quantity data DL is the number of sections in the segmented area, and the section volume data DJ is the sum of the area values ​​of all sections in the segmented area; send the section quantity data DL and section volume data DJ of the segmented area to the comprehensive monitoring module through the intelligent monitoring platform; obtain the area data MJ, pressure data YL and displacement data WY of the section in the segmented area, perform numerical calculations on the area data MJ, pressure data YL and displacement data WY to obtain the section coefficient DM of the section in the segmented area; mark the section with the largest value of the section coefficient DM in the segmented area as the main section of the segmented area, send all the main sections in the segmented area to the intelligent monitoring platform, and the intelligent monitoring platform sends the main section to the distribution analysis module after receiving the main section; The distribution analysis module is used to analyze the cross-sectional distribution state of the tunnel after receiving the main cross-section and obtain the distribution characteristics of the main cross-section of the segmented area, and send the distribution characteristics of all segmented areas to the comprehensive monitoring module through the intelligent monitoring platform; the number of segmented areas with safe, fuzzy and dangerous distribution characteristics in the tunnel is marked as a safety value AS, a modulus value MS and a danger value WS respectively, and a distribution coefficient FB is obtained by numerical calculation, and whether the cross-sectional distribution state of the tunnel meets the requirements is judged by the numerical value of the distribution coefficient FB; The comprehensive monitoring module is used to conduct comprehensive monitoring and analysis on the deformation risk of the tunnel and obtain the deformation coefficient BX, and to determine whether the deformation state of the segmented area meets the requirements according to the value of the deformation coefficient BX; The area data MJ of the section in the segmented area is the area value of the section. The process of obtaining the pressure data YL includes: randomly selecting L2 representative detection points in the section, measuring the surrounding rock pressure at the representative detection points and obtaining L2 detection pressure values, and marking the detection pressure value with the largest value as the pressure data YL; the process of obtaining the displacement data WY includes: measuring the displacement value of the surrounding rock at the representative detection points using a multi-point displacement meter and obtaining L2 detection displacement values, and marking the detection displacement value with the largest value as the displacement data WY; The process of acquiring the distribution characteristics of the segmented area includes: acquiring the center point of the main section, making a segmentation line in the middle position of the segmented area, the segmentation line divides the segmented area into a starting area and an ending area, the starting area is close to the starting position of the tunnel segmentation direction, and the ending area is close to the extension position of the tunnel segmentation direction. If the center point of the main section is located in the starting area, the distribution value of the main section is marked as 0; if the center point of the main section is located at the ending position, the distribution value of the main section is marked as 1; the distribution analysis of the main section in the segmented area is performed and the distribution characteristics of the segmented area are marked as safe, fuzzy or dangerous.

2. The intelligent monitoring system for soft surrounding rock deformation of shallow buried large-section tunnels according to claim 1 is characterized in that: The specific process of performing distribution analysis on the main section in the segmented area includes: forming an area group from two adjacent segmented areas, marking the segmented area with the smallest serial number in the area group as element A of the area group, and marking the segmented area with the largest serial number in the area group as element B of the area group; if the distribution value of element A is 0 and the distribution value of element B is 1, then the distribution feature of the segmented area corresponding to element A is marked as safe; if the distribution value of element A is 1 and the distribution value of element B is 0, then the distribution feature of the segmented area corresponding to element A is marked as dangerous; otherwise, the distribution feature of the segmented area corresponding to element A is marked as fuzzy.

3. The intelligent monitoring system for soft surrounding rock deformation of shallow buried large-section tunnels according to claim 2 is characterized in that: The specific process of determining whether the cross-sectional distribution state of the tunnel meets the requirements includes: obtaining the distribution threshold FBmax through the storage module, and comparing the distribution coefficient FB of the tunnel with the distribution threshold FBmax: if the distribution coefficient FB is less than the distribution threshold FBmax, it is determined that the cross-sectional distribution state of the tunnel meets the requirements; if the distribution coefficient FB is greater than or equal to the distribution threshold FBmax, it is determined that the cross-sectional distribution state of the tunnel does not meet the requirements, and a distribution abnormality signal is generated and sent to the mobile terminal of the manager through the intelligent monitoring platform.

4. The intelligent monitoring system for soft surrounding rock deformation of shallow buried large-section tunnels according to claim 3 is characterized in that: The specific process of the comprehensive monitoring module for comprehensive monitoring and analysis of the deformation risk of the tunnel includes: obtaining the deformation coefficient BX of the segmented area through the formula BX=t1*(γ1*DL+γ2*DJ), wherein γ1 and γ2 are both proportional coefficients, and γ1>γ2>1, and t1 is the correction factor; obtaining the deformation threshold BXmax through the storage module, and comparing the deformation coefficient BX with the deformation threshold BXmax: if the deformation coefficient BX is less than the deformation threshold BXmax, it is determined that the deformation state of the segmented area meets the requirements; if the deformation coefficient BX is greater than or equal to the deformation threshold BXmax, it is determined that the deformation state of the segmented area does not meet the requirements, and the comprehensive monitoring module sends a deformation warning signal to the intelligent monitoring platform, and after receiving the deformation warning signal, the intelligent monitoring platform sends the deformation warning signal to the mobile terminal of the manager.

5. The intelligent monitoring system for soft surrounding rock deformation of shallow buried large-section tunnels according to claim 4 is characterized in that: The process of taking the value of t1 includes: if the distribution characteristic of the segmented area is safe, then t1=0.85; if the distribution characteristic of the segmented area is fuzzy, then t1=1; if the distribution characteristic of the segmented area is dangerous, then t1=1.

15.

6. An intelligent monitoring system for soft surrounding rock deformation of shallow buried large-section tunnels according to any one of claims 1 to 5, characterized in that: The working method of the intelligent monitoring system for soft surrounding rock deformation of shallow buried large-section tunnels includes the following steps: Step 1: Segment the tunnel into regions. Segment the tunnel into regions with a length of L1 meters on one side of the tunnel and obtain a number of segmented regions. Step 2: Perform cross-sectional analysis on the segmented area and obtain the cross-sectional coefficient of each cross-sectional area, and mark the main cross-sectional area by the value of the cross-sectional coefficient; Step 3: Analyze the cross-sectional distribution state of the tunnel and obtain the distribution coefficient of the tunnel, and determine whether the cross-sectional distribution state of the tunnel meets the requirements according to the value of the distribution coefficient; Step 4: Conduct comprehensive monitoring and analysis on the deformation risk of the tunnel and obtain the deformation coefficient of the segmented area. Determine whether the deformation state of the segmented area meets the requirements based on the numerical value of the deformation coefficient.

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