Tunnel surrounding rock block collapse comprehensive monitoring and early warning method and system based on mems sensor

Abstract

The application provides a tunnel surrounding rock block collapse comprehensive monitoring and early warning method and system based on MEMS sensing, and belongs to the technical field of tunnel surrounding rock block collapse disaster monitoring and early warning, and comprises the following steps: based on the features of the local block body obtained by combining the internal occurrence structure surface of the surrounding rock and the openwork surface formed by excavation, MEMS sensors are arranged, three-dimensional vibration data of the local block body are collected, spatial inclination, three-dimensional vibration absolute mean value and dominant frequency are calculated and compiled, four-level change trends of the spatial inclination, three-dimensional vibration absolute mean value and dominant frequency are obtained respectively, and the maximum values of the respective change rates are recorded; based on the maximum values of the respective change rates, it is determined whether the second-level change trend or the third-level change trend needs to jump to the next-level change trend; based on the final change trends of the spatial inclination, three-dimensional vibration absolute mean value and dominant frequency, the early warning level of each local block body of the tunnel surrounding rock is comprehensively judged. The application can monitor and early warn the tunnel surrounding rock block collapse.

Description

Technical Field

[0001] This invention belongs to the field of tunnel surrounding rock block collapse disaster monitoring and early warning technology, specifically referring to a comprehensive monitoring and early warning method and system for tunnel surrounding rock block collapse based on MEMS sensing. Background Technology

[0002] Tunnel (tunnel) surrounding rock mass collapse refers to an underground dynamic disaster in which isolated or semi-isolated dangerous rock masses, formed by the combination and cutting of internal structural planes and excavated free faces, suddenly collapse and become unstable under the influence of factors such as their own weight, rainfall infiltration, and blasting operations. This type of disaster is characterized by its significant suddenness, short duration, and lack of significant macroscopic precursors. Furthermore, tunnel (tunnel) surrounding rock masses are formed by the combination and cutting of multiple structural planes and excavated free faces; that is, the stability of the rock mass is controlled by a combination of multiple weak planes, resulting in a significant spatial characteristic of the collapse, rather than instability and failure along a single direction. However, existing monitoring and early warning methods for tunnel (tunnel) surrounding rock mass collapse disasters only monitor in a single direction, and these methods lack comprehensive monitoring and analysis technologies that integrate multi-dimensional information collection. Summary of the Invention

[0003] To address the technical problems existing in the prior art, this invention provides a comprehensive monitoring and early warning method and system for tunnel surrounding rock block collapse based on MEMS sensing. The technical solution is as follows:

[0004] On the one hand, a comprehensive monitoring and early warning method for tunnel surrounding rock block collapse based on MEMS sensing is provided, the method including:

[0005] S1. Obtain the characteristics of the local block cut by the combination of the structural surface inside the surrounding rock and the free surface formed by excavation, and deploy MEMS sensors based on the characteristics of the local block.

[0006] S2. Acquire three-dimensional vibration data of the local block using the MEMS sensor;

[0007] S3. Based on the three-dimensional vibration data of the local block, calculate and compile the spatial tilt angle, the three-dimensional vibration absolute mean and the dominant frequency;

[0008] S4. Based on the reorganized spatial tilt angle, three-dimensional vibration absolute mean and dominant frequency data, obtain the four-level variation trends of spatial tilt angle, three-dimensional vibration absolute mean and dominant frequency respectively, and record the maximum value of their respective variation rates.

[0009] S5. Based on the maximum value of the change rate of the spatial tilt angle, the absolute mean of the three-dimensional vibration, and the dominant frequency, determine whether the second-level or third-level change trend needs to jump to the next level of change trend.

[0010] S6. Based on the changes in the spatial tilt angle, the three-dimensional vibration absolute mean, and the dominant frequency, a comprehensive early warning level is determined for each local block of the tunnel surrounding rock.

[0011] On the other hand, a comprehensive monitoring and early warning system for tunnel surrounding rock block collapse based on MEMS sensing is provided, the system comprising:

[0012] The acquisition and deployment module is used to acquire the characteristics of the local block cut by the combination of the internal structure surface of the surrounding rock and the free surface formed by excavation, and to deploy MEMS sensors based on the characteristics of the local block.

[0013] The acquisition module is used to acquire three-dimensional vibration data of the local block through the MEMS sensor;

[0014] The calculation and compilation module is used to calculate and compile the spatial tilt angle, the three-dimensional vibration absolute mean and the dominant frequency based on the three-dimensional vibration data of the local block;

[0015] The recording module is used to obtain the four-level variation trends of the spatial tilt angle, the three-dimensional vibration absolute mean, and the dominant frequency based on the compiled spatial tilt angle, the three-dimensional vibration absolute mean, and the dominant frequency data, and to record the maximum value of each variation rate.

[0016] The determination module is used to determine whether the second-level or third-level trend needs to transition to the next level trend based on the maximum value of the change rate of the spatial tilt angle, the absolute mean of the three-dimensional vibration, and the dominant frequency.

[0017] The comprehensive discrimination module is used to comprehensively discriminate the early warning level of each local block of the tunnel surrounding rock based on the changes in the spatial tilt angle, the three-dimensional vibration absolute mean and the dominant frequency.

[0018] On the other hand, an electronic device is provided, comprising a processor and a memory, wherein the memory stores at least one instruction, which is loaded and executed by the processor to realize the above-mentioned comprehensive monitoring and early warning method for tunnel surrounding rock block collapse based on MEMS sensing.

[0019] On the other hand, a computer-readable storage medium is provided, wherein at least one instruction is stored in the storage medium, and the at least one instruction is loaded and executed by a processor to realize the above-mentioned comprehensive monitoring and early warning method for tunnel surrounding rock block collapse based on MEMS sensing.

[0020] The beneficial effects of the technical solution provided by this invention include at least the following:

[0021] This invention identifies the monitoring target by acquiring characteristic information such as the orientation of the internal structural surface of a local dangerous block, the angle between the internal structural surface and the free surface, the angle between the structural surface and the tunnel axis, and the surface roughness. It also sets the installation method of the MEMS sensor and uses integrated MEMS sensor acquisition and calculation to consider the spatial tilt angle, three-dimensional vibration absolute mean, and dominant frequency data of the surrounding rock block instability. Based on the analysis of the changing trends and rates of change of the three indicators, the invention comprehensively determines the early warning level of the surrounding rock block collapse.

[0022] This invention addresses the limitations of conventional displacement monitoring and natural frequency monitoring methods, which fail to consider the spatial characteristics of surrounding rock block collapse, and the inability of conventional monitoring methods to achieve integrated acquisition and calculation of multi-dimensional information on surrounding rock block collapse. It proposes mathematical expressions for the spatial dip angle characterizing the deformation characteristics of dangerous surrounding rock blocks, the three-dimensional vibration absolute mean characterizing the degree of loosening of dangerous surrounding rock blocks, and the dominant frequency characterizing the connection strength between dangerous surrounding rock blocks and stable rock mass. This enables integrated analysis of at least three dimensions of information related to surrounding rock block collapse and instability, forming a comprehensive monitoring and early warning method for tunnel surrounding rock collapse.

[0023] This invention solves the problem that conventional displacement early warning systems struggle to capture early signs of instability in tunnel (cavity) surrounding rock masses through a comprehensive monitoring and early warning method for tunnel surrounding rock collapse. This significantly improves the timeliness and accuracy of collapse disaster early warning. Furthermore, compared to comprehensive monitoring methods that collect multiple indicators such as displacement, microseismic activity, and natural frequency, this invention substantially reduces monitoring costs.

[0024] This invention is simple to operate, low in cost, and provides reliable early warning and judgment results. It can monitor the collapse of surrounding rock blocks in tunnels in real time, ensuring safety during tunnel construction and operation, and is suitable for widespread promotion. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a flowchart of a comprehensive monitoring and early warning method for tunnel surrounding rock block collapse based on MEMS sensing, provided by an embodiment of the present invention.

[0027] Figure 2 This is a schematic diagram of the selection of dangerous blocks in the surrounding rock of a tunnel and the installation of MEMS sensors provided in an embodiment of the present invention;

[0028] Figure 3 This is a schematic diagram of anomaly filtering for three-dimensional vibration data of unstable rock masses provided in an embodiment of the present invention;

[0029] Figure 4 This is a schematic diagram of supplementing missing values ​​of spatial dip angle of dangerous rock mass and data smoothing provided in the embodiments of the present invention;

[0030] Figure 5 This is a schematic diagram illustrating the four-level variation trend of spatial tilt angle provided in an embodiment of the present invention;

[0031] Figure 6 This is a schematic diagram illustrating a significant abrupt change in spatial tilt angle that has not recovered for a long period of time, provided by an embodiment of the present invention.

[0032] Figure 7 This is a schematic diagram illustrating the four-level variation trend of the three-dimensional vibration absolute mean provided in an embodiment of the present invention;

[0033] Figure 8 This is a schematic diagram illustrating the significant abrupt change in the absolute mean of three-dimensional vibration and its failure to recover over a long period of time, provided in an embodiment of the present invention.

[0034] Figure 9 This is a schematic diagram of the four-level variation trend of the dominant frequency provided in the embodiments of the present invention;

[0035] Figure 10 This is a schematic diagram illustrating a significant change in the dominant frequency that has not recovered for a long period of time, provided by an embodiment of the present invention.

[0036] Figure 11 This is a schematic diagram illustrating the transition of the spatial tilt angle from level II to level III in this invention;

[0037] Figure 12 This is a schematic diagram of the MEMS sensor installation method provided in an embodiment of the present invention;

[0038] Figure 13 This is a spatial tilt angle data curve provided in an embodiment of the present invention;

[0039] Figure 14 This is a three-dimensional vibration absolute mean data curve provided in the embodiments of the present invention;

[0040] Figure 15 This is the dominant frequency data curve provided in the embodiments of the present invention;

[0041] Figure 16 This is a line graph showing the evolution of the early warning level of surrounding rock collapse over time, provided in an embodiment of the present invention.

[0042] Figure 17 This is a block diagram of a comprehensive monitoring and early warning system for tunnel surrounding rock block collapse based on MEMS sensing, provided in an embodiment of the present invention.

[0043] Figure 18This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0044] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0045] This invention provides a comprehensive monitoring and early warning method for tunnel surrounding rock block collapse based on MEMS sensing. This method can be implemented by an electronic device, which can be a terminal or a server. Figure 1 The diagram shown is a flowchart of the method. The processing flow may include the following steps:

[0046] S1. Obtain the characteristics of the local block cut by the combination of the structural surface inside the surrounding rock and the free surface formed by excavation, and deploy MEMS sensors based on the characteristics of the local block.

[0047] Optionally, the features of the local block in S1 include: the orientation of the internal structural surface of the block, the angle between the internal structural surface and the free surface, the angle between the structural surface and the tunnel axis, and the surface roughness.

[0048] The deployment of MEMS sensors based on the features of the local block in S1 includes:

[0049] By comprehensively analyzing the attitude of internal structural planes, the angle between internal structural planes and the free face, and the angle between structural planes and the tunnel axis, dangerous rock blocks with collapse potential formed by the combination of various structural planes are identified. The rock mass integrity of these dangerous rock blocks is then analyzed and evaluated. For rock blocks with high integrity, one MEMS sensor is used for monitoring. For rock blocks with low integrity, based on the roughness of each structural plane, key potential hazard areas are identified, and multiple MEMS sensors are installed. The rock mass integrity is characterized by the number of volumetric joints, which is the number of structural planes per cubic meter of rock mass, calculated using the following formula:

[0050] (1)

[0051] in, This represents the volumetric joint number of the rock mass, expressed in units of joints / m. 3 ; This represents the number of structural surface groups within the statistical region. For the first The number of structural surfaces per meter along the normal direction in a group; This represents the number of ungrouped joints per cubic meter of rock mass.

[0052] In one feasible implementation, the number of volumetric joints in the rock mass is measured directly, that is, the number of structural planes per unit volume of rock mass is directly counted. And a setting is made when... <3 items / m 3 When the rock mass is in good condition, its integrity is high; conversely, when it is not in good condition, its integrity is poor.

[0053] In one feasible implementation, the internal structural surface of the block refers to the weak geological interfaces such as strata, joints, and faults within the surrounding rock of the tunnel. The attitude of the internal structural surface refers to the strike, dip, and dip angle of the weak geological interface. Through comprehensive analysis of the attitude of the internal structural surface, the angle between the internal structural surface and the free face, and the angle between the structural surface and the tunnel axis, dangerous rock blocks with collapse conditions formed by the combination and cutting of various structural surfaces are identified. The integrity of the dangerous rock blocks is then analyzed and evaluated. For rock blocks with high integrity, only one MEMS sensor can be used for monitoring. For rock blocks with low integrity, multiple MEMS sensors need to be installed to identify key potential hazards based on the roughness of each structural surface.

[0054] like Figure 2 As shown, the internal structural surfaces of the surrounding rock block include internal structural surface 1, internal structural surface 2, and internal structural surface 3, while the free surface 4 is formed after excavation. Through analysis, a dangerous rock block 5 with collapse conditions was identified, formed by the combination and cutting of various structural surfaces. This rock block has high integrity. A MEMS sensor (numbered 6) was installed, and the installation methods included drilling, expansion bolts, or high-strength glue fixing to the surface. The sensor was installed in the middle area cut by structural surface 1 and structural surface 2, with a depth of 30cm. After installation, concrete was poured to seal it.

[0055] Among them, MEMS sensors are high-precision intelligent sensing equipment based on microelectromechanical systems. They can realize ultra-high frequency continuous acquisition and calculation of three-dimensional vibration data of objects. The acquired three-dimensional vibration data simultaneously includes gravitational acceleration and externally induced vibration acceleration of the object, enabling integrated acquisition and calculation of object tilt characteristics and vibration characteristics.

[0056] S2. Acquire three-dimensional vibration data of the local block using the MEMS sensor;

[0057] Optionally, the three-dimensional vibration data of the local block acquired in S2 refers to the triaxial acceleration data acquired by the MEMS sensor:

[0058] (2)

[0059] in, A vector of three-axis acceleration data acquired by a MEMS sensor; Acceleration data collected in the X, Y, and Z directions; This is the three-dimensional component data of static gravitational acceleration collected in the XYZ directions; To collect three-dimensional component data of vibration acceleration caused by external factors in the XYZ directions.

[0060] Optionally, the method in this embodiment of the invention further includes: filtering outliers from the three-dimensional vibration data of the unstable rock mass.

[0061] Optionally, the quartile method can be used to analyze the three-dimensional vibration data acquired by the MEMS sensor, marking outliers that exceed the normal range. When the total number of outliers accounts for 30% of the total vibration data, the vibration data is discarded. Figure 3 As shown, this method filters abnormal vibration data caused by construction activities such as blasting and drilling, removing abnormal information from the raw data used for index calculation and avoiding false alarms in subsequent index calculations.

[0062] S3. Based on the three-dimensional vibration data of the local block, calculate and compile the spatial tilt angle, the three-dimensional vibration absolute mean and the dominant frequency;

[0063] Optionally, the spatial tilt angle in S3 , is the angle between the initial three-dimensional vector and the current three-dimensional vector of the dangerous rock mass, in degrees, calculated by equation (3):

[0064] (3)

[0065] in, The static gravitational acceleration triaxial component data corresponding to the initial state three-dimensional vector of the dangerous rock mass acquired by the MEMS sensor; The static gravitational acceleration triaxial component data corresponding to the three-dimensional vector of the current state of the dangerous rock mass acquired by the MEMS sensor;

[0066] This invention enables the monitoring of spatial tilt deformation characteristics during the instability of a dangerous rock mass by calculating the angle between the initial three-dimensional vector and the current three-dimensional vector of the rock mass. This overcomes the shortcomings of single-direction deformation monitoring and early warning methods such as tunnel arch settlement, clearance convergence, horizontal displacement, and horizontal tilt angle.

[0067] The three-dimensional vibration absolute mean in S3 It is calculated from the three-dimensional component data of the vibration acceleration of the dangerous rock mass according to equation (4), and the unit is mg:

[0068] (4)

[0069] in, The dangerous rock mass, as captured by the MEMS sensor, was caused by external factors. One vibration acceleration triaxial component data; N represents the amount of monitored data;

[0070] This invention overcomes the difficulty in determining the instability direction throughout the entire collapse process by integrating the three-dimensional vibration characteristics of the dangerous rock mass, thus achieving spatial characterization of the vibration characteristics throughout the collapse process. This index effectively characterizes the vibration energy and amplitude of the surrounding rock mass, thereby indirectly reflecting the degree of loosening of the rock mass.

[0071] The dominant frequency in S3 It is calculated from the three-dimensional component data of the vibration acceleration of the dangerous rock mass according to equation (5), and the unit is Hz:

[0072] (5)

[0073] in, The fundamental frequencies of the dangerous rock mass in the X, Y, and Z directions are calculated from the three-dimensional component data of the vibration acceleration of the dangerous rock mass caused by external factors, collected by MEMS sensors, including:

[0074] The Welch method is used to process the three-dimensional component data of vibration acceleration acquired by MEMS sensors, specifically including:

[0075] The power spectrum of the rock mass vibration signal is calculated by segmenting the signal, overlapping the segmented data, windowing, calculating the periodogram, and averaging, as shown in equation (6):

[0076] (6)

[0077] in, Indicates frequency The corresponding power spectral amplitude at that location; This indicates that the entire data segment has been divided into K segments; This represents the first division of the entire data segment. The segment data is obtained after calculation at the frequency The amplitude at point i, 1≤i≤K;

[0078] The vibration data of the rock block in the X, Y and Z directions are processed to obtain their respective power spectra. After removing high-frequency noise components, dominant site periods and spurious modal components, the frequency value corresponding to the position of the maximum peak in the power spectrum within a preset frequency range (in this example, the abscissa is in the range of 5~50Hz) is taken as the fundamental frequency.

[0079] This invention, by selecting the minimum fundamental frequency in the three-dimensional directions of the surrounding rock mass, effectively captures the dominant modal characteristics throughout the entire process of surrounding rock mass instability. In actual engineering, the vibration characteristics of surrounding rock masses are mainly low-frequency, and low-order modes are the easiest information to monitor on-site. By selecting the minimum fundamental frequencies of the rock mass in the X, Y, and Z directions, the dominant modal information of surrounding rock mass instability can be consistently monitored, overcoming the difficulties in determining the instability direction and the continuous changes in the instability direction throughout the entire process of surrounding rock collapse. This indicator can directly characterize the degree of connection between the dangerous rock mass and the surrounding rock, thereby achieving early warning of collapse.

[0080] This invention utilizes a MEMS sensor to achieve high-frequency continuous acquisition of triaxial acceleration data at a sampling frequency of 1000Hz. The triaxial acceleration data accuracy is 20ug, the range is ±2g, and the duration of a single acquisition can be freely set. Furthermore, within a temperature range of -40℃ to 70℃ and a humidity range of 0 to 98%RH, the spatial tilt angle accuracy calculated by the MEMS sensor is ±0.005°, with a resolution of 0.0001°; the accuracy of the absolute mean of three-dimensional vibration is 0.01mg, with a resolution of 0.001mg; and the accuracy of the dominant frequency is 0.1Hz, with a resolution of 0.01Hz.

[0081] Furthermore, after calculating the spatial tilt angle, the three-dimensional absolute mean of vibration, and the dominant frequency data, these data are processed, including: imputing missing values ​​using cubic spline interpolation and smoothing the data using locally weighted regression (Lowess), such as... Figure 4 As shown, this facilitates subsequent data curve fitting and indicator trend identification.

[0082] S4. Based on the reorganized spatial tilt angle, three-dimensional vibration absolute mean and dominant frequency data, obtain the four-level variation trends of spatial tilt angle, three-dimensional vibration absolute mean and dominant frequency respectively, and record the maximum value of their respective variation rates.

[0083] Optionally, the four-level variation trend of the spatial tilt angle in S4 includes: Level I - steady stage, Level II - constant velocity deformation stage, Level III - accelerated deformation stage, and Level IV - pre-disaster deformation stage.

[0084] like Figure 5 The diagram shows the four-level trend of the spatial tilt data curve.

[0085] The so-called Level I-Stable Phase refers to the space tilt data curve satisfying the constant equation. Furthermore, the spatial tilt data fluctuation does not exceed ±0.1° in the following stages. It is a constant obtained after curve fitting;

[0086] The Level II - constant velocity deformation stage refers to the stage where the space tilt angle data curve satisfies the linear equation. ,and The stage in which The constants are obtained after curve fitting; the maximum values ​​of the spatial dip angle change rates during multiple isotropic deformation stages in the continuous monitoring of this hazardous rock mass are recorded as a set. ;

[0087] The aforementioned Level III - accelerated deformation stage refers to the stage where the spatial dip angle relative rate ratio is between 2 and 8; the maximum value of the spatial dip angle change rate during multiple accelerated deformation stages in the continuous monitoring of this hazardous rock mass is recorded as a set. ;

[0088] The Level IV - Disaster-Pressure Deformation Stage refers to a stage where the relative rate ratio of spatial tilt is greater than 8, or where the abrupt change in spatial tilt is greater than... The rate of change of spatial tilt angle is greater than And during the period when the space tilt data has not been recovered for a long time, among which These are experience values ​​defined based on preliminary case analysis;

[0089] like Figure 6 As shown, in one feasible embodiment, based on previous experience in monitoring the collapse of surrounding rock blocks, and considering that the surrounding rock is an approximately rigid structure that cannot withstand large deformations, the threshold for the sudden change in spatial tilt angle is set to 1°, and the threshold for the rate of change of spatial tilt angle is set to 0.5° / h. If the deformation has not recovered for 5 consecutive hours, it indicates that the surrounding rock block is undergoing permanent macroscopic deformation, with a high probability of collapse, and is in the Level IV - pre-disaster deformation stage.

[0090] The ratio of spatial tilt angle relative rates is calculated using equation (7):

[0091] (7)

[0092] in, It is the ratio of the spatial tilt angle relative velocity at time t, and is dimensionless; The rate of change of the spatial tilt angle at time t; It is the arithmetic mean of the rate of change of spatial tilt angle at each time interval during the constant velocity deformation stage;

[0093] The rate of change of the spatial tilt angle is calculated by equation (8):

[0094] (8)

[0095] in, Indicates the rate of change of the spatial tilt angle; These represent the times of the 0th and (0-1)th data uploads, respectively. They represent in and Spatial tilt data at any given time.

[0096] In the field of geological disaster monitoring and early warning, the displacement tangent angle is mainly used to divide the instability stages of disasters such as landslides and collapses. However, research has shown that this method, due to the different dimensions of the horizontal and vertical coordinates, will cause the tangent angle of the curve to change at any time if any coordinate axis is stretched or compressed, resulting in an insufficiently rigorous division of instability stages. Therefore, this invention proposes to define the spatial dip angle relative rate ratio by dividing the rate of change of the spatial dip angle at any time at each point by the rate of the constant-rate deformation stage. This normalizes the horizontal and vertical coordinates, resulting in a dimensionless spatial dip angle rate ratio. This avoids the one-sidedness of absolute rates and eliminates the influence of dimensions, making the division of the various stages of tunnel (cavity) surrounding rock collapse and instability more reasonable.

[0097] Optionally, the four-level variation trend of the three-dimensional vibration absolute mean in S4 includes: Level I - constant micro-motion stage, Level II - linear amplitude evolution stage, Level III - amplitude power law gradual increase stage, and Level IV - amplitude power law steep increase stage.

[0098] like Figure 7 The figure shows a schematic diagram of the four-level variation trend of the three-dimensional vibration absolute mean data curve.

[0099] The Level I - constant-time micro-motion stage refers to the stage where the three-dimensional vibration absolute mean data curve satisfies the constant equation. Furthermore, the fluctuation of the absolute mean of the three-dimensional vibration data does not exceed ±0.5 mg. It is a constant obtained after curve fitting;

[0100] The Level II-amplitude linear evolution stage refers to the stage where the three-dimensional vibration absolute mean data curve satisfies the linear equation. ,and The stage in which The constants are those obtained after curve fitting; the maximum values ​​of the absolute mean change rate of three-dimensional vibration during multiple linear evolution stages of amplitude in the continuous monitoring of this hazardous rock mass are recorded as a set. ;

[0101] The aforementioned Level III amplitude power-law gradual rise stage refers to the stage where the three-dimensional vibration absolute mean data curve satisfies the power-law equation. ,and The stage in which The constants are those obtained after curve fitting; the maximum values ​​of the absolute mean change rate of three-dimensional vibration during multiple power-law rising phases of the continuous monitoring of this hazardous rock mass are recorded as a set. ;

[0102] The aforementioned Level IV amplitude power-law steep increase stage refers to the stage where the three-dimensional vibration absolute mean data curve satisfies the power-law equation. ,and The stage, or the abrupt change in the absolute mean of three-dimensional vibration is greater than The rate of change of the absolute mean of three-dimensional vibration is greater than Furthermore, during the period when the absolute mean data of three-dimensional vibration did not recover for a long time, among which These are experience values ​​defined based on preliminary case analysis.

[0103] like Figure 8 As shown, in a feasible embodiment, considering the fluctuation range of vibration acceleration data collected when the MEMS sensor is not fixed to the surrounding rock under the influence of the on-site environment, and combined with the experience of previous cases of surrounding rock block collapse monitoring, the threshold of the sudden change of the absolute mean of three-dimensional vibration is set to 2mg, and the threshold of the rate of change of the absolute mean of three-dimensional vibration is set to 2mg / h. If it does not recover for 5 consecutive hours, it indicates that the vibration energy and amplitude of the surrounding rock block have increased suddenly, the loosening degree of the rock block has increased significantly, the probability of collapse is high, and it is in the stage of level IV - amplitude power law steep increase.

[0104] Optionally, the four-level variation trend of the dominant frequency in S4 includes: Level I - rock mass integrity stage, Level II - rock mass separation stage, Level III - rock mass separation acceleration stage, and Level IV - rock mass failure stage;

[0105] like Figure 9 The diagram shows the four-level trend of the dominant frequency data curve.

[0106] The so-called Grade I - intact rock mass stage refers to the stage where the dominant frequency data curve satisfies the constant equation. And the dominant frequency data fluctuation does not exceed ±1Hz in the following period, It is a constant obtained after curve fitting;

[0107] The aforementioned Level II rock mass separation stage refers to the stage where the dominant frequency data curve satisfies a linear equation. ,and The stage in which The constants are those obtained after curve fitting; the maximum values ​​of the dominant frequency change rates during multiple rock mass separation stages in the continuous monitoring of this hazardous rock mass are recorded as a set. ;

[0108] The aforementioned Level III - rock mass separation acceleration stage refers to the stage where the dominant frequency data curve satisfies the power-law equation. ,and The stage in which The constants are those obtained after curve fitting; the maximum values ​​of the dominant frequency change rates during multiple rock mass separation acceleration stages in the continuous monitoring of this hazardous rock mass are recorded as a set. ;

[0109] The aforementioned Level IV rock mass failure stage refers to the stage where the dominant frequency data curve satisfies the power-law equation. ,and The stage, or the dominant frequency mutation amount is greater than The rate of change of the dominant frequency is greater than And during the period when the dominant frequency data did not recover for a long time, among which These are experience values ​​defined based on preliminary case analysis.

[0110] like Figure 10 As shown, in one feasible embodiment, considering the dominant frequency range after the surrounding rock block collapses into an isolated rock, and combining the experience of previous surrounding rock block collapse monitoring cases, the threshold for the dominant frequency mutation is set to 3Hz, the threshold for the absolute value of the dominant frequency change rate is 1Hz / h, and if it does not recover for 5 consecutive hours, it indicates that the connection strength between the rock block and the surrounding rock has decreased significantly, the probability of collapse is high, and it is in the Class IV rock mass failure stage.

[0111] S5. Based on the maximum value of the change rate of the spatial tilt angle, the absolute mean of the three-dimensional vibration, and the dominant frequency, determine whether the second-level or third-level change trend needs to jump to the next level of change trend.

[0112] Optionally, in step S5, determining whether a second-level or third-level trend needs to transition to the next level trend based on the maximum value of the spatial tilt rate includes:

[0113] The spatial tilt angle is in the Level II - constant velocity deformation stage, and the rate of change of the spatial tilt angle is greater than... In actual early warning, the spatial tilt angle is transitioned from Level II - constant velocity deformation stage to Level III - accelerated deformation stage;

[0114] The spatial tilt angle is in the Level III - accelerated deformation stage, and the rate of change of the spatial tilt angle is greater than... In actual early warning, the spatial tilt angle is shifted from Level III - accelerated deformation stage to Level IV - pre-disaster deformation stage.

[0115] Similarly, corresponding judgments and transition processing are performed on the second-order or third-order variation trends of the absolute mean of three-dimensional vibration and the dominant frequency.

[0116] Optionally, due to the influence of rainfall infiltration and repeated collapses during the monitoring of surrounding rock collapse, there may be multiple occurrences of the Level II-isotropic deformation stage and the Level III-accelerated deformation stage in terms of spatial dip angle; multiple occurrences of the Level II-linear amplitude evolution stage and the Level III-power law gradual amplitude increase stage in terms of the absolute mean of three-dimensional vibration; and multiple occurrences of the Level II-rock mass separation stage and the Level III-rock mass separation acceleration stage in terms of dominant frequency. Therefore, the rate of change of the corresponding data curves is calculated according to Equation (9), the maximum rate of change is obtained by comparison, and the values ​​are recorded respectively. , , , , , In the set.

[0117] (9)

[0118] in, Indicates the first The rate of change of each indicator; These represent the times of the 0th and (0-1)th data uploads, respectively. They represent in and The first moment Individual indicator data; =1 corresponds to the space tilt angle. =2 corresponds to the absolute mean of three-dimensional vibration. =3 corresponds to the dominant frequency.

[0119] like Figure 11 As shown, the space dip angle data curve exhibits multiple trends during the Level II-constant velocity deformation stage. The most recent fourth trend is used for illustration. The maximum space dip angle values ​​for the first three constant velocity deformation stages are recorded, forming a set of maximum rate of change values. In the most recent fourth data trend, the maximum rate of change of spatial tilt was... Greater than the maximum value in the set This indicates that the rate of constant-velocity deformation of the spatial tilt angle has exceeded the maximum value of the previous multiple deformations, increasing the risk of collapse. Therefore, in the early warning assessment, the trend of spatial tilt angle change is shifted from Level II - constant-velocity deformation stage to Level III - accelerated deformation stage, and this is given special consideration.

[0120] S6. Based on the changes in the spatial tilt angle, the three-dimensional vibration absolute mean, and the dominant frequency, a comprehensive early warning level is determined for each local block of the tunnel surrounding rock.

[0121] Optionally, the comprehensive judgment of the warning level in S6 includes: green safety level, blue attention level, yellow warning level, orange alert level, and red alarm level;

[0122] Green safety level: The trends in spatial dip angle, absolute mean of three-dimensional vibration, and dominant frequency are all in stage I. This indicates that, based on a comprehensive analysis of the rock mass's deformation, loosening, and connection with the surrounding rock, the rock mass is in a safe state with a low probability of collapse.

[0123] Blue Alert Level: At least two of the trends in spatial dip angle, three-dimensional vibration absolute mean, and dominant frequency have reached Level II, while the rest are at Level I. This indicates that the rock mass has exhibited isochronous deformation, loosening, or connection failure characteristics, and the probability of collapse has increased, but is still at a low level.

[0124] Yellow Alert Level: The changing trends of spatial dip angle, three-dimensional vibration absolute mean, and dominant frequency reach at least two of Level III, with the remainder at Level I or Level II; or all three reach Level II. This indicates that the rock mass has shown signs of accelerated deformation, loosening, or connection failure, and the probability of collapse is relatively high.

[0125] Orange Alert Level: One of the trends in spatial dip angle, three-dimensional vibration absolute mean, and dominant frequency reaches Level IV, while the remaining trends are at Level I, II, or III; or all three reach Level III. This indicates that one of the deformation, loosening, or connection failure characteristics of the rock mass has reached a pre-disaster evolution stage, increasing the risk of instability and the probability of collapse.

[0126] Red Alert Level: Two of the trends in spatial dip angle, three-dimensional vibration absolute mean, and dominant frequency reach Level IV, and the remaining trends are at Level I, II, or III; or all three reach Level IV. This indicates that at least two of the deformation, loosening, or connection failure characteristics of the rock mass have reached the pre-disaster evolution stage, and a rock mass collapse disaster has occurred.

[0127] Furthermore, the simplified criteria for determining the warning level are shown in Table 1 below:

[0128] Table 1

[0129]

[0130] The following describes a specific embodiment of the present invention:

[0131] This embodiment illustrates a comprehensive monitoring and early warning method for tunnel surrounding rock collapse based on MEMS sensing, using a real-world case study of tunnel surrounding rock monitoring. The specific steps are as follows:

[0132] (1) The surrounding rock of the tunnel has well-developed joints, dividing the rock mass into multiple local blocks. These internal structural surfaces, combined with the free face created by the tunnel excavation, form multiple isolated or semi-isolated dangerous rock blocks with geometric collapse potential. Within the statistical range, the number of volumetric joints in the rock mass exceeds the set threshold of 3 joints / m². 3 The rock mass has low integrity and the dangerous rock blocks are located at a wide depth range, covering the tunnel surface to a depth of more than 20m.

[0133] (2) For example Figure 12As shown, based on the local block characteristics of the tunnel surrounding rock, and to accommodate the monitoring needs of dangerous rock blocks at different depths, three boreholes were installed at key sections of the surrounding rock, located at the arch crown, left arch crown, and right arch crown, respectively. Five MEMS sensors were installed in each borehole at different depths: 2m, 5m, 8m, 10m, and 15m from the surface of the tunnel arch crown. A three-dimensional vibration data acquisition mode for the surrounding rock blocks was also set to achieve automated data acquisition and calculation. Given that only the five MEMS sensors installed in the vertical borehole at the arch crown location detected significant changes in the data in this case, this embodiment only analyzes and explains the data from these five measuring points, and the measuring points at depths of 2m, 5m, 8m, 10m, and 15m are named Measuring Point 1, Measuring Point 2, Measuring Point 3, Measuring Point 4, and Measuring Point 5, respectively.

[0134] (3) such as Figure 13 As shown, the spatial dip angle data of the surrounding rock block was calculated using three-dimensional vibration data collected by five MEMS sensors installed at the arch location. Outlier filtering, missing value supplementation, and data smoothing were performed using the quartile method, cubic spline interpolation method, and local weighted regression method to obtain the spatial dip angle data curve of the surrounding rock block. The spatial dip angle curves of measuring points 1, 2, 3, and 4 all conformed to the constant equation during the monitoring period from 16:02:30 on 2024 / 12 / 19 to 13:31:35 on 2025 / 1 / 16. , , , Furthermore, the fluctuation of the spatial dip angle data is less than ±0.1°, indicating that all four measuring points are in the Level I-stable stage and the surrounding rock block where the measuring points are located has not deformed.

[0135] Furthermore, the spatial tilt curve at measuring point 5 satisfies the constant equation during the monitoring period from 16:02:30 on December 19, 2024 to 14:02:07 on December 26, 2024. Furthermore, the spatial tilt data fluctuated by less than ±0.1°, placing it in the Level I - stable phase; and it satisfied the linear equation during the monitoring period from 14:02:07 on 2024 / 12 / 26 to 13:31:35 on 2025 / 1 / 16. It is currently in the Level II - constant velocity deformation stage, within which the maximum rate of change of the spatial tilt angle is 0.0022° / h. The data curve does not show multiple constant velocity deformation stages, and there is no issue of abrupt transitions in the deformation trend.

[0136] like Figure 14As shown, similarly, the three-dimensional vibration absolute mean data curves of the surrounding rock block were obtained. Among them, the three-dimensional vibration absolute mean curves of measuring points 1, 2, 3, and 4 all satisfied the constant equation during the monitoring period from 16:02:30 on 2024 / 12 / 19 to 13:31:35 on 2025 / 1 / 16, respectively. , , , Furthermore, the fluctuation of the absolute mean value of the three-dimensional vibration data is less than ±0.5mg, indicating that all four measuring points are in the Level I to constant micro-motion stage.

[0137] Furthermore, the three-dimensional vibration absolute mean data curve of measuring point 5 satisfies the constant equation during the period from 16:02:30 on 2024 / 12 / 19 to 13:31:04 on 2025 / 1 / 10. Furthermore, the absolute mean fluctuation of the three-dimensional vibration data is less than ±0.5mg, placing it in the Level I to constant micro-motion stage; and the data curve from 13:31:04 on 2025 / 1 / 10 to 13:31:35 on 2025 / 1 / 16 satisfies the linear equation. It is currently in the Level II – linear amplitude evolution stage. The maximum rate of change of the absolute mean of the three-dimensional vibration within this stage is 0.00005 mg / h. The data curve does not show multiple linear amplitude evolution stages, and there is no issue of trend transitions.

[0138] like Figure 15 As shown, similarly, the dominant frequency data curves of the surrounding rock block were obtained. Among them, the dominant frequency curves of measuring points 1, 2, 3, and 4 all satisfy the constant equation from 16:02:30 on 2024 / 12 / 19 to 13:31:35 on 2025 / 1 / 16, respectively. , , , Furthermore, the fluctuation of the dominant frequency data is less than ±1Hz, indicating that all four measuring points are in the Class I to intact rock mass stage.

[0139] Furthermore, the dominant frequency data curve at measurement point 5 satisfies the constant equation from 16:02:30 on December 19, 2024 to 6:30:58 on January 9, 2025. Furthermore, the dominant frequency data fluctuation is less than ±1Hz, indicating it is in the Grade I to intact rock mass stage; and the data curve from 6:30:58 on January 9, 2025 to 13:31:35 on January 16, 2025 satisfies the linear equation. It is currently in the Class II rock mass separation stage. The absolute value of the maximum rate of change of the dominant frequency during this stage is 0.00003 Hz / h. The data curve does not show multiple rock mass separation stages, and there is no issue of trend transitions.

[0140] (4) such as Figure 16 As shown, according to the comprehensive judgment method of tunnel surrounding rock block collapse disaster warning level according to the present invention, the evolution of the warning level of measuring point 5 from 16:02:30 on 2024 / 12 / 19 to 13:31:35 on 2025 / 1 / 16 is analyzed, and a line graph of the evolution of the warning level of measuring point 5 over time is drawn.

[0141] From 16:02:30 on 2024 / 12 / 19 to 14:02:07 on 2024 / 12 / 26, the changing trends of various indicators at measuring point 5 are as follows: spatial dip angle is Level I - stable stage, three-dimensional vibration absolute mean is Level I - constant micro-motion stage, dominant frequency is Level I - rock mass integrity stage, which is a green safety level, and no early warning information will be issued.

[0142] From 14:02:07 on December 26, 2024 to 6:30:58 on January 9, 2025, the changing trends of various indicators at measuring point 5 are as follows: spatial dip angle is Class II - isodynamic deformation stage; three-dimensional vibration absolute mean is Class I - constant micro-motion stage; dominant frequency is Class I - rock mass integrity stage; and a blue alert warning is issued.

[0143] From 6:30:58 on January 9, 2025 to 13:31:04 on January 10, 2025, the changing trends of various indicators at measuring point 5 are as follows: spatial dip angle is at level II - isotropic deformation stage; the absolute mean of three-dimensional vibration is at level I - constant micro-motion stage; the dominant frequency is at level II - rock mass separation stage; and a blue alert level warning is issued.

[0144] From 13:31:04 on 2025 / 1 / 10 to 13:31:35 on 2025 / 1 / 16, the changing trends of various indicators at measuring point 5 include: spatial dip angle is at level II - isodynamic deformation stage, three-dimensional vibration absolute mean is at level II - linear amplitude evolution stage, dominant frequency is at level II - rock mass separation stage, and a yellow warning level early warning information is issued.

[0145] Analysis of monitoring data revealed that among the five monitoring points at the arch borehole, only point 5 exhibited characteristics of tilting deformation, rock loosening, and decreased connectivity in the rock mass. The other four monitoring points remained normal, and the data from the monitoring points in the other two boreholes were also normal. Therefore, the anomaly at point 5 was determined to be a localized feature. Furthermore, considering that the arch borehole is grouted vertically upwards, and that point 5 is located at the deepest point (15m), it is prone to issues such as incomplete grouting and numerous pores. Currently, the tunnel is under construction, primarily using blasting excavation. The analysis suggests that the pore expansion and localized damage at point 5 were caused by multiple recent blasting operations. On-site verification confirmed the accuracy of the early warning results based on this method.

[0146] like Figure 17 As shown in the figure, this embodiment of the invention also provides a comprehensive monitoring and early warning system for tunnel surrounding rock block collapse based on MEMS sensing, the system comprising:

[0147] The deployment module 1710 is used to acquire the characteristics of a local block cut by the combination of the internal structure surface of the surrounding rock and the free surface formed by excavation, and to deploy MEMS sensors based on the characteristics of the local block.

[0148] Acquisition module 1720 is used to acquire three-dimensional vibration data of the local block through the MEMS sensor;

[0149] The calculation and compilation module 1730 is used to calculate and compile the spatial tilt angle, the three-dimensional vibration absolute mean and the dominant frequency based on the three-dimensional vibration data of the local block.

[0150] The recording module 1740 is used to obtain the four-level variation trends of the spatial tilt angle, the three-dimensional vibration absolute mean, and the dominant frequency based on the compiled spatial tilt angle, the three-dimensional vibration absolute mean, and the dominant frequency data, and to record the maximum value of their respective variation rates.

[0151] The determination module 1750 is used to determine whether the second-level or third-level trend needs to transition to the next level trend based on the maximum value of the change rate of the spatial tilt angle, the absolute mean of the three-dimensional vibration and the dominant frequency.

[0152] The comprehensive discrimination module 1760 is used to comprehensively discriminate the early warning level of each local block of the tunnel surrounding rock based on the changes in the spatial tilt angle, the three-dimensional vibration absolute mean and the dominant frequency.

[0153] The embodiment of this invention provides a comprehensive monitoring and early warning system for tunnel surrounding rock block collapse based on MEMS sensing. Its functional structure corresponds to the comprehensive monitoring and early warning method for tunnel surrounding rock block collapse based on MEMS sensing provided in this embodiment of the invention, and will not be described again here.

[0154] Figure 18 This is a schematic diagram of the structure of an electronic device 1800 provided in an embodiment of the present invention. The electronic device 1800 may vary considerably due to different configurations or performance. It may include one or more central processing units (CPUs) 1801 and one or more memories 1802. The memory 1802 stores at least one instruction, which is loaded and executed by the processor 1801 to implement the steps of the flotation foam color analysis method based on multi-spectral dual-branch deep fusion described above.

[0155] In an exemplary embodiment, a computer-readable storage medium is also provided, such as a memory including instructions that can be executed by a processor in a terminal to complete the aforementioned flotation foam color analysis method based on multi-spectral dual-branch deep fusion. For example, the computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, or optical data storage device.

[0156] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0157] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A comprehensive monitoring and early warning method for tunnel surrounding rock block collapse based on MEMS sensing, characterized in that, The method includes: S1. Obtain the characteristics of the local block cut by the combination of the structural surface inside the surrounding rock and the free surface formed by excavation, and deploy MEMS sensors based on the characteristics of the local block. S2. Acquire three-dimensional vibration data of the local block using the MEMS sensor; S3. Based on the three-dimensional vibration data of the local block, calculate and compile the spatial tilt angle, the three-dimensional vibration absolute mean and the dominant frequency; S4. Based on the reorganized spatial tilt angle, three-dimensional vibration absolute mean and dominant frequency data, obtain the four-level variation trends of spatial tilt angle, three-dimensional vibration absolute mean and dominant frequency respectively, and record the maximum value of their respective variation rates. S5. Based on the maximum value of the change rate of the spatial tilt angle, the absolute mean of the three-dimensional vibration, and the dominant frequency, determine whether the second-level or third-level change trend needs to jump to the next level of change trend. S6. Based on the final changing trends of the spatial tilt angle, the three-dimensional vibration absolute mean, and the dominant frequency, a comprehensive judgment of the early warning level is made for each local block of the tunnel surrounding rock. The three-dimensional vibration absolute mean in S3 It is calculated from the three-dimensional component data of the vibration acceleration of the dangerous rock mass according to equation (4), and the unit is mg: （4） in, The dangerous rock mass, as captured by the MEMS sensor, was caused by external factors. i One vibration acceleration triaxial component data; N represents the amount of monitored data; The dominant frequency in S3 It is calculated from the three-dimensional component data of the vibration acceleration of the dangerous rock mass according to equation (5), and the unit is Hz: （5） in, The fundamental frequencies of the dangerous rock mass in the X, Y, and Z directions are given. The four-level variation trend of the spatial tilt angle in S4 includes: Level I - steady stage, Level II - constant velocity deformation stage, Level III - accelerated deformation stage, and Level IV - pre-disaster deformation stage. The so-called Level I-Stable Phase refers to the space tilt data curve satisfying the constant equation. Furthermore, the spatial tilt data fluctuation does not exceed ±0.1° in the following stages. It is a constant obtained after curve fitting; The Level II - constant velocity deformation stage refers to the stage where the space tilt angle data curve satisfies the linear equation. ,and The stage in which The constants are obtained after curve fitting; the maximum values ​​of the spatial dip angle change rates during multiple isotropic deformation stages in the continuous monitoring of this hazardous rock mass are recorded as a set. ; The aforementioned Level III - accelerated deformation stage refers to the stage where the spatial dip angle relative rate ratio is between 2 and 8; the maximum value of the spatial dip angle change rate during multiple accelerated deformation stages in the continuous monitoring of this hazardous rock mass is recorded as a set. ; The Level IV - Disaster-Pressure Deformation Stage refers to a stage where the relative rate ratio of spatial tilt is greater than 8, or where the abrupt change in spatial tilt is greater than... The rate of change of spatial tilt angle is greater than And during the period when the space tilt data has not been recovered for a long time, among which These are experience values ​​defined based on preliminary case analysis; The ratio of spatial tilt angle relative rates is calculated using equation (7): （7） in, It is the ratio of the spatial tilt angle relative velocity at time t, and is dimensionless; The rate of change of the spatial tilt angle at time t; It is the arithmetic mean of the rate of change of spatial tilt angle at each time interval during the constant velocity deformation stage; The four-level variation trend of the absolute mean of three-dimensional vibration in S4 includes: Level I - constant micro-motion stage, Level II - linear evolution stage of amplitude, Level III - gradual increase stage of amplitude power law, and Level IV - steep increase stage of amplitude power law. The Level I - constant-time micro-motion stage refers to the stage where the three-dimensional vibration absolute mean data curve satisfies the constant equation. Furthermore, the fluctuation of the absolute mean of the three-dimensional vibration data does not exceed ±0.5 mg. It is a constant obtained after curve fitting; The Level II-amplitude linear evolution stage refers to the stage where the three-dimensional vibration absolute mean data curve satisfies the linear equation. ,and The stage in which The constants are those obtained after curve fitting; the maximum values ​​of the absolute mean change rate of three-dimensional vibration during multiple linear evolution stages of amplitude in the continuous monitoring of this hazardous rock mass are recorded as a set. ; The aforementioned Level III amplitude power-law gradual rise stage refers to the stage where the three-dimensional vibration absolute mean data curve satisfies the power-law equation. ,and The stage in which The constants are those obtained after curve fitting; the maximum values ​​of the absolute mean change rate of three-dimensional vibration during multiple power-law rising phases of the continuous monitoring of this hazardous rock mass are recorded as a set. ; The aforementioned Level IV amplitude power-law steep increase stage refers to the stage where the three-dimensional vibration absolute mean data curve satisfies the power-law equation. ,and The stage, or the abrupt change in the absolute mean of three-dimensional vibration is greater than The rate of change of the absolute mean of three-dimensional vibration is greater than Furthermore, during the period when the absolute mean data of three-dimensional vibration did not recover for a long time, among which These are experience values ​​defined based on preliminary case analysis; The four-level variation trend of the dominant frequency in S4 includes: Level I - intact rock mass stage, Level II - rock mass separation stage, Level III - accelerated rock mass separation stage, and Level IV - rock mass failure stage. The so-called Grade I - intact rock mass stage refers to the stage where the dominant frequency data curve satisfies the constant equation. And the dominant frequency data fluctuation does not exceed ±1Hz in the following period, It is a constant obtained after curve fitting; The aforementioned Level II rock mass separation stage refers to the stage where the dominant frequency data curve satisfies a linear equation. ,and The stage in which The constants are those obtained after curve fitting; the maximum values ​​of the dominant frequency change rates during multiple rock mass separation stages in the continuous monitoring of this hazardous rock mass are recorded as a set. ; The aforementioned Level III - rock mass separation acceleration stage refers to the stage where the dominant frequency data curve satisfies the power-law equation. ,and The stage in which The constants are those obtained after curve fitting; the maximum values ​​of the dominant frequency change rates during multiple rock mass separation acceleration stages in the continuous monitoring of this hazardous rock mass are recorded as a set. ; The aforementioned Level IV rock mass failure stage refers to the stage where the dominant frequency data curve satisfies the power-law equation. ,and The stage, or the dominant frequency mutation amount is greater than The rate of change of the dominant frequency is greater than And during the period when the dominant frequency data did not recover for a long time, among which These are experience values ​​defined based on preliminary case analysis; In step S5, based on the maximum value of the spatial tilt rate of change, it is determined whether the second-level or third-level trend needs to transition to the next-level trend, including: The spatial tilt angle is in the Level II - constant velocity deformation stage, and the rate of change of the spatial tilt angle is greater than... In actual early warning, the spatial tilt angle is transitioned from Level II - constant velocity deformation stage to Level III - accelerated deformation stage; The spatial tilt angle is in the Level III - accelerated deformation stage, and the rate of change of the spatial tilt angle is greater than... In actual early warning, the spatial tilt angle is jumped from Level III - accelerated deformation stage to Level IV - pre-disaster deformation stage; The comprehensive judgment of the warning level in S6 includes: green safety level, blue attention level, yellow warning level, orange alert level, and red alert level; The green safety level is defined as follows: the variation trends of spatial tilt angle, three-dimensional vibration absolute mean, and dominant frequency are all in stage I. The blue attention level is defined as follows: at least one and at most two of the trends in spatial tilt angle, three-dimensional vibration absolute mean and dominant frequency reach the level II stage, and the rest are in the level I stage. The yellow warning level is defined as follows: at least one and at most two of the trends in spatial tilt angle, three-dimensional vibration absolute mean and dominant frequency reach level III, and the remaining are at level I or level II; or all three reach level II. The orange alert level is defined as follows: one of the trends in spatial tilt angle, three-dimensional vibration absolute mean, and dominant frequency reaches level IV, and the remaining trends are at level I, level II, or level III; or all three reach level III. The red alert level is defined as follows: two of the trends in spatial tilt angle, three-dimensional vibration absolute mean, and dominant frequency reach level IV, and the remaining trends are at level I, level II, or level III; or all three reach level IV.

2. The method according to claim 1, characterized in that, The features of the local block in S1 include: the orientation of the internal structural surface of the block, the angle between the internal structural surface and the free surface, the angle between the structural surface and the tunnel axis, and the roughness of the structural surface. The deployment of MEMS sensors based on the features of the local block in S1 includes: By comprehensively analyzing the attitude of internal structural planes, the angle between internal structural planes and the free face, and the angle between structural planes and the tunnel axis, dangerous rock blocks with collapse potential formed by the combination of various structural planes are identified. The rock mass integrity of these dangerous rock blocks is then analyzed and evaluated. For rock blocks with high integrity, one MEMS sensor is used for monitoring. For rock blocks with low integrity, based on the roughness of each structural plane, key potential hazard areas are identified, and multiple MEMS sensors are installed. The rock mass integrity is characterized by the number of volumetric joints, which is the number of structural planes per cubic meter of rock mass, calculated using the following formula: （1） in, This represents the volumetric joint number of the rock mass, expressed in units of joints / m. 3 ; This represents the number of structural surface groups within the statistical region. For the first i The number of structural surfaces per meter along the normal direction in a group; This represents the number of ungrouped joints per cubic meter of rock mass.

3. The method according to claim 1, characterized in that, The three-dimensional vibration data of the local block acquired in S2 refers to the triaxial acceleration data acquired by the MEMS sensor: （2） in, A vector of three-axis acceleration data acquired by a MEMS sensor; Acceleration data collected in the X, Y, and Z directions; This is the three-dimensional component data of static gravitational acceleration collected in the XYZ directions; To collect three-dimensional component data of vibration acceleration caused by external factors in the XYZ directions.

4. The method according to claim 3, characterized in that, The spatial tilt angle in S3 , is the angle between the initial three-dimensional vector and the current three-dimensional vector of the dangerous rock mass, in degrees, calculated by equation (3): （3） in, The static gravitational acceleration triaxial component data corresponding to the initial state three-dimensional vector of the dangerous rock mass acquired by the MEMS sensor; The static gravitational acceleration triaxial component data corresponding to the three-dimensional vector of the current state of the dangerous rock mass acquired by the MEMS sensor; The fundamental frequency is calculated from the three-dimensional component data of the vibration acceleration of the dangerous rock mass caused by external factors, collected by MEMS sensors, including: The Welch method is used to process the three-dimensional component data of vibration acceleration acquired by MEMS sensors, specifically including: The power spectrum of the rock mass vibration signal is calculated by segmenting the signal, overlapping the segmented data, windowing, calculating the periodogram, and averaging, as shown in equation (6): （6） in, Indicates frequency The corresponding power spectral amplitude at that location; This indicates that the entire data segment has been divided into K segments; This represents the first division of the entire data segment. i The segment data is obtained after calculation at the frequency The amplitude at that point, 1≤ i ≤K; Vibration data of the rock block in the X, Y and Z directions are processed to obtain their respective power spectra. After removing high-frequency noise components, dominant site periods and spurious modal components, the frequency value corresponding to the position of the maximum peak in the preset frequency range of the power spectrum is taken as the fundamental frequency.

5. The method according to claim 1, characterized in that, The rate of change of the spatial tilt angle is calculated by equation (8): （8） in, Indicates the rate of change of the spatial tilt angle; These represent the times of the 0th and (0-1)th data uploads, respectively. They represent in Spatial tilt data at any given time.

6. A comprehensive monitoring and early warning system for tunnel surrounding rock block collapse based on MEMS sensing, characterized in that, The system is used to implement the method according to any one of claims 1-5, the system comprising: The acquisition and deployment module is used to acquire the characteristics of the local block cut by the combination of the internal structure surface of the surrounding rock and the free surface formed by excavation, and to deploy MEMS sensors based on the characteristics of the local block. The acquisition module is used to acquire three-dimensional vibration data of the local block through the MEMS sensor; The calculation and compilation module is used to calculate and compile the spatial tilt angle, the three-dimensional vibration absolute mean and the dominant frequency based on the three-dimensional vibration data of the local block; The recording module is used to obtain the four-level variation trends of the spatial tilt angle, the three-dimensional vibration absolute mean, and the dominant frequency based on the compiled spatial tilt angle, the three-dimensional vibration absolute mean, and the dominant frequency data, and to record the maximum value of each variation rate. The determination module is used to determine whether the second-level or third-level trend needs to transition to the next level trend based on the maximum value of the change rate of the spatial tilt angle, the absolute mean of the three-dimensional vibration, and the dominant frequency. The comprehensive discrimination module is used to comprehensively discriminate the early warning level of each local block of the tunnel surrounding rock based on the changes in the spatial tilt angle, the three-dimensional vibration absolute mean and the dominant frequency.

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