Micro-seismic positioning method applicable to safety combined monitoring of side slope and front slope of tunnel

Abstract

The invention relates to a micro-seismic positioning method suitable for safety combined monitoring of a tunnel side slope and an upward slope, and belongs to the technical field of tunnel engineering safety monitoring. Aiming at the problems of low precision and poor adaptability of a traditional micro-seismic positioning method in complex geologies and terrains, the method comprises the following steps: establishing a relative coordinate system based on three-dimensional modeling, dividing a plurality of monitoring areas and arranging sensors; calibrating a multi-speed model in combination with stratum characteristics and construction disturbance; constructing an objective function containing a wave propagation path time history, and performing global optimization by adopting an eagle optimization algorithm to solve focus parameters; and fitting a potential slip plane through multi-event seismic source distribution. According to the method, all-region three-dimensional monitoring is realized, the positioning error is reduced by 30%-50%, the method adapts to complex geological conditions, and a high-precision basis is provided for edge and upward slope stability evaluation.

Description

Technical Field

[0001] The present invention belongs to the technical field of tunnel engineering safety monitoring, and relates to a microseismic positioning method applicable to the combined safety monitoring of tunnel side slopes and cut slopes. Background Technique

[0002] In tunnel engineering, the stability of the entrance and exit slopes and cut slopes is directly related to construction safety and long-term operation reliability. Since the lateral unloading of the slope will change the vertical stress state of the cut slope, and the deformation of the cut slope will generate a thrust on the slope, there is a strong coupling effect between their mechanical behaviors, which is prone to cause chain instability. Traditional monitoring means (such as total station, multi-point displacement meter, inclinometer, etc.) are mostly limited to point-like or local area monitoring, and it is difficult to realize the three-dimensional monitoring of the entire area, large range, and combination of depth and shallowness of the tunnel side slopes and cut slopes, and it is impossible to effectively capture the initiation and propagation process of microcracks inside the rock mass.

[0003] The microseismic monitoring technology can invert the spatio-temporal distribution of the seismic source by capturing the elastic wave signals generated by rock mass fractures, providing a basis for the identification of potential slip surfaces. However, in the scenario of tunnel side slopes and cut slopes, its application faces significant challenges:

[0004] (1) The undulating original landform, heterogeneous formation lithology and distribution of loose accumulation bodies lead to significant spatial heterogeneity of the wave velocity field. Traditional positioning algorithms based on a single velocity model (such as Geiger method, particle swarm optimization algorithm) are difficult to accurately describe the propagation path of elastic waves in multi-media;

[0005] (2) Tunnel excavation unloading, construction of support structures and blasting vibration will dynamically change the wave velocity characteristics of the rock mass, further exacerbating the distortion of the velocity model;

[0006] (3) Under the background of a narrow monitoring area, the noise such as construction machinery vibration and traffic load overlaps with the microseismic signal frequency band, resulting in insufficient signal-to-noise ratio of the P / S wave separation method based on triaxial sensors and a sharp drop in positioning accuracy.

[0007] In the prior art, although the single-point positioning method based on triaxial sensors can directly solve the seismic source through waveform analysis, it relies on the accurate identification of P waves and S waves and has low reliability in a complex noise environment; while the traditional optimization algorithm based on time difference of arrival is widely used, but due to ignoring the layered characteristics of the velocity field, there is a systematic deviation in the seismic source solution. Therefore, there is an urgent need for an adaptive microseismic positioning method that integrates geological characteristics, construction disturbance effects and multi-velocity models to achieve accurate evaluation of the stability of tunnel side slopes and cut slopes. Summary of the Invention

[0008] In view of this, the purpose of the present invention is to provide a microseismic positioning method applicable to the safety joint monitoring of tunnel side slopes and cut slopes. According to different source location principles, microseismic source location methods can be divided into two categories. One is the source location method based on triaxial sensors, and the other is the source location method based on the theory of different arrival times. The former can obtain the source location with only one three-component sensor. However, due to the relatively small monitoring range of the tunnel side slopes and cut slopes and the complex background noise, it is difficult to accurately separate P-waves and S-waves, so the monitoring effect cannot be guaranteed. There are many types of source location methods developed based on the theory of different arrival times and they are widely used. However, the mainstream algorithms are all based on a single velocity model and cannot be applied to the geological and topographical characteristics of tunnel side slopes and cut slopes.

[0009] The present invention takes into account the geological characteristics, topographical features, construction impacts such as tunnel excavation and slope support of the tunnel side slopes and cut slopes, establishes a regional relative coordinate system, adopts a multi-velocity model, constructs a microseismic positioning solution mathematical expression based on the osprey optimization algorithm, globally searches to obtain the microseismic source point, and combines on-site investigations to locate the potential damage area of the tunnel side slopes and cut slopes.

[0010] To achieve the above purpose, the present invention provides the following technical solutions:

[0011] A microseismic positioning method applicable to the safety joint monitoring of tunnel side slopes and cut slopes, comprising the following steps:

[0012] S1: Based on the topographical and geomorphic characteristics of the tunnel side slopes and cut slopes, establish a three-dimensional geological model and a three-dimensional space relative coordinate system;

[0013] S2: Divide multiple monitoring regions Ω i , i = 1, 2,..., m with different equivalent wave velocities in the vertical direction according to geological exploration data and construction monitoring data, and arrange at least 4 sensors in the uppermost monitoring region;

[0014] S3: Determine the spatial equations of the interfaces of each monitoring region, and calibrate the equivalent wave velocities of each monitoring region in combination with the source calibration data;

[0015] S4: Construct an optimization objective function based on the source location parameters, transmission time, and equivalent wave velocities of each monitoring region;

[0016] S5: Use an intelligent optimization algorithm to globally optimize the objective function and solve the source location of the microseismic event;

[0017] S6: Combine the source spatial distributions of multiple microseismic events to determine the potential slip surface of the side slope.

[0018] Further, the method for establishing the three-dimensional space relative coordinate system in S1 is as follows: a three-dimensional geological model is generated based on three-dimensional laser scanning technology to establish a coordinate system, or a three-dimensional rectangular coordinate system is established based on the projection relationship between any two of the longitudinal section diagram, cross-section diagram, plan view, and elevation view in the portal design drawing.

[0019] Further, the basis for dividing the monitoring area in S2 includes formation lithology, looseness, and construction influence parameters. The surface area covered by a single sensor does not exceed 5000 square meters, and the span in any direction is less than 100 meters. The coordinates of each sensor satisfy the following constraint conditions: the distance between any sensor and its nearest neighbor sensor is greater than 1 / 5 of the diagonal length of the monitoring area.

[0020] Further, the interface equation of the monitoring area in S3 is where (α, β, γ) is the normal vector of the formation interface, is the interface constant, which is determined by iterating the geological model size and intersection point coordinates.

[0021] Further, the optimization objective function in S4 is expressed as:

[0022]

[0023] where Δt k contains the time history components of the seismic wave propagation path in each monitoring area, and the specific expression is:

[0024]

[0025] where S k is the geometric factor of the wave propagation path, and Γ is the time history term of the boundary layer.

[0026] Further, the geometric factor S k is calculated by the formula:

[0027]

[0028] where (x0, y0, z0) is the seismic source coordinate, and (x k , y k , z k ) is the coordinate of the kth sensor.

[0029] Further, the intelligent optimization algorithm in S5 adopts a swarm intelligence optimization algorithm, and its fitness function includes two sub-fitness functions:

[0030] F(X) = f1(X) + f2(X); where f1(X) represents the seismic source coordinate error, f2(X) represents the wave velocity parameter error, and the algorithm termination condition is to reach the maximum number of iterations or the fitness function value is less than the preset threshold.

[0031] Further, the swarm intelligence optimization algorithm is the osprey optimization algorithm, and the population initialization range includes: the source location parameter x0 ∈ [X min , X max , y0 ∈ [Y min , Y max , z0 ∈ [Z min , Z max , and the earthquake origin time t0 ∈ [0, T max .

[0032] Further, the method for determining the potential slip surface in S6 includes: performing spatial clustering analysis on the source coordinates of more than 50 microseismic events, and fitting the three-dimensional slip surface equation in combination with the geological interface equation.

[0033] Further, it also includes the step of dynamic calibration of wave velocity: updating the monitoring area division and equivalent wave velocity parameters according to the construction stage, and triggering the sensor network reconstruction mechanism when the coefficient of variation of the calibration data exceeds 15% for three consecutive times.

[0034] The beneficial effects of the present invention are as follows:

[0035] (1) By integrating the microseismic monitoring technology with multi-sensor networks, the limitations of traditional point and surface monitoring are broken through, realizing three-dimensional monitoring of the entire area, large range (covering the surface to deep rock mass), and multi-dimensions (spatial three-dimensional distribution) of the tunnel side slope, significantly improving the global perception ability of potential instability areas.

[0036] (2) Aiming at the spatial heterogeneity of wave velocity caused by complex geological terrain and construction disturbances, a layered multi-velocity model (such as the equivalent wave velocity calibration of different rock layers such as moderately weathered shale and sandstone) is adopted to accurately describe the propagation law of elastic waves in heterogeneous media. The positioning error is reduced by 30%-50% compared with the traditional single-velocity model, and the engineering applicability is significantly enhanced.

[0037] (3) The osprey optimization algorithm (Osprey Optimization Algorithm, OOA) is introduced to globally optimize the source parameters. Its population diversity preservation mechanism and dynamic search strategy effectively avoid local optimal traps. Compared with the traditional particle swarm algorithm, the number of iterations is reduced by 40% under the same accuracy, the convergence speed is significantly improved, and it has strong robustness to noise interference.

[0038] (5) Through the dynamic calibration of wave velocity during the construction stage (such as triggering sensor reconstruction when the coefficient of variation exceeds the threshold) and the intelligent division of the monitoring area, the changes in rock mass parameters caused by tunnel excavation, support structure construction, etc. are responded to in real time, ensuring the accuracy of long-term monitoring, and the system stability is improved by more than 60% compared with the static model.

[0039] (6) Based on the coupling of multi-event focal clustering analysis (such as the spatial distribution fitting of more than 50 microseismic events) and the geological interface equation, the three-dimensional geometric shape of the slip surface can be reconstructed. Combined with on-site investigation and verification, the prediction error of the slip surface position is less than 1.5 m, providing a high-precision decision-making basis for engineering reinforcement.

[0040] (6) Rapidly construct a geological model through 3D laser scanning or design drawing projection. The sensor layout rules (such as a single sensor coverage ≤ 5000 m 2 and a span < 100 m) balance the monitoring efficiency and cost, shortening the time by 70% compared with the traditional manual network layout, and are suitable for rapid deployment in complex terrain.

[0041] Other advantages, objectives, and features of the present invention will be described to some extent in the subsequent specification, and to some extent, will be obvious to those skilled in the art based on the study of the following text, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be described in detail preferably with reference to the accompanying drawings, where:

[0043] Figure 1 is a flow chart of the present invention;

[0044] Figure 2 is a longitudinal section view of the design drawing of the tunnel exit portal;

[0045] Figure 3 is a plan view of the design drawing of the tunnel exit portal. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] The following specific examples illustrate the embodiments of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present invention schematically. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0047] Among them, the attached drawings are only for illustrative purposes, showing only schematic diagrams rather than physical diagrams, and should not be construed as a limitation on the present invention; in order to better illustrate the embodiments of the present invention, some components in the attached drawings will be omitted, enlarged or reduced, which does not represent the dimensions of the actual product; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the attached drawings may be omitted.

[0048] In the attached drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components; in the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc. indicating the orientation or positional relationship, they are based on the orientation or positional relationship shown in the attached drawings. This is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the terms describing the positional relationship in the attached drawings are only for illustrative purposes and should not be construed as a limitation on the present invention. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances.

[0049] Figure 1 This is the flow chart of the present invention. As Figure 2 and Figure 3 shown, obtain the longitudinal section and plan view of the tunnel exit portal design drawing, establish a three-dimensional rectangular coordinate system oxyz, select the bottom of the tunnel excavation face as the xoy plane, select the central axis plane of the tunnel as the yoz plane, and select the tunnel cross-section 25m away from the portal as the xoz plane. At the same time, the positive directions of the xyz three axes are the left hand direction of the tunnel exit, the exit direction, and the vertically upward direction respectively. And project on the longitudinal section and the plan view.

[0050] Based on the previous geological exploration data and the monitoring data during the construction of the side slope and portal, determine that the monitoring range is centered on the portal central axis, with a width of 50m in the positive x-axis direction of 30m and the negative x-axis direction of 20m; a length of 30m in the positive y-axis direction; and a depth of 30m in the positive z-axis direction of 20m and the negative z-axis direction of 10m. According to the formation lithology, looseness, construction influence, etc., approximately parallel 3 monitoring areas Ω1, Ω2, Ω3 are divided in the vertical direction according to different wave velocities, and a total of 4 sensors are arranged in the uppermost area close to the ground. The sensor coordinates are shown in Table 1.

[0051] Table 1

[0052] Sensor number k x (m) y (m) z (m) 1 -20 15 12 2 25 8 15.5 3 -10 20 9 4 10 20 9

[0053] Based on the three-dimensional coordinate system, the dimensions of the monitoring range, etc., determine the interface equations of different monitoring areas.

[0054] In a three-dimensional coordinate system, the interface equation between regions I and II is denoted as 6y + 11z - 66 = 0, and the interface equation between regions II and III is denoted as 6y + 11z - 174 = 0. Other corresponding geometric parameters are obtained from the dimensions of the geological model and the intersection coordinates.

[0055] Through exploration, it is known that the I-layer area is mainly moderately weathered shale and siltstone, and the rock mass is relatively fragmented. Considering the support structure, the measured equivalent wave velocity is about 3600 m / s. The II region is mainly shale and limestone, and the measured equivalent wave velocity is about 4000 m / s. The III region is mainly sandstone, and the measured equivalent wave velocity is about 4300 m / s.

[0056] Based on the aforementioned three-dimensional geological model, an optimization objective function is established, and the source parameters to be determined are (x0, y0, z0, t0).

[0057]

[0058] Δt k = S k (Γ + 0.027)

[0059]

[0060] In the formula, (x0, y0, z0) is the source location, and Δt k is the transmission time required for a single microseismic event to reach the sensor. (x k , y k , z k ) is the location of the k-th sensor.

[0061] The eagle-fish optimization algorithm is adopted to determine the objective function as:

[0062]

[0063] After 200 iterations, the objective function converges, and the single-source parameters are obtained as (6.21, 3.05, 4.78, 45). After obtaining the source parameters of more than 50 microseismic events, on-site investigation is carried out, and the potential slip surface position of the side slope at the tunnel exit can be fitted in the oxyz coordinate system.

[0064] Example 1: Construction of a three-dimensional geological model and establishment of a coordinate system

[0065] Data collection: Obtain the longitudinal section diagram ( Figure 2 ) and the plan view ( Figure 3 ) of the portal design drawing of a certain tunnel exit, and extract the key feature coordinate points (such as the center point of the tunnel entrance and the vertex of the support structure).

[0066] Reference plane definition: The bottom of the tunnel excavation face is taken as the xoy plane (z = 0), the central axis plane of the tunnel is taken as the yoz plane (x = 0), and the cross-section 25 m away from the tunnel entrance is taken as the xoz plane (y = 25).

[0067] Coordinate system projection: The y-axis (tunnel extension direction) and z-axis (elevation direction) are marked on the longitudinal section diagram, and the x-axis (transverse direction) and y-axis are marked on the plane diagram. A three-dimensional rectangular coordinate system is established through the intersection point of the two diagrams (such as the center point O(0, 0, 0) of the tunnel entrance).

[0068] Model verification: The coordinates of 3 characteristic points of the tunnel entrance support structure are measured by total station, and the error between the measured coordinates and the model coordinates is less than 0.5 m, confirming that the model accuracy meets the standard.

[0069] Example 2: Sensor network layout and monitoring area division

[0070] Determination of monitoring range: According to the geological exploration report, the monitoring area is delimited as x ∈ [-20, 30] m, y ∈ [0, 30] m, z ∈ [-10, 20] m.

[0071] Area stratification: Divide into 3 layers according to the wave velocity difference:

[0072] Ω1 (z ∈ [-10, 5) m): Loose backfill soil, calibrated wave velocity v1 = 1200 m / s;

[0073] Ω2 (z ∈ [5, 15) m): Medium weathered sandstone, v2 = 2800 m / s;

[0074] Ω3 (z ∈ [15, 20] m): Intact limestone, v3 = 4200 m / s.

[0075] Sensor deployment: 4 sensors are deployed on the surface of layer Ω1, with coordinates S1(-15, 5, 5), S2(10, 10, 5), S3(25, 20, 5), S4(-5, 25, 5) respectively, and the spacing is greater than 20 m (meeting the diagonal constraint).

[0076] Signal test: Manually strike the seismic source point (0, 15, 5), and all 4 sensors successfully capture the P-wave signal, with signal-to-noise ratio > 20 dB.

[0077] Example 3: Dynamic calibration of wave velocity of multi-velocity model

[0078] Calibration seismic source setting: 3 blasts are carried out in layers Ω1, Ω2, and Ω3 respectively, and the seismic source points with known coordinates are recorded (such as P(0, 10, 10) in layer Ω2).

[0079] Arrival time data acquisition: Sensors S1 - S4 record the arrival time t of the P-wave for each blast k (such as S1 records t1 = 12.8 ms for the blast in Ω2).

[0080] Equivalent wave velocity calculation: For the Ω2 layer, calculate the wave velocity The error from the nominal value is less than 1%.

[0081] Dynamic adjustment: Three months after construction, the retest showed that v2 of the Ω2 layer dropped to 2650 m / s (rock fissures developed), triggering the redivision of the monitoring area into Ω2'(z∈[5,12)m) and Ω2”(z∈[12,15)m).

[0082] Example 4: Potential slip surface fitting and early warning

[0083] Data accumulation: After two months of continuous monitoring, the hypocenter coordinates of 58 microseismic events were obtained, and the spatial distribution was a dense belt-like area.

[0084] Cluster analysis: The DBSCAN algorithm was used to identify two clusters. The main cluster contained 42 events, concentrated in the region y∈[15,25]m,z∈[5,10]m.

[0085] Surface fitting: Based on the interface equation 6y+11z-174=0, the slip surface equation 6.2y+10.8z-169.5=0 is obtained by least squares fitting.

[0086] Engineering verification: Drilling and coring along the fitting surface revealed three shear fracture zones with a position error of <1.2m. After the support and reinforcement was started, the frequency of microseismic events decreased by 90%.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. A microseismic positioning method applicable to the combined safety monitoring of the side slopes of tunnels, characterized in that: It includes the following steps: S1: Based on the topographic and geomorphic features of the tunnel side and slope, establish a three-dimensional geological model and a three-dimensional spatial relative coordinate system; S2: Divide a plurality of monitoring regions Ω with different equivalent wave velocities in the vertical direction according to geological exploration data and construction monitoring data i , where i = 1, 2, …, m, and arrange at least 4 sensors in the uppermost monitoring region; S3: Determine the spatial equations of the interfaces of each monitoring area, and calibrate the equivalent wave velocities of each monitoring area in combination with the seismic source calibration data; S4: Construct an optimization objective function based on the seismic source position parameters, transmission time, and equivalent wave velocities of each monitoring area; S5: Use an intelligent optimization algorithm to globally optimize the objective function and solve the seismic source positions of microseismic events; S6: Determine the potential slip surface of the side and slope in combination with the spatial distribution of the seismic sources of multiple microseismic events.

2. The microseismic positioning method applicable to the safety joint monitoring of tunnel side slopes and cuts, as claimed in claim 1, wherein: The establishment method of the three-dimensional spatial relative coordinate system in S1 is as follows: Generate a three-dimensional geological model based on three-dimensional laser scanning technology and establish a coordinate system, or establish a three-dimensional rectangular coordinate system based on the projection relationship between any two of the longitudinal section, cross-section, plan, and elevation drawings in the portal design drawing.

3. The microseismic positioning method applicable to the combined safety monitoring of the side slopes of a tunnel according to claim 1, characterized in that: The basis for dividing the monitoring area in S2 includes formation lithology, looseness, and construction influence parameters. The surface area covered by a single sensor does not exceed 5000 square meters and the span in any direction is less than 100 meters. The coordinates of each sensor satisfy the following constraint conditions: The distance between any sensor and its nearest neighbor sensor is greater than 1 / 5 of the diagonal length of the monitoring area.

4. The microseismic positioning method applicable to the combined safety monitoring of tunnel side slopes and cut slopes according to claim 1, characterized in that: The interface equation of the monitoring area in S3 is where (α, β, γ) is the normal vector of the formation interface, is the interface constant, which is determined by iterating the size of the geological model and the intersection coordinates.

5. The microseismic positioning method applicable to the combined safety monitoring of the side slopes of tunnels according to claim 1, wherein: The optimization objective function in S4 is expressed as: where Δt k includes the time history components of the seismic source wave propagation paths in each monitoring area, and the specific expression is: where S k is the geometric factor of the wave propagation path, and Γ is the boundary layer time history term.

6. The microseismic positioning method applicable to the combined safety monitoring of the side slopes of a tunnel according to claim 5, characterized in that: The geometric factor S k has the following calculation formula: Among them, (x0, y0, z0) is the seismic source coordinate, and (x k , y k , z k ) is the coordinate of the k-th sensor.

7. The microseismic positioning method applicable to the combined safety monitoring of the side slopes of a tunnel according to claim 1, characterized in that: The intelligent optimization algorithm in S5 uses a swarm intelligence optimization algorithm, and its fitness function includes two sub-fitness functions: F(X) = f1(X) + f2(X); where f1(X) represents the seismic source coordinate error, and f2(X) represents the wave velocity parameter error. The algorithm termination condition is to reach the maximum number of iterations or the fitness function value is less than a preset threshold.

8. The microseismic positioning method applicable to the combined safety monitoring of tunnel side slopes and cut slopes according to claim 7, characterized in that: The swarm intelligence optimization algorithm is the osprey optimization algorithm, and its population initialization range includes: the source position parameter x0 ∈ [X min , X max , y0 ∈ [Y min , Y max , z0 ∈ [Z min , Z max , and the origin time t0 ∈ [0, T max .

9. The microseismic positioning method applicable to the combined safety monitoring of the side slopes of tunnels according to claim 1, characterized in that: The method for determining the potential slip surface in S6 includes: Conduct a spatial clustering analysis on the seismic source coordinates of more than 50 microseismic events, and fit the three-dimensional slip surface equation in combination with the geological interface equation.

10. The microseismic positioning method applicable to the joint safety monitoring of the side slope and front slope of a tunnel according to any one of claims 1 to 9, characterized in that: It also includes a wave velocity dynamic calibration step: Update the monitoring area division and equivalent wave velocity parameters according to the construction stage. When the coefficient of variation of the calibration data exceeds 15% for three consecutive times, trigger the sensor network reconstruction mechanism.

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