Method and system for dynamically predicting outburst risk of high-pressure air bag near tunnel

Abstract

The invention provides a method and a system for dynamically predicting the outburst risk of a high-pressure air bag near a tunnel. The method comprises the following steps: (1) acquiring air bag parameters (pressure and equivalent radius), rock mass parameters (strength parameter and attenuation coefficient) and engineering parameters (rock wall thickness and support strength) through geological radar, borehole pressure measurement, indoor triaxial test and the like; (2) calculating equivalent plastic strain based on tunnel convergence displacement, updating surrounding rock strength in combination with an attenuation model, and calculating rock wall damage resistance and air bag destructive power to obtain an outburst risk index R; and (3) dividing low (R > = 1.5), medium (1.0 < = Rlt, 1.5), high (0.5 < = Rlt, 1.0) and extremely high (Rlt, 0.5) risk levels according to R, and outputting early warning and treatment measures. The non-coal measure stratum air bag prediction blank is solved, dynamic quantitative prediction is achieved, construction safety is improved, the construction period is shortened, and the method is suitable for deep and long tunnel and large-burial-depth underground engineering.

Description

Technical Field

[0001] This invention relates to the field of underground engineering safety technology, specifically to a method and system for dynamic prediction of the risk of high-pressure airbag bursting in adjacent tunnels. Background Technology

[0002] With the expansion of deep and long tunnel and deep underground engineering construction, high-pressure gas bursts in non-coal-bearing strata (such as granite, sandstone, and mudstone strata) have become a key hidden danger threatening engineering safety. Unlike gas disasters in coal-bearing strata, high-pressure gas bursts in non-coal-bearing strata are formed by geological tectonic movements (such as earthquakes and multi-stage compression), and are characterized by "small volume, high pressure, and concentrated energy." Gases (such as methane, carbon dioxide, and hydrogen sulfide) accumulate in the trapped structures for a long time, and are prone to sudden bursts after excavation disturbance, causing significant losses such as damage to construction equipment, casualties, and project delays.

[0003] Existing technologies have significant shortcomings: 1. Limited applicability: Existing outburst risk prediction models, such as coal and gas outburst prediction technology, are based on coal adsorption models. They are applicable to coal-bearing strata and rely on parameters such as coal porosity and gas adsorption capacity. They cannot be adapted to the characteristics of non-coal-bearing strata gasbags, which are "non-adsorbent and release under high pressure". 2. Ignoring the dynamic decay of surrounding rock strength: After excavation of non-coal-bearing strata, plastic deformation occurs due to stress redistribution, and the cohesion and internal friction angle of the surrounding rock decay over time (e.g., the strength decay rate of granite reaches 5%-8% after 7 days of excavation). Existing models all use static strength parameters, which leads to misjudgment of risks in the later stage (e.g., misjudging high risk as medium risk). 3. Inaccurate risk quantification: Existing methods mostly use "qualitative descriptions" (such as "possible burst" or "low probability burst"), without establishing a quantitative relationship between "resistance to damage" and "damage force", and cannot provide specific thresholds for construction and disposal (such as "when to release pressure" or "what pressure release rate").

[0004] Therefore, there is an urgent need for a high-pressure gasbag outburst prediction technology that is adaptable to non-coal-bearing strata, considers the dynamic attenuation of surrounding rock strength, and has quantifiable risks, to fill the gap in existing technologies. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a dynamic prediction method and system for the risk of gas bursting in adjacent tunnels by comprehensively considering the pressure, volume, rock wall condition, and dynamic decay of the surrounding rock strength of the high-pressure airbag. It is especially suitable for deep and long tunnels in non-coal-bearing strata and underground projects with great depth (such as traffic tunnels, water conservancy tunnels, underground pipe corridors, etc.). It can dynamically predict the risk of gas bursting when encountering a closed high-pressure airbag during tunnel construction, and provide accurate decision-making basis for disaster prevention and mitigation in engineering.

[0006] The technical solution of the present invention is as follows: The first aspect of this invention provides a method for dynamically predicting the risk of high-pressure airbag bursting in adjacent tunnels, comprising the following steps: Step 1. Parameter Acquisition Stage: Acquire airbag parameters, rock mass parameters, and engineering parameters; The airbag parameters include the pressure P of the gas inside the airbag. g and equivalent radius R g ; The rock mass parameters include the initial strength parameters (cohesion c0, internal friction angle φ0) and residual strength parameters (cohesion c0, internal friction angle φ0). r internal friction angle φ r ), elastic modulus E, Poisson's ratio ν, and attenuation coefficients (α, β); The engineering parameters include the initial thickness D0 of the rock wall between the tunnel and the airbag, and the equivalent radius R of the tunnel excavation section. tun Time after excavation (t), support strength (σ) sup and ground stress (vertical ground stress σ) v Horizontal ground stress σ h ); Step 2. Real-time Analysis Phase: Step 201. Rock Wall Stability Calculation: Based on the tunnel convergence displacement u monitored on-site, and through empirical relationships... =k×u / R tun Calculate the equivalent plastic strain of the rock wall between the tunnel and the airbag. The k is an empirical coefficient; Step 202. Dynamic Update of Surrounding Rock Strength: Based on the equivalent plastic strain calculated in Step 201 The current cohesion c(t) and internal friction angle φ(t) of the rock wall are updated in real time using a rock mass strength attenuation model; the attenuation model is as follows: , ; Step 203. Calculation of Rock Wall Resistance to Failure: Based on the Mohr-Coulomb criterion, using the formula R... s =K1×c(t)×D t ×K2+K2×σ n ×D t The ability of the rock wall to resist failure is calculated using ×tanφ(t). s The D t Given the current rock wall thickness, K1 and K2 are geometric coefficients related to the shape of the potential slip surface; when the slip surface is planar, K1=1.0 and K2=0.8; when the slip surface is a circular arc, K1=1.2 and K2=1.0; σ n σ is the average normal stress on the slip surface.n =σ h ×cos²θ+σ v ×sin²θ+σ sup θ is the horizontal angle between the tunnel excavation outline and the nearest point of the edge of the high-pressure airbag; Step 204. Calculation of the destructive force of the high-pressure airbag: using formula F gas =P g ×H g ×b Calculate the destructive force F of the high-pressure airbag gas The H g The effective projected height of the high-pressure airbag on the side adjacent to the tunnel is obtained through three-dimensional modeling and measurement; b is the unit height of the airbag in the thrust direction at the most unfavorable section, which is taken as 1m; Step 205. Calculation of the Sudden Incident Risk Index: Using the formula R=R s / F gas Calculate the sudden attack risk index R; Step 3. Risk warning and consequence assessment: Based on the aforementioned outbreak risk index R, risk levels are classified, and corresponding warning information and response measures are output.

[0007] A further preferred technical solution is that P mentioned in Step 1 g The R was obtained by combining advanced drilling with a portable gas pressure recorder. g The data was obtained through ground-penetrating radar combined with borehole imaging, where D0 was obtained through ground-penetrating radar profiling, and σ... v =γh, where γ is the rock mass density and h is the tunnel burial depth, and the σ h =Kσ v K is the lateral pressure coefficient, ranging from 0.6 to 0.9; triaxial compression tests were conducted using a rock mechanics testing machine with confining pressures of 0.5 MPa to 1.5 MPa to obtain the peak strength parameters c0 and φ0 of the rock samples; the residual strength parameter c was determined through post-peak softening section testing. r φ r Based on the full stress-strain curve, nonlinear least squares inversion analysis is used to calibrate the attenuation coefficients α and β, with α ranging from 0.8 to 1.2 and β ranging from 0.05 to 0.15. The portable gas pressure recorder has a measurement accuracy of no less than ±0.01 MPa, the ground-penetrating radar has a detection depth of no less than 30 m, and the rock mechanics testing machine has a stress measurement accuracy of no less than ±0.1 MPa.

[0008] A further preferred technical solution is that the tunnel convergence displacement u in Step 201 is measured by a high-precision digital displacement meter. The displacement meter has a measurement accuracy of not less than ±0.01mm. The monitoring frequency is adjusted according to the risk level: once every 3 days for low risk, once every day for medium risk, once every 2 hours for high risk, and once every 30 minutes for extremely high risk. The empirical coefficient k is adapted to the lithology: k is 0.8~1.0 for granite, 0.6~0.8 for sandstone, and 0.5~0.7 for mudstone. k is verified and corrected by at least 3 sets of on-site convergence monitoring data.

[0009] A further preferred technical solution is that, in Step 3, the low-risk response measure is normal excavation without special treatment; the medium-risk response measure is to add a hazardous gas concentration monitoring point, with monitoring indicators including CO≤24ppm and CH4≤0.5%; the high-risk response measure is to stop excavation and use single-hole depressurization with a depressurization rate ≤0.01MPa / h; and the extremely high-risk response measure is to immediately evacuate personnel and equipment, activate the emergency plan, and use a combined treatment method of cement-water glass dual-liquid grouting and sealing combined with borehole depressurization.

[0010] A further preferred technical solution is that the risk levels are divided as follows: R≥1.5 is low risk, 1.0≤R<1.5 is medium risk, 0.5≤R<1.0 is high risk, and R<0.5 is extremely high risk.

[0011] The second aspect of this invention provides a dynamic prediction system for the risk of high-pressure airbag bursting in a nearby tunnel, including a data acquisition module, a data processing and model calculation module, and a risk warning and visualization module; The data acquisition module includes a ground-penetrating radar, a borehole imaging instrument, a portable gas pressure recorder, a high-precision digital displacement gauge, a rock mechanics testing machine, and a geostress monitoring device, used to acquire the airbag parameters, rock mass parameters, and engineering parameters in Step 1. The data processing and model calculation module has built-in numerical calculation software and prediction algorithms, which are used to perform rock wall stability calculation, surrounding rock strength dynamic update, rock wall resistance to damage calculation, high-pressure airbag destructive force calculation and outburst risk index calculation in Step 2. It also has an outlier removal function, adopts Grubbs criterion, and significance level α=0.05. The risk warning and visualization module includes a display, a graded audible and visual alarm, and a data storage unit, used to display real-time risk levels, output warning information, and store monitoring data and calculation results; the risk warning and visualization module also has a remote data transmission function, which can transmit real-time data to a remote monitoring platform to achieve multi-terminal synchronous monitoring.

[0012] A further preferred technical solution is that the warning signals of the graded sound and light alarm are distinguished according to risk level: low risk is green light, medium risk is yellow light + intermittent sound and light, high risk is orange light + continuous sound and light, and extremely high risk is red light + high-frequency sound and light.

[0013] The beneficial effects of this invention are: 1. Strong scenario adaptability: For the first time, it is designed for non-coal-bearing strata, solving the problem of "coal-bearing adaptation but non-coal-bearing failure" in existing models, with a prediction accuracy of over 90% (based on verification of 10 non-coal-bearing tunnel cases). 2. Advantages of dynamic prediction: By introducing a surrounding rock strength attenuation model, the risk is updated in real time (rather than static assessment), and the risk trend can be predicted 72 hours in advance, allowing sufficient time for emergency response; 3. Quantitative decision support: Establish a one-to-one correspondence between risk indices and response measures to avoid "over-response" (e.g., no work stoppage is required for low- to medium-risk areas), and shorten the tunnel construction period by an average of 15%-20%; 4. High system integration: It integrates the entire process of "data acquisition-calculation-early warning", supports remote monitoring (data is transmitted to the project department / owner platform), and realizes synchronous management and control of multiple terminals. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the initial stress state; Figure 2 A schematic diagram of the mechanical model of the "airbag-rock wall-tunnel" system after the step excavation; Figure 3 This is a schematic diagram of the mechanical model of the "airbag-rock wall-tunnel" system after the step excavation; Figure 4 This is the overall flowchart of the early warning system; Detailed Implementation

[0015] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] This invention provides a method for dynamically predicting the risk of high-pressure airbag bursting in nearby tunnels, comprising the following stages: (1) Parameter acquisition stage (Step 1) Three types of core parameters were obtained using a three-dimensional approach combining geological exploration, on-site monitoring, and laboratory testing. The measurement accuracy and methods for these parameters are as follows:

[0017] Key points: Pre-drilling should be carried out to the edge of the airbag (confirmed by a borehole imaging device), and the pressure recorder should be left to stand for ≥24 hours to avoid instantaneous pressure errors; The confining pressure of the triaxial test needs to simulate the actual ground stress (0.5MPa~1.5MPa) to obtain the full stress-strain curve from peak value to residual stress. Geostress calculation: Vertical geostress σ v =γh (γ is the rock mass density, taken as 26kN / m³; h is the burial depth), horizontal in-situ stress σ h =Kσ v (K is the lateral pressure coefficient, which is taken as 0.6~0.9 for non-coal-bearing strata).

[0018] (2) Real-time analysis stage (Step 2) Step 201 Calculation of Equivalent Plastic Strain of Rock Wall Based on the empirical relationship between tunnel convergence displacement and plastic strain, the degree of surrounding rock damage is quantified: formula:

[0019] Equivalent plastic strain (dimensionless); k: Empirical coefficient (adapted to lithology: granite 0.8~1.0, sandstone 0.6~0.8, mudstone 0.5~0.7, requiring verification and correction from at least 3 sets of monitoring data). u: Tunnel convergence displacement (mm); R tun Equivalent radius of tunnel (mm).

[0020] Example: When t = 1 day, u = 1.2 mm, k = 0.9, R tun =5000mm, therefore =0.9×1.2 / 5000=2.16×10 -4 .

[0021] Step 202 Dynamic Update of Surrounding Rock Strength Considering the attenuation law of surrounding rock strength with plastic strain, a dynamic strength model is established: Cohesive decay: c(t) = C0 - (C0 - c r )×(1-e^(-α )) Internal friction angle attenuation: φ(t) = φ0 - (φ0 - φ r )×(1-e^(-β )) Example: When t = 1 day, c(t) = 25 - (25 - 8) × (1 - e^(-1.0 × 2.16 × 10^3)).-4 ))≈24.96MPa;φ(t)=50-(50-30)×(1-e^(-0.1×2.16×10 -4 ))≈49.996°.

[0022] Step 203 Calculation of Rock Wall Resistance to Damage Based on the Mohr-Coulomb criterion, the rock wall is treated as a "rock column," and its shear capacity is calculated (unit: kN / m, calculated per unit length): Formula: R s =K1×c(t)×D t ×K2+K2×σ n ×D t ×tanφ(t) R s The rock face's resistance to damage; K1, K2: Geometric coefficients (K1=1.0, K2=0.8 when the slip surface is planar; K1=1.2, K2=1.0 when the slip surface is circular, verified by FLAC3D numerical simulation). D t Current rock wall thickness (D) t =D0- ×D0, due to reduced plastic deformation); σ n Mean normal stress (σ) on the slip surface n =σ h ×cos²θ+σ v ×sin²θ+σ sup θ is the horizontal angle between the airbag and the nearest point of the tunnel. Directly in front of the tunnel face, θ = 0°, therefore σ n =σ h +σ sup ).

[0023] Example: When t=1 day, D t =4.0-2.16×10 -4 ×4.0≈3.999m, σ n =16.64+0.8=17.44MPa, therefore R s =1.0×24.96×3.999×0.8+0.8×17.44×3.999×tan49.996°≈204.4kN / m.

[0024] Step 204 Calculation of the destructive force of the high-pressure airbag Quantification of the thrust of the airbag on the rock wall (unit: kN / m): Formula: F gas =P g ×H g ×b Fgas Airbag destructive power; P g : Airbag pressure (MPa, converted to kN / m² × 10³); H g : Effective projected height of the airbag (m, measured by AutoCAD modeling of the maximum projected length of the airbag in the tunnel normal direction). b: Unit height of the most unfavorable section (take 1m, calculated per unit length).

[0025] Example: P g =0.15MPa, H g =3.0m, therefore F gas =0.15×10³×3.0×1=450kN / m.

[0026] Step 205: Calculation of the Sudden Breakthrough Risk Index Risk is quantified using the ratio of "resistance to damage" to "damage capacity": Formula: R = R s / F gas R: Burst risk index (dimensionless, the smaller the R, the higher the risk).

[0027] Example: When t=1 day, R=204.4 / 450≈0.454.

[0028] (3) Risk warning and consequence assessment (Step 3) Based on the risk index R, four levels of risk are divided, and corresponding differentiated response measures are implemented to achieve "precise early warning - scientific response":

[0029] The system that implements the above method includes a data acquisition module, a data processing and model calculation module, and a risk warning and visualization module; The data acquisition module includes a ground-penetrating radar, a borehole imaging instrument, a portable gas pressure recorder, a high-precision digital displacement gauge, a rock mechanics testing machine, and a geostress monitoring device, used to acquire the airbag parameters, rock mass parameters, and engineering parameters in Step 1. The data processing and model calculation module has built-in numerical calculation software and prediction algorithms, which are used to perform rock wall stability calculation, surrounding rock strength dynamic update, rock wall resistance to damage calculation, high-pressure airbag destructive force calculation and outburst risk index calculation in Step 2. It also has an outlier removal function, adopts Grubbs criterion, and significance level α=0.05. The risk warning and visualization module includes a display, a graded audible and visual alarm, and a data storage unit, used to display real-time risk levels, output warning information, and store monitoring data and calculation results; the risk warning and visualization module also has a remote data transmission function, which can transmit real-time data to a remote monitoring platform to achieve multi-terminal synchronous monitoring; The warning signals of the graded sound and light alarm are distinguished according to risk level: low risk is green light, medium risk is yellow light + intermittent sound and light, high risk is orange light + continuous sound and light, and extremely high risk is red light + high-frequency sound and light.

[0030] The following example, a deep and long granite tunnel (depth h = 800m, circular cross-section, diameter 10m) in a non-coal-bearing strata, is used to further illustrate the implementation process of this invention: 1. Preliminary preparations Equipment deployment: Three ground-penetrating radar profiles (2m apart) and three advance boreholes (15m deep, 90mm in diameter) are arranged at the tunnel face; four displacement gauges (symmetrically distributed) are arranged on the inner wall of the tunnel; and six sets of granite rock samples (Φ50mm×100mm) are prepared indoors.

[0031] 2. Parameter Acquisition (Step 1) Airbag parameters: R measured by ground-penetrating radar + borehole imaging instrument g =3.0m; P was measured by the pressure recorder after standing for 24 hours. g =0.15MPa; Rock mass parameters: Triaxial tests (confining pressure 0.5 / 1.0 / 1.5 MPa) yielded c0=25 MPa, φ0=50°, and c r =8MPa, φ r =30°, the inversion yields α=1.0 and β=0.1; Engineering parameters: Ground penetrating radar measured D0 = 4.0m; R tun =5.0m; σ sup =0.8MPa; σ v =26×800×10 -3 =20.8MPa, σ h =0.8×20.8=16.64MPa.

[0032] 3. Real-time analysis (Step 2) t = 1 day: u = 1.2 mm → =2.16×10 -4 →c(t)=24.96MPa、φ(t)=49.996°→D t =3.999m→R s =204.4kN / m→F gas=450kN / m→R=0.454 (extremely high risk); t=3 days: u=2.5mm→ =4.5×10 -4 →c(t)=24.92MPa、φ(t)=49.991°→R s =204.23kN / m→R=0.454 (extremely high risk); t=7 days (after grouting and pressure relief): u=1.8mm→ =3.24×10 -4 →c(t)=24.94MPa→R s =204.3kN / m; P g Reduced to 0.08 MPa → F gas =0.08×10³×3.0×1=240kN / m→R=0.851 (high risk).

[0033] 4. Handling and Feedback Extremely high risk stage (t=1-3 days): immediately evacuate personnel and equipment, grout the working face (cement-water glass double liquid grout, water-cement ratio 1:1, pressure 2MPa), and after 3 days of curing, drill 2 pressure relief holes (hole diameter 50mm) and slowly release pressure to 0.08MPa; High-risk phase (t=7 days): Resume monitoring, stop depressurization, continue excavation, and increase the monitoring frequency to once every 2 hours; Final result: There was no outburst when excavating to the location of the airbag, and the construction period was only delayed by 2 days (traditional treatment would have delayed it by more than 10 days).

[0034] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made to it in form and detail without departing from the scope defined by the claims of the present invention.

Claims

1. A method for dynamically predicting the risk of a sudden burst of a high-pressure airbag near a tunnel, characterized in that, Comprising the following steps: Step1. Parameter acquisition stage: obtain air bag parameters, rock mass parameters and engineering parameters; The airbag parameters include the pressure P of the gas inside the airbag g and the equivalent radius R g ; The rock mass parameters include initial strength parameters (cohesion c0, internal friction angle φ0) of the rock mass, residual strength parameters (cohesion c r , internal friction angle φ r ), elastic modulus E, Poisson's ratio v and attenuation coefficients (α, β); The engineering parameters include the initial thickness D0 of the rock wall between the tunnel and the airbag, and the equivalent radius R of the tunnel excavation section. tun Time after excavation (t), support strength (σ) sup and ground stress (vertical ground stress σ) v Horizontal ground stress σ h ); Step2. Real-time analysis stage: Step 201. Rock wall stability calculation: Based on the field monitored tunnel convergence displacement u, the equivalent plastic strain of the rock wall between the tunnel and the airbag is calculated through an empirical relationship = k x u / R tun = k x u / R , where k is an empirical coefficient; Step 202. Surrounding rock strength dynamic updating: according to the equivalent plastic strain calculated in Step 201 , the current cohesion c(t) and internal friction angle φ(t) of the rock wall are updated in real time in combination with the rock mass strength attenuation model; the attenuation model is: ， ； Step 203. Calculate the rock wall resistance to failure: based on the Mohr-Coulomb criterion, the rock wall resistance to failure R is calculated by the formula R = K1 x c(t) x D s t x K2 + K2 x σ n x D t x tan φ(t) s ; the D t is the current rock wall thickness, D t = D0- x D0; the K1, K2 are geometric coefficients related to the shape of the potential sliding surface, K1 = 1.0, K2 = 0.8 when the sliding surface is a plane, K1 = 1.2, K2 = 1.0 when the sliding surface is a circular arc surface; the σ n is the average normal stress on the sliding surface, σ n = σ h x cos2 θ + σ v x sin2 θ + σ sup , θ is the horizontal angle between the tunnel excavation profile line and the edge line of the high-pressure air bag.​​​​​​​​​​​​​ Step 204. Calculation of the destructive force of the high-pressure airbag: using formula F gas =P g ×H g ×b Calculate the destructive force F of the high-pressure airbag gas The H g The effective projected height of the high-pressure airbag on the side adjacent to the tunnel is obtained through three-dimensional modeling and measurement; b is the unit height of the airbag in the thrust direction at the most unfavorable section, which is taken as 1m; Step 205. Risk of outburst index calculation: by formula R = R s / F gas Risk of outburst index R is calculated; Step3. Risk early warning and consequence assessment: divide the risk level according to the outburst risk index R, and output early warning information and disposal measures correspondingly.

2. The method of claim 1, wherein, P described in step 1 g R is obtained by advanced drilling combined with portable gas pressure recorder detection, and D0 is obtained by geological radar profile detection g D0 is obtained by geological radar profile detection, and σ is obtained by geological radar combined with borehole imaging instrument detection v =γh, γ is the weight of the rock mass, and h is the tunnel depth, and σ h =Kσ v , K is a lateral pressure coefficient, and the value is 0.6-0.9; triaxial compression test is carried out through a rock mechanics testing machine, the confining pressure is 0.5-1.5 MPa, and the peak strength parameters c0 and φ0 of the rock sample are obtained; the residual strength parameters c r , φ r are determined through post-peak softening section test; based on the whole stress-strain curve, the attenuation coefficients a and β are calibrated by using nonlinear least square method inversion analysis, the value range of a is 0.8-1.2, and the value range of β is 0.05-0.15; the measurement accuracy of the portable gas pressure recorder is not less than ±0.01 MPa, the detection depth of the geological radar is not less than 30 m, and the stress measurement accuracy of the rock mechanics testing machine is not less than ±0.1 MPa.

3. The method of claim 1, wherein, The tunnel convergence displacement u in Step201 is measured by a high-precision digital displacement meter, and the measurement accuracy of the displacement meter is not less than ±0.01mm, and the monitoring frequency is adjusted according to the risk level: 1 time / 3 days for low risk, 1 time / day for medium risk, 1 time / 2h for high risk, and 1 time / 30min for extremely high risk; the experience coefficient k is adapted according to the lithology: k is taken as 0.8~1.0 for granite lithology, k is taken as 0.6~0.8 for sandstone lithology, and k is taken as 0.5~0.7 for mudstone lithology, and k is verified and corrected by at least 3 groups of field convergence monitoring data.

4. The method of claim 1, wherein, The disposal measures corresponding to the low risk in Step3 are normal excavation, and no special disposal is needed; the disposal measures corresponding to the medium risk are to add harmful gas concentration monitoring points, and the monitoring indexes include CO≤24ppm and CH4≤0.5%; the disposal measures corresponding to the high risk are to stop excavation, and to adopt single-hole pressure relief with a pressure relief rate≤0.01MPa / h; the disposal measures corresponding to the extremely high risk are to immediately evacuate personnel and equipment, to start an emergency plan, and to adopt a combined treatment mode of cement-sodium silicate double slurry grouting and drilling pressure relief.

5. The method of claim 1, wherein, The risk level division in Step3 is as follows: R≥1.5 is low risk, 1.0≤R<1.5 is medium risk, 0.5≤R<1.0 is high risk, and R<0.5 is extremely high risk.

6. A system for dynamically predicting the risk of peritubular high pressure balloon rupture in proximity to a tunnel, the system implementing the method of any one of claims 1-5. Comprising a data acquisition module, a data processing and model calculation module, and a risk early warning and visualization module; The data acquisition module comprises a geological radar, a borehole imaging instrument, a portable gas pressure recorder, a high-precision digital displacement meter, a rock mechanics testing machine, and a ground stress monitoring device, which are used to obtain the air bag parameters, rock mass parameters and engineering parameters in Step1; The data processing and model calculation module is built-in numerical calculation software and prediction algorithm, which is used to perform rock wall stability calculation, surrounding rock strength dynamic updating, rock wall resistance to damage calculation, high-pressure air bag damage force calculation and outburst risk index calculation in Step2, and has an abnormal value elimination function, adopts Grubbs criterion, and the significance level α=0.05; The risk early warning and visualization module comprises a display, a hierarchical sound and light alarm and a data storage unit, which is used to display real-time risk level, output early warning information, and store monitoring data and calculation results; the risk early warning and visualization module also has a remote data transmission function, which can transmit real-time data to a remote monitoring platform to realize multi-terminal synchronous monitoring.

7. The system of claim 6, wherein, The early warning signals of the hierarchical sound and light alarm are distinguished according to the risk level: green light for low risk, yellow light+intermittent sound and light for medium risk, orange light+continuous sound and light for high risk, and red light+high-frequency sound and light for extremely high risk.

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