Time-delay type rock burst risk area analysis method and system for drill-and-blast tunneling

Abstract

The application provides a time-delay type rock burst risk area analysis method and system for a drill-and-blast tunnel, relates to the technical field of tunnel risk analysis, and comprises the following steps: acquiring first information, wherein the first information comprises geological reconnaissance information and microseismic data information in a tunnel excavation process; performing actual disaster grade analysis and microseismic activity mapping grade analysis according to the geological reconnaissance information to obtain actual disaster grades and microseismic activity mapping grades; performing energy release rate calculation processing based on all the actual disaster grades and the microseismic activity mapping grades, and identifying a potential time-effect disaster risk area according to the calculated energy release rate; evaluating the risk degree of the potential time-effect disaster risk area based on a preset time-effect disaster risk degree evaluation table to obtain a time-effect disaster risk analysis result of the area. The application not only improves the objectivity and accuracy of time-effect disaster risk identification, but also can guide the arrangement of sensors and the selection of monitoring ranges.

Description

Technical Field

[0001] This invention relates to the field of tunnel risk analysis technology, and more specifically, to a time-delay rockburst risk zone analysis method and system for drill-and-blast tunnels. Background Technology

[0002] With the large-scale construction of underground engineering projects, especially deep-buried hard rock tunnels, the problem of engineering disasters induced by geostress has become increasingly prominent. Among them, time-delayed rockbursts are a typical type of time-dependent disaster, characterized by rockbursts that occur delayed after tunnel excavation unloading and stress redistribution in the surrounding rock, under the influence of external disturbances. These disasters are highly concealed and random, often occurring far from the working face, and are extremely likely to cause casualties and equipment damage. Existing technologies mostly focus on the identification and prediction of immediate rockbursts (which mostly occur within a few hours or 1-3 days after excavation, and are mostly within three times the tunnel diameter from the working face). Research on time-delayed rockbursts is still in the exploratory stage. Existing technologies not only lack accuracy in the spatiotemporal identification of time-delayed rockbursts, but also exhibit blindness in the selection of monitoring ranges and sensor placement. Publicly available early warning methods based on geological discrimination or acoustic-electric technology also suffer from defects such as strong subjectivity in identification results, low accuracy, and ambiguity in monitoring target areas, making it difficult to meet the needs of construction safety for accurate early warning and prevention of time-delayed rockbursts.

[0003] Therefore, there is an urgent need for a time-delay rockburst risk zone analysis method and system for drill-and-blast tunnels, in order to solve the aforementioned technical problems. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for analyzing time-delay rockburst risk zones in drill-and-blast tunnels, thereby improving the aforementioned problems. To achieve this objective, the technical solution adopted by this invention is as follows:

[0005] Firstly, this application provides a method for analyzing time-delay rockburst risk zones in drill-and-blast tunnels, including:

[0006] Obtain first information, which includes geological reconnaissance information during tunnel excavation and microseismic data collected by the microseismic monitoring system;

[0007] Based on the geological reconnaissance information, actual disaster level analysis and microseismic activity mapping level analysis are performed to obtain the actual disaster level and microseismic activity mapping level of all preset tunnel zones;

[0008] Energy release rate is calculated based on the actual disaster level and microseismic activity mapping level of all the preset tunnel zones, and potential time-sensitive disaster risk areas are identified based on the calculated energy release rate.

[0009] The risk level of potential time-sensitive disaster risk areas is assessed based on a pre-set time-sensitive disaster risk assessment table, and the time-sensitive disaster risk analysis results for the area are obtained.

[0010] Secondly, this application also provides a time-delay rockburst risk zone analysis system for drill-and-blast tunnels, comprising:

[0011] The acquisition unit is used to acquire first information, which includes geological reconnaissance information during the tunnel excavation process and microseismic data information collected by the microseismic monitoring system.

[0012] The grading unit is used to perform actual disaster level analysis and microseismic activity mapping level analysis based on the geological reconnaissance information, and to obtain the actual disaster level and microseismic activity mapping level of all preset tunnel zones;

[0013] The calculation unit is used to calculate the energy release rate based on the actual disaster level and microseismic activity mapping level of all the preset tunnel zones, and to identify potential time-sensitive disaster risk areas based on the calculated energy release rate.

[0014] The analysis unit is used to assess the risk level of potential time-sensitive disaster risk areas based on a pre-set time-sensitive disaster risk assessment table, and obtain the time-sensitive disaster risk score for the area.

[0015] The beneficial effects of this invention are as follows:

[0016] This invention integrates geological reconnaissance information and microseismic monitoring data from tunnel excavation, utilizing a disaster level analysis model and neural network mapping technology to achieve dual identification of disaster levels. It also introduces energy release rate as a quantitative indicator to identify potential time-sensitive disaster risk areas. Based on this, a risk assessment table is constructed by combining engineering geology and support information, thereby achieving hierarchical management and scientific prediction of risk areas. This solution not only improves the objectivity and accuracy of time-sensitive disaster risk identification but also provides targeted guidance for sensor deployment and monitoring range selection.

[0017] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing embodiments of the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the time-delay rockburst risk zone analysis method for drill-and-blast tunnels as described in this embodiment of the invention;

[0020] Figure 2 This is a schematic diagram of the time-delay rockburst risk area analysis system for drill-and-blast tunnels as described in this embodiment of the invention;

[0021] Figure 3 This is the potential time-sensitive risk area identification table in the time-delay rockburst risk area analysis method for drill-and-blast tunnels described in this embodiment of the invention;

[0022] Figure 4 This is the geological reconnaissance information record table for drill-and-blast tunnels in the time-delay rockburst risk zone analysis method for drill-and-blast tunnels described in this embodiment of the invention.

[0023] Figure 5 This is a schematic diagram illustrating the mapping relationship between microseismic activity and disaster level in the time-delay rockburst risk area analysis method for drill-and-blast tunnels described in this embodiment of the invention.

[0024] Figure 6 This is a schematic diagram of a time-delay rockburst occurring in the field, as described in the time-delay rockburst risk zone analysis method for drill-and-blast tunnels in this embodiment of the invention.

[0025] Figure 7 The time-delayed disaster risk assessment table in the time-delayed rockburst risk area analysis method for drill-and-blast tunnels described in this embodiment of the invention.

[0026] In the figure: 1. Microseismic activity information; 2. Microseismic information mapping to rockburst level and probability; 3. Tunnel where time-delayed rockburst disasters occurred; 4. Adjacent tunnels; 5. Blasting time; 6. Working face location; 7. Excavation direction; 8. Area where time-delayed rockburst disasters occurred; 9. Blasting stress wave; 10. On-site photos of time-delayed rockburst disasters; 701. Acquisition unit; 702. Grading unit; 703. Calculation unit; 704. Analysis unit. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0028] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0029] Example 1:

[0030] This embodiment provides a time-delay rockburst risk zone analysis method for drill-and-blast tunnels.

[0031] See Figure 1 , Figure 3 and Figure 7 The figure shows that the method includes steps S1, S2, S3 and S4.

[0032] Step S1: Obtain first information, which includes geological reconnaissance information during tunnel excavation and microseismic data collected by the microseismic monitoring system;

[0033] It is understandable that, such as Figure 1As shown, this step constructs a unified data foundation spanning "blasting cycle - spatial zoning - monitoring indicators": taking each blasting cycle advance as a time-space unit, the area in front of the tunnel face is divided into several "time-sensitive risk area identification units," and two types of complementary information are collected simultaneously within each unit: first, on-site geological reconnaissance information, including lithology, geological structure, surrounding rock grade and burial depth / ground stress, cross-sectional dimensions and shape, actual advance, support type and parameters, as well as the grade, location, type and treatment records of rockbursts that have occurred; second, quantitative indicators of the microseismic monitoring system, including at least the cumulative number of microseismic events, cumulative released energy, cumulative apparent volume, and the corresponding event rate, energy rate and apparent volume rate, and the sensor array is moved forward as the tunnel face advances to ensure temporal continuity and stable coverage. In terms of engineering implementation, this step not only completes the closed-loop process of "data acquisition - partitioning - alignment" (after the sensors are calibrated, they are aligned with the tunnel axis to form a unified coordinate system; during the blasting period, a window / trapping and threshold triggering method is used to remove strong earthquake saturation and non-tectonic noise; P / S picking and time-based inversion are used for event location and apparent volume estimation; and reconnaissance and monitoring establish a one-to-one data table based on the blasting cycle number), but also significantly reduces the deviation between traditional subjective segmentation and post-event experience judgment by integrating macroscopic (geological and support constraints) and microscopic (acoustic emission / microseismic response of fractures) under the same partition and the same time scale; and because it adopts "cyclic advance" as the granularity, it is naturally adapted to the disturbance rhythm of the drill-and-blast method, making the disturbance effect distinguishable, accumulative, and traceable in terms of indicators, providing high signal-to-noise ratio and weak non-stationarity friendly training / computation samples for subsequent neural network mapping of disaster level and calculation of energy release rate. In this step, step S1 includes steps S11 and S12.

[0034] Step S11: Based on the advance of one blasting cycle during tunnel excavation, divide at least two time-sensitive risk zone identification units, and record the engineering geological information, excavation support information and rock burst information of all time-sensitive risk zones in each blasting cycle, and generate a geological reconnaissance information record table for the drill-and-blast method tunnel.

[0035] Understandably, this step uses a single blasting cycle advance as the smallest spatiotemporal unit, dividing the tunnel surrounding rock into at least two time-sensitive risk zone identification units. This division reflects the spatial distribution differences and stress release characteristics of the surrounding rock under the same blasting disturbance. This fine-grained division not only avoids obscuring local high-risk areas in previous single-cycle overall assessments but also ensures sufficient spatial resolution in subsequent analyses to characterize the evolution trajectory of time-delayed hazards. Within each risk unit, comprehensive engineering geological information (such as lithology, joint and fracture distribution, surrounding rock integrity, and geostress characteristics), excavation and support information (such as support type, parameter configuration, shotcrete thickness, anchor bolt and arch frame arrangement), and the actual situation of rockburst occurrence (including grade, location, failure mode, and on-site treatment measures) need to be recorded. This information, after standardization, is incorporated into a unified geological reconnaissance information record form, providing a structured basis for subsequent alignment with microseismic data and forming a dynamically updated "construction-geology-hazard" database. The unique effect of this step is that it transforms the traditional approach that relies solely on static geological descriptions into a dynamic record based on cycles and zones, thus closely linking the spatial variability of rockburst disaster risk with construction conditions.

[0036] Step S12: Set up microseismic sensors at preset locations in the tunnel and record microseismic data during the tunnel excavation process using the microseismic sensors. The microseismic data includes the cumulative number of microseismic events, the cumulative microseismic energy release, the cumulative microseismic apparent volume, the microseismic event rate, the microseismic energy release rate, and the microseismic apparent volume rate.

[0037] It is understandable that the deployment of the microseismic monitoring system in this step is a crucial step in achieving dynamic identification of time-sensitive disasters. Its core lies in the rational placement of microseismic sensors at predetermined locations within the tunnel to obtain the most direct and sensitive energy release signals during the evolution of surrounding rock fracturing. Typically, sensors are arranged in rows along the tunnel wall or shoulder behind the tunnel face, and are moved forward or added as the excavation progresses, ensuring the continuity and timeliness of monitoring coverage. At the data acquisition level, not only are individual microseismic events recorded, but also "cumulative microseismic event count" and "cumulative microseismic energy release" are obtained through time-series accumulation. These indicators characterize the overall intensity and energy evolution trend of rock mass fracturing activity; "cumulative microseismic apparent volume" reflects the extent of expansion of the fracturing spatial range. Simultaneously, the time derivatives of the event count, energy, and apparent volume are used to obtain the "event rate," "energy rate," and "apparent volume rate," respectively, to reveal the dynamic activity and energy release rate of the fracturing process. In practical applications, the comprehensive analysis of these indicators can be used to identify the evolution of surrounding rock from microcrack initiation to macroscopic fracturing, especially the response characteristics under drilling and blasting disturbances or other dynamic effects.

[0038] Step S2: Based on the geological reconnaissance information, perform actual disaster level analysis and microseismic activity mapping level analysis to obtain the actual disaster level and microseismic activity mapping level of all preset tunnel zones;

[0039] Understandably, this step begins with an actual hazard level analysis based on geological reconnaissance information. This involves inputting lithology, structural joints, burial depth, stress conditions, surrounding rock integrity, and support parameters collected during tunnel excavation into a pre-defined hazard level analysis model. This model determines the actual hazard level of each time-sensitive risk zone by comparing typical criteria (such as high-stress sections, distribution of weak structural surfaces, and rock mass integrity index) with existing hazard level standards. This result reflects the inherent possibility of rockbursts occurring in the surrounding rock under objective geological and construction conditions. Secondly, for microseismic monitoring data, neural networks or other nonlinear mapping methods are used to establish a mapping relationship between microseismic activity parameters (cumulative event count, energy, apparent volume and its rate, etc.) and hazard levels, generating a "microseismic activity mapping level." This approach avoids the subjectivity of relying solely on empirical thresholds, instead revealing the implicit connection between microseismic evolution characteristics and hazard intensity through data-driven pattern recognition. In this step, step S2 includes steps S21 and S22.

[0040] Step S21: The geological reconnaissance information is sent to a preset disaster level analysis model for analysis. The energy release of the surrounding rock is calculated based on the initial three-dimensional geostress field and crater volume of the tunnel area in the geological reconnaissance information. The energy release of the surrounding rock is classified based on the calculated energy release. The energy release of the surrounding rock is classified based on the analytic hierarchy process to obtain the actual disaster level corresponding to each time-sensitive risk area identification unit during the tunnel excavation process. The time-sensitive risk area identification unit is used as a preset tunnel partition.

[0041] Understandably, this step inputs the data from the time-sensitive risk zone identification units formed by each blasting cycle into a pre-set disaster level analysis model. This model typically combines multiple factors such as rock mechanics indicators, structural conditions, and support measures for comprehensive evaluation. For example, lithology and integrity determine the bearing capacity of the surrounding rock, burial depth and geostress level reflect the external stress environment, structural surface orientation and density reveal potential weak fracture surfaces, and support strength and type affect whether the surrounding rock can effectively confine energy accumulation. The analysis model first calculates the energy density distribution in the surrounding rock after tunnel excavation based on the initial three-dimensional geostress field of the tunnel area using the following formula.

[0042] ;

[0043] ;

[0044] ;

[0045] ;

[0046] ;

[0047] ;

[0048] ;

[0049] In the formula, The elastic strain energy density of the surrounding rock; Poisson's ratio of the surrounding rock; The elastic modulus of the surrounding rock; , , , , and The initial geostress field consists of three-dimensional six-component stresses; , , , , and The stress is a three-dimensional six-component stress of the disturbance stress field after excavation.

[0050] After a rockburst occurs, a three-dimensional laser scan of the tunnel section where the rockburst occurred can determine the volume of the crater. The energy released during a rockburst is the product of the elastic strain energy density of the surrounding rock and the volume of the crater.

[0051] Subsequently, the energy release was classified using the analytic hierarchy process (AHP): a judgment matrix was constructed from geological reconnaissance information, incorporating criteria such as lithology, burial depth, geostress level, and structural surface development. The weights of each factor were determined through expert scoring and consistency checks, ultimately mapping continuous energy release to actual hazard levels (none, minor, moderate, severe, and extremely severe). This process transforms geological parameters into quantitative risk indicators, avoiding biases from subjective experience-based judgments and achieving objectivity and standardization of zonal hazard levels. In this process, each time-sensitive risk identification unit was established as an independent tunnel zone, giving the hazard level determination results a clear spatial orientation. The unique aspect of this step is that it establishes a direct quantitative relationship between "geology—operating conditions—risk," thus avoiding the shortcomings of previous reliance on subjective experience-based judgments.

[0052] Step S22: Perform actual disaster level mapping processing based on the microseismic data information. Specifically, a convolutional neural network is used to learn the mapping relationship between preset historical microseismic data information and preset historical actual disaster levels. The microseismic data information is then output to the learned convolutional neural network to obtain the corresponding microseismic activity mapping level for each preset tunnel partition.

[0053] It is understandable that in this step, microseismic activity essentially reflects the evolution of internal rock fissures from initiation to propagation and ultimately macroscopic instability. Its characteristic quantities (such as the cumulative number of events, released energy, apparent volume, and its rate of change) often exhibit a nonlinear and strongly coupled relationship with the intensity and probability of disaster occurrence. Traditional linear threshold discrimination methods are insufficient to effectively reveal these complex patterns. Therefore, through neural network training, existing disaster instances can be used as samples to automatically learn the correspondence between different parameter combinations and disaster levels, and possess generalization capabilities to predict risk levels under unknown conditions. Specifically, based on microseismic data information (number of microseismic events, released energy, apparent volume, and its rate), a convolutional neural network (CNN) is used to map disaster levels. The CNN automatically extracts spatial and temporal features (energy release rhythm) from microseismic time-series data through convolutional and pooling layers, and learns the nonlinear mapping relationship between these features and historical actual disaster levels. The trained CNN can directly input real-time microseismic data and output the corresponding microseismic activity mapping level. This method overcomes the shortcomings of traditional threshold methods in adapting to complex microseismic patterns. Through data-driven approaches, it improves the accuracy and generalization ability of identification. In practical applications, microseismic data from each zone are fed into the network, and the output is the corresponding disaster level. This "data-driven" identification avoids the subjectivity caused by manually setting thresholds and can adapt to complex geological conditions and diverse disturbances in construction environments. Specifically, the neural network in this step is a convolutional neural network, trained on existing data (microseismic data and disaster levels) to obtain the trained neural network.

[0054] Step S3: Calculate the energy release rate based on the actual disaster level and microseismic activity mapping level of all the preset tunnel zones, and identify potential time-sensitive disaster risk areas based on the calculated energy release rate;

[0055] It is understandable that this step, by dividing the actual disaster level by the microseismic mapping level, yields a normalized energy release rate index. This index essentially measures the relative balance between the disaster performance of the rock mass within a zone and the intensity of its microseismic activity: if the energy release rate is greater than or close to 1, it indicates that microseismic activity and geological risk are consistent, and the rock mass energy has been relatively released; if the energy release rate is less than 1, it indicates that the geological conditions are judged to be high-risk, but microseismic activity is insufficient to fully release the potential energy, and the surrounding rock is in a critical or subcritical accumulation state, representing a typical incubation environment for time-delayed disasters. In practical applications, by calculating and comparing the energy release rate of each blasting cycle zone, it is possible to intuitively identify which areas have insufficient energy release, thereby pinpointing potential time-delayed disaster risk areas. In this step, step S3 includes steps S31 and S32.

[0056] Step S31: Divide the actual disaster level of each tunnel section by the microseismic activity mapping level to obtain the energy release rate of each tunnel section in each blasting cycle;

[0057] It is understandable that, such as Figure 3 As shown, this step constructs the energy release rate at the zonal level by dividing the "actual disaster level by the microseismic activity mapping level." This is a key operation that unifies the macroscopic static risk (the actual disaster level given by geological and support conditions) and the microscopic dynamic response (the microseismic mapping level output by the neural network) onto the same scale. Specifically, the two levels are first unified to a consistent ordinal level / numerical domain (such as 1–5 equidistant or non-equidistant scale calibrated with historical samples). Outliers and missing measurements are robustly handled (such as setting a lower limit for mapping levels of 0 or minimum values, and using interpolation or elimination for sensor saturation periods). Then, the ratio is calculated zonally with the blasting cycle as the time granularity. If necessary, sliding median / quantile smoothing can be used for adjacent cycles to suppress the spike error caused by a single disturbance. The physical meaning of this ratio is the relative gap between the "instability demand implied by geology / support" and the "energy share currently released by microseismic activity." A value approximately 1 indicates that macroscopic risk and microseismic release are roughly balanced. A value greater than 1 is often seen in matching scenarios of low-microseismic-low-risk or high-microseismic-high-risk, while a value less than 1 reveals a subcritical energy storage state of "high macroscopic risk - insufficient microseismic release," which is a typical embryonic area for time-delay disasters. In engineering implementation, confidence weights (e.g., weighting the mapping level according to sensor coverage, event location accuracy, and signal-to-noise ratio) and partition area / volume normalization can be introduced to avoid interference from differences in partition scale on the results.

[0058] Step S32: Compare the energy release rate of each tunnel section in each blasting cycle with a preset threshold, and determine the potential time-sensitive disaster risk area based on the comparison results.

[0059] Understandably, this step involves statistically summarizing energy release rates under different geological conditions and monitoring scenarios to extract the critical value for a zone to transition from a safe state to a potentially hazardous state. In practical applications, the energy release rate of each zone in a single blasting cycle is compared with this threshold: if the release rate is higher than or close to 1, it indicates that the microseismic activity has basically matched the risk level under geological conditions, and the surrounding rock energy has been partially released, making the risk relatively controllable in the short term; if the release rate is significantly lower than the threshold, it means that there is energy accumulation but insufficient release in this zone, and the surrounding rock is in a critical or subcritical state, which is highly likely to evolve into a time-delayed disaster under continuous disturbance. Through continuous iterative comparison, the distribution of potential risk areas can be dynamically updated, achieving "real-time locking" of potential disaster hazards.

[0060] Step S4: Assess the risk level of potential time-sensitive disaster risk areas based on the preset time-sensitive disaster risk assessment table, and obtain the time-sensitive disaster risk analysis results for the area.

[0061] Understandably, this step normalizes and scores "geological constraints" such as lithology and integrity, structural plane occurrence and density, burial depth / situational stress level, water content and unloading conditions, and "engineering constraints" such as support type, parameters, and construction conditions, according to indicator weights (which can be obtained from historical case statistics or expert-data hybrid weighting). Robust aggregation (such as quantiles or Huber loss) is used to suppress the influence of extreme values, and Bayesian updates or confidence lower limits are used to handle uncertainties or missing data, ensuring that the score maintains a conservative bias towards "adverse situations." Subsequently, the comprehensive score is mapped to a risk level and compared with... Figure 7 The table shows a threshold rule linkage mechanism—for example, when the assessment value reaches or exceeds a threshold (e.g., a score ≥5 is considered high risk in experience), a "high risk" conclusion and its evidence chain are output, serving as the basis for the time-sensitive disaster risk analysis results and response priorities for that zone (see the handover notes for the use of the assessment table and thresholds: the risk level is constructed and determined by engineering geology and support information, and when the risk level value is ≥5, it is classified as a higher risk, forming the trigger condition for a high-risk conclusion). In this step, step S4 includes steps S41 and S42.

[0062] Step S41: Based on the engineering geological information and excavation support information in the geological exploration information of each preset tunnel zone, construct a time-sensitive disaster risk assessment table and determine the time-sensitive disaster risk level of each potential time-sensitive disaster risk area;

[0063] Understandably, this step first parameterizes the rock mass conditions of each zone, such as the type of surrounding rock, lithological hardness, degree of joint and fracture development, geostress level, and burial depth. These factors determine the stability and energy storage potential of the surrounding rock itself. Then, combined with the support methods and parameters used during construction, such as anchor type, length and spacing, steel arch model, and shotcrete thickness, this reflects the ability of human intervention to regulate the energy balance of the surrounding rock. Subsequently, these indicators are normalized and integrated according to a preset scoring system and weights to form a risk assessment table. In this way, the geological and support conditions of different zones are quantified and horizontally comparable, objectively reflecting the level of their time-sensitive disaster risk. Finally, the assessment table is used to score each potential time-sensitive disaster risk area and map it to a risk level (e.g., low, medium, high), thereby achieving a graded determination of the risk level of each zone.

[0064] Step S42: If the time-term disaster risk level of the potential time-term disaster risk area is greater than the preset level, then the potential time-term disaster risk area is determined to be a high-risk time-term disaster risk area, and it is used as the time-term disaster risk analysis result corresponding to the area.

[0065] Understandably, in this step, when the risk level assessment table outputs a zoning risk level exceeding the preset critical level (e.g., a value ≥ 5 for medium-high level), it means that the zoning can no longer maintain a safe balance in terms of geological conditions, energy accumulation state, and support capacity, and its surrounding rock is in a metastable state that is highly susceptible to dynamic disturbances. At this point, the system clearly identifies the zoning as a high-risk area and outputs it as the formal time-sensitive disaster risk analysis result. The unique value of this process lies in its ability to converge complex multi-parameter assessment results into a clear decision signal, enabling monitoring personnel and construction managers to identify areas requiring immediate attention and avoid delays in response due to ambiguous judgments.

[0066] It is understandable that step S4 is followed by steps S5, S6, S7, and S8.

[0067] Step S5: Real-time acquisition of data information on whether new rupture events occur in potential time-risk areas, and the spectrum and time-frequency diagram of vibration waveforms in historical potential time-risk areas;

[0068] It is understandable that in this step, newly formed fracturing events typically manifest as the sudden expansion of deep rock fissures or the initiation of new fissures under dynamic disturbance. The high-frequency pulses, sudden increases in waveform energy, and event location clustering characteristics acquired by the microseismic monitoring system through its sensor array can serve as the basis for identification. Simultaneously, spectral and time-frequency analysis of the vibration waveforms in historical potential risk areas is necessary. This involves using Fast Fourier Transform and Time-Frequency Transform methods to decompose the original waveform signal into energy distributions within different frequency bands and time windows. The spectral graph reveals the dominant frequency range of the fracturing event, while the time-frequency graph depicts the characteristics of the event's energy evolution over time. Combining the two can distinguish between shallow fracturing and deep macroscopic fracturing. By simultaneously acquiring newly formed fracturing data and historical waveform evolution patterns, it is possible not only to identify whether the current risk area is evolving towards a disaster state but also to determine whether the area exhibits an "accumulation-release" pattern under past disturbances.

[0069] Step S6: Based on the data information of the newly formed rupture event, determine whether the corresponding potential time-sensitive risk area will experience a time-sensitive disaster within a preset time period, and obtain the judgment result.

[0070] In step S6, the judgment of "whether a time-sensitive disaster will occur within a preset time period" needs to be transformed into a set of executable near-field triggering criteria: taking each potential risk zone as the object, a monitoring window that rolls over time (such as 1–3 blasting cycles or 24–72 hours) is constructed to extract features and identify triggers for the new rupture event flow—including event rate and its acceleration, cumulative energy and step increment, Benioff strain cumulative slope, proportion of low-frequency events (indicating deep macroscopic rupture), average duration and proportion of long-duration events, b-value and its decrease (energy concentration towards large events), spatial clustering radius shrinkage and source migration to the predetermined weak surface / stress concentration area, etc.; and combining blasting time period gating (specific denoising and notch filtering are performed within the short blasting time window, and the normal threshold is restored after blasting) and sensor health factors to robustly weight anomalies. The decision is then made through statistical / signal triggering (such as event rate / energy rate crossing the historical P95 threshold and continuing to rise for multiple consecutive sampling steps, significant change point detection, and simultaneous increase in low frequency proportion and average duration), and then compared with the preset threshold to determine whether a time-sensitive disaster is likely to occur.

[0071] In a specific implementation, the specific operation scheme is shown in the following example:

[0072] like Figure 3 , Figure 4 , Figure 5 and Figure 6 As shown in the illustration, this specific embodiment is located in a deep-buried tunnel in southwestern China. The case site is approximately 850m deep, and the surrounding rock is granodiorite, with a relatively intact and hard rock mass. The tunnel adopts a double-line layout and is excavated using the drill-and-blast method. The cross-section is horseshoe-shaped, with dimensions of approximately 10m (width) × 10m (height). The present invention employs a time-delayed rockburst risk area analysis method for drill-and-blast tunnels to identify and predict the time-delayed disaster risk area of ​​this deep-buried tunnel.

[0073] The specific steps are as follows:

[0074] First, the potential time-sensitive hazard risk areas for deeply buried, high-stress hard rock tunnels are identified. Each blasting cycle advance is designated as a risk area identification unit. During tunnel excavation, on-site geological reconnaissance is conducted, recording engineering geological information, excavation and support information, and rockburst information for each blasting cycle, such as... Figure 4 As shown, Figure 4 This is a geological reconnaissance information record form for tunnels constructed using the drill-and-blast method.

[0075] During tunnel excavation, two rows of microseismic sensors were installed 60m and 90m behind the tunnel face to record rock fracture information. As the tunnel excavation progressed, the two rows of sensors moved forward alternately to ensure continuous monitoring. The following data were statistically analyzed within each blasting cycle area throughout the entire excavation process: cumulative number of microseismic events, cumulative microseismic energy release, cumulative microseismic apparent volume, microseismic event rate, microseismic energy release rate, and microseismic apparent volume rate.

[0076] Next, based on the geological reconnaissance information collected for each blasting cycle and the microseismic activity information obtained from microseismic monitoring for each blasting cycle, a mapping relationship between microseismic activity and disaster level is established using a neural network system, as follows: Figure 5 As shown.

[0077] Furthermore, the energy release rate is obtained by dividing the actual disaster level by the microseismic activity mapping level. For blasting cycles with an energy release rate less than 1, areas with potential time-sensitive disaster risk are identified. For example... Figure 3 As shown, blasting cycles 5-10 are potential time-sensitive risk areas.

[0078] Finally, based on the engineering geological and support information collected during the excavation process, through Figure 4 Further analysis of the risk level of potential rockburst hazards was conducted. Geological reconnaissance at the tunnel face revealed that the surrounding rock in the potential risk area was hard, intact, and dry. A set of hard structural surfaces with an angle of less than 30 degrees to the direction of the maximum principal stress existed in the stress concentration area of ​​the right arch shoulder. Rockburst hazards during tunnel construction were predominantly minor; however, to ensure construction safety, moderate rockburst support measures were adopted in this area. These included: anchor bolts, arch frames, and shotcrete. The anchor bolts were hollow grouting anchor bolts with a diameter of 25mm and a length of 3m, spaced 1.5m apart along both the tunnel axial and circumferential directions. The steel arch frames were longitudinally connected using 6mm diameter steel bars, spaced 2m apart along both the tunnel axial and circumferential directions. CF30 high-performance steel fiber reinforced concrete was shotcreted circumferentially onto the tunnel walls, with a shotcrete thickness of 8cm. Figure 3 The risk level of time-sensitive disasters in this potential time-sensitive risk area is assessed as 5, indicating a high risk of time-sensitive disasters.

[0079] This invention, after analyzing the risk level of time-delayed disasters, predicts the occurrence of time-delayed disasters by considering the triggering effect of disturbance factors such as blasting and excavation in drill-and-blast construction on time-delayed rockbursts.

[0080] First, after the excavation of the potential time-sensitive risk area was completed, the tunnel face was approximately 30 meters away from the potential time-sensitive risk area. However, during the blasting at the tunnel face and in adjacent tunnels, numerous microseismic events still occurred in the potential time-sensitive risk area, such as... Figure 5 As shown.

[0081] Then, the risk of imminent time-sensitive disasters in the area was assessed. This was achieved by using Fast Fourier Transform and Hilbert Transform to obtain the frequency spectrum and time-frequency diagram of the vibration waveform. Statistical analysis showed that the dominant frequency of rock mass fracture events in the time-sensitive risk area was mainly concentrated in the 50-150Hz range, and the duration of the vibration waves was mainly 100-150ms. This indicates that the risk area has generated numerous deep macroscopic fractures in the surrounding rock, and the disaster level will be high when time-sensitive failure occurs. Under repeated dynamic disturbances, initial support damage occurred on site, and torsional deformation occurred at the steel frame arch shoulder, such as... Figure 6 As shown.

[0082] This embodiment accurately identified potential time-sensitive risk areas using the surrounding rock energy release index. Furthermore, based on collected engineering geological and support information, it assessed the time-sensitive disaster risk level of these potential risk areas. By further considering the triggering effect of disturbance factors such as blasting excavation during drill-and-blast construction on time-delayed rockbursts, the occurrence of time-sensitive disasters was predicted.

[0083] Example 2:

[0084] like Figure 2 As shown, this embodiment provides a time-delay rockburst risk zone analysis system for drill-and-blast tunnels. See [link to documentation]. Figure 2 The system includes an acquisition unit 701, a hierarchical unit 702, a calculation unit 703, and an analysis unit 704.

[0085] The acquisition unit 701 is used to acquire first information, which includes geological reconnaissance information during the tunnel excavation process and microseismic data information collected by the microseismic monitoring system.

[0086] The grading unit 702 is used to perform actual disaster level analysis and microseismic activity mapping level analysis based on the geological reconnaissance information, and to obtain the actual disaster level and microseismic activity mapping level of all preset tunnel zones;

[0087] The calculation unit 703 is used to calculate the energy release rate based on the actual disaster level and microseismic activity mapping level of all the preset tunnel zones, and to identify potential time-sensitive disaster risk areas based on the calculated energy release rate.

[0088] Analysis unit 704 is used to assess the risk level of potential time-sensitive disaster risk areas based on a preset time-sensitive disaster risk level assessment table, and obtain the time-sensitive disaster risk analysis results for the area.

[0089] It should be noted that the specific methods by which each module performs operations in the system described in the above embodiments have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0090] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0091] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for analyzing time-delay rockburst risk zones in drill-and-blast tunnels, characterized in that, include: Obtain first information, which includes geological reconnaissance information during tunnel excavation and microseismic data collected by the microseismic monitoring system; Based on the geological reconnaissance information, actual disaster level analysis and microseismic activity mapping level analysis are performed to obtain the actual disaster level and microseismic activity mapping level of all preset tunnel zones; Energy release rate is calculated based on the actual disaster level and microseismic activity mapping level of all the preset tunnel zones, and potential time-sensitive disaster risk areas are identified based on the calculated energy release rate. The risk level of potential time-sensitive disaster risk areas is assessed based on a pre-set time-sensitive disaster risk assessment table, and the time-sensitive disaster risk analysis results for the area are obtained. The analysis of actual disaster level and microseismic activity mapping level based on the geological reconnaissance information includes: The geological reconnaissance information is sent to a preset disaster level analysis model for analysis. The energy release of the surrounding rock is calculated based on the initial three-dimensional geostress field and crater volume of the tunnel area in the geological reconnaissance information. The energy release of the surrounding rock is then classified based on the calculated energy release. The energy release of the surrounding rock is further classified based on the analytic hierarchy process (AHP) to obtain the actual disaster level corresponding to each time-sensitive risk area identification unit during the tunnel excavation process. The time-sensitive risk area identification unit is then used as a preset tunnel partition. Based on the microseismic data information, actual disaster level mapping processing is performed. Specifically, a pre-set mapping relationship between pre-set historical microseismic data information and pre-set historical actual disaster levels is learned through a convolutional neural network. The microseismic data information is then output to the learned convolutional neural network to obtain the corresponding microseismic activity mapping level for each pre-set tunnel partition. The energy release rate calculation process, based on the actual disaster level and microseismic activity mapping level of all the preset tunnel zones, includes: Divide the actual disaster level of each tunnel section by the microseismic activity mapping level to obtain the energy release rate of each tunnel section in each blasting cycle. The energy release rate of each tunnel section in each blasting cycle is compared with a preset threshold, and the potential time-sensitive disaster risk area is determined based on the comparison results. Among them, potential time-sensitive disaster risk areas were identified based on the calculated energy release rate, including: The energy release rate of each zone in a single blasting cycle is compared with a preset threshold. If the release rate is higher than or close to 1, it indicates that the microseismic activity has matched the risk level under geological conditions, and the energy of the surrounding rock has been partially released, making the risk relatively controllable in the short term. If the release rate is less than the threshold, it means that there is an energy accumulation but insufficient release in the zone, and the surrounding rock is in a critical or subcritical state, which is very likely to evolve into a time-delay disaster under continuous disturbance.

2. The method for analyzing time-delay rockburst risk zones in drill-and-blast tunnels according to claim 1, characterized in that... Obtain first information, which includes geological reconnaissance information during tunnel excavation and microseismic data collected by the microseismic monitoring system, including: Based on the advance of one blasting cycle during tunnel excavation, at least two time-sensitive risk zone identification units are divided, and the engineering geological information, excavation support information and rock burst information of all time-sensitive risk zones in each blasting cycle are recorded to generate a geological reconnaissance information record table for the drill-and-blast method tunnel. Microseismic sensors are installed at predetermined locations in the tunnel to record microseismic data during the tunnel excavation process. The microseismic data includes the cumulative number of microseismic events, the cumulative microseismic energy release, the cumulative microseismic apparent volume, the microseismic event rate, the microseismic energy release rate, and the microseismic apparent volume rate.

3. The method for analyzing time-delay rockburst risk zones in drill-and-blast tunnels according to claim 1, characterized in that... Based on a pre-set time-sensitive disaster risk assessment table, the risk level of potential time-sensitive disaster risk areas is assessed, resulting in the time-sensitive disaster risk analysis results for that area, including: Based on the engineering geological information and excavation and support information in the geological exploration information of each preset tunnel zone, a time-sensitive disaster risk assessment table is constructed, and the time-sensitive disaster risk level of each potential time-sensitive disaster risk area is determined. If the time-sensitive disaster risk level of the potential time-sensitive disaster risk area is greater than the preset level, then the potential time-sensitive disaster risk area is determined to be a high-risk time-sensitive disaster risk area, and this is taken as the time-sensitive disaster risk analysis result for that area.

4. A time-delay rockburst risk zone analysis system for drill-and-blast tunnels, characterized in that, include: The acquisition unit is used to acquire first information, which includes geological reconnaissance information during the tunnel excavation process and microseismic data information collected by the microseismic monitoring system. The grading unit is used to perform actual disaster level analysis and microseismic activity mapping level analysis based on the geological reconnaissance information, and to obtain the actual disaster level and microseismic activity mapping level of all preset tunnel zones; The calculation unit is used to calculate the energy release rate based on the actual disaster level and microseismic activity mapping level of all the preset tunnel zones, and to identify potential time-sensitive disaster risk areas based on the calculated energy release rate. The analysis unit is used to assess the risk level of potential time-sensitive disaster risk areas based on a preset time-sensitive disaster risk assessment table, and obtain the time-sensitive disaster risk analysis results for the area; The hierarchical unit includes: The first grading subunit is used to send the geological reconnaissance information to a preset disaster level analysis model for analysis. The model calculates the energy release of the surrounding rock based on the initial three-dimensional geostress field and crater volume of the tunnel area in the geological reconnaissance information, and grades the energy release of the surrounding rock based on the calculated energy release. The model also grades the energy release of the surrounding rock based on the analytic hierarchy process (AHP) to obtain the actual disaster level corresponding to each time-sensitive risk area identification unit during the tunnel excavation process, and uses the time-sensitive risk area identification unit as a preset tunnel partition. The second hierarchical subunit is used to perform actual disaster level mapping processing based on the microseismic data information. The mapping relationship between preset historical microseismic data information and preset historical actual disaster levels is learned through a convolutional neural network, and the microseismic data information is output to the learned convolutional neural network to obtain the corresponding microseismic activity mapping level for each preset tunnel partition. The computing unit includes: The first calculation subunit is used to divide the actual disaster level of each tunnel section by the microseismic activity mapping level to obtain the energy release rate of each tunnel section in each blasting cycle. The second calculation subunit is used to compare the energy release rate of each tunnel section in each blasting cycle with a preset threshold, and to determine the potential time-sensitive disaster risk area based on the comparison result. Among them, potential time-sensitive disaster risk areas were identified based on the calculated energy release rate, including: The energy release rate of each zone in a single blasting cycle is compared with a preset threshold. If the release rate is higher than or close to 1, it indicates that the microseismic activity has matched the risk level under geological conditions, and the energy of the surrounding rock has been partially released, making the risk relatively controllable in the short term. If the release rate is less than the threshold, it means that there is an energy accumulation but insufficient release in the zone, and the surrounding rock is in a critical or subcritical state, which is very likely to evolve into a time-delay disaster under continuous disturbance.

5. The time-delay rockburst risk zone analysis system for drill-and-blast tunnels according to claim 4, characterized in that, The acquisition unit includes: The first acquisition subunit is used to divide at least two time-sensitive risk zone identification units based on the advance of one blasting cycle during tunnel excavation, and to record the engineering geological information, excavation support information and rock burst information of all time-sensitive risk zones in each blasting cycle, and generate a geological reconnaissance information record table for the drill-blast method tunnel; The second acquisition subunit is used to set up microseismic sensors at preset locations in the tunnel and record microseismic data information during the tunnel excavation process through the microseismic sensors. The microseismic data information includes the cumulative number of microseismic events, the cumulative microseismic energy release, the cumulative microseismic apparent volume, the microseismic event rate, the microseismic energy release rate, and the microseismic apparent volume rate.

6. The time-delay rockburst risk zone analysis system for drill-and-blast tunnels according to claim 4, characterized in that, The analysis unit includes: The first analysis subunit is used to construct a time-sensitive disaster risk assessment table based on the engineering geological information and excavation support information in the geological exploration information of each preset tunnel zone, and to determine the time-sensitive disaster risk level of each potential time-sensitive disaster risk area; The second analysis subunit is used to determine that the potential time-sensitive disaster risk area is a high-risk time-sensitive disaster risk area if the time-sensitive disaster risk level of the potential time-sensitive disaster risk area is greater than a preset level, and to use it as the time-sensitive disaster risk analysis result corresponding to the area.

Images