A method and system for identifying time-delayed rockburst precursors based on deep-hole sensing

Abstract

This invention discloses a method and system for identifying time-delayed rockburst precursors based on deep-hole sensing. The method includes: drilling monitoring boreholes within the monitoring area of ​​the tunnel surrounding rock; deploying strain sensors and acoustic emission sensors within the monitoring boreholes; acquiring long-term synchronous signals to obtain strain time series and acoustic emission waveform signals at different locations in the deep rock mass, and calculating strain rate and acoustic emission event rate; performing synchronous sliding window analysis on the strain rate and acoustic emission event rate to extract their temporal evolution characteristics; establishing a two-parameter coupled criterion and making a judgment based on the strain rate and acoustic emission event rate; and issuing an early warning when a high-risk precursor is identified. This invention, by directly sensing the deep surrounding rock damage evolution within the rock mass and employing a two-parameter coupled criterion, can accurately identify high-risk precursor characteristics, significantly reduce the false negative rate, provide an early warning window, reserve sufficient time for the implementation of proactive mitigation measures, and effectively reduce the sudden hazards of time-delayed rockbursts.

Description

Technical Field

[0001] This invention patent relates to the field of tunnel engineering safety monitoring technology, specifically to a method and system for identifying time-delayed rockburst precursors based on deep hole sensing. Background Technology

[0002] As infrastructure construction, including transportation, water conservancy, and mining, extends deeper into the earth, tunnel and underground cavern projects in high-stress hard rock environments are increasingly common. In these projects, rockburst, as a major dynamic geological hazard, seriously threatens the lives of construction workers and the stability of the engineering structure. Rockburst refers to the dynamic phenomenon where, under high stress conditions, the elastic strain energy accumulated in the rock mass is suddenly released, causing the rock to burst and eject. Based on the time characteristics of rockburst occurrence, it can be divided into immediate rockbursts and time-delayed rockbursts. Immediate rockbursts typically occur within hours of excavation, with obvious precursory characteristics, making them relatively easy to predict. Time-delayed rockbursts, on the other hand, refer to delayed rockburst disasters that occur suddenly after the surrounding rock has experienced a relatively long "quiet period" (ranging from several days to several months) following tunnel excavation and unloading. Time-delayed rockbursts are characterized by their suddenness, high destructiveness, and difficulty in early warning, making them a key focus and challenge in the safety monitoring of deep engineering projects.

[0003] Existing rockburst monitoring technologies mainly include surface convergence monitoring, multi-point displacement meter monitoring, microseismic monitoring, and acoustic emission monitoring. While these technologies have achieved some success in real-time rockburst early warning, they have significant shortcomings in time-delay rockburst early warning. Traditional monitoring sensors are mostly deployed on the surface of the surrounding rock or in shallow boreholes, making it difficult to directly and effectively perceive stress accumulation and microscopic damage incubation processes within deep rock masses—precisely the source regions of time-delay rockbursts. Secondly, many early warning methods rely on changes in a single physical quantity (such as a surge in acoustic emission activity parameters or an acceleration in displacement rate), but the precursors of time-delay rockbursts often manifest as complex coupled evolution of multiple physical field parameters, making single-parameter criteria prone to missed detections. Therefore, there is an urgent need in this field for a time-delay rockburst precursor identification technology that can directly perceive the evolution of deep surrounding rock damage and integrate multi-parameter coupled criteria to improve the accuracy and lead time of time-delay rockburst early warnings. Summary of the Invention

[0004] This invention addresses the technical problems of existing technologies, such as the inability to effectively perceive the evolution of deep rock mass damage, the easy obscuring of time-delayed rockburst precursor features, and the high false negative rate due to the single criterion dimension. It provides a method and system for identifying time-delayed rockburst precursors based on deep borehole sensing, aiming to achieve accurate and early identification of high-risk time-delayed rockburst precursors through deep collaborative sensing and dual-parameter coupled analysis.

[0005] To achieve the above-mentioned technical objectives, the technical solution adopted by the present invention is as follows: A method for identifying time-delayed rockburst precursors based on deep-hole sensing includes the following steps: S1: Drill monitoring boreholes in the area to be monitored within the tunnel surrounding rock to penetrate deep into the surrounding rock; S2: Strain sensors for monitoring rock strain and acoustic emission sensors for monitoring acoustic emission signals of rock are installed in the monitoring borehole; the strain sensors and acoustic emission sensors are arranged alternately along the depth of the borehole to form a three-dimensional spatial sensing array covering the entire depth of the monitoring borehole. S3: Perform long-term continuous synchronous signal acquisition on the strain sensor and acoustic emission sensor to obtain strain time series and acoustic emission waveform signals at different locations in the deep rock mass, and calculate strain rate and acoustic emission event rate; S4: Perform synchronous sliding window analysis on strain rate and acoustic emission event rate to extract their temporal evolution characteristics, including: strain rate trend determination, to determine whether the strain rate maintains a stable and non-negative overall trend within the sliding time window; acoustic emission abnormal quiet period prolongation determination, to determine whether the acoustic emission event rate shows an abnormal quiet period prolongation phenomenon that is significantly lower than the normal background activity level and lasts for a duration exceeding the preset threshold. S5: Establish a dual-parameter coupled criterion for high-risk precursors of time-delay rockbursts: When the strain rate of a rock mass at a certain depth does not decrease continuously, the acoustic emission event rate shows an abnormally long period of calm at the same time, and the state continues to exceed the preset confirmation period, it is judged as a high-risk precursor of time-delay rockbursts. S6: Tiered Early Warning Issuance: After determining that a time-delayed rockburst is a high-risk precursor, an early warning message is issued.

[0006] Furthermore, the strain sensor adopts a fiber optic strain gauge with a resolution of not less than 1 microstrain and a measurement range of ±10,000 microstrains; the acoustic emission sensor adopts a wideband piezoelectric ceramic probe with a frequency response range of 5kHz to 300kHz and a sensitivity of not less than 60dB.

[0007] Furthermore, the method for determining the strain rate trend is as follows: extract the strain rate of all strain measurement points within the target monitoring area, calculate the regional average strain rate, set a 72-hour sliding time window, perform linear fitting on the average strain rate-time series within each sliding time window, and perform a one-sided t-test on the fitting slope. If the null hypothesis "slope is less than zero" is rejected and the significance level is 0.05, then the slope of the sliding time window period is significantly non-negative, and it is determined that the strain rate continues to decrease.

[0008] Furthermore, the method for determining the extension of the acoustic emission abnormal calm period is as follows: take one month ahead of the sliding time window as the relatively stable period, calculate the mean and standard deviation of the acoustic emission event rate within the relatively stable period, and set the acoustic emission calm discrimination threshold; extract the maximum continuous duration for which the acoustic emission event rate is continuously lower than the discrimination threshold within the current sliding time window, and if the maximum continuous duration is not less than the preset discrimination duration, it is determined that the acoustic emission abnormal calm period is extended.

[0009] Furthermore, the acoustic emission calm discrimination threshold is set as follows: , in, The threshold for determining acoustic emission calmness. μ N and σ N These are the mean and standard deviation of the acoustic emission event rate during the relatively stable period, respectively.

[0010] Furthermore, step S5 also includes locating the space of the hazard source: when the dual-parameter coupling criterion is triggered, the system automatically performs a spatial scan of all measuring points to find the set of measuring points that simultaneously satisfy "non-negative local strain rate" and "prolonged local acoustic emission abnormal calm period", and uses the kernel density estimation method to determine the risk location of high-risk precursors.

[0011] Furthermore, in step S6, issuing the early warning information includes pushing the early warning level, dual-parameter evolution map, and risk location to the on-site management platform in real time, prompting the implementation of risk avoidance or de-stress relief measures.

[0012] Furthermore, step S6 also includes closed-loop management, which involves continuously monitoring the changes in the strain rate parameter and acoustic emission event rate parameter after taking pressure relief and emergency response measures, and automatically adjusting the warning level or canceling the warning based on the monitoring results.

[0013] A system for implementing the time-delay rockburst precursor identification method based on deep hole sensing, comprising: The advanced deep borehole monitoring unit monitors strain sensors and acoustic emission sensors deployed inside the borehole to collect strain and acoustic emission signals from deep rock masses. The data acquisition and transmission unit is used to transmit the signals monitored by the sensors to the data processing and analysis unit in real time. The data processing and analysis unit is used to preprocess the collected strain and acoustic emission signal data, calculate the strain rate and acoustic emission event rate, and perform two-parameter coupling analysis; determine the strain rate trend and the phenomenon of prolonged abnormal quiet period of acoustic emission; based on the two-parameter coupling criterion for high-risk precursors of time-delay rockburst, when the strain rate continues to not decay and the acoustic emission event rate shows an abnormally prolonged quiet period at the same time, it is determined to be a high-risk precursor of time-delay rockburst. The early warning issuance and management unit is connected to the data processing and analysis unit and is used to generate and issue graded early warning information based on the dual-parameter coupling criterion.

[0014] Furthermore, when the data processing and analysis unit performs dual-parameter coupled analysis, it adopts a 72-hour sliding time window with a window step size of 1 hour, and continuously calculates the strain rate trend and acoustic emission calm time within the window. When both meet the criterion conditions and the preset confirmation period is continuously maintained, an early warning signal is sent to the early warning release and management unit.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention integrates acoustic emission sensors and strain sensors and deploys them inside deep monitoring boreholes, enabling direct and real-time monitoring of micro-fracture activity and stress field adjustment processes in deep rock masses. This solves the problem that traditional surface and shallow hole (≤5 meters) monitoring methods cannot cover deep rockburst incubation areas.

[0016] This invention establishes a dual-parameter coupled criterion of strain rate and acoustic emission event rate to identify the core precursor characteristics of time-delayed rockbursts: "continuous stress accumulation and abnormally reduced micro-fracture activity." Compared to traditional methods that rely on a single parameter, the dual-parameter coupled criterion has higher identification accuracy and can significantly reduce the missed detection rate, lowering the missed detection rate of time-delayed rockbursts from over 70% to below 10%. It can identify high-risk precursors 7 to 15 days before a rockburst occurs, with an early warning window 3 to 10 times earlier than traditional monitoring methods. This allows sufficient time for the implementation of proactive mitigation measures such as deep-hole stress-relief blasting and high-pressure hydraulic fracturing, effectively reducing the sudden hazards of time-delayed rockbursts.

[0017] This invention not only provides early warning of risks but also precisely locates the spatial position of risk sources, offering accurate target guidance for subsequent pressure relief and mitigation measures. Employing a combination of fiber optic strain gauges and broadband acoustic emission probes, it features resistance to electromagnetic interference, high stress, moisture, and long-term stability, enabling continuous operation for over six months in complex tunnel construction environments. Furthermore, the advanced deep-boring construction technology is compatible with existing tunnel construction processes, sensor deployment is simple, and data processing and early warning processes are fully automated, requiring minimal manual intervention. It can be widely applied to various high-stress hard rock tunnels, deep mines, and other engineering projects. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, 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 this application and should not be regarded as a limitation of 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 flowchart illustrating the method of the present invention; Figure 2 This is a flowchart of the two-parameter coupling feature analysis in this invention; Figure 3 This is a schematic diagram of the system of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0021] A time-delay rockburst precursor identification method based on deep hole sensing, such as Figure 1 , Figure 2 As shown, it includes the following steps: S1: In the area to be monitored in the surrounding rock of the tunnel, drilling monitoring boreholes to penetrate deep into the surrounding rock; specifically, in front of the tunnel face or outside the excavation outline, advanced monitoring boreholes with a depth of 15 to 30 meters are drilled, with a borehole diameter of 75 to 110 mm, and the borehole direction is perpendicular to the tunnel axis or points towards the stress concentration area, depending on the geological conditions and monitoring purpose.

[0022] S2: Strain sensors for monitoring rock mass strain and acoustic emission sensors for monitoring rock mass acoustic emission signals are installed in the advanced monitoring borehole. The strain sensors and acoustic emission sensors form an integrated sensing chain. The strain sensors and acoustic emission sensors are arranged alternately along the borehole depth with a spacing of 1 to 2 meters, forming a three-dimensional spatial sensing array covering the entire monitoring borehole depth. The strain sensor employs a fiber optic grating (FBG) strain gauge with a resolution of at least 1 microstrain and a measurement range of ±10,000 microstrains. It features advantages such as resistance to electromagnetic interference, high stress resistance, and good long-term stability. The acoustic emission sensor uses a wideband piezoelectric ceramic probe with a frequency response range of 5kHz to 300kHz and a sensitivity of at least 60dB, effectively capturing weak elastic wave signals generated by micro-fractures within the rock mass.

[0023] S3: 24-hour long-term, continuous signal acquisition of strain sensors and acoustic emission sensors is conducted through downhole data acquisition substations to obtain strain time series at different locations in the deep rock mass. Based on the high-frequency acoustic emission waveform signal, calculate the following two core monitoring parameters: strain rate Acoustic emission event rate .

[0024] S4: Strain rate Harmony emission event rate Perform synchronous sliding window analysis to extract its temporal evolution characteristics; including: S4a: Strain Rate Trend Determination: Judging Strain Rate Whether the overall trend of change remains stable and non-negative within the sliding time window, and whether there are statistical signs of convergence towards creep decay, i.e. whether it maintains a "continuous non-decaying" state; The method for determining the strain rate trend specifically involves: extracting the strain rate of all strain measurement points within the target monitoring area and calculating the average strain rate of the area. A 72-hour sliding time window was set, and linear fitting was performed on the average strain rate-time series within each sliding time window. And perform a one-sided t-test on the fitted slope k. If the null hypothesis "the slope is less than zero" is true, then... k The value <0) was rejected, and the significance level was set to 0.05, which proves that the strain rate during the sliding time window is significantly non-negative. k If the value is ≥0, the strain rate is determined to be continuously undiminished.

[0025] S4b: Determination of prolonged abnormal quiet period in acoustic emission: Determine whether the acoustic emission event rate is significantly lower than the normal background activity level and the duration exceeds the preset threshold for prolonged abnormal quiet period. Determining the acoustic emission event rate The question asks whether an "abnormally calm" characteristic exists, meaning that the current acoustic emission event rate is significantly lower than the normal background activity level, and this low-activity state is maintained for a period exceeding the normal fluctuation cycle, exhibiting an "abnormally prolonged calm period." The specific method for determining the prolonged abnormally calm period of acoustic emission is as follows: First, take one month forward from the sliding time window as the relatively stable period, and calculate the average acoustic emission event rate during the relatively stable period. μ N and standard deviation σ N Set the acoustic emission calm discrimination threshold Then, within the current sliding time window, the acoustic emission event rate is continuously lower than the discrimination threshold. For the maximum continuous duration If the maximum continuous duration If the time is not less than the preset judgment time (e.g., 12 hours), it is determined to be an extended period of abnormal acoustic emission calm.

[0026] S5: Establish a dual-parameter coupled criterion for high-risk precursors of time-delay rockbursts; when the strain rate of a rock mass at a certain depth does not decrease continuously, the acoustic emission event rate shows an abnormally long period of calm at the same time, and the state continues to exceed the preset confirmation period (e.g., 3 hours), it is determined to be a high-risk precursor of time-delay rockbursts; setting a preset confirmation period can effectively filter out interference caused by short-term fluctuations or data noise, avoid false alarms, and improve the reliability of early warning.

[0027] It also includes locating the spatial source of danger: when the dual-parameter coupling criterion is triggered, the system automatically performs a spatial scan of all measuring points to find the set of measuring points that simultaneously satisfy "non-negative local strain rate" and "prolonged local acoustic emission abnormal quiet period". The system uses the spatial coordinates of these measuring points to estimate the kernel density, and the density peak area is the most likely location of the earthquake core area, i.e. the risk location of high-risk precursor.

[0028] S6: Tiered Early Warning Issuance: After determining that a time-delayed rockburst is a high-risk precursor, an early warning message is issued.

[0029] The warning information, including the warning level, dual-parameter evolution map, and risk location (corresponding to the borehole depth range), is pushed to the on-site management platform in real time, prompting decision-makers to take immediate risk avoidance or pressure relief measures.

[0030] It also includes closed-loop management steps. After the hazard relief work is carried out, the system continues to monitor changes in the two parameters and automatically adjusts the warning level or cancels the warning based on the monitoring results. After the pressure relief measures are taken, the changes in the strain rate parameter and acoustic emission event rate parameter are continuously monitored. If the strain rate decreases significantly and acoustic emission activity recovers, the warning is automatically downgraded or canceled; if the strain rate continues to rise and acoustic emission remains abnormally quiet, it indicates that the danger has intensified and the response needs to be upgraded.

[0031] This invention also provides a dynamic inversion system for the rheological parameters of the surrounding rock of deep-buried tunnels to implement the above-mentioned method, such as... Figure 3 As shown, it includes an advanced deep borehole monitoring unit, a data acquisition and transmission unit, a data processing and analysis unit, and an early warning release and management unit.

[0032] The advanced deep borehole monitoring unit is equipped with strain sensors and acoustic emission sensors inside the monitoring borehole to collect strain and acoustic emission signals from deep rock masses.

[0033] The data acquisition and transmission unit is responsible for transmitting the signals monitored by the sensors to the data processing and analysis unit in real time via optical fiber or wireless transmission.

[0034] The data processing and analysis unit is used to preprocess the collected strain and acoustic emission signal data, calculate the strain rate and acoustic emission event rate, and perform two-parameter coupling analysis; it determines the strain rate trend and the phenomenon of prolonged abnormal quiet period of acoustic emission. Based on the two-parameter coupling criterion for high-risk precursors of time-delay rockburst, when the strain rate does not decrease continuously and the acoustic emission event rate shows an abnormally prolonged quiet period at the same time, it is determined to be a high-risk precursor of time-delay rockburst. Specifically, when the data processing and analysis unit performs two-parameter coupling analysis, it adopts a 72-hour sliding time window with a window step size of 1 hour, and continuously calculates the strain rate trend and acoustic emission quiet duration within the window. When both simultaneously meet the criterion conditions and a preset confirmation period is continuously established, an early warning signal is sent to the early warning release and management unit.

[0035] The early warning release and management unit is connected to the data processing and analysis unit and is used to generate and release graded early warning information based on the dual-parameter coupling criterion.

[0036] Furthermore, it also includes a database and visualization unit for storing historical monitoring data and early warning records, and providing data query, playback and visualization functions.

[0037] The following is a specific experimental example: A time-delay rockburst precursor identification method based on deep hole sensing, such as Figure 1 , Figure 2 As shown, it includes the following steps: S1: Within the monitoring area of ​​the tunnel surrounding rock, drilling monitoring boreholes will be carried out to penetrate deep into the surrounding rock. One set of advanced monitoring boreholes will be constructed on each of the left and right sidewalls of the tunnel face (1.5m above the floor slab). An XY-2PC geological drilling rig with diamond drill bits will be used. The borehole diameter will be 90mm, the depth 25m, the borehole direction perpendicular to the tunnel axis, the inclination angle consistent with the designed longitudinal slope, and the deviation rate controlled within ±1°. After drilling, a 0.6~0.8MPa high-pressure air system will be used to clean the entire borehole, removing rock dust, accumulated water, and loose rock fragments to ensure the integrity of the borehole wall.

[0038] S2: Integrated Sensor Chain Installation and Coupling. A modular integrated sensor chain is deployed within the borehole, consisting of fiber optic grating (FBG) strain gauges and broadband piezoelectric ceramic acoustic emission probes connected in series. Sensor parameters: FBG strain gauge resolution 0.5 microstrain, measurement range ±15000 microstrain, temperature self-compensation; acoustic emission probe frequency response 10kHz~200kHz, sensitivity 65dB, built-in preamplifier. Ten strain gauges and nine acoustic emission probes are deployed at 1.5m intervals, forming a 0~25m full-hole depth sensing array. P.O42.5 grade micro-expansion cement grout is used for full-hole backfilling, with a water-cement ratio of 0.45~0.55 and a grouting pressure of 0.3~0.5MPa. Data acquisition is initiated after a 24-hour settling period to allow the cement grout to initially set. Grouting tightly couples the strain and acoustic emission sensors to the surrounding rock mass, ensuring that the sensors can accurately and realistically respond to the stress, strain, and micro-fracture activity of the rock mass, providing the foundation for obtaining high-quality monitoring data.

[0039] S3: Multi-parameter continuous acquisition and preprocessing. 24-hour uninterrupted synchronous acquisition is performed using an explosion-proof downhole data acquisition substation. Strain data sampling frequency is 1Hz, with an accuracy of ±0.1 microstrain; acoustic emission data sampling frequency is 1MHz, A / D conversion accuracy is 16 bits, and trigger threshold is 40dB (relative to 1V / μbar). The acquisition substation has a built-in 8GB cache, capable of storing at least 72 hours of data during network interruption, with automatic retransmission upon recovery. After wavelet denoising, outlier removal, and timestamp alignment, the raw data is used to calculate the instantaneous strain rate (microstrain / hour) and hourly acoustic emission event rate (times / hour) for each measuring point in real time.

[0040] S4: Two-parameter synchronous sliding window feature extraction. Time series analysis is performed using a 72-hour sliding time window and a 1-hour step size. S4a: Strain Rate Trend Determination. The average strain rate of 10 strain measurement points in the target area is extracted, and the slope k is obtained by linear fitting using the least squares method. A one-sided t-test is then performed on the slope (significance level α = 0.05). If the null hypothesis "slope less than zero" is rejected (p < 0.05), the strain rate is determined to be continuously constant.

[0041] S4b: Determination of prolonged acoustic emission anomalies and quiet periods. Take stable monitoring data for 30 days prior to the sliding window (excluding periods of construction interference such as blasting and muck removal), and calculate the average acoustic emission event rate. μ and standard deviation σ The acoustic emission calm discrimination threshold is defined as follows: In this embodiment μ =120 times / hour σ=30 times / hour, therefore the calming threshold is 60 times / hour. The maximum consecutive duration for which the event rate within the current window is continuously below the discrimination threshold is counted. If the maximum consecutive duration is ≥24 hours, an abnormally prolonged calming period is determined.

[0042] S5: Dual-parameter coupling criterion and hazard source location. A time-delay type high-risk rockburst precursor dual-parameter coupling criterion is established: when a rock mass at a certain depth simultaneously satisfies the conditions of continuous non-decaying strain rate and prolonged abnormal acoustic emission quiet period, and the state persists for more than a 3-hour confirmation cycle, an early warning is triggered. After the criterion is triggered, the system automatically scans all 19 measuring points, selects the set of measuring points that simultaneously meet the conditions, uses a Gaussian kernel function for kernel density estimation, and determines the bandwidth using cross-validation. The density peak area is the seismogenic core area. In this embodiment, 5 measuring points at depths of 12-18m are selected, and the seismogenic core area is determined to be located at a depth of 15m.

[0043] S6: Graded Early Warning Issuance and Closed-Loop Management. Upon determining a high-risk precursor to a time-delayed rockburst, the system automatically generates an early warning message including the warning level, risk location, dual-parameter evolution map, and recommended measures. This message is disseminated through multiple channels, including audible and visual alarms, SMS push notifications, and web platform pop-ups. In this embodiment, the criteria are met continuously for 4.5 hours to trigger a red, extremely high-risk warning. After implementing deep-hole stress-relief blasting (hole depth 20m, hole diameter 75mm, maximum single-section charge 0.5kg), the system continuously monitors the dual parameters: if the strain rate slope k < 0 and p < 0.05 within a 72-hour window, and acoustic emission recovers to ≥ 60 times / hour, the warning is automatically downgraded to yellow and lifted after 24 hours without abnormalities; if the parameters do not improve or even worsen, the warning is upgraded to a special level and the personnel evacuation plan is activated.

[0044] Of course, the present invention may have other various embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art can make various corresponding changes and modifications according to the present invention, but these corresponding changes and modifications should all fall within the protection scope of the appended claims.

Claims

1. A method for identifying time-delayed rockburst precursors based on deep-hole sensing, characterized in that, Includes the following steps: S1: Drill monitoring boreholes in the area to be monitored within the tunnel surrounding rock to penetrate deep into the surrounding rock; S2: Strain sensors for monitoring rock strain and acoustic emission sensors for monitoring acoustic emission signals of rock are installed in the monitoring borehole; the strain sensors and acoustic emission sensors are arranged alternately along the depth of the borehole to form a three-dimensional spatial sensing array covering the entire depth of the monitoring borehole. S3: Perform long-term continuous synchronous signal acquisition on the strain sensor and acoustic emission sensor to obtain strain time series and acoustic emission waveform signals at different locations in the deep rock mass, and calculate strain rate and acoustic emission event rate; S4: Perform synchronous sliding window analysis on strain rate and acoustic emission event rate to extract their temporal evolution characteristics, including: strain rate trend determination, to determine whether the strain rate maintains a stable and non-negative overall trend within the sliding time window; acoustic emission abnormal quiet period prolongation determination, to determine whether the acoustic emission event rate shows an abnormal quiet period prolongation phenomenon that is significantly lower than the normal background activity level and lasts for a duration exceeding the preset threshold. S5: Establish a dual-parameter coupled criterion for high-risk precursors of time-delay rockbursts: When the strain rate of a rock mass at a certain depth does not decrease continuously, the acoustic emission event rate shows an abnormally long period of calm at the same time, and the state continues to exceed the preset confirmation period, it is judged as a high-risk precursor of time-delay rockbursts. S6: Tiered Early Warning Issuance: After determining that a time-delayed rockburst is a high-risk precursor, an early warning message is issued.

2. The method for identifying time-delay rockburst precursors based on deep-hole sensing according to claim 1, characterized in that, The strain sensor is a fiber optic strain gauge with a resolution of not less than 1 microstrain and a measurement range of ±10,000 microstrains; the acoustic emission sensor is a wideband piezoelectric ceramic probe with a frequency response range of 5 kHz to 300 kHz and a sensitivity of not less than 60 dB.

3. The method for identifying time-delayed rockburst precursors based on deep-hole sensing according to claim 1, characterized in that, The method for determining the strain rate trend is as follows: extract the strain rate of all strain measurement points within the target monitoring area, calculate the regional average strain rate, set a 72-hour sliding time window, perform linear fitting on the average strain rate-time series within each sliding time window, and perform a one-sided t-test on the fitting slope. If the null hypothesis "slope is less than zero" is rejected and the significance level is set to 0.05, then the slope of the sliding time window is significantly non-negative, and the strain rate is determined to be continuously non-decreasing.

4. The method for identifying time-delayed rockburst precursors based on deep-hole sensing according to claim 1, characterized in that, The method for determining the extension of the abnormal quiet period of acoustic emission is as follows: take one month ahead of the sliding time window as the relatively stable period, calculate the mean and standard deviation of the acoustic emission event rate within the relatively stable period, and set the acoustic emission quiet period discrimination threshold; extract the maximum continuous duration for which the acoustic emission event rate is continuously lower than the discrimination threshold within the current sliding time window, and if the maximum continuous duration is not less than the preset discrimination duration, it is determined that the abnormal quiet period of acoustic emission is extended.

5. The method for identifying time-delayed rockburst precursors based on deep-hole sensing according to claim 4, characterized in that, The acoustic emission calm discrimination threshold is set as follows: ， in, The threshold for determining acoustic emission calmness. μ N and σ N These are the mean and standard deviation of the acoustic emission event rate during the relatively stable period, respectively.

6. The method for identifying time-delayed rockburst precursors based on deep-hole sensing according to claim 1, characterized in that, Step S5 also includes locating the space of the hazard source: when the dual-parameter coupling criterion is triggered, the system automatically performs a spatial scan of all measuring points to find the set of measuring points that simultaneously satisfy "non-negative local strain rate" and "prolonged local acoustic emission abnormal quiet period", and uses the kernel density estimation method to determine the risk location of high-risk precursors.

7. The method for identifying time-delayed rockburst precursors based on deep-hole sensing according to claim 6, characterized in that, In step S6, issuing the early warning information includes pushing the early warning level, dual-parameter evolution map and risk location to the on-site management platform in real time, prompting the implementation of risk avoidance or de-stress relief measures.

8. The method for identifying time-delayed rockburst precursors based on deep-hole sensing according to claim 7, characterized in that, Step S6 also includes closed-loop management, which involves continuously monitoring the changes in the strain rate parameter and acoustic emission event rate parameter after taking pressure relief and emergency response measures, and automatically adjusting the warning level or canceling the warning based on the monitoring results.

9. A system for implementing the time-delay rockburst precursor identification method based on deep hole sensing as described in any one of claims 1 to 8, characterized in that, include: The advanced deep borehole monitoring unit monitors strain sensors and acoustic emission sensors deployed inside the borehole to collect strain and acoustic emission signals from deep rock masses. The data acquisition and transmission unit is used to transmit the signals monitored by the sensors to the data processing and analysis unit in real time. The data processing and analysis unit is used to preprocess the collected strain and acoustic emission signal data, calculate the strain rate and acoustic emission event rate, and perform two-parameter coupling analysis; determine the strain rate trend and the phenomenon of prolonged abnormal quiet period of acoustic emission; based on the two-parameter coupling criterion for high-risk precursors of time-delay rockburst, when the strain rate continues to not decay and the acoustic emission event rate shows an abnormally prolonged quiet period at the same time, it is determined to be a high-risk precursor of time-delay rockburst. The early warning issuance and management unit is connected to the data processing and analysis unit and is used to generate and issue graded early warning information based on the dual-parameter coupling criterion.

10. The system according to claim 9, characterized in that: When the data processing and analysis unit performs dual-parameter coupled analysis, it adopts a 72-hour sliding time window with a window step size of 1 hour. It continuously calculates the strain rate trend and acoustic emission calm time within the window. When both meet the criterion conditions and the preset confirmation period is continuously maintained, it sends an early warning signal to the early warning release and management unit.

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