A method for early warning of rock burst of engineering rock mass surrounding rock based on laser ultrasound

Abstract

The application discloses a kind of engineering rock mass surrounding rock rock burst early warning method based on laser ultrasound, belongs to surrounding rock monitoring technical field.It is characterized by comprising the following steps: step 1, the sound velocity-stress correlation model of rock sample is established;Step 2, laser ultrasound inspection device is arranged in surrounding rock;Step 3, laser ultrasound inspection device reciprocating operation along the trend of surrounding rock, and the inspection data is obtained in real time;Step 4, the inspection data obtained in real time by step 3, and the sound velocity-stress correlation model established in step 1 is combined, and the classification warning of rock burst disaster is carried out to surrounding rock.In the technical scheme of the present application, by laser ultrasound non-contact monitoring, without drilling implantation equipment, the original stress field of surrounding rock can be completely reserved, and the "stress drop process" is used as the core index of early warning, which can improve the advance amount of rock burst early warning, reserve sufficient time for on-site personnel evacuation and equipment protection, and significantly reduce rock burst disaster loss.

Description

Technical Field

[0001] A method for early warning of rockburst in engineering rock mass based on laser ultrasound belongs to the field of surrounding rock monitoring technology. Background Technology

[0002] In underground engineering fields such as mining and tunnel construction, rockburst is a typical sudden geological disaster. Essentially, it occurs when the surrounding rock of a tunnel, under high stress, experiences a sudden release of energy, leading to rock mass fracturing and ejection. This can cause damage to the tunnel support structure, or even result in casualties and work stoppages. Therefore, monitoring rockburst hazards is crucial. Current technologies for monitoring rockburst hazards mainly include the following: Option 1: Stress-based monitoring scheme. This method utilizes stress sensors (such as fiber optic strain gauges and resistance strain gauges) to monitor the stress in the surrounding rock, thereby enabling further monitoring of rockbursts. This is exemplified by the technical solution described in Chinese invention patent application number 202210788830.X, filed on July 6, 2022, entitled "A Deformation Measurement and Early Warning System and Method for Deep-Buried Tunnels Crossing Active Faults." The drawbacks of stress-based monitoring schemes are: they require drilling into the surrounding rock, which not only disrupts the original stress field of the rock mass, leading to distorted monitoring data, but also makes them prone to damage under high stress and strong vibration environments, resulting in short lifespans and difficulty in achieving long-term stable monitoring. More importantly, these technologies generally use the "peak stress of the surrounding rock" as the rockburst threshold—ignoring the crucial precursor of "rapid stress decline from the peak value" before a rockburst occurs. When micro-cracks expand within the surrounding rock, stress has already begun to slowly release. By the time the stress peak is detected, the rock mass is often close to a critical instability state, resulting in insufficient early warning and a high risk of missed detections.

[0003] Option 2: Non-stress monitoring solution. This approach utilizes non-stress technologies such as microseismic monitoring and infrared thermography. While it doesn't require damaging the rock mass, its monitoring logic is to "indirectly capture signals associated with rockbursts." Microseismic monitoring primarily captures vibration waves generated by rock fractures, but it cannot predict the initial stage of stress reduction from stability. Infrared thermography relies on temperature changes caused by frictional heating of the rock mass before a rockburst, and is greatly affected by tunnel ventilation and ambient temperature, making it almost impossible to trigger an early warning in low-stress-release-rate scenarios (such as slow micro-crack propagation). Although non-stress technologies can capture vibration signals or temperature changes before and after a rockburst, they cannot directly monitor the dynamic evolution of surrounding rock stress, resulting in insufficient early warning lead time, low accuracy, cumbersome analysis, and difficulty in meeting engineering emergency needs.

[0004] In addition to the above-mentioned technical solutions, some new monitoring solutions have also emerged in the existing technology, such as: Option 3: Rockburst monitoring based on 3D models. Examples include the technical solutions described in Chinese invention patent application number 202310893419.3 (filed July 19, 2023), entitled "A Method and System for Monitoring Rockburst Process Based on a 3D Model," and Chinese invention patent application number 202510590653.8 (filed May 8, 2025), entitled "Dynamic Detection Device for the Loosening Zone of Surrounding Rock in Semi-coal-rock Roadways Based on 3D Laser Scanning." These options obtain a 3D model of the monitored object (such as a tunnel or roadway) through scanning or other methods, and then monitor rockbursts based on the deformation of the 3D model.

[0005] Option 4: A scheme using sound waves as the monitoring indicator. For example, the technical solution described in Chinese invention patent application number 202510485853.7, filed on April 17, 2025, entitled "A Method, Device, Equipment and Medium for Monitoring Deformation in Coal Mine Roadways," uses sound wave data as the monitoring indicator. By acquiring sound wave data and combining it with image recognition technology, the maximum width and depth of the crack are determined. Then, based on the maximum depth and width of the crack, it is determined whether deformation alarm information needs to be generated, enabling more timely identification of potential safety risks.

[0006] However, existing technologies, including all the above-mentioned solutions, still tend to overlook the monitoring of the specific precursor indicator of the "stress reduction process" of the surrounding rock before rockburst occurs during actual implementation. Therefore, it is still difficult to predict rockburst disasters in advance during actual implementation, and thus cannot provide sufficient time for on-site personnel evacuation and equipment protection, posing significant safety hazards. Summary of the Invention

[0007] The technical problem to be solved by this invention is to overcome the shortcomings of the prior art and provide a laser-ultrasound-based method for early warning of rockbursts in engineering rock masses. This method uses non-contact monitoring with laser ultrasound, requires no drilling or implantation of equipment, can completely preserve the original stress field of the surrounding rock, and uses the "stress reduction process" as the core indicator for early warning. This method can improve the advance warning of rockbursts, allow sufficient time for on-site personnel evacuation and equipment protection, and significantly reduce the losses caused by rockburst disasters.

[0008] The technical solution adopted by this invention to solve its technical problem is: a method for early warning of rockburst in engineering rock mass based on laser ultrasound, characterized by including the following steps: Step 1: Establish a sound velocity-stress correlation model for the rock sample. The sound velocity-stress correlation model includes the wave velocity-stress calibration curve of the rock sample, as well as the stress-wave velocity formula for the rock sample under different stresses at various stages. Step 2: Deploy a laser ultrasonic inspection device in the surrounding rock; Step 3: The laser ultrasonic inspection device reciprocates along the direction of the surrounding rock to inspect the surrounding rock and obtain inspection data in real time. Step 4: Using the inspection data obtained in real time in Step 3, and combined with the sound velocity-stress correlation model established in Step 1, a graded early warning of rockburst disaster is carried out on the surrounding rock.

[0009] Preferably, step 1 includes the following steps: Step 1-1: Collect rock samples from the surrounding rock of the roadway to be monitored; Steps 1-2: Fix the rock sample on the pressure platen of the press, and place the transmitter and receiver of the laser ultrasonic system on the same side of the rock sample to form a same-side excitation-reception optical path; Steps 1-3: Using a fixed pressure as the step size, apply stress to the rock sample in stages using a pressure machine, start the laser ultrasonic system, measure the surface wave propagation time using the laser ultrasonic system, calculate the corresponding wave velocity, establish the "wave velocity-stress" calibration curve of the current rock sample, and record the rock sample's critical plastic stress, ultimate stress, and critical stress at instability. Steps 1-4 determine the stress-wave velocity formulas for rock samples at different stages after being subjected to pressure.

[0010] Preferably, in steps 1-4, the stress-wave velocity formula for the rock sample includes: Formula 1: Stress-wave velocity formula for rock samples before reaching the elastic limit after compression: Formula 2: Stress-wave velocity formula for rock samples under compression from critical plastic stress to ultimate stress: Formula 3: Stress-wave velocity formula for rock samples under compression from ultimate stress to critical stress: in: v z This represents the Rayleigh wave velocity when a rock is under stress. v 0 represents the initial Rayleigh wave velocity when the rock is stress-free. v 1 represents the wave velocity at the elastic limit. v 2 represents the wave velocity at the ultimate stress; σ Indicates the stress on the rock. k Indicates the stress wave velocity coefficient of rock. φ Indicates rock porosity. D Indicates the damage coefficient. σ j This represents the stress value corresponding to the elastic limit. σ max This represents the stress value corresponding to the ultimate stress.

[0011] Preferably, the laser ultrasonic inspection device in step 2 includes: a guide rail arranged on the surrounding rock wall, and an inspection vehicle that moves back and forth along the guide rail. An inspection system is installed in the inspection vehicle. The inspection system includes a main controller and a laser ultrasonic system connected to the main controller. The transmitting end and receiving end of the laser ultrasonic system face the rock wall.

[0012] Preferably, the inspection vehicle has a groove on its side, a guide rail is located in the groove, and slots are provided on the upper and lower surfaces of the guide rail. A pulley is provided in the groove of the inspection vehicle and is respectively engaged with the upper and lower slots, wherein at least one pulley is a drive wheel.

[0013] Preferably, several monitoring points are set at intervals on the rock wall, and an RFID card is set at each monitoring point. An RFID card reader connected to the main controller is set in the inspection system.

[0014] Preferably, in step 4, a three-level early warning threshold is set based on the rock's critical stress, ultimate stress, and critical stress, and corrected according to field measurements: Level 1 Warning: The monitored stress has not decreased and has reached the critical stress or the stress shows a non-continuous decrease, with a stress decrease rate of <-0.5%; Level 2 Warning: The monitored stress has not decreased and has reached the ultimate stress or the stress begins to show a continuous decrease, with a stress decrease rate of <-5%; Level 3 Warning: The monitored stress has decreased and is approaching the critical stress or the stress continues to decrease.

[0015] Compared with the prior art, the beneficial effects of this invention are: In the laser ultrasound-based early warning method for rockburst in engineering rock mass, the non-contact monitoring using laser ultrasound eliminates the need for drilling and equipment insertion, thus preserving the original stress field of the surrounding rock. Furthermore, by using the "stress reduction process" as the core indicator for early warning, the advance warning time for rockburst can be increased, allowing sufficient time for on-site personnel evacuation and equipment protection, and significantly reducing the losses caused by rockburst disasters.

[0016] The technical solution of this application breaks through the inherent logic of the traditional stress-related technology "stress peak warning" and establishes for the first time a quantitative correlation model of "laser ultrasonic velocity change - surrounding rock stress decrease - rockburst risk level". This realizes the technological leap from "passively capturing stress peak" to "actively predicting the initial stage of stress instability". Moreover, the laser ultrasonic equipment adopts a modular design, which is suitable for narrow spaces and high dust environments in tunnels. It can realize distributed inspection along the tunnel axis, filling the application gap of non-contact stress dynamic monitoring in the field of underground engineering. Compared to microseismic monitoring, which "can only capture vibration signals," and infrared monitoring, which "can only sense temperature changes," the technical solution in this application directly monitors the "core driving factor of rockburst—stress," eliminating the need to infer risk through indirect signals. Its monitoring accuracy and early warning lead time are significantly superior to these two non-stress-based technologies. Compared to traditional stress sensors, the laser ultrasonic module used in this technology is reusable, reducing long-term monitoring costs by more than 60%. Furthermore, equipment deployment requires no downtime and can be completed during normal tunnel excavation, significantly reducing project downtime losses. Attached Figure Description

[0017] Figure 1 This is a flowchart of a method for early warning of rockburst in engineering rock mass based on laser ultrasound.

[0018] Figure 2 This is a schematic diagram of the laser ultrasonic inspection device layout.

[0019] Figure 3 for Figure 2 Sectional view along line AA.

[0020] Figure 4 This is a block diagram illustrating the principle of a laser ultrasonic inspection device.

[0021] The components include: 1. Surrounding rock; 2. Monitoring point; 3. Guide rail; 4. Inspection vehicle; 5. Fixing frame. Detailed Implementation

[0022] Figures 1-3 This is the preferred embodiment of the present invention, which is described below in conjunction with the accompanying drawings. Figures 1-3 The present invention will be further described below.

[0023] like Figure 1 As shown, a method for early warning of rockburst in engineering rock mass based on laser ultrasound includes the following steps: Step 1: Establish a sound velocity-stress correlation model for the rock sample; Step 1 includes the following steps: Step 1-1: Collect rock core samples (rock samples) from the surrounding rock of the roadway to be monitored. The rock sample dimensions are 50mm in diameter × 100mm in height. Ensure that the rock sample lithology is consistent with the site conditions and that there are no cracks or weathering defects. Then, place the rock sample in a drying oven (60℃, 24h) to remove moisture and avoid the moisture content affecting the sound velocity measurement.

[0024] Steps 1-2: Construct the "press-laser ultrasonic system" test platform: Fix the rock sample on the press platform, and place the transmitter and receiver of the laser ultrasonic system on the same side of the rock sample with a fixed distance of 5-10 cm to form a same-side excitation-reception optical path.

[0025] Steps 1-3 involve applying stress to the rock sample in 5 MPa increments using a pressure machine. After the sample stabilizes for one minute at each pressure level, a laser ultrasonic system is activated to measure the surface wave propagation time. This process is repeated three times at each pressure level, and the average value is calculated to determine the corresponding wave velocity. A wave velocity-stress calibration curve for the current rock sample is established using data fitting. Simultaneously, the critical plastic stress, ultimate stress, and critical stress at instability of the rock sample are recorded.

[0026] Steps 1-4: Based on the experiment, determine the stress-wave velocity formula for the rock sample at different stages after compression: The stress-wave velocity formula for rock samples includes: Formula 1: Stress-wave velocity formula for rock samples before reaching the elastic limit after compression: in, v z Rayleigh wave velocity (m / s) represents the stress on a rock. v 0 represents the initial Rayleigh wave velocity (m / s) when the rock is stress-free. σ This indicates the stress (Pa) experienced by the rock. k This represents the stress wave velocity coefficient (Pa⁻¹) of the rock. φ This indicates the porosity of the rock.

[0027] Formula 2: Stress-wave velocity formula for rock samples under compression from critical plastic stress to ultimate stress: in, v z Rayleigh wave velocity (m / s) represents the rock under stress. v 1 represents the wave velocity (m / s) at the elastic limit. D Indicates the damage coefficient; σ This indicates the stress (Pa) experienced by the rock. σ j This represents the stress value (Pa) corresponding to the elastic limit.

[0028] Formula 3: Stress-wave velocity formula for rock samples under compression from ultimate stress to critical stress: in, v z Rayleigh wave velocity (m / s) represents the stress on a rock. v 2 represents the wave velocity (m / s) at the ultimate stress. n This represents the post-peak stress-wave velocity attenuation index; σ This indicates the stress (Pa) experienced by the rock. σ maxThis represents the stress value (Pa) corresponding to the ultimate stress.

[0029] Step 2: Deploy a laser ultrasonic inspection device in the surrounding rock; An inspection system should be deployed in areas of stress concentration in the surrounding rock mass of the engineering project (such as the middle of the roadway sidewalls and roadway intersections). Combined with... Figures 2-3 The laser ultrasonic inspection device includes several fixed frames 5 arranged at intervals along the rock wall of the surrounding rock 1. All fixed frames 5 are arranged at the same height, and the interval between the fixed frames 5 is 2-3m. Guide rails 3 are arranged on the sides of all fixed frames 5, and inspection vehicles 4 are clamped on the guide rails 3. The inspection vehicles 4 move back and forth along the guide rails 3, and limit devices are set at both ends of the guide rails 3 to prevent the inspection vehicles 4 from detaching from the guide rails 3.

[0030] Slots are formed on the upper and lower surfaces of the guide rail 3, and a groove is formed on the side of the inspection vehicle 4. The guide rail 3 is entirely placed within the groove on the side of the inspection vehicle 4. Rollers are respectively installed at the upper and lower parts of the groove on the side of the inspection vehicle 4, and the upper and lower rollers are respectively engaged in the upper and lower slots of the guide rail 3, thus achieving a locking connection between the inspection vehicle 4 and the guide rail 3. Of the two rollers engaged with the guide rail 3, one is a drive roller, allowing the inspection vehicle 4 to move along the guide rail 3.

[0031] On the rock face of the surrounding rock 1, several monitoring points 2 are set at intervals along the direction of the guide rail 3. The interval between monitoring points 2 is 5-10m, and the interval is increased to 3-5m in the stress concentration zone. An RFID tag is set at each monitoring point 2, and each RFID tag records the information of the monitoring point 2, including but not limited to the monitoring point number. The inspection vehicle 4 faces the end face of the rock face of the surrounding rock 1, and the distance between the inspection vehicle 4 and the rock face is less than 0.4m. That is, when the inspection vehicle 4 moves to a certain monitoring point 2, the distance between it and the monitoring point 2 is less than 0.4m.

[0032] An inspection system is installed inside the inspection vehicle 4, such as... Figure 4 As shown, the inspection system includes a main controller, which is connected to the laser ultrasonic system. An RFID reader and a temperature sensor are installed at the input port of the main controller. The output of the main controller is connected to a drive motor. The motor shaft of the drive motor (through a reducer) is connected to the drive wheel of the two pulleys mentioned above. A wireless communication module is also connected to the input and output of the main controller.

[0033] The transmitter and receiver of the laser ultrasonic system are arranged in the inspection vehicle 4 according to the test platform arrangement of "press machine-laser ultrasonic system" in step 1, that is, the transmitter and receiver are arranged at a distance of 5~10cm, and the optical path is adjusted to focus the laser on the surface of the surrounding rock 1 (the spot diameter is ≤2mm); the module is equipped with a double-layer dustproof coated lens (transmittance ≥98%).

[0034] To facilitate data transmission, wireless transmission repeaters are also installed on the rock face. These repeaters are connected to the wireless communication module inside the inspection vehicle 4 to enable wireless data transmission.

[0035] Step 3: Dynamically monitor the stress of the surrounding rock using a laser ultrasonic inspection system; The main controller inside the inspection vehicle 4 controls the drive motor to work, so that the inspection vehicle 4 moves back and forth along the guide rail 3 to collect data at each monitoring point 2, thereby completing the inspection of the surrounding rock 1.

[0036] When the inspection vehicle 4 moves to a monitoring point 2, the main controller reads the data from the RFID card at monitoring point 2 via the radio frequency reader and records the current status. Then, the main controller controls the drive motor to stop rotating, thereby stopping the inspection vehicle 4. At this time, the main controller controls the laser ultrasonic system to start, and the transmitter of the laser ultrasonic system sends signals to the rock wall three times in succession, while the receiver receives the returned signals.

[0037] After the main controller calculates the average value of the signal received by the receiver, it saves the corresponding monitoring data locally and uploads it to the ground workstation via the wireless communication module.

[0038] During the monitoring of monitoring point 2, the inspection vehicle 4, after moving to a certain monitoring point 2, records the monitoring time and ambient temperature (±2℃) in addition to recording the number of monitoring point 2.

[0039] Step 4: Data processing and graded early warning and emergency response for rockburst disasters; After receiving the data sent by the inspection vehicle 4, the workstation first verifies the data's integrity. If any data is missing, it supplements the missing data using the local data stored in the inspection vehicle 4. The workstation first preprocesses the raw wave velocity data—using wavelet threshold filtering to remove mechanical vibration noise below 1kHz. Then, it uses a temperature compensation algorithm to correct the effect of ambient temperature on sound velocity (the sound velocity correction is ±20m / s for every 5℃ temperature change). The stress value corresponding to the surrounding rock 1 is obtained from the wave velocity-stress calibration curve obtained in step 1. The real-time stress value and stress change rate are calculated to determine the corresponding stress-wave velocity formula.

[0040] The workstation determines the rockburst classification warning and emergency response for surrounding rock 1 based on the corresponding stress-wave velocity formula: The workstation sets three warning thresholds based on laboratory tests of rock's critical stress, ultimate stress, and minimum stress, and with corrections made according to field measurements: Level 1 Warning: The monitored stress has not decreased and has reached the critical stress or the stress shows a non-continuous decrease, with a stress decrease rate of <-0.5%; Level 2 Warning: The monitored stress has not decreased and has reached the ultimate stress or the stress begins to show a continuous decrease, with a stress decrease rate of <-5%; Level 3 Warning: The monitored stress has decreased and is approaching the critical stress or the stress continues to decrease. The aforementioned work of obtaining the stress value corresponding to the surrounding rock 1 through the "wave velocity-stress" calibration curve, determining the corresponding stress-wave velocity formula, and further determining the corresponding pre-tightening level can also be completed by the main controller of the inspection system. Furthermore, when the warning level of the surrounding rock 1 reaches the corresponding level, an early warning is triggered: the main controller sends a warning signal to the ground dispatch center via the wireless module—for a Level 1 warning, a "strengthen inspection" command is pushed; for a Level 2 warning, the power supply to the equipment in the warning area is automatically cut off, and non-essential personnel are notified to evacuate; for a Level 3 warning, the audible and visual alarm system in the warning area is activated, the ventilation equipment in the emergency shelter is triggered, and the stress data for the last 10 minutes is stored for subsequent analysis. Step 5: System maintenance, data updates, and intelligent prediction; The maintenance steps include the following: 5-1 Regular maintenance: Clean the dust on the surface of the laser probe every 7 days and check the alignment of the optical path; calibrate the "wave velocity-stress" curve once a month, correct the stress-wave velocity formula for the corresponding stage, and verify the accuracy of the data through the on-site benchmark monitoring point (the stable section without stress change). 5-2 Data Update: Every 3 months, based on field rockburst cases (if they occur) or stress monitoring data, optimize the early warning threshold parameters and revise the stress-wave velocity formula for the corresponding stage to ensure that the model adapts to the dynamic changes in the stress evolution law of the surrounding rock. 5-3 Intelligent Prediction: Using the "stress-wave velocity" time series data, surrounding rock stress monitoring data, and rockburst cases (if any) obtained during regular maintenance and data update phases as core samples, an AI prediction model adapted to the evolution of surrounding rock stress in mines is constructed. The model uses a long short-term memory network (LSTM) to adapt to the time series evolution characteristics of stress-wave velocity data and capture the long-term dependence of surrounding rock stress from stability to abrupt change.

[0041] A random forest (RF) model was introduced to correct the LSTM prediction results and reduce the error of a single model. The training set, validation set and test set were divided in a 7:2:1 ratio. The model parameters (such as the number of hidden layer nodes and the number of iterations of LSTM, and the number of decision trees of RF) were optimized with the goal of minimizing the mean square error (MSE) between the predicted stress value and the measured value. The basic accuracy of the model was verified by stable segment data from field benchmark monitoring points.

[0042] The AI ​​prediction results are compared with the field measured data (regularly maintained wave velocity-stress calibration values) every week. If the prediction error exceeds 5%, the model is automatically fine-tuned (the latest data is added and the local parameters are retrained). The prediction results are incorporated into the "wave velocity-stress" curve calibration process every month to correct the model input feature weights and ensure that the prediction accuracy is adapted to the dynamic changes of the surrounding rock. Every 3 months, the model is fully iterated once, combining the latest rockburst cases, stress monitoring data and early warning and disposal effects.

[0043] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for early warning of rockburst in engineering rock masses based on laser ultrasound, characterized in that: Includes the following steps: Step 1: Establish a sound velocity-stress correlation model for the rock sample. The sound velocity-stress correlation model includes the "wave velocity-stress" calibration curve of the rock sample, as well as the stress-wave velocity formulas for the rock sample under different stresses at various stages. Step 2: Deploy a laser ultrasonic inspection device in the surrounding rock; Step 3: The laser ultrasonic inspection device reciprocates along the direction of the surrounding rock to inspect the surrounding rock and obtain inspection data in real time. Step 4: Using the inspection data obtained in real time in Step 3, and combined with the sound velocity-stress correlation model established in Step 1, a graded early warning of rockburst disaster is carried out on the surrounding rock.

2. The method for early warning of rockburst in engineering rock mass based on laser ultrasound according to claim 1, characterized in that: Step 1 includes the following steps: Step 1-1: Collect rock samples from the surrounding rock of the roadway to be monitored; Steps 1-2: Fix the rock sample on the pressure platen of the press, and place the transmitter and receiver of the laser ultrasonic system on the same side of the rock sample to form a same-side excitation-reception optical path; Steps 1-3: Using a fixed pressure as the step size, apply stress to the rock sample in stages using a pressure machine, start the laser ultrasonic system, measure the surface wave propagation time using the laser ultrasonic system, calculate the corresponding wave velocity, establish the "wave velocity-stress" calibration curve of the current rock sample, and record the rock sample's critical plastic stress, ultimate stress, and critical stress at instability. Steps 1-4 determine the stress-wave velocity formulas for rock samples at different stages after being subjected to pressure.

3. The method for early warning of rockburst in engineering rock mass based on laser ultrasound according to claim 2, characterized in that: In steps 1-4, the stress-wave velocity formula for the rock sample includes: Formula 1: Stress-wave velocity formula for rock samples before reaching the elastic limit after compression: Formula 2: Stress-wave velocity formula for rock samples under compression from critical plastic stress to ultimate stress: Formula 3: Stress-wave velocity formula for rock samples under compression from ultimate stress to critical stress: in: v z This represents the Rayleigh wave velocity when a rock is under stress. v 0 represents the initial Rayleigh wave velocity when the rock is stress-free. v 1 represents the wave velocity at the elastic limit. v 2 represents the wave velocity at the ultimate stress; σ Indicates the stress on the rock. k Indicates the stress wave velocity coefficient of rock. φ Indicates rock porosity. D Indicates the damage coefficient. σ j This represents the stress value corresponding to the elastic limit. σ max This represents the stress value corresponding to the ultimate stress.

4. The method for early warning of rockburst in engineering rock mass based on laser ultrasound according to claim 1, characterized in that: The laser ultrasonic inspection device in step 2 includes: a guide rail (3) arranged on the rock wall of the surrounding rock (1), and an inspection vehicle (4) that moves back and forth along the guide rail (3). An inspection system is set in the inspection vehicle (4). The inspection system includes a main controller and a laser ultrasonic system connected to the main controller. The transmitting end and receiving end of the laser ultrasonic system face the rock wall.

5. The method for early warning of rockburst in engineering rock mass based on laser ultrasound according to claim 4, characterized in that: The inspection vehicle (4) has a groove on its side, and the guide rail (3) is located in the groove. The upper and lower surfaces of the guide rail (3) are provided with slots. The groove of the inspection vehicle (4) is provided with pulleys that are respectively engaged with the upper and lower slots, and at least one of the pulleys is a drive wheel.

6. The method for early warning of rockburst in engineering rock mass based on laser ultrasound according to claim 4, characterized in that: Several monitoring points (2) are set at intervals on the rock wall. An RFID card is set at each monitoring point (2). An RFID card reader connected to the main controller is set in the inspection system.

7. The method for early warning of rockburst in engineering rock mass based on laser ultrasound according to claim 2, characterized in that: In step 4, based on the rock's critical stress, ultimate stress, and critical stress, and after correction according to field measurements, a three-level early warning threshold is set: Level 1 Warning: The monitored stress has not decreased and has reached the critical plastic stress, or the stress shows a non-continuous decrease, with a stress decrease rate of <-0.5%; Level 2 warning: The monitored stress has not decreased and has reached the limit stress, or the stress has begun to show a continuous decrease, with a stress decrease rate of <-5%; Level 3 warning: The stress detected by the survey decreases and approaches the critical stress or the stress continues to decrease.

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