A method and system for rapid identification of risk areas on rock slopes

Abstract

This invention discloses a method and system for rapid identification of risk areas on rock slopes, belonging to the field of rock slope engineering monitoring and geological disaster early warning technology. The method includes: a model construction stage, constructing a three-dimensional point cloud model of the original rock surface of a steep rock slope based on UAV oblique photography and three-dimensional laser scanning; a preliminary risk zone delineation stage, delineating preliminary risk zones on the original rock surface based on the three-dimensional point cloud model; a system deployment stage, deploying a slope microseismic monitoring system according to the preliminary risk zones before slope excavation; a risk level evaluation stage, using joint spacing and the moment magnitude of microseismic events as preliminary evaluation indicators to delineate slope excavation risk areas and evaluate risk levels; and a risk verification stage, issuing early warnings based on risk levels, verifying risk levels using in-depth evaluation indicators, and dynamically delineating the final risk area range through multi-source parameters. This invention can dynamically and rapidly identify risk areas on rock slopes in real time as excavation progresses.

Description

Technical Field

[0001] This invention relates to the field of rock slope engineering monitoring and geological disaster early warning technology, and in particular to a method and system for rapid identification of risk areas on rock slopes. Background Technology

[0002] Existing risk area identification methods rely on limited monitoring tools: manual surveys and total station displacement monitoring are insufficient to simultaneously capture internal rock mass damage (such as micro-fractures) and geological changes at the excavation face (such as structural surface development), resulting in incomplete information. Furthermore, the methods lack timeliness: traditional approaches, based on "static prediction + post-construction verification," are ill-suited to address dynamic deformation and damage to slopes during construction, leading to delayed risk identification. Finally, multi-source data integration is lacking: technologies such as UAV oblique photography, 3D laser scanning, and microseismic monitoring are used independently, failing to form a closed-loop system of "modeling-monitoring-analysis-early warning," thus undermining the full potential of the data. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a method and system for rapid identification of risk areas on rock slopes. By constructing a three-dimensional model that integrates multi-source data, the original rock surface characteristics of the rock slope are accurately restored; a dynamic monitoring mechanism for the entire construction process is established, covering "pre-excavation planning → in-excavation monitoring → rapid risk assessment"; and through multi-parameter coupling analysis, the accuracy and reliability of risk area identification are improved, providing real-time support for construction safety decisions.

[0004] The objective of this invention is achieved through the following technical solution: The first aspect of this invention provides a method for rapid identification of risk areas on rock slopes, comprising the following steps:

[0005] In the model building phase, a three-dimensional point cloud model of the original rock surface of a steep rock slope is constructed based on UAV oblique photography and three-dimensional laser scanning.

[0006] In the preliminary risk zone delineation stage, the preliminary risk zone of the original rock surface is delineated based on the three-dimensional point cloud model. The distance between adjacent joints is determined by the geometric shape of the collected point cloud data, and the area where the distance between joints is less than the preset distance is delineated as the preliminary risk zone.

[0007] During the system deployment phase, before slope excavation, a slope microseismic monitoring system is deployed based on the preliminary risk zone.

[0008] During the risk level assessment phase, the internal damage of the rock mass is monitored in real time through a microseismic monitoring system during the slope excavation process, and the geological conditions of the rock excavation face are monitored simultaneously through three-dimensional laser scanning. Based on the internal damage of the rock mass and the geological conditions of the rock excavation face, multi-source parameters are collected, and the joint spacing and the moment magnitude of the microseismic events are used as preliminary evaluation indicators to delineate the slope excavation risk area and evaluate the risk level.

[0009] During the risk verification phase, early warnings are issued based on the risk level. Joint length, microseismic event b-value, and the number of microseismic events per day are used as in-depth evaluation indicators to verify the risk level. Finally, the risk area is dynamically divided through multi-source parameters.

[0010] Preferably, the model building stage further includes the following steps:

[0011] Multi-view images of the slope were obtained by using drone oblique photography to extract the macroscopic morphology. Then, point cloud data was collected using 3D laser scanning to capture details of the rock surface, joint distribution, and structural surface orientation, thereby constructing a 3D point cloud model of the original rock surface of the steep rock slope.

[0012] Preferably, the preset spacing is 1m, and the spacing between adjacent joints is obtained by observing the joint distribution on the original rock surface through a three-dimensional point cloud model.

[0013] Preferably, the system deployment phase further includes the following steps:

[0014] Based on the preliminary risk zone, microseismic sensors are deployed in the failure-sensitive sections inside the rock mass to cover the preliminary risk zone and collect microseismic signals within the preliminary risk zone.

[0015] Preferably, the risk level assessment stage further includes the following steps:

[0016] The initial risk area is monitored in two dimensions: internal damage monitoring and external damage monitoring.

[0017] The internal damage monitoring includes the following steps: using a slope microseismic monitoring system to collect rock mass microfracture signals in real time to obtain the moment magnitude of microseismic events, and classifying the potential location and scale of rock mass damage according to the magnitude of the moment magnitude;

[0018] The external damage monitoring includes the following steps: obtaining the joint spacing of the excavation face through three-dimensional laser scanning;

[0019] Then, a risk assessment model based on internal loss and surface geology is constructed to delineate risk areas for slope excavation and evaluate the risk level.

[0020] Preferably, the analysis is performed on areas with a moment magnitude greater than 1. If the joint spacing in the target area is less than 0.5m and the moment magnitude of the microseismic events collected in the target area is greater than 1, then the preliminary evaluation indicators are considered to be abnormal.

[0021] If the joint spacing in the target area is greater than 0.5m and less than 1m and the moment magnitude of the microseismic events collected in the target area is greater than 1, or if the joint spacing in the target area is less than 0.5m and the moment magnitude of the microseismic events collected in the target area is greater than 0 and less than 1, then it is considered an anomaly of one of the preliminary evaluation indicators.

[0022] If the joint spacing in the target area is greater than 0.5m and less than 1m, and the moment magnitude of the microseismic events collected in the target area is greater than 0 and less than 1, then the target area is considered to be without anomalies.

[0023] For areas where all preliminary evaluation indicators are abnormal or one of the preliminary evaluation indicators is abnormal, in-depth analysis is conducted using advanced evaluation indicators. Areas with joint lengths greater than 5m, microseismic events greater than 15 per day, and microseismic event b-values ​​less than 1 with a continuous decline are identified as abnormal. If all preliminary evaluation indicators are abnormal and 2 to 3 advanced evaluation indicators are abnormal, the area is classified as a Level I warning area. If all preliminary evaluation indicators are abnormal and one advanced evaluation indicator is abnormal, or if one preliminary evaluation indicator is abnormal and 2 to 3 advanced evaluation indicators are abnormal, the area is classified as a Level II warning area. If one preliminary evaluation indicator is abnormal and one advanced evaluation indicator is abnormal, the area is classified as a Level III warning area.

[0024] Preferably, the risk verification stage further includes the following steps:

[0025] By incorporating surface displacement, rock mass stress, and groundwater level data, a multi-parameter coupling algorithm is used to dynamically adjust the final risk area range and provide graded early warnings.

[0026] A second aspect of the present invention provides: a rapid risk area identification system for rock slopes, used to implement the rapid risk area identification method for any of the above-mentioned rock slopes, comprising the following steps:

[0027] The model building module is used to construct a 3D point cloud model of the original rock surface of a steep rock slope based on UAV oblique photography and 3D laser scanning.

[0028] The preliminary risk zone delineation module is used to delineate the preliminary risk zone of the original rock surface based on the three-dimensional point cloud model. It determines the distance between adjacent joints by the geometric shape of the collected point cloud data and delineates the area where there are joints with a distance smaller than the preset distance as the preliminary risk zone.

[0029] The system deployment module is used to deploy the slope microseismic monitoring system according to the preliminary risk zone before slope excavation;

[0030] The risk level assessment module is used to monitor the internal damage of the rock mass in real time through a microseismic monitoring system during slope excavation, and to simultaneously monitor the geological conditions of the rock mass excavation face through three-dimensional laser scanning. Based on the internal damage of the rock mass and the geological conditions of the rock mass excavation face, multi-source parameters are collected, and the joint spacing and the moment magnitude of the microseismic event are used as preliminary evaluation indicators to delineate the risk areas of slope excavation and evaluate the risk level.

[0031] The risk verification module is used to issue early warnings based on risk levels. It uses joint length, microseismic event b-value, and the number of microseismic events per day as in-depth evaluation indicators to verify risk levels, and dynamically divides the final risk area range through multi-source parameters.

[0032] The beneficial effects of this invention are:

[0033] 1) It can dynamically and rapidly identify risk areas of rock slopes in real time as excavation progresses. Through a combination of qualitative and quantitative methods, the risk areas of rock slopes are quickly determined. This invention utilizes a macroscopic approach, employing oblique photography by UAVs and 3D laser scanning to construct a 3D point cloud model of the original rock surface of steep rock slopes. Based on this high-precision model, risk areas are initially identified. Then, full-area microseismic monitoring is conducted on these identified risk areas. By analyzing the characteristics of the microseismic events obtained from the monitoring, the location of potential risk areas is continuously narrowed down. Finally, in-depth analysis and multi-source parameter integration are used to further determine the location of risk areas and classify them into risk levels, thus enabling rapid identification of risk areas on rock slopes. Attached Figure Description

[0034] Figure 1 This is a flowchart of the method of the present invention;

[0035] Figure 2 This is a diagram illustrating the layout of the microseismic monitoring system.

[0036] Figure 3 Flowchart for risk level assessment;

[0037] In the figure, 1. The monitored slope; 2. The acceleration sensor of the microseismic monitoring system; 2-1, 2-2, 2-3, 2-4, 2-5 and 2-6 are sensor numbers; 3. Grouting tunnel; 4. Risk area detection range; 5. Data acquisition device; 6. Signal processing system; 7. Wireless transmitter; 8. Computer; 9. Initial risk area. Detailed Implementation

[0038] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] See Figures 1-3 The first aspect of this invention provides a method for rapid identification of risk areas on rock slopes, comprising the following steps:

[0040] In the model building phase, a three-dimensional point cloud model of the original rock surface of a steep rock slope is constructed based on UAV oblique photography and three-dimensional laser scanning.

[0041] In the preliminary risk zone delineation stage, the preliminary risk zone of the original rock surface is delineated based on the three-dimensional point cloud model. The distance between adjacent joints is determined by the geometric shape of the collected point cloud data, and the area where the distance between joints is less than the preset distance is delineated as the preliminary risk zone.

[0042] During the system deployment phase, before slope excavation, a slope microseismic monitoring system is deployed based on the preliminary risk zone.

[0043] During the risk level assessment phase, the internal damage of the rock mass is monitored in real time through a microseismic monitoring system during the slope excavation process, and the geological conditions of the rock excavation face are monitored simultaneously through three-dimensional laser scanning. Based on the internal damage of the rock mass and the geological conditions of the rock excavation face, multi-source parameters are collected, and the joint spacing and the moment magnitude of the microseismic events are used as preliminary evaluation indicators to delineate the slope excavation risk area and evaluate the risk level.

[0044] During the risk verification phase, early warnings are issued based on the risk level. Joint length, microseismic event b-value, and the number of microseismic events per day are used as in-depth evaluation indicators to verify the risk level. Finally, the risk area is dynamically divided through multi-source parameters.

[0045] In some embodiments, the model building phase further includes the following steps:

[0046] Multi-view images of the slope were obtained by using drone oblique photography to extract the macroscopic morphology. Then, point cloud data was collected using 3D laser scanning to capture details of the rock surface, joint distribution, and structural surface orientation, thereby constructing a 3D point cloud model of the original rock surface of the steep rock slope.

[0047] In this embodiment, UAV oblique photography technology is used to acquire multi-view images of the slope and extract its macroscopic shape;

[0048] Four fixed-point 3D laser scanners were placed around the slope to scan point cloud data of the slope. The coordinate system of the point cloud data from the on-site scan was converted to the geodetic coordinate system, allowing the point cloud data from different coordinate systems to be stitched together. Noise was removed from the point cloud data to improve data accuracy and make the geometric shape of the point cloud data more precise, thereby improving the visualization effect of the 3D model. The noise-reduced point cloud data was then stitched together to form a complete 3D point cloud model of the original rock surface of the steep rock slope.

[0049] In some embodiments, the preset spacing is 1m, and the spacing between adjacent joints is obtained by observing the joint distribution on the original rock surface through a three-dimensional point cloud model.

[0050] In this embodiment, the distribution of joints on the original rock surface is observed based on a three-dimensional point cloud model. The distance between joints is used as a criterion to initially divide the risk area of ​​the original rock surface. Areas where the measured joint distance is less than 1m are classified as preliminary risk areas.

[0051] In some embodiments, the system deployment phase further includes the following steps:

[0052] Based on the preliminary risk zone, microseismic sensors are deployed in the failure-sensitive sections inside the rock mass to cover the preliminary risk zone and collect microseismic signals within the preliminary risk zone.

[0053] In this embodiment, based on the preliminary risk zone, microseismic sensors are deployed in the fault-sensitive sections inside the rock mass, such as... Figure 2 As shown, sensors are deployed to monitor the slope for microseismic activity, ensuring that the monitoring range covers the risk area. Microseismic signals within the risk area are collected, and the collected signals are stored in a processor via a data acquisition unit. Then, the signals are transmitted to a computer system via a wireless transmitter. The system focuses on processing or calculating the moment magnitude, number, and b-value of the collected microseismic signals.

[0054] In some embodiments, the risk level assessment stage further includes the following steps:

[0055] The initial risk area is monitored in two dimensions: internal damage monitoring and external damage monitoring.

[0056] The internal damage monitoring includes the following steps: using a slope microseismic monitoring system to collect rock mass microfracture signals in real time to obtain the moment magnitude of microseismic events, and classifying the potential location and scale of rock mass damage according to the magnitude of the moment magnitude;

[0057] The external damage monitoring includes the following steps: obtaining the joint spacing of the excavation face through three-dimensional laser scanning;

[0058] Then, a risk assessment model based on internal loss and surface geology is constructed to delineate risk areas for slope excavation and evaluate the risk level.

[0059] In this embodiment, during the excavation process, the initially delineated risk zones on the original rock surface are monitored in two dimensions: internal damage monitoring, where a microseismic system collects real-time signals of microfractures in the rock mass, and the potential location and scale of rock mass damage are delineated based on the magnitude of the collected microseismic events, and the risk level is evaluated; and geological monitoring of the excavation face, where three-dimensional laser scanning obtains information such as the joint spacing of the excavation face for analysis and evaluation of the risk level; and a risk assessment model of "internal damage + surface geology" is constructed, integrating indicators such as the b-value of microseismic events, the number of microseismic events, and the joint length of the excavation face, to quickly delineate risk areas and evaluate risk levels within minutes.

[0060] In some embodiments, the region with a moment magnitude greater than 1 is analyzed. If the joint spacing in the target region is less than 0.5m and the moment magnitude of the microseismic events collected in the target region is greater than 1, then the preliminary evaluation indicators are considered to be abnormal.

[0061] If the joint spacing in the target area is greater than 0.5m and less than 1m and the moment magnitude of the microseismic events collected in the target area is greater than 1, or if the joint spacing in the target area is less than 0.5m and the moment magnitude of the microseismic events collected in the target area is greater than 0 and less than 1, then it is considered an anomaly of one of the preliminary evaluation indicators.

[0062] If the joint spacing in the target area is greater than 0.5m and less than 1m, and the moment magnitude of the microseismic events collected in the target area is greater than 0 and less than 1, then the target area is considered to be without anomalies.

[0063] For areas where all preliminary evaluation indicators are abnormal or one of the preliminary evaluation indicators is abnormal, in-depth analysis is conducted using advanced evaluation indicators. Areas with joint lengths greater than 5m, microseismic events greater than 15 per day, and microseismic event b-values ​​less than 1 with a continuous decline are identified as abnormal. If all preliminary evaluation indicators are abnormal and 2 to 3 advanced evaluation indicators are abnormal, the area is classified as a Level I warning area. If all preliminary evaluation indicators are abnormal and one advanced evaluation indicator is abnormal, or if one preliminary evaluation indicator is abnormal and 2 to 3 advanced evaluation indicators are abnormal, the area is classified as a Level II warning area. If one preliminary evaluation indicator is abnormal and one advanced evaluation indicator is abnormal, the area is classified as a Level III warning area.

[0064] In this embodiment, microseismic monitoring was conducted in areas with joint spacing less than 0.5m and areas with joint spacing greater than 0.5m but less than 1m, respectively. The moment magnitudes of the obtained microseismic data were analyzed, and data with moment magnitudes greater than 1.0 were given priority for analysis. For areas without abnormalities, support was provided to minimize construction disturbance.

[0065] The formula for calculating the B value is: ,in M The magnitude of the earthquake; Based on magnitude M The small interval centered The number of earthquakes that occur within a certain period; a b is a constant. a The b-value represents the level of seismic activity within a statistical timeframe and region, and is a function representing the relative magnitude distribution of microseismic events.

[0066] Corresponding follow-up construction recommendations are proposed for different warning areas: Level I warning area: construction is suspended and personnel and equipment are evacuated; Level II warning area: excavation is suspended and protective measures are strengthened; Level III warning area: the excavation construction progress is slowed down.

[0067] In some embodiments, the risk verification phase further includes the following steps:

[0068] By incorporating surface displacement, rock mass stress, and groundwater level data, a multi-parameter coupling algorithm is used to dynamically adjust the final risk area range and provide graded early warnings.

[0069] In this embodiment, data such as surface displacement (inclinometer), rock mass stress (strain gauge), and groundwater level are introduced. The risk area boundary is dynamically adjusted through a multi-parameter coupling algorithm to solve the "false judgment / missed judgment" problem of single monitoring and improve the identification accuracy. The adjusted risk area is then given a graded warning (audio-visual alarm, mobile push notification).

[0070] A second aspect of the present invention provides: a rapid risk area identification system for rock slopes, used to implement the rapid risk area identification method for any of the above-mentioned rock slopes, comprising the following steps:

[0071] The model building module is used to construct a 3D point cloud model of the original rock surface of a steep rock slope based on UAV oblique photography and 3D laser scanning.

[0072] The preliminary risk zone delineation module is used to delineate the preliminary risk zone of the original rock surface based on the three-dimensional point cloud model. It determines the distance between adjacent joints by the geometric shape of the collected point cloud data and delineates the area where there are joints with a distance smaller than the preset distance as the preliminary risk zone.

[0073] The system deployment module is used to deploy the slope microseismic monitoring system according to the preliminary risk zone before slope excavation;

[0074] The risk level assessment module is used to monitor the internal damage of the rock mass in real time through a microseismic monitoring system during slope excavation, and to simultaneously monitor the geological conditions of the rock mass excavation face through three-dimensional laser scanning. Based on the internal damage of the rock mass and the geological conditions of the rock mass excavation face, multi-source parameters are collected, and the joint spacing and the moment magnitude of the microseismic event are used as preliminary evaluation indicators to delineate the risk areas of slope excavation and evaluate the risk level.

[0075] The risk verification module is used to issue early warnings based on risk levels. It uses joint length, microseismic event b-value, and the number of microseismic events per day as in-depth evaluation indicators to verify risk levels, and dynamically divides the final risk area range through multi-source parameters.

[0076] The above description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the concept described herein through the above teachings or related technologies or knowledge. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. A method for rapid identification of risk areas on rock slopes, characterized in that: Includes the following steps: In the model building phase, a three-dimensional point cloud model of the original rock surface of a steep rock slope is constructed based on UAV oblique photography and three-dimensional laser scanning. In the preliminary risk zone delineation stage, the preliminary risk zone of the original rock surface is delineated based on the three-dimensional point cloud model. The distance between adjacent joints is determined by the geometric shape of the collected point cloud data, and the area where the distance between joints is less than the preset distance is delineated as the preliminary risk zone. During the system deployment phase, before slope excavation, a slope microseismic monitoring system is deployed based on the preliminary risk zone. During the risk level assessment phase, the internal damage of the rock mass is monitored in real time through a microseismic monitoring system during the slope excavation process, and the geological conditions of the rock excavation face are monitored simultaneously through three-dimensional laser scanning. Based on the internal damage of the rock mass and the geological conditions of the rock excavation face, multi-source parameters are collected, and the joint spacing and the moment magnitude of the microseismic events are used as preliminary evaluation indicators to delineate the slope excavation risk area and evaluate the risk level. During the risk verification phase, early warnings are issued based on the risk level. Joint length, microseismic event b-value, and the number of microseismic events per day are used as in-depth evaluation indicators to verify the risk level. The final risk area is dynamically divided through multi-source parameters. The model building phase also includes the following steps: Multi-view images of the slope were obtained by using drone oblique photography to extract the macroscopic morphology, and point cloud data was collected by using 3D laser scanning to capture rock surface details, joint distribution and structural surface attitude, thereby constructing a 3D point cloud model of the original rock surface of the steep rock slope. The system deployment phase also includes the following steps: Based on the preliminary risk zone, microseismic sensors are deployed in the failure-sensitive section inside the rock mass to cover the preliminary risk zone and collect microseismic signals within the preliminary risk zone. The risk level assessment stage also includes the following steps: The initial risk area is monitored in two dimensions: internal damage monitoring and external damage monitoring. The internal damage monitoring includes the following steps: using a slope microseismic monitoring system to collect rock mass microfracture signals in real time to obtain the moment magnitude of microseismic events, and classifying the potential location and scale of rock mass damage according to the magnitude of the moment magnitude; The external damage monitoring includes the following steps: obtaining the joint spacing of the excavation face through three-dimensional laser scanning; Then, a risk assessment model based on internal loss and surface geology is constructed to delineate the risk zones of slope excavation and evaluate the risk level. The risk verification phase also includes the following steps: By incorporating surface displacement, rock mass stress, and groundwater level data, a multi-parameter coupling algorithm is used to dynamically adjust the final risk area range and provide graded early warnings.

2. The method for rapid identification of risk areas on rock slopes according to claim 1, characterized in that: The preset spacing is 1m. The distribution of joints on the original rock surface is observed through a three-dimensional point cloud model to obtain the spacing between adjacent joints.

3. The method for rapid identification of risk areas on rock slopes according to claim 1, characterized in that: For areas with a moment magnitude greater than 1, if the joint spacing in the target area is less than 0.5m and the moment magnitude of the microseismic events collected in the target area is greater than 1, then the preliminary evaluation indicators are considered to be abnormal. If the joint spacing in the target area is greater than 0.5m and less than 1m and the moment magnitude of the microseismic events collected in the target area is greater than 1, or if the joint spacing in the target area is less than 0.5m and the moment magnitude of the microseismic events collected in the target area is greater than 0 and less than 1, then it is considered an anomaly of one of the preliminary evaluation indicators. If the joint spacing in the target area is greater than 0.5m and less than 1m, and the moment magnitude of the microseismic events collected in the target area is greater than 0 and less than 1, then the target area is considered to be without anomalies. For areas where all preliminary evaluation indicators are abnormal or one of the preliminary evaluation indicators is abnormal, in-depth analysis is conducted through in-depth evaluation indicators. Areas with joint length greater than 5m, number of microseismic events greater than 15 per day, and microseismic event b-value less than 1 and continuously decreasing are identified as abnormal. If all preliminary evaluation indicators are abnormal and 2 to 3 in-depth evaluation indicators are abnormal, the area is classified as a Level I warning area; if all preliminary evaluation indicators are abnormal and 1 in-depth evaluation indicator is abnormal, or if one preliminary evaluation indicator is abnormal and 2 to 3 in-depth evaluation indicators are abnormal, the area is classified as a Level II warning area; if one preliminary evaluation indicator is abnormal and 1 in-depth evaluation indicator is abnormal, the area is classified as a Level III warning area.

4. A rapid identification system for risk areas on rock slopes, characterized in that: The method for rapid identification of risk areas of rock slopes as described in any one of claims 1-3 includes the following steps: The model building module is used to construct a 3D point cloud model of the original rock surface of a steep rock slope based on UAV oblique photography and 3D laser scanning. The preliminary risk zone delineation module is used to delineate the preliminary risk zone of the original rock surface based on the three-dimensional point cloud model. It determines the distance between adjacent joints by the geometric shape of the collected point cloud data and delineates the area where there are joints with a distance smaller than the preset distance as the preliminary risk zone. The system deployment module is used to deploy the slope microseismic monitoring system according to the preliminary risk zone before slope excavation; The risk level assessment module is used to monitor the internal damage of the rock mass in real time through a microseismic monitoring system during slope excavation, and to simultaneously monitor the geological conditions of the rock mass excavation face through three-dimensional laser scanning. Based on the internal damage of the rock mass and the geological conditions of the rock mass excavation face, multi-source parameters are collected, and the joint spacing and the moment magnitude of the microseismic event are used as preliminary evaluation indicators to delineate the risk areas of slope excavation and evaluate the risk level. The risk verification module is used to issue early warnings based on risk levels. It uses joint length, microseismic event b-value, and the number of microseismic events per day as in-depth evaluation indicators to verify risk levels, and dynamically divides the final risk area range through multi-source parameters.

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