A method and system for monitoring sliding surface characteristics based on acoustic emission

Abstract

The present invention discloses a sliding surface feature monitoring method and system based on acoustic emission, and relates to the technical field of landslide monitoring. The process of the present invention includes: installation of acoustic emission monitoring device; establishment of wave velocity field; division of sliding surface area; monitoring and analysis of acoustic emission signals; data processing and analysis; positioning and modeling of sliding surface; real-time monitoring and early warning. The present invention installs a highly sensitive acoustic emission monitoring device, establishes a wave velocity field, divides the sliding surface area, monitors the acoustic emission signal in real time, and accurately locates the sliding surface position through professional data processing and analysis, constructs a three-dimensional model, and realizes real-time monitoring and early warning of landslide risks. This method can effectively improve the accuracy and real-time performance of landslide monitoring, and provide strong technical support for the prevention and control of landslide disasters.

Description

Technical Field

[0001] The invention belongs to the technical field of landslide monitoring, and in particular relates to a sliding surface feature monitoring method and system based on acoustic emission. Background Art

[0002] Landslide is a common geological disaster, mainly occurring in mountainous and hilly areas and areas with frequent human activities. Landslides are often accompanied by serious casualties and property losses. Therefore, landslide monitoring and early warning have become one of the important aspects of geological disaster prevention and control.

[0003] Traditional landslide monitoring methods mainly include ground inspections, topographic surveys, borehole observations, etc. Although these methods can provide information on landslide activities to a certain extent, they also have the following shortcomings:

[0004] Poor timeliness: Traditional methods rely on regular manual inspections and measurements and cannot achieve real-time monitoring.

[0005] Low accuracy: Ground inspections and topographic measurements are greatly affected by factors such as weather and topography, making it difficult to obtain high-precision data.

[0006] High cost: Methods such as drilling observation require a lot of equipment and human resources, which are relatively costly.

[0007] Limited coverage: Traditional methods can usually only monitor local areas and it is difficult to fully cover the entire landslide area.

[0008] Acoustic emission technology is a monitoring method based on acoustic wave signals. It can monitor the mechanical behavior of materials in real time by capturing elastic waves generated by the expansion and fracture of microcracks inside the material. In landslide monitoring, acoustic emission technology has the following advantages: real-time monitoring, high precision, non-contact monitoring and multi-point monitoring.

[0009] In recent years, the application of acoustic emission technology in landslide monitoring has gradually increased, but there are still some challenges:

[0010] Complex signal processing: Acoustic emission signals are affected by many factors, such as noise interference, signal attenuation, etc., which require complex signal processing technology.

[0011] Data analysis is difficult: The feature extraction and analysis of acoustic emission signals are relatively complex and require professional software and algorithm support.

[0012] Imperfect early warning mechanism: The existing acoustic emission monitoring system is not perfect in terms of early warning mechanism and needs further optimization. Summary of the invention

[0013] In order to overcome the shortcomings and deficiencies of the above-mentioned prior art, the first purpose of the present invention is to provide a sliding surface characteristic monitoring method based on acoustic emission; the second purpose of the present invention is to provide a sliding surface characteristic monitoring system based on acoustic emission.

[0014] The first object of the present invention adopts the following technical solution:

[0015] A method for monitoring sliding surface characteristics based on acoustic emission, the steps are as follows:

[0016] Step 1: Install the acoustic emission monitoring device: On both sides of the potential landslide area, select the monitoring node location according to the geological design drawings and the sliding surface structure to ensure that the monitoring node can cover the entire landslide area;

[0017] Step 2: Establishing the wave velocity field: Monitor the sound wave propagation velocity between different positions by means of the self-transmitting and self-receiving method of the acoustic emission monitoring device, and establish a wave velocity distribution map of the entire monitoring area; use the wave velocity distribution map to correct the propagation time and path of the acoustic emission signal to ensure the accuracy of the data;

[0018] Step 3: Divide the sliding surface area;

[0019] Step 4: Acoustic emission signal monitoring and analysis;

[0020] Step 5: Process and analyze the collected acoustic emission data: Process the collected acoustic emission data, including denoising and feature extraction steps; analyze the characteristics of the acoustic emission signals, including energy size and occurrence frequency, to determine the extent and development trend of the landslide activity;

[0021] Step 6: Slide surface location and modeling: Use the spatial distribution characteristics of acoustic emission signals to locate the position of the slide surface and build a three-dimensional model to intuitively display the structural characteristics of the landslide body;

[0022] Step 7: Real-time monitoring and early warning.

[0023] Preferably, step one further comprises:

[0024] By setting the acoustic emission monitoring node, the acoustic emission monitoring node set is obtained. ; ,in, represents the i-th acoustic emission monitoring node, and m represents the number of monitoring nodes;

[0025] Install a highly sensitive and stable acoustic emission sensor above the acoustic emission monitoring node to obtain the initial acoustic emission signal set ; ,in, Represents the initial signal of the i-th acoustic emission monitoring node.

[0026] Preferably, the division of the sliding surface area in step 3 is as follows:

[0027] S31: Acoustic emission monitoring node As the first parent node, calculate the acoustic emission monitoring node to The set of acoustic emission signal intensity differences at ,in, Indicates With The difference in acoustic emission signal intensity is calculated as follows: ;in, represents the signal strength of the i-th acoustic emission monitoring node; represents the signal strength of the jth acoustic emission monitoring node;

[0028] S32: Set the node signal strength difference threshold , traverse and retrieve the acoustic emission signal intensity difference set in turn ,when When the retrieval is stopped, the AE signal intensity difference corresponding to the AE monitoring node is extracted. , the acoustic emission monitoring node To Acoustic Emission Monitoring The area is included in the first monitoring zone;

[0029] S33: Acoustic emission monitoring node As the second mother node, repeat steps S31 and S32 to obtain a second acoustic emission signal strength difference set and a second monitoring partition;

[0030] S34: Obtain the third monitoring zone to the Nth monitoring zone according to the same rules as steps S31 to S33, where N is the total number of monitoring zones.

[0031] Preferably, the acoustic emission signal monitoring and analysis in step 4 is as follows:

[0032] S41: using an acoustic emission sensor to capture acoustic emission signals in the landslide risk area, and extracting acoustic emission signals from the first monitoring section to the Nth monitoring section;

[0033] S42: Obtain the maximum intensity value of each signal in the acoustic emission signal of the first monitoring area to the Nth monitoring area in turn, and mark it as the acoustic emission signal prediction value ,in Indicates Monitoring zone acoustic emission signal prediction value;

[0034] S43: Calculate the acoustic emission signal intensity value set from the first monitoring zone to the Nth monitoring zone according to the zone signal calculation strategy ,in Indicates Monitor the acoustic emission signal intensity values ​​of the partitions.

[0035] Preferably, the partition signal calculation strategy includes the following steps:

[0036] S431: Add all parent nodes in step S3 to the parent node set ,in Indicates the number of parent nodes and collects the corresponding initial acoustic emission signal set , the initial signal corresponding to the acoustic emission monitoring node Write into the initial acoustic emission signal set and get ;

[0037] S432: Calculate the first Monitoring partition acoustic emission signal intensity value , the calculation formula is:

[0038] ;

[0039] in, represents the weight of the acoustic emission signal prediction value, represents the mean weight of node signal; Indicates Monitor the mean value of the partition node signal;

[0040] S433: extracting the maximum acoustic emission signal threat value M;

[0041] .

[0042] As a preferred embodiment, the real-time monitoring and early warning in step seven are as follows:

[0043] S71: Setting the acoustic emission signal safety threshold and , when the maximum acoustic emission signal threat value Less than When the maximum acoustic emission signal threat value is Greater than or equal to and less than or equal to When the maximum acoustic emission signal threat value is Greater than When the alarm is raised, the monitoring area is located and an alarm is sounded immediately;

[0044] S72: Monitor the rising speed of the acoustic emission signal in the landslide risk area through the acoustic emission signal rising threat monitoring strategy, and calculate the acoustic emission signal rising threat value , set the acoustic emission signal rising threat threshold , when the acoustic emission signal rises to a threat value Greater than or equal to When the alarm is raised, the monitoring area is located and an alarm is sounded immediately;

[0045] S73: Record monitoring data and monitor the changes of acoustic emission signals in the landslide risk area in real time.

[0046] As a preferred embodiment, the self-generation and self-collection method in step 1 is:

[0047] Each acoustic emission monitoring device can both send acoustic wave signals and receive acoustic wave signals from other devices, and each monitoring point can communicate with other monitoring points in a two-way manner.

[0048] As a preferred method, the degree and development trend of landslide activity in step 5 are determined as follows:

[0049] Comprehensive analysis of multiple indicators: combining energy size and occurrence frequency indicators to determine the extent of landslide activity;

[0050] Trend prediction: predict the future development trend of landslide activities through time series analysis;

[0051] Risk assessment: Based on the analysis results, assess the risk level of landslide.

[0052] The second object of the present invention adopts the following technical solution:

[0053] A sliding surface feature monitoring system based on acoustic emission is used to implement a sliding surface feature monitoring method based on acoustic emission. The system includes an acoustic emission monitoring device installation module, a wave velocity field establishment module, a sliding surface area division module, an acoustic emission signal monitoring and analysis module, a data processing and analysis module, a sliding surface positioning and modeling module, and a real-time monitoring and early warning module.

[0054] Acoustic emission monitoring device installation module: Set up acoustic emission monitoring nodes according to geological design drawings and sliding surface structure, generate an acoustic emission monitoring node set, install a highly sensitive and stable acoustic emission sensor above each acoustic emission monitoring node, and obtain an initial acoustic emission signal set;

[0055] Wave velocity field establishment module: through the self-transmission and self-reception of the acoustic emission monitoring device, the wave velocity distribution map of the entire monitoring area is established, and the propagation time and path of the acoustic emission signal are corrected;

[0056] Slide surface area division module: divide the landslide area into multiple monitoring areas;

[0057] Acoustic emission signal monitoring and analysis module: captures the acoustic emission signals in the landslide risk area and analyzes them;

[0058] Data processing and analysis module: process and analyze the collected acoustic emission data; extract the characteristics of the acoustic emission signals, and analyze the extent and development trend of the landslide activity based on the characteristics;

[0059] Slide surface positioning and modeling module: Use the spatial distribution characteristics of acoustic emission signals to accurately locate the position of the sliding surface and build a three-dimensional model to intuitively display the structural characteristics of the landslide body;

[0060] Real-time monitoring and early warning module: real-time monitoring of acoustic emission signals in landslide risk areas, and issuing alarms based on set thresholds.

[0061] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0062] 1. The present invention can realize high-precision real-time monitoring of acoustic emission signals in the landslide area by installing a highly sensitive acoustic emission monitoring device and combining it with the establishment of a wave velocity field. Compared with traditional landslide monitoring methods, this technology has higher sensitivity and accuracy and can detect signs of landslide earlier.

[0063] 2. The present invention proposes a sliding surface area division strategy based on the difference in acoustic emission signal intensity. By calculating the signal intensity difference between different monitoring nodes and setting thresholds, multiple monitoring areas can be automatically divided, thereby achieving refined management of landslide risks.

[0064] 3. The present invention utilizes the spatial distribution characteristics of acoustic emission signals. This method can accurately locate the position of the sliding surface and construct a three-dimensional model. This three-dimensional visualization technology enables technicians to intuitively understand the structural characteristics of the landslide body and provide a more scientific decision-making basis for landslide prevention and control. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0066] Figure 1 A flow chart of a method for monitoring sliding surface characteristics based on acoustic emission according to the present invention is shown;

[0067] Figure 2 A module diagram of a sliding surface characteristic monitoring system based on acoustic emission according to the present invention is shown;

[0068] Figure 3 A flow chart of the sliding surface area division of the present invention is shown. DETAILED DESCRIPTION

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] In addition, the described features, structures or characteristics may be combined in one or more example embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the example embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or other methods, components, steps, etc. may be adopted. In other cases, well-known structures, methods, implementations or operations are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0071] Embodiment 1:

[0072] See also Figure 1 As shown, a sliding surface feature monitoring method based on acoustic emission in this embodiment comprises the following steps:

[0073] Step 1: Installation of acoustic emission monitoring device.

[0074] S11: On both sides of the potential landslide area, acoustic emission monitoring nodes are set according to the geological design drawings and the sliding surface structure to obtain the acoustic emission monitoring node set ;

[0075] ,in, represents the ith acoustic emission monitoring node, and m represents the number of monitoring nodes.

[0076] S12: Install a highly sensitive and stable acoustic emission sensor above the acoustic emission monitoring node to obtain an initial acoustic emission signal set ;

[0077] ,in, Represents the initial signal of the i-th acoustic emission monitoring node.

[0078] Step 2: Establish the wave velocity field.

[0079] S21: Through the self-transmitting and self-receiving mode of the acoustic emission monitoring device, that is, each device can both send and receive sound wave signals, the sound wave propagation speed between different positions is monitored, and the wave speed distribution map of the entire monitoring area is established.

[0080] S22: Use the wave velocity distribution diagram to correct the propagation time and path of the acoustic emission signal to ensure the accuracy of the data.

[0081] Step 3: Divide the sliding surface area.

[0082] See also Figure 3 As shown in the figure, the specific steps of sliding surface area division are as follows:

[0083] S31: Acoustic emission monitoring node As the first parent node, calculate the acoustic emission monitoring node to The set of acoustic emission signal intensity differences at ,in, Indicates With The difference in acoustic emission signal intensity is calculated as follows: ;in, represents the signal strength of the i-th acoustic emission monitoring node; Represents the signal strength of the jth acoustic emission monitoring node.

[0084] S32: Set the node signal strength difference threshold , traverse and retrieve the acoustic emission signal intensity difference set in turn ,when When the retrieval is stopped, the AE signal intensity difference corresponding to the AE monitoring node is extracted. , the acoustic emission monitoring node To Acoustic Emission Monitoring The area is included in the first monitoring zone.

[0085] S33: Acoustic emission monitoring node As the second mother node, step S31 and step S32 are repeated to obtain a second acoustic emission signal intensity difference set and a second monitoring partition.

[0086] S34: Obtain the third monitoring zone to the Nth monitoring zone according to the same rules as steps S31 to S33, where N is the total number of monitoring zones.

[0087] Step 4: Acoustic emission signal monitoring and analysis.

[0088] S41: using an acoustic emission sensor to capture acoustic emission signals in the landslide risk area, and extracting acoustic emission signals from the first monitoring section to the Nth monitoring section.

[0089] S42: sequentially obtain the maximum intensity value of each signal in the acoustic emission signals of the first monitoring area to the Nth monitoring area, and mark it as the acoustic emission signal prediction value ,in Indicates Monitor the predicted value of acoustic emission signal in the partition.

[0090] S43: Calculate the acoustic emission signal strength value set from the first monitoring partition to the Nth monitoring partition according to the partition signal calculation strategy ,in Indicates Monitoring the partition acoustic emission signal intensity value; the partition signal calculation strategy includes the following steps:

[0091] S431: Add all parent nodes in step S3 to the parent node set ,in Indicates the number of parent nodes and collects the corresponding initial acoustic emission signal set , the initial signal corresponding to the acoustic emission monitoring node Write into the initial acoustic emission signal set, and obtain .

[0092] S432: Calculate the first Monitoring partition acoustic emission signal intensity value , the calculation formula is:

[0093] ;

[0094] in, represents the weight of the acoustic emission signal prediction value, represents the mean weight of node signal; Indicates Monitor the mean value of the partition node signal.

[0095] S433: extracting the maximum acoustic emission signal threat value M;

[0096] .

[0097] Step 5: Data processing and analysis.

[0098] S51: The collected acoustic emission data needs to be processed by professional software, including denoising, feature extraction and other steps.

[0099] S52: By analyzing the characteristics of acoustic emission signals, such as energy level and frequency of occurrence, the extent and development trend of landslide activity can be determined.

[0100] Step 6: Sliding surface positioning and modeling.

[0101] S61: By utilizing the spatial distribution characteristics of acoustic emission signals, the position of the sliding surface can be accurately located, and a three-dimensional model can be constructed to intuitively display the structural characteristics of the landslide.

[0102] Step 7: Real-time monitoring and early warning.

[0103] S71: Setting the acoustic emission signal safety threshold and , when the maximum acoustic emission signal threat value Less than When the maximum acoustic emission signal threat value Greater than or equal to and less than or equal to When the maximum acoustic emission signal threat value is Greater than When a fault occurs, the monitoring partition is located and an alarm is issued immediately.

[0104] S72: Monitor the rising speed of the acoustic emission signal in the landslide risk area through the acoustic emission signal rising threat monitoring strategy, and calculate the acoustic emission signal rising threat value , set the acoustic emission signal rising threat threshold , when the acoustic emission signal rises to a threat value Greater than or equal to When a fault occurs, the monitoring partition is located and an alarm is issued immediately.

[0105] S73: Record monitoring data and monitor the changes of acoustic emission signals in the landslide risk area in real time.

[0106] The beneficial effects of this embodiment are: by installing a highly sensitive acoustic emission monitoring device, establishing a wave velocity field, dividing the sliding surface area, monitoring the acoustic emission signal in real time, and accurately locating the sliding surface position through professional data processing and analysis, building a three-dimensional model, and realizing real-time monitoring and early warning of landslide risks. This method can effectively improve the accuracy and real-time performance of landslide monitoring and provide strong technical support for the prevention and control of landslide disasters.

[0107] Embodiment 2:

[0108] See also Figure 2 As shown, a sliding surface feature monitoring system based on acoustic emission in this embodiment includes an acoustic emission monitoring device installation module, a wave velocity field establishment module, a sliding surface area division module, an acoustic emission signal monitoring and analysis module, a data processing and analysis module, a sliding surface positioning and modeling module, and a real-time monitoring and early warning module.

[0109] Acoustic emission monitoring device installation module: set up acoustic emission monitoring nodes according to geological design drawings and sliding surface structure, generate an acoustic emission monitoring node set, install highly sensitive and stable acoustic emission sensors above each acoustic emission monitoring node, and obtain an initial acoustic emission signal set.

[0110] Wave velocity field establishment module: Through the self-transmission and self-reception of the acoustic emission monitoring device, the wave velocity distribution map of the entire monitoring area is established, and the propagation time and path of the acoustic emission signal are corrected.

[0111] Slide surface area division module: divide the landslide area into multiple monitoring areas.

[0112] Acoustic emission signal monitoring and analysis module: captures acoustic emission signals in landslide risk areas and analyzes them.

[0113] Data processing and analysis module: process and analyze the collected acoustic emission data; extract the characteristics of the acoustic emission signals, and analyze the extent and development trend of the landslide activity based on the characteristics.

[0114] Slide surface positioning and modeling module: Utilize the spatial distribution characteristics of acoustic emission signals to accurately locate the position of the sliding surface and build a three-dimensional model to intuitively display the structural characteristics of the landslide body.

[0115] Real-time monitoring and early warning module: real-time monitoring of acoustic emission signals in landslide risk areas, and issuing alarms based on set thresholds.

[0116] The beneficial effects of this embodiment are: through the high-sensitivity acoustic emission monitoring device, the acoustic emission signals of the landslide area are captured and analyzed in real time, the sliding surface position is accurately located, and a three-dimensional model is constructed to achieve real-time monitoring and early warning of landslide risks. The system improves the accuracy and real-time performance of landslide monitoring and provides strong technical support for the prevention and control of landslide disasters.

[0117] The weights of the present invention are used to measure the degree of influence of different factors or variables on a certain result or decision. The definition of weight refers to the value assigned to each factor when comparing and evaluating multiple factors to reflect its importance or priority. These weights can be determined according to specific circumstances and needs, and are usually jointly formulated and confirmed by professionals or relevant stakeholders. By setting weights reasonably, it can help programs or systems make decisions or predictions more accurately.

[0118] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

[0119] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A sliding surface feature monitoring method based on acoustic emission, characterized in that: The method steps are as follows: Step 1: Install the acoustic emission monitoring device: On both sides of the potential landslide area, select the monitoring node location according to the geological design drawings and the sliding surface structure to ensure that the monitoring node can cover the entire landslide area; Step 2: Establishing the wave velocity field: Monitor the sound wave propagation velocity between different positions by means of the self-transmitting and self-receiving method of the acoustic emission monitoring device, and establish a wave velocity distribution map of the entire monitoring area; use the wave velocity distribution map to correct the propagation time and path of the acoustic emission signal to ensure the accuracy of the data; Step 3: Divide the sliding surface area; Step 4: Acoustic emission signal monitoring and analysis; Step 5: Process and analyze the collected acoustic emission data: Process the collected acoustic emission data, including denoising and feature extraction steps; analyze the characteristics of the acoustic emission signals, including energy size and occurrence frequency, to determine the extent and development trend of the landslide activity; Step 6: Slide surface location and modeling: Use the spatial distribution characteristics of acoustic emission signals to locate the position of the slide surface and build a three-dimensional model to intuitively display the structural characteristics of the landslide body; Step 7: Real-time monitoring and early warning; The division of the sliding surface area in step 3 is as follows: S31: Acoustic emission monitoring node As the first parent node, calculate the acoustic emission monitoring node to The set of acoustic emission signal intensity differences at ,in, Indicates With The acoustic emission signal intensity difference is calculated as follows: ;in, Represents the signal strength of the i-th acoustic emission monitoring node; represents the signal strength of the jth acoustic emission monitoring node; S32: Set the node signal strength difference threshold , traverse and retrieve the acoustic emission signal intensity difference set in turn ,when When the retrieval is stopped, the AE signal intensity difference corresponding to the AE monitoring node is extracted. , the acoustic emission monitoring node To Acoustic Emission Monitoring The area is included in the first monitoring zone; S33: Acoustic emission monitoring node As the second mother node, repeat steps S31 and S32 to obtain a second acoustic emission signal strength difference set and a second monitoring partition; S34: Obtain the third monitoring zone to the Nth monitoring zone according to the same rules as steps S31 to S33, where N is the total number of monitoring zones; The acoustic emission signal monitoring and analysis in step 4 are as follows: S41: using an acoustic emission sensor to capture acoustic emission signals in the landslide risk area, and extracting acoustic emission signals from the first monitoring section to the Nth monitoring section; S42: sequentially obtain the maximum intensity value of each signal in the acoustic emission signals of the first monitoring area to the Nth monitoring area, and mark it as the acoustic emission signal prediction value ,in Indicates Monitoring zone acoustic emission signal prediction value; S43: Calculate the acoustic emission signal strength value set from the first monitoring partition to the Nth monitoring partition according to the partition signal calculation strategy ,in Indicates Monitor the acoustic emission signal intensity value of the partition; The partition signal calculation strategy includes the following steps: S431: Add all parent nodes in step S3 to the parent node set ,in Indicates the number of parent nodes and collects the corresponding initial acoustic emission signal set , the initial signal corresponding to the acoustic emission monitoring node Write into the initial acoustic emission signal set, and obtain ; S432: Calculate the first Monitoring partition acoustic emission signal intensity value , the calculation formula is: ； in, represents the weight of the acoustic emission signal prediction value, represents the mean weight of node signal; Indicates Monitor the mean value of the partition node signal; S433: extracting the maximum acoustic emission signal threat value M; 。 2. The method for monitoring sliding surface characteristics based on acoustic emission according to claim 1, characterized in that: The step one also includes: By setting the acoustic emission monitoring node, the acoustic emission monitoring node set is obtained. ; ,in, represents the i-th acoustic emission monitoring node, and m represents the number of monitoring nodes; Install a highly sensitive and stable acoustic emission sensor above the acoustic emission monitoring node to obtain an initial acoustic emission signal set ; ,in, Represents the initial signal of the i-th acoustic emission monitoring node.

3. The method for monitoring sliding surface characteristics based on acoustic emission according to claim 1, characterized in that: The real-time monitoring and early warning in step seven are as follows: S71: Setting the acoustic emission signal safety threshold and , when the maximum acoustic emission signal threat value Less than When the maximum acoustic emission signal threat value Greater than or equal to and less than or equal to When the maximum acoustic emission signal threat value is Greater than When the alarm is raised, the monitoring area is located and an alarm is sounded immediately; S72: Monitor the rising speed of the acoustic emission signal in the landslide risk area through the acoustic emission signal rising threat monitoring strategy, and calculate the acoustic emission signal rising threat value , set the acoustic emission signal rising threat threshold , when the acoustic emission signal rises to a threat value Greater than or equal to When the alarm is raised, the monitoring area is located and an alarm is sounded immediately; S73: Record monitoring data and monitor the changes of acoustic emission signals in the landslide risk area in real time.

4. The method for monitoring sliding surface characteristics based on acoustic emission according to claim 1, characterized in that: The self-generated and self-collected method in step 1 is: Each acoustic emission monitoring device can both send acoustic wave signals and receive acoustic wave signals from other devices, and each monitoring point can communicate with other monitoring points in a two-way manner.

5. The method for monitoring sliding surface characteristics based on acoustic emission according to claim 1, characterized in that: The determination of the extent and development trend of landslide activity in step 5 is specifically as follows: Comprehensive analysis of multiple indicators: combining energy size and occurrence frequency indicators to determine the extent of landslide activity; Trend prediction: predict the future development trend of landslide activities through time series analysis; Risk assessment: Based on the analysis results, assess the risk level of landslide.

Images