Sector-shaped slope crack monitoring system and monitoring method thereof

Abstract

The invention provides a sector-shaped slope crack monitoring system and a monitoring method thereof, and relates to the technical field of crack monitoring, and the sector-shaped slope crack monitoring system comprises an ultrasonic detector which is used for generating and receiving a required sound wave frequency; the sensing network is used for collecting crack data in the sector area; the data acquisition unit is used for acquiring data of the sensing network and sound wave frequency data of the ultrasonic detector and preprocessing the data; the communication module is used for transmitting the data acquired by the data acquisition unit to the central processing platform; and the central processing platform is used for analyzing and processing the collected data, generating a report and sending out an alarm notification according to a preset threshold value, can realize omnibearing coverage of slope cracks by combining underground crack monitoring and earth surface crack monitoring, and can realize comprehensive coverage of the slope cracks based on analysis of the monitoring data. Continuous innovation and perfection of related monitoring technologies and early warning systems can be promoted, and the automation and intelligence level of geological disaster monitoring and early warning is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of crack monitoring, and in particular to a fan-shaped slope crack monitoring system and a monitoring method thereof. Background Art

[0002] Ground fissures are geological phenomena in which surface rocks and soils crack under the influence of natural or human factors, forming cracks of a certain length and width. Ground fissures are a slowly developing progressive geological disaster. Affected by the geological environment and human factors, the development of ground fissures is gradual and cyclical. As time changes, the hazards of ground fissures cause deformation and stress fields in the geological bodies within a certain range around them. For slope hazards, the development of surface cracks is the most common deformation manifestation, and its development and change trend has a strong correlation with the overall stability of the slope. Therefore, monitoring of the deformation characteristics of ground fissures is also an important technical means for slope disaster prevention and mitigation.

[0003] Currently, for the detection of cracks on slopes, professionals usually use crack depth gauges and crack width gauges to regularly inspect the slopes, and then judge the danger level of the cracks based on their experience. However, slopes generally have an inclination, and manual detection is dangerous, time-consuming and labor-intensive, making it difficult to conduct real-time detection. In addition, manual detection is prone to missed judgments and misjudgments.

[0004] Therefore, it is necessary to provide a new fan-shaped slope crack monitoring system and a monitoring method thereof to solve the above-mentioned technical problems. Summary of the invention

[0005] In order to solve the technical problems that slopes generally have an inclination, manual detection is dangerous, time-consuming and labor-intensive, and difficult to perform real-time detection, and manual detection is prone to missed judgments and misjudgments, the present invention provides a fan-shaped slope crack monitoring system and a monitoring method thereof.

[0006] The fan-shaped slope crack monitoring system provided by the present invention comprises an ultrasonic detector: used for generating and receiving the required sound wave frequency, the ultrasonic detector comprises a transducer transmitting end and a transducer receiving end, the transducer transmitting end is perpendicular to the slope fan area, the transducer receiving end is located above the transducer transmitting end, and the transducer transmitting end and the transducer receiving end are in the same vertical line;

[0007] Sensor network: includes multiple sensors installed in the slope fan area, which are used to collect crack data in the fan area, where the crack data includes crack opening width, local slope inclination and stress changes inside the crack;

[0008] Data acquisition unit: used to collect data from the sensor network and the sound wave frequency data from the ultrasonic detector, and perform preprocessing;

[0009] Communication module: used to transmit the data collected by the data acquisition unit to the central processing platform;

[0010] Central processing platform: used to analyze and process the collected data, generate reports, and issue alarms based on preset thresholds.

[0011] Further, the sensing network includes: a displacement sensor for monitoring changes in crack opening width;

[0012] Inclination sensor, used to monitor the local inclination of the slope;

[0013] Stress sensors are used to monitor stress changes inside cracks.

[0014] Another aspect of the present invention provides a monitoring method for a fan-shaped slope crack monitoring system, the method comprising the following steps:

[0015] S1. Divide the slope into several sectors according to the geological characteristics of the slope and the direction of the cracks, and arrange a sensor network and ultrasonic detector in each sector;

[0016] S2. Place the transmitting end of the transducer in the ultrasonic detector perpendicular to the slope sector area, and the receiving end of the transducer is located above the transmitting end of the transducer, and the transmitting end of the transducer and the receiving end of the transducer are placed on the same vertical line;

[0017] S3, each sensor in the sensor network collects crack width, displacement, and tilt angle data at a predetermined frequency;

[0018] S4, sending the sensor network and ultrasonic detector data to the data acquisition unit by wireless or wired means;

[0019] S5. The central processing platform pre-processes the data received by the data acquisition unit, and analyzes the crack width, the stress change inside the slope crack, the local slope inclination and the sound wave frequency, and generates an analysis report;

[0020] S6. Continuously monitor the development trend of cracks;

[0021] S7. When the crack development exceeds the preset threshold, the system triggers an alarm.

[0022] Furthermore, the crack width analysis comprises the following steps:

[0023] S1. Calculation of crack width change rate: Calculate the crack width difference between two adjacent time points and find the average change rate;

[0024] S2. Crack extension trend analysis: The trend of crack width extension was analyzed using a linear regression model;

[0025] S3, threshold comparison: compare the crack width expansion trend with the preset safety threshold;

[0026] S4. Early warning judgment: When the crack width expansion trend exceeds the safety threshold, it is determined that there is a potential risk and a warning is triggered.

[0027] Furthermore, the analysis of the local slope inclination degree includes the following steps:

[0028] S1, establishing a time series set based on the inclination angle data collected by the inclination sensor, representing the inclination angle of the slope at different times;

[0029] S2, using time series analysis to predict the inclination of local cracks on the slope;

[0030] S3. When the predicted inclination of the local cracks on the slope exceeds the warning threshold, the warning mechanism is triggered.

[0031] Furthermore, the analysis of internal stress changes in slope cracks includes the following steps:

[0032] S1. Establish the stress state equation;

[0033] S2. Establish stress observation equation;

[0034] S3, predicting the stress state at the current moment: predicting the state at the current moment based on the state estimation and control input at the previous moment;

[0035] S4, prediction covariance:

[0036] S5, calculating the Kalman gain according to the prediction covariance and the observation matrix;

[0037] S6, updating the state estimate according to the observed stress value and the Kalman gain;

[0038] S7, updating the covariance matrix of the state estimate;

[0039] S8. Early warning judgment: When the predicted stress value exceeds the early warning threshold, the early warning mechanism is triggered.

[0040] Furthermore, the sound wave frequency analysis comprises the following steps:

[0041] S1. Signal decomposition: Use wavelet basis functions to decompose the sound wave frequency signal into different scales;

[0042] S2, feature extraction: extract the energy distribution and frequency component characteristics of the signal at each scale;

[0043] S3, crack identification: judging the existence of cracks based on the changes in characteristics;

[0044] S4. Quantification of crack degree: quantify the degree of cracks by the amplitude change of the feature;

[0045] S5. Early warning judgment: When the detected crack change degree exceeds the early warning threshold, the early warning mechanism is triggered.

[0046] Compared with the related art, the fan-shaped slope crack monitoring system and monitoring method provided by the present invention have the following beneficial effects:

[0047] 1. The present invention places the transmitting end of the transducer perpendicular to the slope fan area, and the receiving end of the transducer is located above the transmitting end of the transducer, and the transmitting end of the transducer and the receiving end of the transducer are on the same vertical line, so as to ensure that the ultrasonic wave can be emitted along a specific direction (i.e., perpendicular to the slope fan area) to improve the concentration and propagation efficiency of the sound wave energy. At the same time, the receiving end is located above the transmitting end and on the same vertical line, which is conducive to accurately receiving the reflected sound wave signal. By maintaining the vertical relationship between the transmitting end and the receiving end, the sound wave interference from other directions can be reduced, thereby improving the accuracy and reliability of the measurement.

[0048] 2. The present invention monitors underground cracks by generating and receiving the required sound wave frequency through an ultrasonic detector, and then combines a plurality of sensors installed in the fan area of ​​the slope to collect the crack opening width in the fan area, the local inclination of the slope, and the stress changes inside the cracks. By combining underground crack monitoring and surface crack monitoring, all-round coverage of slope cracks can be achieved, reducing monitoring blind spots, solving the problem that underground cracks are difficult to directly observe and the impact of underground cracks on slope stability is easily overlooked. Based on the analysis of monitoring data, it can promote the continuous innovation and improvement of related monitoring technologies and early warning systems, and improve the automation and intelligence level of geological disaster monitoring and early warning.

[0049] 3. The present invention divides the slope into several sectors according to the geological characteristics of the slope and the direction of the cracks. A sensor network and an ultrasonic detector are arranged in each sector to carry out detailed monitoring of the specific geological characteristics and crack directions of each sector. This zoning monitoring method can capture subtle local changes better than overall monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A structural block diagram of the fan-shaped slope crack monitoring system provided by the present invention;

[0051] Figure 2 A flowchart of a monitoring method for a fan-shaped slope crack monitoring system provided by the present invention;

[0052] Figure 3 A flowchart of the crack width analysis provided by the present invention;

[0053] Figure 4A flowchart of the slope local inclination analysis provided by the present invention;

[0054] Figure 5 A flowchart of the internal stress change analysis of a slope crack provided by the present invention;

[0055] Figure 6 This is a flowchart of the sound wave frequency analysis provided by the present invention. DETAILED DESCRIPTION

[0056] The present invention will be further described below in conjunction with the accompanying drawings and implementation modes.

[0057] Please refer to Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 as well as Figure 6 ,in, Figure 1 A structural block diagram of the fan-shaped slope crack monitoring system provided by the present invention; Figure 2 A flowchart of a monitoring method for a fan-shaped slope crack monitoring system provided by the present invention; Figure 3 A flowchart of the crack width analysis provided by the present invention; Figure 4 A flowchart of the slope local inclination analysis provided by the present invention; Figure 5 A flowchart of the internal stress change analysis of a slope crack provided by the present invention; Figure 6 This is a flowchart of the sound wave frequency analysis provided by the present invention.

[0058] Embodiment 1

[0059] In the specific implementation process, Figure 1 As shown, the present invention provides a fan-shaped slope crack monitoring system and a monitoring method thereof.

[0060] The fan-shaped slope crack monitoring system provided by the present invention includes an ultrasonic detector: used for generating and receiving the required sound wave frequency, the ultrasonic detector includes a transducer transmitting end and a transducer receiving end, the transducer transmitting end is perpendicular to the slope fan area, the transducer receiving end is located above the transducer transmitting end, and the transducer transmitting end and the transducer receiving end are in the same vertical line, which is conducive to accurately receiving the reflected sound wave signal, and by maintaining the vertical relationship between the transmitting end and the receiving end, the sound wave interference from other directions can be reduced;

[0061] Sensor network: includes multiple sensors installed in the slope fan area, which are used to collect crack data in the fan area, where the crack data includes crack opening width, local slope inclination and stress changes inside the crack;

[0062] Data acquisition unit: used to collect data from the sensor network and the sound wave frequency data of the ultrasonic detector, and perform preprocessing. It integrates multiple sensor interfaces and is responsible for collecting and storing data. Data preprocessing includes cleaning the collected data and removing noise and outliers.

[0063] Communication module: used to transmit the data collected by the data acquisition unit to the central processing platform. Wireless communication (such as LoRa, Bluetooth, Wi-Fi, etc.) or wired communication (such as RS485, Ethernet, etc.) can be selected, depending on the monitoring range and environmental conditions. Wireless communication is suitable for long-distance and difficult wiring occasions, while wired communication is suitable for short-distance and easy wiring situations;

[0064] Central processing platform: used to analyze and process the collected data, generate reports, and issue alarms based on preset thresholds. Alarm notifications include sending alarm notifications to relevant personnel via SMS, email or APP.

[0065] Furthermore, the sensing network includes: a displacement sensor for monitoring the change of the crack opening width, the displacement sensor adopting a laser displacement sensor;

[0066] The tilt sensor is used to monitor the local inclination of the slope. The tilt sensor is an electronic inclinometer that measures the angle change of the slope through a built-in gyroscope or accelerometer;

[0067] The stress sensor is used to monitor the stress changes inside the crack. The stress sensor can be a resistance strain gauge or a fiber Bragg grating (FBG) sensor.

[0068] Embodiment 2

[0069] Another aspect of the present invention provides a monitoring method for a fan-shaped slope crack monitoring system, referring to Figure 2-Figure 6 As shown, the method comprises the following steps:

[0070] S1. Divide the slope into several sectors according to the geological characteristics and crack orientation of the slope. A sensor network and ultrasonic detector are arranged in each sector to conduct detailed monitoring of the specific geological characteristics and crack orientation of each sector. This zoning monitoring method can capture more subtle local changes than overall monitoring.

[0071] S2. The transducer transmitting end of the ultrasonic detector is placed perpendicular to the slope sector area, the transducer receiving end is located above the transducer transmitting end, and the transducer transmitting end and the transducer receiving end are placed on the same vertical line. The sensor network and the ultrasonic detector are fully arranged in the sector to ensure that all areas of the slope are monitored without blind spots, avoiding potential risks caused by monitoring blind spots;

[0072] S3, each sensor in the sensor network collects crack width, displacement, and tilt angle data at a predetermined frequency;

[0073] S4, sending the sensor network and ultrasonic detector data to the data acquisition unit by wireless or wired means;

[0074] S5. The central processing platform pre-processes the data received by the data acquisition unit, and analyzes the crack width, the stress change inside the slope crack, the local slope inclination and the sound wave frequency, and generates an analysis report;

[0075] S6. Continuously monitor the development trend of cracks;

[0076] S7. When the crack development exceeds the preset threshold, the system triggers an alarm.

[0077] Further, the crack width analysis includes the following steps:

[0078] S1. Calculation of crack width change rate: Calculate the crack width difference between two adjacent time points and find the average change rate;

[0079] S2. Crack extension trend analysis: The trend of crack width extension was analyzed using a linear regression model;

[0080] S3, threshold comparison: compare the crack width expansion trend with the preset safety threshold;

[0081] S4. Early warning judgment: When the crack width expansion trend exceeds the safety threshold, it is determined that there is a potential risk and a warning is triggered.

[0082] It should be noted that the linear regression model is used to predict the change trend of cracks: assuming that the crack width at time t is w(t), the following model is established:

[0083] w(t)=a+bt

[0084] Among them, a and b are the intercept and slope, respectively, which represent the rate of change of crack width over time, and are obtained by fitting the time data to predict the future crack width;

[0085] Furthermore, the local slope inclination analysis includes the following steps:

[0086] S1. Establish a time series set y based on the tilt angle data collected by the tilt sensor t , represents the inclination angle of the slope at different times t;

[0087] S2. Use time series analysis to predict the inclination of local cracks on the slope:

[0088] (1-φ1B-…-φ pB p )(1-B) d y t =c+(1+θ1B+…+θ q B q )∈ t

[0089] Among them, B is the backshift operator, ∈ t is a white noise process;

[0090] S3. When the predicted inclination of the local cracks on the slope exceeds the warning threshold, the warning mechanism is triggered.

[0091] In a specific embodiment, the analysis of internal stress changes in slope cracks includes the following steps:

[0092] S1. Establish the stress state equation: x t-1 =αx t +w t , where x t is the stress value, α is the state transfer coefficient, w t is the process noise;

[0093] S2. Establish stress observation equation: t =x t +v t , where z t is the observed stress value, v t is the observation noise;

[0094] S3. Predict the stress state at the current moment:

[0095]

[0096] Predict the current state based on the previous state estimate and control input;

[0097] S4, prediction covariance:

[0098]

[0099] Among them, Q t is the process noise covariance matrix;

[0100] S5. Calculate the Kalman gain based on the prediction covariance and the observation matrix:

[0101]

[0102] Among them, R t is the observation noise covariance matrix;

[0103] S6. Update the state estimate based on the observed stress value and Kalman gain:

[0104]

[0105] S7. Update the covariance matrix of the state estimate:

[0106] P t|t =(IK t H t ) t|t-1 =(1-K t ) t|t-1

[0107] S8. Early warning judgment: When the predicted stress value exceeds the early warning threshold, the early warning mechanism is triggered.

[0108] Furthermore, at each time step, the state transfer coefficient α and the process noise covariance matrix Q are adjusted according to the prediction error. t And the observation noise covariance matrix R t parameter.

[0109] Experiment 1:

[0110] A stress sensor was placed inside a specific slope crack. The sensor collected stress data every 10 minutes, and a week of data was collected as a historical data set for subsequent analysis:

[0111] The collected stress data are as follows:

[0112]

[0113]

[0114] Initialization parameters:

[0115] State vector: x t =[s t ], where s t is the stress value at time t;

[0116] Initialize the state estimate: That is, the first observation;

[0117] Initial state covariance matrix: P 0|0 =100;

[0118] State transition matrix: F t =1, indicating that the change of stress value can be approximately regarded as a first-order autoregressive process;

[0119] Control input matrix: B t =0, because there is no external control input;

[0120] Process noise covariance matrix: Q t=0.01, indicating the variance of process noise;

[0121] Observation matrix: H t =1, indicating that the observation directly corresponds to the state;

[0122] Observation noise covariance matrix: R t =1, indicating the variance of the observation noise;

[0123] The prediction and update process is as follows:

[0124] Initial state

[0125] Taking the first data point as an example, assuming t = 1

[0126] Prediction status:

[0127] Estimated covariance: P 1|0 =P 0|0 +Q0=100+0.01=100.01

[0128] Calculate the Kalman gain:

[0129] Update the state estimate:

[0130] Update the covariance matrix: P 1|1 =(1-0.9901)×100.01≈0.9999

[0131] Continue using the updated state estimate and covariance matrix to predict the state at the next time point, and so on.

[0132] In one embodiment, the acoustic wave frequency analysis comprises the following steps:

[0133] S1. Signal decomposition: Use wavelet basis functions to decompose the sound wave frequency signal into different scales;

[0134] S2, feature extraction: extract the energy distribution and frequency component characteristics of the signal at each scale;

[0135] S3, crack identification: judging the existence of cracks based on the changes in characteristics;

[0136] S4. Quantification of crack degree: quantify the degree of cracks by the amplitude change of the feature;

[0137] S5. Early warning judgment: When the detected crack change degree exceeds the early warning threshold, the early warning mechanism is triggered.

[0138] application:

[0139] Suppose the acoustic signal x(t), use the wavelet basis function ψ(t) to perform multi-scale wavelet transform on it

[0140] 1. Wavelet transform: decompose the signal into detail coefficients at different scales

[0141]

[0142] Among them, a is the scale factor and b is the translation factor;

[0143] 2. Repeat the wavelet transform at multiple scales:

[0144] W x (a i ,b i )for i=1,2,…,N and j=1,2,…,M

[0145] 3. Extract the energy distribution at each scale:

[0146]

[0147] 4. Identify the presence of cracks by comparing the energy distribution at different scales:

[0148] ΔE=E i+1 -E i

[0149] If ΔE is greater than zero, it means there is a gap;

[0150] 5. Quantify the extent of the crack by the degree of change in energy distribution:

[0151]

[0152] The crack identification threshold ΔE can be set based on historical data th ;

[0153] According to the quantitative value C of the crack degree, different warning levels are set;

[0154] Continuously monitor the changes in cracks inside the pavement when ΔE>ΔE th When the alarm is triggered.

[0155] The above comprehensive monitoring method can reduce the false alarms and missed alarms caused by a single monitoring method. Through multi-source data fusion analysis, the actual situation and potential risks of slope cracks can be judged more accurately.

[0156] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a general hardware platform, and of course, by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0157] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the attached claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention, and any figure mark in the claims should not be regarded as limiting the claims involved.

[0158] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A fan-shaped slope crack monitoring system, characterized in that: An ultrasonic detector is included: used for generating and receiving the required sound wave frequency, the ultrasonic detector includes a transducer transmitting end and a transducer receiving end, the transducer transmitting end is perpendicular to the slope fan area, the transducer receiving end is located above the transducer transmitting end, and the transducer transmitting end and the transducer receiving end are in the same vertical line; Sensor network: includes multiple sensors installed in the slope fan area, which are used to collect crack data in the fan area, where the crack data includes crack opening width, local slope inclination and stress changes inside the crack; Data acquisition unit: used to collect data from the sensor network and the sound wave frequency data from the ultrasonic detector, and perform preprocessing; Communication module: used to transmit the data collected by the data acquisition unit to the central processing platform; Central processing platform: used to analyze and process the collected crack width, internal stress changes in slope cracks, local slope inclination and sound wave frequency, generate reports, and issue alarm notifications based on preset thresholds.

2. The fan-shaped slope crack monitoring system according to claim 1 is characterized in that: The sensing network includes: a displacement sensor for monitoring changes in crack opening width; Inclination sensor, used to monitor the local inclination of the slope; Stress sensors are used to monitor stress changes inside cracks.

3. The fan-shaped slope crack monitoring system according to claim 1 is characterized in that: The alarm notification includes sending an alarm notification to relevant personnel via SMS, email or APP.

4. A monitoring method for a fan-shaped slope crack monitoring system according to any one of claims 1 to 3, characterized in that: The method comprises the following steps: S1. Divide the slope into several sectors according to the geological characteristics of the slope and the direction of the cracks, and arrange a sensor network and ultrasonic detector in each sector; S2. Place the transmitting end of the transducer in the ultrasonic detector perpendicular to the slope sector area, and the receiving end of the transducer is located above the transmitting end of the transducer, and the transmitting end of the transducer and the receiving end of the transducer are placed on the same vertical line; S3, each sensor in the sensor network collects crack width, displacement, and tilt angle data at a predetermined frequency; S4, sending the sensor network and ultrasonic detector data to the data acquisition unit by wireless or wired means; S5. The central processing platform pre-processes the data received by the data acquisition unit, and analyzes the crack width, the stress change inside the slope crack, the local slope inclination and the sound wave frequency, and generates an analysis report; S6. Continuously monitor the development trend of cracks; S7. When the crack development exceeds the preset threshold, the system triggers an alarm.

5. The monitoring method of the fan-shaped slope crack monitoring system according to claim 4 is characterized in that: The crack width analysis comprises the following steps: S1. Calculation of crack width change rate: Calculate the crack width difference between two adjacent time points and find the average change rate; S2. Crack extension trend analysis: The trend of crack width extension was analyzed using a linear regression model; S3, threshold comparison: compare the crack width expansion trend with the preset safety threshold; S4. Early warning judgment: When the crack width expansion trend exceeds the safety threshold, it is determined that there is a potential risk and a warning is triggered.

6. The monitoring method of the fan-shaped slope crack monitoring system according to claim 5, characterized in that: The local slope inclination analysis includes the following steps: S1, establishing a time series set based on the inclination angle data collected by the inclination sensor, representing the inclination angle of the slope at different times; S2, using time series analysis to predict the inclination of local cracks on the slope; S3. When the predicted inclination of the local cracks on the slope exceeds the warning threshold, the warning mechanism is triggered.

7. The monitoring method of the fan-shaped slope crack monitoring system according to claim 6, characterized in that: The analysis of internal stress changes in slope cracks includes the following steps: S1. Establish the stress state equation; S2. Establish stress observation equation; S3, predicting the stress state at the current moment: predicting the state at the current moment based on the state estimation and control input at the previous moment; S4, prediction covariance: S5, calculating the Kalman gain according to the prediction covariance and the observation matrix; S6, updating the state estimate according to the observed stress value and the Kalman gain; S7, updating the covariance matrix of the state estimate; S8. Early warning judgment: When the predicted stress value exceeds the early warning threshold, the early warning mechanism is triggered.

8. The monitoring method of the fan-shaped slope crack monitoring system according to claim 7, characterized in that: The acoustic wave frequency analysis comprises the following steps: S1. Signal decomposition: Use wavelet basis functions to decompose the sound wave frequency signal into different scales; S2, feature extraction: extract the energy distribution and frequency component characteristics of the signal at each scale; S3, crack identification: judging the existence of cracks based on the changes in characteristics; S4. Quantification of crack degree: quantify the degree of cracks by the amplitude change of the characteristics; S5. Early warning judgment: When the detected crack change degree exceeds the early warning threshold, the early warning mechanism is triggered.

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