Slope stability evaluation method based on micro-seismic signal double-dominant-frequency mechanism characteristics

Abstract

The invention discloses a slope stability evaluation method based on micro-seismic signal double-dominant-frequency mechanism characteristics, and relates to material analysis and application. The method is based on the objective principle that rock acoustic emission dominant frequency characteristics and micro-seismic signal dominant frequency characteristics have consistency and relevance, and the phenomenon of double dominant frequency characteristics existing in acoustic emission tests and micro-seismic monitoring. A rock sample dominant frequency characteristic rule obtained by an acoustic emission test is used for processing micro-seismic signal waveform data obtained by micro-seismic monitoring, so that a dominant frequency characteristic evolution rule of slope rock damage can be obtained through a micro-seismic signal, and the stress condition of the slope rock is more accurately judged based on the dominant frequency characteristic evolution rule; the stability of the slope is evaluated, so that the accuracy of an evaluation result is remarkably improved; the evaluation method combines an acoustic emission test and micro-seismic monitoring, has the advantages of high evaluation accuracy and good universality, and is suitable for large-scale application in monitoring and prevention of geological disasters such as landslide and the like.

Description

Technical Field

[0001] The present invention relates to the field of material analysis and application technology, specifically to the analysis and application technology of rock fracture mechanism, and especially to a slope stability evaluation method based on the dual main frequency mechanism characteristics of microseismic signals. Background Art

[0002] The geological disasters such as collapse caused by the instability of rock slopes not only seriously threaten human life and safety, but also seriously damage infrastructure and affect various engineering activities. Therefore, monitoring unstable rock slopes that may collapse is one of the essential geological disaster prevention and control measures. However, since the collapse of rock slopes usually has the characteristics of wide spread, fast movement speed and high prediction difficulty, it greatly affects the accuracy and timeliness of monitoring. Therefore, in order to better study the collapse mechanism of rock slopes and establish a more accurate and timely disaster warning system, the monitoring method or system of rock slopes needs to be continuously updated and replaced. Microseismic monitoring technology and acoustic emission detection technology are both widely used geophysical detection methods. Among them, microseismic monitoring technology has also been widely used in the monitoring project of unstable rock slopes, and has achieved good warning effects.

[0003] The existing acoustic emission detection technology uses the instantaneous elastic waves generated inside the rock when it is loaded. By collecting and analyzing the elastic waves, the stress state, physical state and failure mode of the rock are studied. It has the advantages of diverse research methods and the ability to deeply study the acoustic emission characteristics of various rocks.

[0004] Microseismic monitoring technology is a technology that uses sensors to collect and acquire seismic wave signals emitted by rock mass damage or rock fracture. It is mainly used to monitor the dynamics of cracks in rock mass in real time. When microcracks appear in rock mass and gradually expand, stress waves will propagate in rock. By real-time collection and analysis of information such as source spatial coordinates, energy and seismic torque from the initiation of cracks in rock to fracture, it is not only helpful to study the mechanism of rock mass damage and fracture, but also can effectively evaluate the stability of deep rock mass. However, there are few studies on the changes of natural rock microfracture spectrum characteristics through microseismic monitoring technology, especially the correspondence between the dual main frequency characteristics of microseismic signals and the rock fracture mechanism. There is still a lack of theoretical and experimental basis, which limits the widespread development and application of this technology. At present, the main application method of microseismic monitoring technology is to evaluate the stability of slopes by analyzing the spatiotemporal coordinates, energy density and magnitude of microseismic events and combining field investigations. However, without the analysis of microseismic waveform data, the frequency characteristics and change laws of rock failure cannot be clearly understood. Therefore, the accuracy of the existing rock slope stability evaluation method based on microseismic signals needs to be further improved. Summary of the invention

[0005] The purpose of the present invention is to overcome the defect of poor evaluation accuracy of the existing rock slope stability evaluation method based on microseismic positioning, and propose a slope stability evaluation method based on the dual main frequency mechanism characteristics of microseismic signals.

[0006] In order to achieve the above-mentioned object of the invention, the present invention provides a slope stability evaluation method based on the dual-main-frequency mechanism characteristics of microseismic signals, comprising the following steps: S1. Acquiring the acoustic emission signals of the monitored slope rock samples during the rupture process under different rupture mechanisms through acoustic emission detection technology, and extracting the main frequency characteristics of the acoustic emission signals of different rupture mechanisms respectively; the rupture mechanisms are divided into tension failure and shear failure; acquiring the microseismic signal waveform data of the monitored slope through microseismic monitoring technology, and extracting the dual main frequency characteristics of the microseismic signal; S2. Based on the consistency and correlation between the main frequency characteristics of the acoustic emission signal and the main frequency characteristics of the microseismic signal, the rupture mechanism corresponding to the dual main frequency characteristics of the microseismic signal is identified; S3. Based on the rupture mechanism corresponding to the dual main frequency characteristics of the microseismic signal, the proportion of the main frequency characteristics of different rupture mechanisms in the dual main frequency characteristics of the microseismic signal within the limited period is counted respectively, and the precursory failure characteristic parameters of the monitored slope are calculated; S4. Determine the stress damage of the monitored slope based on the precursor damage characteristic parameters, so as to evaluate the stability of the slope.

[0007] The invention discloses a slope stability evaluation method based on the dual-main-frequency mechanism characteristics of microseismic signals. Based on the objective principle that the main-frequency characteristics of rock acoustic emission and the main-frequency characteristics of microseismic signals are consistent and correlated, and the dual-main-frequency characteristic phenomenon existing in both acoustic emission tests and microseismic monitoring, the main-frequency characteristic law of rock samples obtained by the acoustic emission test is used to process the microseismic signal waveform data obtained by microseismic monitoring, so that the main-frequency characteristic evolution law (precursor failure characteristic parameter) of slope rock damage can be obtained through the microseismic signal, and the stress condition of the slope rock can be judged more accurately based on the main-frequency characteristic evolution law, and then the stability of the slope is evaluated, so that the accuracy of the evaluation result is significantly improved; the evaluation method combines the acoustic emission test with the microseismic monitoring, has the advantages of high evaluation accuracy and good universality, and is suitable for large-scale application in the monitoring and prevention of geological disasters such as landslides.

[0008] Among them, in step S1, preferably, the specific method for obtaining the main frequency characteristics of the acoustic emission signals of the different fracture mechanisms includes: collecting rock samples of the monitored slope, and obtaining the waveform data of the acoustic emission signals of the rock samples during the tension failure test and the shear failure test by means of the acoustic emission detection technology, and extracting the main frequency characteristics of the acoustic emission signals from the waveform data of the acoustic emission signals, that is, the main frequency characteristics of the acoustic emission signals of the different fracture mechanisms; the main frequency characteristics of the acoustic emission signals are divided into the main frequency characteristics of the tensile failure acoustic emission signals and the main frequency characteristics of the shear failure acoustic emission signals.

[0009] Preferably, the rock sample is the type of rock included in the microseismic monitoring area, and the rock integrity is good; more preferably, the size of the rock sample is Φ50 mm×H100 mm, the height error does not exceed 0.3 mm, and the two end faces are parallel.

[0010] Preferably, the method for extracting the main frequency characteristics of the acoustic emission signal from the waveform data of the acoustic emission signal includes: first performing Hilbert-Huang transform (HHT) on the obtained waveform data, then obtaining a two-dimensional spectrum graph using time-frequency distribution, and finally removing low frequencies, blurring and rasterizing the extreme values ​​of the two-dimensional spectrum graph to obtain the main frequency characteristics of the acoustic emission signal.

[0011] Preferably, the microseismic signal waveform data is collected for no less than 1 year; the longer the collection period, the larger the data, and the more accurate the evaluation result of the slope stability.

[0012] Among them, in step S3, the main frequency characteristics of different rupture mechanisms in the dual main frequency characteristics of the microseismic signal are divided into tensile failure microseismic main frequency characteristics and shear failure microseismic main frequency characteristics.

[0013] Preferably, the statistical method for calculating the proportion of main frequency characteristics of different rupture mechanisms in the dual main frequency characteristics of microseismic signals within a limited period includes: firstly dividing the main frequency range of the microseismic signal into several main frequency bands according to the limited frequency, and then identifying the dual main frequency characteristics of the microseismic signal within the limited period, and counting the proportion of each tension damage microseismic main frequency band and the proportion of each shear damage microseismic main frequency band, and accumulating the proportion of all tension damage microseismic main frequency bands or the proportion of shear damage microseismic main frequency bands to obtain the proportion of tension damage microseismic main frequency characteristics or the proportion of shear damage microseismic main frequency characteristics.

[0014] Preferably, the limited frequency is confirmed and adjusted according to the magnitude of the main frequency of the microseismic signal, so as to better distinguish the main frequency breaks of tensile damage microseismic signals from the main frequency breaks of shear damage microseismic signals.

[0015] Preferably, the main frequency range is confirmed and adjusted according to the microseismic signal generation environment to better divide the main frequency bands and ensure the rationality of the statistical analysis of the proportion of the main frequency breaks of tensile damage microseismic breaks or the main frequency breaks of shear damage microseismic breaks.

[0016] Preferably, the limited period is determined according to the geological conditions of the monitored slope and is generally set to 1 month.

[0017] Among them, preferably, the precursory damage characteristic parameters include a first parameter and a second parameter; the first parameter is the ratio of the proportion of tension damage microseismic main frequency characteristics to the proportion of shear damage microseismic main frequency characteristics in the dual main frequency characteristics of the microseismic signal within a limited period; the second parameter is the difference between the proportion of tension damage microseismic main frequency characteristics in the dual main frequency characteristics of the microseismic signal in the previous limited period and the proportion of tension damage microseismic main frequency characteristics in the dual main frequency characteristics of the microseismic signal in the next limited period.

[0018] Among them, in step S4, preferably, the judgment standard of the stress damage situation is: when the first parameter is greater than 1, it means that the monitored slope is mainly damaged by tension; when the first parameter is less than 1, it means that the monitored slope is mainly damaged by shear, indicating that the rock damage mode has changed and special attention should be paid; when the first parameter is equal to 1, it means that the monitored slope is subjected to the combined action of tension and shear damage.

[0019] Preferably, the evaluation criteria for slope stability are: when the monitored slope is mainly subjected to tension and the second parameter is greater than 0.15, it means that damage has occurred inside the rock mass of the monitored slope and the damage is relatively large, there may be a risk of landslide, and the slope stability is reduced.

[0020] Preferably, the slope stability evaluation method based on the dual-main-frequency mechanism characteristics of microseismic signals also includes step S5, identifying and locating the damaged area of ​​the slope according to the stability evaluation result, combined with the event excitation number, positioning data, energy density and magnitude obtained by the microseismic monitoring technology and the field verification results; combined with step S5, the stability of the slope can be comprehensively evaluated so as to better realize the monitoring and prevention of geological disasters.

[0021] Compared with the prior art, the present invention has the following beneficial effects: 1. The slope stability evaluation method of the present invention uses the main frequency characteristic law of rock samples obtained by acoustic emission test to process the microseismic signal waveform data obtained by microseismic monitoring, so that the main frequency characteristic evolution law of slope rock failure (precursor failure characteristic parameter) can be obtained through microseismic signals, and the stress condition of the slope rock can be judged more accurately based on the main frequency characteristic evolution law, and then the stability of the slope can be evaluated, so that the accuracy of the evaluation result is significantly improved.

[0022] 2. The slope stability evaluation method of the present invention combines acoustic emission test and microseismic monitoring, and has the advantages of high evaluation accuracy and good universality, and is suitable for large-scale application in the monitoring and prevention of geological disasters such as landslides. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1is a flow chart of the slope stability evaluation method in Example 1 of the present invention; Figure 2 This is a diagram showing the change in tension-shear ratio of rock samples under different stress conditions in Example 1 of the present invention; Figure 3 Statistical diagram of dual main frequency characteristics of acoustic emission of different rock samples in Example 1 of the present invention (a is sample b1; b is sample b2); Figure 4 This is a schematic diagram of the arrangement of the microseismic monitoring system in Example 1 of the present invention; Figure 5 Statistical graphs of dual main frequency characteristics of microseismic signals in some months in Example 1 of the present invention (a is May 2021; b is March 2022); Figure 6 This is a moment tensor theory analysis diagram drawn according to the dual main frequency characteristics of the microseismic signal in Example 1 of the present invention (a is a proportion diagram of the main frequency characteristics of different rupture mechanisms; b is a corresponding relationship diagram between the moment tensor theory and the main frequency characteristics); Figure 7 The tension-shear ratio variation trend diagram drawn according to the dual main frequency characteristics of the microseismic signal in Example 1 of the present invention; Figure 8 The sliding surface prediction map and instability photo (a is the prediction map; b is the instability photo) are obtained according to the dual main frequency characteristics of the seismic signal in Example 1 of the present invention. DETAILED DESCRIPTION

[0024] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. However, it should not be understood that the scope of the above subject matter of the present invention is limited to the following embodiments, and all technologies realized based on the content of the present invention belong to the scope of the present invention.

[0025] Embodiment 1: The stability of the Baige slope is determined by a slope stability evaluation method based on the dual-dominant frequency mechanism characteristics of microseismic signals (see the flowchart for Figure 1 ), and predict the landslide situation of the slope. The specific steps are as follows: S1. Collect rock samples from the monitored slope (the integrity of the rock should be good; the size of the rock should be made into a standard rock sample of Φ50 mm×H100 mm, and the height error of the rock should not exceed 0.3 mm, and the two end faces should be parallel), and conduct an acoustic emission experiment (using uniaxial compression + acoustic emission instrument, and the test adopts closed-loop displacement control, first apply a force of 0.5 KN to make the top of the instrument fit the test sample, and then apply 0.2 KN / min until the sample is completely destroyed. The acoustic emission instrument and the rock sample should be fitted with a coupling agent; 4 sensors are attached to the upper and lower parts of the rock, 10 mm away from the upper and lower ends, and the upper and lower sensors are crossed at an angle of 45°. The sensors are tightly attached to the rock surface with coupling agents such as vaseline and tape to meet their accuracy requirements), and the waveform data of the acoustic emission signal of the rock sample during the tension failure test and the shear failure test are recorded in real time, and the low main frequency characteristics of the tensile failure acoustic emission and the high main frequency characteristics of the shear failure acoustic emission are extracted from the waveform data of the acoustic emission signal; according to the main frequency characteristics of the acoustic emission, a tension-shear ratio change diagram of the rock sample under different stress conditions is drawn ( Figure 2 ) and the dual main frequency characteristics of different rock samples ( Figure 3 ); Through the microseismic monitoring system (composed of detectors, data acquisition instruments, signal processors, communication systems and analysis and processing software; a field monitoring station was established at a safe location on the top of the Baige slope, and the microseismic system equipment was arranged. The monitoring station is equipped with 4 three-component detectors (G1-G4), 2 data acquisition instruments, 1 signal processor and 1 4G router. It is powered by 2 solar panels and 1 UPS battery; the arrangement is as follows Figure 4 As shown in the figure, the microseismic signal waveform data of the monitored slope is obtained (time period: May 2021 to July 2022; it needs to be separately transcoded into ASCII code), and the dual main frequency characteristics of the microseismic signal are extracted; The method of extracting the main frequency feature from the waveform data includes: firstly performing Hilbert-Huang transform (HHT) on the obtained waveform data, then obtaining a two-dimensional spectrum graph using time-frequency distribution, and finally performing low-frequency removal, fuzzification and gridding extreme value processing on the two-dimensional spectrum graph to obtain the main frequency feature; S2. Based on the consistency and correlation between the main frequency characteristics of the acoustic emission signal and the main frequency characteristics of the microseismic signal, the rupture mechanism corresponding to the dual main frequency characteristics of the microseismic signal is identified; S3. Based on the rupture mechanism corresponding to the dual main frequency characteristics of the microseismic signal, the proportion of the main frequency characteristics of different rupture mechanisms in the dual main frequency characteristics of the microseismic signal within the limited period (1 month) is counted respectively (first, the main frequency range of the microseismic signal is divided into several main frequency bands according to the limited frequency (10Hz), and then the dual main frequency characteristics of the microseismic signal within the limited period are identified, and the proportion of each tension damage microseismic main frequency band and the proportion of each shear damage microseismic main frequency band are counted. By accumulating the proportion of all tension damage microseismic main frequency bands or shear damage microseismic main frequency proportions, the proportion of tension damage microseismic main frequency characteristics or the proportion of shear damage microseismic main frequency characteristics are obtained), and drawn into a graph ( Figure 5 ), calculate the precursory damage characteristic parameters of the monitored slope, and count the proportion of main frequency characteristics of different rupture mechanisms and precursory damage characteristic parameters (Table 1; the precursory damage characteristic parameters include the first parameter and the second parameter; the first parameter is the ratio of the proportion of tension damage microseismic main frequency characteristics to the proportion of shear damage microseismic main frequency characteristics in the dual main frequency characteristics of the microseismic signal within a limited period; the second parameter is the difference between the proportion of tension damage microseismic main frequency characteristics in the dual main frequency characteristics of the microseismic signal in the previous limited period and the proportion of tension damage microseismic main frequency characteristics in the dual main frequency characteristics of the microseismic signal in the next limited period); S4. Determine the stress condition of the monitored slope based on the precursor failure characteristic parameters, and draw a moment tensor theory analysis diagram based on this. Figure 6 ) and the trend diagram of tension shear ratio change ( Figure 7 ); thus evaluating the slope stability; S5. Based on the stability evaluation results, the number of event excitations, positioning data, energy density and magnitude obtained by microseismic monitoring technology are combined to identify and locate the damaged area of ​​the slope and obtain a sliding surface prediction map ( Figure 8 a), and collected instability photos on site ( Figure 8 b).

[0026] Table 1 The proportion of main frequency characteristics of different rupture mechanisms and the statistical table of precursor failure characteristic parameters of Baige slope month Main frequency characteristic ratio of tensile damage microseismic The main frequency characteristic ratio of shear failure microseismic First parameter Second parameter 21 / 05 28.04% 71.96% 0.39 / 21 / 06 32.06% 67.94% 0.47 4.02% 21 / 07 22.82% 77.18% 0.30 9.24% 21 / 08 36.83% 63.17% 0.58 14.01% 21 / 09 27.11% 72.89% 0.37 9.72% 21 / 10 22.66% 77.34% 0.29 4.45% 21 / 11 13.86% 86.14% 0.16 8.80% 21 / 12 11.56% 88.44% 0.13 2.30% 22 / 01 16.65% 83.35% 0.20 5.09% 22 / 02 13.70% 86.30% 0.16 2.95% 22 / 03 22.82% 77.18% 0.30 9.12% 22 / 04 76.15% 23.85% 3.19 53.33% 22 / 05 91.89% 8.11% 11.33 15.74% 22 / 06 58.88% 41.12% 1.43 33.01% 22 / 07 94.96% 5.04% 18.84 36.08% Stability evaluation analysis: analyze Figure 2 It can be seen that in the direct tensile test, the rock samples are mainly tensile fractured with low RA values ​​and high AF values ​​in the elastic and yield stages. As the stress increases, more shear fractures with high RA values ​​and low AF values ​​begin to occur in the strengthening stage until the sample is destroyed. The proportion of shear cracks gradually increases, but overall, tensile fractures are far more than shear fractures.

[0027] analyze Figure 3 It can be seen that the rock acoustic emission signal has a dual main frequency characteristic band phenomenon, in which the high and low main frequency bands range from 200 to 230 kHz and 30 to 90 kHz.

[0028] analyze Figure 5 It can be seen that the microseismic signal of Baige landslide has a double main frequency characteristic band phenomenon, in which the high and low main frequency bands range from 210 to 250 Hz and 31 to 70 Hz.

[0029] analyze Figure 6 It can be seen that the microscopic rupture mechanism of the rock mass reflected by the microseismic signal of the Baige landslide is mainly shear failure, which changes significantly with time. The microseismic signals at the rear edge of the Baige landslide were mainly high-frequency signals before March 2022, indicating that the microscopic rupture inside the slope was mainly shear failure, while from March to July 2022, they were mainly low-frequency signals, indicating that the internal rupture mechanism of the slope has changed, and it is mainly tensile failure.

[0030] Combination Figure 2 , Figure 3 , Figure 5 and Figure 6 It can be concluded that there is consistency and correlation between the main frequency characteristics of the acoustic emission signal and the main frequency characteristics of the microseismic signal. Both the acoustic emission signal and the microseismic signal show a dual main frequency phenomenon, and the low main frequency corresponds to tension failure, and the high main frequency corresponds to shear failure. The tension-shear ratio of the internal fracture of the rock changes greatly, and the stability of the slope can be further explained by calculating the precursor failure characteristic parameters.

[0031] analyze Figure 7 As can be seen from Table 1, the main frequency ratio of the Baige landslide changes from shear failure at the beginning to tension failure. The first parameter of the precursory failure characteristic parameter changes in April 2022. Its value is greater than 1, indicating that the tension shear failure mode has changed. The larger the value, the more serious the internal damage of the rock. The second parameter of the precursory failure characteristic parameter represents the comparison with the proportion of the previous month. It is generally believed that its value exceeds 15%, indicating that a rupture has occurred inside the rock mass. Combined with the change in the value of the first parameter of the precursory failure characteristic parameter, when the tension shear mode of the rock mass changes, it changes from the original shear failure to tension failure faster. The value of the second parameter of the precursory failure characteristic parameter changes by about 30%, and the change is more rapid, which means that when the precursor feature appears, it just corresponds to the internal damage of the rock mass, and the degree of damage is getting more and more serious.

[0032] The third landslide of Baige landslide (November 30, 2022) was verified based on the precursory damage characteristic parameters. Combined with the change in the tension-shear state of the rock in April 2022, it indicates that a large rupture occurred in the internal rock mass, which may have generated a sliding surface. The rapid change in the tension-shear ratio in the following months indicates that the degree of internal rock mass rupture is high. By comparing and analyzing the data of microseismic monitoring and on-site investigation and analysis (such as Figure 8 a and Figure 8b) all indicate that when the rock tension-shear failure mode changes, the stability of the slope begins to decrease. The location of the sliding surface is identified through the precursory characteristic area. From the development of the sliding surface to its complete penetration, and finally to the instability of the slope, it is shown that the method of the present invention can identify the sliding surface in advance and can also make a more accurate evaluation of the stability of the slope.

Claims

1. A slope stability evaluation method based on the dual-dominant frequency mechanism characteristics of microseismic signals, characterized in that: The following steps are involved: S1. Acquiring the acoustic emission signals of the monitored slope rock samples during the fracture process under different fracture mechanisms through acoustic emission detection technology, and extracting the main frequency characteristics of the acoustic emission signals of different fracture mechanisms respectively; The rupture mechanisms are divided into tension failure and shear failure; The microseismic signal waveform data of the monitored slope is obtained through microseismic monitoring technology, and the dual main frequency characteristics of the microseismic signal are extracted; S2. Based on the consistency and correlation between the main frequency characteristics of the acoustic emission signal and the dual main frequency characteristics of the microseismic signal, the rupture mechanism corresponding to the dual main frequency characteristics of the microseismic signal is identified; S3. Based on the rupture mechanism corresponding to the dual main frequency characteristics of the microseismic signal, the proportions of the main frequency characteristics of different rupture mechanisms in the dual main frequency characteristics of the microseismic signal within a limited period are respectively counted, and the precursory damage characteristic parameters of the monitored slope are calculated; the precursory damage characteristic parameters include a first parameter and a second parameter; the first parameter is the ratio of the proportion of the tension damage microseismic main frequency characteristics to the proportion of the shear damage microseismic main frequency characteristics in the dual main frequency characteristics of the microseismic signal within a limited period; the second parameter is the difference between the proportion of the tension damage microseismic main frequency characteristics in the dual main frequency characteristics of the microseismic signal within the previous limited period and the proportion of the tension damage microseismic main frequency characteristics in the dual main frequency characteristics of the microseismic signal within the next limited period; S4. Determine the stress damage of the monitored slope based on the precursor damage characteristic parameters, so as to evaluate the stability of the slope.

2. The slope stability evaluation method according to claim 1, characterized in that: In step S1, the specific method for obtaining the main frequency characteristics of the acoustic emission signal of different fracture mechanisms includes: collecting rock samples of the monitored slope, and obtaining the waveform data of the acoustic emission signal of the rock sample during the tension failure test and the shear failure test by the acoustic emission detection technology, and extracting the main frequency characteristics of the acoustic emission signal from the waveform data of the acoustic emission signal, that is, the main frequency characteristics of the acoustic emission signal of different fracture mechanisms.

3. The slope stability evaluation method according to claim 2, characterized in that: The main frequency characteristics of the acoustic emission signal are divided into main frequency characteristics of tensile failure acoustic emission and main frequency characteristics of shear failure acoustic emission.

4. The slope stability evaluation method according to claim 2, characterized in that: The method for extracting the main frequency characteristics of the acoustic emission signal from the waveform data of the acoustic emission signal includes: firstly performing Hilbert-Huang transform on the obtained waveform data, then obtaining a two-dimensional spectrum diagram using time-frequency distribution, and finally performing low-frequency removal, fuzzification and gridding extreme value processing on the two-dimensional spectrum diagram to obtain the main frequency characteristics of the acoustic emission signal.

5. The slope stability evaluation method according to claim 1, characterized in that: In step S1, the microseismic signal waveform data is collected for a period of no less than 1 year.

6. The slope stability evaluation method according to claim 1, characterized in that: In step S3, the main frequency characteristics of different rupture mechanisms in the dual main frequency characteristics of the microseismic signal are divided into the main frequency characteristics of tensile failure microseismic signal and the main frequency characteristics of shear failure microseismic signal.

7. The slope stability evaluation method according to claim 1, characterized in that: In step S3, the statistical method for calculating the proportion of main frequency characteristics of different rupture mechanisms in the dual main frequency characteristics of microseismic signals within a limited period includes: firstly dividing the main frequency range of the microseismic signal into a number of main frequency bands according to the limited frequency, and then identifying the dual main frequency characteristics of the microseismic signal within the limited period, and counting the proportion of each tension damage microseismic main frequency band and the proportion of each shear damage microseismic main frequency band, and accumulating the proportion of all tension damage microseismic main frequency bands or the proportion of shear damage microseismic main frequency bands to obtain the proportion of tension damage microseismic main frequency characteristics or the proportion of shear damage microseismic main frequency characteristics.

8. The slope stability evaluation method according to claim 1, characterized in that: In step S4, the judgment criteria for the stress damage situation are: when the first parameter is greater than 1, it means that the monitored slope is mainly damaged by tension; when the first parameter is less than 1, it means that the monitored slope is mainly damaged by shear, indicating that the rock damage mode has changed and special attention should be paid; when the first parameter is equal to 1, it means that the monitored slope is affected by the combined effects of tension and shear damage.

9. The slope stability evaluation method according to claim 1, characterized in that: The evaluation criteria for slope stability are as follows: when the monitored slope is mainly subjected to tension and the second parameter is greater than 0.15, it means that damage has occurred inside the rock mass of the monitored slope and the damage is severe, there may be a risk of landslide, and the slope stability is reduced.

10. The slope stability evaluation method according to any one of claims 1 to 9, characterized in that: The method further includes step S5, identifying and locating the damaged area of ​​the slope according to the stability evaluation result, the number of event excitations, the positioning data, the energy density and the magnitude obtained by the microseismic monitoring technology and the field verification result.

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