Dangerous rock mass stability evaluation method and system based on amplitude ratio and frequency ratio

Abstract

The invention discloses a dangerous rock mass stability evaluation method and system based on an amplitude ratio and a frequency ratio, and relates to the technical field of geological disaster risk assessment, and the method comprises the steps: collecting dangerous rock three-way vibration data and bed rock three-way vibration data in the same time interval; the dangerous rock three-dimensional vibration data and the bedrock three-dimensional vibration data are synthesized into dangerous rock one-dimensional amplitude data and bedrock one-dimensional amplitude data respectively, and the ratio of the dangerous rock amplitude standard deviation to the bedrock amplitude standard deviation is calculated to obtain an amplitude ratio; calculating the ratio of the dangerous rock peak frequency to the bedrock peak frequency to obtain a frequency ratio; and inputting the amplitude ratio and the frequency ratio as inputs into a trained dangerous rock mass stability evaluation model, and identifying the stable state of the dangerous rock mass. According to the method, the problem that the accuracy of a stability evaluation result is insufficient due to excitation and equipment temperature drift in dangerous rock mass vibration monitoring in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of geological hazard risk assessment technology, and in particular to a method and system for evaluating the stability of unstable rock masses based on amplitude ratio and frequency ratio. Background Technology

[0002] Because unstable rock masses fall freely down steep slopes during landslides, and due to the large speed and scale of rock fragment detachment, their identification and stability assessment are typically more difficult than other types of geological hazards, thus posing greater risks and damage. Current methods for analyzing the stability of unstable rock masses still have many shortcomings. Most stability assessment methods are based on external factors (morphological characteristics, structural plane combinations, and spatial distribution), neglecting the intrinsic properties of the unstable rock mass. Deformation-based analysis methods (tilt angle, tilt direction, fracture opening) are mostly suitable for slopes with creep characteristics, but their effectiveness in assessing the brittle failure stability of rock masses with rigid structural planes is poor.

[0003] In recent years, stability analysis methods based on dynamic characteristics have gradually attracted attention. However, current evaluation methods for dynamic indicators mostly only monitor the vibration characteristics of the unstable rock mass itself. Under complex environmental excitation scenarios (such as traffic, strong winds, construction disturbances, etc.), the vibration characteristics of the unstable rock mass fluctuate greatly due to changes in environmental excitation. In addition, vibration sensors in high temperature difference environments often experience fluctuations in monitoring data due to the "temperature drift" of the equipment itself, affecting the accuracy of the dynamic evaluation results. Summary of the Invention

[0004] To address the aforementioned technical problems in existing technologies, this invention provides a method and system for evaluating the stability of unstable rock masses based on amplitude ratio and frequency ratio. The technical solution is as follows:

[0005] On the one hand, a method for evaluating the stability of unstable rock masses based on amplitude ratio and frequency ratio is provided. The method includes: collecting triaxial vibration data of unstable rock and triaxial vibration data of bedrock within the same time interval; synthesizing the triaxial vibration data of unstable rock and triaxial vibration data of bedrock into one-dimensional amplitude data of unstable rock and one-dimensional amplitude data of bedrock, respectively, and calculating the standard deviation of the amplitude of unstable rock and the standard deviation of the amplitude of bedrock; calculating the ratio of the standard deviation of unstable rock amplitude to the standard deviation of bedrock amplitude to obtain the amplitude ratio; and calculating the ratio of the peak frequency of unstable rock to the peak frequency of bedrock based on the one-dimensional amplitude data of unstable rock and one-dimensional amplitude data of bedrock to obtain the frequency ratio; and inputting the amplitude ratio and the frequency ratio as inputs into a trained unstable rock mass stability evaluation model to identify the stable state of unstable rock mass.

[0006] Optionally, the calculation formula for the one-dimensional amplitude data of the unstable rock or the one-dimensional amplitude data of the bedrock, and the calculation formula for the standard deviation of the amplitude of the unstable rock or the standard deviation of the amplitude of the bedrock, include: In the formula, A i Let (x, y, z) be the i-th data point in the one-dimensional amplitude data of the unstable rock or the one-dimensional amplitude data of the bedrock, and let (x, y, z) be the triaxial vibration data of the unstable rock or the triaxial vibration data of the bedrock. The standard deviation of the amplitude of the dangerous rock or the standard deviation of the amplitude of the bedrock is given, where N is the total number of data points. It is the absolute mean of the one-dimensional amplitude data of the dangerous rock or the absolute mean of the one-dimensional amplitude data of the bedrock.

[0007] Optionally, based on the one-dimensional amplitude data of the unstable rock and the one-dimensional amplitude data of the bedrock, the frequency ratio is obtained by calculating the ratio of the peak frequency of the unstable rock to the peak frequency of the bedrock, including: converting the time-domain curves of the one-dimensional amplitude data of the unstable rock and the one-dimensional amplitude data of the bedrock in the direction perpendicular to the fracture into frequency curves based on Fourier transform, and determining the peak frequency of the unstable rock and the peak frequency of the bedrock respectively; calculating the ratio of the peak frequency of the unstable rock to the peak frequency of the bedrock to obtain the frequency ratio.

[0008] Optionally, the method further includes: training the PSO-SVM model based on the rock vibration index dataset to obtain a trained rock mass stability evaluation model.

[0009] On the other hand, a rock mass stability evaluation system based on amplitude ratio and frequency ratio is also provided to implement the rock mass stability evaluation method based on amplitude ratio and frequency ratio provided in the embodiments of the present invention. The system includes: a data acquisition module, a first calculation module, a second calculation module, and an evaluation module. The data acquisition module is used to acquire three-dimensional vibration data of the rock mass and three-dimensional vibration data of the bedrock within the same time interval. The first calculation module is used to synthesize the three-dimensional vibration data of the rock mass and the three-dimensional vibration data of the bedrock into one-dimensional amplitude data of the rock mass and one-dimensional amplitude data of the bedrock. The first module is used to obtain the amplitude ratio by calculating the standard deviation of the one-dimensional amplitude data of the dangerous rock and the standard deviation of the one-dimensional amplitude data of the bedrock; the second calculation module is used to calculate the amplitude ratio by calculating the ratio of the standard deviation of the amplitude of the dangerous rock to the standard deviation of the amplitude of the bedrock, and to calculate the frequency ratio by calculating the ratio of the peak frequency of the dangerous rock to the peak frequency of the bedrock based on the one-dimensional amplitude data of the dangerous rock and the one-dimensional amplitude data of the bedrock; the evaluation module is used to input the amplitude ratio and the frequency ratio as inputs into the trained dangerous rock mass stability evaluation model to identify the stability state of the dangerous rock mass.

[0010] Optionally, the system further includes a training module for training the PSO-SVM model based on a rock vibration index dataset to obtain a trained rock mass stability evaluation model.

[0011] On the other hand, an electronic device is also provided, including: a memory, a processor, and a computer program stored on the memory and running on the processor, wherein the processor executes the computer program to implement the method provided in the embodiments of the present invention.

[0012] On the other hand, a computer-readable storage medium is also provided, wherein program code is stored in the computer-readable storage medium, and the program code can be called by a processor to execute the method provided in the embodiments of the present invention.

[0013] This invention provides a method and system for evaluating the stability of unstable rock masses based on amplitude ratio and frequency ratio. It uses the same sensing equipment to simultaneously record the vibration characteristics of unstable rock and bedrock under the same environmental excitation. Focusing on the differences in vibration characteristics between bedrock and unstable rock, it improves the stability of the indicators by analyzing the relative ratios of the vibration characteristics of unstable rock and bedrock under the same environmental excitation. Furthermore, it combines support vector machine and particle swarm optimization algorithms to study the stability analysis method for falling unstable rock masses, alleviating the problem of insufficient accuracy in stability evaluation results caused by vibration monitoring and equipment temperature drift. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a flowchart of a method for evaluating the stability of unstable rock masses based on amplitude ratio and frequency ratio, provided by an embodiment of the present invention; Figure 2 This is a schematic diagram of a falling rock mass model provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the spatial amplitude ratio as a function of cutting depth, provided by an embodiment of the present invention. Figure 4 This is a graph showing the prediction results of the PSO-SVM training set and test set provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the stability classification results of falling rock masses based on amplitude ratio-frequency ratio provided in an embodiment of the present invention; Figure 6This is a schematic diagram of a rock mass stability evaluation system based on amplitude ratio and frequency ratio provided in an embodiment of the present invention. Detailed Implementation

[0016] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0017] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0018] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0019] Example 1 Figure 1 This is a flowchart of a method for evaluating the stability of unstable rock masses based on amplitude ratio and frequency ratio, provided by an embodiment of the present invention. Figure 1 As shown, the method specifically includes the following steps:

[0020] Step S102: Collect triaxial vibration data of the unstable rock and the bedrock within the same time interval.

[0021] Specifically, triaxial vibration sensors were deployed on the unstable rock and the bedrock respectively to collect triaxial vibration data of the unstable rock and the bedrock within the same time interval.

[0022] Step S104: Combine the three-dimensional vibration data of the unstable rock and the three-dimensional vibration data of the bedrock into one-dimensional amplitude data of the unstable rock and one-dimensional amplitude data of the bedrock, respectively, and calculate the standard deviation of the unstable rock amplitude data and the standard deviation of the bedrock amplitude data of the one-dimensional amplitude data of the bedrock.

[0023] Specifically, using the spatial Euclidean distance calculation formula, the calculation formulas for the one-dimensional amplitude data of the unstable rock or the one-dimensional amplitude data of the bedrock are calculated respectively, along with the standard deviation of the unstable rock amplitude or the standard deviation of the bedrock amplitude: In the formula, A i is the i-th data point in the one-dimensional amplitude data of the unstable rock or the one-dimensional amplitude data of the bedrock, and is the distance from the origin; (x, y, z) represents the triaxial vibration data of the unstable rock or the triaxial vibration data of the bedrock. The standard deviation of the amplitude of the unstable rock or the standard deviation of the amplitude of the bedrock is given, where N is the total number of data points. It represents the absolute mean of the one-dimensional amplitude data of the unstable rock or the absolute mean of the one-dimensional amplitude data of the bedrock.

[0024] Step S106: Calculate the amplitude ratio by the ratio of the standard deviation of the unstable rock amplitude to the standard deviation of the bedrock amplitude, and calculate the frequency ratio by the ratio of the peak frequency of the unstable rock to the peak frequency of the bedrock based on the one-dimensional amplitude data of the unstable rock and the one-dimensional amplitude data of the bedrock.

[0025] Specifically, the ratio of the standard deviation of rock amplitude to the standard deviation of bedrock amplitude is defined as the amplitude ratio: In the formula: R is the amplitude ratio, a is the standard deviation of bedrock amplitude, and b is the standard deviation of dangerous rock amplitude.

[0026] Specifically, the frequency ratio is calculated as follows: Based on Fourier transform, the time-domain curves of the one-dimensional amplitude data of the unstable rock and the one-dimensional amplitude data of the bedrock in the direction of vertical fracture are transformed into frequency curves, and the peak frequency of the unstable rock and the peak frequency of the bedrock are determined respectively. The frequency ratio is obtained by calculating the ratio of the peak frequency of the unstable rock to the peak frequency of the bedrock.

[0027] The formula for calculating the frequency ratio includes: In the formula, λ is the frequency ratio. The peak frequency of bedrock. This represents the peak frequency of the unstable rock formation.

[0028] Step S108: Input the amplitude ratio and frequency ratio as inputs into the trained unstable rock mass stability evaluation model to identify the stable state of the unstable rock mass.

[0029] Specifically, the method provided in this embodiment of the invention further includes: The PSO-SVM model was trained based on the unstable rock vibration index dataset to obtain a trained unstable rock mass stability evaluation model.

[0030] The PSO-SVM model is a hybrid machine learning method that combines Particle Swarm Optimization (PSO) and Support Vector Machine (SVM), primarily used to improve the performance of classification or regression tasks. Its core idea is to optimize key parameters of the SVM (such as the kernel parameter γ and the penalty coefficient C) using the PSO algorithm, thereby overcoming the inefficiency of traditional grid search methods and improving the model's generalization ability.

[0031] This invention provides a method for evaluating the stability of unstable rock masses based on amplitude ratio and frequency ratio. It uses the same sensing equipment to simultaneously record the vibration characteristics of unstable rock and bedrock under the same environmental excitation. Focusing on the differences in vibration characteristics between bedrock and unstable rock, the method improves the stability of the index by analyzing the relative ratios of vibration characteristics of unstable rock and bedrock under the same environmental excitation. Furthermore, it combines support vector machine and particle swarm optimization algorithms to study the stability analysis method for falling unstable rock masses, thus alleviating the problem of insufficient accuracy in stability evaluation results caused by vibration monitoring and equipment temperature drift.

[0032] Example 2 In an optional embodiment provided by the present invention, the vibration of the rock mass in the direction perpendicular to the joint surface, when the bedrock by During vibration, the unstable rock mass The vibration has the following expression: In the formula, The quality of the unstable rock mass; and bedrock Displacement and unstable rock mass The displacement; The stiffness of the bonded section; Damping for the bonded section.

[0033] Solving the above equation, we can obtain amplitude for: In the formula: λ represents the damping ratio of the unstable rock mass, and λ is the frequency ratio of the peak frequency of the unstable rock mass to the peak frequency of the bedrock. .

[0034] When vibration is transmitted from the bedrock to the unstable rock mass, the unstable rock mass will rapidly reach its maximum response. During this process, because the dampers in the jointed sections absorb relatively little energy from the vibration system, the damping effect of the joints can be ignored, and the vibration of the unstable rock mass can be simplified to undamped forced vibration. Under these conditions, the frequency ratio and amplitude ratio of the unstable rock mass to the bedrock can be expressed as:

[0035] The amplitude ratio and frequency ratio are significantly correlated with the stability of unstable rock masses. The amplitude ratio is approximately inversely proportional to stiffness; as stiffness increases, the vibration amplitudes of the unstable rock and bedrock tend to be consistent, and the amplitude ratio approaches 1. The vibration characteristics of the bedrock on the slope are long-period ground pulsations, and the natural frequency can be considered a stable constant. Therefore, as the degree of instability of the unstable rock mass increases, the stiffness k of the structural surface decreases, and the frequency ratio decreases exponentially.

[0036] Design a collapse-like model test, using a falling rock mass as the research object, and fix the model to the ground, such as... Figure 2 As shown, the model's trailing edge crack was pre-cut to a position of 13cm. After cutting, it was left to stand for 3 minutes, then white noise excitation was activated, and vibration data of the unstable rock mass model in the X, Y, and Z directions under environmental vibration were recorded. Each data acquisition lasted for 10 minutes. Each time, the model was cut downwards by 1cm, left to stand for 3 minutes, and then data was collected again for 10 minutes until the model became unstable.

[0037] The curve of spatial amplitude ratio as a function of cutting depth is shown below. Figure 3 As shown, the index exhibits a step phenomenon when the cutting fissure depth is 16cm to 17cm and 19cm to 20cm. The frequency of the unstable rock decreases from 176Hz to 129Hz, and the bedrock frequency stabilizes. The frequency ratio shows a step phenomenon after the fissure cutting depth reaches 16cm.

[0038] A total of 24 sets of stable rock mass data were collected. Rock mass with a fracture depth greater than 17cm was marked as understability. This invention randomly selected 16 sets of data as training data and the remaining 8 sets of data as test data, as shown in Table 1, which is the PSO-SVM training and test dataset.

[0039] Table 1. PSO-SVM Training and Testing Datasets Figure 4 This is a prediction result diagram of the PSO-SVM training set and test set provided according to an embodiment of the present invention. In this dataset, the basic stable state of the unstable rock mass is preset to 0, and the understability state is preset to 1. In the 8 sets of data in the test set, the error rate of the PSO-SVM classification prediction model is 0, which indicates that the model can accurately distinguish between the basic stable state and the understability state of the unstable rock mass after training.

[0040] Figure 5 This is a schematic diagram illustrating the stability classification results of a falling rock mass based on amplitude ratio-frequency ratio, according to an embodiment of the present invention. Figure 5 As shown, the frequency ratio is set as the X-axis, the amplitude ratio is set as the Y-axis, and the classification line P represents the hyperplane constructed by SVM, which divides the dataset into two regions: the region below the hyperplane is the basically stable region, and the region above the hyperplane is the understable region.

[0041] Example 3 Figure 6 This is a schematic diagram of a rock mass stability evaluation system based on amplitude ratio and frequency ratio according to an embodiment of the present invention, used to implement the rock mass stability evaluation method based on amplitude ratio and frequency ratio provided in the embodiment of the present invention. Figure 6As shown, the system includes: a data acquisition module 10, a first calculation module 20, a second calculation module 30, and an evaluation module 40.

[0042] Specifically, the acquisition module 10 is used to acquire triaxial vibration data of dangerous rock and triaxial vibration data of bedrock within the same time interval; The first calculation module 20 is used to synthesize the three-dimensional vibration data of the unstable rock and the three-dimensional vibration data of the bedrock into one-dimensional amplitude data of the unstable rock and one-dimensional amplitude data of the bedrock, respectively, and to calculate the standard deviation of the unstable rock amplitude data and the standard deviation of the bedrock amplitude data of the one-dimensional amplitude data of the bedrock. The second calculation module 30 is used to calculate the amplitude ratio by comparing the standard deviation of the unstable rock amplitude with the standard deviation of the bedrock amplitude, and to calculate the frequency ratio by comparing the peak frequency of the unstable rock with the peak frequency of the bedrock based on the one-dimensional amplitude data of the unstable rock and the one-dimensional amplitude data of the bedrock. Evaluation module 40 is used to input the amplitude ratio and frequency ratio as inputs into the trained unstable rock mass stability evaluation model to identify the stable state of the unstable rock mass.

[0043] Specifically, such as Figure 6 As shown, the system also includes a training module 50, which is used to train the PSO-SVM model based on the rock vibration index dataset to obtain a trained rock mass stability evaluation model.

[0044] The present invention also provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and running on the processor, wherein the processor executes the computer program to implement the method provided in the embodiments of the present invention.

[0045] The present invention also provides a computer-readable storage medium storing program code, which can be called by a processor to execute the method provided in the embodiments of the present invention.

[0046] It should be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0047] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0048] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0049] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0050] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0051] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0052] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0053] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0054] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0055] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for evaluating the stability of unstable rock masses based on amplitude ratio and frequency ratio, characterized in that, The method includes: Collect triaxial vibration data of unstable rock and bedrock within the same time interval; The three-dimensional vibration data of the unstable rock and the three-dimensional vibration data of the bedrock are synthesized into one-dimensional amplitude data of the unstable rock and one-dimensional amplitude data of the bedrock, respectively. The standard deviation of the unstable rock amplitude data and the standard deviation of the bedrock amplitude data of the one-dimensional amplitude data of the bedrock are calculated. The amplitude ratio is obtained by calculating the ratio of the standard deviation of the unstable rock amplitude to the standard deviation of the bedrock amplitude, and the frequency ratio is obtained by calculating the ratio of the peak frequency of the unstable rock to the peak frequency of the bedrock based on the one-dimensional amplitude data of the unstable rock and the one-dimensional amplitude data of the bedrock. The amplitude ratio and the frequency ratio are used as inputs to the trained unstable rock mass stability evaluation model to identify the stable state of the unstable rock mass.

2. The method according to claim 1, characterized in that, The calculation formulas for the one-dimensional amplitude data of the unstable rock or the one-dimensional amplitude data of the bedrock, and the calculation formulas for the standard deviation of the amplitude of the unstable rock or the standard deviation of the amplitude of the bedrock, include: In the formula, A i Let (x, y, z) be the i-th data point in the one-dimensional amplitude data of the unstable rock or the one-dimensional amplitude data of the bedrock, and let (x, y, z) be the triaxial vibration data of the unstable rock or the triaxial vibration data of the bedrock. The standard deviation of the amplitude of the dangerous rock or the standard deviation of the amplitude of the bedrock is given, where N is the total number of data points. It is the absolute mean of the one-dimensional amplitude data of the dangerous rock or the absolute mean of the one-dimensional amplitude data of the bedrock.

3. The method according to claim 1, characterized in that, Based on the one-dimensional amplitude data of the unstable rock and the one-dimensional amplitude data of the bedrock, the ratio of the peak frequency of the unstable rock to the peak frequency of the bedrock is calculated to obtain the frequency ratio, including: Based on Fourier transform, the one-dimensional amplitude data of the dangerous rock and the one-dimensional amplitude data of the bedrock are converted into frequency curves in the direction perpendicular to the fracture, and the peak frequency of the dangerous rock and the peak frequency of the bedrock are determined respectively. The frequency ratio is obtained by calculating the ratio of the peak frequency of the dangerous rock to the peak frequency of the bedrock.

4. The method according to claim 1, characterized in that, The method also includes: training the PSO-SVM model based on the rock vibration index dataset to obtain a trained rock mass stability evaluation model.

5. A stability evaluation system for unstable rock masses based on amplitude ratio and frequency ratio, characterized in that, The system is used to implement the method for evaluating the stability of unstable rock masses based on amplitude ratio and frequency ratio as described in any one of claims 1-4; the system includes: a data acquisition module, a first calculation module, a second calculation module, and an evaluation module; wherein, The acquisition module is used to acquire triaxial vibration data of unstable rock and triaxial vibration data of bedrock within the same time interval, respectively. The first calculation module is used to synthesize the three-dimensional vibration data of the unstable rock and the three-dimensional vibration data of the bedrock into one-dimensional amplitude data of the unstable rock and one-dimensional amplitude data of the bedrock, respectively, and to calculate the standard deviation of the unstable rock amplitude data and the standard deviation of the bedrock amplitude data of the one-dimensional amplitude data of the bedrock; The second calculation module is used to calculate the amplitude ratio by the ratio of the standard deviation of the unstable rock amplitude to the standard deviation of the bedrock amplitude, and to calculate the frequency ratio by the ratio of the peak frequency of the unstable rock to the peak frequency of the bedrock based on the one-dimensional amplitude data of the unstable rock and the one-dimensional amplitude data of the bedrock. The evaluation module is used to input the amplitude ratio and the frequency ratio as inputs into the trained unstable rock mass stability evaluation model to identify the stable state of the unstable rock mass.

6. The system according to claim 5, characterized in that, The system also includes a training module for training the PSO-SVM model based on the rock vibration index dataset to obtain a trained rock mass stability evaluation model.

7. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor, when executing the computer program, implements the method as described in any one of claims 1-4.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium contains program code that can be invoked by a processor to execute the method as described in any one of claims 1 to 4.

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