A method for evaluating the damage degree of rock samples

Abstract

A method for evaluating the degree of damage of a rock sample comprises the following steps: obtaining a rock sample and recording joint characteristics; dividing the rock sample into multi-layer block regions and performing uniaxial compression tests and acoustic emission tests to obtain the stress-strain curve and cumulative ringing curve of the rock sample; calculating the spatial distance between the positions of the high-incidence crack regions of two adjacent layers and calculating the three-dimensional energy distribution vector of the rock sample according to the characteristic parameters of the ringing signal; establishing a support vector regression SVR model to form a rock sample stress state prediction function; predicting the stress state of the rock sample under load, and evaluating the degree of damage of the rock sample. The present invention introduces a support vector regression SVR model to form a prediction relationship function between rock-related parameters and the development stage of its stress-strain curve, and considers the dynamic response of the relevant parameters of the rock sample during the development of each stage, comprehensively evaluates the degree of damage of the rock sample, and the evaluation result is accurate and reliable.

Description

Technical Field

[0001] The invention relates to the technical field of rock mass engineering, and in particular to a method for evaluating the damage degree of a rock mass sample. Background Art

[0002] Rock mass strength prediction plays a vital role in mining and maintenance. In the mining process, accurate assessment of rock mass strength is of decisive significance for ensuring operational safety, preventing collapse accidents, controlling support costs, and improving mining efficiency.

[0003] Rock mass is a complex geological aggregate composed of various rock particles and the cements and fillings between them. Therefore, its mechanical properties, overall mechanical properties and physical and chemical properties are very complex. When open-pit mining and underground mining are carried out in mines, the surrounding rock mass will be disturbed, its strength will be reduced, and the safety of the mine will be affected. When the damaged rock mass is subjected to complex environmental factors such as dry-wet cycles and frost-heave cycles, its mechanical properties will change greatly, which poses certain difficulties in analyzing its strength. At the same time, when conducting dry-wet and freeze-thaw tests on damaged rock mass, due to the lack of corresponding technical means, it is impossible to judge the actual degree of damage to the rock mass sample before the test, which brings difficulties to the subsequent result analysis. Summary of the invention

[0004] The purpose of the present invention is to overcome the defects and problems of the prior art in that the assessment of the degree of damage of rock samples is difficult and the accuracy is low, and to provide a method for assessing the degree of damage of rock samples that is convenient to assess and has high accuracy.

[0005] To achieve the above objectives, the technical solution of the present invention is: a method for evaluating the degree of damage to a rock sample, the method comprising the following steps:

[0006] Step 1: Obtain rock samples and record the joint characteristics of the rock samples;

[0007] Step 2: divide the rock sample into multiple block regions, and conduct uniaxial compression test and acoustic emission test on the rock sample divided into multiple block regions to obtain stress-strain curve and cumulative ringing curve of the rock sample. According to the stress-strain curve of the rock sample, the stress state stage is divided into initial compaction stage, linear elastic deformation stage, plastic deformation stage and rapid overall destruction stage;

[0008] The dividing strength value between the initial compaction stage and the linear elastic deformation stage is defined as The dividing point strength value between the linear elastic deformation stage and the plastic deformation stage is The dividing point strength value between the plastic deformation stage and the rapid overall failure stage is The uniaxial compressive strength of the rock mass specimen at final failure is ;

[0009] According to the determined cut-off point strength value , , And the uniaxial compressive strength value , establish the average range of the development stage of the stress-strain curve of the rock sample, that is, the initial compaction stage is The linear elastic deformation stage is , the plastic deformation stage is , the rapid overall destruction stage is , the rock mass specimen reaches the uniaxial compressive strength value The corresponding time is taken as the total time of the cumulative ringing curve, and the total time is divided into multiple intervals, and the cumulative ringing number ratio, the origin slope angle change rate, and the curve slope change rate of the cumulative ringing curve in each interval are calculated;

[0010] Step 3: Obtain characteristic parameters of the ringing signal according to the acoustic emission test, record the cumulative energy value in each layer of the multi-layer block area, divide the area in the multi-layer block area where the cumulative energy value is greater than the set value into a high-incidence crack area, calculate the spatial distance between the positions of the high-incidence crack areas of two adjacent layers, and calculate the three-dimensional energy distribution vector of the rock sample according to the spatial distance;

[0011] Step 4: According to the joint characteristics of the rock sample, the characteristic parameters of the cumulative ringing curve, the characteristic parameters of the ringing signal, and the three-dimensional energy distribution vector of the rock sample, a support vector regression SVR model is established to form a rock sample stress state prediction function:

[0012] ;

[0013] ;

[0014] in, is the number of intervals into which the cumulative ringing curve is divided, , is the Lagrange coefficient, is a natural constant, is the kernel function parameter, is the bias, vector For each interval, the parameters corresponding to the rock sample are vectors. , For the , The parameters corresponding to the rock samples in each interval are: is the number of joints, is the joint width, is the joint length, is the joint inclination angle, is the cumulative ringing ratio corresponding to each interval segment, is the rate of change of the slope angle of the origin corresponding to each interval segment, is the rate of change of the slope of the curve corresponding to each interval segment, The ratio of the ringing signals with different signal frequencies and amplitudes in each interval to the total accumulated ringing signals. is the three-dimensional energy distribution vector of the rock sample;

[0015] Step 5: According to the rock sample stress state prediction function, the stress state of the rock sample under load is predicted. Determine the stress state stage of the rock sample and predict the value The calculation formula is:

[0016] ;

[0017] in, is the stress value of the stress-strain curve of the rock sample corresponding to the right endpoint in the interval;

[0018] Evaluate the damage degree of rock mass specimens according to the stress state stage of the rock mass specimens;

[0019] The three-dimensional energy distribution vector of the rock sample The calculation formula is:

[0020] ;

[0021] ;

[0022] in, , , , , , They refer to the spatial distance between the first and second layers of the rock mass specimen with high crack incidence, the spatial distance between the second and third layers of the rock mass specimen with high crack incidence, the spatial distance between the third and fourth layers of the rock mass specimen with high crack incidence, the spatial distance between the fourth-to-last and third-to-last layers of the rock mass specimen with high crack incidence, the spatial distance between the third-to-last and second-to-last layers of the rock mass specimen with high crack incidence, and the spatial distance between the second-to-last and last layers of the rock mass specimen with high crack incidence. is the spatial distance between the crack-prone areas of a certain layer of the rock mass specimen and the next layer, is the number of high-incidence crack areas in each layer, , , is the three-dimensional coordinate of the high-incidence crack area in a certain layer, , , It is the three-dimensional coordinate of the area with high incidence of cracks in the next layer.

[0023] The cumulative number of ringings corresponding to each interval segment is The calculation formula is:

[0024] ;

[0025] in, is the accumulated ringing value at the left endpoint of the interval. The accumulated ringing value for the right endpoint of the interval.

[0026] The origin slope angle change rate corresponding to each interval segment The calculation formula is:

[0027] ;

[0028] in, is the slope angle of the line connecting the left endpoint and the origin of the cumulative ringing curve in the interval segment, is the slope angle of the line connecting the right endpoint of the cumulative ringing curve in the interval and the origin, is the length of the interval.

[0029] The corresponding curve slope change rate in each interval segment The calculation formula is:

[0030] ;

[0031] in, is the maximum slope of the cumulative ringing curve within the interval, It is the minimum slope of the cumulative ringing curve within the interval.

[0032] The ratio of the ringing signals with different signal frequencies and amplitudes in each interval to the total accumulated ringing signals The calculation formula is:

[0033] ;

[0034] in, , , , , , are the cumulative number of low-frequency and low-amplitude signals, low-frequency and high-amplitude signals, medium-frequency and low-amplitude signals, medium-frequency and high-amplitude signals, high-frequency and low-amplitude signals, and high-frequency and high-amplitude signals, respectively. The accumulated ringing value for the right endpoint of the interval.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] 1. In a method for evaluating the degree of damage of a rock sample of the present invention, a uniaxial compression test and an acoustic emission test are carried out on the rock sample to obtain the stress-strain curve development stage of the rock sample and various parameters of the cumulative ringing curve and the ringing signal, and the obtained rock sample data are introduced into the support vector regression SVR model to form a prediction relationship function between the relevant parameters of the rock sample and the development stage of its stress-strain curve. The function takes into account the dynamic response of the relevant parameters of the rock sample during the development of each stage. The stress-strain stage of the rock sample can be directly judged by the function, thereby determining the degree of damage of the rock sample, which is convenient for evaluation. At the same time, the degree of damage is comprehensively judged in combination with various parameters of the rock sample, and the accuracy is high. Therefore, the present invention is convenient for evaluation and has high accuracy.

[0037] 2. In a method for evaluating the degree of damage of a rock sample of the present invention, the stress state of the rock sample in a uniaxial compression test is divided into multiple stages, and the degree of damage is measured by these stages. In order to fully reflect the change process of the stress state of the rock sample under load, the cumulative ringing curve characteristics in the acoustic emission test are extracted, and relevant parameters such as the cumulative ringing number ratio and the slope angle change rate are established to reflect the change of the ringing curve characteristics of the rock sample under different stress states, thereby judging whether the rock sample has entered different stress stages. Therefore, the present invention has a comprehensive assessment and high accuracy.

[0038] 3. In a method for evaluating the degree of damage of a rock sample of the present invention, the three-dimensional energy distribution vector parameters of the rock sample are introduced to reflect the development process of the internal cracks of the rock sample under load and the possibility of forming through cracks; the support vector regression SVR model is used to establish the function mapping relationship between the stress state of the rock sample and its own parameters and dynamic characteristic parameters, and the kernel function is used to obtain the high-dimensional characteristics of the data, so that the established function mapping relationship is more accurate. Therefore, the present invention has high reliability and high accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 The present invention is a schematic flow chart of a method for evaluating the degree of damage to a rock sample.

[0040] Figure 2 It is a structural schematic diagram of the normal area of ​​the rock sample in the present invention.

[0041] Figure 3 It is a structural schematic diagram of the normal area and the high-incidence area of ​​cracks in the rock sample in the present invention. DETAILED DESCRIPTION

[0042] The present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0043] Embodiment 1:

[0044] See also Figure 1 , a method for evaluating the degree of damage to a rock sample, the method comprising the following steps:

[0045] Step 1: Obtain rock samples and record the joint characteristics of the rock samples;

[0046] Step 2: divide the rock sample into multiple block regions, and conduct uniaxial compression test and acoustic emission test on the rock sample divided into multiple block regions to obtain stress-strain curve and cumulative ringing curve of the rock sample. According to the stress-strain curve of the rock sample, the stress state stage is divided into initial compaction stage, linear elastic deformation stage, plastic deformation stage and rapid overall destruction stage;

[0047] The dividing strength value between the initial compaction stage and the linear elastic deformation stage is defined as The dividing point strength value between the linear elastic deformation stage and the plastic deformation stage is The dividing point strength value between the plastic deformation stage and the rapid overall failure stage is The uniaxial compressive strength of the rock mass specimen at final failure is ;

[0048] According to the determined cut-off point strength value , , And the uniaxial compressive strength value , establish the average range of the development stage of the stress-strain curve of the rock sample, that is, the initial compaction stage is The linear elastic deformation stage is , the plastic deformation stage is , the rapid overall destruction stage is , the rock mass specimen reaches the uniaxial compressive strength value The corresponding time is taken as the total time of the cumulative ringing curve, and the total time is divided into multiple intervals, and the cumulative ringing number ratio, the origin slope angle change rate, and the curve slope change rate of the cumulative ringing curve in each interval are calculated;

[0049] Step 3: Obtain characteristic parameters of the ringing signal according to the acoustic emission test, record the cumulative energy value in each layer of the multi-layer block area, divide the area in the multi-layer block area where the cumulative energy value is greater than the set value into a high-incidence crack area, calculate the spatial distance between the positions of the high-incidence crack areas of two adjacent layers, and calculate the three-dimensional energy distribution vector of the rock sample according to the spatial distance;

[0050] Step 4: According to the joint characteristics of the rock sample, the characteristic parameters of the cumulative ringing curve, the characteristic parameters of the ringing signal, and the three-dimensional energy distribution vector of the rock sample, a support vector regression SVR model is established to form a rock sample stress state prediction function:

[0051] ;

[0052] ;

[0053] in, is the number of intervals into which the cumulative ringing curve is divided, , is the Lagrange coefficient, is a natural constant, is the kernel function parameter, is the bias, vector For each interval, the parameters corresponding to the rock sample are vectors. , For the , The parameters corresponding to the rock samples in each interval are: is the number of joints, is the joint width, is the joint length, is the joint inclination angle, is the cumulative ringing ratio corresponding to each interval segment, is the rate of change of the slope angle of the origin corresponding to each interval segment, is the rate of change of the slope of the curve corresponding to each interval segment, The ratio of the ringing signals with different signal frequencies and amplitudes in each interval to the total accumulated ringing signals. is the three-dimensional energy distribution vector of the rock sample;

[0054] Step 5: According to the rock sample stress state prediction function, the stress state of the rock sample under load is predicted. Determine the stress state stage of the rock sample and predict the value The calculation formula is:

[0055] ;

[0056] in, is the stress value of the stress-strain curve of the rock sample corresponding to the right endpoint in the interval;

[0057] The damage degree of the rock sample is evaluated according to the stress state stage of the rock sample.

[0058] In this example, according to the "Engineering Rock Mass Test Method Standard", the rock block is cored, cut and polished to make a cylindrical sample with a height of 100 mm and a diameter of 50 mm. The rock sample is taken from the same area, has inclined joints, and contains the same mineral composition. The number of layers is (layer), the number of block regions divided in each layer is (), the joint characteristics of rock specimens refer to the lithology, number of joints, joint length, joint width and joint inclination of the rock specimen itself. Acoustic emission test reflects the process of internal crack generation and development by detecting transient sound waves generated by rock specimens during stress. Ringing is a signal feature that reflects the relevant characteristics of transient sound waves inside the rock specimen, including the location of the sound wave emission source and the corresponding energy; the cumulative ringing curve is a curve formed by the cumulative number of ringing signals recorded by the rock specimen in uniaxial compression and acoustic emission tests. When the stress-strain curve of the rock specimen develops to each stage, the slope of the cumulative ringing curve will also change accordingly;

[0059] The stress-strain curves of rock samples obtained under uniaxial compression tests and acoustic emission tests are segmented according to the changes in the curves to evaluate the degree of damage to the rock samples. The cumulative ringing curve corresponding to the rock sample in the uniaxial compression test is obtained according to the acoustic emission test, and the characteristic parameters of the cumulative ringing curve and the characteristic parameters of the ringing signal in the acoustic emission test are obtained to reflect the development stage of the stress-strain curve of the rock sample. At the same time, the three-dimensional energy distribution vector of the rock sample is formed according to the energy value and spatial position corresponding to the ringing signal obtained in the acoustic emission test. Finally, the various parameters obtained are brought into the SVR model to form a function for predicting the development stage of the stress-strain curve of the rock sample, thereby completing the evaluation of the degree of damage to the rock sample with high evaluation accuracy.

[0060] The development stage of the rock sample stress-strain curve is the initial compaction stage, linear elastic deformation stage, plastic deformation stage and rapid overall destruction stage experienced by the rock sample during the uniaxial compression test. The four development stages characterize the degree of development of internal cracks in the rock sample during the uniaxial compression process, that is, the degree of internal structural fragmentation, and the slope of the rock sample stress-strain curve changes significantly in the four stages. The development stage division of the rock sample stress-strain curve is based on the significant change in the slope of the rock sample stress-strain curve. The dividing point of each development stage is the ratio of the compressive strength corresponding to the significant change in the slope of the stress-strain curve to the peak compressive strength corresponding to the destruction of the sample. The dividing point of the development stage is the average dividing point under the results of uniaxial compression tests of multiple groups of rock samples.

[0061] The stress-strain curves of rock samples obtained under uniaxial compression tests and acoustic emission tests are segmented according to the changes in the curves, so as to evaluate the degree of damage of the rock samples with high accuracy.

[0062] Embodiment 2:

[0063] The basic content is the same as that of Example 1, except that:

[0064] The cumulative number of ringings corresponding to each interval segment is The calculation formula is:

[0065] ;

[0066] in, is the accumulated ringing value at the left endpoint of the interval. The cumulative ringing value at the right end of the interval. The cumulative ringing ratio specifically refers to the difference between the cumulative ringing number at the right end of the interval and the cumulative ringing number at the left end of the interval within a period of time, and the value formed by the ratio of the difference to the cumulative ringing number at the right end;

[0067] The origin slope angle change rate corresponding to each interval segment The calculation formula is:

[0068] ;

[0069] in, is the slope angle of the line connecting the left endpoint and the origin of the cumulative ringing curve in the interval segment, is the slope angle of the line connecting the right endpoint of the cumulative ringing curve in the interval and the origin, The origin slope angle change rate specifically refers to the difference between the slope angle of the line formed by the right end point of the cumulative ringing curve and the origin within a time interval and the corresponding slope angle of the line formed by the left end point of the interval, and the difference is divided by the length of the time interval to obtain the origin slope angle change rate;

[0070] The corresponding curve slope change rate in each interval segment The calculation formula is:

[0071] ;

[0072] in, is the maximum slope of the cumulative ringing curve within the interval, It is the minimum slope of the cumulative ringing curve within the interval.

[0073] Acoustic emission ringing signals of different amplitudes and frequencies in acoustic emission tests. In acoustic emission tests, the transient acoustic wave signal corresponding to each ringing is transformed into a frequency domain signal through Fourier transform, and then its frequency and energy characteristics are analyzed. In the uniaxial compression test of rock samples, the generation and development of internal cracks will be accompanied by the appearance of acoustic emission ringing signals of different amplitudes and frequencies;

[0074] The ratio of the ringing signals with different signal frequencies and amplitudes in each interval to the total cumulative ringing signals The calculation formula is:

[0075] ;

[0076] in, , , , , , are the cumulative number of low-frequency and low-amplitude signals, low-frequency and high-amplitude signals, medium-frequency and low-amplitude signals, medium-frequency and high-amplitude signals, high-frequency and low-amplitude signals, and high-frequency and high-amplitude signals, respectively. The accumulated ringing value for the right endpoint of the interval.

[0077] In this embodiment, in order to eliminate the influence of the size and dimension of parameters such as the cumulative ringing number ratio, the origin slope angle change rate, and the curve slope change rate on data analysis, the parameters are normalized so that the parameter values ​​are within the interval [0,1]. The calculation formula is as follows:

[0078] ;

[0079] in, is the data normalization value, is the parameter value, is the minimum value of the parameter, is the maximum value of the parameter;

[0080] According to the data normalization value, the initial regression function relationship between the input parameters and the output values ​​is established:

[0081] ;

[0082] Among them, the matrix , Bias All are function fitting parameters;

[0083] According to the initial regression function relationship, in order to find the optimal function fitting parameters , , using the Lagrange multiplier method and KKT conditions, it is transformed into an optimization problem with inequality constraints, the formula is as follows:

[0084] ;

[0085] ;

[0086] in, is the penalty coefficient, the value is 1; To tolerate deviations, it is used to improve the generalization ability and accuracy of the model;

[0087] In order to solve the established inequality constrained optimization problem, a kernel function is used to transform the parameter characteristics corresponding to the sample data, i.e. the rock mass specimen, into The output value is mapped to a high-dimensional space, so that the sample data can be linearly separated in the high-dimensional space, and the correlation between the sample data can be shown. The kernel function uses the radial basis kernel function, and the kernel function is as follows:

[0088] ;

[0089] The support vector regression (SVR) model is a supervised learning algorithm that finds a function in the feature space to minimize the error between the function and the actual value of the response variable and keep it within a certain tolerance range. The cumulative ringing number ratio, the rate of change of the slope angle at the origin, the rate of change of the curve steepness, the characteristics of the rock sample itself, the proportion of ringing signals of different amplitudes and frequencies, the three-dimensional energy distribution vector, and the dividing point of the development stage of the stress-strain curve of the rock sample are introduced into the support vector regression (SVR) model to form a rock sample stress state prediction function, thereby completing the assessment of the degree of damage of the rock sample, and the assessment result is accurate and reliable.

[0090] Embodiment 3:

[0091] The basic content is the same as that of Example 1, except that:

[0092] The three-dimensional energy distribution vector of the rock sample The calculation formula is:

[0093] ;

[0094] ;

[0095] in, , , , , , They refer to the spatial distance between the first and second layers of the rock mass specimen with high crack incidence, the spatial distance between the second and third layers of the rock mass specimen with high crack incidence, the spatial distance between the third and fourth layers of the rock mass specimen with high crack incidence, the spatial distance between the fourth-to-last and third-to-last layers of the rock mass specimen with high crack incidence, the spatial distance between the third-to-last and second-to-last layers of the rock mass specimen with high crack incidence, and the spatial distance between the second-to-last and last layers of the rock mass specimen with high crack incidence. is the spatial distance between the crack-prone areas of a certain layer of the rock mass specimen and the next layer, is the number of high-incidence crack areas in each layer, , , is the three-dimensional coordinate of the high-incidence crack area in a certain layer, , , It is the three-dimensional coordinate of the area with high incidence of cracks in the next layer.

[0096] In this embodiment, the three-dimensional energy distribution vector of the rock sample is firstly to subdivide the rock sample into multiple layers of block regions; secondly, according to the ringing position and corresponding energy value obtained in the acoustic emission test, the cumulative energy value in each layer of block region is recorded at regular intervals, and the block region with a larger cumulative energy value is used as a high-incidence crack region; the high-incidence crack region of the first layer is connected with the high-incidence crack region of the second layer, and the length of the connection line is calculated to form the easy-to-penetrate crack path length, and then the easy-to-penetrate crack path length of the second layer and the third layer is calculated until the calculation of each layer is completed; finally, the ratio of the easy-to-penetrate crack path length from the first layer to the second layer to the easy-to-penetrate crack path length from the second layer to the third layer is obtained, and so on, and finally the ratios are arranged in order to form the three-dimensional energy distribution vector of the rock sample, see Figure 2 and Figure 3 , when the value of a certain element in the vector is closer to 1, it indicates that the corresponding three-layer crack-prone areas are more likely to form through cracks during the subsequent loading process of the rock sample. Therefore, the established three-dimensional energy distribution vector reflects the development degree of cracks inside the rock sample and the possibility of forming through cracks, and the evaluation accuracy is relatively high.

Claims

1. A method for evaluating the degree of damage to a rock sample, characterized in that: The method comprises the following steps: Step 1: Obtain rock samples and record the joint characteristics of the rock samples; Step 2: divide the rock sample into multiple block regions, and conduct uniaxial compression test and acoustic emission test on the rock sample divided into multiple block regions to obtain stress-strain curve and cumulative ringing curve of the rock sample. According to the stress-strain curve of the rock sample, the stress state stage is divided into initial compaction stage, linear elastic deformation stage, plastic deformation stage and rapid overall destruction stage; The dividing strength value between the initial compaction stage and the linear elastic deformation stage is defined as The dividing point strength value between the linear elastic deformation stage and the plastic deformation stage is The dividing strength value between the plastic deformation stage and the rapid overall failure stage is The uniaxial compressive strength of the rock mass specimen at final failure is ; According to the determined cut-off point strength value , , And the uniaxial compressive strength value , establish the average range of the development stage of the stress-strain curve of the rock sample, that is, the initial compaction stage is The linear elastic deformation stage is , the plastic deformation stage is , the rapid overall destruction stage is , the rock mass specimen reaches the uniaxial compressive strength value The corresponding time is taken as the total time of the cumulative ringing curve, and the total time is divided into multiple intervals, and the cumulative ringing number ratio, origin slope angle change rate, and curve slope change rate of the cumulative ringing curve in each interval are calculated; Step 3: Obtain characteristic parameters of the ringing signal according to the acoustic emission test, record the cumulative energy value in each layer of the multi-layer block area, divide the area in the multi-layer block area where the cumulative energy value is greater than the set value into a high-incidence crack area, calculate the spatial distance between the positions of the high-incidence crack areas of two adjacent layers, and calculate the three-dimensional energy distribution vector of the rock sample according to the spatial distance; Step 4: According to the joint characteristics of the rock sample, the characteristic parameters of the cumulative ringing curve, the characteristic parameters of the ringing signal, and the three-dimensional energy distribution vector of the rock sample, a support vector regression SVR model is established to form a rock sample stress state prediction function: ； ； in, is the number of intervals into which the cumulative ringing curve is divided, , is the Lagrange coefficient, is a natural constant, is the kernel function parameter, is the bias, vector For each interval, the parameters corresponding to the rock sample are vectors. , For the , The parameters corresponding to the rock samples in each interval are: is the number of joints, is the joint width, is the joint length, is the joint inclination angle, is the cumulative ringing ratio corresponding to each interval segment, is the rate of change of the slope angle of the origin corresponding to each interval segment, is the rate of change of the slope of the curve corresponding to each interval segment, The ratio of the ringing signals with different signal frequencies and amplitudes in each interval to the total accumulated ringing signals. is the three-dimensional energy distribution vector of the rock sample; Step 5: According to the rock sample stress state prediction function, the stress state of the rock sample under load is predicted. Determine the stress state stage of the rock sample and predict the value The calculation formula is: ； in, is the stress value of the stress-strain curve of the rock sample corresponding to the right endpoint in the interval; The damage degree of the rock sample is evaluated according to the stress state stage of the rock sample.

2. A method for assessing the degree of damage to a rock sample according to claim 1, characterized in that: The three-dimensional energy distribution vector of the rock sample The calculation formula is: ； ； in, , , , , , They refer to the spatial distance between the first and second layers of the rock mass specimen with high crack incidence, the spatial distance between the second and third layers of the rock mass specimen with high crack incidence, the spatial distance between the third and fourth layers of the rock mass specimen with high crack incidence, the spatial distance between the fourth-to-last and third-to-last layers of the rock mass specimen with high crack incidence, the spatial distance between the third-to-last and second-to-last layers of the rock mass specimen with high crack incidence, and the spatial distance between the second-to-last and last layers of the rock mass specimen with high crack incidence. is the spatial distance between the crack-prone areas of a certain layer of the rock mass specimen and the next layer, is the number of high-incidence crack areas in each layer, , , is the three-dimensional coordinate of the crack-prone area in a certain layer, , , It is the three-dimensional coordinate of the area with high incidence of cracks in the next layer.

3. A method for assessing the degree of damage to a rock sample according to claim 1, characterized in that: The cumulative ringing number ratio corresponding to each interval segment The calculation formula is: ； in, is the accumulated ringing value at the left endpoint of the interval. The accumulated ringing value for the right endpoint of the interval.

4. A method for assessing the degree of damage to a rock sample according to claim 1, characterized in that: The rate of change of the slope angle of the origin corresponding to each interval segment The calculation formula is: ； in, is the slope angle of the line connecting the left endpoint and the origin of the cumulative ringing curve in the interval segment, is the slope angle of the line connecting the right endpoint of the cumulative ringing curve in the interval and the origin, is the length of the interval.

5. A method for assessing the degree of damage to a rock sample according to claim 1, characterized in that: The corresponding curve slope change rate in each interval segment The calculation formula is: ； in, is the maximum slope of the cumulative ringing curve within the interval, It is the minimum slope of the cumulative ringing curve within the interval.

6. A method for assessing the degree of damage to a rock sample according to claim 1, characterized in that: The ratio of the ringing signals with different signal frequencies and amplitudes in each interval to the total accumulated ringing signals The calculation formula is: ； in, , , , , , are the cumulative number of low-frequency and low-amplitude signals, low-frequency and high-amplitude signals, medium-frequency and low-amplitude signals, medium-frequency and high-amplitude signals, high-frequency and low-amplitude signals, and high-frequency and high-amplitude signals, respectively. The accumulated ringing value for the right endpoint of the interval.

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