Rock failure time and failure energy prediction method

Abstract

A rock failure time and failure energy prediction method, comprising: performing uniaxial compression tests on multiple rock samples of the same type, and measuring cumulative acoustic emission counts during the failure process by an acoustic emission system; determining a failure precursor of each rock sample according to a rapid growth point of the cumulative acoustic emission count of the rock sample; determining an average proportion of the failure precursor points of all rock samples in the entire failure time; calculating the elastic strain energy density of all rock samples during the loading process; establishing a corresponding relationship between the rock failure time and the elastic strain energy density; for the rock to be tested of the same type, first obtaining the failure precursor point, and predicting the rock failure time in advance according to the average proportion of the failure precursor points of all rock samples in the entire failure time; and then calculating the rock failure energy according to the corresponding relationship between the failure time and the elastic strain energy density and the rock volume. The method can realize accurate prediction of the rock failure time and the failure energy in advance through analysis of acoustic emission data.

Description

Technical Field

[0001] This invention relates to the field of underground engineering, specifically to a method for predicting rock failure time and failure energy. Background Technology

[0002] In contemporary engineering construction and mining, rock mass stability has always been a major concern, significantly impacting the integrity and safety of engineering projects. With accelerating urbanization and increasing resource demands, engineering activities are expanding into more complex and geologically hazardous environments. Against this backdrop, short-term rock failure prediction technology has emerged and rapidly developed into an indispensable component of engineering safety assurance systems. Short-term rock failure prediction is a complex problem involving multiple fields such as rock mechanics, monitoring technology, data analysis, and risk management. Currently used monitoring methods include acoustic emission technology, distributed fiber optic sensing, infrared thermal imaging, and digital image correlation. Among these, acoustic emission technology can detect microcrack activity within the rock mass, providing an important indicator for predicting large-scale failure. However, existing short-term rock failure prediction methods are primarily qualitative, focusing mainly on precursory indicators. Effective quantitative methods are still lacking for accurate prediction of failure time and the energy released during failure. Summary of the Invention

[0003] The purpose of this invention is to provide a method for predicting rock failure time and energy. This method is based on acoustic emission technology, which quantitatively predicts rock failure time and energy, and solves the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A method for predicting rock failure time and failure energy, comprising the following steps:

[0006] S1. Perform uniaxial compression tests on multiple rock samples of the same type, and measure the cumulative acoustic emission count during the failure process of each rock sample using an acoustic emission system;

[0007] S2. Determine the precursors of failure based on the rapid increase point of the cumulative acoustic emission count for each rock sample;

[0008] S3. Determine the average proportion of the failure precursor points of all rock samples to the total failure time, and use this as the average proportion of the failure precursor points of this type of rock to the total failure time.

[0009] S4. Calculate the elastic strain energy density of all rock samples during the loading process;

[0010] S5. Establish the relationship between failure time and elastic strain energy density for this type of rock;

[0011] S6. For the same type of rock to be tested, first obtain its failure precursor points, and then use the average proportion of the failure precursor points of this type of rock to the total failure time obtained in step S3 to predict the rock failure time in advance.

[0012] S7. Based on the rock failure time predicted in step S6, and using the relationship between the rock failure time and elastic strain energy density and the rock volume obtained in step S5, calculate the rock failure energy.

[0013] The beneficial effects of this invention are:

[0014] Based on acoustic emission technology, this invention proposes a quantitative method that can accurately predict the time and energy of rock failure, which can be extended to the prediction of surrounding rock failure in engineering. Attached Figure Description

[0015] Figure 1 This is a flowchart of a method for predicting rock failure time and failure energy in an embodiment.

[0016] Figure 2 This is a schematic diagram of the sensor mounting surface in an embodiment.

[0017] Figure 3 This is a schematic diagram of the rock failure precursor point in an embodiment.

[0018] Figure 4 This is a schematic diagram illustrating the linear relationship between rock failure time and elastic strain energy density in an embodiment.

[0019] Figure 5 This is a statistical graph showing the destruction time and energy of multiple test rock samples in the embodiment. Detailed Implementation

[0020] The technical solutions provided in this application will be further described below with reference to specific embodiments and accompanying drawings. The advantages and features of this application will become clearer from the following description.

[0021] like Figure 1 As shown, a method for predicting rock failure time and failure energy includes the following steps:

[0022] S1. Perform uniaxial compression tests on multiple rock samples of the same type, and measure the cumulative acoustic emission count during the failure process of each rock sample using an acoustic emission system;

[0023] S2. Determine the precursors of failure based on the rapid increase point of the cumulative acoustic emission count for each rock sample;

[0024] S3. Determine the average proportion of the failure precursor points of all rock samples to the total failure time, and use this as the average proportion of the failure precursor points of this type of rock to the total failure time.

[0025] S4. Calculate the elastic strain energy density of all rock samples during the loading process;

[0026] S5. Establish the relationship between failure time and elastic strain energy density for this type of rock;

[0027] S6. For the same type of rock to be tested, first obtain its failure precursor points, and then use the average proportion of the failure precursor points of this type of rock to the total failure time obtained in step S3 to predict the rock failure time in advance.

[0028] S7. Based on the rock failure time predicted in step S6, and using the relationship between the rock failure time and elastic strain energy density and the rock volume obtained in step S5, calculate the rock failure energy.

[0029] Furthermore, in step S1:

[0030] As an example, the selected rock was granite, and the rock sample had dimensions of 50×50×100mm.

[0031] A single-axis compressor was used to compress the rock sample at a fixed loading rate, such as 0.15 mm / min. The failure time of the rock sample and the stress-strain curve of the rock sample during the compression process were recorded.

[0032] When uniaxially loading a rock sample, the cumulative acoustic emission count during the failure process of each rock sample is measured using an acoustic emission system. This includes: arranging acoustic emission probes on the surface of the rock sample, monitoring the acoustic emission count data in real time using an acoustic emission host, and storing the data. The acoustic emission probes can be arranged on any side of the rock sample except the compression surface. Preferably, the cumulative acoustic emission count is calculated in integer seconds, representing the total acoustic emission count from the start of compression to that integer second.

[0033] Further, in step S2, the precursor to rock failure is determined based on the rapid increase point of the cumulative acoustic emission count for each rock sample. Specifically, the original cumulative acoustic emission count signal is filtered using a multi-point moving average to reduce random noise; the first-order difference of the cumulative acoustic emission count between adjacent time points is calculated and compared with a set first-order difference threshold; the first time exceeding the first-order difference threshold is taken as the precursor point of rock failure. In this embodiment, the multi-point is set to 20 points, and the threshold is set to 5.

[0034] Further, in step S3, firstly, the proportion of the failure precursor points of all rock samples to the total failure time is calculated, and then the average value is taken as the proportion of the failure precursor points of this type of rock to the total failure time, as shown in the following formulas (1) and (2):

[0035]

[0036] Among them, A n t represents the percentage of the time before the failure of the nth rock sample relative to the total failure time; n It is the moment of the precursor point of failure for the nth rock sample; T n is the failure time of the nth rock sample; A is the average proportion of the failure precursor point of this type of rock to the total failure time.

[0037] Further, in step S4, the elastic strain energy density of all rock samples during the loading process is calculated. Specifically:

[0038] Since the energy released by rock failure is the elastic strain energy stored in the rock, the elastic strain energy of the rock can be used as the failure energy. The elastic strain energy per unit volume of rock, i.e., the elastic strain energy density, is shown in the following formula (3):

[0039]

[0040] Where E is the unloading elastic modulus; for ease of calculation, the elastic modulus is usually used instead of E. In this invention, the elastic modulus is the slope of the linear phase of the stress-strain curve of the test sample. σ i U represents the rock stress at the i-th moment. e This represents the elastic strain energy per unit volume of rock, also known as the elastic strain energy density.

[0041] Further, in step S5, the relationship between rock failure time and elastic strain energy density is established. Specifically, this includes:

[0042] Based on the failure times of multiple rock samples obtained in step S1 and the elastic strain energy density calculated in step S4, a linear relationship between failure time and elastic strain energy density is established, as shown in the following formula (4):

[0043] U e =aT k +b (4)

[0044] Among them, a and b are relevant parameters fitted from multiple rock samples, and T k The time it takes for the rock to break down.

[0045] Furthermore, in step S6, for the same type of rock to be tested, first obtain its precursor point t for damage. k Then, using the average proportion A of the precursor points of this type of rock failure to the total failure time obtained in step S3, the failure time T of the rock to be tested can be predicted in advance. k As shown in the following formula (5):

[0046]

[0047] Further, in step S7, based on the rock failure time predicted in step S6, and using the correspondence between the rock failure time and elastic strain energy density obtained in step S5, as well as the rock volume, the rock failure energy is calculated. Specifically, this includes:

[0048] S71 will use the predicted rock failure time T obtained in step S6. k Substitute the linear relationship between the failure time and elastic strain energy density determined in step S5 into formula (4) to calculate the elastic strain energy density of the rock to be tested.

[0049] S72 Then, the elastic strain energy density of the rock to be tested is multiplied by the volume of the rock to be tested to calculate the destructive energy of the rock to be tested, as shown in formula (6).

[0050] Q e =U e ×V(6)

[0051] Among them, Q e V is the elastic strain energy, or destruction energy, of rock failure, and V is the rock volume.

[0052] Figure 2 A schematic diagram of a sensor mounting surface for a granite sample according to an embodiment of the present invention is shown. In the figure, an acoustic emission sensor is used and mounted on the right side of the granite sample.

[0053] Figure 3 This diagram illustrates the precursor point of granite failure according to an embodiment of the present invention. The rock is granite, and failure occurs at 1450 seconds. The X-axis represents time, ranging from 0 to 1600 seconds. The Y-axis represents the cumulative acoustic emission count, ranging from 0 to 4500. The cumulative acoustic emission curve reaches its maximum value at 825 seconds, with a cumulative acoustic emission count of 3565. The precursor point of granite failure is reached at 515 seconds, with a cumulative acoustic emission count of 265.

[0054] Figure 4 This is a schematic diagram illustrating the linear relationship between rock failure time and elastic strain energy density, as shown in an embodiment of the present invention. The X-axis represents failure time, ranging from 1200 to 1900 seconds. The Y-axis represents rock elastic strain energy density, ranging from 0 to 300,000 J. A strong linear relationship exists between rock failure time and elastic strain energy density, R... 2 The value is 0.9023. The linear equation is U. e =415.81T k -475591.

[0055] Figure 5This is a statistical chart showing the failure time and energy of multiple test rock samples as illustrated in an embodiment of the present invention. A total of eight granite test samples were used, and for each sample, the time to failure precursor, failure time, the ratio of failure precursor time to failure time, the average ratio, elastic strain energy, and elastic strain energy density were statistically analyzed.

[0056] This invention utilizes acoustic emission technology to quantitatively predict rock failure time and energy through data analysis. Specifically, a loading rate is set, and uniaxial loading tests are conducted on multiple rock samples of the same type. The cumulative acoustic emission counts during the failure process of multiple rock samples are measured using an acoustic emission system. Rapid increases in the acoustic emission counts are used to identify pre-failure indicators, and the proportion of these pre-failure indicators to the total failure time is determined based on the entire loading time. The elastic strain energy density during the loading process of multiple rock samples is calculated, establishing a correlation between failure time and elastic strain energy density. For the rock under test, after obtaining the pre-failure indicators, the accurate failure time is deduced based on the proportion of these indicators to the total failure time. Finally, the rock failure energy is calculated based on the failure time and rock volume.

[0057] The method of this invention can be extended to the prediction of surrounding rock failure in engineering projects. After the excavation of underground tunnels or roadways, stress redistribution and concentration occur in the surrounding rock. This process is similar to a uniaxial compression test of rock in a laboratory. Therefore, installing acoustic emission sensors on the surrounding rock of the excavated roadway can monitor the changes in acoustic emission counts during the stress redistribution process. By analyzing the changing trends and performing relevant calculations, it is helpful to predict the time when the surrounding rock may fail and the energy released during the failure.

[0058] The above description is merely a description of preferred embodiments of this application and is not intended to limit the scope of this application in any way. Any changes or modifications made by those skilled in the art based on the above-disclosed technical content should be considered as equivalent and valid embodiments and fall within the scope of protection of the technical solution of this application.

Claims

1. A rock failure time and failure energy prediction method, characterized by, The method comprises the steps of: S1. performing uniaxial compression tests on multiple rock samples of the same type, and measuring the cumulative acoustic emission count of each rock sample during the failure process by an acoustic emission system; S2. determining the failure precursor of each rock sample according to the rapid growth point of the cumulative acoustic emission count of the rock sample; S3. determining the average proportion of the failure precursor points of all rock samples in the entire failure time, and taking the average proportion as the average proportion of the failure precursor points of the rock of the type in the entire failure time; S4. calculating the elastic strain energy density of all rock samples during the loading process; S5. establishing the corresponding relationship between the failure time and the elastic strain energy density of the rock of the type; S6. for the rock to be tested of the same type, obtaining the failure precursor point, and predicting the failure time of the rock in advance by using the average proportion of the failure precursor points of the rock of the type in the entire failure time obtained in step S3; S7. according to the failure time of the rock predicted in step S6, the corresponding relationship between the failure time and the elastic strain energy density of the rock of the type obtained in step S5, and the volume of the rock, the failure energy of the rock is calculated.

2. The method of claim 1, wherein the rock failure time and failure energy are predicted by the steps of: Step S1: ​ A uniaxial compression machine is used to compress the rock sample at a fixed loading rate, and the failure time of the rock sample and the stress-strain curve of the rock sample during the compression process are recorded.

3. The method of claim 1, wherein the rock failure time and failure energy are predicted by the steps of: Step S1: ​ Acoustic emission probes are arranged on the surface of the rock sample, and acoustic emission count data are monitored in real time by an acoustic emission host and stored; the acoustic emission probes are arranged on any one side of the compression surface of the rock sample.

4. The method of claim 1, wherein the rock failure time and failure energy are predicted by the steps of: Step S1: ​ The cumulative acoustic emission count is calculated in integer seconds, and the total acoustic emission count from the start of compression to the integer second is calculated.

5. The method of claim 1, wherein the rock failure time and failure energy are predicted by the steps of: Step S2: ​ The original acoustic emission cumulative count signal is filtered by a multi-point moving average filter to reduce random noise, a first-order difference of the acoustic emission cumulative count at adjacent time points is calculated, compared with a set first-order difference threshold, and the first time point exceeding the first-order difference threshold is taken as the rock failure precursor point.

6. The method of claim 1, wherein the rock failure time and failure energy are predicted by the steps of: Step S3: ​ First, the proportion of the failure precursor points of all rock samples in the entire failure time is calculated, and then the average value is obtained, which is taken as the proportion of the failure precursor points of the rock of the type in the entire failure time, as shown in the following formulas (1) and (2): Wherein, A n is the percentage of the precursor point time of the nth rock sample to the entire destruction time; t n is the precursor point time of the nth rock sample; T n is the destruction time of the nth rock sample; and A is the average percentage of the precursor point of the rock of this type to the entire destruction time.

7. The method of claim 1, wherein the rock failure time and failure energy are predicted by the steps of: Step S4: ​ The elastic strain energy of the rock is taken as the failure energy, and the elastic strain energy per unit volume of the rock is the elastic strain energy density, and the calculation formula of the elastic strain energy density is shown in the following formula (3): where E is the unloading elastic modulus, specifically corresponding to the slope of the linear stage of the stress-strain curve of the test sample; σ i is the stress of the rock corresponding to the ith moment; U e represents the elastic strain energy per unit volume of rock, i.e. the elastic strain energy density.

8. The method of claim 1, wherein the rock failure time and failure energy are predicted by the steps of: Step S5, specifically comprising: ​ According to the failure time of the multiple rock samples obtained in step S1 and the elastic strain energy density calculated in step S4, a linear relationship between the failure time and the elastic strain energy density is established, as shown in the following formula (4): U e = aT k + b (4) wherein a, b are relevant parameters fitted by a plurality of rock samples, T k is the failure time of the rock.

9. The method of claim 1, wherein the rock failure time and failure energy are predicted by the steps of: Step S6, for the same type of rock to be measured, first obtain its failure precursor point t k , and then use the average proportion A of the failure precursor point of the type of rock obtained in step S3 in the entire failure time to predict the failure time T of the rock to be measured in advance k , as shown in the following formula (5): ​ 10. The method of claim 1, wherein, Step S7, specifically comprising: S71 will step S6 predicted to be measured rock failure time T k The linear relationship between the failure time determined in step S5 and the elastic strain energy density is calculated in formula (4) to obtain the elastic strain energy density of the rock to be measured; S72, and the failure energy of the rock to be tested is calculated by multiplying the elastic strain energy density of the rock to be tested by the volume of the rock to be tested, as shown in formula (6): Q e = U e x V (6) where Q e is the elastic strain energy of rock failure, i.e., failure energy, and V is the rock volume.

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