Coal rock damage prediction method and device based on acoustic emission real-time statistical analysis

Abstract

The invention relates to the technical field of coal rock sample testing, and provides a coal rock damage prediction method and device based on acoustic emission real-time statistical analysis, and the method comprises the following steps: screening coal rock samples through a pre-experiment and a formal experiment; based on the screened coal rock sample, determining a b value according to acoustic emission information recorded in the loading process of the coal rock sample; determining the change rate of the b value in unit time according to the b value; determining an early warning signal threshold according to the change rate of the b value in the unit time, and releasing an early warning signal when the actually measured change rate of the b value in the unit time exceeds the early warning signal threshold; analyzing the acoustic emission data, and determining the position of a macro-energy event greater than a first energy threshold as a coal rock failure position high-risk point; and determining the position of a small-energy event smaller than a second energy threshold, and taking a surface which is connected with the accumulation area of the large-energy event and passes through the accumulation area of the small-energy event as a damage surface. The problems that in the prior art, real-time early warning cannot be achieved, and the time difference between early warning signal release and final damage is uncertain are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of coal-rock sample testing, and in particular to a coal-rock damage prediction method and device based on real-time statistical analysis of acoustic emission. Background Art

[0002] The prediction and early warning of coal and rock damage is of great significance for the prevention of natural and engineering disasters. In the fields of coal mining, tunneling, underground engineering, etc., the stability of coal and rock mass is a key factor in ensuring engineering safety. Coal and rock damage is often accompanied by the release of energy, which is manifested in various forms. Among them, acoustic emission signals are an important source of early warning information for internal damage of coal and rock mass. Through real-time monitoring and analysis of acoustic emission signals, the damage trend of coal and rock mass can be predicted, providing important guarantee for engineering safety.

[0003] At present, the existing methods for predicting coal and rock damage mainly include the elastic wave emission-reception method based on elastic mechanics theory, the deformation characteristic method based on plastic mechanics and expansion theory, the thermal infrared method, and the early warning method based on acoustic emission characteristics. Among them, the early warning method based on acoustic emission characteristics has attracted much attention because it directly reflects the internal destruction process of coal and rock. This method monitors the acoustic emission signals released by coal and rock during loading, analyzes the characteristic parameters of the signals such as amplitude, frequency, and energy, to predict coal and rock damage. In particular, the existing technology often uses acoustic emission ring counts or energy for prediction, and uses the acoustic emission entering a quiet period or the acoustic emission b value steadily decreasing as a warning signal.

[0004] However, the existing coal-rock damage prediction methods based on acoustic emission characteristics have significant defects. On the one hand, the time difference between the release of the early warning signal and the impact damage of the coal-rock is uncertain, and the relationship between the load on the coal-rock at the time of the early warning signal release and the ultimate load that the coal-rock can withstand is also uncertain. This uncertainty makes it difficult for the early warning signal to accurately reflect the actual damage state of the coal-rock mass, thereby reducing the accuracy and reliability of the early warning. On the other hand, the existing methods cannot effectively predict the specific location and damage mode of coal-rock damage. This limits the application effect of the early warning method in engineering practice, making it difficult for engineers to take effective preventive measures based on the early warning information. Summary of the invention

[0005] The present invention provides a method and device for predicting coal-rock damage based on real-time statistical analysis of acoustic emission, which solves the problems in the prior art of being unable to provide real-time warning and the uncertain time difference between the release of the warning signal and the final damage, realizes real-time warning of coal-rock impact damage, and accurately obtains the time difference between the release of the warning signal and the coal-rock damage.

[0006] The present invention provides a coal-rock damage prediction method based on real-time statistical analysis of acoustic emission, comprising the following steps: Acquire preliminary experimental data through preliminary experiments, and screen coal and rock samples according to the preliminary experimental data during the formal test; Based on the screened coal and rock samples, a b value is determined according to the acoustic emission information recorded during the loading process of the coal and rock samples; the b value is an energy index of the acoustic emission signal; Determine the rate of change of the b value per unit time according to the b value; Determine the warning signal threshold value according to the change rate of the b value within the unit time, and release the warning signal when the measured change rate of the b value within the unit time exceeds the warning signal threshold value; Analyze the acoustic emission data to determine the location of large energy events greater than the first energy threshold, and use them as high-risk points for coal rock damage. Determine the location of small energy events less than the second energy threshold, and use the surface connecting the gathering area of ​​the large energy events and passing through the gathering area of ​​the small energy events as the damage surface.

[0007] According to a coal-rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, the b-value is determined according to the acoustic emission information recorded during the loading process of the coal-rock sample, specifically comprising: recording the acoustic emission signal in real time during the loading process of the coal-rock sample; determining the window size according to the time step or a fixed number of acoustic emission events, and determining the sliding step according to the window size; obtaining the number of intervals of preset acoustic emission amplitudes; performing statistical analysis on the recorded acoustic emission signal based on the window size and the sliding step to determine the number of acoustic emission events in each amplitude interval; performing linear fitting on each interval according to the number of acoustic emission events in each amplitude interval, and determining the b-value according to the fitting result; determining the b-value corresponding to each time step or each fixed number of acoustic emission events according to the statistical analysis result.

[0008] According to a coal-rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, the method of determining the rate of change of the b value per unit time according to the b value specifically includes: obtaining a b value time series per unit time based on statistical analysis of acoustic emission signals; for every two adjacent b values ​​in the b value time series, determining the absolute value of the change between every two adjacent b values; determining a single b value change slope according to the absolute value of the change and the time difference between every two adjacent b values; and determining the sum of the absolute values ​​of the change slopes of each b value per unit time as the rate of change of the b value per unit time.

[0009] According to a coal and rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, the warning signal threshold is determined according to the rate of change of the b value per unit time, and the warning signal is released when the measured rate of change of the b value per unit time exceeds the warning signal threshold. Specifically, the method includes: taking the average value of the rate of change of the b value per unit time of all moments before the current moment, and adding x times the standard deviation of all moments before the current moment to the average value, where x is a preset constant, and taking the sum obtained as the warning signal threshold; when the measured rate of change of the b value per unit time is greater than the warning signal threshold, releasing the warning signal.

[0010] According to a coal-rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, the location of large energy events greater than a first energy threshold is determined as a high-risk point of the coal-rock damage location, which specifically includes: determining the first energy threshold according to preliminary experimental data; traversing the acoustic emission data, screening out large energy events with energy greater than the first energy threshold, and recording the positioning information of the large energy events; analyzing the location distribution of large energy events according to the positioning information, and determining the concentrated area of ​​the large energy events as the high-risk point of the coal-rock damage location.

[0011] According to a coal-rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, the location of small energy events less than a second energy threshold is determined, and the surface connecting the gathering area of ​​the large energy events and passing through the gathering area of ​​the small energy events is used as the damage surface, which specifically includes: determining the second energy threshold according to preliminary experimental data; traversing the acoustic emission data, screening out small energy events with energy less than the second energy threshold, and recording the location information of the small energy events; determining the gathering area of ​​the small energy events in the coal-rock sample according to the location information of the small energy events; and determining the surface connecting the gathering areas of each large energy event and passing through the gathering area of ​​the small energy events as a potential damage surface according to the distribution characteristics of the large energy events and the small energy events.

[0012] According to a coal-rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, linear fitting is performed on each interval according to the number of acoustic emission events in each amplitude interval, and the b value is determined according to the fitting result, which specifically includes: linear fitting is performed on each interval according to the number of acoustic emission events in each amplitude interval, and the goodness of fit of the linear fit is obtained; if the goodness of fit is greater than a preset fitting threshold, the slope of the linear fitting equation at the current moment is used as the b value; if the goodness of fit is not greater than the preset fitting threshold, the linear fitting is performed again after adjusting the fitting parameters until the slope of the linear fitting equation at the current moment is used as the b value when the goodness of fit is greater than the preset fitting threshold.

[0013] According to a coal and rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, the corresponding warning level is determined according to the number of times the measured rate of change of the b value per unit time at the current moment is greater than the warning signal threshold; in the warning state, the number of levels of warning level increase is determined according to the number of unit times that the measured rate of change of the b value per unit time at the current moment continuously exceeds the warning signal threshold.

[0014] According to a coal and rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, pre-experimental data is obtained through a preliminary experiment, and coal and rock samples are screened according to the pre-experimental data during the formal experiment. Specifically, the method includes: during the preliminary experiment, a plurality of coal and rock samples are randomly selected for loading, basic parameters of the coal and rock samples are obtained, and the statistics of the basic parameters are determined to generate pre-experimental data; during the formal experiment, formal test data are obtained, and valid coal and rock samples are screened out after comparing the formal test data with the pre-experimental data.

[0015] The present invention also provides a coal-rock damage prediction device based on real-time statistical analysis of acoustic emission, comprising the following modules: A coal and rock sample screening module is used to obtain pre-experimental data through pre-experiments, and to screen coal and rock samples according to the pre-experimental data during the formal test; A b value determination module is used to determine the b value based on the screened coal rock sample and the acoustic emission information recorded during the loading process of the coal rock sample; the b value is the energy index of the acoustic emission signal; A b value change rate acquisition module is used to determine the change rate of the b value per unit time according to the b value; A warning signal threshold and release module, used to determine the warning signal threshold according to the change rate of the b value within the unit time, and release the warning signal when the measured change rate of the b value within the unit time exceeds the warning signal threshold; The high-risk point determination module for coal and rock damage is used to analyze the acoustic emission data, determine the location of large energy events greater than the first energy threshold, and use them as high-risk points for coal and rock damage; determine the location of small energy events less than the second energy threshold, and use the surface connecting the gathering area of ​​the large energy events and passing through the gathering area of ​​the small energy events as the damage surface.

[0016] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for predicting coal and rock damage based on real-time statistical analysis of acoustic emissions as described above is implemented.

[0017] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described coal-rock damage prediction methods based on real-time statistical analysis of acoustic emissions.

[0018] The present invention also provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-mentioned coal-rock damage prediction methods based on real-time statistical analysis of acoustic emissions.

[0019] The present invention provides a method and device for predicting coal and rock damage based on real-time statistical analysis of acoustic emission, including the following beneficial effects: by real-time statistical analysis of the b-value change rate of acoustic emission per unit time, a threshold is established to determine the timing of releasing the warning signal, ensuring that the time difference between the moment of warning signal release and the moment of coal and rock damage is relatively fixed, thereby improving the accuracy of the warning. At the moment of warning signal release, the load borne by the coal and rock and the ultimate load that the coal and rock can withstand satisfy a specific functional relationship, making the warning signal more practical and providing a strong basis for subsequent disaster prevention and control measures. By analyzing the acoustic emission positioning data after the warning, finding the location of the large energy event as a high-risk point of the coal and rock damage location, and analyzing the positioning information of the small energy event captured interspersed with the large energy event to obtain the damage surface, the accurate prediction of the coal and rock damage location can be achieved, providing important reference information for disaster prevention and control. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 It is a flow chart of the coal-rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention.

[0022] Figure 2 This is the time evolution characteristic of the b value provided by the present invention.

[0023] Figure 3 The present invention provides Evolution of features over time.

[0024] Figure 4 The present invention provides a measured The evolution trend of the value and warning signal threshold with loading time.

[0025] Figure 5It is a structural schematic diagram of a coal-rock damage prediction device based on real-time statistical analysis of acoustic emission provided by the present invention.

[0026] Figure 6 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] The prediction and early warning of coal and rock failure is of great significance to the prediction and forecast of natural and engineering disasters. The existing methods for predicting coal and rock failure mainly include: elastic wave emission-reception method based on elastic mechanics theory, deformation characteristic method based on plastic mechanics and expansion theory, thermal infrared method and early warning method based on acoustic emission characteristics.

[0029] Acoustic emission signals originate from the internal damage of the loaded coal and rock mass, and are an important source of early warning information for coal and rock mass damage. In existing methods, when early warning is based on acoustic emission characteristics, the acoustic emission ring count or energy is often used for prediction, and the acoustic emission entering a quiet period or the acoustic emission b value steadily decreases as a warning signal. This type of method can indeed give an early warning of coal and rock damage, but the time difference between the release of the early warning signal and the impact damage of the coal and rock is uncertain, and the relationship between the load on the coal and rock at the time of the release of the early warning signal and the ultimate load that the coal and rock can withstand is uncertain, resulting in the early warning signal losing its warning significance. On the other hand, none of the above methods can predict the location and mode of coal and rock damage.

[0030] The present invention provides a coal-rock damage early warning method based on the statistical analysis of the b-value change rate of acoustic emission per unit time. A threshold is established based on the b-value change rate of acoustic emission per unit time to determine the timing of early warning signal release. Then, the acoustic emission data after the early warning is analyzed to find the location of the large energy event as the high-risk point of the coal-rock damage location; and the positioning information of the small energy event captured interspersed with the large energy event is analyzed to obtain the damage surface. In this method, the time difference between the early warning signal release moment and the coal-rock damage moment is relatively fixed, and the load borne by the coal-rock at the time of early warning signal release and the limit load that the coal-rock can withstand meet a specific functional relationship, which truly realizes the impact damage early warning and the prediction of the damage location.

[0031] The process of the present invention is summarized as follows: ① Prepare samples, install acoustic emission probes, and conduct inspections and preliminary tests; ② Load the sample at a constant rate to obtain acoustic emission characteristic data, such as time, amplitude and positioning data; ③ Determine various calculation parameters, such as window size and sliding step size; ④ b value statistical analysis, The value and warning signal threshold are determined in real time, and the warning signal is released; ⑤ Determination of warning level; ⑥ Predict high-risk areas and potential damage surfaces based on acoustic emission positioning data after early warning.

[0032] Combine the following Figure 1-Figure 6 Embodiments of the present invention are described in detail.

[0033] Figure 1 This is one of the flow charts of the coal-rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, such as Figure 1 As shown, the method comprises the following steps: S110, obtaining preliminary experimental data through preliminary experiments, and screening coal and rock samples according to the preliminary experimental data during the formal test.

[0034] According to a coal and rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, pre-experimental data are obtained through a pre-experiment, and coal and rock samples are screened according to the pre-experimental data during the formal test. Specifically, the method includes: during the pre-experimental process, a plurality of coal and rock samples are randomly selected for loading, basic parameters of the coal and rock samples are obtained, and the statistics of the basic parameters are determined to generate pre-experimental data; during the formal test, formal test data are obtained, and valid coal and rock samples are screened out after comparing the formal test data with the pre-experimental data.

[0035] Specifically, sample preparation.

[0036] 1. A rectangular specimen is preferred to facilitate the installation of the acoustic emission probe and the accurate positioning of the acoustic emission probe; 2. The sample size can be determined according to the size of the acoustic emission probe and the loading capacity of the testing machine, but in principle it should not be less than 50*50*100mm; 3. The number of acoustic emission probes shall be no less than 8 and shall be evenly arranged on the surface of the sample; 4. The wave velocity test can be completed by the test function of the acoustic emission instrument. At the same time, other suitable instruments can also be selected for testing; 5. After the acoustic emission probe is accurately installed, a lead-breaking test is required on the surface of the sample to check whether the probe is positioned correctly. If there is any deviation, it needs to be adjusted in time.

[0037] The preferred rectangular parallelepiped specimen facilitates the installation and positioning of the acoustic emission probe because the regular shape of the rectangular parallelepiped provides a stable structure, facilitating standardized operation and accurate measurement.

[0038] Sample loading.

[0039] 1. The loading process can adopt displacement control mode or load control mode, and the load needs to be applied continuously at a constant rate until the sample is damaged; 2. During the entire loading process, the time parameters, amplitude parameters and positioning information of the received acoustic emission signal must be recorded in real time and accurately.

[0040] During the loading process, the time parameters, amplitude parameters and positioning information of the acoustic emission signal are recorded in real time and accurately, providing rich raw data for subsequent data analysis and interpretation.

[0041] The process of preliminary experiment and formal test data screening is as follows.

[0042] 1. Randomly select three specimens for loading test to obtain the basic parameters of the specimens, including but not limited to strength, number of acoustic emission events, etc. In this process, the minimum value of the intensity and number of acoustic emission events needs to be determined, and their mean needs to be calculated. At the same time, the maximum energy and loading time of the specimens need to be recorded and obtained; 2. In the formal test stage, if the intensity or number of acoustic emission events of a sample is lower than 1 / 2 of the lowest value obtained in the preliminary test, or lower than 1 / 3 of the mean value, it can be determined that there is an error in the experimental process of the sample and it needs to be discarded. The ratio of 1 / 2 and 1 / 3 here can be appropriately adjusted according to the actual situation.

[0043] Through data screening of preliminary experiments and formal experiments, the coal-rock failure prediction method relies on high-quality data input, which can avoid investing too many resources in invalid samples, thereby saving test costs and improving the overall efficiency of the experiment.

[0044] S120. Based on the screened coal and rock samples, determine the b value according to the acoustic emission information recorded during the loading process of the coal and rock samples; the b value is the energy index of the acoustic emission signal.

[0045] According to a coal-rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, the b-value is determined according to the acoustic emission information recorded during the loading process of the coal-rock sample, and specifically includes: during the loading process of the coal-rock sample, the acoustic emission signal is recorded in real time; the window size is determined according to the time step or a fixed number of acoustic emission events, and the sliding step is determined according to the window size; the number of intervals of preset acoustic emission amplitudes is obtained; based on the window size and the sliding step, the recorded acoustic emission signal is statistically analyzed to determine the number of acoustic emission events in each amplitude interval; linear fitting is performed on each interval according to the number of acoustic emission events in each amplitude interval, and the b-value is determined according to the fitting result; according to the statistical analysis result, the b-value corresponding to each time step or each fixed number of acoustic emission events is determined.

[0046] According to a coal-rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, linear fitting is performed on each interval according to the number of acoustic emission events in each amplitude interval, and the b value is determined according to the fitting result, which specifically includes: linear fitting is performed on each interval according to the number of acoustic emission events in each amplitude interval, and the goodness of fit of the linear fit is obtained; if the goodness of fit is greater than a preset fitting threshold, the slope of the linear fitting equation at the current moment is used as the b value; if the goodness of fit is not greater than the preset fitting threshold, the linear fitting is performed again after adjusting the fitting parameters until the slope of the linear fitting equation at the current moment is used as the b value when the goodness of fit is greater than the preset fitting threshold.

[0047] Specifically, b-value statistical analysis.

[0048] 1. According to formula (1), obtain the number of acoustic emission events N and the acoustic emission amplitude A dB The quantitative relationship between them.

[0049] (1) In the formula, A dB is the acoustic emission amplitude in decibels; N is the acoustic emission amplitude in A dB The following are the numbers of acoustic emission events; a and b are constants; 2. Before performing statistical analysis of acoustic emission signals, you need to set the appropriate window size and sliding step size. The window size determines the number or time range of acoustic emission signals included in each statistical analysis, while the sliding step size determines the update frequency of the statistical analysis. The window size can be selected based on the time step or a fixed number of acoustic emission events; 3. If you choose to use the time step as the basis for the window size, the specific size of the window will be closely related to the loading rate; 4. If a fixed number of AE events is selected as the window size division standard, the window size is more affected by the number of AE probes deployed; 5. Regardless of the method used to determine the window size, in order to ensure the accuracy and effectiveness of statistical analysis, the window can be divided into about 100 intervals; 6. When setting the sliding step size, you can set the sliding step size to 1 / 5 of the b-value calculation window to ensure the timeliness and accuracy of statistical analysis; 7. Although the two methods of selecting the window size according to the time step and according to the fixed number of acoustic emission events have their own unique advantages, it has been verified in practice that the method of determining the window size and calculating the b value according to the fixed number of acoustic emission events often has better prediction effects; 8. Based on the above formula, the time evolution characteristics of b value are obtained, such as Figure 2 As shown in the figure, the time corresponding to the b value is the time of the last event of all acoustic emission events of the b value; 9. Goodness of fit is R 2 . Verify R 2 Is it greater than 0.85? 2 If R is greater than 0.85, the slope of the linear fitting equation is determined to be b value. 2 If it is less than 0.85, then the A in the fitting equation (1) will be dB Reduce by 1 dB, perform fitting, and check R 2 Is it greater than 0.85? And so on, until R 2 Until it is greater than 0.85.

[0050] By setting the appropriate window size and sliding step size according to actual needs, the statistical analysis can adapt to different test conditions and data characteristics, improving the applicability and accuracy of the analysis. Dividing the window into about 100 intervals helps to more accurately analyze the distribution characteristics of the acoustic emission signal and improve the resolution and sensitivity of the statistical analysis.

[0051] S130, determining the rate of change of the b value per unit time according to the b value.

[0052] According to a coal-rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, the rate of change of the b value per unit time is determined according to the b value, specifically comprising: obtaining a b value time series based on statistical analysis of acoustic emission signals; determining a unit time, for every two adjacent b values ​​in the b value time series, determining the amount of change between every two adjacent b values, and determining the rate of change of the b value per unit time according to the amount of change.

[0053] Specifically, the absolute change rate of b value per unit time is Value calculation.

[0054] 1. The change of b value has a strong volatility. However, when it is close to destruction, the fluctuation frequency and amplitude of b value increase significantly. Therefore, the change rate of b value per unit time is calculated by formula (2): : (2) In the formula, is the i+1th b value per unit time, is the i-th b value per unit time, for and The difference between the corresponding times; the absolute rate of change of the b value per unit time That is, the sum of the absolute values ​​of the slopes of all b-value changes per unit time; 2. The unit time can be 1s or longer. When the unit time is 1s, real-time monitoring at the second level can be achieved; 3. Based on the above formula (2), we can calculate Characteristics that evolve over time, such as Figure 3 As shown, The corresponding time is to calculate the The time of the last event for all b values.

[0055] Since the b value will fluctuate significantly when the material is close to damage, early warning of material damage risks can be achieved by monitoring the absolute change rate of the b value.

[0056] S140, determining a warning signal threshold value according to a change rate of the b value within a unit time, and determining a warning signal release time according to an actually measured change rate of the b value within a unit time.

[0057] According to a coal and rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, the warning signal threshold is determined according to the change rate of the b value per unit time, and the warning signal release time is determined according to the measured change rate of the b value per unit time, specifically including: taking the average value of the change rate of the b value per unit time of all moments before the current moment, and adding x times the standard deviation of all moments before the current moment to the average value, where x is a preset constant, and taking the obtained sum as the warning signal threshold; when the measured change rate of the b value per unit time is greater than the warning signal threshold, releasing the warning signal.

[0058] Specifically, the warning signal threshold and the corresponding load are determined.

[0059] 1. Obtain acoustic emission information in real time and use formula (1) to statistically analyze the b value; 2. Use the mean value plus x times the standard deviation as the warning signal threshold. Greater than All previous When the mean of the values ​​is equal to the sum of x times the standard deviation of these data, a warning signal is released; the judgment standard is as follows: (3) In the formula, the right side of the inequality is the threshold value, For the jth value, For the j-1th All previous The sum of the values, For the j-1th All previous values Standard deviation of values; measured The evolution trend of the value and the warning signal threshold with loading time is as follows Figure 4 shown.

[0060] 3. b value and The statistical analysis and calculation of the value can only be obtained based on the data before that moment; 4. Determine the warning time t according to the warning signal threshold, determine the load F borne by the sample at this moment, and calculate the stress of the sample; 5. If the pre-experimental sample is lower than 1 / 2 of the minimum value or lower than 1 / 3 of the mean value when the warning signal is released, the warning signal is invalid. Continue to carry out real-time monitoring and warning according to step 2 until the next data that meets the warning signal appears.

[0061] By adopting the mean value plus x times the standard deviation as the warning signal threshold, the average level and fluctuation of historical data are comprehensively considered, making the threshold setting more scientific and reasonable, and effectively avoiding false alarms and omissions.

[0062] According to a coal and rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, the corresponding warning level is determined according to the number of times the measured rate of change of the b value per unit time at the current moment is greater than the warning signal threshold; in the warning state, the number of levels of warning level increase is determined according to the number of unit times that the measured rate of change of the b value per unit time at the current moment continuously exceeds the warning signal threshold.

[0063] Specifically, warning levels are divided.

[0064] 1. When measured When it is greater than the threshold for the first time, that is, when the warning signal is released for the first time, it is a blue warning; and so on, the second warning is a yellow warning; the third warning is an orange warning; and the fourth warning is a red warning.

[0065] 2. If a warning is given, the actual measurement If the threshold is exceeded for 2 consecutive time units (2 seconds), the warning level will be raised by one level. If the threshold is exceeded for 3 consecutive time units (3 seconds), the warning level will be raised to level 2; If the threshold is exceeded for 4 consecutive time periods (4 seconds), the warning level will be raised by three levels.

[0066] By setting four warning levels with different colors, clear warning standards are provided for the monitoring of acoustic emission signals, which helps personnel quickly identify the current degree of danger and take appropriate countermeasures.

[0067] S150. After the early warning signal is released, the acoustic emission data is analyzed to determine the location of large energy events greater than a first energy threshold in the acoustic emission data, which are used as high-risk points for coal and rock damage. The location of small energy events less than a second energy threshold in the acoustic emission data is determined, and the area formed by connecting the large energy event aggregation area and the small energy event aggregation area is used as the damage surface.

[0068] According to a coal-rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, after the early warning signal is released, the acoustic emission data is analyzed to determine the location of large energy events greater than a first energy threshold in the acoustic emission data as a high-risk point for the coal-rock damage location, specifically comprising: collecting acoustic emission data after the early warning signal is released; determining the first energy threshold based on pre-experimental data; traversing the acoustic emission data, screening out large energy events with energy greater than the first energy threshold, and recording the positioning information of the large energy events; analyzing the location distribution of the large energy events based on the positioning information, and determining the clustering area of ​​the large energy events as the high-risk point for the coal-rock damage location.

[0069] According to a coal and rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the present invention, the position of the small energy event less than a second energy threshold in the acoustic emission data is determined, and the area formed by connecting the aggregation area of ​​the large energy event and the aggregation area of ​​the small energy event is used as the damage surface, which specifically includes: collecting acoustic emission data after the early warning signal is released; determining the second energy threshold according to preliminary experimental data; traversing the acoustic emission data, screening out small energy events with energy less than the second energy threshold, and recording the position information of the small energy events; determining the aggregation area of ​​the small energy events in the coal and rock samples according to the position information of the small energy events; and determining the area formed by connecting the aggregation areas of each large energy event with the aggregation areas of the small energy events as a potential damage surface according to the distribution characteristics of the large energy events and the small energy events.

[0070] Specifically, prediction of rupture location.

[0071] 1. Focus on the acoustic emission event location dataset after the release of the warning signal; 2. To screen the large energy events, you can choose more than 1000aJ as the critical value of the large energy events. The selection of the critical value refers to the maximum energy collected in the pre-experiment, which can be 2 to 4 orders of magnitude lower than the maximum energy. 3. The screening of high energy events is carried out according to the time period. The length of the time period is determined according to the loading time during the preliminary experiment, such as 1 / 10 of the loading time or 5s; 4. If after the warning signal is released, large-energy acoustic emission events gather in a certain period of time, the large-energy event cluster area is a high-risk area for damage; 5. Mark the area where small energy events gather within this time period, and the line connecting the large energy event gathering areas through the small energy event gathering areas is the potential destruction surface.

[0072] The accuracy and reliability of rupture location prediction have been significantly improved through targeted energy screening, flexible time period analysis, high-risk area identification, potential failure surface prediction, and effective use of pre-experimental data.

[0073] The present invention proposes a coal-rock damage early warning method based on the statistical analysis of the acoustic emission b-value change rate per unit time. By acquiring and analyzing the acoustic emission signal in real time, the moment and position of coal-rock impact damage can be accurately predicted, the time difference between the release of the early warning signal and the coal-rock damage can be accurately obtained, and the relationship between the load borne by the coal-rock and the ultimate load can be clarified, thereby significantly improving the accuracy and reliability of coal-rock damage prediction and early warning, and providing strong support for the prediction and forecast of natural and engineering disasters.

[0074] The coal-rock damage prediction device based on real-time statistical analysis of acoustic emission provided by the present invention is described below. The coal-rock damage prediction device based on real-time statistical analysis of acoustic emission described below and the coal-rock damage prediction method based on real-time statistical analysis of acoustic emission described above can be referenced to each other.

[0075] like Figure 5 The present invention shows a coal-rock damage prediction device based on real-time statistical analysis of acoustic emission, comprising: The coal and rock sample screening module 510 is used to obtain pre-experimental data through pre-experiments, and screen the coal and rock samples according to the pre-experimental data during the formal test; The b value determination module 520 is used to determine the b value based on the screened coal-rock sample and the acoustic emission information recorded during the loading process of the coal-rock sample; the b value is the energy index of the acoustic emission signal; The b value change rate acquisition module 530 is used to determine the change rate of the b value per unit time according to the b value; The warning signal threshold and release module 540 is used to determine the warning signal threshold according to the change rate of the b value per unit time, and determine the warning signal release time according to the measured change rate of the b value per unit time; The damage position and damage surface analysis module 550 is used to analyze the acoustic emission data after the early warning signal is released, determine the location of the large energy event greater than the first energy threshold in the acoustic emission data, and use it as the high-risk point of the coal rock damage position; determine the location of the small energy event less than the second energy threshold in the acoustic emission data, and use the area formed by connecting the gathering area of ​​the large energy event and the gathering area of ​​the small energy event as the damage surface.

[0076] Figure 6 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 6 As shown, the electronic device may include: a processor 610, a communication interface 620, a memory 630 and a communication bus 640, wherein the processor 610, the communication interface 620 and the memory 630 communicate with each other through the communication bus 640. The processor 610 may call the logic instructions in the memory 630 to execute the coal-rock damage prediction method based on the real-time statistical analysis of acoustic emission, the method comprising: screening the coal-rock samples through preliminary experiments and formal experiments; based on the screened coal-rock samples, determining the b value according to the acoustic emission information recorded during the loading process of the coal-rock samples; determining the rate of change of the b value per unit time according to the b value; determining the threshold of the warning signal according to the rate of change of the b value per unit time, and determining the release time of the warning signal according to the measured rate of change of the b value per unit time; after the warning signal is released, analyzing the acoustic emission data, determining the position of the large energy event greater than the first energy threshold in the acoustic emission data as the high-risk point of the coal-rock damage position; determining the position of the small energy event less than the second energy threshold in the acoustic emission data, and obtaining the damage surface.

[0077] In addition, the logic instructions in the above-mentioned memory 630 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0078] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the coal and rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the above methods, the method including: screening coal and rock samples through preliminary experiments and formal experiments; based on the screened coal and rock samples, determining the b value according to the acoustic emission information recorded during the loading process of the coal and rock samples; determining the rate of change of the b value per unit time according to the b value; determining the warning signal threshold according to the rate of change of the b value per unit time, and determining the warning signal release time according to the measured rate of change of the b value per unit time; after the warning signal is released, analyzing the acoustic emission data, determining the position of a large energy event greater than a first energy threshold in the acoustic emission data, as a high-risk point of the coal and rock damage position; determining the position of a small energy event less than a second energy threshold in the acoustic emission data, and obtaining a damage surface.

[0079] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the coal and rock damage prediction method based on real-time statistical analysis of acoustic emission provided by the above-mentioned methods, the method comprising: screening the coal and rock samples through preliminary experiments and formal experiments; determining the b-value based on the screened coal and rock samples according to the acoustic emission information recorded during the loading process of the coal and rock samples; determining the rate of change of the b-value per unit time according to the b-value; determining the warning signal threshold according to the rate of change of the b-value per unit time, and determining the time of releasing the warning signal according to the measured rate of change of the b-value per unit time; after the warning signal is released, analyzing the acoustic emission data, determining the position of a large energy event greater than a first energy threshold in the acoustic emission data, as a high-risk point of the coal and rock damage position; determining the position of a small energy event less than a second energy threshold in the acoustic emission data, and obtaining a damage surface.

[0080] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, i.e., they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative effort.

[0081] Through the description of the above implementation modes, those skilled in the art can clearly understand that each implementation mode can be implemented by means of software plus a necessary general hardware platform, or of course by hardware. Based on such an understanding, the above technical solution can essentially or in other words be embodied in the form of a software product that contributes to the prior art. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiment.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A coal-rock damage prediction method based on real-time statistical analysis of acoustic emission, characterized in that: include: Acquire preliminary experimental data through preliminary experiments, and screen coal and rock samples according to the preliminary experimental data during the formal test; Based on the screened coal and rock samples, a b value is determined according to the acoustic emission information recorded during the loading process of the coal and rock samples; the b value is an energy index of the acoustic emission signal; Determine the rate of change of the b value per unit time according to the b value; Determine the warning signal threshold value according to the change rate of the b value within the unit time, and release the warning signal when the measured change rate of the b value within the unit time exceeds the warning signal threshold value; Analyze the acoustic emission data to determine the location of large energy events greater than the first energy threshold as high-risk points for coal and rock damage; The positions of small energy events less than a second energy threshold are determined, and a surface connecting the gathering area of ​​the large energy events and passing through the gathering area of ​​the small energy events is used as a destruction surface.

2. The coal-rock damage prediction method based on real-time statistical analysis of acoustic emission according to claim 1 is characterized in that: The b value is determined according to the acoustic emission information recorded during the loading process of the coal and rock samples, specifically including: During the loading process of coal and rock samples, the acoustic emission signals are recorded in real time; Determine the window size according to the time step or the fixed number of acoustic emission events, and determine the sliding step size according to the window size; Obtaining the preset number of intervals of acoustic emission amplitude; Performing statistical analysis on the recorded acoustic emission signals based on the window size and the sliding step size to determine the number of acoustic emission events in each amplitude interval; Perform linear fitting on each interval according to the number of acoustic emission events in each amplitude interval, and determine the b value based on the fitting result; Based on the statistical analysis results, the b value corresponding to each time step or each fixed number of acoustic emission events is determined.

3. The coal-rock damage prediction method based on real-time statistical analysis of acoustic emission according to claim 1 is characterized in that: Determining the change rate of the b value per unit time according to the b value specifically includes: Based on the statistical analysis of the acoustic emission signal, the b-value time series per unit time is obtained; For each two adjacent b values ​​in the b value time series, determining an absolute value of a change between each two adjacent b values; Determine a single b value change slope according to the absolute value of the change and the time difference between every two adjacent b values; The sum of the absolute values ​​of the slopes of each b-value change within a unit time is determined as the rate of change of the b-value within a unit time.

4. The coal-rock damage prediction method based on real-time statistical analysis of acoustic emission according to claim 1 is characterized in that: The step of determining the warning signal threshold value according to the change rate of the b value within the unit time, and releasing the warning signal when the measured change rate of the b value within the unit time exceeds the warning signal threshold value specifically includes: Take the average value of the rate of change of the b value per unit time at all moments before the current moment, and add x times the standard deviation of all moments before the current moment to the average value, where x is a preset constant, and use the obtained sum as the warning signal threshold; When the measured change rate of the b value per unit time is greater than the warning signal threshold, the warning signal is released.

5. The method for predicting coal-rock damage based on real-time statistical analysis of acoustic emission according to claim 1, characterized in that: The step of determining the location of a large energy event greater than the first energy threshold as a high-risk point of coal-rock damage specifically includes: Determine a first energy threshold value according to preliminary experimental data; Traversing the acoustic emission data, screening out high-energy events whose energy is greater than the first energy threshold, and recording the location information of the high-energy events; The location distribution of large energy events is analyzed according to the positioning information, and the gathering area of ​​the large energy events is determined as the high-risk point of the coal-rock damage location.

6. The method for predicting coal-rock damage based on real-time statistical analysis of acoustic emission according to claim 1, characterized in that: The determining of the location of the small energy event less than the second energy threshold, and taking the surface connecting the gathering area of ​​the large energy event and passing through the gathering area of ​​the small energy event as the destruction surface, specifically includes: Determine a second energy threshold according to preliminary experimental data; Traversing the acoustic emission data, screening out small energy events whose energy is less than the second energy threshold, and recording the position information of the small energy events; Determine the gathering area of ​​the small energy event in the coal rock sample according to the position information of the small energy event; According to the distribution characteristics of large energy events and small energy events, the surface connecting the gathering areas of large energy events and passing through the gathering areas of small energy events is determined as a potential destruction surface.

7. The method for predicting coal-rock damage based on real-time statistical analysis of acoustic emission according to claim 2, characterized in that: The linear fitting is performed on each interval according to the number of acoustic emission events in each amplitude interval, and the b value is determined according to the fitting result, specifically including: Perform a linear fit on each interval according to the number of acoustic emission events in each amplitude interval to obtain the goodness of fit of the linear fit; If the goodness of fit is greater than a preset fitting threshold, the slope of the linear fitting equation at the current moment is used as the b value; If the goodness of fit is not greater than the preset fitting threshold, the linear fitting is performed again after adjusting the fitting parameters until the goodness of fit is greater than the preset fitting threshold, and the slope of the linear fitting equation at the current moment is used as the b value.

8. The method for predicting coal-rock damage based on real-time statistical analysis of acoustic emission according to claim 1, characterized in that: Determine the corresponding warning level according to the number of times the change rate of the b value per unit time at the current moment is greater than the warning signal threshold; In the warning state, the level of warning level increase is determined according to the number of unit times that the change rate of the b value per unit time at the current moment continuously exceeds the warning signal threshold.

9. The method for predicting coal-rock damage based on real-time statistical analysis of acoustic emission according to claim 1, characterized in that: The method of obtaining preliminary experimental data through preliminary experiments and screening coal and rock samples according to the preliminary experimental data during the formal experiment specifically includes: During the pre-experimental process, a plurality of coal and rock samples are randomly selected for loading, basic parameters of the coal and rock samples are obtained, and statistics of the basic parameters are determined to generate pre-experimental data; During the formal test, formal test data are obtained, and after comparing the formal test data with the preliminary test data, effective coal and rock samples are screened out.

10. A coal-rock damage prediction device based on real-time statistical analysis of acoustic emission, characterized in that: include: A coal and rock sample screening module is used to obtain pre-experimental data through pre-experiments, and to screen coal and rock samples according to the pre-experimental data during the formal test; A b value determination module is used to determine the b value based on the screened coal rock sample and the acoustic emission information recorded during the loading process of the coal rock sample; the b value is the energy index of the acoustic emission signal; A b value change rate acquisition module is used to determine the change rate of the b value per unit time according to the b value; A warning signal threshold and release module, used to determine the warning signal threshold according to the change rate of the b value within the unit time, and release the warning signal when the measured change rate of the b value within the unit time exceeds the warning signal threshold; The failure position and failure surface analysis module is used to analyze the acoustic emission data and determine the location of the large energy event greater than the first energy threshold as the high-risk point of the coal and rock failure location; The positions of small energy events less than a second energy threshold are determined, and a surface connecting the gathering area of ​​the large energy events and passing through the gathering area of ​​the small energy events is used as a destruction surface.

Images