A method and apparatus for determining the slope of the boundary line in RA-AF analysis based on probability density distribution.

Abstract

This invention discloses a method and apparatus for determining the slope of the RA-AF analysis boundary line based on probability density distribution, relating to the field of acoustic emission monitoring technology. It includes: acquiring acoustic emission monitoring waveform signals; extracting the average frequency value AF and elevation cotangent value RA of acoustic emission events from the waveform signals; normalizing the average frequency value AF and elevation cotangent value RA to their maximum and minimum values; estimating the probability density distribution function using a Gaussian kernel function after normalization; setting the coordinates of the critical point based on the probability density distribution function and calculating the slope of the RA-AF analysis boundary line; and dividing the RA-AF plane into tensile crack regions, shear crack regions, or combined tensile-shear fracture regions using the slope of the RA-AF analysis boundary line as the dividing standard. This invention is applicable to all materials for which the RA-AF joint analysis method of acoustic emission signals is valid, and is more objective and universal compared to existing technologies.

Description

Technical Field

[0001] This invention relates to the field of acoustic emission monitoring technology, and in particular to a method and apparatus for determining the slope of the boundary line in RA-AF analysis based on probability density distribution. Background Technology

[0002] Microscopic fractures in materials can be classified into tensile and shear cracks. Both types of cracks produce acoustic emission phenomena when they form. By using acoustic emission acquisition equipment combined with signal analysis methods, crack types can be identified and quantitatively calculated, which helps to reveal the damage evolution mechanism of microscopic fractures in materials.

[0003] The Japan Building Materials Standards Association recommends using the ratio of the average acoustic emission frequency (AF) to the elevation angle cotangent (RA) to characterize different cracking modes, a method known as the RA-AF joint analysis method. Compared to methods such as P-wave initial motion theory and moment tensor analysis, this method has the advantages of simple principles and readily available parameters, and is widely used in the discrimination analysis of micro-fracture types in various ductile and brittle materials. However, this method subjectively relies on human experience to determine the critical value of the boundary slope, reducing the reliability of the discrimination results. Current research has proposed multi-parameter joint determination methods (see patent CN111812211A, "A Classification Method for Brittle Fracture Cracks in Rock Materials Based on Acoustic Emission Parameters: RA–AF–E") and machine learning methods (see patent CN112857987A, "A Machine Learning Algorithm for Discriminating Micro-Cracking Modes Based on Acoustic Emission Characteristics"), but these require additional feature parameters, involve complex calculation steps, and lack physical meaning, making them unsuitable for guiding practical applications. Summary of the Invention

[0004] This invention addresses the shortcomings of existing methods for determining parameters based on human experience, multiple parameters, and machine learning clustering.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0006] On one hand, this invention provides a method for determining the slope of the boundary line in RA-AF analysis based on probability density distribution. This method is implemented by an electronic device and includes:

[0007] S1. Acquire acoustic emission monitoring waveform signal, and extract the average frequency value AF and elevation angle cotangent value RA of acoustic emission events from the acoustic emission monitoring waveform signal.

[0008] S2. Normalize the average frequency value AF and the elevation angle cotangent value RA by performing maximum and minimum values. After normalization, use the Gaussian kernel function to estimate the probability density distribution function.

[0009] S3. Set the critical point coordinates according to the probability density distribution function, and calculate the slope of the RA-AF analysis boundary line.

[0010] S4. Using the slope of the RA-AF analysis boundary line as the dividing standard, the RA-AF plane is divided into tensile crack region, shear crack region, or tensile-shear combined fracture region.

[0011] Optionally, the average frequency value AF and elevation angle cotangent value RA of the acoustic emission event are extracted from the acoustic emission monitoring waveform signal in S1, as shown in the following equation (1):

[0012]

[0013] Among them, AF i Let RA be the average frequency value of the impact characteristic parameter of the i-th acoustic emission event in a total of n events. i Let be the elevation cotangent value of the impact characteristic parameter for the i-th acoustic emission event with a total of n, Count be the ringing count, Duration be the duration, Rise time be the rise time, and Maximum amplitude be the maximum amplitude.

[0014] Optionally, the average frequency value AF and the elevation angle cotangent value RA in S2 are normalized to their maximum and minimum values, as shown in equation (2) below:

[0015]

[0016] Optionally, the estimation of the probability density distribution function using the Gaussian kernel function in S2 includes:

[0017] S21. Determine the kernel function bandwidth h according to the silver curve criterion.

[0018] S22. Estimate the probability density functions of AF and RA based on the kernel function bandwidth h and the Gaussian kernel function.

[0019] Optionally, the kernel function bandwidth h in S21 is determined according to the silver curve criterion, as shown in equation (3) below:

[0020]

[0021] Where σ is the standard deviation of the data sample, IQR is the interquartile range of the data sample, and n is the total number of acoustic emission events.

[0022] Optionally, the probability density functions of AF and RA estimated in S22 based on the kernel function bandwidth h and the Gaussian kernel function are as shown in equation (4) below:

[0023]

[0024] in, For sample point x i The nuclear density estimate is given by n, where n is the total number of acoustic emission events.

[0025] Optionally, in S3, the critical point coordinates are set based on the probability density distribution function, and the slope of the RA-AF analysis boundary line is calculated, including:

[0026] S31. Based on the probability density distribution function, take the AF and RA values ​​with a cumulative value of 0.95 as the critical equations.

[0027] S32. Solve the critical equation to obtain the coordinates of the critical point.

[0028] S33. Calculate the slope k of the RA-AF analysis boundary line based on the coordinates of the critical point.

[0029] Optionally, in S4, the RA-AF plane is divided into tensile crack regions, shear crack regions, or combined tensile-shear fracture regions based on the slope of the RA-AF analysis boundary line, including:

[0030] Using the slope of the RA-AF analysis boundary line as the dividing standard, acoustic emission events located in the AF>k·RA half-plane are classified as tensile fractures.

[0031] Acoustic emission events located in the AF<k·RA half-plane are classified as shear fractures.

[0032] Acoustic emission events located on the dividing line AF = k·RA are classified as tension-shear composite fractures.

[0033] On the other hand, the present invention provides a device for determining the slope of the boundary line in RA-AF analysis based on probability density distribution. This device is used to implement a method for determining the slope of the boundary line in RA-AF analysis based on probability density distribution. The device includes:

[0034] The acquisition module is used to acquire acoustic emission monitoring waveform signals and extract the average frequency value AF and elevation cotangent value RA of acoustic emission events from the acoustic emission monitoring waveform signals.

[0035] The estimation module is used to normalize the average frequency value AF and the elevation angle cotangent value RA by performing maximum and minimum value normalization. After normalization, the probability density distribution function is estimated using the Gaussian kernel function.

[0036] The slope calculation module is used to set the critical point coordinates based on the probability density distribution function and calculate the slope of the RA-AF analysis boundary line.

[0037] The output module is used to divide the RA-AF plane into tensile crack regions, shear crack regions, or tensile-shear combined fracture regions based on the slope of the RA-AF analysis boundary line.

[0038] Optionally, the average frequency value AF and elevation cotangent value RA of the acoustic emission event are extracted from the acoustic emission monitoring waveform signal, as shown in the following equation (1):

[0039]

[0040] Among them, AF i Let RA be the average frequency value of the impact characteristic parameter of the i-th acoustic emission event in a total of n events. i Let be the elevation cotangent value of the impact characteristic parameter for the i-th acoustic emission event with a total of n, Count be the ringing count, Duration be the duration, Rise time be the rise time, and Maximum amplitude be the maximum amplitude.

[0041] Optionally, the average frequency value AF and the elevation angle cotangent value RA are normalized to their maximum and minimum values, as shown in equation (2) below:

[0042]

[0043] Optionally, the estimation module is further used for:

[0044] S21. Determine the kernel function bandwidth h according to the silver curve criterion.

[0045] S22. Estimate the probability density functions of AF and RA based on the kernel function bandwidth h and the Gaussian kernel function.

[0046] Alternatively, the kernel function bandwidth h can be determined according to the silver curve criterion, as shown in equation (3) below:

[0047]

[0048] Where σ is the standard deviation of the data sample, IQR is the interquartile range of the data sample, and n is the total number of acoustic emission events.

[0049] Alternatively, the probability density functions of AF and RA can be estimated based on the kernel function bandwidth h and the Gaussian kernel function, as shown in equation (4) below:

[0050]

[0051] in, For sample point x i The nuclear density estimate is given by n, where n is the total number of acoustic emission events.

[0052] Optionally, the slope calculation module is further used for:

[0053] S31. Based on the probability density distribution function, take the AF and RA values ​​with a cumulative value of 0.95 as the critical equations.

[0054] S32. Solve the critical equation to obtain the coordinates of the critical point.

[0055] S33. Calculate the slope k of the RA-AF analysis boundary line based on the coordinates of the critical point.

[0056] Optionally, the output module is further used for:

[0057] Using the slope of the RA-AF analysis boundary line as the dividing standard, acoustic emission events located in the AF>k·RA half-plane are classified as tensile fractures.

[0058] Acoustic emission events located in the AF<k·RA half-plane are classified as shear fractures.

[0059] Acoustic emission events located on the dividing line AF = k·RA are classified as tension-shear composite fractures.

[0060] On the one hand, an electronic device is provided, comprising a processor and a memory, wherein the memory stores at least one instruction, which is loaded and executed by the processor to implement the above-described method for determining the slope of the RA-AF analysis boundary line based on probability density distribution.

[0061] On the one hand, a computer-readable storage medium is provided, wherein at least one instruction is stored in the storage medium, the at least one instruction being loaded and executed by a processor to implement the above-described method for determining the slope of the boundary line in RA-AF analysis based on probability density distribution.

[0062] The above technical solution has at least the following advantages compared with the existing technology:

[0063] The above scheme discloses a method for determining the slope of the RA-AF analysis boundary line based on probability density distribution. First, characteristic parameters, the average frequency (AF) and elevation cotangent (RA), are extracted from the acoustic emission (AE) waveform signal. Second, the probability density distribution function is estimated using a Gaussian kernel function for the normalized AF and RA. The coordinates of the critical points of AF and RA with a cumulative probability density distribution function value of 0.95 are obtained. Then, the slope of the RA-AF analysis boundary line is calculated based on the coordinates of the critical points. Finally, the slope of the obtained RA-AF joint analysis boundary line is used as the dividing standard, dividing the RA-AF plane into two regions: tensile crack and shear crack. This invention is applicable to all materials for which the acoustic emission signal RA-AF joint analysis method is valid, and it is more objective and universal than existing technologies. Attached Figure Description

[0064] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0065] Figure 1 This is a schematic diagram of the method for determining the slope of the boundary line in RA-AF analysis based on probability density distribution provided in an embodiment of the present invention;

[0066] Figure 2 This is a schematic diagram of the acoustic emission monitoring test of a compact tensile specimen made of cast steel provided in an embodiment of the present invention;

[0067] Figure 3 This is a joint analysis diagram of displacement load and acoustic emission data provided in an embodiment of the present invention;

[0068] Figure 4 This is a schematic diagram illustrating the determination of the slope of the RA-AF joint analysis boundary line provided in an embodiment of the present invention;

[0069] Figure 5 This is a block diagram of the RA-AF analysis boundary slope determination device based on probability density distribution provided in the embodiments of the present invention;

[0070] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0071] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0072] like Figure 1 As shown, this embodiment of the invention provides a method for determining the slope of the RA-AF analysis boundary line based on probability density distribution, which can be implemented by electronic devices. Figure 1 The flowchart shown is for determining the slope of the boundary line in RA-AF analysis based on probability density distribution. The processing flow of this method may include the following steps:

[0073] S1. Acquire acoustic emission monitoring waveform signal, and extract the average frequency value AF and elevation angle cotangent value RA of acoustic emission event in the acoustic emission monitoring waveform signal according to the preset threshold voltage.

[0074] Optionally, the average frequency value AF and elevation angle cotangent value RA of the acoustic emission event are extracted from the acoustic emission monitoring waveform signal in S1, as shown in the following equation (1):

[0075]

[0076] Among them, AFi Let RA be the average frequency value of the impact characteristic parameter of the i-th acoustic emission event in a total of n events. i Let be the elevation cotangent value of the impact characteristic parameter for the i-th acoustic emission event with a total of n, Count be the ringing count, Duration be the duration (ms), Rise time be the rise time (ms), and Maximum amplitude be the maximum amplitude (V).

[0077] S2. Normalize the average frequency value AF and the elevation angle cotangent value RA by performing maximum and minimum values. After normalization, use the Gaussian kernel function to estimate the probability density distribution function.

[0078] Optionally, the average frequency value AF and the elevation angle cotangent value RA in S2 are normalized to their maximum and minimum values, as shown in equation (2) below:

[0079]

[0080] Optionally, the probability density distribution function is estimated using the Gaussian kernel function in S2, including S21-S22:

[0081] S21. Determine the kernel function bandwidth h according to the silver curve criterion, as shown in equation (3) below:

[0082]

[0083] Where σ is the standard deviation of the data sample, IQR is the interquartile range of the data sample, and n is the total number of acoustic emission events.

[0084] S22. Estimate the probability density functions of AF and RA based on the kernel function bandwidth h and the Gaussian kernel function, as shown in equation (4) below:

[0085]

[0086] in, For sample point x i The nuclear density estimate is given by n, where n is the total number of acoustic emission events.

[0087] S3. Set the critical point coordinates according to the probability density distribution function, and calculate the slope of the RA-AF analysis boundary line.

[0088] Optionally, step S3 above may include the following steps S31-S33:

[0089] S31. Based on the probability density distribution function, the AF and RA values ​​with a cumulative value of 0.95 are taken as the critical equations, as shown in equation (5) below:

[0090]

[0091] S32. Solve the critical equation to obtain the coordinates of the critical point.

[0092] S33. Based on the coordinates of the critical point, calculate the slope k of the RA-AF analysis boundary line, as shown in the following formula (6):

[0093]

[0094] S4. Using the slope of the RA-AF analysis boundary line as the dividing standard, the RA-AF plane is divided into tensile crack region, shear crack region, or tensile-shear combined fracture region.

[0095] Specifically, using the slope of the RA-AF analysis boundary line as the dividing standard, acoustic emission events located in the AF>k·RA half-plane are classified as tensile fractures.

[0096] Acoustic emission events located in the AF<k·RA half-plane are classified as shear fractures.

[0097] Acoustic emission events located on the dividing line AF = k·RA are classified as tension-shear composite fractures.

[0098] For example, the fracture toughness test of a certain cast steel compact tensile specimen is as follows: Figure 2 As shown, the specimen includes a DDL-100 microcomputer-controlled electronic universal testing machine loading end 1, a COD clamp extensometer 2, a PAC acoustic emission sensor 3, and a compact tensile specimen 4; the CT specimen has a thickness of 15 mm, a width of 60 mm, a step height of 4.5 mm, a machining notch length of 17.5 mm, a pre-existing fatigue crack length of 2 mm, an initial crack length of 24 mm, an ultimate tensile strength of 583.9 MPa, and a yield strength of 330.4 MPa.

[0099] A PCI-2 type acoustic emission monitor and an R15 resonant narrowband sensor were used. The threshold voltage was 35dB, the preamplifier gain was 40dB, the sampling frequency was 3MHz, the peak defined event was set to 300us, the impact defined time was set to 600us, the impact latch-up time was set to 1000us, and the maximum duration was set to 1000us. The acoustic emission sensor layout is shown in [reference needed]. Figure 2 .

[0100] Monotonic tensile tests were performed on the specimens. The loading device was a DDL-100 microcomputer-controlled electronic universal testing machine (loading capacity of 10t). The loading was carried out by displacement control and the loading rate was 0.5mm / min.

[0101] From the start of loading to specimen failure, the experimental process was monitored using acoustic emission equipment, such as... Figure 3As shown, the test displacement-load and the corresponding acoustic emission count and cumulative count relationship are obtained. The average frequency value AF and elevation angle cotangent value RA of all acoustic emission events are extracted according to Equation (1).

[0102] According to equation (2), the average frequency value AF and the elevation cotangent value RA of all acoustic emission events are normalized to the maximum and minimum, and the kernel function bandwidth is determined according to equation (3). In this embodiment, the RA kernel function bandwidth is 2.55 and the AF kernel function bandwidth is 58.64.

[0103] like Figure 4 As shown, the probability density distributions of AF and RA are estimated according to the Gaussian kernel function of equation (4). The AF and RA values ​​with a cumulative value of 0.95 are taken as the critical point coordinates, and the slope of the dividing line k = 14.10 is calculated.

[0104] Using the line AF = 14.1RA as the boundary, acoustic emission events are divided into two categories: tensile fracture (corresponding to AF > 14.1RA) and shear fracture (corresponding to AF < 14.1RA). In this embodiment, tensile cracks account for 74.45% and shear cracks account for 25.55%.

[0105] This invention discloses a method for determining the slope of the RA-AF analysis boundary line based on probability density distribution. First, characteristic parameters, the average frequency (AF) and elevation cotangent (RA), are extracted from the acoustic emission (AE) waveform signal. Second, the probability density distribution function is estimated using a Gaussian kernel function on the normalized AF and RA. The coordinates of the critical points of AF and RA with a cumulative probability density distribution function value of 0.95 are obtained. Then, the slope of the RA-AF analysis boundary line is calculated based on the critical point coordinates. Finally, the slope of the obtained RA-AF joint analysis boundary line is used as the dividing standard, dividing the RA-AF plane into two regions: tensile crack and shear crack. This invention is applicable to all materials for which the acoustic emission signal RA-AF joint analysis method is valid, and it is more objective and universal compared to existing technologies.

[0106] like Figure 5 As shown, this embodiment of the invention provides a device 500 for determining the slope of the RA-AF analysis boundary line based on probability density distribution. This device 500 is used to implement a method for determining the slope of the RA-AF analysis boundary line based on probability density distribution. The device 500 includes:

[0107] The acquisition module 510 is used to acquire acoustic emission monitoring waveform signals and extract the average frequency value AF and elevation angle cotangent value RA of acoustic emission events from the acoustic emission monitoring waveform signals.

[0108] The estimation module 520 is used to normalize the average frequency value AF and the elevation angle cotangent value RA by performing maximum and minimum value normalization, and then using the Gaussian kernel function to estimate the probability density distribution function after normalization.

[0109] The slope calculation module 530 is used to set the coordinates of the critical point based on the probability density distribution function and to calculate the slope of the RA-AF analysis boundary line.

[0110] Output module 540 is used to divide the RA-AF plane into tensile crack region, shear crack region, or tensile-shear combined fracture region based on the slope of the RA-AF analysis boundary line.

[0111] Optionally, the average frequency value AF and elevation cotangent value RA of the acoustic emission event are extracted from the acoustic emission monitoring waveform signal, as shown in the following equation (1):

[0112]

[0113] Among them, AF i Let RA be the average frequency value of the impact characteristic parameter of the i-th acoustic emission event in a total of n events. i Let be the elevation cotangent value of the impact characteristic parameter for the i-th acoustic emission event with a total of n, Count be the ringing count, Duration be the duration, Rise time be the rise time, and Maximum amplitude be the maximum amplitude.

[0114] Optionally, the average frequency value AF and the elevation angle cotangent value RA are normalized to their maximum and minimum values, as shown in equation (2) below:

[0115]

[0116] Optionally, the estimation module is further used for:

[0117] S21. Determine the kernel function bandwidth h according to the silver curve criterion.

[0118] S22. Estimate the probability density functions of AF and RA based on the kernel function bandwidth h and the Gaussian kernel function.

[0119] Alternatively, the kernel function bandwidth h can be determined according to the silver curve criterion, as shown in equation (3) below:

[0120]

[0121] Where σ is the standard deviation of the data sample, IQR is the interquartile range of the data sample, and n is the total number of acoustic emission events.

[0122] Alternatively, the probability density functions of AF and RA can be estimated based on the kernel function bandwidth h and the Gaussian kernel function, as shown in equation (4) below:

[0123]

[0124] in, For sample point x i The nuclear density estimate is given by n, where n is the total number of acoustic emission events.

[0125] Optionally, the slope calculation module is further used for:

[0126] S31. Based on the probability density distribution function, take the AF and RA values ​​with a cumulative value of 0.95 as the critical equations.

[0127] S32. Solve the critical equation to obtain the coordinates of the critical point.

[0128] S33. Calculate the slope k of the RA-AF analysis boundary line based on the coordinates of the critical point.

[0129] Optionally, the output module is further used for:

[0130] Using the slope of the RA-AF analysis boundary line as the dividing standard, acoustic emission events located in the AF>k·RA half-plane are classified as tensile fractures.

[0131] Acoustic emission events located in the AF<k·RA half-plane are classified as shear fractures.

[0132] Acoustic emission events located on the dividing line AF = k·RA are classified as tension-shear composite fractures.

[0133] This invention discloses a method for determining the slope of the RA-AF analysis boundary line based on probability density distribution. First, characteristic parameters, the average frequency (AF) and elevation cotangent (RA), are extracted from the acoustic emission (AE) waveform signal. Second, the probability density distribution function is estimated using a Gaussian kernel function on the normalized AF and RA. The coordinates of the critical points of AF and RA with a cumulative probability density distribution function value of 0.95 are obtained. Then, the slope of the RA-AF analysis boundary line is calculated based on the critical point coordinates. Finally, the slope of the obtained RA-AF joint analysis boundary line is used as the dividing standard, dividing the RA-AF plane into two regions: tensile crack and shear crack. This invention is applicable to all materials for which the acoustic emission signal RA-AF joint analysis method is valid, and it is more objective and universal compared to existing technologies.

[0134] Figure 6This is a schematic diagram of the structure of an electronic device 600 provided in an embodiment of the present invention. The electronic device 600 can vary considerably due to differences in configuration or performance. It may include one or more central processing units (CPUs) 601 and one or more memories 602. The memory 602 stores at least one instruction, which is loaded and executed by the processor 601 to implement the following method for determining the slope of the RA-AF analysis boundary line based on probability density distribution:

[0135] S1. Acquire acoustic emission monitoring waveform signal, and extract the average frequency value AF and elevation angle cotangent value RA of acoustic emission events from the acoustic emission monitoring waveform signal.

[0136] S2. Normalize the average frequency value AF and the elevation angle cotangent value RA by performing maximum and minimum values. After normalization, use the Gaussian kernel function to estimate the probability density distribution function.

[0137] S3. Set the critical point coordinates according to the probability density distribution function, and calculate the slope of the RA-AF analysis boundary line.

[0138] S4. Using the slope of the RA-AF analysis boundary line as the dividing standard, the RA-AF plane is divided into tensile crack region, shear crack region, or tensile-shear combined fracture region.

[0139] In an exemplary embodiment, a computer-readable storage medium is also provided, such as a memory including instructions that can be executed by a processor in a terminal to perform the above-described method for determining the slope of the RA-AF analysis boundary line based on probability density distribution. For example, the computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0140] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0141] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for determining the slope of a RA-AF analysis boundary based on a probability density distribution, characterized by, The method comprises: S1, acquiring an acoustic emission monitoring waveform signal, and extracting an average frequency value AF and an elevation cotangent value RA of an acoustic emission event in the acoustic emission monitoring waveform signal; S2, performing maximum-minimum value normalization on the average frequency value AF and the elevation cotangent value RA, and estimating a probability density distribution function by using a Gaussian kernel function after normalization; S3, setting a critical point coordinate according to the probability density distribution function, and calculating a RA-AF analysis boundary line slope; S4, dividing an RA-AF plane into a tensile crack region or a shear crack region or a tensile-shear composite fracture according to the RA-AF analysis boundary line slope as a division standard; The extraction of the average frequency value AF and the elevation cotangent value RA of the acoustic emission event in the acoustic emission monitoring waveform signal in S1 is shown in the following formula (1): （1） in, The total number is The The average frequency value of the impact characteristic parameter of each acoustic emission event. The total number is The The impact characteristic parameters of an acoustic emission event are: elevation cotangent value, count (ring count), duration (duration), rise time (rise time), and maximum amplitude (maximum amplitude). The maximum-minimum value normalization of the average frequency value AF and the elevation cotangent value RA in S2 is shown in the following formula (2): （2） The estimation of the probability density distribution function by using the Gaussian kernel function in S2 comprises: S21, determining the kernel bandwidth according to the silver curve criterion ; S22、according to the kernel function bandwidth and the Gaussian kernel function estimate the probability density distribution function of AF and RA; determining the kernel bandwidth in S21 according to the silver curve criterion as shown in the following formula (3): （3） wherein, is the standard deviation of the data samples, is the interquartile range of the data samples, is the total number of acoustic emission events; The bandwidth of the kernel function in S22 is determined according to the following formula (3) : And the Gaussian kernel function estimates the probability density distribution function of AF and RA, as shown in the following formula (4): （4） wherein is the kernel density estimate for the sample points is the kernel density estimate for the sample points is the total number of acoustic emission events; The setting of the critical point coordinate according to the probability density distribution function and the calculation of the RA-AF analysis boundary line slope in S3 comprise: S31, taking an AF and RA value with a cumulative value of 0.95 as a critical equation according to the probability density distribution function; S32, solving the critical equation to obtain the critical point coordinates ; S33、According to the critical point coordinates, calculate the RA-AF analysis demarcation line slope ; The division of the RA-AF plane into the tensile crack region or the shear crack region or the tensile-shear composite fracture according to the RA-AF analysis boundary line slope as the division standard in S4 comprises: With the slope of the RA-AF analysis demarcation line as the dividing standard, the acoustic emission events located The semi-planar acoustic emission events are divided into tensile fractures; The located The semi-planar acoustic emission event is classified as a shear fracture; The acoustic emission events located on the boundary line are classified as a tensile-shear composite fracture.

2. A device for determining a slope of a boundary line in RA-AF analysis based on a probability density distribution, the device for determining a slope of a boundary line in RA-AF analysis based on a probability density distribution being used to implement the method for determining a slope of a boundary line in RA-AF analysis based on a probability density distribution as claimed in claim 1, characterized in that, The device comprises: An acquisition module configured to acquire an acoustic emission monitoring waveform signal, and extract an average frequency value AF and an elevation cotangent value RA of an acoustic emission event in the acoustic emission monitoring waveform signal; An estimation module configured to perform maximum-minimum value normalization on the average frequency value AF and the elevation cotangent value RA, and estimate a probability density distribution function by using a Gaussian kernel function after normalization; A slope calculation module configured to set a critical point coordinate according to the probability density distribution function, and calculate a RA-AF analysis boundary line slope; An output module configured to divide an RA-AF plane into a tensile crack region or a shear crack region or a tensile-shear composite fracture according to the RA-AF analysis boundary line slope as a division standard.

Images