Coal rock characteristic load determination method, device, equipment and storage medium

Abstract

The present application provides a kind of coal rock characteristic load determination method, device, equipment and storage medium, comprising: the deformation parameter corresponding to each collection time obtained by collecting in the process of coal rock sample test is acquired;According to the deformation parameter corresponding to each collection time, the volume deformation and crack volume deformation corresponding to each collection time are calculated;Based on the corresponding relationship between the axial load, axial deformation, hoop deformation, volume deformation and crack volume deformation corresponding to each collection time, the characteristic value of the multiple characteristic loads corresponding to coal rock sample test is determined.The scheme of the present application improves the accuracy of coal rock characteristic load.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of coal rock testing, and in particular to a coal rock characteristic load determination method, device, equipment and storage medium. BACKGROUND

[0002] In the process of physical and mechanical property determination of coal rock materials in the construction area of geotechnical engineering construction, a plurality of coal rock characteristic loads need to be determined. For example, crack closure load, crack initiation load, damage load, extreme load, expansion load and peak load.

[0003] At present, coal rock characteristic loads are mainly determined by information obtained by external devices such as acoustic emission devices. In practice, fasteners are needed to ensure that the external device is in close contact with the sample to be tested throughout the test process. The contact quality of the external device, the quality of the obtained information and the use of the fastener will all affect the value of the coal rock characteristic load.

[0004] In related technologies, coal rock characteristic loads need to be determined by external devices, and the accuracy of coal rock characteristic loads is low. SUMMARY

[0005] The present application provides a coal rock characteristic load determination method, device, equipment and storage medium to solve the defect that the accuracy of coal rock characteristic loads is low in the prior art, which avoids the influence of external devices on coal rock characteristic loads and improves the accuracy of coal rock characteristic loads.

[0006] The present application provides a coal rock characteristic load determination method, which comprises: obtaining the deformation parameters corresponding to each collection time collected in the process of testing a coal rock sample, wherein the deformation parameters include axial load, axial deformation and hoop deformation; calculating the volume deformation and crack volume deformation corresponding to each collection time according to the deformation parameters corresponding to each collection time; determining the characteristic values of a plurality of characteristic loads corresponding to the coal rock sample test based on the corresponding relationship between the axial load, axial deformation, hoop deformation, volume deformation and crack volume deformation corresponding to each collection time; wherein the plurality of characteristic loads corresponding to the coal rock sample test include crack closure load, crack initiation load, damage load, extreme load, expansion load and peak load.

[0007] The application provides a coal rock characteristic load determination method, which is based on the corresponding relationship among axial load, axial deformation, hoop deformation, volume deformation and crack volume deformation corresponding to each collection time, determines characteristic values of a plurality of characteristic loads corresponding to coal rock sample testing, and comprises the following steps: constructing collection time data set, axial load data set, axial deformation data set, hoop deformation data set, volume deformation data set and crack volume deformation data set according to the axial load, axial deformation, hoop deformation, volume deformation and crack volume deformation corresponding to each collection time; determining first intermediate values of crack closure load, first intermediate values of crack initiation load, first intermediate values of extreme value load and first intermediate values of peak value load through moving point regression calculation based on the axial load data set and the axial deformation data set; determining second intermediate values of crack closure load, second intermediate values of crack initiation load, second intermediate values of extreme value load, second intermediate values of peak value load and first intermediate values of dilatancy load through moving point regression calculation based on the axial load data set, the hoop deformation data set and the collection time data set; determining third intermediate values of crack initiation load, first intermediate values of damage load, second intermediate values of dilatancy load, third intermediate values of extreme value load and third intermediate values of peak value load through moving point regression calculation based on the axial load data set, the volume deformation data set and the collection time data set; determining third intermediate values of crack closure load, fourth intermediate values of crack initiation load, second intermediate values of damage load, third intermediate values of dilatancy load, fourth intermediate values of extreme value load and fourth intermediate values of peak value load through moving point regression calculation based on the axial load data set, the crack volume deformation data set and the collection time data set; and calculating the characteristic values of the plurality of characteristic loads corresponding to the coal rock sample testing according to the intermediate values of each characteristic load corresponding to each corresponding relationship.

[0008] According to the coal rock characteristic load determination method provided by the application, the first intermediate value of the crack closure load, the first intermediate value of the crack initiation load, the first intermediate value of the extreme value load and the first intermediate value of the peak value load are determined by moving point regression calculation based on the axial load data set and the axial deformation data set, including: performing moving point linear regression based on the axial load data set and the axial deformation data set to obtain a first regression coefficient data set; performing moving point linear regression based on the axial load data set and the first regression coefficient data set to calculate the first regression goodness corresponding to the axial load corresponding to each collection time; in the order of collection time, the axial load corresponding to the first regression goodness greater than the first threshold value in the first regression goodness increasing process is taken as the first intermediate value of the crack closure load; the axial load corresponding to the first regression goodness smaller than the first threshold value in the first regression goodness decreasing process is taken as the first intermediate value of the crack initiation load; for all the first regression coefficients in the first regression coefficient data set, the first product result of adjacent two first regression coefficients is calculated; if the first product result is smaller than 0, the last axial load in the data window corresponding to the smaller first regression coefficient of the adjacent two first regression coefficients is taken as the first intermediate value of the extreme value load; the maximum value of all the first intermediate values of the extreme value load is taken as the first intermediate value of the peak value load.

[0009] According to the coal rock characteristic load determination method provided by the application, the second intermediate value of crack closure load, the second intermediate value of crack initiation load, the second intermediate value of extreme value load, the second intermediate value of peak load and the first intermediate value of dilatancy load are determined through moving point regression calculation based on the axial load data set, the hoop deformation data set and the collection time data set, including: taking the axial load corresponding to the axial deformation greater than 0 in the hoop deformation data set as the second intermediate value of crack closure load; performing moving point linear regression based on the axial load data set and the hoop deformation data set to obtain a second regression coefficient data set; performing moving point linear regression based on the second regression coefficient data set and the collection time data set to obtain a third regression coefficient data set; taking the axial load corresponding to the third regression coefficient greater than 0 in the third regression coefficient data set as the second intermediate value of crack initiation load; calculating the second product result of adjacent two second regression coefficients for all second regression coefficients in the second regression coefficient data set; if the second product result is less than 0, taking the last axial load in the data window corresponding to the smaller second regression coefficient of the adjacent two second regression coefficients as the second intermediate value of extreme value load; taking the maximum value of all second intermediate values of extreme value load as the second intermediate value of peak load; calculating the first ratio result of the hoop deformation and the axial deformation in the hoop deformation data set and the axial deformation data set in the order of collection time; taking the axial load corresponding to the first ratio result greater than the second threshold value as the first intermediate value of dilatancy load.

[0010] According to the coal rock characteristic load determination method provided by the application, the third intermediate value of the cracking load, the first intermediate value of the damage load, the second intermediate value of the expansion load, the third intermediate value of the extreme value load and the third intermediate value of the peak value load are determined through moving point regression calculation based on the axial load data set, the volume deformation data set and the collection time data set, and the method comprises the following steps: according to the order of the collection time, the axial load corresponding to the volume deformation of 0 in the second volume deformation in the volume deformation data set is taken as the second intermediate value of the expansion load; moving point linear regression is performed based on the axial load data set and the volume deformation data set to obtain a fourth regression coefficient data set; moving point linear regression is performed based on the fourth regression coefficient data set and the collection time data set to obtain a fifth regression coefficient data set; the axial load corresponding to the fourth regression coefficient equal to 0 in the fourth regression coefficient data set is taken as the first intermediate value of the damage load; the axial load corresponding to the fifth regression coefficient equal to 0 in the fifth regression coefficient data set is taken as the third intermediate value of the cracking load; for all the fourth regression coefficients in the fourth regression coefficient data set, the third product result of adjacent two fourth regression coefficients is calculated; if the third product result is less than 0, the last axial load in the data window corresponding to the smaller fourth regression coefficient of the adjacent two fourth regression coefficients is taken as the third intermediate value of the extreme value load; and the maximum value of all the third intermediate values of the extreme value load is taken as the third intermediate value of the peak value load.

[0011] According to the coal rock characteristic load determination method provided by the application, the third intermediate value of crack closure load, the fourth intermediate value of crack initiation load, the second intermediate value of damage load, the third intermediate value of dilatancy load, the fourth intermediate value of extreme value load and the fourth intermediate value of peak value load are determined through moving point regression calculation based on the axial load data set, the crack volume deformation data set and the collection time data set, and the method comprises the following steps: taking the first crack volume deformation of 0 in the crack volume deformation data set as the third intermediate value of the crack closure load in the order of collection time; taking the second crack volume deformation of 0 in the crack volume deformation data set as the third intermediate value of the dilatancy load; performing moving point linear regression based on the axial load data set and the crack volume deformation data set to obtain a sixth regression coefficient data set; performing moving point linear regression based on the sixth regression coefficient data set and the collection time data set to obtain a seventh regression coefficient data set; taking the axial load corresponding to the sixth regression coefficient of 0 in the sixth regression coefficient data set as the second intermediate value of the damage load; taking the axial load corresponding to the seventh regression coefficient of 0 in the seventh regression coefficient data set as the fourth intermediate value of the crack initiation load; calculating the fourth product result of adjacent two sixth regression coefficients for all sixth regression coefficients in the sixth regression coefficient data set; if the fourth product result is less than 0, taking the last axial load in the data window corresponding to the smaller sixth regression coefficient of the adjacent two sixth regression coefficients as the fourth intermediate value of the extreme value load; and taking the maximum value of all fourth intermediate values of the extreme value load as the fourth intermediate value of the peak value load.

[0012] According to the coal rock characteristic load determination method provided by the application, the characteristic value of each characteristic load corresponding to each corresponding relationship is calculated to obtain the characteristic values of the multiple characteristic loads corresponding to the coal rock sample test, and the method comprises the following steps: for each characteristic load, calculating the relative error value of all intermediate values corresponding to the characteristic load; if the relative error value is less than an error threshold value, calculating the average value of all intermediate values to obtain the characteristic value of the characteristic load; and if the relative error value is not less than the error threshold value, removing the intermediate values that do not meet the error requirement and calculating the average value of all intermediate values that meet the error requirement to obtain the characteristic value of the characteristic load.

[0013] The application further provides a coal rock characteristic load determination device, comprising: a collection module, configured to acquire a deformation parameter corresponding to each collection time collected in a coal rock sample test process, wherein the deformation parameter comprises an axial load, an axial deformation and a hoop deformation; a calculation module, configured to calculate a volume deformation and a crack volume deformation corresponding to each collection time according to the deformation parameter corresponding to each collection time; and a processing module, configured to determine characteristic values of a plurality of characteristic loads corresponding to the coal rock sample test based on a corresponding relationship among the axial load, the axial deformation, the hoop deformation, the volume deformation and the crack volume deformation corresponding to each collection time, wherein the plurality of characteristic loads corresponding to the coal rock sample test comprise a crack closure load, a crack initiation load, a damage load, an extreme load, an expansion load and a peak load.

[0014] The application further provides an electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the coal rock characteristic load determination method according to any one of the above when executing the program.

[0015] The application further provides a non-transitory computer readable storage medium having a computer program stored thereon, wherein the computer program is executable by a processor to implement the coal rock characteristic load determination method according to any one of the above.

[0016] The application further provides a computer program product comprising a computer program, wherein the computer program is executable by a processor to implement the coal rock characteristic load determination method according to any one of the above.

[0017] The coal rock characteristic load determination method, device, equipment and storage medium provided by the application can calculate the volume deformation and the crack volume deformation corresponding to each collection time based on the deformation parameter collected in the coal rock sample test process, and can determine the characteristic values of the plurality of characteristic loads corresponding to the coal rock sample test by considering the corresponding relationship among the axial load, the axial deformation, the hoop deformation, the volume deformation and the crack volume deformation corresponding to each collection time. Therefore, the coal rock characteristic load determination can be realized without external equipment according to the scheme of the application, the influence of the external equipment on the coal rock characteristic load is avoided, the accuracy of the coal rock characteristic load is improved, and the accuracy and reliability of the coal rock test are further improved. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the application or prior art, the following will briefly introduce the drawings needed in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0019] Figure 1 is one of flowcharts of the coal rock characteristic load determination method provided by the present application.

[0020] Figure 2 is one of flowcharts of the coal rock characteristic load determination method provided by the present application.

[0021] Figure 3 is one of structural diagrams of the coal rock characteristic load determination device provided by the present application.

[0022] Figure 4 is one of structural diagrams of the coal rock characteristic load determination device provided by the present application.

[0023] Figure 5 is one of structural diagrams of the coal rock characteristic load determination device provided by the present application. DETAILED DESCRIPTION

[0024] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below with reference to the drawings in the present application. Obviously, the described embodiments are some embodiments but not all embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work belong to the scope of protection of the present application.

[0025] The technical solutions of the present application and how the technical solutions of the present application solve the above technical problems will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes can not be described again in some embodiments. The embodiments of the present application will be described below with reference to the drawings.

[0026] Figure 1 is one of flowcharts of the coal rock characteristic load determination method provided by the present application, as shown in Figure 1 the method comprises steps 101 to 103.

[0027] Step 101: obtaining the deformation parameters corresponding to each collection time collected in the process of testing the coal rock sample, wherein the deformation parameters include axial load, axial deformation and hoop deformation.

[0028] The axial load refers to the load generated in the axial direction of the coal rock sample. The axial deformation refers to the deformation size of the coal rock sample caused by external force in the axial direction. The hoop deformation refers to the deformation size of the coal rock sample caused by external force in the hoop direction. In actual application, the axial load, axial deformation and hoop deformation can be directly collected in the process of testing the coal rock sample.

[0029] In combination with the application scenario, the standard coal rock sample is processed, and the displacement control method is used for uniaxial loading test of the standard coal rock sample. The loading rate can be set to 0.03 mm / min until the standard coal rock sample is completely destroyed. During the whole coal rock sample test process, the axial load, axial deformation and hoop deformation at the collection time are collected. For example, the deformation parameters can be collected periodically, and the collection frequency of the deformation parameters can be set before the coal rock sample test starts, that is, the time interval between adjacent collection times during the coal rock sample test is fixed. For example, the collection frequency of the deformation parameters is not less than 1 kHz.

[0030] Step 102: According to the deformation parameters corresponding to each collection time, the volume deformation and crack volume deformation corresponding to each collection time are calculated.

[0031] It should be noted that the axial load, axial deformation and hoop deformation corresponding to each collection time can be collected. Based on the axial load, axial deformation and hoop deformation corresponding to each collection time, the volume deformation and crack volume deformation corresponding to the collection time can be obtained.

[0032] For example, the axial load is denoted as f, the axial deformation is denoted as l1, and the hoop deformation is denoted as l2. Specifically, the volume deformation l is calculated according to the axial deformation l1 and the hoop deformation l2. v , l v = l1-2l2. Further, the elastic volume deformation l is calculated according to the axial load f. In the formula, μ is the Poisson's ratio of the coal rock sample, and E is the elastic modulus of the coal rock sample. Further, the crack volume deformation l v is calculated according to the volume deformation l

[0033] Step 103: Based on the corresponding relationship between the axial load, axial deformation, hoop deformation, volume deformation and crack volume deformation corresponding to each collection time, the characteristic values of the multiple characteristic loads corresponding to the coal rock sample test are determined; wherein the multiple characteristic loads corresponding to the coal rock sample test include: crack closure load, crack initiation load, damage load, extreme load, expansion load and peak load.

[0034] In practical application, the axial load f, the axial deformation l1, the hoop deformation l2, the volume deformation l v , the crack volume deformation l and the multiple characteristic loads have a correlation. In this embodiment, the axial load f, the axial deformation l1, the hoop deformation l2, the volume deformation l v , the crack volume deformation l corresponding to the coal rock sample test, the characteristic values of the plurality of characteristic loads corresponding to the coal rock sample test can be determined. For example, the axial load f, the axial deformation l1, the hoop deformation l2, the volume deformation l3 and the crack volume deformation l4 corresponding to each collection time can be analyzed respectively. v crack volume deformation corresponding to the coal rock sample test, the characteristic values of the plurality of characteristic loads corresponding to the coal rock sample test can be determined. For example, the axial load f, the axial deformation l1, the hoop deformation l2, the volume deformation l3 and the crack volume deformation l4 corresponding to each collection time can be analyzed respectively.

[0035] It can be understood that the coal rock characteristic load determination method provided in the embodiment can determine the coal rock characteristic load without external equipment, avoids the influence of external equipment on the coal rock characteristic load, improves the accuracy of the coal rock characteristic load, and further improves the accuracy and reliability of the coal rock test.

[0036] For the determination method of the characteristic values of the plurality of characteristic loads corresponding to the coal rock sample test, as an example, in a possible implementation manner, Figure 2 is a flowchart of the coal rock characteristic load determination method provided by the present application, as shown in Figure 2 the above step 103 includes steps 201 to 206.

[0037] Step 201: According to the axial load, the axial deformation, the hoop deformation, the volume deformation and the crack volume deformation corresponding to each collection time, the collection time data set, the axial load data set, the axial deformation data set, the hoop deformation data set, the volume deformation data set and the crack volume deformation data set are constructed.

[0038] In practical application, the axial load f, the axial deformation l1, the hoop deformation l2, the volume deformation l3 and the crack volume deformation l4 corresponding to all collection times are extracted respectively. v crack volume deformation The collection time data set, the axial load data set, the axial deformation data set, the hoop deformation data set, the volume deformation data set and the crack volume deformation data set are constructed. It should be noted that the data in the collection time data set, the axial load data set, the axial deformation data set, the hoop deformation data set, the volume deformation data set and the crack volume deformation data set are stored in the order of the collection time.

[0039] It can be understood that the collection time data set includes each collection time. The axial load data set includes the axial load corresponding to each collection time. The axial deformation data set includes the axial deformation corresponding to each collection time. The hoop deformation data set includes the hoop deformation corresponding to each collection time. The volume deformation data set includes the volume deformation corresponding to each collection time. The crack volume deformation data set includes the crack volume deformation.

[0040] Step 202: based on the axial load data set and the axial deformation data set, a first intermediate value of the crack closure load, a first intermediate value of the crack initiation load, a first intermediate value of the extreme value load, and a first intermediate value of the peak load are determined by moving point regression calculation.

[0041] In practical applications, in order to ensure the reliability of the moving point linear regression, it is necessary to calculate the regression goodness of fit R 2 , and according to the regression goodness of fit R 2 , it is determined whether the current moving point linear regression is effective, and when it is not effective, the data amount of the data window is adjusted according to the regression goodness of fit R 2 . Specifically, in the moving point linear regression process, the regression goodness of fit R 2 is calculated, and the calculation formula of the regression goodness of fit R 2 is as follows.

[0042]

[0043] Among them, is the fitting data calculated by the fitting function corresponding to the moving point linear regression, y i is the actually measured data, is the mean value of the measured data. Specifically, a regression threshold can be set, for example, the regression threshold is set to 0.85, if the regression goodness of fit R 2 is not greater than the regression threshold, it is determined that the moving point linear regression is invalid, at this time, the data amount of the data window is increased, and linear regression is performed again.

[0044] In an example, the step 202 includes the following steps. Moving point linear regression is performed based on the axial load data set and the axial deformation data set to obtain a first regression coefficient data set. Moving point linear regression is performed based on the axial load data set and the first regression coefficient data set to calculate the first regression goodness of fit corresponding to each acquisition time corresponding to the axial load. According to the order of the acquisition time, the first regression goodness of fit is increased, and the first regression goodness of fit corresponding to the first threshold is taken as the first intermediate value of the crack closure load. The first regression goodness of fit is decreased, and the first regression goodness of fit corresponding to the first threshold is taken as the first intermediate value of the crack initiation load. For all first regression coefficients in the first regression coefficient data set, the first product result of adjacent two first regression coefficients is calculated. If the first product result is less than 0, the last axial load in the data window corresponding to the smaller first regression coefficient of the adjacent two first regression coefficients is taken as the first intermediate value of the extreme value load. The maximum value of all first intermediate values of the extreme value load is taken as the first intermediate value of the peak load.

[0045] In practical applications, the data window corresponding to the moving-point linear regression should include no fewer than 5 data points and no more than 1% of the total data. A first regression equation is established for the axial load dataset and the axial deformation dataset: f = a1 × l1 + b1, where a1 is the first regression coefficient, representing the magnitude of the influence of axial deformation on the axial load. b1 is the error coefficient of the first regression equation. Specifically, the data window is moved sequentially, and moving-point linear regression is performed on the axial load dataset and the axial deformation dataset. The change of the first regression coefficient a1 with the axial load f during the entire moving-point linear regression process is recorded, resulting in the first regression coefficient dataset.

[0046] Furthermore, linear regression at moving points is performed based on the axial load dataset and the first regression coefficient dataset. Throughout the linear regression process, the first regression degree corresponding to the axial load at each acquisition time is calculated.

[0047] In practical applications, the first regression degree is determined according to the order of data collection time. First increase, then decrease. Adjust the first regression goodness. During the increase, the first regression goodness that exceeds the first threshold The corresponding axial load f is used as the first intermediate value f of the crack closure load. 11 The first regression goodness During the reduction process, the first regression goodness of the first value below the first threshold The corresponding axial load f is used as the first intermediate value f of the crack initiation load. 12 .

[0048] Specifically, the i-th first regression coefficient is denoted as a. 1i The (i+1)th first regression coefficient is denoted as a. 1i+1 The i-th first product result is represented as p 1i p 1i =a 1i ×a 1i+1 , where i = 1, ..., m-1; m is the number of first regression coefficients in the first regression coefficient dataset.

[0049] In practical applications, the i-th first product result is represented as p. 1i Less than 0 indicates that a 1i and a 1i+1 With the signs reversed, and in conjunction with the above explanation, the first regression coefficient a1 characterizes the magnitude of the influence of axial deformation on axial load. Therefore, the smaller of the two adjacent first regression coefficients a1 and a2 is used. 1i The last axial load f in the corresponding data window is taken as the first intermediate value f of the extreme load. 14 .

[0050] It should be noted that there can be multiple extreme loads in the process of one-time loading test of one coal rock sample, therefore, the first intermediate value f 14 of each extreme load is recorded. Further, the maximum value among the first intermediate values f 14 of all extreme loads is taken as the first intermediate value f 16 of the peak load.

[0051] Step 203: Based on the axial load data set, the hoop deformation data set and the acquisition time data set, the second intermediate value of the crack closure load, the second intermediate value of the crack initiation load, the second intermediate value of the extreme load, the second intermediate value of the peak load and the first intermediate value of the dilatancy load are determined by moving point regression calculation.

[0052] In an example, the above step 203 includes the following steps. The axial load corresponding to the axial deformation greater than 0 in the hoop deformation data set is taken as the second intermediate value of the crack closure load. Moving point linear regression is performed based on the axial load data set and the hoop deformation data set to obtain a second regression coefficient data set. Moving point linear regression is performed based on the second regression coefficient data set and the acquisition time data set to obtain a third regression coefficient data set. The axial load corresponding to the third regression coefficient greater than 0 in the third regression coefficient data set is taken as the second intermediate value of the crack initiation load. For all second regression coefficients in the second regression coefficient data set, the second product result of the adjacent two second regression coefficients is calculated. If the second product result is less than 0, the last axial load in the data window corresponding to the smaller second regression coefficient of the adjacent two second regression coefficients is taken as the second intermediate value of the extreme load. The maximum value among the second intermediate values of all extreme loads is taken as the second intermediate value of the peak load. According to the order of acquisition time, the first ratio result of the hoop deformation and the axial deformation in the hoop deformation data set and the axial deformation data set is calculated; the axial load corresponding to the first ratio result greater than the second threshold value is taken as the first intermediate value of the dilatancy load.

[0053] Specifically, the axial deformation l1 greater than 0 in the hoop deformation data set is determined, and the axial load f corresponding to the axial deformation l1 greater than 0 is taken as the second intermediate value f 21 of the crack closure load.

[0054] Furthermore, a moving-point linear regression is performed based on the axial load dataset and the circumferential deformation dataset to obtain the second regression coefficient dataset. In practical applications, a second regression equation f = a² × l² + b² is established for the axial load dataset and the circumferential deformation dataset, where a² is the second regression coefficient, characterizing the magnitude of the influence of circumferential deformation on the axial load, and b² is the error coefficient of the second regression equation. Specifically, the data window is moved sequentially, and a moving-point linear regression is performed on the axial load dataset and the circumferential deformation dataset. The change of the second regression coefficient a² with the axial load f during the entire moving-point linear regression process is recorded to obtain the second regression coefficient dataset.

[0055] Furthermore, a third regression equation a2 = a2 is established corresponding to the second regression coefficient dataset and the dataset collected at different times. 21 ×t+b 21 , where a 21 , where b is the third regression coefficient, representing the magnitude of the influence of the data collection time on the second regression coefficient. 21 This represents the error coefficient of the third regression equation. Specifically, by sequentially moving the data window, linear regression is performed on the second regression coefficient dataset and the dataset collected at different times. The third regression coefficient 'a' is recorded throughout the entire linear regression process. 21 As the axial load f changes, a dataset of third regression coefficients is obtained. Specifically, the third regression coefficients 'a' that are greater than 0 in the dataset are determined. 21 The third regression coefficient a that is greater than 0 21 The corresponding axial load f is used as the second intermediate value of the crack initiation load f. 22 .

[0056] Specifically, the i-th second regression coefficient is denoted as a. 2i The (i+1)th second regression coefficient is denoted as a. 2i+1 The i-th second product result is represented as p 2i p 2i =a 2i ×a 2i+1 , where i = 1, ..., m-1; m is the number of first regression coefficients in the second regression coefficient dataset.

[0057] In practical applications, the i-th second product result is represented as p. 2i Less than 0 indicates that a 2i and a 2i+1 With the signs opposite, and in conjunction with the above explanation, the second regression coefficient a2 characterizes the magnitude of the influence of circumferential deformation on axial load. Therefore, the smaller of the two adjacent second regression coefficients a2 is used. 2i The last axial load f in the corresponding data window is used as the second intermediate value f of the extreme load. 24 .

[0058] It should be noted that during a single loading test of a coal and rock sample, there may be multiple extreme loads. Therefore, the second intermediate value f for each extreme load is... 24 All were recorded. The second intermediate value f of all extreme loads was recorded. 24 The maximum value in the range is used as the second intermediate value f of the peak load. 26 .

[0059] Furthermore, the real-time ratio μ of circumferential deformation to axial deformation is calculated. i =l 2i / l 1i The first ratio result μ is obtained. i The dataset for the first ratio result is denoted as dataset μ, where l 2i For the i-th data in the circumferential deformation dataset, l 1i Let i be the data points in the axial deformation dataset.

[0060] Specifically, determine the first ratio result μ in the dataset μ that is greater than the second threshold. i The result μ of the first ratio that is greater than the second threshold will be... i The corresponding axial load f is used as the first intermediate value f of the expansion load. 25 .

[0061] Step 204: Based on the axial load dataset, volumetric deformation dataset, and acquisition time dataset, determine the third intermediate value of the crack initiation load, the first intermediate value of the damage load, the second intermediate value of the expansion load, the third intermediate value of the extreme load, and the third intermediate value of the peak load through moving point regression calculation.

[0062] In one example, step 204 includes the following steps: Following the order of acquisition time, the axial load corresponding to the second volumetric deformation in the volumetric deformation dataset that is 0 is taken as the second intermediate value of the expansion load. Moving-point linear regression is performed based on the axial load dataset and the volumetric deformation dataset to obtain the fourth regression coefficient dataset. Moving-point linear regression is performed based on the fourth regression coefficient dataset and the acquisition time dataset to obtain the fifth regression coefficient dataset. The axial load corresponding to the fourth regression coefficient that is equal to 0 in the fourth regression coefficient dataset is taken as the first intermediate value of the damage load. The axial load corresponding to the fifth regression coefficient that is equal to 0 in the fifth regression coefficient dataset is taken as the third intermediate value of the crack initiation load. For all fourth regression coefficients in the fourth regression coefficient dataset, the third product of two adjacent fourth regression coefficients is calculated. If the third product is less than 0, the last axial load in the data window corresponding to the smaller of the two adjacent fourth regression coefficients is taken as the third intermediate value of the extreme load. The maximum value among the third intermediate values ​​of all extreme loads is taken as the third intermediate value of the peak load.

[0063] In practical applications, there are two volume deformations l v with a value of 0 in the volume deformation data set. v The first volume deformation l v corresponds to the time when the coal rock sample is not subjected to external load, that is, the axial load f is 0. The second volume deformation l 35 corresponds to the second intermediate value f v of the dilatancy load.

[0064] In practical applications, a fourth regression equation f = a3 x l v +b3 is established, where a3 is a fourth regression coefficient representing the influence of volume deformation on axial load. b3 is an error coefficient of the fourth regression equation. Specifically, the moving point linear regression is performed on the axial load data set and the volume deformation data set by moving the data window, and the change process of the fourth regression coefficient a3 with the axial load f in the entire moving point linear regression process is recorded to obtain a fourth regression coefficient data set.

[0065] Further, a fifth regression equation a3 = a 31 x t + b 31 is established, where a 31 is a fifth regression coefficient representing the influence of the collection time on the fourth regression coefficient. b 31 is an error coefficient of the fifth regression equation. Specifically, the moving point linear regression is performed on the fourth regression coefficient data set and the collection time data set by moving the data window, and the change process of the fifth regression coefficient a 31 with the axial load f in the entire moving point linear regression process is recorded to obtain a fifth regression coefficient data set.

[0066] Specifically, the fourth regression coefficient a3 equal to 0 in the fourth regression coefficient data set is determined, and the axial load f corresponding to the fourth regression coefficient a3 equal to 0 is taken as the first intermediate value f 33 of the damage load. The fifth regression coefficient a 31 equal to 0 in the fifth regression coefficient data set is determined, and the axial load f corresponding to the fifth regression coefficient a 31 equal to 0 is taken as the third intermediate value f 32 of the cracking load.

[0067] Specifically, the i-th fourth regression coefficient is represented as a 3i , the i+1-th fourth regression coefficient is represented as a 3i+1 , the i-th third product result is represented as p 3i , and p 3i =a 3i x a3i+1 wherein, i = 1, …, m-1; m is the number of fourth regression coefficients in the fourth regression coefficient dataset.

[0068] In practical applications, the ith third product result is represented as p 3i less than 0, indicating that a 3i and a 3i+1 have opposite signs. In combination with the above description, the fourth regression coefficient a3represents the influence of volume deformation on axial load, and thus, the smaller of the two adjacent fourth regression coefficients a 3i is taken as the third intermediate value f 34 of the extreme load.

[0069] It should be noted that there can be multiple extreme loads in the process of one-time loading test of one-time coal rock sample, and thus, the third intermediate value f 34 of each extreme load is recorded. The maximum value among the third intermediate values f 34 of all extreme loads is taken as the third intermediate value f 36 of the peak load.

[0070] Step 205: Based on the axial load dataset, the crack volume deformation dataset, and the collection time dataset, the third intermediate value of the crack closure load, the fourth intermediate value of the crack initiation load, the second intermediate value of the damage load, the third intermediate value of the dilatancy load, the fourth intermediate value of the extreme load, and the fourth intermediate value of the peak load are determined through moving point regression calculation.

[0071] In one example, the above step 205 includes the following steps. In the order of collection time, the first crack volume deformation of 0 in the crack volume deformation dataset is taken as the third intermediate value of the crack closure load. The second crack volume deformation of 0 in the crack volume deformation dataset is taken as the third intermediate value of the dilatancy load. Moving point linear regression is performed based on the axial load dataset and the crack volume deformation dataset to obtain a sixth regression coefficient dataset. Moving point linear regression is performed based on the sixth regression coefficient dataset and the collection time dataset to obtain a seventh regression coefficient dataset. The axial load corresponding to the sixth regression coefficient of 0 in the sixth regression coefficient dataset is taken as the second intermediate value of the damage load. The axial load corresponding to the seventh regression coefficient of 0 in the seventh regression coefficient dataset is taken as the fourth intermediate value of the crack initiation load. For all sixth regression coefficients in the sixth regression coefficient dataset, the fourth product result of the adjacent two sixth regression coefficients is calculated. If the fourth product result is less than 0, the last axial load in the data window corresponding to the smaller sixth regression coefficient of the adjacent two sixth regression coefficients is taken as the fourth intermediate value of the extreme load. The maximum value among the fourth intermediate values of all extreme loads is taken as the fourth intermediate value of the peak load.

[0072] In practical applications, there are two crack volume deformation data in the crack volume deformation data set with a value of 0 Specifically, according to the order of the collection time, the first crack volume deformation with a value of 0 in the crack volume deformation data set is taken as the third intermediate value f of the crack closure load 41 . The second crack volume deformation with a value of 0 in the crack volume deformation data set is taken as the third intermediate value f of the dilatancy load 45 .

[0073] Further, a sixth regression equation f = a4 x l v +b4 is established, where a4 is a sixth regression coefficient, representing the influence of crack volume deformation on axial load. b4 is an error coefficient of the sixth regression equation. Specifically, the moving point linear regression is performed on the axial load data set and the crack volume deformation data set in sequence, and the change process of the sixth regression coefficient a4 with the axial load f in the entire moving point linear regression process is recorded to obtain a sixth regression coefficient data set.

[0074] Further, a seventh regression equation a4 = a 41 x t + b 41 is established, where a 41 is a seventh regression coefficient, representing the influence of the collection time on the sixth regression coefficient. b 41 is an error coefficient of the seventh regression equation. Specifically, the moving point linear regression is performed on the sixth regression coefficient data set and the collection time data set in sequence, and the change process of the seventh regression coefficient a 41 with the axial load f in the entire moving point linear regression process is recorded to obtain a seventh regression coefficient data set.

[0075] Specifically, the sixth regression coefficient a4 equal to 0 in the sixth regression coefficient data set is determined, and the axial load f corresponding to the sixth regression coefficient a4 equal to 0 is taken as the second intermediate value f of the damage load 43 . The seventh regression coefficient a 41 equal to 0 in the seventh regression coefficient data set is determined, and the axial load f corresponding to the seventh regression coefficient a 41 equal to 0 is taken as the fourth intermediate value f of the crack initiation load 42 .

[0076] Further, for all sixth regression coefficients in the sixth regression coefficient data set, the fourth product result of adjacent two sixth regression coefficients is calculated. Specifically, the i-th sixth regression coefficient is represented as a 4i , the i+1-th sixth regression coefficient is represented as a 3i+1 , and the i-th fourth product result is represented as p4i , p 4i = a 4i × a 4i+1 , i = 1, …, m-1; m is the number of the sixth regression coefficients in the sixth regression coefficient data set.

[0077] In practical applications, the i-th fourth product result is represented as p 4i < 0, which indicates that a 4i and a 4i+1 have opposite signs. In combination with the above description, the sixth regression coefficient a4 represents the influence of crack volume deformation on the axial load, so the sixth regression coefficient a 4i with the smaller value in the adjacent two terms is taken as the last axial load f in the data window corresponding to the sixth regression coefficient a 44 .

[0078] It should be noted that there can be multiple extreme loads in the process of one-time loading test of a coal rock sample, so the fourth intermediate value f 44 of each extreme load is recorded. The maximum value of the fourth intermediate value f 44 of all extreme loads is taken as the fourth intermediate value f 46 of the peak load.

[0079] Step 206: According to the intermediate values corresponding to each characteristic load under each corresponding relationship, the characteristic values of the characteristic loads corresponding to the coal rock sample test are calculated.

[0080] Specifically, for each characteristic load, the average value of the intermediate values corresponding to the characteristic load under all corresponding relationships can be calculated to obtain the characteristic value of the characteristic load.

[0081] In practical applications, to further improve the accuracy of the characteristic load, the intermediate values with larger errors are removed, and the characteristic values of the characteristic loads are calculated based on the intermediate values that meet the error requirement. As an example, in one possible implementation, the above step 206 includes the following steps. For each characteristic load, the relative error values of all intermediate values corresponding to the characteristic load are calculated; if the relative error value is less than the error threshold, the average value of all intermediate values is calculated to obtain the characteristic value of the characteristic load; if the relative error value is not less than the error threshold, the intermediate values that do not meet the error requirement are removed, and the average value of all intermediate values that meet the error requirement is calculated to obtain the characteristic value of the characteristic load.

[0082] In combination with the above description, the three intermediate values corresponding to the crack closure load are f 11 , f 21 and f 41 . The four intermediate values corresponding to the crack initiation load are f 12 , f 22 , f32 and f 42 . The damage load corresponds to two intermediate values f 33 and f 43 . The extreme load corresponds to four intermediate values f 14 , f 24 , f 34 and f 44 . The expansion load corresponds to three intermediate values f 25 , f 35 and f 45 . The peak load corresponds to four intermediate values f 16 , f 26 , f 36 and f 46 .

[0083] Specifically, for each characteristic load, the minimum value and the maximum value among all the intermediate values are determined. Further, for each characteristic load, a first difference result between the maximum value and the minimum value among all the intermediate values is calculated; a ratio of the first difference result to the minimum value among all the intermediate values is calculated to obtain a relative error value of all the intermediate values corresponding to the characteristic load. For example, for the crack initiation load, the maximum value f max2 = max{f 12 , f 22 , f 32 , f 42} and the minimum value f min2 = min{f 12 , f 22 , f 32 , f 42} among all the intermediate values are determined, and the relative error value

[0084] In actual application, if the relative error is not less than an error threshold, it indicates that the gap between all the intermediate values corresponding to the characteristic load is large, and thus the characteristic load obtained this time can be determined as invalid. Optionally, the intermediate values that do not meet the error requirement can be removed, for example, the intermediate values that have a large gap with other intermediate values are removed, and the average value of the remaining intermediate values is calculated to obtain the characteristic value of the characteristic load.

[0085] Correspondingly, if the relative error is less than the error threshold, it indicates that the gap between all the intermediate values corresponding to the characteristic load is small, and the average value of all the intermediate values is calculated to obtain the characteristic value of the characteristic load.

[0086] In this embodiment, the deformation parameters collected during the coal rock sample test can be used to calculate the volume deformation and crack volume deformation corresponding to each collection time. On this basis, the intermediate values corresponding to each characteristic load under each corresponding relationship are determined based on the corresponding relationship between the axial deformation data set, the hoop deformation data set, the volume deformation data set, the crack volume deformation data set and the axial load data set. The characteristic values of the multiple characteristic loads corresponding to the coal rock sample test are calculated according to the intermediate values corresponding to each characteristic load under each corresponding relationship. The determination of the coal rock characteristic load can be realized without external equipment, which avoids the influence of external equipment on the coal rock characteristic load, improves the accuracy of the coal rock characteristic load, and further improves the accuracy and reliability of the coal rock test.

[0087] The coal rock characteristic load determination method provided in this embodiment can calculate the volume deformation and crack volume deformation corresponding to each collection time based on the deformation parameters collected during the coal rock sample test. On this basis, the characteristic values of the multiple characteristic loads corresponding to the coal rock sample test can be determined by considering the corresponding relationship between the axial load, axial deformation, hoop deformation, volume deformation and crack volume deformation corresponding to each collection time. Therefore, the determination of the coal rock characteristic load can be realized without external equipment, which avoids the influence of external equipment on the coal rock characteristic load, improves the accuracy of the coal rock characteristic load, and further improves the accuracy and reliability of the coal rock test.

[0088] The coal rock characteristic load determination device provided in the present application is described below. The coal rock characteristic load determination device described below can be referred to in conjunction with the coal rock characteristic load determination method described above.

[0089] Figure 3 is one of the structural schematic diagrams of the coal rock characteristic load determination device provided in the present application. As shown in Figure 3 , the coal rock characteristic load determination device comprises a collection module 31, a calculation module 32 and a processing module 33.

[0090] The collection module 31 is used to obtain the deformation parameters corresponding to each collection time collected during the coal rock sample test, wherein the deformation parameters include axial load, axial deformation and hoop deformation.

[0091] The axial load refers to the load generated in the axial direction of the coal rock sample. The axial deformation refers to the deformation size of the coal rock sample in the axial direction caused by external force. The hoop deformation refers to the deformation size of the coal rock sample in the hoop direction caused by external force. In actual application, the collection module 31 can directly collect the axial load, axial deformation and hoop deformation during the coal rock sample test.

[0092] In combination with the application scenarios, the standard coal rock sample is processed, and the displacement control method is used for uniaxial loading test of the standard coal rock sample until the standard coal rock sample is completely destroyed. During the whole coal rock sample test process, the axial load, axial deformation and hoop deformation at the collection time are collected. For example, the deformation parameters can be collected periodically, and the collection frequency of the deformation parameters can be set before the coal rock sample test starts, that is, the time interval between adjacent collection times during the coal rock sample test is fixed.

[0093] The calculation module 32 is configured to calculate the volume deformation and crack volume deformation corresponding to each collection time according to the deformation parameters corresponding to each collection time.

[0094] It should be noted that the axial load, axial deformation and hoop deformation corresponding to each collection time can be collected. Based on the axial load, axial deformation and hoop deformation corresponding to each collection time, the calculation module 32 can obtain the volume deformation and crack volume deformation corresponding to the collection time.

[0095] The processing module 33 is configured to determine the characteristic values of the multiple characteristic loads corresponding to the coal rock sample test based on the corresponding relationship between the axial load, axial deformation, hoop deformation, volume deformation and crack volume deformation corresponding to each collection time; wherein the multiple characteristic loads corresponding to the coal rock sample test include: crack closure load, crack initiation load, damage load, extreme load, expansion load and peak load.

[0096] In practical applications, the axial load f, axial deformation l1, hoop deformation l2, volume deformation l v , crack volume deformation and the multiple characteristic loads have a correlation relationship. In this embodiment, the processing module 33 analyzes the corresponding relationship between the axial load f, axial deformation l1, hoop deformation l2, volume deformation l v , crack volume deformation and the multiple characteristic loads, and can determine the characteristic values of the multiple characteristic loads corresponding to the coal rock sample test. For example, the corresponding relationship between any two data of the axial load f, axial deformation l1, hoop deformation l2, volume deformation l v , crack volume deformation and the multiple characteristic loads can be analyzed, or the corresponding relationship between multiple data can be analyzed to determine the characteristic values of the multiple characteristic loads corresponding to the coal rock sample test.

[0097] It can be understood that the coal rock characteristic load determination device provided in the embodiment can determine the coal rock characteristic load without external equipment, avoids the influence of external equipment on the coal rock characteristic load, improves the accuracy of the coal rock characteristic load, and further improves the accuracy and reliability of the coal rock test.

[0098] As an example, in one possible implementation, Figure 4 is a structural schematic diagram of the coal rock characteristic load determination device provided by the present application, as shown in Figure 4 The processing module 33 includes a construction unit 331, a first processing unit 332, a second processing unit 333, a third processing unit 334, a fourth processing unit 335, and a calculation unit 336.

[0099] The construction unit 331 is configured to construct, according to the axial load, axial deformation, hoop deformation, volume deformation, and crack volume deformation corresponding to each acquisition time, an acquisition time data set, an axial load data set, an axial deformation data set, a hoop deformation data set, a volume deformation data set, and a crack volume deformation data set.

[0100] In actual application, the axial load f, axial deformation l1, hoop deformation l2, volume deformation l v , and crack volume deformation The construction unit 331 is configured to construct, according to the axial load, axial deformation, hoop deformation, volume deformation, and crack volume deformation corresponding to each acquisition time, an acquisition time data set, an axial load data set, an axial deformation data set, a hoop deformation data set, a volume deformation data set, and a crack volume deformation data set.

[0101] The first processing unit 332 is configured to determine, based on the axial load data set and the axial deformation data set, a first intermediate value of the crack closure load, a first intermediate value of the crack initiation load, a first intermediate value of the extreme value load, and a first intermediate value of the peak load through moving point regression calculation.

[0102] In actual application, in order to ensure the reliability of the moving point linear regression, it is necessary to calculate the regression goodness R 2 , determine whether the current moving point linear regression is valid according to the regression goodness R 2 , and adjust the data amount of the data window according to the regression goodness R 2 when it is invalid.

[0103] In an example, the first processing unit 332 is specifically configured to: perform moving point linear regression based on the axial load data set and the axial deformation data set to obtain a first regression coefficient data set; perform moving point linear regression based on the axial load data set and the first regression coefficient data set to calculate a first regression goodness of fit corresponding to the axial load at each acquisition time; in the order of the acquisition times, the first regression goodness of fit increases, the axial load corresponding to the first regression goodness of fit which is first greater than a first threshold value is taken as a first intermediate value of the crack closure load; the first regression goodness of fit decreases, the axial load corresponding to the first regression goodness of fit which is first less than the first threshold value is taken as a first intermediate value of the crack initiation load; for all the first regression coefficients in the first regression coefficient data set, a first product result of adjacent two first regression coefficients is calculated; if the first product result is less than 0, the last axial load in the data window corresponding to the smaller first regression coefficient of the adjacent two first regression coefficients is taken as a first intermediate value of the extreme value load; and a maximum value of all the first intermediate values of the extreme value load is taken as a first intermediate value of the peak load.

[0104] The second processing unit 333 is configured to: based on the axial load data set, the hoop deformation data set and the acquisition time data set, determine a second intermediate value of the crack closure load, a second intermediate value of the crack initiation load, a second intermediate value of the extreme value load, a second intermediate value of the peak load and a first intermediate value of the expansion load through moving point regression calculation.

[0105] In an example, the second processing unit 333 is specifically configured to: take the axial load corresponding to the axial deformation greater than 0 in the hoop deformation data set as the second intermediate value of the crack closure load; perform moving point linear regression based on the axial load data set and the hoop deformation data set to obtain a second regression coefficient data set; perform moving point linear regression based on the second regression coefficient data set and the acquisition time data set to obtain a third regression coefficient data set; take the axial load corresponding to the third regression coefficient greater than 0 in the third regression coefficient data set as the second intermediate value of the crack initiation load; for all the second regression coefficients in the second regression coefficient data set, calculate a second product result of adjacent two second regression coefficients; if the second product result is less than 0, take the last axial load in the data window corresponding to the smaller second regression coefficient of the adjacent two second regression coefficients as the second intermediate value of the extreme value load; take the maximum value of all the second intermediate values of the extreme value load as the second intermediate value of the peak load; in the order of the acquisition times, calculate a first ratio result of the hoop deformation in the hoop deformation data set and the axial deformation in the axial deformation data set; take the axial load corresponding to the first ratio result greater than a second threshold value as the first intermediate value of the expansion load.

[0106] The third processing unit 334 is configured to determine the third intermediate value of the crack initiation load, the first intermediate value of the damage load, the second intermediate value of the dilatancy load, the third intermediate value of the extreme load and the third intermediate value of the peak load based on the axial load data set, the volume deformation data set and the acquisition time data set by moving point regression calculation.

[0107] In an example, the third processing unit 334 is specifically configured to: in the order of the acquisition time, take the axial load corresponding to the second volume deformation of 0 in the volume deformation data set as the second intermediate value of the dilatancy load. Perform moving point linear regression based on the axial load data set and the volume deformation data set to obtain a fourth regression coefficient data set. Perform moving point linear regression based on the fourth regression coefficient data set and the acquisition time data set to obtain a fifth regression coefficient data set. Take the axial load corresponding to the fourth regression coefficient equal to 0 in the fourth regression coefficient data set as the first intermediate value of the damage load. Take the axial load corresponding to the fifth regression coefficient equal to 0 in the fifth regression coefficient data set as the third intermediate value of the crack initiation load. For all fourth regression coefficients in the fourth regression coefficient data set, calculate a third product result of adjacent two fourth regression coefficients. If the third product result is less than 0, take the last axial load in the data window corresponding to the smaller fourth regression coefficient of the adjacent two as the third intermediate value of the extreme load. Take the maximum value of all third intermediate values of the extreme load as the third intermediate value of the peak load.

[0108] The fourth processing unit 335 is configured to determine the crack initiation load, the fourth intermediate value of the crack initiation load, the second intermediate value of the damage load, the third intermediate value of the dilatancy load, the fourth intermediate value of the extreme load and the fourth intermediate value of the peak load based on the axial load data set, the crack volume deformation data set and the acquisition time data set by moving point regression calculation.

[0109] In an example, the fourth processing unit 335 is specifically configured to: take the first crack volume deformation in the crack volume deformation dataset as the third intermediate value of the crack closure load, according to the order of the collection time; take the second crack volume deformation in the crack volume deformation dataset as the third intermediate value of the dilatancy load; perform moving point linear regression based on the axial load dataset and the crack volume deformation dataset to obtain a sixth regression coefficient dataset; perform moving point linear regression based on the sixth regression coefficient dataset and the collection time dataset to obtain a seventh regression coefficient dataset; take the axial load corresponding to the sixth regression coefficient equal to 0 in the sixth regression coefficient dataset as the second intermediate value of the damage load; take the axial load corresponding to the seventh regression coefficient equal to 0 in the seventh regression coefficient dataset as the fourth intermediate value of the crack initiation load; for all the sixth regression coefficients in the sixth regression coefficient dataset, calculate the fourth product result of the adjacent two sixth regression coefficients; if the fourth product result is less than 0, take the last axial load in the data window corresponding to the smaller sixth regression coefficient of the adjacent two sixth regression coefficients as the fourth intermediate value of the extreme value load; and take the maximum value of the fourth intermediate values of all the extreme value loads as the fourth intermediate value of the peak load.

[0110] The calculation unit 336 is configured to calculate the characteristic value of each characteristic load of the coal rock sample according to the intermediate value corresponding to each characteristic load under each corresponding relationship.

[0111] Specifically, for each characteristic load, the calculation unit 336 can calculate the average value of the intermediate values corresponding to the characteristic load under all corresponding relationships to obtain the characteristic value of the characteristic load.

[0112] In actual application, the accuracy of the characteristic load is further improved, and the intermediate value with larger error is removed. The characteristic value of the characteristic load is calculated based on the intermediate value meeting the error requirement. As an example, in a possible implementation, the calculation unit 336 is specifically configured to: for each characteristic load, calculate the relative error value of all the intermediate values corresponding to the characteristic load; if the relative error value is less than an error threshold, calculate the average value of all the intermediate values to obtain the characteristic value of the characteristic load; if the relative error value is not less than the error threshold, remove the intermediate value not meeting the error requirement, and calculate the average value of all the intermediate values meeting the error requirement to obtain the characteristic value of the characteristic load.

[0113] In actual application, if the relative error is not less than the error threshold, it indicates that the gap between all the intermediate values corresponding to the characteristic load is large, and thus the characteristic load obtained this time can be determined as invalid. Optionally, the intermediate values that do not meet the error requirement can be removed, for example, the intermediate values with a large gap from other intermediate values are removed, and the average of the remaining intermediate values is calculated to obtain the characteristic value of the characteristic load. Correspondingly, if the relative error is less than the error threshold, it indicates that the gap between all the intermediate values corresponding to the characteristic load is small, and the average of all the intermediate values is calculated to obtain the characteristic value of the characteristic load.

[0114] In the embodiment, the calculation module 32 can calculate the volume deformation and the crack volume deformation corresponding to each collection time based on the deformation parameters collected by the collection module 31 in the process of the coal rock sample test. On this basis, the processing module 33 determines the intermediate value corresponding to each characteristic load under each corresponding relationship based on the corresponding relationship between the axial deformation data set, the hoop deformation data set, the volume deformation data set, the crack volume deformation data set and the axial load data set. The characteristic value of the multiple characteristic loads corresponding to the coal rock sample test is calculated according to the intermediate value corresponding to each characteristic load under each corresponding relationship. The determination of the coal rock characteristic load can be realized without external equipment, the influence of the external equipment on the coal rock characteristic load is avoided, the accuracy of the coal rock characteristic load is improved, and thus the accuracy and reliability of the coal rock test are improved.

[0115] In the coal rock characteristic load determination device provided in the embodiment, the volume deformation and the crack volume deformation corresponding to each collection time can be calculated based on the deformation parameters collected in the process of the coal rock sample test. On this basis, the characteristic value of the multiple characteristic loads corresponding to the coal rock sample test can be determined by considering the corresponding relationship between the axial load, the axial deformation, the hoop deformation, the volume deformation and the crack volume deformation corresponding to each collection time. Therefore, the determination of the coal rock characteristic load can be realized without external equipment according to the scheme of the present application, the influence of the external equipment on the coal rock characteristic load is avoided, the accuracy of the coal rock characteristic load is improved, and thus the accuracy and reliability of the coal rock test are improved.

[0116] Figure 5 An example of a schematic diagram of a physical structure of an electronic device is shown in FIG. 1. Figure 5 As shown in FIG. 1, the electronic device can include a processor 510, a communications interface 520, a memory 530 and a communications bus 540, wherein the processor 510, the communications interface 520 and the memory 530 complete mutual communication through the communications bus 540. The processor 510 can invoke the logical instructions in the memory 530 to execute the coal rock characteristic load determination method.

[0117] In addition, the logic instructions in the memory 530 described above can be implemented in the form of software function units and sold or used as independent products, and can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0118] In another aspect, the present application also provides a computer program product, which comprises a computer program, the computer program can be stored on a non-transitory computer readable storage medium, and the computer program can be executed by a processor to enable a computer to execute the coal rock characteristic load determination method provided by the above-mentioned methods.

[0119] In another aspect, the present application also provides a non-transitory computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the coal rock characteristic load determination method provided by the above-mentioned methods.

[0120] The device embodiments described above are only schematic, wherein the units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, that is, they can be located in one place, or distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the present embodiment. Those skilled in the art can understand and implement without creative labor.

[0121] From the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be realized by means of software plus necessary universal hardware platforms, and of course can also be realized by hardware. Based on such understanding, the above technical solutions essentially or the parts that contribute to the prior art can be embodied in the form of a software product. The computer software product can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments.

[0122] It should be pointed out finally that the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit the same; and although the present application has been described in detail with reference to the foregoing embodiments, it should be appreciated by those skilled in the art that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features thereof can be replaced equivalently; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for determining characteristic loads of coal and rock, characterized in that, include: Deformation parameters corresponding to each acquisition moment are obtained during the testing of coal and rock samples, wherein the deformation parameters include axial load, axial deformation and circumferential deformation; Based on the deformation parameters corresponding to each acquisition moment, the volumetric deformation and crack volumetric deformation corresponding to each acquisition moment are calculated. Based on the correspondence between axial load, axial deformation, circumferential deformation, volumetric deformation and crack volumetric deformation at each acquisition moment, the characteristic values ​​of multiple characteristic loads corresponding to the coal and rock sample test are determined; wherein the multiple characteristic loads corresponding to the coal and rock sample test include: crack closure load, crack initiation load, damage load, extreme value load, expansion load and peak load. Based on the correspondence between axial load, axial deformation, circumferential deformation, volumetric deformation, and crack volumetric deformation at each acquisition moment, the characteristic values ​​of multiple characteristic loads corresponding to the coal and rock sample test are determined, including: Based on the axial load, axial deformation, circumferential deformation, volumetric deformation, and crack volumetric deformation corresponding to each acquisition moment, an acquisition moment dataset, an axial load dataset, an axial deformation dataset, a circumferential deformation dataset, a volumetric deformation dataset, and a crack volumetric deformation dataset are constructed. Based on the axial load dataset and the axial deformation dataset, the first intermediate value of crack closure load, the first intermediate value of crack initiation load, the first intermediate value of extreme load, and the first intermediate value of peak load are determined by moving point regression calculation. Based on the axial load dataset, the circumferential deformation dataset, and the acquisition time dataset, the second intermediate value of the crack closure load, the second intermediate value of the crack initiation load, the second intermediate value of the extreme load, the second intermediate value of the peak load, and the first intermediate value of the expansion load are determined by moving point regression calculation. Based on the axial load dataset, the volumetric deformation dataset, and the acquisition time dataset, the third intermediate value of the crack initiation load, the first intermediate value of the damage load, the second intermediate value of the expansion load, the third intermediate value of the extreme load, and the third intermediate value of the peak load are determined by moving point regression calculation. Based on the axial load dataset, the crack volume deformation dataset, and the acquisition time dataset, the third intermediate value of the crack closure load, the fourth intermediate value of the crack initiation load, the second intermediate value of the damage load, the third intermediate value of the expansion load, the fourth intermediate value of the extreme load, and the fourth intermediate value of the peak load are determined by moving point regression calculation. Based on the intermediate value corresponding to each characteristic load under each correspondence, the characteristic values ​​of multiple characteristic loads corresponding to the coal and rock sample test are calculated. The step of calculating the characteristic values ​​of multiple characteristic loads corresponding to the coal and rock sample test based on the intermediate value corresponding to each characteristic load under each correspondence includes: For each characteristic load, the average of all intermediate values ​​that meet the error requirements is calculated to obtain the characteristic value of the characteristic load.

2. The method for determining coal and rock characteristic loads according to claim 1, characterized in that, The determination of the first median value of crack closure load, the first median value of crack initiation load, the first median value of extreme load, and the first median value of peak load based on the axial load dataset and the axial deformation dataset through moving point regression calculation includes: Based on the axial load dataset and the axial deformation dataset, linear regression of the moving points is performed to obtain the first regression coefficient dataset; Based on the axial load dataset and the first regression coefficient dataset, linear regression of moving points is performed to calculate the first regression goodness of the axial load corresponding to each acquisition time. According to the order of the acquisition time, the axial load corresponding to the first regression goodness greater than the first threshold during the process of increasing the first regression goodness is taken as the first intermediate value of the crack closure load; the axial load corresponding to the first regression goodness less than the first threshold during the process of decreasing the first regression goodness is taken as the first intermediate value of the crack initiation load. For all first regression coefficients in the first regression coefficient dataset, calculate the first product of two adjacent first regression coefficients; If the result of the first product is less than 0, then the last axial load in the data window corresponding to the smaller first regression coefficient among the two adjacent terms is taken as the first intermediate value of the extreme load. The maximum value among all the first intermediate values ​​of extreme loads is taken as the first intermediate value of the peak load.

3. The method for determining coal and rock characteristic loads according to claim 1, characterized in that, The determination of the second intermediate value of crack closure load, the second intermediate value of crack initiation load, the second intermediate value of extreme load, the second intermediate value of peak load, and the first intermediate value of expansion load based on the axial load dataset, the circumferential deformation dataset, and the acquisition time dataset, through moving point regression calculation, includes: The axial load corresponding to the axial deformation that is greater than 0 in the circumferential deformation data is taken as the second intermediate value of the crack closure load. Based on the axial load dataset and the circumferential deformation dataset, linear regression of the moving points is performed to obtain the second regression coefficient dataset; Based on the second regression coefficient dataset and the data collection time dataset, linear regression of moving points is performed to obtain the third regression coefficient dataset; The axial load corresponding to the third regression coefficient that is greater than 0 in the third regression coefficient dataset is taken as the second intermediate value of the crack initiation load; For all second regression coefficients in the second regression coefficient dataset, calculate the second product of two adjacent second regression coefficients; If the result of the second product is less than 0, then the last axial load in the data window corresponding to the smaller second regression coefficient among the two adjacent terms is taken as the second intermediate value of the extreme load. The maximum value among all the second intermediate values ​​of extreme loads is taken as the second intermediate value of the peak load; According to the order of acquisition time, calculate the first ratio of the circumferential deformation to the axial deformation in the circumferential deformation dataset and the axial deformation dataset; The axial load corresponding to the first ratio result that is greater than the second threshold is taken as the first intermediate value of the expansion load.

4. The method for determining coal and rock characteristic loads according to claim 1, characterized in that, The process of determining the third intermediate value of the crack initiation load, the first intermediate value of the damage load, the second intermediate value of the expansion load, the third intermediate value of the extreme load, and the third intermediate value of the peak load based on the axial load dataset, the volumetric deformation dataset, and the acquisition time dataset through moving point regression calculation includes: According to the order of the acquisition time, the axial load corresponding to the second volume deformation that is 0 in the volume deformation data is taken as the second intermediate value of the expansion load. Based on the axial load dataset and the volume deformation dataset, linear regression of moving points is performed to obtain the fourth regression coefficient dataset. Based on the fourth regression coefficient dataset and the acquisition time dataset, linear regression of moving points is performed to obtain the fifth regression coefficient dataset; The axial load corresponding to the fourth regression coefficient that is equal to 0 in the fourth regression coefficient dataset is taken as the first intermediate value of the damage load; The axial load corresponding to the fifth regression coefficient that is equal to 0 in the fifth regression coefficient dataset is taken as the third intermediate value of the crack initiation load; For all fourth regression coefficients in the aforementioned fourth regression coefficient dataset, calculate the third product of two adjacent fourth regression coefficients; If the result of the third product is less than 0, then the last axial load in the data window corresponding to the smaller fourth regression coefficient among the two adjacent terms is taken as the third intermediate value of the extreme load. The maximum value among the third intermediate values ​​of all extreme loads is taken as the third intermediate value of the peak load.

5. The method for determining coal and rock characteristic loads according to claim 1, characterized in that, Based on the axial load dataset, the crack volume deformation dataset, and the acquisition time dataset, the third intermediate value of the crack closure load, the fourth intermediate value of the crack initiation load, the second intermediate value of the damage load, the third intermediate value of the expansion load, the fourth intermediate value of the extreme load, and the fourth intermediate value of the peak load are determined through moving point regression calculation, including: According to the order of the acquisition time, the first crack volume deformation that is 0 in the crack volume deformation data set is taken as the third intermediate value of the crack closure load; the second crack volume deformation that is 0 in the crack volume deformation data set is taken as the third intermediate value of the expansion load. Based on the axial load dataset and the crack volume deformation dataset, linear regression of moving points is performed to obtain the sixth regression coefficient dataset. Based on the sixth regression coefficient dataset and the data collection time dataset, linear regression of moving points is performed to obtain the seventh regression coefficient dataset; The axial load corresponding to the sixth regression coefficient that is equal to 0 in the sixth regression coefficient dataset is taken as the second intermediate value of the damage load; The axial load corresponding to the seventh regression coefficient that is equal to 0 in the seventh regression coefficient dataset is taken as the fourth intermediate value of the crack initiation load; For all sixth regression coefficients in the sixth regression coefficient dataset, calculate the fourth product of two adjacent sixth regression coefficients; If the result of the fourth product is less than 0, then the last axial load in the data window corresponding to the smaller of the six regression coefficients of the two adjacent terms is taken as the fourth intermediate value of the extreme load. The maximum value among the fourth intermediate values ​​of all extreme loads is taken as the fourth intermediate value of the peak load.

6. The method for determining coal and rock characteristic loads according to any one of claims 1-5, characterized in that, The step of calculating the characteristic values ​​of multiple characteristic loads corresponding to the coal and rock sample test based on the intermediate value corresponding to each characteristic load under each correspondence includes: For each characteristic load, calculate the relative error value of all intermediate values ​​corresponding to the characteristic load; If the relative error value is less than the error threshold, then the average of all intermediate values ​​is calculated to obtain the characteristic value of the characteristic load; If the relative error value is not less than the error threshold, then the intermediate values ​​that do not meet the error requirements are removed, and the average value of all intermediate values ​​that meet the error requirements is calculated to obtain the characteristic value of the characteristic load.

7. A device for determining coal and rock characteristic loads, characterized in that, include: The acquisition module is used to acquire deformation parameters corresponding to each acquisition moment during the testing of coal and rock samples. The deformation parameters include axial load, axial deformation, and circumferential deformation. The calculation module is used to calculate the volumetric deformation and crack volumetric deformation corresponding to each acquisition moment based on the deformation parameters corresponding to each acquisition moment. The processing module is used to determine the characteristic values ​​of multiple characteristic loads corresponding to the coal and rock sample test based on the correspondence between axial load, axial deformation, circumferential deformation, volumetric deformation and crack volumetric deformation at each acquisition time; wherein the multiple characteristic loads corresponding to the coal and rock sample test include: crack closure load, crack initiation load, damage load, extreme value load, expansion load and peak load. Based on the correspondence between axial load, axial deformation, circumferential deformation, volumetric deformation, and crack volumetric deformation at each acquisition moment, the characteristic values ​​of multiple characteristic loads corresponding to the coal and rock sample test are determined, including: Based on the axial load, axial deformation, circumferential deformation, volumetric deformation, and crack volumetric deformation corresponding to each acquisition moment, an acquisition moment dataset, an axial load dataset, an axial deformation dataset, a circumferential deformation dataset, a volumetric deformation dataset, and a crack volumetric deformation dataset are constructed. Based on the axial load dataset and the axial deformation dataset, the first intermediate value of crack closure load, the first intermediate value of crack initiation load, the first intermediate value of extreme load, and the first intermediate value of peak load are determined by moving point regression calculation. Based on the axial load dataset, the circumferential deformation dataset, and the acquisition time dataset, the second intermediate value of the crack closure load, the second intermediate value of the crack initiation load, the second intermediate value of the extreme load, the second intermediate value of the peak load, and the first intermediate value of the expansion load are determined by moving point regression calculation. Based on the axial load dataset, the volumetric deformation dataset, and the acquisition time dataset, the third intermediate value of the crack initiation load, the first intermediate value of the damage load, the second intermediate value of the expansion load, the third intermediate value of the extreme load, and the third intermediate value of the peak load are determined by moving point regression calculation. Based on the axial load dataset, the crack volume deformation dataset, and the acquisition time dataset, the third intermediate value of the crack closure load, the fourth intermediate value of the crack initiation load, the second intermediate value of the damage load, the third intermediate value of the expansion load, the fourth intermediate value of the extreme load, and the fourth intermediate value of the peak load are determined by moving point regression calculation. Based on the intermediate value corresponding to each characteristic load under each correspondence, the characteristic values ​​of multiple characteristic loads corresponding to the coal and rock sample test are calculated. The step of calculating the characteristic values ​​of multiple characteristic loads corresponding to the coal and rock sample test based on the intermediate value corresponding to each characteristic load under each correspondence includes: For each characteristic load, the average of all intermediate values ​​that meet the error requirements is calculated to obtain the characteristic value of the characteristic load.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for determining coal and rock characteristic loads as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for determining coal and rock characteristic loads as described in any one of claims 1 to 6.

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