Rock uniaxial compression test data processing method, system, equipment and medium

Abstract

The invention discloses a rock uniaxial compression test data processing method, system, equipment and medium, and relates to the technical field of rock mechanics, and the rock uniaxial compression test data processing method comprises the following steps: acquiring rock uniaxial compression test data collected by a rock mechanics testing machine, and intercepting the rock uniaxial compression test data according to a preset extreme value data interception method to obtain rock uniaxial compression test data; obtaining target test data; fitting the target test data to obtain a stress-strain curve after fitting, acquiring an instantaneous change rate of stress to strain in the stress-strain curve after fitting, and intercepting a target fitting curve of which the instantaneous change rate meets a preset elastic stage data condition; and performing dual linear regression analysis of axial strain-stress and radial strain-axial strain on the target fitting curve to obtain an elastic modulus result and a Poisson's ratio result of the rock uniaxial compression test data. Through automatic process processing, personal errors are avoided, and the efficiency, precision and reliability of rock uniaxial compression test data processing are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of rock mechanics, and in particular to a method, system, equipment and medium for processing rock uniaxial compression test data. Background Art

[0002] The uniaxial compression test of rock is a core experimental method for evaluating the mechanical properties of rock. It is widely used in geological engineering, mining engineering, civil engineering and other fields to determine key parameters of rock such as uniaxial compressive strength, elastic modulus and Poisson's ratio. The traditional data processing method mainly includes the following steps: collecting axial stress, axial strain and radial strain data of rock samples through a testing machine; manually intercepting the elastic stage of the stress-strain curve (usually an approximately linear segment); performing a single linear regression analysis on the intercepted data to calculate the elastic modulus and Poisson's ratio. However, the above method has significant drawbacks in practical applications:

[0003] Manual interception is highly subjective: the elastic stage boundary relies on the operator's experience and judgment. Multiple operations by different personnel or the same person are prone to deviations, resulting in large discreteness in parameter calculation results (the error can reach 10%-15%).

[0004] Fixed thresholds have poor adaptability: Existing automated algorithms mostly use fixed strain thresholds, such as using a strain of 0.05%-0.2% to intercept the elastic stage. However, rock types are diverse, such as brittle granite and ductile shale, and their stress-strain curves have significant differences in morphology. Fixed thresholds are difficult to dynamically adapt to the complex changes in nonlinear transition sections.

[0005] High noise sensitivity: Test data is often subject to noise due to interference such as sensor drift and environmental vibration. Traditional single linear regression or low-order polynomial fitting methods have weak anti-interference capabilities, and the calculation results have significant deviations under low signal-to-noise ratios (SNR<15dB). Summary of the Invention

[0006] In view of this, the present invention aims to provide a method, system, device, and medium for processing rock uniaxial compression test data. By automating the process, human errors are avoided and the efficiency, accuracy, and reliability of rock uniaxial compression test data processing are improved. The specific scheme is as follows:

[0007] In a first aspect, the present application discloses a method for processing rock uniaxial compression test data, comprising:

[0008] Obtaining rock uniaxial compression test data collected by a rock mechanics testing machine, and intercepting and processing the rock uniaxial compression test data according to a preset extreme value data interception method to obtain target test data;

[0009] Performing fitting processing on the target test data to obtain a fitted stress-strain curve, obtaining the instantaneous rate of change of stress to strain in the fitted stress-strain curve, and intercepting a target fitting curve whose instantaneous rate of change meets a preset elastic stage data condition;

[0010] Double linear regression analysis of axial strain-stress and radial strain-axial strain is performed on the target fitting curve to obtain elastic modulus results and Poisson's ratio results of the rock uniaxial compression test data.

[0011] Optionally, obtaining rock uniaxial compression test data collected by a rock mechanics testing machine includes:

[0012] The axial stress, axial strain and radial strain data of the rock sample are collected in real time through the sensors of the rock mechanics testing machine to obtain the rock uniaxial compression test data.

[0013] Optionally, the truncation processing of the rock uniaxial compression test data according to a preset extreme value data truncation method to obtain target test data includes:

[0014] Searching for a minimum data value in the rock uniaxial compression test data, and using the minimum data value as a truncation starting point, searching for a maximum data value in the rock uniaxial compression test data in chronological order, and using the maximum data value as a truncation end point;

[0015] The rock uniaxial compression test data between the interception starting point and the interception end point are intercepted to obtain target test data.

[0016] Optionally, performing fitting processing on the target test data to obtain a fitted stress-strain curve includes:

[0017] Performing low-order polynomial fitting on the target test data to obtain an initial fitting curve;

[0018] Selecting a candidate order polynomial according to a change in a curvature index of the initial fitting curve;

[0019] Determining a target order polynomial of the initial fitting curve from the candidate order polynomials using a cross-validation method;

[0020] The target test data is subjected to polynomial fitting processing using the target order polynomial to obtain a fitted stress-strain curve.

[0021] Optionally, intercepting a target fitting curve whose instantaneous change rate satisfies a preset elastic stage data condition includes:

[0022] Acquire several local peaks of the fitted stress-strain curve through a sliding window, use each local peak as a maximum peak value in a corresponding elastic stage interval, and set a target threshold value for the corresponding elastic stage interval based on each maximum peak value;

[0023] Filtering target fitting data whose instantaneous change rate of the fitting data in the stress-strain curve after fitting is greater than or equal to the target threshold value of the corresponding elastic stage interval from each elastic stage interval, so as to obtain a target fitting curve for each elastic stage interval;

[0024] Accordingly, the target fitting curve is subjected to double linear regression analysis of axial strain-stress and radial strain-axial strain respectively to obtain the elastic modulus result and Poisson's ratio result of the rock uniaxial compression test data, including:

[0025] Linear regression analysis is performed on the axial strain-stress data and radial strain-axial strain data in the target fitting curve of each elastic stage interval to obtain the elastic modulus results and Poisson's ratio results of each elastic stage interval of the rock uniaxial compression test data.

[0026] Optionally, the rock uniaxial compression test data processing method further includes:

[0027] Calculating the stress fitting goodness of the fitted stress-strain curve based on the true stress value of the target test data and the corresponding fitted stress value on the fitted stress-strain curve to obtain a fitting coefficient;

[0028] When the fitting coefficient is less than a preset fitting coefficient threshold, the abnormal data of the stress-strain curve after fitting is marked and a visualization report is generated, so as to execute the step of obtaining the rock uniaxial compression test data collected by the rock mechanics testing machine based on the visualization report.

[0029] Optionally, after obtaining the elastic modulus result and Poisson's ratio result of the rock uniaxial compression test data, the method further includes:

[0030] The elastic modulus result is fed back to the testing machine control system in real time, so that the testing machine control system controls the rock mechanics testing machine to dynamically adjust the loading rate of the testing process according to the elastic modulus result.

[0031] In the second aspect, the present application discloses a rock uniaxial compression test data processing system, including a data acquisition module, a dynamic fitting module, an elastic stage interception module, a parameter calculation module, and a verification and packaging module, wherein:

[0032] The data acquisition module is connected to the stress sensor and the strain sensor of the rock mechanics testing machine, and is used to obtain rock uniaxial compression test data collected by the rock mechanics testing machine in real time, and intercept and process the rock uniaxial compression test data according to a preset extreme value data interception method to obtain target test data;

[0033] The dynamic fitting module is used to perform fitting processing on the target test data to obtain a fitted stress-strain curve and obtain the instantaneous rate of change of stress to strain in the fitted stress-strain curve;

[0034] The elastic stage interception module is used to intercept the target fitting curve whose instantaneous change rate meets the preset elastic stage data conditions;

[0035] The parameter calculation module is used to perform double linear regression analysis of axial strain-stress and radial strain-axial strain on the target fitting curve to obtain elastic modulus results and Poisson's ratio results of the rock uniaxial compression test data;

[0036] The verification and packaging module is used to calculate the stress fitting goodness of the fitted stress-strain curve based on the true stress value of the target test data and the corresponding fitted stress value on the fitted stress-strain curve to obtain a fitting coefficient; when the fitting coefficient is less than a preset fitting coefficient threshold, abnormal data of the fitted stress-strain curve is marked and a visual report is generated.

[0037] In a third aspect, the present application discloses an electronic device, comprising:

[0038] Memory, used to store computer programs;

[0039] The processor is used to execute the computer program to implement the steps of the rock uniaxial compression test data processing method disclosed above.

[0040] In a fourth aspect, the present application discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the steps of the aforementioned rock uniaxial compression test data processing method are implemented.

[0041] It can be seen that the present application discloses a method for processing rock uniaxial compression test data, including: obtaining rock uniaxial compression test data collected by a rock mechanics testing machine, and intercepting the rock uniaxial compression test data according to a preset extreme value data interception method to obtain target test data; fitting the target test data to obtain a stress-strain curve after fitting, and obtaining the instantaneous change rate of stress to strain in the stress-strain curve after fitting, and intercepting a target fitting curve whose instantaneous change rate meets the preset elastic stage data conditions; performing double linear regression analysis of axial strain-stress and radial strain-axial strain on the target fitting curve to obtain the elastic modulus result and Poisson's ratio result of the rock uniaxial compression test data. It can be seen that the target test data is automatically screened by the preset extreme value data interception method, avoiding the subjectivity of manually intercepting the elastic stage and eliminating the discrete error caused by manual operation. The target fitting curve is intercepted according to the instantaneous change rate of the fitting curve, and the elastic stage boundary is dynamically adjusted. Then, the axial and radial strain data on the target fitting curve are independently fitted. This method can adapt to the diverse curves of brittle rocks (obvious linearity) and ductile rocks (significant nonlinearity), has a wider applicability to rock types, and the instantaneous change rate retains the true mechanical characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0043] Figure 1 This is a flow chart of a rock uniaxial compression test data processing method disclosed in this application;

[0044] Figure 2 This is a schematic diagram of target test data acquisition results disclosed in this application;

[0045] Figure 3 This is a schematic diagram of the fitting results of a target test data disclosed in this application;

[0046] Figure 4 This is a schematic diagram of the interception result of a target fitting curve disclosed in this application;

[0047] Figure 5 This is a schematic diagram of the elastic modulus results of a target fitting curve disclosed in this application;

[0048] Figure 6 A schematic diagram of the Poisson's ratio result of a target fitting curve disclosed in this application;

[0049] Figure 7 This is a schematic diagram of an invalid data marking display result disclosed in this application;

[0050] Figure 8 This is a structural schematic diagram of a rock uniaxial compression test data processing system disclosed in this application;

[0051] Figure 9 This is a structural diagram of an electronic device disclosed in this application. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0053] The uniaxial compression test of rock is a core experimental method for evaluating the mechanical properties of rock. It is widely used in geological engineering, mining engineering, civil engineering and other fields to determine key parameters of rock such as uniaxial compressive strength, elastic modulus and Poisson's ratio. The traditional data processing method mainly includes the following steps: collecting axial stress, axial strain and radial strain data of rock samples through a testing machine; manually intercepting the elastic stage of the stress-strain curve (usually an approximately linear segment); performing a single linear regression analysis on the intercepted data to calculate the elastic modulus and Poisson's ratio. However, the above method has significant drawbacks in practical applications:

[0054] Manual interception is highly subjective: the elastic stage boundary relies on the operator's experience and judgment. Multiple operations by different personnel or the same person are prone to deviations, resulting in large discreteness in parameter calculation results (the error can reach 10%-15%).

[0055] Fixed thresholds have poor adaptability: Existing automated algorithms mostly use fixed strain thresholds, such as using a strain of 0.05%-0.2% to intercept the elastic stage. However, rock types are diverse, such as brittle granite and ductile shale, and their stress-strain curves have significant differences in morphology. Fixed thresholds are difficult to dynamically adapt to the complex changes in nonlinear transition sections.

[0056] High noise sensitivity: Test data is often subject to noise due to interference such as sensor drift and environmental vibration. Traditional single linear regression or low-order polynomial fitting methods have weak anti-interference capabilities, and the calculation results have significant deviations under low signal-to-noise ratios (SNR<15dB).

[0057] To this end, the present invention provides a rock uniaxial compression test data processing solution, which avoids human errors through process automation and improves the efficiency, accuracy and reliability of rock uniaxial compression test data processing.

[0058] Reference Figure 1 As shown, the embodiment of the present invention discloses a method for processing rock uniaxial compression test data, comprising:

[0059] Step S11: obtaining rock uniaxial compression test data collected by a rock mechanics testing machine, and intercepting and processing the rock uniaxial compression test data according to a preset extreme value data interception method to obtain target test data.

[0060] In this embodiment, sensors on a rock mechanics testing machine collect real-time axial stress, axial strain, and radial strain data from rock specimens to obtain rock uniaxial compression test data. It is understood that stress sensors and strain sensors are installed on the rock mechanics testing machine. When the rock mechanics testing machine performs a uniaxial compression test on rock, the axial stress, axial strain, and radial strain data collected by the stress and strain sensors are acquired in real time as the rock uniaxial compression test data. A uniaxial compression test on rock involves applying gradually increasing pressure along a single axis (usually vertical) to a cylindrical or cubic rock specimen under laboratory conditions until the rock specimen fails. This test can be used to obtain the above-mentioned rock uniaxial compression test data.

[0061] In this embodiment, the minimum data value in the rock uniaxial compression test data is searched, and the minimum data value is used as the interception starting point, and the maximum data value in the rock uniaxial compression test data is searched in chronological order, and the maximum data value is used as the interception end point; the rock uniaxial compression test data located between the interception starting point and the interception end point is intercepted to obtain the target test data. It can be understood that since only elastic stage data is required to calculate the elastic modulus and Poisson's ratio, and the elastic stage data is only contained in the part before the peak strength, when intercepting the rock uniaxial compression test data, the maximum and minimum values of the entire rock uniaxial compression test data sequence are first found, and then the search is started according to the data index. When the minimum value is searched, it is recorded as the start, and when the maximum value is searched, it is recorded as the end. The intercepted data segment is the target test data. Figure 2 As shown, the red points represent the rock uniaxial compression test data, and the blue points are the target test data. Figure 2 It can be seen that the target test data to be intercepted are all the rock uniaxial compression test data before the peak strength reaches the highest level. In this way, the elastic stage data can be obtained.

[0062] Step S12: fitting the target test data to obtain a fitted stress-strain curve, obtaining the instantaneous rate of change of stress to strain in the fitted stress-strain curve, and intercepting a target fitting curve whose instantaneous rate of change meets the preset elastic stage data condition.

[0063] In a specific embodiment, a third-order polynomial is directly used to fit the target test data to obtain a fitted stress-strain curve, wherein the third-order polynomial fitting formula is as follows:

[0064] ;

[0065] in, Indicates axial stress in MPa. represents the axial strain, dimensionless, 、 、 、 represents the polynomial coefficients determined by least squares fitting.

[0066] In another specific embodiment, a low-order polynomial is fitted to the target test data to obtain an initial fitting curve; a candidate order polynomial is selected based on the change in curvature index of the initial fitting curve; a target order polynomial of the initial fitting curve is determined from the candidate order polynomials using a cross-validation method; and the target test data is subjected to polynomial fitting processing using the target order polynomial to obtain a fitted stress-strain curve. It is understood that the target test data is analyzed by second-order derivatives to obtain an initial fitting curve, and based on the curvature change of the initial fitting curve, a target order polynomial is dynamically determined from candidate order polynomials of order 2 to 5. If the curvature index change is greater than a preset curvature index threshold, a 4th-order or 5th-order polynomial is used for fitting, otherwise a 2nd-order or 3rd-order polynomial is used. Furthermore, a cross-validation method, such as a leave-one-out method, is used to determine the optimal order to avoid overfitting. In this way, by determining the target order polynomial above, the corresponding target order polynomial can be selected for fitting the target test data in different scenarios according to the scenario. For example, for brittle rock (with obvious linearity), a low-order polynomial is used to reduce the amount of calculation; for ductile rock (with significant nonlinearity), a high-order fit is automatically upgraded to improve the curve representation capability. The target test data is then polynomially fitted according to the selected target order polynomial to obtain the fitted stress-strain curve.

[0067] like Figure 3 As shown, Figure 3 The fitted stress-strain curve is obtained by polynomial fitting based on the intercepted target test data, where the blue curve is the target test data and the red curve is the fitted stress-strain curve.

[0068] In a specific embodiment, the instantaneous rate of change of stress to strain in the fitted stress-strain curve is calculated using the first-order derivative, wherein the instantaneous rate of change is calculated using the following formula:

[0069] ;

[0070] in, It represents the instantaneous rate of change of stress with respect to strain.

[0071] Furthermore, a target fitting curve whose instantaneous change rate satisfies a preset elastic stage data condition is intercepted, wherein the preset elastic stage data condition is:

[0072] ;

[0073] It can be seen that the target fitting curve is obtained by filtering the instantaneous change rate and retaining the data segment that decays to 70% of the peak value. Figure 4 As shown, the blue part is the intercepted data and the green part is the target fitting curve.

[0074] In another specific embodiment, a sliding window is used to obtain several local peaks of the fitted stress-strain curve, and each local peak is used as the maximum peak value in the corresponding elastic stage interval. A target threshold value for the corresponding elastic stage interval is set based on each maximum peak value. Target fitting data whose instantaneous rate of change of the fitted data in the fitted stress-strain curve is greater than or equal to the target threshold value for the corresponding elastic stage interval are screened from each elastic stage interval to obtain a target fitting curve for each elastic stage interval. It is understood that the derivative threshold method is improved to address the potential multiple elastic stages of complex rocks (such as layered rock masses). Specifically, a sliding window is used to identify multiple local peaks of the derivative curve, and the fitted stress-strain curve is segmented into multiple elastic intervals based on each local peak value. Linear regression is performed on each elastic interval to calculate the equivalent elastic modulus range. This more accurately reflects the mechanical properties of anisotropic or layered rock structures. The elastic modulus interval values are output to provide a basis for engineering safety factor calculation.

[0075] Step S13: performing double linear regression analysis of axial strain-stress and radial strain-axial strain on the target fitting curve to obtain elastic modulus results and Poisson's ratio results of the rock uniaxial compression test data.

[0076] In this embodiment, linear regression analysis is performed on the axial strain-stress data and radial strain-axial strain data in the target fitting curves for each elastic stage interval to obtain the elastic modulus and Poisson's ratio results for each elastic stage interval of the rock uniaxial compression test data. It can be understood that the elastic modulus calculation formula is:

[0077] ;

[0078] in: Indicates the elastic modulus result in GPa. It represents the axial stress increment in MPa, taking the stress difference between the beginning and the end of the intercepted segment linear fitting. It represents the axial strain increment, dimensionless, and is the difference between the first and last strains of the intercepted segment linear fit. Figure 5 As shown, the blue part is the curve data of the target fitting curve, and the red part is the fitting result of the curve data. The elastic modulus result is 39.06 GPa.

[0079] The Poisson's ratio is calculated as follows:

[0080] ;

[0081] in, represents the Poisson's ratio result, It represents the radial strain increment of the linear fit, dimensionless. Figure 6 As shown, the blue part is the curve data of the target fitting curve, the red part is the fitting result of the curve data, and the Poisson's ratio result is 0.1.

[0082] In this embodiment, the stress goodness of fit of the fitted stress-strain curve is calculated based on the actual stress value of the target test data and the corresponding fitted stress value on the fitted stress-strain curve to obtain a fitting coefficient. When the fitting coefficient is less than a preset fitting coefficient threshold, the abnormal data of the fitted stress-strain curve is marked and a visual report is generated. Based on the visual report, the step of obtaining the rock uniaxial compression test data collected by the rock mechanics testing machine is performed. It is understood that the fitting coefficient calculation formula is as follows:

[0083] ;

[0084] in, represents the fitting coefficient, i represents the index number of the data point, The value range is [0,1], Indicates the true stress value in MPa. Indicates the fitting stress value on the fitting curve, in MPa. It represents the measured true stress mean value, in MPa.

[0085] If the fitting coefficient is less than 0.8 (the preset fitting coefficient threshold), it indicates that there is an abnormality in the current fitting process, and the current data are all invalid data. In this case, a translucent red stamp is added to the visual report to cover the abnormal curve interval, such as Figure 7 The result shown is an invalid result in the Poisson's ratio calculation. Then jump back to the step of obtaining the rock uniaxial compression test data collected by the rock mechanics testing machine until Stop when ≥0.8 or the number of iterations exceeds 3.

[0086] In this embodiment, after obtaining the elastic modulus and Poisson's ratio results for the rock uniaxial compression test data, the method further includes: providing real-time feedback of the elastic modulus results to the testing machine control system, so that the testing machine control system can dynamically adjust the loading rate of the rock mechanics testing machine during the test based on the elastic modulus results. It is understood that providing real-time feedback of the calculated results (elastic modulus and Poisson's ratio results) to the testing machine control system allows the control system to dynamically adjust the loading rate based on the initial elastic modulus value, such as reducing the loading rate for high-modulus rock. For example, if the elastic modulus calculation results are fed back to the testing machine in real time and the E value exceeds a preset threshold, the loading rate is automatically adjusted to 50%-80% of the original rate. If abnormal data is detected, the test is automatically paused and a prompt is issued to inspect the specimen or sensor. This prevents unnatural specimen damage caused by improper loading rates, reduces the measured failure rate by 40%, and improves the test success rate.

[0087] It can be seen that the present application discloses a method for processing rock uniaxial compression test data, including: obtaining rock uniaxial compression test data collected by a rock mechanics testing machine, and intercepting the rock uniaxial compression test data according to a preset extreme value data interception method to obtain target test data; fitting the target test data to obtain a stress-strain curve after fitting, and obtaining the instantaneous change rate of stress to strain in the stress-strain curve after fitting, and intercepting a target fitting curve whose instantaneous change rate meets the preset elastic stage data conditions; performing double linear regression analysis of axial strain-stress and radial strain-axial strain on the target fitting curve to obtain the elastic modulus result and Poisson's ratio result of the rock uniaxial compression test data. It can be seen that the target test data is automatically screened by the preset extreme value data interception method, avoiding the subjectivity of manually intercepting the elastic stage and eliminating the discrete error caused by manual operation. The target fitting curve is intercepted according to the instantaneous change rate of the fitting curve, and the elastic stage boundary is dynamically adjusted. Then, the axial and radial strain data on the target fitting curve are independently fitted. This method can adapt to the diverse curves of brittle rocks (obvious linearity) and ductile rocks (significant nonlinearity), has a wider applicability to rock types, and the instantaneous change rate retains the true mechanical characteristics.

[0088] Reference Figure 8 As shown, the present invention also discloses a rock uniaxial compression test data processing system, including a data acquisition module 11, a dynamic fitting module 12, an elastic stage interception module 13, a parameter calculation module 14, and a verification and packaging module 15, wherein:

[0089] The data acquisition module 11 is connected to the stress sensor and the strain sensor of the rock mechanics testing machine, and is used to obtain the rock uniaxial compression test data collected by the rock mechanics testing machine in real time, and intercept and process the rock uniaxial compression test data according to a preset extreme value data interception method to obtain target test data;

[0090] The dynamic fitting module 12 is used to perform fitting processing on the target test data to obtain a fitted stress-strain curve and obtain the instantaneous rate of change of stress to strain in the fitted stress-strain curve;

[0091] The elastic stage interception module 13 is used to intercept the target fitting curve whose instantaneous change rate meets the preset elastic stage data conditions;

[0092] The parameter calculation module 14 is used to perform double linear regression analysis of axial strain-stress and radial strain-axial strain on the target fitting curve to obtain elastic modulus results and Poisson's ratio results of the rock uniaxial compression test data;

[0093] The verification and packaging module 15 is used to calculate the stress fitting goodness of the fitted stress-strain curve based on the true stress value of the target test data and the corresponding fitted stress value on the fitted stress-strain curve to obtain a fitting coefficient; when the fitting coefficient is less than a preset fitting coefficient threshold, abnormal data of the fitted stress-strain curve is marked and a visual report is generated.

[0094] It can be seen that the present application discloses the acquisition of rock uniaxial compression test data collected by a rock mechanics testing machine, and intercepting the rock uniaxial compression test data according to a preset extreme value data interception method to obtain target test data; fitting the target test data to obtain a stress-strain curve after fitting, and obtaining the instantaneous rate of change of stress to strain in the stress-strain curve after fitting, and intercepting a target fitting curve whose instantaneous rate of change meets the preset elastic stage data conditions; performing double linear regression analysis of axial strain-stress and radial strain-axial strain on the target fitting curve to obtain the elastic modulus result and Poisson's ratio result of the rock uniaxial compression test data. It can be seen that the target test data is automatically screened by the preset extreme value data interception method, avoiding the subjectivity of manually intercepting the elastic stage and eliminating the discrete error caused by manual operation. The target fitting curve is intercepted according to the instantaneous change rate of the fitting curve, and the elastic stage boundary is dynamically adjusted. Then, the axial and radial strain data on the target fitting curve are independently fitted. This method can adapt to the diverse curves of brittle rocks (obvious linearity) and ductile rocks (significant nonlinearity), has a wider applicability to rock types, and the instantaneous change rate retains the true mechanical characteristics.

[0095] Furthermore, the embodiment of the present application also discloses an electronic device, Figure 9 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram should not be considered as any limitation to the scope of application of the present application.

[0096] Figure 9 This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps of the rock uniaxial compression test data processing method disclosed in any of the aforementioned embodiments. Furthermore, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0097] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device. The communication protocol it follows is any communication protocol that can be applied to the technical solution of this application and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world. Its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0098] Among them, the processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 can be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 21 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 21 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0099] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or CD, etc. The resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0100] The operating system 221 is used to manage and control the hardware devices and computer programs 222 on the electronic device 20, enabling the processor 21 to calculate and process the massive amount of data 223 in the memory 22. It can be run on Windows Server, NetWare, Unix, Linux, or other operating systems. In addition to including computer programs capable of performing the rock uniaxial compression test data processing method performed by the electronic device 20 as disclosed in any of the aforementioned embodiments, the computer programs 222 may further include computer programs capable of performing other specific tasks. Data 223 may include data received by the electronic device from external devices, as well as data collected by its own input / output interface 25.

[0101] Furthermore, this application discloses a computer-readable storage medium for storing a computer program. When executed by a processor, the computer program implements the aforementioned rock uniaxial compression test data processing method. The specific steps of this method can be found in the corresponding content disclosed in the aforementioned embodiments and will not be further elaborated here.

[0102] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from the other embodiments. Reference can be made to the descriptions of the identical or similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and the relevant parts can be referred to the descriptions of the methods.

[0103] Professionals may further appreciate that the units and algorithmic steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application. The steps of the method or algorithm described in conjunction with the embodiments disclosed herein can be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module can be placed in a random access memory RAM (Random Access Memory), memory, read-only memory ROM (Read Only Memory), electrically programmable EPROM (Electrically Programmable Read Only Memory), electrically erasable programmable EEPROM (Electric Erasable Programmable Read Only Memory), registers, hard disk, removable disk, CD-ROM (Compact Disc-Read Only Memory), or any other form of storage medium known in the technical field.

[0104] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0105] The above is a detailed introduction to the solution provided by the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

Claims

1. A method for processing rock uniaxial compression test data, characterized in that: include: Obtaining rock uniaxial compression test data collected by a rock mechanics testing machine, and intercepting and processing the rock uniaxial compression test data according to a preset extreme value data interception method to obtain target test data; Performing fitting processing on the target test data to obtain a fitted stress-strain curve, obtaining the instantaneous rate of change of stress to strain in the fitted stress-strain curve, and intercepting a target fitting curve whose instantaneous rate of change meets a preset elastic stage data condition; Double linear regression analysis of axial strain-stress and radial strain-axial strain is performed on the target fitting curve to obtain elastic modulus results and Poisson's ratio results of the rock uniaxial compression test data.

2. The rock uniaxial compression test data processing method according to claim 1, characterized in that: The obtaining of rock uniaxial compression test data collected by a rock mechanics testing machine includes: The axial stress, axial strain and radial strain data of the rock sample are collected in real time through the sensors of the rock mechanics testing machine to obtain the rock uniaxial compression test data.

3. The rock uniaxial compression test data processing method according to claim 1, characterized in that: The method of intercepting the rock uniaxial compression test data according to a preset extreme value data interception method to obtain target test data includes: Searching for a minimum data value in the rock uniaxial compression test data, and using the minimum data value as a truncation starting point, searching for a maximum data value in the rock uniaxial compression test data in chronological order, and using the maximum data value as a truncation end point; The rock uniaxial compression test data between the interception starting point and the interception end point are intercepted to obtain target test data.

4. The rock uniaxial compression test data processing method according to claim 1, characterized in that: The fitting process of the target test data to obtain a fitted stress-strain curve includes: Performing low-order polynomial fitting on the target test data to obtain an initial fitting curve; Selecting a candidate order polynomial according to a change in a curvature index of the initial fitting curve; Determining a target order polynomial of the initial fitting curve from the candidate order polynomials using a cross-validation method; The target test data is subjected to polynomial fitting processing using the target order polynomial to obtain a fitted stress-strain curve.

5. The rock uniaxial compression test data processing method according to claim 1, characterized in that: The target fitting curve whose intercepting instantaneous change rate satisfies the preset elastic stage data condition includes: Acquire several local peaks of the fitted stress-strain curve through a sliding window, use each local peak as a maximum peak value in a corresponding elastic stage interval, and set a target threshold value for the corresponding elastic stage interval based on each maximum peak value; Filtering target fitting data whose instantaneous change rate of the fitting data in the stress-strain curve after fitting is greater than or equal to the target threshold value of the corresponding elastic stage interval from each elastic stage interval, so as to obtain a target fitting curve for each elastic stage interval; Accordingly, the target fitting curve is subjected to double linear regression analysis of axial strain-stress and radial strain-axial strain respectively to obtain the elastic modulus result and Poisson's ratio result of the rock uniaxial compression test data, including: Linear regression analysis is performed on the axial strain-stress data and radial strain-axial strain data in the target fitting curve of each elastic stage interval to obtain the elastic modulus results and Poisson's ratio results of each elastic stage interval of the rock uniaxial compression test data.

6. The rock uniaxial compression test data processing method according to any one of claims 1 to 5, characterized in that: Also includes: Calculating the stress fitting goodness of the fitted stress-strain curve based on the true stress value of the target test data and the corresponding fitted stress value on the fitted stress-strain curve to obtain a fitting coefficient; When the fitting coefficient is less than a preset fitting coefficient threshold, the abnormal data of the stress-strain curve after fitting is marked and a visual report is generated, so as to execute the step of obtaining the rock uniaxial compression test data collected by the rock mechanics testing machine based on the visual report.

7. The rock uniaxial compression test data processing method according to claim 1, characterized in that: After obtaining the elastic modulus result and Poisson's ratio result of the rock uniaxial compression test data, the method further includes: The elastic modulus result is fed back to the testing machine control system in real time, so that the testing machine control system controls the rock mechanics testing machine to dynamically adjust the loading rate of the testing process according to the elastic modulus result.

8. A rock uniaxial compression test data processing system, characterized in that: It includes data acquisition module, dynamic fitting module, elastic stage interception module, parameter calculation module, verification and packaging module, among which, The data acquisition module is connected to the stress sensor and the strain sensor of the rock mechanics testing machine, and is used to obtain rock uniaxial compression test data collected by the rock mechanics testing machine in real time, and intercept and process the rock uniaxial compression test data according to a preset extreme value data interception method to obtain target test data; The dynamic fitting module is used to perform fitting processing on the target test data to obtain a fitted stress-strain curve and obtain the instantaneous rate of change of stress to strain in the fitted stress-strain curve; The elastic stage interception module is used to intercept the target fitting curve whose instantaneous change rate meets the preset elastic stage data conditions; The parameter calculation module is used to perform double linear regression analysis of axial strain-stress and radial strain-axial strain on the target fitting curve to obtain elastic modulus results and Poisson's ratio results of the rock uniaxial compression test data; The verification and packaging module is used to calculate the stress fitting goodness of the fitted stress-strain curve based on the true stress value of the target test data and the corresponding fitted stress value on the fitted stress-strain curve to obtain a fitting coefficient; when the fitting coefficient is less than a preset fitting coefficient threshold, abnormal data of the fitted stress-strain curve is marked and a visual report is generated.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor is used to execute the computer program to implement the steps of the rock uniaxial compression test data processing method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that Used to store computer programs; wherein, when the computer program is executed by a processor, the steps of the rock uniaxial compression test data processing method according to any one of claims 1 to 7 are implemented.

Images