Multi-stage fatigue crack propagation demarcation point identification and evaluation method and system, electronic equipment and medium

Abstract

The invention relates to the technical field of material fatigue performance evaluation and structural integrity detection, in particular to a multi-stage fatigue crack propagation demarcation point identification and evaluation method and system, electronic equipment and a medium. Comprising the following steps: acquiring test data and constructing a curve, calculating a derivative by adopting a sliding window and identifying candidate demarcation points, and determining the demarcation points in combination with material behavior verification; the invention further discloses electronic equipment and a computer readable storage medium applying the method. The problems that in the prior art, a crack propagation stage division method depends on manual interpretation, the subjectivity of an identification result is high, and unified standards are lacked are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of material fatigue performance evaluation and structural integrity detection, and particularly relates to a multi-stage fatigue crack propagation boundary point identification and evaluation method and system, an electronic device and a medium. BACKGROUND

[0002] Fatigue cracks are prone to occur in metal structures under long-term service or repeated loading. The crack propagation process usually goes through crack initiation stage, stable propagation stage and rapid propagation instability stage. The mechanical behavior and evolution mechanism of different stages are significantly different, which is an important basis for fatigue life prediction, structural reliability evaluation and service decision. Therefore, the identification of the boundary points of each stage in the fatigue crack propagation process has become one of the key problems in fatigue research and engineering application.

[0003] The existing problem of the traditional technology is that the division of the crack propagation stage is mostly dependent on the relationship curve between the crack propagation rate (da / dN) and the stress intensity factor range (ΔK), and the stage boundary points are determined by manually judging the slope change of the curve or setting a threshold value by experience, thereby leading to strong subjectivity, dependence on the experience of the operator, lack of unified standard, and especially under the conditions of complex material behavior or variable loading path (such as variable amplitude, non-proportional multi-axial loading), it is difficult to accurately determine the turning points of each stage. SUMMARY

[0004] In view of this, the purpose of the present application is to provide a multi-stage fatigue crack propagation boundary point identification and evaluation method, system, electronic device and medium, which solves the problem of the crack propagation stage division method in the prior art relying on manual judgment, the strong subjectivity of the identification result, and the lack of unified standard.

[0005] In the first aspect, the present application discloses a multi-stage fatigue crack propagation boundary point identification and evaluation method, comprising the following steps: obtaining fatigue crack propagation test data, including crack length, loading cycle number and load information, calculating crack propagation rate da / dN and stress intensity factor range ΔK, and constructing da / dN-ΔK curve; performing traversal processing on the curve by using a sliding window, and calculating the first derivative and the second derivative of the curve in each sliding window; setting mutation thresholds of the first derivative and the second derivative, and identifying the points that simultaneously satisfy the first derivative mutation and the second derivative mutation conditions as candidate crack propagation stage boundary points; combining the material fatigue behavior and the mechanical model, verifying the physical mechanism of the candidate boundary points, and finally determining the boundary points B1 of the crack initiation and stable propagation stages, and the boundary points B2 of the stable propagation and rapid fracture stages.

[0006] Specifically, the first derivative is a local slope.

[0007] Specifically, the second derivative is a slope change rate or acceleration.

[0008] The optimized sliding window width w is dynamically adjusted according to the data noise level and material characteristics, and satisfies the following formula: w = w0 x (1 + σ / μ).

[0009] More specifically, w0 is an initial window width, σ is a standard deviation of data in the window, and μ is a mean value of data in the window.

[0010] In a second aspect, the present application discloses an electronic device applied to the multi-stage fatigue crack propagation boundary point identification and evaluation method, comprising a memory and a processor, the memory is used for storing a computer program, and the processor runs the computer program to make the electronic device execute the multi-stage fatigue crack propagation boundary point identification and evaluation method.

[0011] In a third aspect, the present application discloses a computer readable storage medium applied to the multi-stage fatigue crack propagation boundary point identification and evaluation method, and the computer readable storage medium stores a computer program, and the computer program is executed by a processor to realize the multi-stage fatigue crack propagation boundary point identification and evaluation method.

[0012] The present application has the following beneficial effects:

[0013] Compared with the traditional method, the present application solves the problem that the crack propagation stage division method in the prior art relies on manual interpretation, the identification result is highly subjective, and there is a lack of unified standard. The crack propagation stage boundary point evaluation technology provided by the present application is highly universal, highly accurate, and can be automatically executed, so as to improve the objectivity and intelligent level of fatigue analysis, and can be embedded in an existing structure health monitoring system, nondestructive testing data processing flow or material testing platform, and promote the transformation of fatigue evaluation from traditional manual interpretation to intelligent analysis. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 FIG. 1 is a flowchart of the multi-stage fatigue crack propagation boundary point identification and evaluation method of the present application.

[0015] Figure 2 FIG. 4 is a schematic diagram of a relationship curve between the crack propagation rate da / dN and the stress intensity factor range ΔK.

[0016] Figure 3 FIG. 6 is a schematic diagram of a crack propagation relationship curve and multi-stage boundary point identification of the present application.

[0017] Figure 4 FIG. 8 is a fracture morphology comparison diagram of the present application.

[0018] Figure 5 FIG. 10 is a system architecture diagram of the multi-stage fatigue crack propagation boundary point identification and evaluation system of the present application.

[0019] Figure 6An electronic device and a computer readable storage medium architecture of the present application. DETAILED DESCRIPTION

[0020] In order to clearly understand the technical solutions of the present application, a multi-stage fatigue crack propagation demarcation point identification and evaluation method, system, electronic device and medium provided by the present application will be described in detail below in combination with specific embodiments and drawings.

[0021] The terms used in the following embodiments are only for the purpose of describing specific embodiments and are not intended to be limiting on the present application. As used in the specification and the claims of the present application, the singular forms "a," "an," and "the" are intended to include the plural forms as well, e.g., "one or more," unless the context clearly indicates otherwise. It will be further understood that "at least one," "one or more," means one, two, or more than two.

[0022] In the present specification, the phrase "one embodiment" or "some embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present application. Thus, the appearances of the phrase "one embodiment," "in some embodiments," "in other embodiments," "in yet other embodiments," or the like, in various places in the specification are not necessarily all referring to the same embodiment, unless otherwise specifically noted. The terms "including," "containing," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.

[0023] Embodiment 1 provides a multi-stage fatigue crack propagation demarcation point identification and evaluation method, the specific steps are as follows:

[0024] Step 1, data acquisition and curve construction.

[0025] First, collect crack propagation data from fatigue crack propagation tests, including crack length a i , cycle number N i , stress load σ i . The sampling frequency is not less than 10 Hz to ensure data continuity and calculation accuracy.

[0026] The crack propagation rate da / dN is calculated using the following formula:

[0027]

[0028] Where i is the sample point number.

[0029] The stress intensity factor range is calculated as:

[0030]

[0031] where Y is a geometry correction factor, which is determined by looking up a table according to the specimen type.

[0032] Thus, a curve of crack growth rate da / dN versus stress intensity factor range ΔK is constructed.

[0033] Input data: raw experimental data (crack length a i , cycle number N i , stress load σ i ) collected from fatigue crack growth test. Output result: raw fatigue crack growth curve da / dN-ΔK.

[0034] Step 2, sliding window derivative extraction and mutation detection.

[0035] On the basis of the above curve, sliding window traversal is used to analyze the crack growth process:

[0036] Set initial sliding window width W0=N total / 50, where N total is the total number of data points;

[0037] Set window step size s=1, i.e. each data point participates in the calculation.

[0038] In each sliding window, a quadratic polynomial is fitted to the da / dN-ΔK curve:

[0039] f(x)=a0+a1x+a2x 2 ;

[0040] where x=ΔK, f(x)=da / dN.

[0041] From the fitted curve, calculate:

[0042] First derivative (slope): f'(x)=a1+2a2x;

[0043] Second derivative (acceleration): f"(x)=2a2;

[0044] To enhance adaptability and stability, the window width is dynamically adjusted according to the local complexity of the curve:

[0045]

[0046] where λ is the material sensitivity coefficient and j is the sliding window number.

[0047] Input data: da / dN-ΔK curve constructed in step 1; output result: corresponding first derivative f'(x j) and second derivative f"(x j ) of the first derivative f'(x j ). j .

[0048] Step 3: Candidate boundary point identification and calculation of characteristic quantities.

[0049] Adopting the principle of moving window change point detection, compare the changes of statistical characteristics of two adjacent moving windows:

[0050] If the two windows are in the signal stationary section, the derivative characteristics are similar;

[0051] If located in the signal mutation section, the derivative difference is significant.

[0052] Calculate the following two types of characteristic indexes for mutation point identification:

[0053] (1) The first derivative change rate:

[0054]

[0055] (2) The second derivative extreme value ratio:

[0056]

[0057] Set the following judgment conditions:

[0058] If R1≥T1 and R2≥T2, identify the boundary point B1 between crack initiation and stable expansion stage;

[0059] If R1≤-T3 and R2≤-T4, identify the boundary point B2 between stable expansion and unstable fracture stage.

[0060] Wherein, the threshold value is determined according to the experience of material S-N curve characteristics:

[0061] T1=25%, T2=0.7;

[0062] T3=40%, T4=0.6;

[0063] Input data: the first derivative f'(x j ) and the second derivative f"(x j ) sequence of the moving window obtained in step 2; output result: candidate boundary points B1 and B2; coordinate form: (ΔK B1 , da / dN B1 ), (ΔK B2 , da / dN B2 ), provided to the next step for physical significance judgment.

[0064] Step 4: Energy release rate verification and physical confirmation.

[0065] To ensure the physical rationality of the identification point, an energy release rate criterion is further introduced:

[0066]

[0067] Wherein: v: Poisson's ratio, E: elastic modulus;

[0068] The judgment standard is:

[0069] B1 point: G B1 ≈G c / 10;

[0070] B2 point: G B2 ≥0.9G c ; Wherein, G c is the critical energy release rate of the material.

[0071] Input data: the ΔK value of the candidate points B1 and B2 identified in step 3; Output data: judge the physical rationality (effectiveness screening) of B1 and B2; If the condition is not met, it can be discarded and re-identified.

[0072] Step 5: Comprehensive fracture analysis confirmation.

[0073] In order to enhance the reliability of the determination result, the final confirmation can be combined with the fracture morphology characteristics, for example:

[0074] B1 area fatigue strip gradually clear;

[0075] B2 area fatigue strip quickly sparse or turn into brittle fracture surface.

[0076] The final output of the two-stage demarcation point coordinates:

[0077] (ΔK B1 , da / dN B1 ) and (ΔK B2 , da / dN B2 );

[0078] The demarcation point result can be used for three-stage fatigue life modeling, life segment prediction and material service limit evaluation.

[0079] Experimental verification is as follows: verify the multi-stage fatigue crack propagation demarcation point identification and evaluation method of the application, select the same material (Al6082-T6 aluminum alloy) and the same loading condition of the fatigue crack propagation data, and use the traditional method and the method of the application respectively to identify the demarcation point.

[0080] (1) The materials and conditions of the above two methods are consistent:

[0081] Material: Al6082-T6 aluminum alloy;

[0082] Test form: CT test (compact open);

[0083] Loading mode: constant amplitude tension-tension fatigue loading;

[0084] Load ratio: R = 0.1, frequency = 10 Hz;

[0085] Sampling frequency: ≥ 10 Hz, crack length a i , cycle number N i , stress load σ i ;

[0086] (2) Respectively apply the above two methods to set up experimental groups:

[0087] Experimental group A: traditional method;

[0088] Method type: bilinear fitting + manual interpretation;

[0089] Determination of demarcation point: subjective judgment B1, B2 depending on the experience of setting the turning point of linear fitting;

[0090] Fitting function: piecewise linear regression.

[0091] Experimental group B: the method of the application;

[0092] Method type: sliding window derivative + threshold judgment + energy verification;

[0093] Determination of demarcation point: automatically identify the derivative mutation point, combined with physical parameter verification;

[0094] Fitting function: local quadratic fitting + dynamic window self-adaption.

[0095] (3) Comparison of key data after applying the two methods:

[0096] Experimental group A: traditional method;

[0097] B1 position ΔK B1 (MPa·m 1 / 2 ): 9.2;

[0098] B2 position ΔK B2 (MPa·m 1 / 2 ): 25.1;

[0099] G B1 / G c : 0.35;

[0100] G B2 / G c : 0.78;

[0101] Three-section model fitting error RMSE: ± 19%.

[0102] Experiment group B: the method of the present application;

[0103] B1 position ΔK B1 (MPa·m 1 / 2 ): 7.6 (closer to the initiation stage, consistent with the low energy release rate characteristic);

[0104] B2 position ΔK B2 (MPa·m 1 / 2 ): 21.7 (consistent with the initial stage of unstable expansion, and more early identification of risk area);

[0105] G B1 / G c : 0.10 (the present application meets the physical judgment criterion G≈G c / 10);

[0106] G B2 / G c : 0.94 (closer to the energy release rate limit at the instability point);

[0107] Three-stage model fitting error RMSE: ±6% (significantly improves the accuracy of fatigue life segmentation prediction).

[0108] From the above two sets of comparative experiments, it can be seen that the traditional method has obvious subjectivity in identifying the demarcation point of the crack propagation stage, and the determined point has large deviation in physical meaning, which easily leads to inaccurate life prediction. The method of the present application can objectively and accurately identify the key turning points in the crack propagation process through the sliding window derivative analysis and energy release rate verification mechanism. The B1 and B2 points identified are highly consistent with the material energy evolution law and the fracture microstructure, significantly improving the accuracy and engineering applicability of crack modeling. Under the same data set, the fitting error of the three-stage life model established by the method of the present application is reduced by about 68%, effectively enhancing the prediction ability of the service life of the structure.

[0109] Figure 1 A flowchart of a multi-stage fatigue crack propagation demarcation point identification and evaluation method is shown, which shows the overall processing flow of the multi-stage fatigue crack propagation demarcation point identification and evaluation method, which corresponds to steps 1 to 5 one by one, and is a visual summary of the overall logic of the technical solution of the present application. It not only shows the processing path of the crack propagation data, but also embodies the three-determination mechanism of "sliding window identification + derivative mutation detection + energy physical verification" which is different from the traditional method.

[0110] Figure 2 A relationship curve diagram of crack propagation rate da / dN and stress intensity factor range ΔK is shown, Figure 2Corresponding to step 1 in the present application, i.e. the data acquisition and curve construction part, is specifically used to illustrate the da / dN-ΔK relationship curve constructed in the fatigue crack propagation test and its typical segmented characteristics. The typical relationship between the crack propagation rate da / dN and the stress intensity factor range ΔK is shown in the figure. The figure is divided into three crack propagation stages:

[0111] (1) Stage I (crack initiation stage): in the low stress intensity range, the crack propagation rate is slow, and the crack is mainly caused by the gradual initiation of material defects, microstructure or stress concentration; the starting point is the threshold value ΔK IPT , the turning point is the stable expansion starting point ΔK SPT , and the corresponding rate is da / dN I .

[0112] (2) Stage II (stable expansion stage): the crack propagation rate has a power function relationship with ΔK (such as the Paris formula), which is the most commonly used modeling area; the end point is the unstable expansion starting point ΔK PFT , and the corresponding rate is da / dN II .

[0113] (3) Stage III (unstable fracture stage): the crack propagation rate rapidly rises and eventually reaches the critical fracture state; the end point is the fracture toughness K C , and the corresponding expansion rate is da / dN III .

[0114] The gray area in the figure is the transition area between the two stages, which shows the area where the curve has a "non-linear transition", and is the location of the demarcation point identified by the present application.

[0115] Figure 3 The figure shows the crack propagation relationship curve and the identification of the multi-stage demarcation point, Figure 3 corresponding to steps 2 and 3, which specifically embodies the key process of derivative extraction analysis and mutation recognition algorithm based on sliding window. It shows the candidate demarcation points based on sliding window detection and the first and second derivative trends, and the figure shows how the method of the present application applies the sliding window technology to the test data curve, and identifies the demarcation points of the key crack propagation stages by combining the first and second derivative trends. Specifically includes:

[0116] The upper side of the figure is the actually constructed da / dN-ΔK curve (logarithmic coordinate system), wherein point B1 represents the candidate demarcation point of the transition from crack initiation to stable expansion; point B2 represents the candidate demarcation point of the transition from stable expansion to unstable fracture; and the gray area in the figure is the fitting analysis area in the sliding window (labeled u-v-w), which is used for local derivative calculation.

[0117] The thick solid line on the lower side of the figure is the first derivative image (i.e. the slope change curve); the dashed line is the second derivative image (i.e. the acceleration change curve); the positions of the abrupt points of the derivative curve are clearly marked: B1', B1" correspond to the first and second derivative jump points of B1; B2', B2" correspond to B2.

[0118] Figure 4 The fracture morphology contrast diagram is shown, Figure 4 Corresponding to step 5 in the specification: comprehensive fracture analysis confirmation, used for further verification of the physical reasonableness of the candidate boundary points B1 and B2. The metallographic characteristics of different stages of crack propagation are shown in the figure; the micro-fracture characteristics formed by the fatigue specimen at different crack propagation stages are shown, which are used to assist in verifying the physical reasonableness of the crack propagation stage boundary points identified by the present application. The following three regions can be clearly distinguished in the figure:

[0119] Crack initiation area (inner circle on the right side): the strip is fine and slightly blurred, which is the micro-crack initiation area caused by local stress concentration of the material; corresponding to the initial stage of crack propagation (Stage I), the physical characteristics are consistent with the point B1 before.

[0120] Crack stable propagation area (middle area): the strip is clear and uniform, and develops at equal intervals, which is a typical Paris stable propagation area; consistent with the identified segment between B1 and B2, verifying the effectiveness of the stable propagation stage model.

[0121] Crack rapid propagation area (outer circle on the left side): the strip is obviously sparse or even interrupted, accompanied by obvious fracture texture, reflecting the acceleration of crack propagation; corresponding to the unstable fracture stage (Stage III), consistent with the point B2 after.

[0122] Figure 4 The positions of the boundary points B1 and B2 identified by the derivative change can be directly and intuitively confirmed to be highly consistent with the actual fracture propagation behavior, proving the physical reasonableness and determination effectiveness of the method in the behavior of engineering materials.

[0123] Example 2, on the basis of the multi-stage fatigue crack propagation boundary point identification and evaluation method in application example 1, the present application also discloses a multi-stage fatigue crack propagation boundary point identification and evaluation system, specifically comprising the following modules:

[0124] Data acquisition module: used for reading crack length, load, cycle number and other original data from the test platform;

[0125] Curve construction module: calling built-in functions to generate da / dN-ΔK curve;

[0126] Sliding window analysis module: according to the above algorithm, the curve is traversed, the derivative is calculated, and the candidate boundary point is output;

[0127] Verification module: call material database or preset theoretical model to screen the demarcation point;

[0128] Result output and visualization module: provide graphical interface to show the whole process of crack propagation and demarcation point positioning;

[0129] Storage module: save intermediate results and final results as project files or database formats for easy calling and tracing.

[0130] The system can be deployed in a test bench control terminal, a portable evaluation device or an industrial computer platform, and has good real-time performance and scalability. Figure 5 The multi-stage fatigue crack propagation demarcation point identification and evaluation system architecture provided by the present application corresponds to the description of the structure of the fatigue crack propagation demarcation point evaluation system in the present application, and embodies the system implementation process from test data collection to demarcation point identification and result output. The figure includes three core parts of data acquisition module, data processing module and result output module, wherein: the data acquisition module is responsible for connecting displacement, load and other sensor interfaces, and acquiring real-time data in the test process through acquisition card and signal conditioning circuit; the data processing module includes curve construction, sliding window analysis, threshold determination and physical verification, etc. Multiple function units realize automatic identification of crack propagation stage; the result output module provides visual interface, report generation and warning notification functions, etc. for outputting the key demarcation point information identified and assisting engineering decision-making.

[0131] In Example 3, on the basis of the multi-stage fatigue crack propagation demarcation point identification and evaluation method in Example 1, the present application further discloses an electronic device and a computer readable storage medium. The method in Example 1 can be packaged as a software program stored in a computer readable storage medium and executed by an electronic device (such as an embedded industrial computer). The program calling module logic is consistent with the above method, and can realize the whole process automatic processing from data import, parameter setting, sliding analysis to demarcation output. The electronic device can be integrated with a fatigue testing machine, a non-destructive testing system or a structural health monitoring system to realize remote control, automatic identification and life state prompting functions. Figure 6It is shown that the electronic device and computer readable storage medium architecture provided by the present application; the figure corresponds to the description of the electronic device and computing platform structure in the present application, which shows the software and hardware support architecture for executing the fatigue boundary point identification method of the present application. The figure contains: processor units, such as CPU (multi-core), GPU (for accelerating calculation) and FPGA (for real-time processing), for running algorithm programs; storage units, including memory RAM, storage devices (SSD / HDD), for storing program codes, curve data and system parameters; I / O interface units, including network interfaces (LAN / WiFi), sensor interfaces, display and input device interfaces, for data exchange and human-computer interaction of the system. The figure embodies that the present application can be integrated into a general computing platform in actual deployment, supporting multiple application scenarios such as automation, visualization and remote operation and maintenance.

Claims

1. A method for multi-stage fatigue crack growth threshold point identification and assessment, comprising: The method comprises the following steps: acquiring fatigue crack propagation test data, including crack length, loading cycle number and load information, calculating crack propagation rate da / dN and stress intensity factor range ΔK, and constructing da / dN-ΔK curve; performing traversal processing on the curve by using sliding window, and calculating first derivative and second derivative of the curve in each sliding window; setting mutation threshold of the first derivative and the second derivative, identifying points satisfying first derivative mutation and second derivative mutation conditions as candidate crack propagation stage boundary points; combining material fatigue behavior and mechanical model, verifying physical mechanism of the candidate boundary points, and finally determining boundary point B1 of crack initiation and stable propagation stage, and boundary point B2 of stable propagation and rapid fracture stage.

2. The multi-stage fatigue crack growth juncture identification and assessment method of claim 1, wherein: The first derivative is a local slope.

3. The multi-stage fatigue crack growth juncture identification and assessment method of claim 1, wherein: The second derivative is a slope change rate or acceleration.

4. The multi-stage fatigue crack growth juncture identification and assessment method of claim 1, wherein: The sliding window width w is dynamically adjusted according to data noise level and material characteristics, and satisfies the following formula: w = w0 × (1 + σ / μ).

5. The multi-stage fatigue crack growth juncture identification and assessment method of claim 4, wherein: w0 is an initial window width, σ is a standard deviation of data in the window, and μ is a mean value of data in the window.

6. An electronic device, comprising: The electronic device for implementing the multi-stage fatigue crack propagation boundary point identification and evaluation method in any one of claims 1 to 5 comprises a memory and a processor, the memory is used for storing a computer program, and the processor runs the computer program to enable the electronic device to perform the multi-stage fatigue crack propagation boundary point identification and evaluation method.

7. A computer-readable storage medium, characterized in that: The electronic device for implementing the multi-stage fatigue crack propagation boundary point identification and evaluation method in any one of claims 1 to 5 stores a computer program, and the computer program is executed by the processor to implement the multi-stage fatigue crack propagation boundary point identification and evaluation method.

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