Material online testing method and system based on partial differential equation

Abstract

The invention relates to the technical field of material testing, and discloses an online material testing method and system based on a partial differential equation, and the method comprises the steps: determining a plurality of high-temperature environment values and a plurality of information collection moments corresponding to each high-temperature environment value, and collecting an initial material high-temperature feedback parameter of each information collection moment, determining a material high-temperature feedback parameter set based on the partial differential equation and the initial material high-temperature feedback parameters; calculating a data set retention factor to obtain a recombinant material high-temperature feedback parameter set; determining a sub-high-temperature tensile strength coefficient corresponding to each high-temperature environment value; and calculating the high-temperature tensile strength coefficient according to the high-temperature environment value and the sub-high-temperature tensile strength coefficient. According to the method, the comprehensive tensile strength of the single-crystal high-temperature alloy in the high-temperature change environment can be determined, the testing precision and efficiency of the comprehensive tensile strength are ensured, a key basis is provided for component optimization and life prediction of the single-crystal high-temperature alloy, and the reliability and safety of practical application are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of material testing, and in particular, to an on-line testing method and system for materials based on partial differential equations. Background Art

[0002] Single crystal superalloys have become the core materials for turbine blades of aeroengines and gas turbines due to their excellent high-temperature tensile strength, and will continue to play a key role for a long time in the future. Therefore, accurately measuring the tensile strength of single crystal superalloys at high temperatures is crucial for evaluating their reliability and safety in practical applications.

[0003] Currently, traditional testing methods for the tensile strength of single crystal superalloys are usually carried out only at a single temperature and a single moment, and cannot characterize the comprehensive tensile strength of single crystal superalloys under the change of time gradient. Moreover, the obtained tensile strength data are difficult to reflect the influence of temperature fluctuations on the performance of single crystal superalloys in the actual high-temperature environment. It is difficult to comprehensively evaluate the performance stability of single crystal superalloys in complex high-temperature environments, resulting in obvious singularity and limitation in the analysis results of tensile strength. Summary of the Invention

[0004] In view of this, the present invention provides an on-line testing method and system for materials based on partial differential equations, which can determine the comprehensive tensile strength of single crystal superalloys in a high-temperature changing environment, ensure the testing accuracy and efficiency of the comprehensive tensile strength, provide a key basis for the composition optimization and life prediction of single crystal superalloys, and ensure the reliability and safety of practical applications.

[0005] The present invention provides an on-line testing method for materials based on partial differential equations, including: Determining a plurality of high-temperature environment values and a plurality of information collection moments corresponding to each high-temperature environment value, collecting initial material high-temperature feedback parameters of the on-line testing material at each information collection moment, and determining a set of material high-temperature feedback parameters based on partial differential equations and the initial material high-temperature feedback parameters; Analyzing the set of material high-temperature feedback parameters, calculating a data set retention factor of the set of material high-temperature feedback parameters, and reorganizing the set of material high-temperature feedback parameters according to the data set retention factor to obtain a reorganized set of material high-temperature feedback parameters; Determining a sub-high-temperature tensile strength coefficient of the on-line testing material corresponding to each high-temperature environment value according to each reorganized set of material high-temperature feedback parameters; Calculating a high-temperature tensile strength coefficient of the on-line testing material according to each high-temperature environment value and the sub-high-temperature tensile strength coefficient of the on-line testing material corresponding to each high-temperature environment value.

[0006] Further, before determining the set of high-temperature feedback parameters of the material based on the partial differential equation and the high-temperature feedback parameters of the initial material, it further includes: Perform anomaly detection on all the high-temperature feedback parameters of the initial material, and delete the abnormal high-temperature feedback parameters of the initial material, where the anomaly detection includes duplicate acquisition detection and error acquisition detection.

[0007] Further, when collecting the high-temperature feedback parameters of the initial material of the on-line test material at each information collection moment and determining the set of high-temperature feedback parameters of the material based on the partial differential equation and the high-temperature feedback parameters of the initial material, it includes: Determine the equivalent thermal conductivity of the on-line test material at each high-temperature environment value based on the partial differential equation; Determine the high-temperature feedback parameters of the material corresponding to each information collection moment according to the equivalent thermal conductivity of the material and the high-temperature feedback parameters of the initial material; Construct the set of high-temperature feedback parameters of the material according to all the high-temperature feedback parameters of the material.

[0008] Further, when calculating the data set retention factor of the set of high-temperature feedback parameters of the material and reorganizing the set of high-temperature feedback parameters of the material according to the data set retention factor to obtain the reorganized set of high-temperature feedback parameters of the material, it includes: Determine the first high-temperature feedback parameter of the material corresponding to the first information collection moment and the second high-temperature feedback parameter of the material corresponding to the second information collection moment from the set of high-temperature feedback parameters of the material; Calculate the difference between the first high-temperature feedback parameter and the second high-temperature feedback parameter as the data set deviation value of the set of high-temperature feedback parameters of the material; Calculate the data set retention factor of the set of high-temperature feedback parameters of the material according to the data set deviation value; Obtain a preset data set retention factor. If the data set retention factor is greater than or equal to the preset data set retention factor, do not reorganize the set of high-temperature feedback parameters of the material, and use the set of high-temperature feedback parameters of the material as the reorganized set of high-temperature feedback parameters of the material; If the data set retention factor is less than the preset data set retention factor, sort the set of high-temperature feedback parameters of the material in ascending order, and extract the first high-temperature feedback parameter and the second high-temperature feedback parameter; Calculate the difference between the first high-temperature feedback parameter and the second high-temperature feedback parameter of the material. If the difference between the high-temperature feedback parameters of the material is greater than or equal to the preset difference, retain the first high-temperature feedback parameter and the second high-temperature feedback parameter; If the difference between the high-temperature feedback parameters of the material is less than the preset difference, delete the first high-temperature feedback parameter and retain the second high-temperature feedback parameter; Extract the high-temperature feedback parameters of the third material and the high-temperature feedback parameters of the fourth material, repeat the iteration, and determine the high-temperature feedback parameter set of the recombinant material according to the retained high-temperature feedback parameters of the material.

[0009] Further, when calculating the data set retention factor of the high-temperature feedback parameter set of the material according to the data set deviation value, it includes: Calculate the data set retention factor of the high-temperature feedback parameter set of the material according to the following formula: ; where q is the data set retention factor of the high-temperature feedback parameter set of the material, w1 max is the maximum high-temperature feedback parameter of the material, w2 min is the minimum high-temperature feedback parameter of the material, e is the data set deviation value, r is the number of high-temperature feedback parameters in the high-temperature feedback parameter set of the material, t i is the i-th high-temperature feedback parameter in the high-temperature feedback parameter set of the material, t i+1 is the (i + 1)-th high-temperature feedback parameter in the high-temperature feedback parameter set of the material.

[0010] Further, when determining the sub-high-temperature tensile strength coefficient of the on-line test material corresponding to each high-temperature environment value according to each high-temperature feedback parameter set of the recombinant material, it includes: Combine the high-temperature feedback parameters in the high-temperature feedback parameter set of the recombinant material to obtain three groups of high-temperature feedback parameters of the material, where the three groups of high-temperature feedback parameters of the material include the first group of high-temperature feedback parameters of the material, the second group of high-temperature feedback parameters of the material, and the third group of high-temperature feedback parameters of the material; Perform a summation calculation on each group of high-temperature feedback parameters of the material to obtain the corresponding sum value of the high-temperature feedback parameters of the material; Determine the second-largest high-temperature feedback parameter from the high-temperature feedback parameter set of the recombinant material, and calculate the ratio of each sum value of the high-temperature feedback parameters of the material to the second-largest high-temperature feedback parameter of the material as the change value of the high-temperature feedback parameters of the high-temperature feedback parameter set of the recombinant material; Determine the sub-high-temperature tensile strength coefficient of the on-line test material according to all the change values of the high-temperature feedback parameters of the material.

[0011] Further, when determining the sub-high-temperature tensile strength coefficient of the on-line test material according to all the change values of the high-temperature feedback parameters of the material, it includes: Determine the sub-high-temperature tensile strength coefficient of the on-line test material according to the following formula: ; Wherein, p is the sub-high temperature tensile strength coefficient of the online test material, s1 is the change value of the first material's high temperature feedback parameter, s2 is the change value of the second material's high temperature feedback parameter, s3 is the change value of the third material's high temperature feedback parameter, a1 is the first calculation coefficient, a2 is the second calculation coefficient, a3 is the third calculation coefficient, a1 + a2 + a3 = 1, a1 > 0, a2 > 0, a3 > 0, f1 is the variance corresponding to the first material's high temperature feedback parameter group, f2 is the variance corresponding to the second material's high temperature feedback parameter group, f3 is the variance corresponding to the third material's high temperature feedback parameter group, and f is the variance corresponding to the recombined material's high temperature feedback parameter set.

[0012] Further, when calculating the high temperature tensile strength coefficient of the online test material according to each high temperature environment value and the sub-high temperature tensile strength coefficient of the online test material corresponding to each high temperature environment value, it includes: Extract the first high temperature environment value and the second high temperature environment value, and extract the first sub-high temperature tensile strength coefficient and the second sub-high temperature tensile strength coefficient; Calculate the absolute value of the high temperature environment difference between the first high temperature environment value and the second high temperature environment value; Extract the maximum high temperature environment value and the minimum high temperature environment value from all high temperature environment values, and calculate the extreme high temperature environment difference between the maximum high temperature environment value and the minimum high temperature environment value; Determine the ratio of the extreme high temperature environment difference to the absolute value of the high temperature environment difference as the first calculation factor; Calculate the absolute value of the difference between the first sub-high temperature tensile strength coefficient and the second sub-high temperature tensile strength coefficient; Extract the maximum sub-high temperature tensile strength coefficient and the minimum sub-high temperature tensile strength coefficient from all sub-high temperature tensile strength coefficients, and calculate the extreme sub-high temperature tensile strength coefficient difference between the maximum sub-high temperature tensile strength coefficient and the minimum sub-high temperature tensile strength coefficient; Determine the ratio of the extreme sub-high temperature tensile strength coefficient difference to the absolute value of the sub-high temperature tensile strength coefficient as the second calculation factor; Take the sum value of the first calculation factor and the second calculation factor as the comprehensive calculation factor; Repeat the iteration to obtain multiple comprehensive calculation factors, and calculate the high temperature tensile strength coefficient of the online test material according to all the comprehensive calculation factors.

[0013] Further, when calculating the high temperature tensile strength coefficient of the online test material according to all the comprehensive calculation factors, it includes: Calculate the high temperature tensile strength coefficient of the online test material according to the following formula: ; Among them, g is the high-temperature tensile strength coefficient of the online test material, h is the number of comprehensive calculation factors, and k j is the jth comprehensive calculation factor, and k min is the minimum comprehensive calculation factor, and k max is the maximum comprehensive calculation factor, ([[]]END]] - ) max is the maximum value of all ([[]]END]] - ).

[0014] On the other hand, the present application also provides a material online test system based on partial differential equations, including: A parameter set determination module for determining a plurality of high-temperature environment values and a plurality of information collection times corresponding to each high-temperature environment value, collecting initial material high-temperature feedback parameters of the online test material at each information collection time, and determining a material high-temperature feedback parameter set based on partial differential equations and the initial material high-temperature feedback parameters; A parameter set recombination module for analyzing the material high-temperature feedback parameter set, calculating a data set retention factor of the material high-temperature feedback parameter set, and recombining the material high-temperature feedback parameter set according to the data set retention factor to obtain a recombined material high-temperature feedback parameter set; A sub-coefficient determination module for determining a sub-high-temperature tensile strength coefficient of the online test material corresponding to each high-temperature environment value according to each recombined material high-temperature feedback parameter set; A coefficient calculation module for calculating the high-temperature tensile strength coefficient of the online test material according to each high-temperature environment value and the sub-high-temperature tensile strength coefficient of the online test material corresponding to each high-temperature environment value.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention determines a plurality of high-temperature environment values and a plurality of information collection times corresponding to each high-temperature environment value, collects initial material high-temperature feedback parameters at each information collection time, and determines a material high-temperature feedback parameter set based on partial differential equations and the initial material high-temperature feedback parameters; calculates a data set retention factor to obtain a recombined material high-temperature feedback parameter set; determines a sub-high-temperature tensile strength coefficient corresponding to each high-temperature environment value; and calculates a high-temperature tensile strength coefficient according to the high-temperature environment value and the sub-high-temperature tensile strength coefficient, so as to determine the comprehensive tensile strength of the single-crystal superalloy in a high-temperature changing environment, ensure the test accuracy and efficiency of the comprehensive tensile strength, provide a key basis for the composition optimization and life prediction of the single-crystal superalloy, and ensure the reliability and safety of practical applications. Description of the Drawings

[0016] Upon reading the following detailed description of the preferred embodiments, various other advantages and benefits will become apparent to those of ordinary skill in the art. The accompanying drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Moreover, throughout the drawings, the same reference numerals are used to denote the same components. In the drawings: Figure 1 FIG. is a schematic flow chart of an on-line material testing method based on partial differential equations provided by an embodiment of the present invention; Figure 2 FIG. is a schematic structural diagram of an on-line material testing system based on partial differential equations provided by an embodiment of the present invention. Specific embodiments

[0017] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. Hereinafter, the present invention will be described in detail with reference to the drawings and in conjunction with the embodiments.

[0018] As Figure 1 shown, in some embodiments of the present application, this embodiment provides an on-line material testing method based on partial differential equations, including: S110: Determine a plurality of high-temperature environment values and a plurality of information acquisition times corresponding to each high-temperature environment value, collect the initial material high-temperature feedback parameters of the on-line test material at each information acquisition time, and determine a set of material high-temperature feedback parameters based on the partial differential equations and the initial material high-temperature feedback parameters; In this embodiment, the high-temperature environment value refers to a specific high-temperature value, such as 900 °C, 920 °C, 950 °C, 1000 °C, etc., which are not shown one by one here and are specifically set according to the application environment of the single-crystal superalloy.

[0019] In this embodiment, the information acquisition time is a specific acquisition time. For example, the acquisition times corresponding to 900 °C are the 10th second, the 20th second, the 30th second, the 40th second, the 50th second, the 60th second, the 70th second, and the 80th second. The number of information acquisition times is preferably 8 here and can be specifically adjusted according to the actual situation.

[0020] In this embodiment, the on-line test material is a single-crystal superalloy.

[0021] In this embodiment, the initial material high-temperature feedback parameter is the material load force, and the material load force refers to the bearing force of the single-crystal superalloy in a high-temperature environment and can be obtained in real time according to a force sensor.

[0022] In some embodiments of the present application, before determining the set of material high-temperature feedback parameters based on partial differential equations and initial material high-temperature feedback parameters, the following steps are further included: Perform anomaly detection on all initial material high-temperature feedback parameters, and delete the abnormal initial material high-temperature feedback parameters, where the anomaly detection includes duplicate acquisition detection and incorrect acquisition detection.

[0023] In this embodiment, each information acquisition moment corresponds to an initial material high-temperature feedback parameter. If there are two or more, it is determined as duplicate acquisition. Incorrect acquisition detection refers to data with obvious errors in the initial material high-temperature feedback parameters, such as the material load force being 0.

[0024] The beneficial effects of the above technical solution are: The present invention performs anomaly detection on all initial material high-temperature feedback parameters and deletes the abnormal initial material high-temperature feedback parameters, which can ensure the test accuracy of the on-line test materials.

[0025] In some embodiments of the present application, when collecting the initial material high-temperature feedback parameters of the on-line test material at each information acquisition moment and determining the set of material high-temperature feedback parameters based on partial differential equations and the initial material high-temperature feedback parameters, the following steps are included: Determine the material equivalent thermal conductivity of the on-line test material at each high-temperature environment value based on partial differential equations; Determine the material high-temperature feedback parameter corresponding to each information acquisition moment according to the material equivalent thermal conductivity and the initial material high-temperature feedback parameter; Construct the set of material high-temperature feedback parameters according to all the material high-temperature feedback parameters.

[0026] In this embodiment, the material equivalent thermal conductivity is a macroscopic parameter describing the overall heat conduction ability of single-crystal superalloys. In the actual application of single-crystal superalloys, with the increase of temperature, pores, cracks, etc. will appear. Therefore, the material equivalent thermal conductivity of single-crystal superalloys is determined.

[0027] In this embodiment, the specific determination method of the material equivalent thermal conductivity is relatively mature and will not be introduced in detail here. It can be determined specifically according to partial differential equations.

[0028] In this embodiment, a first calculation weight is configured for the initial material high-temperature feedback parameter, a second calculation weight is configured for the material equivalent thermal conductivity, the product value of the first calculation weight and the initial material high-temperature feedback parameter is calculated, the product value of the second calculation weight and the thermal conductivity of the material equivalent thermal conductivity is calculated, and the sum value of the product value and the thermal conductivity product value is used as the material high-temperature feedback parameter. Here, the first calculation weight is preferably 0.85, and the second calculation weight is preferably 0.15.

[0029] The beneficial effects of the above technical solution are as follows: In practical applications, the density, porosity, and cracks of single-crystal superalloys will change. Therefore, the present invention introduces the equivalent thermal conductivity of the material to further ensure the comprehensiveness of the determination of the material high-temperature feedback parameter set.

[0030] S120: Analyze the material high-temperature feedback parameter set, calculate the data set retention factor of the material high-temperature feedback parameter set, and reorganize the material high-temperature feedback parameter set according to the data set retention factor to obtain a reorganized material high-temperature feedback parameter set; In some embodiments of the present application, when calculating the data set retention factor of the material high-temperature feedback parameter set and reorganizing the material high-temperature feedback parameter set according to the data set retention factor to obtain a reorganized material high-temperature feedback parameter set, it includes: Determine the first material high-temperature feedback parameter corresponding to the first information acquisition time and the second material high-temperature feedback parameter corresponding to the second information acquisition time from the material high-temperature feedback parameter set; Calculate the difference between the first material high-temperature feedback parameter and the second material high-temperature feedback parameter as the data set deviation value of the material high-temperature feedback parameter set; Calculate the data set retention factor of the material high-temperature feedback parameter set according to the data set deviation value; Obtain a preset data set retention factor. If the data set retention factor is greater than or equal to the preset data set retention factor, do not reorganize the material high-temperature feedback parameter set, and use the material high-temperature feedback parameter set as the reorganized material high-temperature feedback parameter set; If the data set retention factor is less than the preset data set retention factor, sort the material high-temperature feedback parameter set in ascending order, and extract the first material high-temperature feedback parameter and the second material high-temperature feedback parameter; Calculate the material high-temperature feedback parameter difference between the first material high-temperature feedback parameter and the second material high-temperature feedback parameter. If the material high-temperature feedback parameter difference is greater than or equal to the preset difference, retain the first material high-temperature feedback parameter and the second material high-temperature feedback parameter; If the material high-temperature feedback parameter difference is less than the preset difference, delete the first material high-temperature feedback parameter and retain the second material high-temperature feedback parameter; Extract the third material high-temperature feedback parameter and the fourth material high-temperature feedback parameter, and repeat the iteration. Determine the reorganized material high-temperature feedback parameter set according to the retained material high-temperature feedback parameters.

[0031] In this embodiment, the first information acquisition time is the earliest acquisition time, and the second information acquisition time is the latest acquisition time.

[0032] In this embodiment, the preset data set retention factor is preferably 80 kN, where kN stands for kilonewton, and it can be specifically adjusted according to the actual situation.

[0033] In this embodiment, the preset difference is preferably 10 kN, and it can be specifically adjusted according to the actual situation.

[0034] In this embodiment, by repeating the above steps, the high-temperature feedback parameters of all materials can be analyzed. If there are high-temperature feedback parameters of materials that are individual and cannot be pairwise matched, they can be directly retained.

[0035] The beneficial effects of the above technical solution are as follows: The present invention calculates the data set retention factor of the high-temperature feedback parameter set of materials, and can directly determine whether to reorganize the high-temperature feedback parameter set of materials. If so, a reorganized high-temperature feedback parameter set of materials can be obtained, and some redundant data can be deleted, further ensuring the test efficiency of single-crystal superalloys.

[0036] In some embodiments of the present application, when calculating the data set retention factor of the high-temperature feedback parameter set of materials according to the data set deviation value, it includes: Calculate the data set retention factor of the high-temperature feedback parameter set of materials according to the following formula: ; where q is the data set retention factor of the high-temperature feedback parameter set of materials, w1 max is the maximum high-temperature feedback parameter of materials, w2 min is the minimum high-temperature feedback parameter of materials, e is the data set deviation value, r is the number of high-temperature feedback parameters of materials in the high-temperature feedback parameter set of materials, t i is the i-th high-temperature feedback parameter of materials in the high-temperature feedback parameter set of materials, t i+1 is the (i + 1)-th high-temperature feedback parameter of materials in the high-temperature feedback parameter set of materials.

[0037] S130: Determine the sub-high-temperature tensile strength coefficient of the on-line test material corresponding to each high-temperature environment value according to each reorganized high-temperature feedback parameter set of materials; In some embodiments of the present application, when determining the sub-high-temperature tensile strength coefficient of the on-line test material corresponding to each high-temperature environment value according to each reorganized high-temperature feedback parameter set of materials, it includes: Combine the high-temperature feedback parameters of materials in the reorganized high-temperature feedback parameter set of materials to obtain three groups of high-temperature feedback parameters of materials, where the three groups of high-temperature feedback parameters of materials include the first group of high-temperature feedback parameters of materials, the second group of high-temperature feedback parameters of materials, and the third group of high-temperature feedback parameters of materials; Perform a summation calculation on each group of high-temperature feedback parameters of materials to obtain the corresponding sum value of the high-temperature feedback parameters of materials; Determine the second-largest material high-temperature feedback parameter from the set of recombinant material high-temperature feedback parameters, and calculate the ratio of each material high-temperature feedback parameter sum value to the second-largest material high-temperature feedback parameter as the material high-temperature feedback parameter change value of the set of recombinant material high-temperature feedback parameters; Determine the sub-high-temperature tensile strength coefficient of the on-line test material based on all the material high-temperature feedback parameter change values.

[0038] In this embodiment, calculate the mean value of the parameter set corresponding to the set of recombinant material high-temperature feedback parameters. If the material high-temperature feedback parameter is greater than the mean value of the parameter set, then the corresponding material high-temperature feedback parameter is determined as the first material high-temperature feedback parameter group. If the material high-temperature feedback parameter is equal to the mean value of the parameter set, then the corresponding material high-temperature feedback parameter is determined as the second material high-temperature feedback parameter group. If the material high-temperature feedback parameter is less than the mean value of the parameter set, then the corresponding material high-temperature feedback parameter is determined as the third material high-temperature feedback parameter group.

[0039] The beneficial effects of the above technical solution are as follows: The present invention determines the sub-high-temperature tensile strength coefficient of the on-line test material based on all the material high-temperature feedback parameter change values. The present invention ensures the calculation accuracy and calculation efficiency of the sub-high-temperature tensile strength coefficient. The comprehensive performance of the single-crystal superalloy at multiple moments can be reflected by the sub-high-temperature tensile strength coefficient. In practical applications, for the same high-temperature environment value, the influence on the single-crystal superalloy at different moments is also different. Therefore, the sub-high-temperature tensile strength coefficient can characterize the comprehensive tensile strength of the single-crystal superalloy under the time gradient change.

[0040] In some embodiments of the present application, when determining the sub-high-temperature tensile strength coefficient of the on-line test material based on all the material high-temperature feedback parameter change values, it includes: Determine the sub-high-temperature tensile strength coefficient of the on-line test material according to the following formula: ; where p is the sub-high-temperature tensile strength coefficient of the on-line test material, s1 is the first material high-temperature feedback parameter change value, s2 is the second material high-temperature feedback parameter change value, s3 is the third material high-temperature feedback parameter change value, a1 is the first calculation coefficient, a2 is the second calculation coefficient, a3 is the third calculation coefficient, a1 + a2 + a3 = 1, a1 > 0, a2 > 0, a3 > 0, f1 is the variance corresponding to the first material high-temperature feedback parameter group, f2 is the variance corresponding to the second material high-temperature feedback parameter group, f3 is the variance corresponding to the third material high-temperature feedback parameter group, and f is the variance corresponding to the set of recombinant material high-temperature feedback parameters.

[0041] S140: Calculate the high-temperature tensile strength coefficient of the on-line test material according to each high-temperature environment value and the sub-high-temperature tensile strength coefficient of the on-line test material corresponding to each high-temperature environment value.

[0042] In this embodiment, according to the above steps, the sub-high-temperature tensile strength coefficient of the online test material corresponding to each high-temperature environment value can be obtained.

[0043] In some embodiments of the present application, when calculating the high-temperature tensile strength coefficient of the online test material according to each high-temperature environment value and the sub-high-temperature tensile strength coefficient of the online test material corresponding to each high-temperature environment value, it includes: Extract the first high-temperature environment value and the second high-temperature environment value, and extract the first sub-high-temperature tensile strength coefficient and the second sub-high-temperature tensile strength coefficient; Calculate the absolute value of the high-temperature environment difference between the first high-temperature environment value and the second high-temperature environment value; Extract the maximum high-temperature environment value and the minimum high-temperature environment value from all high-temperature environment values, and calculate the extreme high-temperature environment difference between the maximum high-temperature environment value and the minimum high-temperature environment value; Determine the ratio of the extreme high-temperature environment difference to the absolute value of the high-temperature environment difference as the first calculation factor; Calculate the absolute value of the difference between the first sub-high-temperature tensile strength coefficient and the second sub-high-temperature tensile strength coefficient; Extract the maximum sub-high-temperature tensile strength coefficient and the minimum sub-high-temperature tensile strength coefficient from all sub-high-temperature tensile strength coefficients, and calculate the extreme sub-high-temperature tensile strength coefficient difference between the maximum sub-high-temperature tensile strength coefficient and the minimum sub-high-temperature tensile strength coefficient; Determine the ratio of the extreme sub-high-temperature tensile strength coefficient difference to the absolute value of the sub-high-temperature tensile strength coefficient as the second calculation factor; Take the sum value of the first calculation factor and the second calculation factor as the comprehensive calculation factor; Repeat the iteration to obtain multiple comprehensive calculation factors, and calculate the high-temperature tensile strength coefficient of the online test material according to all the comprehensive calculation factors.

[0044] In this embodiment, as described above, 900 °C is the first high-temperature environment value, 920 °C is the second high-temperature environment value, 950 °C is the third high-temperature environment value, and 1000 °C is the fourth high-temperature environment value, which can be specifically determined according to the actual settings.

[0045] In this embodiment, the first sub-high-temperature tensile strength coefficient refers to the sub-high-temperature tensile strength coefficient corresponding to the first high-temperature environment value, and the second sub-high-temperature tensile strength coefficient refers to the sub-high-temperature tensile strength coefficient corresponding to the second high-temperature environment value.

[0046] In this embodiment, calculate the difference between the first high-temperature environment value and the second high-temperature environment value, and then take the absolute value to obtain the absolute value of the high-temperature environment difference.

[0047] In this embodiment, the difference between the maximum high-temperature environment value and the minimum high-temperature environment value is calculated as the extremely high-temperature environment difference.

[0048] In this embodiment, the difference between the first sub-high-temperature tensile strength coefficient and the second sub-high-temperature tensile strength coefficient is calculated, and then the absolute value is taken as the absolute value of the sub-high-temperature tensile strength coefficient difference.

[0049] In this embodiment, the difference between the maximum sub-high-temperature tensile strength coefficient and the minimum sub-high-temperature tensile strength coefficient is calculated as the extremely sub-high-temperature tensile strength coefficient difference.

[0050] In this embodiment, the third high-temperature environment value and the fourth high-temperature environment value are extracted, and the third sub-high-temperature tensile strength coefficient and the fourth sub-high-temperature tensile strength coefficient are extracted, and a second comprehensive calculation factor can be obtained. Therefore, by repeating the above steps, multiple comprehensive calculation factors can be obtained. If there are individual high-temperature environment values and corresponding sub-high-temperature tensile strength coefficients, they can be deleted and not participate in the calculation.

[0051] The beneficial effects of the above technical solutions are as follows: The present invention calculates the high-temperature tensile strength coefficient of the on-line test material according to all the comprehensive calculation factors, without manual participation, ensuring the accuracy of the calculation of the high-temperature tensile strength coefficient, eliminating subjective errors, and also ensuring the influence of the change of the high-temperature environment value on the single-crystal superalloy by calculating the difference between the high-temperature environment values. Therefore, the high-temperature tensile strength coefficient can reflect the comprehensive tensile strength of the single-crystal superalloy in multiple high-temperature environments, multiple moments, and multiple high-temperature environment changes, comprehensively evaluate the performance stability of the single-crystal superalloy in a complex high-temperature environment, provide a key basis for the composition optimization and life prediction of the single-crystal superalloy, and ensure the reliability and safety of practical applications.

[0052] In some embodiments of the present application, when calculating the high-temperature tensile strength coefficient of the on-line test material according to all the comprehensive calculation factors, it includes: Calculate the high-temperature tensile strength coefficient of the on-line test material according to the following formula: ; where g is the high-temperature tensile strength coefficient of the on-line test material, h is the number of comprehensive calculation factors, k j is the jth comprehensive calculation factor, k min is the minimum comprehensive calculation factor, k max is the maximum comprehensive calculation factor, ( - ) max is the maximum value of all ( - ).

[0053] Such as Figure 2As shown, in another preferred embodiment based on the above embodiments, this embodiment provides an on-line testing system for materials based on partial differential equations, including: A parameter set determination module, configured to determine a plurality of high-temperature environment values and a plurality of information collection times corresponding to each high-temperature environment value, collect initial material high-temperature feedback parameters of the on-line tested material at each information collection time, and determine a material high-temperature feedback parameter set based on partial differential equations and the initial material high-temperature feedback parameters; A parameter set recombination module, configured to analyze the material high-temperature feedback parameter set, calculate a data set retention factor of the material high-temperature feedback parameter set, and recombine the material high-temperature feedback parameter set according to the data set retention factor to obtain a recombined material high-temperature feedback parameter set; A sub-coefficient determination module, configured to determine a sub-high-temperature tensile strength coefficient of the on-line tested material corresponding to each high-temperature environment value according to each recombined material high-temperature feedback parameter set; A coefficient calculation module, configured to calculate a high-temperature tensile strength coefficient of the on-line tested material according to each high-temperature environment value and the sub-high-temperature tensile strength coefficient of the on-line tested material corresponding to each high-temperature environment value.

[0054] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0055] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can also be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, so that the instructions executed by the processors of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0056] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implements the functions in the processFigure 1 one process or multiple processes and / or blocks Figure 1 the functions specified in one block or multiple blocks.

[0057] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0058] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: the specific implementation manners of the present invention can still be modified or equivalently replaced, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the protection scope of the present invention.

Claims

1. An on-line testing method for materials based on partial differential equations, characterized in that, Including: Determine multiple high-temperature environment values and multiple information collection times corresponding to each high-temperature environment value, collect the initial material high-temperature feedback parameters of the online test material at each information collection time, and determine the material high-temperature feedback parameter set based on partial differential equations and the initial material high-temperature feedback parameters; Analyze the material high-temperature feedback parameter set, calculate the data set retention factor of the material high-temperature feedback parameter set, and reorganize the material high-temperature feedback parameter set according to the data set retention factor to obtain a reorganized material high-temperature feedback parameter set; Determine the sub-high-temperature tensile strength coefficient of the online test material corresponding to each high-temperature environment value according to each reorganized material high-temperature feedback parameter set; Calculate the high-temperature tensile strength coefficient of the online test material according to each high-temperature environment value and the sub-high-temperature tensile strength coefficient of the online test material corresponding to each high-temperature environment value.

2. The online testing method for materials based on partial differential equations according to claim 1, characterized in that Before determining the material high-temperature feedback parameter set based on partial differential equations and the initial material high-temperature feedback parameters, it further includes: Perform anomaly detection on all initial material high-temperature feedback parameters, and delete the abnormal initial material high-temperature feedback parameters, where the anomaly detection includes duplicate collection detection and error collection detection.

3. The online testing method for materials based on partial differential equations according to claim 1, characterized in that When collecting the initial material high-temperature feedback parameters of the online test material at each information collection time and determining the material high-temperature feedback parameter set based on partial differential equations and the initial material high-temperature feedback parameters, it includes: Determine the material equivalent thermal conductivity of the online test material under each high-temperature environment value based on partial differential equations; Determine the material high-temperature feedback parameter corresponding to each information collection time according to the material equivalent thermal conductivity and the initial material high-temperature feedback parameters; Construct the material high-temperature feedback parameter set according to all the material high-temperature feedback parameters.

4. The online testing method for materials based on partial differential equations according to claim 1, characterized in that When calculating the data set retention factor of the material high-temperature feedback parameter set and reorganizing the material high-temperature feedback parameter set according to the data set retention factor to obtain a reorganized material high-temperature feedback parameter set, it includes: Determine the first material high-temperature feedback parameter corresponding to the first information collection time and the second material high-temperature feedback parameter corresponding to the second information collection time from the material high-temperature feedback parameter set; Calculate the difference between the first material high-temperature feedback parameter and the second material high-temperature feedback parameter as the data set deviation value of the material high-temperature feedback parameter set; Calculate the data set retention factor of the material high-temperature feedback parameter set according to the data set deviation value; Obtain a preset data set retention factor. If the data set retention factor is greater than or equal to the preset data set retention factor, do not reorganize the material high-temperature feedback parameter set, and use the material high-temperature feedback parameter set as the reorganized material high-temperature feedback parameter set; If the data set retention factor is less than the preset data set retention factor, sort the material high-temperature feedback parameter set in ascending order, and extract the first material high-temperature feedback parameter and the second material high-temperature feedback parameter; Calculate the difference in high-temperature feedback parameters of materials between the high-temperature feedback parameter of the first material and that of the second material. If the difference in high-temperature feedback parameters of materials is greater than or equal to the preset difference, retain the high-temperature feedback parameter of the first material and the high-temperature feedback parameter of the second material; If the difference in high-temperature feedback parameters of materials is less than the preset difference, delete the high-temperature feedback parameter of the first material and retain the high-temperature feedback parameter of the second material; Extract the high-temperature feedback parameter of the third material and the high-temperature feedback parameter of the fourth material, repeat the iteration, and determine the set of high-temperature feedback parameters of the reconstituted material based on the retained high-temperature feedback parameters of materials.

5. The online testing method for materials based on partial differential equations according to claim 4, characterized in that When calculating the data set retention factor of the set of high-temperature feedback parameters of materials according to the deviation value of the data set, it includes: Calculate the data set retention factor of the set of high-temperature feedback parameters of materials according to the following formula: ； Among them, q is the data set retention factor of the material high-temperature feedback parameter set, w1 max is the maximum material high-temperature feedback parameter, w2 min is the minimum material high-temperature feedback parameter, e is the data set deviation value, r is the number of material high-temperature feedback parameters in the material high-temperature feedback parameter set, t i is the i-th material high-temperature feedback parameter in the material high-temperature feedback parameter set, t i+1 is the (i + 1)-th material high-temperature feedback parameter in the material high-temperature feedback parameter set.

6. The online testing method for materials based on partial differential equations according to claim 1, characterized in that, When determining the sub-high-temperature tensile strength coefficient of the on-line test material corresponding to each high-temperature environment value according to each set of high-temperature feedback parameters of the reconstituted material, it includes: Combine the high-temperature feedback parameters of materials in the set of high-temperature feedback parameters of the reconstituted material to obtain three groups of high-temperature feedback parameters of materials. Among them, the three groups of high-temperature feedback parameters of materials include the first group of high-temperature feedback parameters of materials, the second group of high-temperature feedback parameters of materials, and the third group of high-temperature feedback parameters of materials; Perform a summation calculation on each group of high-temperature feedback parameters of materials to obtain the corresponding sum value of high-temperature feedback parameters of materials; Determine the second-largest high-temperature feedback parameter of materials from the set of high-temperature feedback parameters of the reconstituted material, and calculate the ratio of each sum value of high-temperature feedback parameters of materials to the second-largest high-temperature feedback parameter of materials as the change value of high-temperature feedback parameters of materials of the set of high-temperature feedback parameters of the reconstituted material; Determine the sub-high-temperature tensile strength coefficient of the on-line test material according to all the change values of high-temperature feedback parameters of materials.

7. The on-line material testing method based on partial differential equations according to claim 6, characterized in that, When determining the sub-high-temperature tensile strength coefficient of the on-line test material according to all the change values of high-temperature feedback parameters of materials, it includes: Determine the sub-high-temperature tensile strength coefficient of the on-line test material according to the following formula: ； Where p is the sub-high-temperature tensile strength coefficient of the on-line test material, s1 is the change value of the high-temperature feedback parameter of the first material, s2 is the change value of the high-temperature feedback parameter of the second material, s3 is the change value of the high-temperature feedback parameter of the third material, a1 is the first calculation coefficient, a2 is the second calculation coefficient, a3 is the third calculation coefficient, a1 + a2 + a3 = 1, a1 > 0, a2 > 0, a3 > 0, f1 is the variance corresponding to the first group of high-temperature feedback parameters of materials, f2 is the variance corresponding to the second group of high-temperature feedback parameters of materials, f3 is the variance corresponding to the third group of high-temperature feedback parameters of materials, and f is the variance corresponding to the set of high-temperature feedback parameters of the reconstituted material.

8. The online testing method for materials based on partial differential equations according to claim 1, characterized in that When calculating the high-temperature tensile strength coefficient of the on-line test material according to each high-temperature environment value and the sub-high-temperature tensile strength coefficient of the on-line test material corresponding to each high-temperature environment value, it includes: Extract the first high-temperature environment value and the second high-temperature environment value, and extract the first sub-high-temperature tensile strength coefficient and the second sub-high-temperature tensile strength coefficient; Calculate the absolute value of the difference in high-temperature environment between the first high-temperature environment value and the second high-temperature environment value; Extract the maximum high-temperature environment value and the minimum high-temperature environment value from all high-temperature environment values, and calculate the extreme high-temperature environment difference between the maximum high-temperature environment value and the minimum high-temperature environment value; Determine the ratio of the extreme high-temperature environment difference to the absolute value of the high-temperature environment difference as the first calculation factor; Calculate the absolute value of the difference in the sub-high-temperature tensile strength coefficient between the first sub-high-temperature tensile strength coefficient and the second sub-high-temperature tensile strength coefficient; Extract the maximum sub-high-temperature tensile strength coefficient and the minimum sub-high-temperature tensile strength coefficient from all sub-high-temperature tensile strength coefficients, and calculate the extreme sub-high-temperature tensile strength coefficient difference between the maximum sub-high-temperature tensile strength coefficient and the minimum sub-high-temperature tensile strength coefficient; Determine the ratio of the extreme sub-high-temperature tensile strength coefficient difference to the absolute value of the sub-high-temperature tensile strength coefficient as the second calculation factor; Take the sum value of the first calculation factor and the second calculation factor as the comprehensive calculation factor; Repeat the iteration to obtain multiple comprehensive calculation factors, and calculate the high-temperature tensile strength coefficient of the online test material based on all the comprehensive calculation factors.

9. The on-line material testing method based on partial differential equations according to claim 8, characterized in that, When calculating the high-temperature tensile strength coefficient of the online test material based on all the comprehensive calculation factors, it includes: Calculate the high-temperature tensile strength coefficient of the online test material according to the following formula: ； Among them, g is the high-temperature tensile strength coefficient of the online test material, h is the number of comprehensive calculation factors, and k j is the j-th comprehensive calculation factor, and k min is the minimum comprehensive calculation factor, and k max is the maximum comprehensive calculation factor. ( - ) max is the maximum value of all ( - ).

10. An on-line material testing system based on partial differential equations, which is applied to an on-line material testing method based on partial differential equations according to any one of claims 1-9, characterized in that, Include: A parameter set determination module, configured to determine multiple high-temperature environment values and multiple information acquisition times corresponding to each high-temperature environment value, collect the initial material high-temperature feedback parameters of the online test material at each information acquisition time, and determine the material high-temperature feedback parameter set based on the partial differential equation and the initial material high-temperature feedback parameters; A parameter set recombination module, configured to analyze the material high-temperature feedback parameter set, calculate the data set retention factor of the material high-temperature feedback parameter set, and recombine the material high-temperature feedback parameter set according to the data set retention factor to obtain a recombined material high-temperature feedback parameter set; A sub-coefficient determination module, configured to determine the sub-high-temperature tensile strength coefficient of the online test material corresponding to each high-temperature environment value according to each recombined material high-temperature feedback parameter set; A coefficient calculation module, configured to calculate the high-temperature tensile strength coefficient of the online test material according to each high-temperature environment value and the sub-high-temperature tensile strength coefficient of the online test material corresponding to each high-temperature environment value.

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