An on-line testing method and system for materials based on partial differential equations

Abstract

The present invention relates to the technical field of material testing, and discloses an on-line material testing method and system based on partial differential equations. The method includes: 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 at each information collection time, and determining a set of material high-temperature feedback parameters based on partial differential equations and the initial material high-temperature feedback parameters; calculating a data set retention factor to obtain a recombined set of material high-temperature feedback parameters; determining a sub-high-temperature tensile strength coefficient corresponding to each high-temperature environment value; and calculating a high-temperature tensile strength coefficient according to the high-temperature environment value and the sub-high-temperature tensile strength coefficient. The comprehensive tensile strength of a single-crystal superalloy under a high-temperature changing environment can be determined, the testing accuracy and efficiency of the comprehensive tensile strength can be ensured, key basis for the composition optimization and life prediction of the single-crystal superalloy can be provided, and the reliability and safety of practical applications can be 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 actual 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, unable to characterize the comprehensive tensile strength of single crystal superalloys under the change of time gradient, and 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 proposes 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 actual applications.

[0005] The present invention proposes an on-line testing method for materials based on partial differential equations, including:

[0006] Determine a plurality of high-temperature environment values and a plurality of information collection moments corresponding to each high-temperature environment value, collect the initial material high-temperature feedback parameters of the on-line tested material at each information collection moment, and determine a set of material high-temperature feedback parameters based on the partial differential equation and the initial material high-temperature feedback parameters;

[0007] Analyze the set of material high-temperature feedback parameters, calculate the data set retention factor of the set of material high-temperature feedback parameters, and reorganize 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;

[0008] Determine the sub-high-temperature tensile strength coefficient of the on-line tested material corresponding to each high-temperature environment value according to each reorganized set of material high-temperature feedback parameters;

[0009] Calculate the 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.

[0010] 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:

[0011] Perform anomaly detection on all 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.

[0012] 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:

[0013] Determine the equivalent thermal conductivity of the on-line test material at each high-temperature environment value based on the partial differential equation;

[0014] Determine the high-temperature feedback parameter of the material corresponding to each information collection moment according to the equivalent thermal conductivity of the material and the high-temperature feedback parameter of the initial material;

[0015] Construct the set of high-temperature feedback parameters of the material according to all the high-temperature feedback parameters of the material.

[0016] 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:

[0017] 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;

[0018] 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;

[0019] Calculate the data set retention factor of the set of high-temperature feedback parameters of the material according to the data set deviation value;

[0020] 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;

[0021] 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;

[0022] Calculating a material high temperature feedback parameter difference between the first material high temperature feedback parameter and the second material high temperature feedback parameter, and if the material high temperature feedback parameter difference is greater than or equal to a preset difference, retaining the first material high temperature feedback parameter and the second material high temperature feedback parameter;

[0023] If the difference between the high-temperature feedback parameters of the materials is less than a preset difference, deleting the high-temperature feedback parameters of the first material and retaining the high-temperature feedback parameters of the second material;

[0024] Extract the third material high temperature feedback parameter and the fourth material high temperature feedback parameter, repeat the iteration, and determine the recombined material high temperature feedback parameter set based on the retained material high temperature feedback parameters.

[0025] Furthermore, when calculating the data set retention factor of the material high-temperature feedback parameter set according to the data set deviation value, it includes:

[0026] The data set retention factor of the high temperature feedback parameter set of the material is calculated according to the following formula:

[0027] ;

[0028] 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 ith material high temperature feedback parameter in the material high temperature feedback parameter set, t i+1 It is the i+1th material high temperature feedback parameter in the material high temperature feedback parameter set.

[0029] Furthermore, when determining the sub-high temperature tensile strength coefficient of the online test material corresponding to each high temperature environment value according to each recombinant material high temperature feedback parameter set, it includes:

[0030] Combining the material high temperature feedback parameters in the recombined material high temperature feedback parameter set to obtain three material high temperature feedback parameter groups, wherein the three material high temperature feedback parameter groups include a first material high temperature feedback parameter group, a second material high temperature feedback parameter group, and a third material high temperature feedback parameter group;

[0031] Perform sum calculation on each material high temperature feedback parameter group to obtain the corresponding material high temperature feedback parameter and value;

[0032] determining a second maximum material high temperature feedback parameter from the reorganized material high temperature feedback parameter set, and calculating a ratio of the sum of each material high temperature feedback parameter to the second maximum material high temperature feedback parameter as a material high temperature feedback parameter change value of the reorganized material high temperature feedback parameter set;

[0033] Determine the sub-high-temperature tensile strength coefficient of the on-line test material according to the change values of all material high-temperature feedback parameters.

[0034] Further, when determining the sub-high-temperature tensile strength coefficient of the on-line test material according to the change values of all material high-temperature feedback parameters, it includes:

[0035] Determine the sub-high-temperature tensile strength coefficient of the on-line test material according to the following formula:

[0036] ;

[0037] where p is the sub-high-temperature tensile strength coefficient of the on-line test material, s1 is the change value of the first material high-temperature feedback parameter, s2 is the change value of the second material high-temperature feedback parameter, s3 is the change value of the third material 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, f'1 is the variance corresponding to the first material high-temperature feedback parameter group, f'2 is the variance corresponding to the second material high-temperature feedback parameter group, f'3 is the variance corresponding to the third material high-temperature feedback parameter group, and f is the variance corresponding to the recombined material high-temperature feedback parameter set.

[0038] Further, 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:

[0039] 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;

[0040] Calculate the absolute value of the high-temperature environment difference between the first high-temperature environment value and the second high-temperature environment value;

[0041] 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;

[0042] 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;

[0043] 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;

[0044] Extract the maximum sub-high-temperature tensile strength coefficient and the minimum sub-high-temperature tensile strength coefficient from all the sub-high-temperature tensile strength coefficients, and calculate the difference in the extreme sub-high-temperature tensile strength coefficients between the maximum sub-high-temperature tensile strength coefficient and the minimum sub-high-temperature tensile strength coefficient;

[0045] Determine the ratio of the difference in the extreme sub-high-temperature tensile strength coefficients to the absolute value of the sub-high-temperature tensile strength coefficient as the second calculation factor;

[0046] Take the sum of the first calculation factor and the second calculation factor as the comprehensive calculation factor;

[0047] Repeat the iteration to obtain multiple comprehensive calculation factors, and calculate the high-temperature tensile strength coefficient of the on-line test material based on all the comprehensive calculation factors.

[0048] Furthermore, when calculating the high-temperature tensile strength coefficient of the on-line test material based on all the comprehensive calculation factors, it includes:

[0049] Calculate the high-temperature tensile strength coefficient of the on-line test material according to the following formula:

[0050] ;

[0051] 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 ( - ).

[0052] On the other hand, the present application also provides a material on-line test system based on partial differential equations, including:

[0053] 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 on-line 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;

[0054] 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;

[0055] The sub - coefficient determination module is used to determine 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 recombinant material;

[0056] The coefficient calculation module is used to 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.

[0057] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0058] The present invention determines multiple high - temperature environment values and multiple information collection times corresponding to each high - temperature environment value, collects the initial material high - temperature feedback parameters at each information collection time, determines the set of material high - temperature feedback parameters based on partial differential equations and the initial material high - temperature feedback parameters; calculates the data set retention factor to obtain the set of recombinant material high - temperature feedback parameters; determines the sub - high - temperature tensile strength coefficient corresponding to each high - temperature environment value; and calculates the 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

[0059] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The 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 represent the same components. In the drawings:

[0060] Figure 1 is a schematic flow chart of the on - line material test method based on partial differential equations provided by an embodiment of the present invention;

[0061] Figure 2 is a schematic structural diagram of the on - line material test system based on partial differential equations provided by an embodiment of the present invention. Detailed Embodiments

[0062] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the 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. The present invention will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0063] As Figure 1 shown, in some embodiments of the present application, this embodiment provides an on-line testing method for materials based on partial differential equations, including:

[0064] S110: Determine a plurality of high-temperature environment values and a plurality of information collection times corresponding to each high-temperature environment value, collect the initial material high-temperature feedback parameters of the on-line tested material at each information collection time, and determine the material high-temperature feedback parameter set based on the partial differential equation and the initial material high-temperature feedback parameters;

[0065] 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.

[0066] In this embodiment, the information collection time is a specific collection time. For example, the collection 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. Here, the number of information collection times is preferably 8, and can also be adjusted according to the actual situation.

[0067] In this embodiment, the on-line tested material is a single-crystal superalloy.

[0068] In this embodiment, the initial material high-temperature feedback parameter is the material load force. 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.

[0069] In some embodiments of the present application, before determining the material high-temperature feedback parameter set based on the partial differential equation and the initial material high-temperature feedback parameters, it further includes:

[0070] Perform anomaly detection on all the initial material high-temperature feedback parameters, and delete the abnormal initial material high-temperature feedback parameters, where the anomaly detection includes repeated collection detection and error collection detection.

[0071] In this embodiment, each information collection time corresponds to an initial material high-temperature feedback parameter. If there are two or more, it is determined as repeated collection. The error collection detection refers to data with obvious errors in the initial material high-temperature feedback parameters, such as the material load force being 0.

[0072] The beneficial effect of the above technical solution is that the present invention performs anomaly detection on all the 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 tested material.

[0073] In some embodiments of the present application, when collecting the initial material high-temperature feedback parameters of the online test material at each information collection moment and determining the material high-temperature feedback parameter set based on the partial differential equation and the initial material high-temperature feedback parameters, it includes:

[0074] Determine the material equivalent thermal conductivity of the online test material at each high-temperature environment value based on the partial differential equation;

[0075] Determine the material high-temperature feedback parameter corresponding to each information collection moment according to the material equivalent thermal conductivity and the initial material high-temperature feedback parameters;

[0076] Construct the material high-temperature feedback parameter set according to all the material high-temperature feedback parameters.

[0077] 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.

[0078] 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 the partial differential equation.

[0079] In this embodiment, a first calculation weight is configured for the initial material high-temperature feedback parameters, a second calculation weight is configured for the material equivalent thermal conductivity, the parameter product value of the first calculation weight and the initial material high-temperature feedback parameters is calculated, the thermal conductivity product value of the second calculation weight and the material equivalent thermal conductivity is calculated, and the sum value of the parameter 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.

[0080] The beneficial effect of the above technical solution is that in actual applications, the density, pores, and cracks of single-crystal superalloys will change. Therefore, the present invention introduces the material equivalent thermal conductivity, which can further ensure the comprehensiveness of the determination of the material high-temperature feedback parameter set.

[0081] 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;

[0082] 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:

[0083] Determine the first material high-temperature feedback parameter corresponding to the first information collection moment and the second material high-temperature feedback parameter corresponding to the second information collection moment from the material high-temperature feedback parameter set;

[0084] 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;

[0085] Calculate the data set retention factor of the material high-temperature feedback parameter set according to the data set deviation value;

[0086] Obtain the 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;

[0087] 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;

[0088] 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;

[0089] 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;

[0090] 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.

[0091] In this embodiment, the first information collection moment is the moment with the earliest collection time, and the second information collection moment is the moment with the latest collection time.

[0092] In this embodiment, the preset data set retention factor is preferably 80 kN, where kN is kilonewton, and it can be adjusted according to the actual situation.

[0093] In this embodiment, the preset difference is preferably 10 kN, and it can be adjusted according to the actual situation.

[0094] In this embodiment, by repeating the above steps, all material high-temperature feedback parameters can be analyzed. If there are individual material high-temperature feedback parameters that cannot be paired in pairs, they can be directly retained.

[0095] The beneficial effects of the above technical solution are as follows: The dataset retention factor of the high-temperature feedback parameter set of the computational material of the present invention can directly determine whether to reorganize the high-temperature feedback parameter set of the material. If so, a reorganized high-temperature feedback parameter set of the material can be obtained, and some redundant data can be deleted, further ensuring the test efficiency of single-crystal superalloys.

[0096] In some embodiments of the present application, when calculating the dataset retention factor of the high-temperature feedback parameter set of the material according to the dataset deviation value, it includes:

[0097] Calculate the dataset retention factor of the high-temperature feedback parameter set of the material according to the following formula:

[0098] ;

[0099] where q is the dataset 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 dataset 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.

[0100] 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 the material;

[0101] 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 the material, it includes:

[0102] Combine the high-temperature feedback parameters in the reorganized high-temperature feedback parameter set of the material to obtain three high-temperature feedback parameter groups, where the three high-temperature feedback parameter groups include a first high-temperature feedback parameter group, a second high-temperature feedback parameter group, and a third high-temperature feedback parameter group;

[0103] Perform a summation calculation on each high-temperature feedback parameter group to obtain the corresponding high-temperature feedback parameter sum value;

[0104] Determine the second-largest high-temperature feedback parameter from the reorganized high-temperature feedback parameter set of the material, and calculate the ratio of each high-temperature feedback parameter sum value to the second-largest high-temperature feedback parameter as the high-temperature feedback parameter change value of the reorganized high-temperature feedback parameter set of the material;

[0105] Determine the sub-high-temperature tensile strength coefficient of the on-line test material according to all the changed values of the high-temperature feedback parameters of the material.

[0106] In this embodiment, calculate the mean value of the parameter set corresponding to the high-temperature feedback parameter set of the recombinant material. If the high-temperature feedback parameter of the material is greater than the mean value of the parameter set, then determine the corresponding high-temperature feedback parameter of the material as the first group of high-temperature feedback parameters of the material. If the high-temperature feedback parameter of the material is equal to the mean value of the parameter set, then determine the corresponding high-temperature feedback parameter of the material as the second group of high-temperature feedback parameters of the material. If the high-temperature feedback parameter of the material is less than the mean value of the parameter set, then determine the corresponding high-temperature feedback parameter of the material as the third group of high-temperature feedback parameters of the material.

[0107] 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 according to all the changed values of the high-temperature feedback parameters of the material, which ensures the calculation accuracy and calculation efficiency of the sub-high-temperature tensile strength coefficient. The sub-high-temperature tensile strength coefficient can reflect the comprehensive performance of the single-crystal superalloy at multiple moments. 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.

[0108] In some embodiments of the present application, when determining the sub-high-temperature tensile strength coefficient of the on-line test material according to all the changed values of the high-temperature feedback parameters of the material, it includes:

[0109] Determine the sub-high-temperature tensile strength coefficient of the on-line test material according to the following formula:

[0110] ;

[0111] where p is the sub-high-temperature tensile strength coefficient of the on-line test material, s1 is the changed value of the first high-temperature feedback parameter of the material, s2 is the changed value of the second high-temperature feedback parameter of the material, s3 is the changed value of the third high-temperature feedback parameter of the 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 the material, f2 is the variance corresponding to the second group of high-temperature feedback parameters of the material, f3 is the variance corresponding to the third group of high-temperature feedback parameters of the material, and f is the variance corresponding to the high-temperature feedback parameter set of the recombinant material.

[0112] 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.

[0113] In this embodiment, according to the above steps, the sub-high-temperature tensile strength coefficient of the on-line test material corresponding to each high-temperature environment value can be obtained.

[0114] 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:

[0115] 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;

[0116] Calculate the absolute value of the high-temperature environment difference between the first high-temperature environment value and the second high-temperature environment value;

[0117] Extract the maximum high-temperature environment value and the minimum high-temperature environment value from all the 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;

[0118] 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;

[0119] Calculate the absolute value of the sub-high-temperature tensile strength coefficient difference between the first sub-high-temperature tensile strength coefficient and the second sub-high-temperature tensile strength coefficient;

[0120] Extract the maximum sub-high-temperature tensile strength coefficient and the minimum sub-high-temperature tensile strength coefficient from all the 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;

[0121] 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;

[0122] Take the sum value of the first calculation factor and the second calculation factor as the comprehensive calculation factor;

[0123] 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.

[0124] 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.

[0125] 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.

[0126] In this embodiment, the difference between the first high-temperature environment value and the second high-temperature environment value is calculated, and then the absolute value is taken to obtain the absolute value of the high-temperature environment difference.

[0127] In this embodiment, the difference between the maximum high-temperature environment value and the minimum high-temperature environment value is calculated as the extreme high-temperature environment difference.

[0128] 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.

[0129] 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 extreme sub-high-temperature tensile strength coefficient difference.

[0130] 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, so that 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 do not participate in the calculation.

[0131] 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, which ensures the calculation accuracy of the high-temperature tensile strength coefficient, eliminates subjective errors, and also ensures 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, at multiple moments, and with multiple high-temperature environment changes, comprehensively evaluate the performance stability of the single-crystal superalloy in complex high-temperature environments, 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.

[0132] 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:

[0133] Calculate the high-temperature tensile strength coefficient of the on-line test material according to the following formula:

[0134] ;

[0135] 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 for all ( - ).

[0136] As Figure 2 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:

[0137] 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 the partial differential equation and the initial material high-temperature feedback parameters;

[0138] 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;

[0139] 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;

[0140] 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.

[0141] 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.

[0142] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowcharts and / or block diagrams can be implemented by computer program instructions, and the combination of processes 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 processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate for implementing in the process Figure 1 one process or multiple processes and / or blocksFigure 1 means for the functions specified in one or more boxes.

[0143] These computer program instructions can also be stored in a computer-readable memory capable of guiding a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured article including an instruction device, and the instruction device implements the functions specified in one Figure 1 process or multiple processes and / or boxes Figure 1 means for the functions specified in one or more boxes.

[0144] 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 one Figure 1 process or multiple processes and / or boxes Figure 1 means for the functions specified in one or more boxes.

[0145] 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 without departing from the spirit and scope of the present invention shall 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 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 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; 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; When collecting the initial material high-temperature feedback parameters of the online test material at each information acquisition time and determining the material high-temperature feedback parameter set based on the partial differential equation 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 the partial differential equation; Determine the material high-temperature feedback parameter corresponding to each information acquisition 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; 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 the 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 the 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 a plurality of comprehensive calculation factors, and calculate the high-temperature tensile strength coefficient of the online test material according to all the comprehensive calculation factors.

2. The on-line 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 the partial differential equation 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 acquisition detection and error acquisition detection.

3. The online testing method for materials based on partial differential equations according to claim 1, characterized in that, When calculating the dataset retention factor of the material high-temperature feedback parameter set and reorganizing the material high-temperature feedback parameter set according to the dataset 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 dataset deviation value of the material high-temperature feedback parameter set; Calculate the dataset retention factor of the material high-temperature feedback parameter set according to the dataset deviation value; Obtain a preset dataset retention factor. If the dataset retention factor is greater than or equal to the preset dataset 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 dataset retention factor is less than the preset dataset 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 to determine the reorganized material high-temperature feedback parameter set according to the retained material high-temperature feedback parameters.

4. The online material testing method based on partial differential equations according to claim 3, characterized in that When calculating the dataset retention factor of the material high-temperature feedback parameter set according to the dataset deviation value, it includes: Calculate the dataset retention factor of the material high-temperature feedback parameter set according to the following formula: ； where 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.

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

6. The online testing method for materials based on partial differential equations according to claim 5, characterized in that, When determining the sub-high-temperature tensile strength coefficient of the on-line test material according to the change values of all material high-temperature feedback parameters, 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 on-line test material, s1 is the change value of the first material high-temperature feedback parameter, s2 is the change value of the second material high-temperature feedback parameter, s3 is the change value of the third material 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 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 recombined material high-temperature feedback parameter set.

7. 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 all comprehensive calculation factors, it includes: Calculate the high-temperature tensile strength coefficient of the on-line 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, which is the maximum value of all .

8. 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 1-7, characterized in that, It includes: A parameter set determination module, configured to 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 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 on-line 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 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.

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