A method for optimizing ultra-low temperature high-toughness welding processes based on fracture surface information

Abstract

The application belongs to the technical field of welding procedure qualification of super-low-temperature high-toughness welds, in particular to a super-low-temperature high-toughness welding procedure optimization method based on fracture information, comprising the following steps: step one, performing a super-low-temperature fracture toughness test on samples 1 to n to obtain the fracture information of each sample, i.e. dimple area a1 and inclusion quantity s1. The super-low-temperature high-toughness welding procedure optimization method based on fracture information can maximize the use of existing test data information, establish a one-to-one mapping relationship between the physical information of the fracture and the super-low-temperature fracture toughness, and take the principal surface as the evaluation index for optimizing different welding procedures.

Description

Technical Field

[0001] This invention relates to the field of welding process evaluation technology for ultra-low temperature high-toughness welds, and particularly to a method for optimizing ultra-low temperature high-toughness welding processes based on fracture information. Background Technology

[0002] Most metallic materials undergo brittle fracture at extremely low temperatures, a sudden and highly dangerous fracture mode without any warning signs. The fracture of welds, particularly non-uniform materials, is even more complex at low temperatures due to the unavoidable inclusions, hot cracks, and even defects that can occur during the welding process. Therefore, the toughness requirements for steels used at extremely low temperatures are stringent; a certain reserve of toughness is essential for safety. However, evaluating the fracture toughness of welds at extremely low temperatures is complex, time-consuming, and expensive. Therefore, a simple and feasible alternative method is needed to assess the fracture toughness of steels used at extremely low temperatures.

[0003] Welding process parameters directly affect the cryogenic fracture toughness of the weld. Different welding heat inputs influence the grain size and shape at the weld location. Because atomic movement becomes difficult at cryogenic temperatures, dislocation movement is suppressed, and plastic deformation of the weld becomes even more challenging. Therefore, a new method for optimizing the welding process is needed to quickly and accurately obtain the optimal welding process parameters for achieving the best cryogenic fracture toughness. However, currently, there is no method for optimizing the welding process of such high-toughness cryogenic welds based on the correlation with fracture surface physics information. Summary of the Invention

[0004] Based on existing technical problems, this invention proposes an optimal method for ultra-low temperature high-toughness welding process based on fracture information.

[0005] The present invention proposes a method for optimizing ultra-low temperature high-toughness welding processes based on fracture surface information, comprising the following steps:

[0006] Step 1: Perform ultra-low temperature fracture toughness tests on samples 1 to n to obtain the fracture information of each sample, namely the dimple area a1 and the number of inclusions s1.

[0007] Step 2: Find the fracture surface information and cryogenic fracture toughness K for each sample. IC i Mapping relationship between Determine the break information a i and s i The welding process parameters used g i .

[0008] Wherein, the welding process parameter g i Including voltage U i Current I iWelding speed v i and maximum heat input Q i .

[0009] Step 3: Plot the relationship between the obtained weld fracture information and the cryogenic fracture toughness to obtain K. IC The principal surface of F(A, S) allows for the convenient acquisition of the optimal welding process parameter g corresponding to the highest toughness. j .

[0010] Step 4: Data digitization of weld fracture information. Data digitization of weld fracture information for samples 1 to n, including the dimple area a. i and the number of inclusions at the fracture surface s i The digitized physical information is expressed as follows:

[0011] a=a i (i=1,2,…n), s=s i (i=1,2,…n).

[0012] Step 5: Select the required value for the cryogenic fracture toughness of the weld in the project as the threshold K. IC T , threshold K IC T With K IC Compare the values ​​in K, if K IC The value in is greater than or equal to the threshold K IC T , will K IC The corresponding welding process parameters are selected as the optimization dataset. If K IC The value in is less than the threshold K IC T , will K IC The corresponding welding process parameters were determined to be unqualified welding process.

[0013] Preferably, the fracture toughness K IC The dimple area A and the number of inclusions S are vectors, and the statistics of the dimple area and the number of inclusions in the weld fracture are achieved through image recognition technology.

[0014] The above technical solution uses image recognition technology based on physical information fusion to determine the physical information of the fracture surface, namely the dimple area A and the number of inclusions S.

[0015] Preferably, the image recognition of the dimple area of ​​the weld fracture surface uses the grayscale of the weld fracture SEM image to distinguish the dimples, calculates the percentage of the dimple area in the entire image, and then quantitatively characterizes the distribution of dimples based on the percentage. The number of inclusions is identified by single-point marking.

[0016] Through the above technical solution, the dimple and inclusion images are converted into binary images recognizable by a computer for processing.

[0017] Preferably, the optimization of the welding process parameters is screened by ultra-low temperature fracture toughness. If the welding process parameter g i corresponding ultra-low temperature fracture toughness K IC i is less than the threshold K IC T , it is determined that this welding process is unqualified. If the welding process parameter g i corresponding ultra-low temperature fracture toughness K IC i is greater than or equal to the threshold K IC T , this welding process is taken as the preferred process 1.

[0018] Through the above technical solution, the dimple and inclusion images are converted into binary images recognizable by a computer for processing.

[0019] Preferably, according to the relationship between the ultra-low temperature fracture toughness K IC i and the threshold K IC T , the preferred processes 2 to m are found in turn, where m < n. According to the maximum value K IC j of the ultra-low temperature fracture toughness corresponding to the preferred processes 1 to m, the optimal welding process g j is obtained.

[0020] Through the above technical solution, the dimple and inclusion images are converted into binary images recognizable by a computer for processing.

[0021] Preferably, the fracture information of the weld fracture toughness is attempted to be reflected by the fracture information of the tensile specimen. The ultra-low temperature fracture toughness of the weld can be evaluated through the tensile specimen, greatly simplifying the evaluation of the ultra-low temperature fracture toughness of the weld.

[0022] Through the above technical solution, the physical information of the ultra-low temperature tensile fracture is associated with the fracture toughness. It is attempted to obtain available fracture physical information through the tensile test, and then the ultra-low temperature fracture toughness data can be obtained according to the established mapping relationship

[0023] Preferably, the fracture information of the weld fracture toughness is on the fracture of the tensile specimen in the same temperature environment. By comparing the fracture of the tensile specimen with the fracture of the fracture toughness specimen, a method for reflecting the ultra-low temperature fracture toughness through the fracture information of the tensile specimen is determined.

[0024] ​Through the above technical solution, an approximate correlation formula K between tensile fracture surface information and fracture toughness fracture surface information at the same temperature can be established. IC T ≈K IC .

[0025] Preferably, the fracture toughness derived from the fracture surface information of the weld tensile specimen has a mapping relationship K with the fracture surface information of the fracture toughness specimen. IC T ≈K IC If the difference between the two is large, the fracture information of the tensile specimen needs to be re-photographed, statistically analyzed, and calculated until the difference between the two data is within ±5%.

[0026] The above technical solutions enable the selection of optimal welding processes for ultra-low temperature and high toughness based on fracture information.

[0027] Preferably, the weld tensile test specimen needs to have the same welding process parameters as the corresponding fracture toughness test specimen to avoid deviations in fracture information caused by differences in welding processes.

[0028] The above technical solution enables the use of tensile specimen data with the same welding process parameters to evaluate fracture toughness, achieving the goal of multiple uses for one test.

[0029] Preferably, the weld seam is determined based on the principal curved surface to find the maximum fracture toughness value K. IC k The corresponding welding process parameters g k That is, voltage U k Current I k Welding speed v k and maximum heat input Q k ;

[0030] Repeatability tests were performed, and new specimens were welded according to the optimal welding process. Cryogenic fracture toughness and cryogenic tensile tests were conducted to determine the mapping relationship K between the fracture surface information and fracture toughness obtained from the cryogenic fracture toughness test. IC 1 =F1(A1, S1) and the mapping relationship between fracture surface information and fracture toughness obtained from ultra-low temperature tensile tests K IC 2 If F2(A2, S2) is consistent, it means that the fracture surface of the tensile test can reflect the fracture surface of the fracture test. If it is inconsistent, repeat the tensile test until it is consistent.

[0031] The above technical solution allows for a one-to-one comparison between the mapping relationship obtained from tensile data and the mapping relationship obtained from fracture toughness tests, thereby verifying the reliability of the tensile data.

[0032] The beneficial effects of this invention are as follows:

[0033] 1. The optimal method for welding process optimization at ultra-low temperature and high toughness can make the most of the information in the existing test data, establish a one-to-one mapping relationship between the physical information of the fracture surface and the ultra-low temperature fracture toughness, and use the master surface as the evaluation index for optimizing different welding processes.

[0034] 2. By establishing a database for optimizing ultra-low temperature welding processes, a data-physical-information fusion solution was provided to achieve intelligent optimization of ultra-low temperature welding processes. This solved the problems of long optimization times and expensive experiments in ultra-low temperature welding processes. It also provided crucial visual data support for establishing optimal welding processes for ultra-low temperature high-toughness welds. Attached Figure Description

[0035] Figure 1 This is a schematic diagram of an optimal welding process for ultra-low temperature high toughness based on fracture information proposed in this invention.

[0036] Figure 2 This is a master surface diagram of an optimal welding process based on fracture information for ultra-low temperature high toughness proposed in this invention. Detailed Implementation

[0037] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0038] Reference Figures 1-2 A method for optimizing ultra-low temperature high-toughness welding processes based on fracture surface information includes the following steps:

[0039] Step 1: Perform ultra-low temperature fracture toughness tests on samples 1 to n to obtain the fracture information of each sample, namely the dimple area a1 and the number of inclusions s1.

[0040] Step 2: Find the fracture surface information and cryogenic fracture toughness K for each sample. IC i Mapping relationship between Determine the break information a i and s i The welding process parameters used g i ;

[0041] Among them, welding process parameter g i Including voltage U i Current I i Welding speed v i and maximum heat input Q i ;

[0042] Step 3: Plot the relationship between the obtained weld fracture information and the cryogenic fracture toughness to obtain K. IC The principal surface of F(A, S) allows for the convenient acquisition of the optimal welding process parameter g corresponding to the highest toughness. j (U) j I j v j Q j );

[0043] Step 4: Data digitization of weld fracture information. Data digitization of weld fracture information for samples 1 to n, including the dimple area a. i and the number of inclusions at the fracture surface s i The digitized physical information is expressed as follows:

[0044] a=a i (i=1,2,…n), s=s i (i=1,2,…n);

[0045] Step 5: Select the required value for the cryogenic fracture toughness of the weld in the project as the threshold K. IC T , threshold K IC T With K IC Compare the values ​​in K, if K IC The value in is greater than or equal to the threshold K IC T , will K IC The corresponding welding process parameters are selected as the optimization dataset. If K IC The value in is less than the threshold K IC T , will K IC The corresponding welding process parameters were determined to be unqualified welding process.

[0046] fracture toughness K IC The dimple area A and the number of inclusions S are vectors, and the statistics of the dimple area and the number of inclusions in the weld fracture are achieved through image recognition technology.

[0047] Image recognition of the dimple area of ​​weld fracture surface uses grayscale values ​​from weld fracture SEM images to distinguish the area, calculates the percentage of the dimple area in the entire image, and then quantitatively characterizes the distribution of dimples based on the percentage. The number of inclusions is identified by single-point marking.

[0048] The optimization of welding process parameters is achieved through screening based on cryogenic fracture toughness. If the welding process parameter g... i Corresponding ultra-low temperature fracture toughness K IC i Less than threshold K ICT It is determined that this welding process is unqualified. If the welding process parameter g i The corresponding ultra-low temperature fracture toughness K IC i is greater than or equal to the threshold value K IC T , this welding process is taken as the preferred process 1.

[0049] According to the ultra-low temperature fracture toughness K IC i and the threshold value K IC T , the preferred processes 2 to m are found in sequence, where m < n. According to the maximum value K IC j of the ultra-low temperature fracture toughness corresponding to the preferred processes 1 to m, the optimal welding process g j is obtained.

[0050] Attempt to reflect the fracture surface information of the weld fracture toughness through the fracture surface information of the tensile specimen. The ultra-low temperature fracture toughness of the weld can be evaluated through the tensile specimen.

[0051] The fracture surface information of the weld fracture toughness is on the fracture surface of the tensile specimen in the same temperature environment. By comparing the fracture surface of the tensile specimen with the fracture surface of the fracture toughness specimen, a method for reflecting the ultra-low temperature fracture toughness through the fracture surface information of the tensile specimen is determined.

[0052] There is a mapping relationship K IC T ≈K IC between the fracture toughness obtained from the fracture surface information of the weld tensile specimen and the fracture surface information of the fracture toughness specimen. If the difference between the two is large, the fracture surface information of the tensile specimen needs to be re-shot, statistically analyzed, and calculated until the data difference between the two is within plus or minus 5%.

[0053] The weld tensile specimen needs to have the same welding process parameters as the corresponding fracture toughness specimen to avoid deviations in fracture surface information caused by differences in welding processes.

[0054] The weld finds the maximum fracture toughness value K IC k corresponding to the welding process parameters g k , that is, the voltage U k , the current I k , the welding speed v k and the maximum heat input Q k ;

[0055] And perform a repeatability test. Weld new specimens according to the optimal welding process, and conduct ultra-low temperature fracture toughness and ultra-low temperature tensile specimens respectively to judge the mapping relationship K between the fracture surface information obtained from the ultra-low temperature fracture toughness test and the fracture toughness.IC 1 =F1(A1, S1) and the mapping relationship between fracture surface information and fracture toughness obtained from ultra-low temperature tensile tests K IC 2 If F2(A2, S2) is consistent, it means that the fracture surface of the tensile test can reflect the fracture surface of the fracture test. If it is inconsistent, repeat the tensile test until it is consistent.

[0056] By establishing a database for optimizing cryogenic welding processes, a data-physical-information fusion solution is provided for achieving intelligent optimization of cryogenic welding processes. This solves the problems of time-consuming and expensive experiments in cryogenic welding process optimization. It also provides crucial visual data support for establishing optimal welding processes for cryogenic high-toughness welds.

[0057] The optimal method for welding processes with high toughness at ultra-low temperatures can make the most of existing experimental data, establish a one-to-one mapping relationship between the physical information of the fracture surface and the fracture toughness at ultra-low temperatures, and use the master surface as an evaluation index for optimizing different welding processes.

[0058] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for a super low temperature high toughness welding process based on fracture information, preferably characterized by, It comprises the following steps: Step one, for sample 1 to n, ultra-low temperature fracture toughness test is carried out, and the fracture information of each sample, i.e. dimple area a1 and inclusion quantity s1, is obtained; Step two, find out the mapping relationship between the fracture information and the ultra-low temperature fracture toughness K IC i of each sample respectively , determine the welding process parameters g i adopted by the fracture information a i and s i ​ wherein the welding process parameters g i comprise a voltage U i , a current I i , a welding speed v i and a maximum heat input Q i ; Step three, the relationship between the obtained weld fracture information and the ultra-low temperature fracture toughness is drawn to obtain K IC =F(A, S) main surface, through the main surface, the optimal welding process parameter g corresponding to the highest toughness can be obtained j ; the fracture toughness K IC The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The fracture toughness K The The image recognition of the weld fracture dimple area adopts the gray scale of the weld fracture SEM image to distinguish, calculates the percentage of the area of the dimple in the whole image, thereby quantitatively characterizes the distribution of the dimple according to the percentage, and the inclusion quantity adopts the single point marking mode to recognize; Step four, weld fracture information data, the weld fracture information data of samples 1 to n, including fracture dimple area a i And the number of inclusions s i The physical information after data is expressed as: a = a i (i = 1, 2,... n), s = s i (i = 1, 2,... n); Step 5: Select the required value for the cryogenic fracture toughness of the weld in the project as the threshold K. IC T , threshold K IC T With K IC Compare the values ​​in K, if K IC The value in is greater than or equal to the threshold K IC T , will K IC The corresponding welding process parameters are selected as the optimization dataset. If K IC The value in is less than the threshold K IC T , will K IC The corresponding welding process parameters are judged to be unqualified welding process; The optimization of the welding process parameters is screened by the ultra-low temperature fracture toughness, if the welding process parameters g i The corresponding ultra-low temperature fracture toughness K IC i Less than the threshold value K IC T , judge this welding process is unqualified, if the welding process parameters g i The corresponding ultra-low temperature fracture toughness K IC i Greater than or equal to the threshold value K IC T This welding process is used as the preferred process 1; According to the super low temperature fracture toughness K IC i and the threshold value K IC T , the preferred processes 2 to m are found in turn, where m < n, according to the maximum value K IC j of the super low temperature fracture toughness in the preferred processes 1 to m, and the optimal welding process g j is obtained. The fracture information of the weld fracture toughness is reflected by the fracture information of the tensile sample, and the weld ultra-low temperature fracture toughness can be evaluated by the tensile sample; The fracture information of the weld fracture toughness is reflected by the fracture information of the tensile sample, and the weld ultra-low temperature fracture toughness can be evaluated by the tensile sample; The fracture toughness derived from the fracture information of the weld tensile specimen has a mapping relationship K with the fracture toughness derived from the fracture information of the fracture toughness specimen IC T ≈K IC If the difference is large, the fracture information of the tensile specimen needs to be rephotographed, counted and calculated until the difference between the two data is within plus or minus 5%.

2. A process for ultra-low temperature high toughness welding based on fracture information according to claim 1, characterized in that: The weld tensile sample needs to have the same welding process parameters as the corresponding fracture toughness sample, so as to avoid the deviation of the fracture information caused by the difference of the welding process.

3. A process for ultra-low temperature high toughness welding based on fracture information according to claim 2, characterized in that: The weld seam finds the maximum fracture toughness value K according to the main curvature IC k The corresponding welding process parameters g k namely the voltage U k , the current I k , the welding speed v k and the maximum heat input Q k ; And the repeatability test, according to the optimal welding process welding new sample, respectively, ultra-low temperature fracture toughness and ultra-low temperature tensile sample, judge ultra-low temperature fracture toughness test get fracture information and the mapping relationship K of fracture toughness IC 1 =F1(A1, S1) and ultra-low temperature tensile test get fracture information and the mapping relationship K of fracture toughness IC 2 =F2(A2, S2) is consistent, if consistent, then the tensile test fracture can reflect the fracture test fracture, if not consistent, then repeat the tensile test until consistent.

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