Data Processing Method, Device, Equipment and Product for Evaluating Solder Joint Performance

Abstract

The present invention provides a data processing method, device, equipment and product for evaluating the performance of solder joints. The method includes: obtaining a first evaluation feature and a second evaluation feature of a solder joint on a welded workpiece, where the first evaluation feature refers to the diameter parameter of the solder joint, and the second evaluation feature refers to the thickness parameter of the welded workpiece at the position of the solder joint; generating a solder joint evaluation parameter according to the first evaluation feature and the second evaluation feature, and inputting the solder joint evaluation parameter into a solder joint performance evaluation model for judgment, where the solder joint performance evaluation model is obtained through training with solder joint samples; determining a solder joint performance index in the solder joint performance evaluation model that matches the solder joint evaluation parameter, and then outputting a solder joint performance evaluation result corresponding to the solder joint performance index. Through big data analysis and model training of solder joint strength tests, the present invention obtains an evaluation model capable of quickly predicting the solder joint strength, realizing accurate prediction of the solder joint strength.

Description

Technical Field

[0001] The present invention relates to the technical field of rail vehicles, and particularly to a data processing method, device, equipment and product for evaluating the performance of solder joints. Background Art

[0002] The performance of resistance spot welding joints is generally verified by destructive test methods. However, in the production of in-service vehicles, destructive tests are often not feasible for components. There is a lack of a non-destructive and rapid evaluation method for determining the performance of solder joints to monitor the quality of component solder joints in the manufacturing process in real time, and to ensure the quality stability and safety of in-service vehicle production. Summary of the Invention

[0003] The present invention provides a data processing method for evaluating the performance of solder joints, aiming to solve the defect in the prior art that the performance of solder joints cannot be determined non-destructively and rapidly. Through big data analysis and model training of solder joint strength tests, an evaluation model capable of rapidly and accurately predicting the strength of solder joints is obtained, realizing the accurate prediction of solder joint strength.

[0004] The present invention also provides a data processing device for evaluating the performance of solder joints.

[0005] The present invention further provides an electronic device.

[0006] The present invention additionally provides a computer program product.

[0007] A data processing method for evaluating the performance of solder joints according to the first aspect of the present invention includes:

[0008] Obtaining a first evaluation feature and a second evaluation feature of a solder joint on a welded workpiece, wherein the first evaluation feature refers to the diameter parameter of the solder joint, and the second evaluation feature refers to the thickness parameter of the welded workpiece at the solder joint position;

[0009] Generating a solder joint evaluation parameter according to the first evaluation feature and the second evaluation feature, and inputting the solder joint evaluation parameter into a solder joint performance evaluation model for judgment, wherein the solder joint performance evaluation model is obtained by training with solder joint samples;

[0010] Determining a solder joint performance index in the solder joint performance evaluation model that matches the solder joint evaluation parameter, and outputting a solder joint performance evaluation result corresponding to the solder joint performance index.

[0011] According to an embodiment of the present invention, in the step of obtaining a first evaluation feature and a second evaluation feature of a solder joint on a welded workpiece, wherein the first evaluation feature refers to the diameter parameter of the solder joint, and the second evaluation feature refers to the thickness parameter of the welded workpiece at the solder joint position, it specifically includes:

[0012] Obtain the instant position parameters of the solder joint, and extract M acquisition nodes corresponding to the solder joint according to the instant position parameters, where M is a positive integer greater than or equal to 2;

[0013] Obtain N instant diameters based on the M acquisition nodes, calculate the weighted average diameter of the solder joint according to the N instant diameters, determine the diameter parameter based on the N instant diameters according to the weighted average diameter, and use the diameter parameter as the first evaluation feature, where N is a positive integer greater than or equal to 2;

[0014] Obtain Q instant thicknesses based on the M acquisition nodes, calculate the weighted average thickness of the welded workpiece at the position of the solder joint according to the Q instant thicknesses, determine the thickness parameter based on the Q instant thicknesses according to the weighted average thickness, and use the thickness parameter as the second evaluation feature, where Q is a positive integer greater than or equal to 2.

[0015] Specifically, this embodiment provides an implementation manner for obtaining the first evaluation feature and the second evaluation feature of the solder joint on the welded workpiece.

[0016] According to an implementation manner of the present invention, the instant thickness is the single-layer sheet thickness of the welded workpiece at the position of the solder joint.

[0017] Specifically, this embodiment provides an implementation manner of the instant thickness.

[0018] According to an implementation manner of the present invention, in the step where the solder joint performance evaluation model is obtained by training with solder joint samples, it specifically includes:

[0019] Obtain K sample diameters and K sample thicknesses of the welded workpiece corresponding to the solder joint, and form a sample pool including the K sample diameters and the K sample thicknesses, where K is a positive integer greater than or equal to 2;

[0020] Obtain the material constants and the equivalent fracture toughness model of the welded workpiece, where the equivalent fracture toughness model is a tensile shear strength prediction model based on the fracture of the solder joint nugget interface;

[0021] Obtain one of the sample diameters and one of the sample thicknesses in the sample pool, and calculate the tensile shear strength sample value based on the material constants through the material constants and the equivalent fracture toughness model;

[0022] Repeat the above steps until the sample diameters and the sample thicknesses in the sample pool are matched to the corresponding tensile shear strength sample values, and generate the solder joint samples based on all the tensile shear strength sample values.

[0023] Specifically, this embodiment provides an implementation manner of training a solder joint performance evaluation model through solder joint samples.

[0024] According to an embodiment of the present invention, in the step of the equivalent fracture toughness model being based on the tensile shear strength prediction model under the fracture of the solder joint nugget interface, it specifically includes:

[0025] Obtain the material constants of the welded workpiece;

[0026] Obtain the solder joint edge notch during the welding process of the welded workpiece, obtain the edge notch tip stress field of the solder joint edge notch, and extract the effective stress intensity factor based on the edge notch tip stress field;

[0027] Obtain the solder joint diameter, base material thickness, and base material width corresponding to the solder joint edge notch under the fracture state of the nugget interface, and construct a geometric correction factor according to the solder joint diameter, the base material thickness, and the base material width;

[0028] Generate the tensile shear strength value corresponding to the welded workpiece according to the material constants, the effective stress intensity factor, and the geometric correction factor;

[0029] Repeat the above steps, obtain multiple tensile shear strength values, and train the equivalent fracture toughness model according to all the tensile shear strength values.

[0030] Specifically, this embodiment provides an implementation manner of training an equivalent fracture toughness model.

[0031] According to an embodiment of the present invention, in the step of obtaining the solder joint edge notch during the welding process of the welded workpiece, obtaining the edge notch tip stress field of the solder joint edge notch, and extracting the effective stress intensity factor based on the edge notch tip stress field, it specifically includes:

[0032] Obtain all the crack parameters of the edge notch tip stress field, and determine the type I stress intensity factor and the type II stress intensity factor according to all the crack parameters;

[0033] Determine the effective stress intensity factor according to the type I stress intensity factor and the type II stress intensity factor.

[0034] Specifically, this embodiment provides an implementation manner of extracting the effective stress intensity factor.

[0035] According to an embodiment of the present invention, in the step of determining the solder joint performance index that matches the solder joint evaluation parameter in the solder joint performance evaluation model, and then outputting the solder joint performance evaluation result corresponding to the solder joint performance index, it specifically further includes:

[0036] Determine the solder joint performance index in the solder joint performance evaluation model that matches the solder joint evaluation parameter;

[0037] Extract the tensile shear strength value corresponding to the welding performance index, and use the tensile shear strength value as the solder joint performance evaluation result.

[0038] Specifically, this embodiment provides an implementation manner for outputting the solder joint performance evaluation result corresponding to the solder joint performance index.

[0039] A data processing device for evaluating the performance of solder joints according to the second aspect of the present invention includes: an acquisition module, an input module, and an output module;

[0040] The acquisition module is used to acquire the first evaluation feature and the second evaluation feature of the solder joint on the welded workpiece, wherein the first evaluation feature refers to the diameter parameter of the solder joint, and the second evaluation feature refers to the thickness parameter of the welded workpiece at the solder joint position;

[0041] The input module is used to generate a solder joint evaluation parameter according to the first evaluation feature and the second evaluation feature, and input the solder joint evaluation parameter into the solder joint performance evaluation model for judgment, wherein the solder joint performance evaluation model is obtained by training with solder joint samples;

[0042] The output module is used to determine the solder joint performance index in the solder joint performance evaluation model that matches the solder joint evaluation parameter, and then output the solder joint performance evaluation result corresponding to the solder joint performance index.

[0043] An electronic device according to the third aspect of the present invention includes: a memory and a processor;

[0044] The memory and the processor communicate with each other through a bus;

[0045] The memory stores computer instructions that can run on the processor;

[0046] When the processor calls the computer instructions, it can execute the above-mentioned data processing method for evaluating the performance of solder joints.

[0047] A computer program product according to the fourth aspect of the present invention includes a non-transitory machine-readable medium storing instructions, and the instructions cause at least one programmable processor to execute the steps of the above-mentioned data processing method for evaluating the performance of solder joints when executed by at least one programmable processor.

[0048] One or more of the above technical solutions in the present invention have at least one of the following technical effects: A data processing method, device, equipment and product for evaluating the performance of solder joints provided by the present invention obtain an evaluation model capable of quickly and accurately predicting the strength of solder joints through big data analysis and model training of solder joint strength tests, realizing accurate prediction of solder joint strength.

[0049] Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0051] Figure 1 is a schematic flowchart of a data processing method for evaluating the performance of solder joints provided by the present invention;

[0052] Figure 2 is a schematic structural diagram of a data processing device for evaluating the performance of solder joints provided by the present invention;

[0053] Figure 3 is a schematic structural diagram of an electronic device provided by the present invention.

[0054] Reference numerals:

[0055] 100, acquisition module; 200, input module; 300, output module; 810, processor; 820, communication interface; 830, memory; 840, communication bus. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0056] The present invention will be specifically described below in conjunction with the accompanying drawings of the specification. The specific operation methods in the method embodiments can also be applied to the device embodiments or system embodiments. In the description of the present invention, unless otherwise specified, "at least one" includes one or more. "Multiple" means two or more. For example, at least one of A, B, and C includes: A alone, B alone, A and B existing simultaneously, A and C existing simultaneously, B and C existing simultaneously, and A, B, and C existing simultaneously. In the present invention, " / " means or. For example, A / B can represent A or B; "and / or" herein is only a description of the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone.

[0057] The present invention will be specifically described below in conjunction with specific embodiments.

[0058] In some specific embodiments of the present invention, as Figure 1 shown, the present solution provides a data processing method for evaluating the performance of solder joints, including:

[0059] Obtain the first evaluation feature and the second evaluation feature of the solder joint on the welded workpiece, wherein the first evaluation feature refers to the diameter parameter of the solder joint, and the second evaluation feature refers to the thickness parameter of the welded workpiece at the solder joint position;

[0060] Generate a solder joint evaluation parameter according to the first evaluation feature and the second evaluation feature, and input the solder joint evaluation parameter into the solder joint performance evaluation model for judgment, wherein the solder joint performance evaluation model is obtained by training with solder joint samples;

[0061] Determine the solder joint performance index in the solder joint performance evaluation model that matches the solder joint evaluation parameter, and then output the solder joint performance evaluation result corresponding to the solder joint performance index.

[0062] Specifically, the present invention provides a data processing method for evaluating the performance of solder joints, which is used to solve the defect in the prior art that the performance of solder joints cannot be determined non-destructively and quickly. Through big data analysis and model training of solder joint strength tests, an evaluation model that can quickly and accurately predict the strength of solder joints is obtained, realizing the accurate prediction of the strength of solder joints.

[0063] In a possible implementation manner, by inputting the plate thickness and solder joint diameter of the workpiece to be welded, the corresponding solder joint performance evaluation result can be obtained, such as strength evaluation result, toughness evaluation result, etc., realizing the accurate prediction of solder joint performance evaluation.

[0064] In some possible embodiments of the present invention, in the step of obtaining the first evaluation feature and the second evaluation feature of the solder joint on the welded workpiece, wherein the first evaluation feature refers to the diameter parameter of the solder joint, and the second evaluation feature refers to the thickness parameter of the welded workpiece at the solder joint position, it specifically includes:

[0065] Obtain the instant position parameter of the solder joint, and extract M acquisition nodes corresponding to the solder joint according to the instant position parameter, where M is a positive integer greater than or equal to 2;

[0066] Obtain N instant diameters based on the M acquisition nodes, calculate the weighted average diameter of the solder joint according to the N instant diameters, determine the diameter parameter based on the N instant diameters according to the weighted average diameter, and use the diameter parameter as the first evaluation feature, where N is a positive integer greater than or equal to 2;

[0067] Obtain Q instantaneous thicknesses based on M acquisition nodes, calculate the weighted average thickness of the welded workpiece at the solder joint position according to the Q instantaneous thicknesses, determine the thickness parameter based on the Q instantaneous thicknesses according to the weighted average thickness, and use the thickness parameter as the second evaluation feature, where Q is a positive integer greater than or equal to 2.

[0068] Specifically, this embodiment provides an implementation manner for obtaining the first evaluation feature and the second evaluation feature of the solder joint on the welded workpiece. By obtaining the instantaneous position parameters of the solder joint and extracting multiple acquisition nodes according to the instantaneous position parameters, the weighted average diameter and weighted average thickness of the solder joint can be obtained through the acquisition nodes, and then the corresponding first evaluation feature and second evaluation feature can be obtained, making the evaluation result closer to the actual situation of the solder joint and correcting the systematic error.

[0069] In a possible implementation manner, when extracting the instantaneous diameter of the solder joint through the acquisition nodes, two acquisition nodes relatively far from the edge of the solder joint nugget are selected to extract an instantaneous diameter of the solder joint. Further, for the weighted assignment of the instantaneous diameter of the solder joint, the diameter acquisition area can be divided in advance according to the nugget shape of the solder joint, at least two types of acquisition areas are set according to the regularity degree of the nugget shape, different numbers of acquisition nodes are set in the areas with different shape regularities, and then the corresponding weight values are assigned according to the number of acquisition nodes in each area, so as to calculate the weighted average diameter.

[0070] In a possible implementation manner, when extracting the instantaneous thickness of the solder joint through the acquisition nodes, multiple acquisition nodes are partitioned in advance to form multiple acquisition areas, the thickness of the solder joint in the acquisition area is extracted, and the average thickness is calculated based on the multiple acquisition areas. Further, the division of the acquisition areas can be repeated multiple times, and the average thickness is collected after each division is completed to form a large data collection of multiple average thicknesses of the solder joint under different divisions of the acquisition areas. Then, according to the number of acquisition nodes divided in each acquisition area, weighted assignment is performed, and finally the weighted average thickness is calculated.

[0071] In some possible embodiments of the present invention, the instantaneous thickness is the single-layer sheet thickness of the welded workpiece at the solder joint position.

[0072] Specifically, this embodiment provides an implementation manner of the instantaneous thickness. The single-layer sheet thickness is more helpful for estimating the performance parameters of the solder joint and avoiding the problem of large noise in the estimation of the solder joint performance parameters caused by the interaction between multiple layers of sheets.

[0073] In some possible embodiments of the present invention, in the step of training the solder joint performance evaluation model through solder joint samples, it specifically includes:

[0074] Obtain K sample diameters and K sample thicknesses of the corresponding solder joints of the welded workpiece, and form a sample pool including the K sample diameters and the K sample thicknesses, where K is a positive integer greater than or equal to 2;

[0075] Obtain the material constants and the equivalent fracture toughness model of the welded workpiece, where the equivalent fracture toughness model is a tensile shear strength prediction model based on the fracture of the solder joint nugget interface;

[0076] Obtain one sample diameter and one sample thickness from the sample pool, and calculate the tensile shear strength sample value based on the material constants through the material constants and the equivalent fracture toughness model;

[0077] Repeat the above steps until the sample diameters and sample thicknesses in the sample pool are matched to the corresponding tensile shear strength sample values, and generate solder joint samples based on all the tensile shear strength sample values.

[0078] Specifically, this embodiment provides an implementation manner of training a solder joint performance evaluation model through solder joint samples. By obtaining the sample diameters and sample thicknesses of the welded workpiece and forming a sample pool, and matching the corresponding ones through the sample pool, a solder joint sample including all the tensile shear strength sample values is realized.

[0079] Furthermore, train the solder joint performance evaluation mode through the solder joint samples, and finally realize obtaining the solder joint performance index of the solder joint to be evaluated by inputting the first evaluation feature pointing to the solder joint diameter parameter and the second evaluation feature pointing to the solder joint position thickness parameter, and then derive the corresponding solder joint performance evaluation result through the solder joint performance index.

[0080] In some possible embodiments of the present invention, in the step where the equivalent fracture toughness model is a tensile shear strength prediction model based on the fracture of the solder joint nugget interface, it specifically includes:

[0081] Obtain the material constants of the welded workpiece;

[0082] Obtain the solder joint edge notch during the welding process of the welded workpiece, obtain the edge notch tip stress field of the solder joint edge notch, and extract the effective stress intensity factor based on the edge notch tip stress field;

[0083] Obtain the solder joint diameter, base material thickness, and base material width corresponding to the solder joint edge notch under the condition of the nugget interface fracture state, and construct a geometric correction factor according to the solder joint diameter, base material thickness, and base material width;

[0084] Generate the tensile shear strength value corresponding to the welded workpiece according to the material constants, the effective stress intensity factor, and the geometric correction factor;

[0085] Repeat the above steps, obtain multiple tensile shear strength values, and train the equivalent fracture toughness model according to all the tensile shear strength values.

[0086] Specifically, this embodiment provides an implementation manner for training an equivalent fracture toughness model. By providing a way to train the equivalent fracture toughness model, the establishment of a tensile shear strength prediction model is achieved.

[0087] In a possible implementation manner, for the calculation of the tensile shear strength value, it is carried out based on the following formula:

[0088]

[0089] In the formula, F s is the tensile shear strength value;

[0090] K eff is the equivalent fracture toughness;

[0091] d is the solder joint diameter corresponding to the notch at the solder joint edge;

[0092] t is the base material thickness corresponding to the notch at the solder joint edge;

[0093] G is the geometric correction factor;

[0094] β' is a function of material constants.

[0095] In a possible implementation manner, the expression of β' as a function of material constants is as follows:

[0096]

[0097] In the formula, β' is a function of material constants;

[0098] β is a material constant.

[0099] In some possible embodiments of the present invention, in the steps of obtaining the notch at the solder joint edge during the welding process of the welded workpiece, obtaining the stress field at the notch tip of the notch at the solder joint edge, and extracting the effective stress intensity factor based on the stress field at the notch tip of the notch, it specifically includes:

[0100] Obtaining all crack parameters of the stress field at the notch tip, and determining the type I stress intensity factor and the type II stress intensity factor according to all crack parameters;

[0101] Determining the effective stress intensity factor according to the type I stress intensity factor and the type II stress intensity factor.

[0102] Specifically, this embodiment provides an implementation manner for extracting the effective stress intensity factor.

[0103] In a possible implementation, during the interface failure process, cracks always propagate along a specific plane, i.e., the weld joint interface. Then, the total energy release rate of each type of crack should satisfy the superposition principle during the crack propagation process or at the critical state where the crack is about to propagate. At this time, it is necessary to consider the mode I stress intensity factor, mode II stress intensity factor, and the mixed loading of mode I and mode II.

[0104] In a possible implementation, cracks are generally classified into opening mode (mode I), sliding mode (mode II), and tearing mode (mode III) according to their mechanical characteristics. In the calculation of the stress field at the tip of the notch at the edge of the solder joint for this embodiment, the mode I stress intensity factor, mode II stress intensity factor, and the mixed loading factor of mode I and mode II are considered.

[0105] In a possible implementation, the calculation of the effective stress intensity factor is carried out based on the following formula:

[0106]

[0107] In the formula, K eff is the equivalent fracture toughness;

[0108] K Ⅰ is the maximum value of the mode I stress intensity factor;

[0109] K II is the maximum value of the mode II stress intensity factor;

[0110] β is the material constant;

[0111] G is the geometric correction factor;

[0112] d is the solder joint diameter;

[0113] t is the thickness of the base material;

[0114] w is the width of the base material.

[0115] In a possible implementation, the calculation of the mode I stress intensity factor is carried out using the following formula:

[0116]

[0117] In the formula, K Ⅰ is the maximum value of the mode I stress intensity factor;

[0118] F' s is the force component transmitted by the solder joint, equal to the load applied at the clamping end;

[0119] d is the solder joint diameter;

[0120] t is the thickness of the base material.

[0121] In a possible implementation, for the calculation of the mode II stress intensity factor, the following formula is used:

[0122]

[0123] Where K II is the maximum value of the mode II stress intensity factor;

[0124] F' s is the force component transmitted by the solder joint, equal to the load applied at the clamping end;

[0125] d is the diameter of the solder joint;

[0126] t is the thickness of the base material.

[0127] In some possible embodiments of the present invention, in the step of determining the solder joint performance index matching the solder joint evaluation parameter in the solder joint performance evaluation model and outputting the solder joint performance evaluation result corresponding to the solder joint performance index, it specifically further includes:

[0128] Determine the solder joint performance index matching the solder joint evaluation parameter in the solder joint performance evaluation model;

[0129] Extract the tensile shear strength value corresponding to the welding performance index and use the tensile shear strength value as the solder joint performance evaluation result.

[0130] Specifically, this embodiment provides an implementation manner of outputting the solder joint performance evaluation result corresponding to the solder joint performance index.

[0131] In a possible implementation, the equivalent fracture toughness K eff of the weld zone material is estimated through a set of solder joint sample data, and the obtained K eff is 1309. In addition, β' is related to the weights of the mode I and mode II stress intensity factors in the mixed loading and can be inversely deduced from the results of actual spot welding failure tests. The calculated β' in the present invention is 11.9, and the solder joint performance evaluation model of the failure load is finally obtained as:

[0132]

[0133] Where F s is the tensile shear strength value;

[0134] d is the solder joint diameter corresponding to the notch at the solder joint edge;

[0135] t is the number of base material thicknesses corresponding to the notch at the solder joint edge.

[0136] In some specific implementation schemes of the present invention, such as Figure 2As shown in the figure, this solution provides a data processing device for evaluating the performance of solder joints, including: an acquisition module 100, an input module 200, and an output module 300;

[0137] The acquisition module 100 is used to acquire the first evaluation feature and the second evaluation feature of the solder joints on the welded workpiece. Among them, the first evaluation feature refers to the diameter parameter of the solder joint, and the second evaluation feature refers to the thickness parameter of the welded workpiece at the solder joint position.

[0138] The input module 200 is used to generate solder joint evaluation parameters according to the first evaluation feature and the second evaluation feature, and input the solder joint evaluation parameters into the solder joint performance evaluation model for judgment. Among them, the solder joint performance evaluation model is obtained by training with solder joint samples.

[0139] The output module 300 is used to determine the solder joint performance index that matches the solder joint evaluation parameter in the solder joint performance evaluation model, and then output the solder joint performance evaluation result corresponding to the solder joint performance index.

[0140] Figure 3 An example of the physical structure diagram of an electronic device is shown as Figure 3 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840. Among them, the processor 810, the communication interface 820, and the memory 830 complete mutual communication through the communication bus 840. The processor 810 can call the logical instructions in the memory 830 to execute a data processing method for evaluating the performance of solder joints. The method includes:

[0141] Acquire the first evaluation feature and the second evaluation feature of the solder joints on the welded workpiece. Among them, the first evaluation feature refers to the diameter parameter of the solder joint, and the second evaluation feature refers to the thickness parameter of the welded workpiece at the solder joint position.

[0142] Generate solder joint evaluation parameters according to the first evaluation feature and the second evaluation feature, and input the solder joint evaluation parameters into the solder joint performance evaluation model for judgment. Among them, the solder joint performance evaluation model is obtained by training with solder joint samples.

[0143] Determine the solder joint performance index that matches the solder joint evaluation parameter in the solder joint performance evaluation model, and then output the solder joint performance evaluation result corresponding to the solder joint performance index.

[0144] It should be noted that the electronic device in this embodiment can be a server, a PC, or other devices when specifically implemented, as long as its structure includes Figure 3A processor 810, a communication interface 820, a memory 830, and a communication bus 840 are shown. Among them, the processor 810, the communication interface 820, and the memory 830 communicate with each other through the communication bus 840, and the processor 810 can call the logical instructions in the memory 830 to execute the above method. The specific implementation form of the electronic device is not limited in this embodiment.

[0145] Among them, the server can be a single server or a server group. The server group can be centralized or distributed (for example, the server can be a distributed system). In some embodiments, the server can be local or remote relative to the terminal. For example, the server can access information stored in the user terminal, database, or any combination thereof via a network. As another example, the server can be directly connected to at least one of the user terminal and the database to access the information and / or data stored therein. In some embodiments, the server can be implemented on a cloud platform; by way of example only, the cloud platform can include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, etc., or any combination thereof. In some embodiments, the server and the user terminal can be implemented on an electronic device having one or more components in the embodiments of the present invention.

[0146] Further, the network can be used for the exchange of information and / or data. In some embodiments, one or more components in the interaction scenario (e.g., servers, user terminals, and databases) can send information and / or data to other components. In some embodiments, the network can be any type of wired or wireless network, or a combination thereof. By way of example only, the network can include a wired network, a wireless network, an optical fiber network, a telecommunications network, an intranet, the Internet, a Local Area Network (LAN), a Wide Area Network (WAN), a Wireless Local Area Network (WLAN), a Metropolitan Area Network (MAN), a Wide Area Network (WAN), a Public Switched Telephone Network (PSTN), a Bluetooth network, a ZigBee network, or a Near Field Communication (NFC) network, etc., or any combination thereof. In some embodiments, the network can include one or more network access points. For example, the network can include wired or wireless network access points, such as base stations and / or network switching nodes, through which one or more components of the interaction scenario can connect to the network to exchange data and / or information.

[0147] In addition, when the logical instructions in the above-mentioned memory 830 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The foregoing storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs, etc., which can store program codes.

[0148] In a possible implementation manner, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is configured to execute the data processing method for evaluating the performance of solder joints provided in the above-mentioned embodiments.

[0149] In a possible implementation manner, an embodiment of the present invention further provides a computer program product. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the methods provided in the above method embodiments.

[0150] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0151] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiments.

[0152] 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 foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments or equivalently replace some of the technical features. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A data processing method for evaluating the performance of solder joints, characterized in that, it includes: Obtain the first evaluation feature and the second evaluation feature of the solder joint on the welded workpiece, wherein the first evaluation feature refers to the diameter parameter of the solder joint, and the second evaluation feature refers to the thickness parameter of the welded workpiece at the solder joint position; Generate a solder joint evaluation parameter according to the first evaluation feature and the second evaluation feature, and input the solder joint evaluation parameter into a solder joint performance evaluation model for judgment, wherein the solder joint performance evaluation model is obtained through training with solder joint samples; Determine the solder joint performance index in the solder joint performance evaluation model that matches the solder joint evaluation parameter, and then output the solder joint performance evaluation result corresponding to the solder joint performance index; In the step where the solder joint performance evaluation model is obtained through training with solder joint samples, it specifically includes: Obtain K sample diameters and K sample thicknesses of the welded workpiece corresponding to the solder joint, and form a sample pool including the K sample diameters and the K sample thicknesses, where K is a positive integer greater than or equal to 2; Obtain the material constant and the equivalent fracture toughness model of the welded workpiece, wherein the equivalent fracture toughness model is a tensile shear strength prediction model based on the fracture of the solder joint nugget interface; Obtain one of the sample diameters and one of the sample thicknesses in the sample pool, and calculate the tensile shear strength sample value based on the material constant through the material constant and the equivalent fracture toughness model; Repeat the above steps until the sample diameters and the sample thicknesses in the sample pool are matched to the corresponding tensile shear strength sample values, and generate the solder joint samples based on all the tensile shear strength sample values; In the step where the equivalent fracture toughness model is a tensile shear strength prediction model based on the fracture of the solder joint nugget interface, it specifically includes: Obtain the material constant of the welded workpiece; Obtain the solder joint edge notch during the welding process of the welded workpiece, obtain the edge notch tip stress field of the solder joint edge notch, and extract the effective stress intensity factor based on the edge notch tip stress field; Obtain the solder joint diameter, base material thickness, and base material width corresponding to the solder joint edge notch under the condition of nugget interface fracture, and construct a geometric correction factor according to the solder joint diameter, the base material thickness, and the base material width; Generate the tensile shear strength value corresponding to the welded workpiece according to the material constant, the effective stress intensity factor, and the geometric correction factor; Repeat the above steps to obtain multiple tensile shear strength values, and train the equivalent fracture toughness model according to all the tensile shear strength values.

2. The data processing method for evaluating the performance of solder joints according to claim 1, characterized in that, in the step of obtaining the first evaluation feature and the second evaluation feature of the solder joint on the welded workpiece, wherein the first evaluation feature refers to the diameter parameter of the solder joint, and the second evaluation feature refers to the thickness parameter of the welded workpiece at the solder joint position, it specifically includes: Obtain the instant position parameters of the solder joint, and extract M acquisition nodes corresponding to the solder joint according to the instant position parameters, where M is a positive integer greater than or equal to 2; Obtain N instant diameters based on the M acquisition nodes, calculate the weighted average diameter of the solder joint according to the N instant diameters, determine the diameter parameter based on the N instant diameters according to the weighted average diameter, and use the diameter parameter as the first evaluation feature, where N is a positive integer greater than or equal to 2; Obtain Q instant thicknesses based on the M acquisition nodes, calculate the weighted average thickness of the welded workpiece at the position of the solder joint according to the Q instant thicknesses, determine the thickness parameter based on the Q instant thicknesses according to the weighted average thickness, and use the thickness parameter as the second evaluation feature, where Q is a positive integer greater than or equal to 2.

3. A data processing method for evaluating the performance of a solder joint according to claim 2, characterized in that, The instant thickness is the thickness of a single-layer sheet of the welded workpiece at the position of the solder joint.

4. A data processing method for evaluating the performance of a solder joint according to claim 1, characterized in that, In the step of obtaining the solder joint edge notch during the welding process of the welded workpiece, obtaining the edge notch tip stress field of the solder joint edge notch, and extracting the effective stress intensity factor based on the edge notch tip stress field, specifically includes: Obtain all crack parameters of the edge notch tip stress field, and determine the type I stress intensity factor and type II stress intensity factor according to all the crack parameters; Determine the effective stress intensity factor according to the type I stress intensity factor and the type II stress intensity factor.

5. A data processing method for evaluating the performance of a solder joint according to any one of claims 1 to 4, characterized in that, In the step of determining the solder joint performance index matching the solder joint evaluation parameter in the solder joint performance evaluation model, and then outputting the solder joint performance evaluation result corresponding to the solder joint performance index, specifically further includes: Determine the solder joint performance index matching the solder joint evaluation parameter in the solder joint performance evaluation model; Extract the tensile shear strength value corresponding to the welding performance index, and use the tensile shear strength value as the solder joint performance evaluation result.

6. A data processing device for evaluating the performance of a solder joint, characterized in that, comprises: An acquisition module, an input module and an output module; The acquisition module is used to acquire the first evaluation feature and the second evaluation feature of the solder joint on the welded workpiece, wherein the first evaluation feature refers to the diameter parameter of the solder joint, and the second evaluation feature refers to the thickness parameter of the welded workpiece at the position of the solder joint; The input module is used to generate a solder joint evaluation parameter according to the first evaluation feature and the second evaluation feature, and input the solder joint evaluation parameter into the solder joint performance evaluation model for judgment, wherein the solder joint performance evaluation model is obtained by training with solder joint samples; The output module is configured to determine a solder joint performance index in the solder joint performance evaluation model that matches the solder joint evaluation parameter, and then output a solder joint performance evaluation result corresponding to the solder joint performance index; In the step of training the solder joint performance evaluation model with solder joint samples, it specifically includes: Obtain K sample diameters and K sample thicknesses of the solder joints corresponding to the welded workpiece, and form a sample pool including the K sample diameters and the K sample thicknesses, where K is a positive integer greater than or equal to 2; Obtain the material constants and the equivalent fracture toughness model of the welded workpiece, where the equivalent fracture toughness model is a tensile shear strength prediction model based on the fracture of the solder joint nugget interface; Obtain one of the sample diameters and one of the sample thicknesses in the sample pool, and calculate a tensile shear strength sample value based on the material constants through the material constants and the equivalent fracture toughness model; Repeat the above steps until the sample diameters and the sample thicknesses in the sample pool are matched to the corresponding tensile shear strength sample values, and generate the solder joint samples based on all the tensile shear strength sample values; In the step that the equivalent fracture toughness model is a tensile shear strength prediction model based on the fracture of the solder joint nugget interface, it specifically includes: Obtain the material constants of the welded workpiece; Obtain the solder joint edge notch during the welding process of the welded workpiece, obtain the edge notch tip stress field of the solder joint edge notch, and extract the effective stress intensity factor based on the edge notch tip stress field; Obtain the solder joint diameter, base material thickness, and base material width corresponding to the solder joint edge notch under the condition of nugget interface fracture, and construct a geometric correction factor according to the solder joint diameter, the base material thickness, and the base material width; Generate a tensile shear strength value corresponding to the welded workpiece according to the material constants, the effective stress intensity factor, and the geometric correction factor; Repeat the above steps to obtain multiple tensile shear strength values, and train the equivalent fracture toughness model according to all the tensile shear strength values.

7. An electronic device, Characterized in that, It includes: A memory and a processor; The memory and the processor communicate with each other through a bus; The memory stores computer instructions that can run on the processor; When the processor calls the computer instructions, it can execute the data processing method for evaluating the performance of solder joints according to any one of claims 1 to 5 above.

8. A computer program product, which includes a non-transitory machine-readable medium storing instructions, Characterized in that, When the instructions are executed by at least one programmable processor, the at least one programmable processor executes the steps of the data processing method for evaluating the performance of solder joints according to any one of claims 1 to 5 above.

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