A method, apparatus, medium, and program product for determining stability of a welding process

Abstract

The purpose of the present application is to provide a method, device, medium and program product for determining the stability of a welding process, the method comprising: obtaining a welding data set in a welding process; determining a plurality of welding data subsets and their corresponding data proportion information according to the welding data set and a set data interval; determining the number of welding data subsets corresponding to each data proportion segmentation information in the plurality of data proportion segmentation information according to the plurality of data proportion segmentation information and their corresponding data proportion information; determining the trajectory repetition rate information corresponding to the welding data set according to the plurality of data proportion segmentation information and the corresponding welding data subset number information; and determining the stability of the welding process according to the trajectory repetition rate information, thereby simplifying the calculation process, improving the calculation efficiency, and avoiding the influence of local welding instability on the calculation when the data volume is too large.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of welding, in particular to a technology for determining stability of a welding process. BACKGROUND

[0002] Arc welding is the most commonly used metal connection method. When dozens or even hundreds of welding machines work simultaneously, it is necessary to collect and detect current and voltage signals in real time during the welding process, analyze data characteristics, and ensure the welding quality. The analysis of the stability of the welding process is one of the important indicators for evaluating the welding quality. Generally, the main idea for determining the stability of the welding process is as follows: the voltage-current phase diagram of the welding process is drawn as a black and white picture, the path of current and voltage in the picture is black, and the picture is white. The essence of the black and white picture is a two-dimensional array, the value of the white part is 1, and the value of the black part is 0; the above two-dimensional data is inverted, that is, 1 in the two-dimensional array is set to 0, and 0 is set to 1; the sum of the overall two-dimensional array is calculated (that is, the sum of all 1s), and then divided by the number of total elements of the two-dimensional array to obtain the proportion of the voltage-current curve path in the total picture area; the repetition rate index of the voltage-current phase diagram trajectory is calculated using the proportion data, the smaller the proportion, the higher the trajectory repetition rate, the larger the proportion, the more scattered the trajectory, and the lower the trajectory repetition rate; the trajectory repetition rate index of different welding data is calculated, and the welding data with a larger trajectory repetition rate is more stable than the welding data with a smaller trajectory repetition rate. SUMMARY

[0003] An object of the present application is to provide a method, device, medium and program product for determining the stability of a welding process.

[0004] According to one aspect of the present application, a method for determining the stability of a welding process is provided, which comprises:

[0005] obtaining a welding data set in a welding process;

[0006] determining a plurality of welding data subsets and data proportion information corresponding to each welding data subset in the plurality of welding data subsets according to the welding data set and a set data interval;

[0007] determining welding data subset quantity information corresponding to each data proportion segmentation information in the plurality of data proportion segmentation information according to the plurality of data proportion segmentation information and the data proportion information corresponding to each welding data subset, wherein the data proportion information of the welding data subset corresponding to each data proportion segmentation information is greater than the data proportion segmentation information;

[0008] determine the trajectory repetition rate information corresponding to the welding data set according to the plurality of data proportion segmentation information and the welding data subset quantity information corresponding to each data proportion segmentation information in the plurality of data proportion segmentation information;

[0009] determine the welding process stability according to the trajectory repetition rate information.

[0010] According to an aspect of the present application, a computer device for determining welding process stability is provided, comprising a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any method described above.

[0011] According to an aspect of the present application, a computer readable storage medium having a computer program stored thereon is provided, wherein the computer program is executed by a processor to implement the steps of any method described above.

[0012] According to an aspect of the present application, a computer program product is provided, comprising a computer program, wherein the computer program is executed by a processor to implement the steps of any method described above.

[0013] According to an aspect of the present application, a device for determining welding process stability is provided, comprising:

[0014] a first module configured to acquire a welding data set in a welding process;

[0015] a second module configured to determine a plurality of welding data subsets and data proportion information corresponding to each welding data subset in the plurality of welding data subsets according to the welding data set and a set data interval;

[0016] a third module configured to determine welding data subset quantity information corresponding to each data proportion segmentation information in a plurality of data proportion segmentation information according to the plurality of data proportion segmentation information and the data proportion information corresponding to each welding data subset, wherein the data proportion information of the welding data subset corresponding to each data proportion segmentation information is greater than the data proportion segmentation information;

[0017] a fourth module configured to determine the trajectory repetition rate information corresponding to the welding data set according to the plurality of data proportion segmentation information and the welding data subset quantity information corresponding to each data proportion segmentation information in the plurality of data proportion segmentation information;

[0018] a fifth module configured to determine the welding process stability according to the trajectory repetition rate information

[0019] Compared with the prior art, the welding data set in the welding process is acquired, a plurality of welding data subsets and data proportion information corresponding to each welding data subset in the plurality of welding data subsets are determined according to the welding data set and a set data interval, welding data subset quantity information corresponding to each data proportion segmentation information in the plurality of data proportion segmentation information is determined according to the plurality of data proportion segmentation information and the data proportion information corresponding to each welding data subset, trajectory repetition rate information corresponding to the welding data set is determined according to the plurality of data proportion segmentation information and the welding data subset quantity information corresponding to each data proportion segmentation information in the plurality of data proportion segmentation information, and then the welding process stability is determined, so that, compared with the prior art in which the proportion of the U-I curve path to the total picture area is calculated, the calculation process is simplified, the calculation efficiency is improved, and the influence of local unstable welding on calculation when the data quantity is too large is avoided. BRIEF DESCRIPTION OF DRAWINGS

[0020] Other features, objects, and advantages of the application will become more apparent from the following detailed description of non-limiting embodiments made with reference to the drawings:

[0021] Figure 1 A flow chart of a method for determining welding process stability according to one embodiment of the application is shown;

[0022] Figure 2 A welding data display schematic diagram according to one embodiment of the application is shown;

[0023] Figure 3 A welding process stability presentation schematic diagram according to one embodiment of the application is shown;

[0024] Figure 4 A device structure diagram for determining welding process stability according to one embodiment of the application is shown;

[0025] Figure 5 An exemplary system that can be used to implement various embodiments described herein is shown.

[0026] The same or similar reference numerals in the drawings represent the same or similar components. DETAILED DESCRIPTION

[0027] The application will be further described in detail below with reference to the drawings.

[0028] In one typical configuration of the application, the terminal, the device of the service network and the trusted party each include one or more processors (for example, a central processing unit (CPU)), an input / output interface, a network interface and a memory.

[0029] Memory can include non-persistent memory and / or volatile memory, random access memory (RAM), and / or non-volatile memory, e.g., read only memory (ROM), EPROM, and / or the like. Memory is an example of computer readable media.

[0030] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PCM), programmable random access memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile discs (DVDs) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device.

[0031] The device referred to in the present application includes but is not limited to a user device, a network device, or a device formed by integrating a user device and a network device through a network. The user device includes but is not limited to any kind of mobile electronic product capable of human-computer interaction (for example, human-computer interaction through a touch panel), such as a smart phone, a tablet computer, etc. The mobile electronic product can adopt any operating system, such as an Android operating system, an iOS operating system, etc. The network device includes an electronic device capable of automatically performing numerical calculation and information processing according to a pre-set or stored instruction. The hardware of the network device includes but is not limited to a microprocessor, an application specific integrated circuit (ASIC), a programmable logic device (PLD), a field programmable gate array (FPGA), a digital signal processor (DSP), an embedded device, etc. The network device includes but is not limited to a computer, a network host, a single network server, a plurality of network servers, or a cloud formed by a plurality of servers. The cloud is formed by a large number of computers or network servers based on cloud computing. The cloud computing is a kind of distributed computing, which is a virtual supercomputer formed by a group of loosely coupled computer clusters. The network includes but is not limited to the Internet, a wide area network, a metropolitan area network, a local area network, a VPN network, a wireless Ad Hoc network, etc. Preferably, the device can also be a program running on the user device, the network device, or a device formed by integrating a user device and a network device, a network device, a touch terminal, or a device formed by integrating a network device and a touch terminal through a network.

[0032] Of course, those skilled in the art should understand that the above device is only an example, and other existing or future devices, such as devices that can be applicable to the present application, should also be included in the protection scope of the present application, and are hereby included by reference.

[0033] In the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise explicitly and specifically limited.

[0034] Figure 1A method flowchart for determining welding process stability according to one embodiment of the present application is shown, which includes steps S11, S12, S13, S14 and S15. In step S11, the device 1 acquires a welding data set in a welding process; in step S12, the device 1 determines a plurality of welding data subsets and data proportion information corresponding to each welding data subset in the plurality of welding data subsets according to the welding data set and a set data interval; in step S13, the device 1 determines welding data subset quantity information corresponding to each data proportion segmentation information in the plurality of data proportion segmentation information according to the plurality of data proportion segmentation information and the data proportion information corresponding to each welding data subset, wherein the data proportion information of the welding data subset corresponding to each data proportion segmentation information is greater than the data proportion segmentation information; in step S14, the device 1 determines trajectory repetition rate information corresponding to the welding data set according to the plurality of data proportion segmentation information and the welding data subset quantity information corresponding to each data proportion segmentation information in the plurality of data proportion segmentation information; in step S15, the device 1 determines the welding process stability according to the trajectory repetition rate information.

[0035] In step S11, the device 1 acquires a welding data set in a welding process. In some embodiments, the device 1 includes but is not limited to a user device, a network device that can perform welding process stability analysis. For example, a device installed with a welding process stability analysis application. In some embodiments, the device 1 acquires the welding data set in the welding process in response to a welding process stability analysis instruction. For example, the device 1 acquires the welding process stability analysis instruction through the operation of a user thereon (e.g., triggering a start analysis button, etc.), and then acquires the welding data set in the welding process for subsequent welding process stability analysis. In some embodiments, the welding data set includes a welding data set in a gas metal arc welding (GMAW) or a submerged arc welding (SAW) process. In some embodiments, referring to the welding data display diagram shown, the device 1 can also present the data situation of the welding data set, for example, the approximate distribution of the welding data, the data acquisition frequency, the data quantity information or the maximum value, the minimum value, etc., so as to facilitate the user to perform comparative analysis and help the user to understand and interpret the subsequently calculated trajectory repetition rate information. Figure 2

[0036] ​In some embodiments, the step S11 comprises: a step S111 (not shown) in which the device 1 acquires an original welding data set in a welding process; and a step S112 (not shown) in which the device 1 processes the original welding data set based on a data preprocessing parameter configured by a user to obtain a welding data set. In some embodiments, the original welding data set can be directly imported by the user or acquired by the device 1 from a corresponding welding database or an Internet of Things gateway in a welding production site. In some embodiments, the device 1 can process the original welding data set based on a user demand. If the user does not configure a corresponding data preprocessing parameter, the device 1 can not process the original welding data set or process the original welding data set based on a default data preprocessing parameter to obtain a corresponding welding data set. If the user configures a data preprocessing parameter through the device 1, the device 1 processes the original welding data set based on the data preprocessing parameter configured by the user. The data preprocessing parameter includes but is not limited to data analysis frequency or filter mode information.

[0037] In some embodiments, the data preprocessing parameter comprises a data analysis frequency; and the step S112 comprises: the device 1 processes the original welding data set based on the data analysis frequency to determine a welding data set. For example, when the data sampling frequency corresponding to the original welding data set is too high, the user can set a corresponding data analysis frequency to complete the frequency reduction of the original welding data set, so that subsequent welding data calculation is analyzed according to the data analysis frequency. The data sampling frequency generally represents the amount of welding data collected in one second in the welding process. The data analysis frequency is less than or equal to the data sampling frequency.

[0038] In some embodiments, the data preprocessing parameter comprises filter mode information; and the step S112 comprises: the device 1 processes the original welding data set based on the filter mode information to determine a welding data set. In some embodiments, the filter mode information includes but is not limited to low-pass filtering, high-pass filtering, band-pass filtering or band-stop filtering. The device 1 can retain certain components in the original welding data set based on the filter mode selected by the user to determine a corresponding welding data set for subsequent calculation. For example, if the filter mode information comprises low-pass filtering, the device 1 retains low-frequency components in the original welding data set to determine a corresponding welding data set. If the filter mode information comprises high-pass filtering, the device 1 retains high-frequency components in the original welding data set to determine a corresponding welding data set. If the filter mode information comprises band-pass filtering, the device 1 retains components in a specific range in the original welding data set to determine a corresponding welding data set. If the filter mode information comprises band-stop filtering, the device 1 excludes components in a specific range in the original welding data set and retains other components to determine a corresponding welding data set.

[0039] In step S12, the device 1 determines a plurality of subsets of welding data and data proportion information corresponding to each of the plurality of subsets of welding data according to the welding data set and a set data range. In some embodiments, the data range can be set according to the distribution of voltage and current in the welding data set. The data range includes a plurality of voltage-current ranges. For example, if the voltage and current in the welding data set can reach 100V and 500A respectively, the voltage-current ranges corresponding to the data range are divided within 0-100V and 0-500A. For example, the voltage range 0-100V and the current range 0-500A are divided into 30 equal parts respectively, and 900 voltage-current ranges can be obtained (for example, {0≤U<10 / 3, 0≤I<50 / 3}, {0≤U<10 / 3, 50 / 3≤I<100 / 3}…). In some embodiments, the device 1 determines a plurality of subsets of welding data according to the plurality of voltage-current ranges included in the data range. The subsets of welding data correspond one-to-one to the voltage-current ranges, and the welding data contained in the subsets of welding data correspond to voltage and current values belonging to the corresponding voltage-current ranges. In some embodiments, the device 1 can also determine the proportion of the amount of data contained in each subset of welding data to the total amount of data in the welding data set, i.e., the data proportion information corresponding to each subset of welding data.

[0040] In some embodiments, the method further includes step S16 (not shown), in which the device 1 determines a plurality of data proportion segmentation information according to the data proportion information corresponding to each of the plurality of subsets of welding data. In some embodiments, the device 1 determines the maximum data proportion information from the determined data proportion information corresponding to each subset of welding data, and divides the data proportion information based on the maximum data proportion information to determine a plurality of data proportion segmentation information. For example, the device 1 determines that the maximum data proportion information is x max , and can perform uniform division with 0 as the starting point and x max as the ending point to obtain a plurality of data proportion segmentation information {0, x max / n, 2x max / n, …, x max}.

[0041] In step S13, device 1 determines the number of welding data subsets corresponding to each data ratio segment based on multiple data ratio segment information and the data ratio information corresponding to each welding data subset. The data ratio information of the welding data subset corresponding to each data ratio segment is greater than that of the data ratio segment information. For example, for each data ratio segment, device 1 determines the number of welding data subsets whose data ratio information is greater than that of the data ratio segment information, and uses this number as the number of welding data subsets corresponding to that data ratio segment information.

[0042] In step S14, device 1 determines the trajectory repetition rate information corresponding to the welding dataset based on the plurality of data proportion segmentation information and the number of welding data subsets corresponding to each of the plurality of data proportion segmentation information. For example, device 1 determines a line graph of the plurality of data proportion segmentation information and the corresponding number of welding data subsets, and then obtains the proportion information of the line region to the total area based on the line graph, thereby using the proportion information to determine the corresponding trajectory repetition rate information. The smaller the proportion information, the higher the trajectory repetition rate; the larger the proportion information, the lower the trajectory repetition rate.

[0043] In some embodiments, step S14 includes: step S141 (not shown), where device 1 draws a corresponding line graph based on the plurality of data ratio segmentation information and the welding data subset quantity information corresponding to each of the plurality of data ratio segmentation information; step S142 (not shown), where device 1 determines the area of ​​the line region based on the line graph; and step S143 (not shown), where device 1 determines the trajectory repetition rate information corresponding to the welding dataset based on the area of ​​the line region. In some embodiments, step S141 includes: device 1 draws a line graph with the data ratio segmentation information as the abscissa and the corresponding welding data subset quantity information as the ordinate, about the plurality of data ratio segmentation information and the welding data subset quantity information corresponding to each of the plurality of data ratio segmentation information. In some embodiments, device 1 determines the area of ​​the line region between the line and the horizontal axis based on the line graph. It then determines the area ratio of the line region in the line graph based on the area of ​​the line region, thereby determining the corresponding trajectory repetition rate information.

[0044] In some embodiments, the step S143 comprises: determining, by the device 1, a maximum rectangular area in the line graph according to the plurality of data proportion segmentation information and the number of welding data subsets corresponding to each data proportion segmentation information in the plurality of data proportion segmentation information; and determining, by the device 1, the trajectory repetition rate information corresponding to the welding data set according to the maximum rectangular area and the area of the line graph. For example, the device 1 determines the maximum data proportion segmentation information and the maximum number of welding data subsets from the plurality of data proportion segmentation information and the number of welding data subsets corresponding to each data proportion segmentation information, respectively. Then, the device 1 determines the maximum rectangular area in the line graph according to the maximum data proportion segmentation information and the maximum number of welding data subsets. The maximum rectangular area = the maximum data proportion segmentation information x the maximum number of welding data subsets. In some embodiments, the device 1 determines the proportion information of the area of the line graph in the maximum rectangular area according to the maximum rectangular area and the area of the line graph, and determines the corresponding trajectory repetition rate information by using the proportion information. The smaller the proportion information, the higher the trajectory repetition rate; the larger the proportion information, the lower the trajectory repetition rate. In some embodiments, the trajectory repetition rate information = 1 - the area of the line graph / the maximum rectangular area.

[0045] In step S15, the device 1 determines the welding process stability according to the trajectory repetition rate information. In some embodiments, the device 1 can determine the welding process stability by using the trajectory repetition rate information. The device 1 can also determine the welding process stability according to the trajectory repetition rate information and the corresponding stability evaluation index. For example, the stability evaluation index includes the trajectory repetition rate interval corresponding to different stability evaluation results (for example, the welding process stability evaluation: excellent, corresponding to the trajectory repetition rate information higher than 90%; the welding process stability evaluation: good, corresponding to the trajectory repetition rate information between 80% and 90%; the welding process stability evaluation: poor, corresponding to the trajectory repetition rate information less than 80%, etc.), and the device 1 can determine the welding process stability by using the stability evaluation results of excellent, good, poor, etc. determined. Figure 3 In some embodiments, the device 1 can present the determined welding process stability to the user by using the welding process stability presentation diagram shown in FIG. 13A (for example, the device 1 presents the determined welding process stability to the user by using the welding process stability presentation diagram shown in FIG. 13A). Figure 3 In addition, the device 1 can also present the calculation results of the standard UI area, the average voltage, the average current, the standard deviation, the range, etc. about the welding data set to the user at the same time, so as to assist the user to understand the welding process stability result.

[0046] Figure 4Fig. 1 shows a structure diagram of an apparatus for determining stability of a welding process according to an embodiment of the present application. The apparatus 1 comprises a first module 11, a second module 12, a third module 13, a fourth module 14 and a fifth module 15. The first module 11 obtains a welding data set in a welding process; the second module 12 determines a plurality of welding data subsets and data proportion information corresponding to each welding data subset in the plurality of welding data subsets according to the welding data set and a set data interval; the third module 13 determines welding data subset quantity information corresponding to each data proportion segmentation information in the plurality of data proportion segmentation information according to the plurality of data proportion segmentation information and the data proportion information corresponding to each welding data subset, wherein the data proportion information of the welding data subset corresponding to each data proportion segmentation information is greater than the data proportion segmentation information; the fourth module 14 determines trajectory repetition rate information corresponding to the welding data set according to the plurality of data proportion segmentation information and the welding data subset quantity information corresponding to each data proportion segmentation information in the plurality of data proportion segmentation information; and the fifth module 15 determines the stability of the welding process according to the trajectory repetition rate information. Figure 4 The specific embodiments of the first module 11, the second module 12, the third module 13, the fourth module 14 and the fifth module 15 are the same as or similar to the specific embodiments of the aforementioned steps S11, S12, S13, S14 and S15 respectively, and thus are not described herein by way of reference.

[0047] In some embodiments, the first module comprises a first unit 111 (not shown) and a second unit 112 (not shown). The first unit 111 obtains an original welding data set in a welding process; and the second unit 112 processes the original welding data set to obtain a welding data set based on data preprocessing parameters configured by a user. The specific embodiments of the first unit 111 and the second unit 112 are the same as or similar to the specific embodiments of the aforementioned steps S111 and S112 respectively, and thus are not described herein by way of reference.

[0048] In some embodiments, the apparatus 1 further comprises a sixth module 16 (not shown). The sixth module 16 determines a plurality of data proportion segmentation information according to the data proportion information corresponding to each welding data subset in the plurality of welding data subsets. The specific embodiments of the sixth module 16 are the same as or similar to the specific embodiments of the aforementioned step S16, and thus are not described herein by way of reference.

[0049] In some embodiments, the one-four module includes a one-four one unit 141 (not shown), a one-four two unit 142 (not shown), and a one-four three unit 143 (not shown). The one-four one unit 141 draws a corresponding line graph according to the plurality of data proportion segment information and the number of subsets of welding data corresponding to each data proportion segment information in the plurality of data proportion segment information; the one-four two unit 142 determines a line graph area according to the line graph; and the one-four three unit 143 determines the trajectory repetition rate information corresponding to the welding data set according to the line graph area. Here, the specific embodiments of the one-four one unit 141, the one-four two unit 142, and the one-four three unit 143 are the same as or similar to the specific embodiments of the foregoing steps S141, step S142, and step S143, respectively, and thus will not be described again, but are included herein by reference.

[0050] Figure 5 An example system that can be used to implement various embodiments described herein is shown;

[0051] As Figure 5 shown, in some embodiments, system 300 can function as any of the devices in the various embodiments described herein. In some embodiments, system 300 can include one or more computer-readable media (e.g., system memory or NVM / storage 320) having instructions and one or more processors (e.g., processor(s) 305) coupled to the one or more computer-readable media and configured to execute the instructions to implement modules to perform the actions described herein.

[0052] For one embodiment, system control module 310 can include any suitable interface controllers to provide for any suitable interface to at least one of the processor(s) 305 and / or any suitable device or component in communication with system control module 310.

[0053] System control module 310 can include a memory controller module 330 to provide an interface to system memory 315. Memory controller module 330 can be a hardware module, a software module, and / or a firmware module.

[0054] System memory 315 can be used to, for example, load and store data and / or instructions for system 300. For one embodiment, system memory 315 can include any suitable volatile memory, such as suitable DRAM. In some embodiments, system memory 315 can include double data rate type four synchronous dynamic random access memory (DDR4 SDRAM).

[0055] For one embodiment, system control module 310 can include one or more input / output (I / O) controllers to provide an interface to NVM / storage 320 and communication interface(s) 325.

[0056] For example, NVM / storage 320 can be used to store data and / or instructions. NVM / storage 320 can include any suitable non-volatile memory (e.g., flash memory) and / or can include any suitable non-volatile storage device(s) (e.g., one or more hard disk drives (HDDs), one or more compact disk (CD) drives, and / or one or more digital versatile disk (DVD) drives).

[0057] NVM / storage 320 can include a storage resource that is physically part of the device on which system 300 is installed, or that is accessed via the device but not necessarily physically part of the device. For example, NVM / storage 320 can be accessed over a network via communication interface(s) 325.

[0058] Communication interface(s) 325 can provide an interface for system 300 to communicate with one or more networks and / or with any other suitable device. System 300 can wirelessly communicate with one or more components of a wireless network according to any of one or more wireless network standards and / or protocols.

[0059] For one embodiment, at least one of processor(s) 305 can be logically packaged with one or more controllers of system control module 310 (e.g., memory controller module 330). For one embodiment, at least one of processor(s) 305 can be logically packaged with one or more controllers of system control module 310 to form a system-in-a-package (SiP). For one embodiment, at least one of processor(s) 305 can be logically integrated on the same die with one or more controllers of system control module 310. For one embodiment, at least one of processor(s) 305 can be logically integrated on the same die with one or more controllers of system control module 310 to form a system-on-a-chip (SoC).

[0060] In various embodiments, system 300 can be, but is not limited to, a server, a workstation, a desktop computing device, or a mobile computing device (e.g., a laptop computing device, a handheld computing device, a tablet, a netbook, etc.). In various embodiments, system 300 can have more or fewer components, and / or different architectures. For example, in some embodiments, system 300 includes one or more cameras, a keyboard, a liquid crystal display (LCD) screen (including touch screen displays), a non- volatile memory port, multiple antennas, a graphics chip, an application specific integrated circuit (ASIC), and a speaker.

[0061] In addition to the methods and devices described in the various embodiments above, the present application provides a computer-readable storage medium storing computer code that, when executed, causes the method of any one of the preceding claims to be performed.

[0062] The present application also provides a computer program product that, when executed by a computer device, causes the method of any one of the preceding claims to be performed.

[0063] The present application also provides a computer device comprising:

[0064] one or more processors;

[0065] a memory for storing one or more computer programs;

[0066] when the one or more computer programs are executed by the one or more processors, cause the one or more processors to implement the method of any one of the preceding claims.

[0067] It is noted that the present application can be implemented in software and / or in a combination of software and hardware, e.g., an application specific integrated circuit (ASIC), a general purpose computer or any other similar hardware device. In one embodiment, the software program of the present application is implemented by the processor to perform the steps or functions described above. Also, the software program of the present application (including related data structures) can be stored in a computer readable storage medium, e.g., a RAM memory, a magnetic or optical drive or diskette, and the like. Additionally, some of the steps or functions can be implemented in hardware, e.g., as circuitry which is cooperated with the processor to perform the various steps or functions.

[0068] In addition, part of the present application can be applied as a computer program product, for example, computer program instructions, when executed by a computer, through the operation of the computer, the method and / or technical solutions according to the present application can be called or provided. Those skilled in the art should understand that the form of computer program instructions in computer readable medium includes but is not limited to source file, executable file, installation package file and the like, and accordingly, the way of computer program instructions executed by computer includes but is not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Here, the computer readable medium can be any available computer readable storage medium or communication medium accessible to the computer.

[0069] Communication media includes any medium by which computer readable instructions, data structures, program modules or other data is communicated from one system to another, for example, via communication signals. Communication media can include wired transmission media (such as cable and lines (e.g., optical, coaxial, etc.)) and wireless (unwired transmission) media that propagate energy waves, such as acoustic, electromagnetic, RF, microwave, and infrared. Computer readable instructions, data structures, program modules, or other data can be embodied as modulated data signals, for example, in wireless media (such as carrier waves or similar mechanisms, such as embodied as part of spread spectrum techniques). The term "modulated data signal" means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. The modulated signals can be analog, digital or mixed.

[0070] By way of example, and not limitation, computer readable storage media can include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. For example, computer readable storage media includes, but is not limited to, random access memory (RAM), such as dynamic RAM (DRAM), static RAM (SRAM), and the like; read only memory (ROM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, and the like; magnetic and optical storage devices such as hard disks, magnetic tape, cassette, CD-ROM, DVD, and the like; and other memory and storage devices that are now known or later developed.

[0071] Here, according to one embodiment of the present application includes a device, the device includes a memory for storing computer program instructions and a processor for executing program instructions, wherein when the computer program instructions are executed by the processor, the device is triggered to run the method and / or technical solutions based on the foregoing according to the plurality of embodiments of the present application.

[0072] It will be obvious to a person skilled in the art that the application is not limited to the details of the above-described exemplary embodiments, but that the application can be implemented in other embodiments without departing from the scope of the application. The embodiments are to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the above description, and all changes which come within the meaning and range of equivalents of the claims are therefore intended to be embraced therein. Any reference signs in the claims should not be construed as limiting the scope of the claims. The word "comprising" does not exclude other elements or steps not mentioned. The singular is not excluded from the plural. Multiple units or devices also can be presented by one unit or device, either by software or hardware. The words "first", "second", etc. are used to identify names, not to indicate any particular order.

Claims

1. A method for determining the stability of a welding process, wherein, The method includes: Obtain the welding dataset during the welding process; Based on the welding dataset and the set data range, multiple welding data subsets and data proportion information corresponding to each welding data subset are determined. Specifically, the proportion of the data volume contained in each welding data subset to the total data volume of the welding dataset is determined as the data proportion information corresponding to each welding data subset. Based on the data ratio information corresponding to each welding data subset, the largest data ratio information is determined; and based on the largest data ratio information, the data ratio information is divided to determine multiple data ratio segment information. Based on multiple data ratio segmentation information and the data ratio information corresponding to each welding data subset, the number of welding data subsets corresponding to each data ratio segmentation information is determined, wherein the data ratio information of the welding data subset corresponding to each data ratio segmentation information is greater than that data ratio segmentation information. Based on the multiple data ratio segmentation information and the number of welding data subsets corresponding to each data ratio segmentation information, the trajectory repetition rate information corresponding to the welding dataset is determined. The stability of the welding process is determined based on the trajectory repetition rate information.

2. The method according to claim 1, wherein, The acquisition of welding data during the welding process includes: Obtain the original welding dataset during the welding process; Based on user-configured data preprocessing parameters, the original welding dataset is processed to obtain a welding dataset.

3. The method according to claim 2, wherein, The data preprocessing parameters include the data analysis frequency; The process of processing the original welding dataset based on user-configured data preprocessing parameters to obtain the welding dataset includes: Based on the data analysis frequency, the original welding dataset is down-processed to determine the welding dataset.

4. The method according to claim 2, wherein, The data preprocessing parameters include filtering method information; The process of processing the original welding dataset based on user-configured data preprocessing parameters to obtain the welding dataset includes: Based on the filtering method information, the original welding dataset is filtered to determine the welding dataset.

5. The method according to claim 1, wherein, The step of determining the trajectory repetition rate information corresponding to the welding dataset based on the plurality of data proportion segmentation information and the welding data subset quantity information corresponding to each of the plurality of data proportion segmentation information includes: Based on the multiple data ratio segmentation information and the number of welding data subsets corresponding to each data ratio segmentation information, a corresponding line graph is drawn. Determine the area of ​​the broken line region based on the broken line graph; Based on the area of ​​the polyline region, the trajectory repetition rate information corresponding to the welding dataset is determined.

6. The method according to claim 5, wherein, The step of determining the trajectory repetition rate information corresponding to the welding dataset based on the area of ​​the polyline region includes: Based on the multiple data ratio segmentation information and the number of welding data subsets corresponding to each data ratio segmentation information, the area of ​​the largest rectangle in the line graph is determined. Based on the area of ​​the maximum rectangle and the area of ​​the polygonal region, the trajectory repetition rate information corresponding to the welding dataset is determined.

7. A computer device for determining the stability of a welding process, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method as described in any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method as described in any one of claims 1 to 6.

9. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the method as described in any one of claims 1 to 6.

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