A method, apparatus, medium, and program product for identifying modality features of a welding current-voltage trajectory plot

Abstract

The purpose of the present application is to provide a method, device, medium and program product for identifying the morphological features of a welding current-voltage trajectory diagram, the method comprising: preprocessing the welding current-voltage trajectory diagram to obtain a current-voltage trajectory diagram to be identified; identifying a plurality of contour information from the current-voltage trajectory diagram to be identified; based on the relationship between the plurality of contour information, contour optimization is performed to determine the target contour information corresponding to the current-voltage trajectory diagram to be identified, wherein the contour optimization method matches the relationship between the plurality of contour information; based on the target contour information, the corresponding morphological features are determined. The one-dimensional time sequence electric signal is converted into a two-dimensional image mode, and the morphological features of the welding current-voltage trajectory diagram are extracted, which provides intuitive and reliable feature basis for the identification of typical defects such as incomplete penetration, spatter or undercut.

Description

Technical Field

[0001] This application relates to the field of welding, and more particularly to a technique for identifying the morphological characteristics of welding current-voltage trajectory diagrams. Background Technology

[0002] In the field of welding quality diagnosis, the identification and judgment of quality status mainly rely on time-frequency domain analysis of electrical signals during the welding process to extract statistical features such as mean, standard deviation, and peak value, or spectral energy distribution characteristics. However, the mapping relationship between electrical signal characteristics and welding defects often depends on manual analysis and modeling, which makes it difficult to comprehensively and accurately characterize various quality anomalies under complex working conditions. Furthermore, single electrical signal analysis lacks the ability to integrate with multi-source information such as arc behavior, resulting in insufficient sensitivity and diagnostic reliability for typical defects such as incomplete fusion and spatter, easily leading to misjudgments and missed detections. Summary of the Invention

[0003] One object of this application is to provide a method, apparatus, medium, and procedure for identifying morphological features of welding current-voltage trajectory diagrams.

[0004] According to one aspect of this application, a method for identifying morphological features of a welding current-voltage trajectory is provided, the method comprising:

[0005] The welding current-voltage trajectory diagram is preprocessed to obtain the current-voltage trajectory diagram to be identified;

[0006] Multiple contour information is identified from the current-voltage trajectory diagram to be identified;

[0007] Based on the relationship between the multiple contour information, contour optimization is performed to determine the target contour information corresponding to the current-voltage trajectory map to be identified, wherein the contour optimization method is matched with the relationship between the multiple contour information;

[0008] Based on the target contour information, the corresponding morphological features are determined.

[0009] According to one aspect of this application, a computer device for identifying morphological features of a welding current-voltage trajectory is provided, 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 any of the methods described above.

[0010] According to one aspect of this application, a computer-readable storage medium is provided having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the steps of any of the methods described above.

[0011] According to one aspect of this application, a computer program product is provided, comprising a computer program, characterized in that, when executed by a processor, the computer program implements the steps of any of the methods described above.

[0012] According to one aspect of this application, an apparatus for identifying morphological features of a welding current-voltage trajectory is provided, the apparatus comprising:

[0013] The module is used to preprocess the welding current-voltage trajectory diagram to obtain the current-voltage trajectory diagram to be identified.

[0014] The first and second modules are used to identify multiple contour information from the current-voltage trajectory diagram to be identified;

[0015] The first and third modules are used to perform contour optimization based on the relationship between the multiple contour information to determine the target contour information corresponding to the current-voltage trajectory map to be identified, wherein the contour optimization method is matched with the relationship between the multiple contour information.

[0016] The first four modules are used to determine the corresponding morphological features based on the target contour information.

[0017] Compared with existing technologies, this application preprocesses the welding current-voltage trajectory map to obtain a current-voltage trajectory map to be identified; identifies multiple contour information from the current-voltage trajectory map to be identified; performs contour optimization based on the relationship between the multiple contour information to determine the target contour information corresponding to the current-voltage trajectory map to be identified, wherein the contour optimization method matches the relationship between the multiple contour information; and determines the corresponding morphological features based on the target contour information. By converting a one-dimensional time-series electrical signal into a two-dimensional image mode and extracting its morphological features using the welding current-voltage trajectory map, this provides an intuitive and reliable feature basis for the identification of typical defects such as incomplete penetration, spatter, or undercut. Attached Figure Description

[0018] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0019] Figure 1-4 Welding current-voltage trajectory diagrams according to one embodiment of this application are shown respectively;

[0020] Figure 5 A flowchart illustrating a method for identifying morphological features of a welding current-voltage trajectory diagram according to an embodiment of this application is shown.

[0021] Figure 6 , 7Schematic diagrams of the bounding rectangles corresponding to the identified contour information according to one embodiment of this application are shown respectively;

[0022] Figure 8 , 9 Schematic diagrams showing target contour information determined according to one embodiment of this application are provided.

[0023] Figure 10 This diagram illustrates a device structure for identifying morphological features of a welding current-voltage trajectory diagram according to an embodiment of this application.

[0024] Figure 11 Exemplary systems that can be used to implement the various embodiments described in this application are shown.

[0025] The same or similar reference numerals in the accompanying drawings represent the same or similar parts. Detailed Implementation

[0026] The present application will now be described in further detail with reference to the accompanying drawings.

[0027] In a typical configuration of this application, the terminal, the device of the service network, and the trusted party all include one or more processors (e.g., a central processing unit (CPU)), input / output interfaces, network interfaces, and memory.

[0028] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory. Memory is an example of computer-readable media.

[0029] Computer-readable media, including both permanent and non-permanent, removable and non-removable media, can store information using any method or technology. Information can be 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 technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0030] The devices referred to in this application include, but are not limited to, user equipment, network equipment, or devices composed of user equipment and network equipment integrated through a network. The user equipment includes, but is not limited to, any mobile electronic product capable of human-computer interaction (e.g., via a touchpad), such as smartphones and tablets. These mobile electronic products can use any operating system, such as Android or iOS. The network equipment includes an electronic device capable of automatically performing numerical calculations and information processing according to pre-set or stored instructions. Its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), and embedded devices. The network equipment includes, but is not limited to, computers, network hosts, single network servers, multiple network server clusters, or clouds composed of multiple servers. Here, a cloud consists of a large number of computers or network servers based on cloud computing, where cloud computing is a type of distributed computing, consisting of a virtual supercomputer composed of a group of loosely coupled computer clusters. The network includes, but is not limited to, the Internet, wide area network, metropolitan area network, local area network, VPN network, wireless ad hoc network, etc. Preferably, the device can also be a program running on the user equipment, network device, or a device formed by integrating user equipment and network device, network device, touch terminal, or network device and touch terminal through a network.

[0031] Of course, those skilled in the art should understand that the above-described devices are merely examples, and other existing or future devices that are applicable to this application should also be included within the scope of protection of this application, and are hereby incorporated by reference.

[0032] In the description of this application, "multiple" means two or more, unless otherwise expressly and specifically defined.

[0033] The inventors considered that welding current-voltage trajectory diagrams can clearly present the dynamic coupling relationship between current and voltage during the welding process, and their trajectory shape directly corresponds to the welding physical process. For example, in short-circuit transition welding, refer to... Figure 1The normal welding current-voltage trajectory diagram shown typically presents a regular rectangular structure, clearly distinguishing between the arcing and short-circuit sections. However, once the welding condition is abnormal, the image shape becomes significantly distorted, such as blurred boundaries, structural fractures, or fragmented morphology. For example, refer to... Figure 2 The welding current-voltage trajectory diagram shown illustrates a welding process with severe spatter. It reveals numerous discrete abnormal points or burr-like protrusions around the short-circuit region, often resulting in voids within the weld contour or an overall discontinuous and fragmented contour. For example, refer to... Figure 3 The welding current-voltage trajectory diagram shown illustrates the occurrence of incomplete penetration or lack of fusion defects, with the arc segment of the trajectory shortened and the overall profile compressed or distorted. For example, refer to... Figure 4 The welding current-voltage trajectory diagram shown exhibits an asymmetrical profile when undercut defects occur, with a localized depression appearing on one side. These profile variations are highly correlated with specific defect types. Therefore, this method quantifies and extracts these morphological features from the welding current-voltage trajectory diagram, providing an intuitive and reliable feature basis for identifying typical defects such as incomplete penetration, spatter, or undercut defects, facilitating stable and efficient diagnosis of welding quality.

[0034] Figure 5 A flowchart illustrating a method for identifying morphological features of a welding current-voltage trajectory diagram according to an embodiment of this application is shown. The method includes steps S11, S12, S13, and S14. In step S11, the welding current-voltage trajectory diagram is preprocessed to obtain a current-voltage trajectory diagram to be identified. In step S12, multiple contour information is identified from the current-voltage trajectory diagram to be identified. In step S13, contour optimization is performed based on the relationship between the multiple contour information to determine the target contour information corresponding to the current-voltage trajectory diagram to be identified, wherein the contour optimization method matches the relationship between the multiple contour information. In step S14, corresponding morphological features are determined based on the target contour information.

[0035] In step S11, the welding current-voltage trajectory map is preprocessed to obtain the current-voltage trajectory map to be identified. Preprocessing highlights the structural features in the welding current-voltage trajectory map and suppresses image noise, facilitating the subsequent extraction of accurate morphological features. The preprocessing includes, but is not limited to, image grayscale conversion, binarization, image denoising, and image enhancement.

[0036] Specifically, step S11 includes: performing image grayscale processing on the welding current-voltage trajectory diagram; performing binarization processing on the grayscale processed welding current-voltage trajectory diagram to obtain the current-voltage trajectory diagram to be identified. For example, the welding current-voltage trajectory diagram can be converted into a grayscale image using image grayscale processing methods such as weighted average, maximum / minimum, or average value methods. The frequency distribution of each pixel value in the converted grayscale image is statistically analyzed to generate a grayscale histogram. A corresponding threshold is determined based on the grayscale histogram, and the grayscale image is converted into a binary image based on the threshold to obtain the current-voltage trajectory diagram to be identified.

[0037] In some embodiments, obtaining the current-voltage trajectory map to be identified further includes: performing median filtering on the binarized welding current-voltage trajectory map to obtain the current-voltage trajectory map to be identified. For example, a filter window of a specified size is set, and it slides pixel by pixel through the aforementioned binarized welding current-voltage trajectory map. At each position, all pixel values ​​within the window are sorted and the median is used to replace the original center pixel value. Median filtering can better preserve the original morphological characteristics of the arc trajectory and short-circuit boundary while significantly reducing abnormal pixels caused by instantaneous fluctuations in current and voltage or acquisition interference, providing a cleaner and more stable image basis for subsequent analysis and processing.

[0038] In step S12, multiple contour information is identified from the current-voltage trajectory map to be identified. In some embodiments, corresponding edge detection algorithms and contour detection algorithms can be used to identify all contours in the current-voltage trajectory map to be identified, obtaining multiple contour information. Taking recognition using OpenCV as an example, commonly used edge detection algorithms include Canny, Sobel, etc., which can be used to detect edge pixels in the current-voltage trajectory map to be identified. Then, the findContours function is used for contour detection to extract the corresponding multiple contour information from these edge pixels.

[0039] The contour information identified in the aforementioned steps often exhibits multiple overlapping or discrete regions, making it difficult to directly obtain complete and representative contour information. Therefore, in step S13, contour optimization is performed based on the relationships between the multiple contour information to determine the target contour information corresponding to the current-voltage trajectory map to be identified. The contour optimization method is matched to the relationships between the multiple contour information. Here, for current-voltage trajectory maps of different shapes, an appropriate contour optimization method is selected based on the inclusion relationships between the multiple contour information to extract the most representative target contour information, laying a reliable foundation for subsequent determination of morphological features.

[0040] In some embodiments, step S13 includes: step S131 (not shown), determining whether the relationship between the plurality of contour information satisfies a preset contour condition, wherein the preset contour condition includes that the bounding rectangle corresponding to one of the plurality of contour information contains the bounding rectangles corresponding to other contour information; step S132 (not shown), if the preset contour condition is satisfied, performing threshold filtering based on the perimeter corresponding to each of the plurality of contour information; step S133 (not shown), determining the target contour information corresponding to the current-voltage trajectory map to be identified based on the filtered contour information.

[0041] The inventors have categorized the contour information identified in the aforementioned steps into two types of contour recognition scenarios. The first type of contour recognition scenario is referenced... Figure 6 The diagram shows a dominant contour information corresponding to a bounding rectangle, which includes bounding rectangles corresponding to other contour information. (See the second type of contour recognition scenario for reference.) Figure 7 The schematic diagram shows that the bounding rectangles corresponding to the contour information are scattered and have no significant inclusion relationship. Based on this, this solution sets corresponding contour conditions. By determining whether the bounding rectangle corresponding to one contour information contains the bounding rectangles corresponding to other contour information, it effectively distinguishes the aforementioned contour recognition scenarios. Then, it selects a contour optimization method that matches the contour recognition scenario to obtain the target contour information, improving the extraction efficiency. If the relationship between multiple contour information satisfies the preset contour condition, it belongs to the first type of contour recognition scenario. Threshold filtering can be performed based on the perimeter of each contour information, filtering out contour information with a perimeter less than a set threshold, and only retaining contour information with a perimeter greater than or equal to the set threshold. Then, one contour information is determined as the target contour information from the filtered contour information, referring to... Figure 8 Extracted target contour information ( Figure 8 (The portion is marked with a black outline). In some embodiments, step S133 includes: if there are multiple filtered contour information, determining the contour information with the largest perimeter as the target contour information. If only one contour information remains after filtering, then directly using that as the target contour information.

[0042] In some embodiments, step S13 further includes: step S134 (not shown), if the preset contour conditions are not met, merging the multiple contour information to determine the target contour information. For the second type of contour recognition scenario, the recognized contour information is often relatively scattered. Adjacent or similar contours can be merged based on the distance between contours to finally determine a target contour information.

[0043] In some embodiments, merging the plurality of contour information to determine the target contour information includes: i. determining the minimum distance between any two contour information in the plurality of contour information; merging contour information whose minimum distance satisfies the corresponding distance threshold condition to obtain updated contour information; repeating step i until a preset stopping condition is met; and determining the target contour information based on the updated contour information. For example, the minimum distance between two contour information can be determined based on the distance between points in any two contour information or the minimum distance from each point in one contour information to another contour information (e.g., calculated using the pointPolygonTest function in OpenCV). Merging two contour information whose minimum distance is less than or equal to the distance threshold. Using the merged contour information as new contour information, continuing the above merging operation until a preset stopping condition is met. The preset stopping condition includes at least one of the following: the number of updated contour information is less than or equal to a preset number threshold, i.e., the number of contour information has been reduced to the expected number through the aforementioned merging; the minimum distance between updated contour information does not meet the distance threshold condition, i.e., the minimum distance between currently updated contour information is greater than the distance threshold, and these contour information will no longer be merged. Based on the last updated contour information, determine the target contour information, referring to... Figure 9 Extracted target contour information ( Figure 9 (The black outline marks the portion). If there is only one updated contour, it can be directly used as the target contour information. If there are multiple updated contour information, morphological methods or convex hull algorithms can be used to merge these updated contour information to determine a single target contour information.

[0044] In step S14, based on the target contour information, corresponding morphological features are determined. In some embodiments, the morphological features include at least one of the following: the area corresponding to the target contour information; the edge smoothness corresponding to the target contour information; and the contour concavity ratio corresponding to the target contour information. For example, the area S can be calculated based on the shape enclosed by the target contour information. Based on the area S and the perimeter L corresponding to the target contour information, the edge smoothness is determined:

[0045]

[0046] The smaller the calculated edge smoothness value, the smoother the target contour information. Based on the area S and the convex hull area S1 corresponding to the target contour information, the contour concavity ratio is determined as: concavity ratio = (S1 - S) / S.

[0047] In some embodiments, the method further includes: step S15 (not shown), determining corresponding welding quality diagnostic information based on the morphological features. In some embodiments, the morphological features can be compared with standard morphological features corresponding to a standard welding process, or the corresponding welding quality diagnostic information can be determined based on a set normal range of morphological features. The welding quality diagnostic information includes, but is not limited to, welding defects such as normal welding, incomplete penetration, weld spatter, and / or undercut. For example, if the area of ​​the morphological feature decreases by more than an area threshold compared to the area of ​​the standard morphological feature, the welding quality diagnostic information includes incomplete penetration. If the edge smoothness of the morphological feature increases by more than a smoothness threshold compared to the edge smoothness value of the standard morphological feature, the welding quality diagnostic information includes weld spatter. If the contour concavity rate of the morphological feature increases by more than a contour concavity rate threshold compared to the contour concavity rate of the standard morphological feature, the welding quality diagnostic information includes undercut. Correspondingly, the above welding quality diagnostic information can also be determined by judging the relationship between the morphological feature and a set normal range of morphological features. If the morphological feature does not have the above conditions or is within the normal range of morphological features, the welding quality diagnostic information includes normal welding.

[0048] In some embodiments, the method further includes: step S16 (not shown), acquiring current and voltage signals during the welding process to generate the welding current-voltage trajectory diagram. For example, electrical signal data during the welding process can be acquired in real time from a high-frequency data acquisition gateway and Hall sensors (voltage / current) deployed on the welding equipment. The acquired time-series current and voltage signals are paired and aligned to generate the corresponding welding current-voltage trajectory diagram.

[0049] Figure 10 This diagram illustrates a device structure for identifying morphological features of a welding current-voltage trajectory diagram according to an embodiment of this application. The device 1 includes a first module 11, a second module 12, a third module 13, and a fourth module 14. The first module 11 preprocesses the welding current-voltage trajectory diagram to obtain a current-voltage trajectory diagram to be identified; the second module 12 identifies multiple contour information from the current-voltage trajectory diagram to be identified; the third module 13 performs contour optimization based on the relationships between the multiple contour information to determine the target contour information corresponding to the current-voltage trajectory diagram to be identified, wherein the contour optimization method matches the relationships between the multiple contour information; the fourth module 14 determines the corresponding morphological features based on the target contour information. Here, the... Figure 10 The specific implementation methods corresponding to modules 11, 12, 13 and 14 shown are the same as or similar to the specific embodiments of steps S11, S12, S13 and S14 mentioned above, and will not be repeated here. They are included here by reference.

[0050] In some embodiments, the three-module 13 includes a three-one unit 131 (not shown), a three-two unit 132 (not shown), and a three-three unit 133 (not shown). The three-one unit 131 determines whether the relationship between the plurality of contour information satisfies a preset contour condition, wherein the preset contour condition includes that the bounding rectangle corresponding to one of the plurality of contour information contains the bounding rectangles corresponding to other contour information. If the preset contour condition is satisfied, the three-two unit 132 performs threshold filtering based on the perimeter corresponding to each of the plurality of contour information. The three-three unit 133 determines the target contour information corresponding to the current-voltage trajectory map to be identified based on the filtered contour information. Here, the specific implementations of the three-one unit 131, the three-two unit 132, and the three-three unit 133 are the same as or similar to the specific embodiments of steps S131, S132, and S133 described above, and therefore will not be repeated here, but are included by reference.

[0051] In some embodiments, the first-third module 13 further includes a third-fourth unit 134 (not shown). If the third-fourth unit 134 does not meet the preset contour conditions, it merges the multiple contour information to determine the target contour information. Here, the specific implementation of the third-fourth unit 134 is the same as or similar to the specific embodiment of the aforementioned step S134, and therefore will not be described again, but is included herein by reference.

[0052] In some embodiments, the device 1 further includes a five-module 15 (not shown). The five-module 15 determines corresponding welding quality diagnostic information based on the morphological features. Here, the specific implementation of the five-module 15 is the same as or similar to the specific implementation of the aforementioned step S15, and therefore will not be repeated here, but is incorporated herein by reference.

[0053] In some embodiments, the device 1 further includes a six-module 16 (not shown). The six-module 16 acquires current and voltage signals during the welding process and generates the welding current-voltage trajectory diagram. Here, the specific implementation of the six-module 16 is the same as or similar to the specific implementation of the aforementioned step S16, and therefore will not be described again, but is incorporated herein by reference.

[0054] Figure 11 Exemplary systems that can be used to implement the various embodiments described in this application are shown; such as Figure 11As shown in some embodiments, system 300 can function as any of the devices described in each of the embodiments. In some embodiments, system 300 may include one or more computer-readable media having instructions (e.g., system memory or NVM / storage device 320) and one or more processors (e.g., one or more processors 305) coupled to the one or more computer-readable media and configured to execute the instructions to implement the module and thus perform the actions described in this application.

[0055] In one embodiment, the system control module 310 may include any suitable interface controller to provide any suitable interface to at least one of the processors 305 and / or any suitable device or component communicating with the system control module 310.

[0056] The system control module 310 may include a memory controller module 330 to provide an interface to the system memory 315. The memory controller module 330 may be a hardware module, a software module, and / or a firmware module.

[0057] System memory 315 can be used, for example, to load and store data and / or instructions for system 300. In one embodiment, system memory 315 may include any suitable volatile memory, such as suitable DRAM. In some embodiments, system memory 315 may include double data rate type quad synchronous dynamic random access memory (DDR4 SDRAM).

[0058] In one embodiment, the system control module 310 may include one or more input / output (I / O) controllers to provide interfaces to the NVM / storage device 320 and (one or more) communication interfaces 325.

[0059] For example, NVM / storage device 320 may be used to store data and / or instructions. NVM / storage device 320 may include any suitable non-volatile memory (e.g., flash memory) and / or may include any suitable (one or more) non-volatile storage devices (e.g., one or more hard disk drive (HDD), one or more optical disc (CD) drives, and / or one or more digital universal optical disc (DVD) drives).

[0060] NVM / storage device 320 may include storage resources that are physically part of a device on which system 300 is mounted, or that can be accessed by the device without necessarily being part of it. For example, NVM / storage device 320 may be accessed via a network through one or more communication interfaces 325.

[0061] One or more communication interfaces 325 may provide the system 300 with an interface to communicate over one or more networks and / or with any other suitable device. The system 300 may wirelessly communicate with one or more components of a wireless network in accordance with any of one or more wireless network standards and / or protocols.

[0062] In one embodiment, at least one of the processors 305 may be logically packaged with one or more controllers of the system control module 310 (e.g., memory controller module 330). In one embodiment, at least one of the processors 305 may be logically packaged with one or more controllers of the system control module 310 to form a system-in-package (SiP). In one embodiment, at least one of the processors 305 may be integrated with the logic of one or more controllers of the system control module 310 on the same die. In one embodiment, at least one of the processors 305 may be integrated with the logic of one or more controllers of the system control module 310 on the same die to form a system-on-a-chip (SoC).

[0063] In various embodiments, system 300 may be, but is not limited to, a server, workstation, desktop computing device, or mobile computing device (e.g., laptop computing device, handheld computing device, tablet computer, netbook, etc.). In various embodiments, system 300 may 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 a touchscreen display), a non-volatile memory port, multiple antennas, a graphics chip, an application-specific integrated circuit (ASIC), and a speaker.

[0064] In addition to the methods and devices described in the above embodiments, this application also provides a computer-readable storage medium storing computer code that, when executed, performs the method described in any of the preceding embodiments.

[0065] This application also provides a computer program product that, when executed by a computer device, performs the method described in any of the preceding claims.

[0066] This application also provides a computer device, the computer device comprising:

[0067] One or more processors;

[0068] Memory, used to store one or more computer programs;

[0069] When the one or more computer programs are executed by the one or more processors, the one or more processors cause the one or more processors to perform the method as described in any of the preceding methods.

[0070] It should be noted that this application can be implemented in software and / or a combination of software and hardware, for example, using an application-specific integrated circuit (ASIC), a general-purpose computer, or any other similar hardware device. In one embodiment, the software program of this application can be executed by a processor to implement the steps or functions described above. Similarly, the software program of this application (including related data structures) can be stored in a computer-readable recording medium, such as RAM memory, a magnetic or optical drive, a floppy disk, or similar devices. Furthermore, some steps or functions of this application can be implemented in hardware, for example, as circuitry that cooperates with a processor to perform the various steps or functions.

[0071] Furthermore, a portion of this application can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to this application through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0072] Communication media include media through which communication signals containing, for example, computer-readable instructions, data structures, program modules, or other data are transmitted from one system to another. Communication media can include guided transmission media (such as cables and wires (e.g., optical fibers, coaxial cables, etc.)) and wireless (unguided transmission) media capable of propagating energy waves, such as sound, electromagnetic, RF, microwave, and infrared. Computer-readable instructions, data structures, program modules, or other data can be embodied as modulated data signals in, for example, wireless media (such as carrier waves or similar mechanisms embodied as part of spread spectrum technology). The term "modulated data signal" refers to a signal whose one or more characteristics are altered or set in a manner that encodes information in the signal. Modulation can be analog, digital, or a hybrid modulation technique.

[0073] By way of example and not limitation, computer-readable storage media may include volatile and non-volatile, removable and non-removable media implemented by any method or technology for storing information such as computer-readable instructions, data structures, program modules or other data. For example, computer-readable storage media include, but are not limited to, volatile memories such as random access memory (RAM, DRAM, SRAM); and non-volatile memories such as flash memory, various read-only memories (ROM, PROM, EPROM, EEPROM), magnetic and ferromagnetic / ferroelectric memories (MRAM, FeRAM); and magnetic and optical storage devices (hard disks, magnetic tapes, CDs, DVDs); or other media now known or hereafter developed capable of storing computer-readable information / data for use by a computer system.

[0074] Herein, one embodiment of this application includes an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein when the computer program instructions are executed by the processor, the apparatus is triggered to run a method and / or technical solution based on the foregoing embodiments of this application.

[0075] It will be apparent to those skilled in the art that this application is not limited to the details of the exemplary embodiments described above, and that this application can be implemented in other specific forms without departing from the spirit or essential characteristics of this application. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of this application is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be embraced within this application. No reference numerals in the claims should be construed as limiting the scope of the claims. Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices recited in the apparatus claims may also be implemented by a single unit or device in software or hardware. The terms "first," "second," etc., are used to indicate names and do not indicate any particular order.

Claims

1. A method for identifying morphological features of welding current-voltage trajectory diagrams, wherein, The method includes: The welding current-voltage trajectory diagram is preprocessed to obtain the current-voltage trajectory diagram to be identified; Multiple contour information is identified from the current-voltage trajectory diagram to be identified; Determine whether the relationship between the multiple contour information satisfies a preset contour condition, wherein the preset contour condition includes that there exists a bounding rectangle corresponding to one of the multiple contour information that contains bounding rectangles corresponding to other contour information. If the preset contour conditions are met, threshold filtering is performed based on the perimeter of each contour information among the multiple contour information; if there are multiple filtered contour information, the contour information with the largest perimeter is determined as the target contour information; if the preset contour conditions are not met, the multiple contour information are merged to determine the target contour information. Based on the target contour information, the corresponding morphological features are determined.

2. The method according to claim 1, wherein, The preprocessing of the welding current-voltage trajectory diagram to obtain the current-voltage trajectory diagram to be identified includes: The welding current-voltage trajectory diagram is converted to grayscale. The welding current-voltage trajectory map after grayscale image processing is binarized to obtain the current-voltage trajectory map to be identified.

3. The method according to claim 2, wherein, The process of obtaining the current-voltage trajectory to be identified also includes: The binarized welding current-voltage trajectory diagram is subjected to median filtering to obtain the current-voltage trajectory diagram to be identified.

4. The method according to claim 1, wherein, The step of merging the multiple contour information to determine the target contour information includes: i. Determine the minimum distance between any two contour information among the multiple contour information, merge the contour information whose minimum distance satisfies the corresponding distance threshold condition, and obtain the updated contour information; Repeat step i above until the preset stopping condition is met, and determine the target contour information based on the updated contour information.

5. The method according to claim 4, wherein, The preset stopping conditions include at least one of the following: The number of updated contour information is less than or equal to a preset threshold. The minimum distance between the updated contour information does not meet the distance threshold condition.

6. The method according to any one of claims 1 to 5, wherein, The morphological features include at least one of the following: The area corresponding to the target contour information; The edge smoothness corresponding to the target contour information; The contour concavity rate corresponding to the target contour information.

7. The method according to any one of claims 1 to 5, wherein, The method further includes: Based on the aforementioned morphological characteristics, corresponding welding quality diagnostic information is determined.

8. The method according to any one of claims 1 to 5, wherein, The method further includes: The current and voltage signals during the welding process are collected to generate the welding current-voltage trajectory diagram.

9. A computer device for identifying morphological features of welding current-voltage trajectory diagrams, 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 8.

10. 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 8.

11. 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 8.

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