A positioning method, system, device, medium and product for automotive welding components

Abstract

This application relates to the field of information technology, and specifically provides a positioning method for automotive welding components, aiming to solve the problem of how to accurately position welding workpieces by a welding robot arm. For this purpose, this application accurately determines the processing process of the automotive welding component based on the number of uncooled welds of the automotive welding component and the category of the current automotive welding component. Based on the processing process of the automotive welding component on the current conveyor belt, a positioning instruction is sent to the corresponding welding robot arm, so that the corresponding welding robot arm accurately positions and welds the automotive welding component on the current conveyor belt according to the positioning instruction, which can effectively prevent the welding robot arm from reprocessing the processed workpieces. Therefore, this application can accurately position the automotive welding component by the welding robot arm.

Description

Technical Field

[0001] The present application relates to the field of information technology, and in particular, to a positioning method, system, device, medium, and product for automotive welding components. Background Art

[0002] With the rapid development of the automotive industry, the concept of automated management has been comprehensively applied in various processes of automotive production. Welding, as an important link in automotive manufacturing, is naturally no exception. Automated control technology enables the welding process to achieve a high degree of automation and intelligence, improving production efficiency and quality. Welding robotic arms have the advantages of high speed, high precision, good consistency, and high stability, and can meet the characteristics of a large variety of products, flexible production, and small batch production in the automotive manufacturing industry. The comprehensive application of welding robotic arms not only improves production efficiency, reduces labor costs and human resource pressure, but also better guarantees the quality, consistency, and certain high-quality production capacity of welded products.

[0003] However, the inventors found that there are at least the following technical problems in the related art:

[0004] During the welding operation, there is a potential risk. Due to the working principle limitations of the conveyor belt or the negligence of welding workers, the completed automotive parts may be mistakenly left on the conveyor belt. Due to the lack of an effective identification mechanism in the welding robotic arm, it may not be able to distinguish between the processed welded workpieces and the workpieces to be processed (automotive welding components), and thus may not be able to accurately position the welded workpieces (to be processed), and there is a possibility of reprocessing the already processed workpieces, resulting in unnecessary losses and waste of resources. Summary of the Invention

[0005] An object of the present application is to provide a positioning method for automotive welding components, which at least solves the technical problem of how to accurately position automotive welding components by a welding robotic arm.

[0006] To achieve the above object, some embodiments of the present application provide the following aspects:

[0007] In a first aspect, some embodiments of the present application further provide a positioning method for automotive welding components, including:

[0008] Obtain a thermal image of the automotive welding component on the current conveyor belt;

[0009] Input the thermal image of the automotive welding component on the current conveyor belt into a welding feature detection model to obtain the number of uncooled weld seams;

[0010] Obtain an image of the current automotive welding component;

[0011] Obtain the preprocessing data of the current automotive welding component based on the image of the current automotive welding component;

[0012] Input the preprocessing data of the current automotive welding component into the automotive welding component classification and detection model to obtain the category of the current automotive welding component;

[0013] Obtain the processing process of the automotive welding component on the current conveyor belt based on the category of the current automotive welding component and the number of uncooled weld seams;

[0014] Based on the processing process of the automotive welding component on the current conveyor belt, send a positioning instruction to the corresponding welding robot arm so that the corresponding welding robot arm positions and welds the automotive welding component on the current conveyor belt according to the positioning instruction.

[0015] In a second aspect, some embodiments of the present application further provide a grasping system for automotive welding components, and the system includes:

[0016] A thermal imaging map acquisition module configured to acquire a thermal imaging map of the automotive welding component on the current conveyor belt;

[0017] A weld seam number prediction module configured to input the thermal imaging map of the automotive welding component on the current conveyor belt into the welding feature detection model to obtain the number of uncooled weld seams;

[0018] An image acquisition module configured to acquire an image of the current automotive welding component;

[0019] A preprocessing acquisition module configured to obtain the preprocessing data of the current automotive welding component based on the image of the current automotive welding component;

[0020] An automotive welding component classification module configured to input the preprocessing data of the current automotive welding component into the automotive welding component classification and detection model to obtain the category of the current automotive welding component;

[0021] A data processing module, which obtains the processing process of the automotive welding component on the current conveyor belt based on the category of the current automotive welding component and the number of uncooled weld seams;

[0022] An information sending module, which sends a positioning instruction to the corresponding welding robot arm based on the processing process of the automotive welding component on the current conveyor belt so that the corresponding welding robot arm positions and welds the automotive welding component on the current conveyor belt according to the positioning instruction.

[0023] In a third aspect, some embodiments of the present application further provide an electronic device, which includes: one or more processors; and a memory storing computer program instructions, and when the computer program instructions are executed, the processors are caused to execute the steps of the method described above.

[0024] In a fourth aspect, some embodiments of the present application further provide a computer-readable medium, on which computer program instructions are stored, and the computer program instructions can be executed by a processor to implement the method described above.

[0025] In a fifth aspect, some embodiments of the present application further provide a computer program product, including a computer program / instructions, and when the computer program / instructions are executed by a processor, the steps of the method described above are implemented.

[0026] Compared with the related art, in the solution provided by the embodiments of the present application, a thermal imaging map of the automotive welding component on the current conveyor belt is obtained, the thermal imaging map of the automotive welding component on the current conveyor belt is input into a welding feature detection model to obtain the number of uncooled welds, an image of the current automotive welding component is obtained, based on the image of the current automotive welding component, preprocessing data of the current automotive welding component is obtained, the preprocessing data of the current automotive welding component is input into an automotive welding component classification detection model to obtain the category of the current automotive welding component, based on the category of the current automotive welding component and the number of uncooled welds, the processing process of the automotive welding component on the current conveyor belt is obtained, and based on the processing process of the automotive welding component on the current conveyor belt, a positioning instruction is sent to the corresponding welding robotic arm, so that the corresponding welding robotic arm positions and welds the automotive welding component on the current conveyor belt according to the positioning instruction. Through the above configuration, the present application accurately determines the processing process of the automotive welding component based on the number of uncooled welds of the automotive welding component and the category of the current automotive welding component, and based on the processing process of the automotive welding component on the current conveyor belt, a positioning instruction is sent to the corresponding welding robotic arm, so that the corresponding welding robotic arm accurately positions and welds the automotive welding component (the automotive welding component to be processed) on the current conveyor belt, and can effectively prevent the welding robotic arm from reprocessing the workpiece that has been processed. Description of the Drawings

[0027] One or more embodiments are exemplarily illustrated by pictures in the corresponding drawings. These exemplary illustrations do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings are represented as similar elements, unless otherwise stated, and the drawings in the figures do not constitute a proportional limitation.

[0028] Figure 1Schematic diagram of the main steps of the positioning method for automotive welding parts according to an embodiment of the present application;

[0029] Figure 2 Schematic diagram of the main component structure of the positioning system for automotive welding parts according to an embodiment of the application;

[0030] Figure 3 Schematic diagram of the processing process of automotive welding parts according to an embodiment of the application;

[0031] Figure 4 Exemplary structural diagram of a processor and a memory according to the present application;

[0032] Figure 5 Exemplary structural diagram of an electronic device according to the present application. Detailed implementation manners

[0033] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Apparently, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0034] Refer to the attached Figure 1 , Figure 1 Schematic diagram of the main steps of the positioning method for automotive welding parts according to an embodiment of the present application. As Figure 1 shown, the positioning method for automotive welding parts in the embodiments of the present application mainly includes the following steps S101 - step S107:

[0035] Step S101: Obtain a thermal imaging map of the automotive welding parts on the current conveyor belt.

[0036] In this embodiment, a thermal imaging map of the automotive welding parts on the current conveyor belt is obtained. By using devices such as infrared cameras, thermal imaging shooting is performed on the automotive welding parts on the current conveyor belt to obtain its thermal imaging map.

[0037] Step S102: Input the thermal imaging map of the automotive welding parts on the current conveyor belt into the welding feature detection model to obtain the number of uncooled welds.

[0038] In this embodiment, the welding feature detection model analyzes the thermal imaging map, extracts the uncooled welds, and calculates their number.

[0039] It should also be noted that infrared thermal imaging technology converts the detected radiation energy of automotive welding components into a thermal image of the target object after processing according to the level of the detected radiation energy. Since the uncooled welds during the welding process of automotive welding components will appear in a darker color, the welding feature detection model can analyze the thermal imaging diagram, extract the uncooled welds, and calculate their quantity.

[0040] In one embodiment, the training of the welding feature detection model further includes the following steps: obtaining a sample set of thermal imaging diagrams of historical automotive welding components; training an initial welding feature detection model based on the sample set of thermal imaging diagrams of historical automotive welding components to obtain the trained welding feature detection model.

[0041] Step S103: Obtain an image of the current automotive welding component.

[0042] In this embodiment, an image of the automotive welding component during the welding process is obtained by using devices such as a camera.

[0043] Step S104: Based on the image of the current automotive welding component, obtain preprocessing data of the current automotive welding component.

[0044] In this embodiment, based on the image of the current automotive welding component, preprocessing data of the current automotive welding component is obtained.

[0045] In one embodiment, step S104 may further include steps S1041 to S1043:

[0046] Step S1041: Denoise the image of the current automotive welding component to obtain a denoised image of the current automotive welding component.

[0047] In this embodiment, due to the uneven illumination in the welding workshop, noise is often generated when obtaining the image, resulting in a decrease in image quality and affecting subsequent image analysis and recognition. Therefore, the image of the current automotive welding component needs to be denoised.

[0048] In one embodiment, the image of the current automotive welding component can be denoised by Gaussian filtering.

[0049] Step S1042: Perform data enhancement processing on the denoised image of the current automotive welding component to obtain an enhanced image of the current automotive welding component.

[0050] In this embodiment, the denoised image of the current automotive welding component is subjected to data enhancement processing to obtain an enhanced image of the current automotive welding component.

[0051] In one embodiment, data augmentation processing can be performed on the image of the current automotive welding component after denoising through image transformation methods such as rotation and flipping.

[0052] Step S1043: Perform illumination enhancement processing on the enhanced image of the current automotive welding component to obtain the preprocessed data of the current automotive welding component.

[0053] In this embodiment, the preprocessed data of the current automotive welding component can be obtained by adjusting the brightness and saturation of the enhanced image of the current automotive welding component for further image optimization.

[0054] Step S105: Input the preprocessed data of the current automotive welding component into the automotive welding component classification and detection model to obtain the category of the current automotive welding component.

[0055] In this embodiment, the preprocessed data of the current automotive welding component is input into the automotive welding component classification and detection model to obtain the category of the current automotive welding component.

[0056] In one embodiment, the training of the automotive welding component classification and detection model further includes the following steps: obtaining a sample set of historical automotive welding component images; training an initial automotive welding component classification and detection model based on the sample set of historical automotive welding component images to obtain the trained automotive welding component classification and detection model.

[0057] Step S106: Based on the category of the current automotive welding component and the number of uncooled welds, obtain the processing process of the current automotive welding component on the conveyor belt.

[0058] In this embodiment, based on the category of the current automotive welding component and the number of uncooled welds, obtain the processing process of the current automotive welding component on the conveyor belt.

[0059] In one embodiment, the category of the current automotive welding component may include automotive doors, automotive chassis, decorative parts (such as front / rear bumpers), etc.

[0060] In one embodiment, the processing process includes a first processing process, a second processing process, a third processing process, and a fourth processing process. Step S106 may further include steps S1061 to S1065:

[0061] Step S1061: Based on the category of the current automotive welding component, obtain a first threshold interval, a second threshold interval, a third threshold interval, and a fourth threshold interval.

[0062] In this embodiment, according to the category of the current automotive welding component, a first threshold range, a second threshold range, a third threshold range, and a fourth threshold range are obtained. Those skilled in the art can customize the first threshold range, the second threshold range, the third threshold range, and the fourth threshold range according to the category of the current automotive welding component and the actual usage situation.

[0063] It should also be noted that the number of welds on the current automotive welding component varies due to different vehicle models, designs, and manufacturing processes. For example, taking the door of the German Volkswagen VW Phaeton as an example, the total length of its welds is 4980 mm, including 7 MIG welds (total length 380 mm), 11 laser welds (total length 1030 mm), and 48 laser-MIG composite welds (total length 3570 mm). Those skilled in the art can set the first threshold range as (5, 16], the second threshold range as (17, 30], the third threshold range as (31, 45], and the fourth threshold range as (45, 66] through the door (the category of the current automotive welding component).

[0064] Step S1062: When the number of uncooled welds is within the first threshold range, it is determined that the current automotive welding component is in the first processing process.

[0065] In this embodiment, when the number of uncooled welds is within the first threshold range, it is determined that the current automotive welding component is in the first processing process.

[0066] Step S1063: When the number of uncooled welds is within the second threshold range, it is determined that the current automotive welding component is in the second processing process.

[0067] In this embodiment, when the number of uncooled welds is within the second threshold range, it is determined that the current automotive welding component is in the second processing process.

[0068] Step S1064: When the number of uncooled welds is within the third threshold range, it is determined that the current automotive welding component is in the third processing process.

[0069] In this embodiment, when the number of uncooled welds is within the third threshold range, it is determined that the current automotive welding component is in the third processing process.

[0070] Step S1065: When the number of uncooled welds is within the fourth threshold range, it is determined that the current automotive welding component is in the fourth processing process.

[0071] In this embodiment, when the number of uncooled welds is within the fourth threshold range, it is determined that the current automotive welding component is in the fourth processing step.

[0072] In one embodiment, step S106 may further include step S1062: When the number of uncooled welds is not within the first threshold range, not within the second threshold range, not within the third threshold range, and not within the fourth threshold range, it indicates the current welding component, and a warning message is sent to the user terminal.

[0073] Step S107: Based on the processing step of the automotive welding component on the current conveyor belt, a positioning instruction is sent to the corresponding welding robotic arm, so that the corresponding welding robotic arm positions and welds the automotive welding component on the current conveyor belt according to the positioning instruction.

[0074] In this embodiment, based on the processing step of the automotive welding component on the current conveyor belt, a positioning instruction is sent to the corresponding welding robotic arm, so that the corresponding welding robotic arm positions and welds the automotive welding component on the current conveyor belt according to the positioning instruction.

[0075] In one embodiment, refer to the appendix Figure 3 , Figure 3 is a schematic diagram of the processing process of an automotive welding component according to an embodiment of the application. As Figure 3 shown, the conveyor belt rotates clockwise. When the current automotive welding component (workpiece 1 or workpiece 2 in the figure) is in the first processing step, the welding robotic arm 3 is controlled to position and weld. When the current automotive welding component is in the second processing step, the welding robotic arm 4 is controlled to position and weld. When the current automotive welding component is in the third processing step, the welding robotic arm 6 is controlled to position and weld. When the current automotive welding component is in the fourth processing step, the welding robotic arm 5 is controlled to position and weld.

[0076] Based on the above steps S101 - S107, obtain the thermal imaging map of the automotive welding parts on the current conveyor belt, input the thermal imaging map of the automotive welding parts on the current conveyor belt into the welding feature detection model to obtain the number of uncooled welds, obtain the image of the current automotive welding parts, based on the image of the current automotive welding parts, obtain the pre - processing data of the current automotive welding parts, input the pre - processing data of the current automotive welding parts into the automotive welding parts classification detection model to obtain the category of the current automotive welding parts, based on the category of the current automotive welding parts and the number of uncooled welds, obtain the processing process of the automotive welding parts on the current conveyor belt, and based on the processing process of the automotive welding parts on the current conveyor belt, send a positioning instruction to the corresponding welding robot arm so that the corresponding welding robot arm positions and welds the automotive welding parts on the current conveyor belt according to the positioning instruction. Through the above configuration method, the present application accurately determines the processing process of the automotive welding parts through the number of uncooled welds of the automotive welding parts and the category of the current automotive welding parts. Based on the processing process of the automotive welding parts on the current conveyor belt, a positioning instruction is sent to the corresponding welding robot arm so that the corresponding welding robot arm accurately positions and welds the automotive welding parts on the current conveyor belt, which can effectively prevent the welding robot arm from re - processing the processed workpieces.

[0077] The step division of the above various methods is only for clear description. During implementation, they can be combined into one step or some steps can be split into multiple steps. As long as the same logical relationship is included, they are all within the protection scope of this patent; adding insignificant modifications to the algorithm or process or introducing insignificant designs, but not changing the core design of its algorithm and process, are all within the protection scope of this patent.

[0078] Refer to the attached Figure 2 , Figure 2 is the main structural schematic diagram of the positioning system of automotive welding parts according to an embodiment of the application. As Figure 2As shown, the positioning system of the automotive welding component in the embodiment of the present application mainly includes a thermal imaging map acquisition module 11, a weld number prediction module 12, an image acquisition module 13, a preprocessing acquisition module 14, an automotive welding component classification module 15, a data processing module 16, and an information sending module 17. In some embodiments, one or more of the thermal imaging map acquisition module 11, the weld number prediction module 12, the image acquisition module 13, the preprocessing acquisition module 14, the automotive welding component classification module 15, the data processing module 16, and the information sending module 17 can be combined into one module. In some embodiments, the thermal imaging map acquisition module 11 is configured to acquire a thermal imaging map of the automotive welding component on the current conveyor belt; the weld number prediction module 12 is configured to input the thermal imaging map of the automotive welding component on the current conveyor belt into a welding feature detection model to obtain the number of uncooled welds; the image acquisition module 13 is configured to acquire an image of the current automotive welding component; the preprocessing acquisition module 14 is configured to obtain preprocessing data of the current automotive welding component based on the image of the current automotive welding component; the automotive welding component classification module 15 is configured to input the preprocessing data of the current automotive welding component into an automotive welding component classification detection model to obtain the category of the current automotive welding component; the data processing module 16 is configured to obtain the processing process of the automotive welding component on the current conveyor belt based on the category of the current automotive welding component and the number of uncooled welds; the information sending module 17 is configured to send a positioning instruction to the corresponding welding robot arm based on the processing process of the automotive welding component on the current conveyor belt, so that the corresponding welding robot arm positions and welds the automotive welding component on the current conveyor belt according to the positioning instruction.

[0079] It is worth mentioning that each module involved in this embodiment is a logical module. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. In addition, in order to highlight the innovative part of the present application, units that are not closely related to solving the technical problems proposed in the present application are not introduced in this embodiment, but this does not mean that there are no other units in this embodiment.

[0080] In addition, some embodiments of the present application also provide an electronic device. The electronic device can be various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and so on. The electronic device can also be various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices, and other similar computing devices.

[0081] The electronic device includes: one or more processors; and a memory storing computer program instructions that, when executed, cause the processors to perform the steps of the method provided in any one or more of the above embodiments. Figure 4 An exemplary structural diagram of the electronic device is disclosed. As Figure 4 shown, the electronic device includes: one or more processors 1101, a memory 1102, and interfaces for connecting the components, including a high-speed interface and a low-speed interface. Each component is interconnected using different buses and can be mounted on a common motherboard or otherwise mounted as required. The processor can process instructions executed within the electronic device, including instructions stored in the memory or on the memory for displaying graphical information of a GUI on an external input / output device (such as a display device coupled to the interface). In some other embodiments, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories if needed. Similarly, multiple electronic devices can be connected, with each device providing part of the necessary operations (such as an array of servers, a set of blade servers, or a multi-processor system). Among them, the components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or claimed herein.

[0082] The electronic device may further include: an input device 1103 and an output device 1104. The processor 1101, the memory 1102, the input device 1103, and the output device 1104 can be connected via a bus or other means, Figure 5 taking connection via a bus as an example.

[0083] The input device 1103 can receive input digital or character information and generate key signal inputs related to the user settings and function controls of the electronic device, such as input devices like a touch screen, a keypad, a mouse, a trackpad, a touchpad, a pointing stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 1104 may include a display device, an auxiliary lighting device (such as an LED), and a haptic feedback device (such as a vibration motor), etc. The display device may include, but is not limited to, a liquid crystal display (LCD), a light-emitting diode (LED) display, and a plasma display. In some embodiments, the display device may be a touch screen.

[0084] To provide interaction with a user, the electronic device may be a computer. The computer has: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or an LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball), through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0085] In the embodiments of the present application, a computer program / instructions is stored on a computer-readable medium. When the computer program / instructions are executed by a processor, the steps of the method provided in any one or more of the above embodiments are implemented. The computer-readable medium may be included in the electronic device described in the above embodiments; or it may exist separately without being assembled into the device. The above computer-readable medium carries one or more computer-readable instructions.

[0086] The memory 1102 can be used as a non-transitory computer-readable storage medium for storing non-transitory software programs, non-transitory computer-executable programs, and modules. The processor 1101 executes various functional applications and data processing of the server by running the non-transitory software programs, instructions, and modules stored in the memory 1102, so as to implement the program instructions / modules corresponding to the method provided in any one or more of the above embodiments of the present application.

[0087] The memory 1102 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the electronic device, etc. In addition, the memory 1102 may include a high-speed random access memory, and may also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory 1102 may optionally include a memory remotely set relative to the processor 1101, and these remote memories can be connected to the electronic device through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0088] It should be noted that the computer-readable medium described in this application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. The computer-readable medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this application, the computer-readable medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0089] The computer-readable medium includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of the computer's storage medium include, but are not limited to, phase change 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 cassette tapes, magnetic disk storage, or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0090] The computer program code for performing the operations of this application can be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0091] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. For example, an application specific integrated circuit (ASIC), a general-purpose computer, or any other similar hardware device can be used. In some embodiments, the software program of the present application can be executed by a processor to implement the above steps or functions. Similarly, the software program (including related data structures) of the present application can be stored in a computer-readable recording medium, for example, a RAM memory, a magnetic or optical drive, or a floppy disk and the like. In addition, some steps or functions of the present application can be implemented by hardware, for example, a circuit that cooperates with a processor to execute each step or function.

[0092] The computer program product provided by the embodiments of the present application includes one or more computer programs / instructions. When the computer program / instructions are executed by a processor, they wholly or partly generate the processes or functions described in the embodiments of the present application. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired manner (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or a wireless manner (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or a data center that includes one or more integrated available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)), etc.

[0093] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of devices, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code, which contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as combinations of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system that performs the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0094] The scope of the present application is defined by the appended claims rather than the above description. Therefore, all changes that fall within the meaning and scope of the equivalent elements of the claims are intended to be included in the present application. Any reference numerals in the claims should not be construed as limiting the claims involved. In addition, it is obvious that the term "comprising" does not exclude other units or steps, and the singular does not exclude the plural. The multiple units or devices stated in the apparatus claims may also be implemented by one unit or device through software or hardware. The terms "first", "second", etc. are only used for descriptive distinction and do not represent any specific order, nor can they be construed as indicating or implying relative importance.

[0095] As described above, it is only the specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily make changes or substitutions, which should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims, and the above embodiments should be regarded as exemplary and non-limiting.

Claims

1. A method for positioning an automobile welding component, characterized in that: include: Get thermal images of the automotive welding parts currently on the conveyor belt; Inputting the thermal imaging image of the automobile welding parts on the current conveyor belt into the welding feature detection model to obtain the number of uncooled welds; Acquire an image of the current automobile welding component; Based on the image of the current automobile welding part, obtaining preprocessing data of the current automobile welding part; Inputting the preprocessed data of the current automobile welding part into the automobile welding part classification detection model to obtain the category of the current automobile welding part; Based on the type of the current automobile welding component and the number of the uncooled welds, obtaining the processing progress of the automobile welding component on the current conveyor belt; Based on the processing process of the automobile welding parts on the current conveyor belt, sending positioning instructions to the corresponding welding robot arm, so that the corresponding welding robot arm positions and welds the automobile welding parts on the current conveyor belt according to the positioning instructions; The step of acquiring preprocessing data of the current automobile welding component based on the image of the current automobile welding component comprises: De-noising the image of the current automobile welding part to obtain a de-noised image of the current automobile welding part; Performing data enhancement processing on the denoised image of the current automobile welding part to obtain an enhanced image of the current automobile welding part; Performing illumination enhancement processing on the enhanced image of the current automobile welding part to obtain preprocessing data of the current automobile welding part; The processing process includes a first processing process, a second processing process, a third processing process and a fourth processing process; Based on the type of the current automobile welding component and the number of the uncooled welds, the processing progress of the automobile welding component on the current conveyor belt is obtained, including: Based on the category of the current automobile welding part, obtaining a first threshold interval, a second threshold interval, a third threshold interval and a fourth threshold interval; When the number of the uncooled welds is within the first threshold range, it is determined that the current automobile welding component is in the first processing process; When the number of the uncooled welds is within the second threshold range, it is determined that the current automobile welding component is in the second processing stage; When the number of the uncooled welds is within the third threshold range, it is determined that the current automobile welding component is in the third processing stage; When the number of the uncooled welds is within the fourth threshold range, it is determined that the current automobile welding component is in the fourth processing stage.

2. The method for positioning automobile welding parts according to claim 1, characterized in that: Also includes: When the number of the uncooled welds is not within the first threshold interval, not within the second threshold interval, not within the third threshold interval, and not within the fourth threshold interval, a warning message is sent to the user terminal.

3. The method for positioning automobile welding parts according to claim 1, characterized in that: The method further comprises training the welding feature detection model according to the following steps: Obtain a sample set of historical thermographic images of automotive welded components; Based on the sample set of the historical thermal imaging images of the automobile welding parts, the initial welding feature detection model is trained to obtain the trained welding feature detection model.

4. The method for positioning automobile welding parts according to claim 1, characterized in that: The method further comprises training the automobile welding parts classification detection model according to the following steps: Obtain a sample set of historical automotive welded component images; Based on the sample set of the historical automobile welding component images, the initial automobile welding component classification detection model is trained to obtain the trained automobile welding component classification detection model.

5. A system for positioning automobile welding parts, characterized in that: The system comprises: A thermal imaging image acquisition module, which is configured to acquire a thermal imaging image of the automobile welding parts currently on the conveyor belt; A weld number prediction module, which is configured to input the thermal imaging image of the automobile welding parts on the current conveyor belt into the welding feature detection model to obtain the number of uncooled welds; An image acquisition module, configured to acquire an image of the current automobile welding component; A preprocessing acquisition module is configured to acquire preprocessing data of the current automobile welding part based on the image of the current automobile welding part; specifically, the image of the current automobile welding part is subjected to denoising to obtain a denoised image of the current automobile welding part; Performing data enhancement processing on the denoised image of the current automobile welding part to obtain an enhanced image of the current automobile welding part; Performing illumination enhancement processing on the enhanced image of the current automobile welding part to obtain preprocessing data of the current automobile welding part; An automobile welding component classification module, which is configured to input the pre-processed data of the current automobile welding component into an automobile welding component classification detection model to obtain the category of the current automobile welding component; A data processing module, based on the type of the current automobile welding part and the number of the uncooled welds, obtains the processing process of the automobile welding part on the current conveyor belt; specifically, the processing process includes a first processing process, a second processing process, a third processing process and a fourth processing process; Based on the type of the current automobile welding component and the number of the uncooled welds, the processing progress of the automobile welding component on the current conveyor belt is obtained, including: Based on the category of the current automobile welding part, obtaining a first threshold interval, a second threshold interval, a third threshold interval and a fourth threshold interval; When the number of the uncooled welds is within the first threshold range, it is determined that the current automobile welding component is in the first processing process; When the number of the uncooled welds is within the second threshold range, it is determined that the current automobile welding component is in the second processing stage; When the number of the uncooled welds is within the third threshold range, it is determined that the current automobile welding component is in the third processing stage; When the number of the uncooled welds is within the fourth threshold range, it is determined that the current automobile welding component is in the fourth processing stage; The information sending module sends positioning instructions to the corresponding welding robot arm based on the processing progress of the automobile welding parts on the current conveyor belt, so that the corresponding welding robot arm positions and welds the automobile welding parts on the current conveyor belt according to the positioning instructions.

6. An electronic device, characterized in that: The electronic device comprises: one or more processors; and A memory storing computer program instructions, which, when executed, cause the processor to perform the steps of the method as claimed in any one of claims 1 to 4.

7. A computer readable medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

8. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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