Method and device for realizing electronic instruction book of electric vehicle instrument and electronic equipment

Abstract

The invention provides an electric vehicle instrument electronic instruction book implementation method and device and electronic equipment, and relates to the field of data processing. The process position and the work content of a worker in the electric vehicle instrument production work are obtained, and the worker wears AR glasses; according to the process position and the work content, determining electronic guidance content from an electronic guidance book, and generating a first image; displaying the first image to a worker through AR glasses; quality detection information for the electric vehicle instrument sent by the detection equipment is received, the quality detection information comprises operated step information, operated step completion time and defective product conditions, and the quality detection information is used for representing whether the quality of the electric vehicle instrument is qualified or not; marking the quality detection information into the first image to generate a second image; and displaying the second image to the worker through AR glasses. According to the technical scheme, the electronic instruction book and the product traceability are reasonably combined, so that the electronic instruction book can be conveniently and beneficially realized.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and in particular to a method, device and electronic equipment for implementing an electronic instruction manual for an electric vehicle instrument. Background Art

[0002] In the production process of electric vehicle instruments, it is crucial to ensure product quality consistency. However, traditional production line inspection and guidance management methods have certain limitations.

[0003] Among them, on the one hand, traditional detection mostly relies on manual experience and offline detection equipment, resulting in a lack of real-time and accurate process guidance data support after defective products are detected. On the other hand, the production process involves multiple complex links, such as welding, assembly and testing, and factors such as operator behavior in each link may affect product quality, but these operators' behaviors are often not guided in a systematic and real-time manner in traditional systems. Therefore, the relevant technical methods have the problem of failing to reasonably combine electronic instructions with product traceability, which is not conducive to the beneficial implementation of electronic instructions.

[0004] Therefore, there is an urgent need for a method, device and electronic equipment for implementing an electronic instruction manual for an electric vehicle instrument. Summary of the invention

[0005] The present application provides a method, device and electronic device for implementing an electronic instruction manual for an electric vehicle instrument, which facilitates the beneficial implementation of the electronic instruction manual by rationally combining the electronic instruction manual with product traceability.

[0006] In a first aspect of the present application, a method for implementing an electronic instruction manual for an electric vehicle instrument is provided, the method comprising: obtaining the process position and work content of a staff member in the production of an electric vehicle instrument, the staff member wearing AR glasses; determining the electronic instruction content from the electronic instruction manual according to the process position and the work content, and generating a first image; displaying the first image to the staff member through the AR glasses; receiving quality inspection information for the electric vehicle instrument sent by a detection device, the quality inspection information including information on operated steps, completion time of the operated steps, and defective product conditions, the quality inspection information being used to indicate whether the quality of the electric vehicle instrument is qualified; marking the quality inspection information to the first image, generating a second image; and displaying the second image to the staff member through the AR glasses.

[0007] By adopting the above technical solution, the system automatically identifies the operator's process position and work content, extracts the corresponding operation instructions from the electronic instruction book, and presents them in real time in the AR glasses. This ensures that the operator can accurately execute the process standards in each step and avoid operational deviations due to unfamiliarity with the process. Through the first image displayed by the AR glasses, the operator does not need to flip through the instructions on paper or handheld devices, and can directly see the operation steps and precautions in the field of vision, reducing operation interruptions and improving efficiency. The system receives quality inspection information from the inspection equipment, including completed operation steps, defective product information, etc., and determines whether the current product meets the quality standards. Real-time annotation of inspection information helps operators to find problems in time and prevent defective products from entering the next process. When an abnormal situation is detected, the system will intuitively present the defective product information through AR glasses, so that the operator can quickly adjust or redo the unqualified steps, reduce rework waste, and improve overall production efficiency. Quality inspection information will be automatically recorded and annotated to the corresponding operation instruction image. This data trace helps to achieve transparent traceability in the production chain and facilitates the search for specific links that produce defective products. The second image with quality information not only contains real-time detection data, but also integrates the completion status of specific operation steps, which facilitates the traceability analysis of each operation step and quality inspection afterwards, and provides data support for process improvement. After the quality problem is detected, the second image is generated through real-time annotation to show the operator specific defect information. This feedback closed loop allows the operator to understand and correct errors in real time, effectively reducing the probability of batch defects. The system records every operation step of the operator and the detection results of defective products, which can be used to optimize the content of the electronic instruction book after analysis, improve the practicality and pertinence of the operation instruction, and thus gradually improve the process quality standards. Therefore, by reasonably combining the electronic instruction book with the product traceability, it is convenient to realize the beneficial implementation of the electronic instruction book.

[0008] Optionally, the obtaining of the process position and work content of the staff in the production of electric vehicle instruments specifically includes: obtaining the position information of the AR glasses; determining the first position of the staff according to the position information; obtaining a work image of the staff taken by the AR glasses; determining the environment in which the staff is located from the work image to obtain the second position; determining the process position in combination with the first position and the second position; and performing image feature recognition on the work image to determine the work content.

[0009] By adopting the above technical solution, the system can more accurately determine the operator's process position through the position information of AR glasses and the environmental recognition in the work image. Combining the first position of AR glasses with the second position identified by environmental features can effectively compensate for the error caused by single positioning, improve positioning accuracy, and ensure that the guidance content is fully matched with the current process. The dual positioning mechanism ensures the accuracy of process identification, avoids erroneous operations caused by positioning deviation, and improves the operator's work safety and production consistency. By performing feature recognition on the work image taken by AR glasses, the system can dynamically obtain the specific work content of the operator. This method not only ensures that the system recognizes the actual work content more accurately, but also lays the foundation for personalized real-time work guidance. By automatically identifying the work content instead of manual judgment, the operator's work errors caused by lack of experience or negligence can be reduced, ensuring that each process is carried out strictly in accordance with the standardized process. Based on the accurate identification of process location and work content, AR glasses can display the guidance content that best matches the current work step. Operators can obtain dynamic and accurate guidance in each step, thereby ensuring the quality of operation and avoiding the problem of lagging traditional guidance content. The system updates the work instructions according to the operator's position and work content in different processes, which can achieve seamless workflow guidance, reduce the operator's switching and waiting time, and improve work efficiency. Through the image acquisition of AR glasses, not only can the operator's work status be recorded, but also the image information can be archived in real time, providing complete traceable data for the production process. Once defective products or abnormal operations occur, the system can quickly trace back to the specific process location and work content, improving traceability efficiency. Accurate process and work content records make quality management more transparent. Managers can view and analyze production data in real time, identify potential problems and make preventive adjustments.

[0010] Optionally, the method of determining electronic guidance contents from an electronic instruction book based on the process location and the work content and generating a first image specifically includes: determining the electronic guidance contents based on the process location and the work content; performing text conversion and image conversion on the electronic guidance contents to generate voice information and action information; inputting the voice information and the action information into an initial digital human model to generate a target digital human including information for explaining the voice information and demonstrating the action information; and generating the first image based on the target digital human.

[0011] By adopting the above technical solutions, a digital human model with voice information and action display is used to provide anthropomorphic operation guidance. This method not only allows the operator to "see" the guidance content, but also "hear" the step-by-step voice explanation, which is more intuitive and easier to understand than traditional text or static diagrams. The digital human can clearly indicate the key operation gestures or tool usage methods by showing complex operation steps through actions, helping the operator to accurately understand the operation requirements. This is particularly important for processes involving fine manual operations, effectively reducing operation deviations. Customized guidance based on process location and work content: The system determines the guidance content based on the operator's current specific process location and operation content, thereby providing "tailored" operation guidance for each process. This personalized guidance method can significantly improve the operator's work efficiency and ensure that each step meets the standard requirements. By generating a digital human in real time and showing the corresponding actions and explanations, the system can dynamically adjust the guidance content according to the operator's progress. The operator does not need to read documents or ask superiors, but only needs to follow the guidance of the digital human to complete standardized operations. For novices or unfamiliar tasks, the voice and action demonstration of the digital human provides a way to learn and use. New operators can quickly learn and master the process on the production line, reducing training time and costs, allowing them to get to work faster. Operators can accurately complete complex or detail-intensive operations with the real-time guidance of digital humans, avoiding errors caused by unfamiliarity with or unclear understanding of the steps, thereby improving overall production quality. Digital humans use voice and action demonstrations to convey information to operators through both visual and auditory channels. Multi-sensory input enhances the effect of information transmission, helps operators understand and remember complex steps, and further improves the proficiency of operations. Compared with traditional static electronic instruction books, dynamic digital humans have a stronger interactive experience, allowing operators to maintain concentration and reduce boredom, which helps improve the overall work experience and participation. The operations and explanations demonstrated by digital humans are standard processes set by the system, which helps all operators achieve consistent operating standards in different shifts and environments. This not only improves the stability of the production process, but also reduces process deviations caused by individual differences. The standardized process of unified explanations and action demonstrations by digital humans is suitable for promotion on multiple production lines, ensuring that each production line and each operator can perform tasks according to the same standards.

[0012] Optionally, the quality inspection information for the electric vehicle instrument sent by the receiving inspection device specifically includes: generating quality inspection information after the first inspection link corresponding to the inspection device completes the inspection of the electric vehicle instrument; determining the next related inspection link of the first inspection link from the electronic instruction book to obtain the second inspection link, and the inspection result corresponding to the first inspection link and the inspection result corresponding to the second inspection link have a causal relationship; based on the second inspection link, obtaining and storing the quality inspection information for the electric vehicle instrument sent by the inspection device, and the inspection device corresponding to the second inspection link includes the AR glasses.

[0013] By adopting the above technical solution, by recording the causal relationship between each detection link in the electronic instruction book, the system can automatically identify the subsequent detection requirements that may be caused by a certain detection result. This function makes the detection information of each link more traceable, which is convenient for analyzing the source and cause of specific problems. Since the system can track and display the causal relationship between different links, quality management personnel can quickly locate the root cause of the problem. For example, if an abnormality is found in the second detection link, the results of the first detection link can be traced back to find possible quality problems, thereby improving the efficiency of troubleshooting. The system automatically generates related detection links to ensure that all necessary detection steps are not ignored, especially for processes with more hidden problems, effectively reducing the risk of missed detection and improving the comprehensiveness and accuracy of overall quality detection. The quality detection information of each detection link will be transmitted and stored immediately after the detection equipment completes the detection. The system can ensure the integrity and real-time nature of the detection data, so that the detection results of the previous link can be immediately referenced in the subsequent detection link to achieve seamless multi-link data integration. AR glasses can not only display the guidance content, but also act as a detection device to transmit detection information to the system in real time. The system combines operation guidance and test feedback, so that the operator is always in a guided state during the test process, reducing the risk of operator misoperation. By automatically identifying related test links and causal relationships, the system realizes a closed-loop management process from detection to problem analysis and then to solution. The test information not only provides a reference for subsequent links, but also automatically triggers relevant measures when there are quality anomalies, such as increasing the frequency of testing or enhancing operation guidance, to ensure continuous quality monitoring and improvement during the production process.

[0014] Optionally, marking the quality inspection information into the first image to generate the second image specifically includes: classifying the quality inspection information to obtain the operated step information, the operated step completion time and the defective product situation; marking the operated step information and the operated step completion time into a dynamic area to obtain the first image content, and the dynamic area is used to display or hide the operated step information and the operated step completion time; determining the coordinate information of the defective product according to the defective product situation; marking the coordinate information of the defective product on the electric vehicle instrument in a color coding manner in a spatial coordinate system to generate the second image content; generating the second image according to the first image content and the second image content.

[0015] By adopting the above technical solution, by setting a dynamic area in the first image to display or hide the information of the operated steps and the completion time, operators and managers can flexibly view and focus on specific detection information, avoid information overload, and make the operation progress and time information of each step more intuitive. This method provides a hierarchical presentation of information, which can help personnel focus on the current process or inspection content and improve work efficiency. By using color coding to mark the coordinate information of defective products on the electric vehicle instrument, managers and operators can quickly identify the areas with problems, avoid complex text descriptions or digital judgments, and improve the operator's sensitivity to problems. The intuitiveness of color makes the location of defective products clear at a glance, helping to accelerate quality repair and processing. By dynamically marking the information of the operated steps and the completion time on the image, the staff can get feedback on the operation progress in real time, understand the execution status of each step and its completion time. This can help operators confirm whether the operation is completed on time, and adjust the work progress in time to avoid quality problems caused by omissions or delays in steps. By marking the coordinates of defective products and using color coding, personnel on the production line can quickly identify problem areas. This instant feedback not only improves the operator's acumen, but also provides important data support for managers, helping to quickly take remedial measures to prevent defective products from flowing into the next link. By classifying quality inspection information, the system can present information more clearly to relevant personnel. The classified information can help managers understand and analyze faster, reduce the time for information screening and filtering, and improve the efficiency of quality management. The coordinates and color-coded markings of defective products can help staff quickly locate problems, avoid tedious inspection and judgment processes, and reduce human errors. By displaying defective product information directly on the image, operators can clearly know which parts or locations need further inspection or repair to ensure that problems are solved in a timely manner.

[0016] Optionally, the method also includes: performing action recognition on the work image to determine the production action corresponding to the staff member; calculating the action similarity between the production action and the preset action corresponding to the work content, and judging whether the key production action included in the production action is consistent with the key production action included in the preset action; if it is determined that the action similarity between the production action and the preset action is greater than or equal to a preset threshold, and the key production action included in the production action is consistent with the key production action included in the preset action, then the production action corresponding to the staff member is determined to be qualified.

[0017] By adopting the above technical solution, the system can automatically determine whether the staff performs the production task according to the prescribed standard action through motion recognition technology, without manual monitoring or intervention. This automated detection method improves the intelligence level of the production line and makes the production process more efficient. Traditional production lines may need to manually check the execution of each process, but now the computer automatically identifies and compares the production actions, reducing manual participation and improving the overall production efficiency and accuracy. Through accurate motion recognition of work images, the system can accurately capture the actual operation of the staff. By calculating the similarity and judging the consistency of key production actions, the system can ensure that each action meets the preset standard requirements, thereby improving the accuracy of the production process. The preset actions are formulated through process flow and production standards. The method of motion recognition and standard comparison is used to ensure that the operator always operates according to the standard, thereby avoiding quality problems caused by differences in personal experience or irregular operations. If the production actions of the staff do not meet the preset standards, the system can detect and feedback immediately. This means that unqualified production operations can be quickly identified when they occur, reducing the risk of unqualified products flowing into the next process or being delivered, thereby improving the level of quality control.

[0018] Optionally, the method also includes: if it is determined that the action similarity between the production action and the preset action is greater than or equal to a preset threshold, and the key production action included in the production action is inconsistent with the key production action included in the preset action, then the production action corresponding to the staff is determined to be unqualified, or, if it is determined that the action similarity between the production action and the preset action is less than a preset threshold, then the production action corresponding to the staff is determined to be unqualified, and abnormal action alarm information is generated; and the abnormal action alarm information is displayed to the staff through the AR glasses.

[0019] By adopting the above technical solution, when the similarity between the production action of the staff and the preset action is lower than the preset threshold, or the key production action is inconsistent, the system can detect potential errors in the production process in real time. This real-time feedback mechanism can ensure that the staff is aware of their operating problems in time, so as to make corrections at the first time and reduce the production of defective products. By comparing the similarity between the preset action and the actual production action, and judging whether the key production action is included, the system can ensure that each operator operates according to the standardized process, thereby improving the consistency and accuracy of production. Even if the operators have different experience, the system can help them maintain consistent operating specifications. The system can clearly point out when and why an action does not meet the requirements, and does not rely solely on manual experience to judge, making the standardization and quality control of production more reliable and avoiding human differences. By judging the similarity of actions, some potential operating errors can be found. Although these errors may not be obvious on the surface, if they are not discovered in time, they may eventually affect the quality of the product. Through this intelligent monitoring, quality problems caused by improper operation can be effectively reduced. The generation of abnormal action alarm information and the real-time feedback mechanism can prevent unqualified actions from continuing to affect production and ensure that product quality can be controlled at an early stage. It avoids the spread of unqualified products on the production line and reduces the risk of rework and scrapping in the later stage. Timely identification and correction of unqualified actions can reduce material waste and rework caused by incorrect operations and improve the work efficiency of the production line. In this way, enterprises can use resources more efficiently, reduce production costs and improve production efficiency. Through rapid detection and feedback, production delays caused by incorrect operations can be avoided, ensuring that the production line runs at the optimal rhythm and improving overall production efficiency.

[0020] In a second aspect of the present application, a device for implementing an electronic instruction manual for an electric vehicle instrument is provided, characterized in that the device includes an acquisition module and a processing module, wherein the acquisition module is used to acquire the process position and work content of a staff member in the production work of an electric vehicle instrument, and the staff member wears AR glasses; the processing module is used to determine the electronic instruction content from the electronic instruction manual according to the process position and the work content, and generate a first image; the processing module is also used to display the first image to the staff member through the AR glasses; the acquisition module is also used to receive quality inspection information for the electric vehicle instrument sent by the inspection equipment, the quality inspection information includes information on the operated steps, completion time of the operated steps, and defective product conditions, and the quality inspection information is used to indicate whether the quality of the electric vehicle instrument is qualified; the processing module is also used to mark the quality inspection information to the first image to generate a second image; the processing module is also used to display the second image to the staff member through the AR glasses.

[0021] In the third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device performs the method described above.

[0022] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, the method described above is executed.

[0023] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: By automatically identifying the operator's process position and work content, the corresponding operation instructions are extracted from the electronic instruction book and presented in real time on the AR glasses. This ensures that the operator can accurately execute the process standards in each step and avoid operational deviations due to unfamiliarity with the process. Through the first image displayed by the AR glasses, the operator does not need to flip through the instructions on paper or handheld devices, and can directly see the operation steps and precautions in the field of vision, reducing operation interruptions and improving efficiency. The system receives quality inspection information from the inspection equipment, including completed operation steps, defective product information, etc., and determines whether the current product meets the quality standards. Real-time annotation of inspection information helps operators to find problems in time and prevent defective products from entering the next process. When an abnormal situation is detected, the system will intuitively present the defective product information through AR glasses, so that the operator can quickly adjust or redo the unqualified steps, reduce rework waste, and improve overall production efficiency. Quality inspection information will be automatically recorded and annotated to the corresponding operation instruction image. This data trace helps to achieve transparent traceability in the production chain and facilitates the search for specific links that produce defective products. The second image with quality information not only contains real-time detection data, but also integrates the completion status of specific operation steps, which facilitates the traceability analysis of each operation step and quality inspection afterwards, and provides data support for process improvement. After the quality problem is detected, the second image is generated through real-time annotation to show the operator specific defect information. This feedback closed loop allows the operator to understand and correct errors in real time, effectively reducing the probability of batch defects. The system records every operation step of the operator and the detection results of defective products, which can be used to optimize the content of the electronic instruction book after analysis, improve the practicality and pertinence of the operation instruction, and thus gradually improve the process quality standards. Therefore, by reasonably combining the electronic instruction book with the product traceability, it is convenient to realize the beneficial implementation of the electronic instruction book. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flowchart of a method for implementing an electronic instruction manual for an electric vehicle instrument provided in an embodiment of the present application.

[0025] Figure 2 Another flowchart of a method for implementing an electronic instruction manual for an electric vehicle instrument provided in an embodiment of the present application.

[0026] Figure 3 A schematic diagram of a module of an electric vehicle instrument electronic instruction manual implementation device provided in an embodiment of the present application.

[0027] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0028] Explanation of the reference numerals: 31, acquisition module; 32, processing module; 41, processor; 42, communication bus; 43, user interface; 44, network interface; 45, memory. DETAILED DESCRIPTION

[0029] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0030] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0031] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0032] In the production process of electric vehicle instruments, it is crucial to ensure the consistency and stability of product quality. However, the existing traditional production line detection and guidance management methods have obvious limitations in practical applications and cannot meet the requirements of modern production processes for efficiency, real-time and accuracy.

[0033] Among them, on the one hand, traditional detection mostly relies on manual experience and offline detection equipment, resulting in a lack of real-time and accurate process guidance data support after defective products are detected. On the other hand, the production process involves multiple complex links, such as welding, assembly and testing, and factors such as operator behavior in each link may affect product quality, but these operators' behaviors are often not guided in a systematic and real-time manner in traditional systems. Therefore, the relevant technical methods have the problem of failing to reasonably combine electronic instructions with product traceability, which is not conducive to the beneficial implementation of electronic instructions.

[0034] In order to solve the above technical problems, the present application provides a method for implementing an electronic instruction book for an electric vehicle instrument. Figure 1 , Figure 1 A flowchart of a method for implementing an electronic instruction book for an electric vehicle instrument provided in an embodiment of the present application. The method is applied to a server and includes steps S110 to S160, which are as follows: S110. Obtaining the process position and work content of the staff in the production of electric vehicle instruments, where the staff wears AR glasses.

[0035] Specifically, the server is a centralized computing and data processing system that is responsible for receiving, processing and analyzing data from different devices. In an embodiment of the present application, the main task of the server is to receive data from AR glasses and provide decision support in the production process based on these data. The staff member refers to an operator or technician who performs tasks on the electric vehicle instrument production line. The staff wears AR glasses to receive work instructions, view process information, etc. in real time. The process position refers to the position of the staff member in the production process, that is, a specific workstation or process link on the production line. For example, a staff member may be responsible for assembling a part of the electric vehicle instrument at an assembly station, or performing instrument function testing at a test station. The acquisition of the process position helps the server understand the current position of the staff member in order to provide correct operation instructions. The work content refers to the tasks that the staff member needs to perform in a specific process. For example, the staff member may need to complete specific tasks such as welding, installation, calibration, and inspection in a certain production link. By obtaining the work content, the system can provide accurate operation steps and requirements to ensure that the staff member performs the work according to the specifications.

[0036] In an embodiment of the present application, AR glasses are a device that integrates augmented reality technology, which can display virtual information related to work in real time, and superimpose this information on the actual field of view to assist workers in completing tasks. Among them, AR glasses and servers can transmit data wirelessly or wired, and the server can control the operation of AR glasses. After the staff wears AR glasses, they can receive real-time process guidance, quality standards, operating steps and other information from the server through the device. In addition, AR glasses can also capture the movements and process information of the staff through built-in cameras and sensors, and transmit them to the server in real time for analysis and feedback.

[0037] In a possible implementation, obtaining the process position and work content of a worker in the production of electric vehicle instruments specifically includes: obtaining the position information of AR glasses; determining the first position of the worker based on the position information; obtaining a work image of the worker taken by the AR glasses; determining the environment in which the worker is located from the work image to obtain the second position; determining the process position by combining the first position and the second position; and performing image feature recognition on the work image to determine the work content.

[0038] Specifically, AR glasses have built-in positioning systems, such as GPS, inertial measurement units, accelerometers, gyroscopes and other sensors, which can track the physical position of the glasses in real time. For example, the glasses can determine the current position of the staff through these sensors. The position information can be provided in the form of coordinates, for example, the location of a workstation or a specific area of ​​a production line. The server can determine the current first position of the staff by obtaining the position information of the AR glasses. This may be the specific position of the staff on the production line. For example, the position of the staff in the assembly process, or the position in the testing link. The server determines which workstation the staff is standing at and which task they are performing based on the position information. AR glasses are equipped with cameras that can capture the current working environment and operation of the staff. Through the captured work images, the server can further analyze the working status of the staff. Among them, these images can include a panoramic view of the production environment, components on the operating table, and the action information of the staff. By analyzing the captured work images, the server can identify the environment in which the staff is located. For example, the image can show whether the staff is on the correct workbench, whether there are the correct tools and parts, and even confirm whether the staff is in the correct position by identifying the characteristics of the equipment or workpiece. The second position generated by this process is a further judgment and positioning of the actual working environment of the staff. Combining the first position and the second position of the worker, the server can accurately determine the worker's current process position. For example, the worker may be at the assembly station of the electric vehicle instrument, or at the functional testing station. The system determines the process in which the worker is located by combining the two. The working images taken by AR glasses are not only used for positioning, but also can be used to identify key elements in the image through image feature recognition technologies such as computer vision and deep learning. For example, the server can identify the parts, tools or equipment that the worker is operating through the image, and then determine the specific task or work content that the worker is performing. This may include operations such as welding, assembly, and testing.

[0039] S120: Determine electronic instruction content from the electronic instruction book according to the process position and the work content, and generate a first image.

[0040] Specifically, the electronic instruction book contains information such as the operating steps, precautions, and quality standards for each process of the production line. It is an "operation manual" followed by the staff during the production process. The electronic instruction book usually provides corresponding guidance based on different process positions and work content. The server automatically filters out relevant guidance content from the electronic instruction book based on the process position and work content of the staff. For example, if the staff is in the "assembly station" and the work content is "installing the display screen", the server will extract the specific steps, precautions, and other information about "display screen installation" from the electronic instruction book. The first image is a visual image generated by the server based on the content extracted from the electronic instruction book. It can be a guidance screen containing graphic information, a flowchart, step instructions, or even a virtual character demonstration. The image shows the operating steps that the staff needs to perform, and displays it to the staff through devices such as AR glasses to help them complete the task accurately.

[0041] In a possible implementation, electronic guidance content is determined from an electronic instruction book according to the process location and work content, and a first image is generated, specifically including: determining the electronic guidance content according to the process location and work content; performing text conversion and image conversion on the electronic guidance content to generate voice information and action information; inputting the voice information and action information into an initial digital human model to generate a target digital human including information for explaining voice information and displaying action information; and generating a first image based on the target digital human.

[0042] Specifically, the server converts the text instructions or steps in the electronic manual into voice information so that the worker can understand the task requirements through hearing. For example, the system will convert "Step 1: Connect the display screen to the circuit board" into a voice broadcast. The server converts the pictures, diagrams or flow charts in the electronic manual into dynamic images or action information to help the worker understand the operation steps through vision. For example, the system may generate an image showing how to properly install the display screen, or show a dynamic demonstration of hand movements. Voice information refers to the explanation of the operation steps played by voice, which can help the worker obtain information through hearing and reduce the need to take the eyes away from the workbench to consult the manual. Action information refers to the operation steps displayed through animation or video, showing how to correctly perform a task, such as how to correctly place and fix the display screen with hands. The initial digital human model is a virtual character, a 3D model created by computer graphics technology. This model can be regarded as a virtual assistant, which can be used to explain the operation steps and demonstrate the actions. The target digital human, combined with the voice information and action information, will be used to demonstrate the operation steps to the worker. This virtual assistant will use appropriate voice and animation to explain how to perform the task. For example, the digital human model can simulate how to correctly place a part or the action of using a tool.

[0043] For example, the target digital human can explain according to the voice information of the electronic guidance content, such as "First connect the interface of the display screen to make sure it is not loose." The target digital human can show the operation steps and simulate actions, such as how to properly connect the display screen to the circuit board. The server converts the image generated by the target digital human, including its voice explanation and action demonstration, into a visual image or animation, and presents it to the staff through the AR device. The staff can see the target digital human and its operation demonstration through AR glasses, and get detailed guidance and feedback in real time.

[0044] S130: Display the first image to the staff through the AR glasses.

[0045] Specifically, the server will display the first image generated according to the process location and work content to the staff through AR glasses. These images or animations are related to the operation steps, and may be diagrams, 3D models, animation demonstrations, etc., to help staff understand how to perform specific work tasks. The first image may be a static image showing the operation steps, or a dynamic 3D model showing how to install or inspect a component. AR glasses display these images in real time through the display, allowing staff to get real-time guidance during operation. For example, after wearing AR glasses, staff can see demonstration images of the display installation steps on the lenses, or see the target digital person demonstrate how to install the display.

[0046] S140, receiving quality inspection information for the electric vehicle instrument sent by the inspection device, the quality inspection information including information on the operated steps, completion time of the operated steps and defective product conditions, and the quality inspection information is used to indicate whether the quality of the electric vehicle instrument is qualified.

[0047] Specifically, the server, as a central control and data processing system, is responsible for receiving data from different devices. The inspection equipment may be an automated inspection tool, sensor, scanning equipment or quality inspection machine on the production line, which transmits quality inspection information to the server in real time through the network. The operated step information indicates the production or inspection steps that have been completed. For example, the production process of electric vehicle instruments may include multiple steps such as welding, assembly, and testing, and the inspection information will record whether each step has been successfully completed. The operated step completion time records the completion time of each production step. Time information helps to evaluate the production progress and can also be used to monitor production efficiency. For example, if the completion time of a step is abnormally long, it may indicate a problem. The defective product status records the status of the product in the quality inspection and indicates whether the electric vehicle instrument is qualified. If the inspection equipment identifies a problem, such as a damaged circuit board or a dark display, the instrument is marked as "unqualified". The server summarizes these inspection information and can be used to evaluate the quality of the entire product. If all operation steps are completed on time and correctly, and no defective products are detected, the server will judge the product as qualified; conversely, if a problem is found in any step, the server can mark it as "unqualified" and issue an alarm.

[0048] In a possible implementation, receiving quality inspection information for electric vehicle instruments sent by a detection device specifically includes: generating quality inspection information after the first inspection link corresponding to the detection device completes the inspection of the electric vehicle instruments; determining the next associated inspection link of the first inspection link from the electronic instruction book to obtain the second inspection link, and the inspection result corresponding to the first inspection link and the inspection result corresponding to the second inspection link have a causal relationship; based on the second inspection link, obtaining and storing the quality inspection information for the electric vehicle instruments sent by the detection device, and the detection device corresponding to the second inspection link includes AR glasses.

[0049] Specifically, in the production process of electric vehicle instruments, there will first be a series of inspection links. The first inspection link usually refers to the first quality inspection step in the production process, such as checking whether the circuit board is firmly welded and whether the screen is clear. The inspection equipment will generate relevant quality inspection information after this link is completed. This information includes whether the inspection step is completed, whether it is qualified, defects that need to be repaired, etc. Once the results of the first inspection link are confirmed, the electronic instruction book will determine the next inspection link to be performed based on this result. For example, if the first inspection link finds a welding problem, the electronic instruction book may instruct to repair the welding or further inspect it in the next link. The second inspection link will be carried out after the first link, which may be to inspect another part of the electric vehicle instrument or to verify the repair of the problem found in the first link. The causal relationship means that the result of the first inspection link directly affects the judgment of the second inspection link. For example, if the first inspection link finds a poor connection of the electric vehicle instrument display screen, the second link may need to verify whether the problem has been repaired, or directly replace the relevant parts. This association ensures that the inspection results of each link are closely connected with the subsequent steps, effectively solving quality problems. The operation and results of the second inspection link are generated by the second inspection equipment, which may include visual inspection equipment, sensors, AR glasses and other equipment. These devices are used to collect quality data of electric vehicle instruments and send this data to the server for processing and storage. AR glasses are used as one of the devices in the second detection link. They not only help staff to view guidance information in real time during the detection process, but also assist in recording specific information of quality inspections, help staff to find problems, and provide instant feedback during the detection process. The quality inspection information obtained by the server, such as whether the inspection is qualified or not, the effect of the repair, etc., will be stored in the server for subsequent analysis, tracing and reporting. This information can provide data support for quality control on the production line, help analyze and avoid the recurrence of similar problems.

[0050] For example, during the production process, the welding process of electric vehicle instruments will be checked by special inspection equipment. Assuming that the inspection equipment detects some loose solder joints in the welding part, the equipment will generate quality inspection information and mark this problem as "bad welding". The electronic instruction book determines the next step to be performed based on the results of the first inspection stage and instructs the operator to enter the display test stage. The display test may include checking brightness, resolution, and color. If a welding problem is found in the first stage, the electronic instruction book may also require the display to be tested for connection problems caused by poor welding. Since poor welding found in the first stage will directly affect the connection quality of the display, the inspection results of the second stage will be affected by the first stage. If the display does not work properly, the system will determine that the problem may be caused by poor welding, and then require the operator to repair the welding problem and re-test. During the display test stage, the operator may wear AR glasses. Through AR glasses, the operator can not only view the steps and repair suggestions in the electronic instruction book in real time, but also see the inspection data of the display. For example, AR glasses may mark areas that need special attention in the corners of the display, or prompt "Check the brightness of the display." All quality inspection information collected by AR glasses and other inspection equipment, such as display brightness test results, display and circuit connectivity, etc., will be stored in the server. These data will support quality traceability and problem analysis in the production process to help confirm whether the electric vehicle instrument meets quality standards and provide a basis for future production improvements.

[0051] S150: Mark the quality detection information into the first image to generate a second image.

[0052] Specifically, quality inspection information refers to specific data about the quality of electric vehicle instruments generated by inspection equipment, such as visual inspection instruments, sensors, etc. Quality inspection information can include multiple aspects, such as completed operation steps, operation completion time, whether defective products appear, whether repair is needed, etc. The first image is displayed to the staff through AR glasses or other devices. It is a real-time image of the production process, such as a staff member operating a part of the electric vehicle instrument, or a graphical display generated by the system. The server integrates the quality inspection information into the first image, such as marking quality problems in a certain area of ​​the image, reminding the staff to pay special attention to the parts, or displaying other information related to quality. In this way, the staff can obtain data related to quality inspection in real time when performing production operations and adjust their operations accordingly. The second image is a new image that contains quality inspection information and the content of the first image. The purpose of generating the second image is to enable the staff to see the quality status of the product more intuitively and help them make decisions. For example, if a part is detected as unqualified, the server will mark the part in the image, which may be marked with a color, such as red, or in the form of arrows, labels, etc., to prompt the staff that there is a problem with the part or require repair. This combination of quality information and images allows workers to quickly identify product problems through visual feedback without having to rely on traditional text descriptions or wait for subsequent manual inspections.

[0053] In a possible implementation, the quality inspection information is marked into the first image to generate the second image, which specifically includes: classifying the quality inspection information to obtain the information of the operated steps, the completion time of the operated steps and the defective product situation; marking the information of the operated steps and the completion time of the operated steps into the dynamic area to obtain the content of the first image, and the dynamic area is used to display or hide the information of the operated steps and the completion time of the operated steps; determining the coordinate information of the defective products according to the defective product situation; marking the coordinate information of the defective products on the electric vehicle instrument in a color coding manner in the spatial coordinate system to generate the content of the second image; and generating the second image according to the content of the first image and the content of the second image.

[0054] Specifically, the information of the operated steps refers to the various operation steps that have been completed in the production process. The completion time of the operated steps indicates the time when each step is completed, which is used to record the time progress of the production process. The defective product situation records the defective product information detected in the production process, such as a component that does not meet the standard or the entire product has defects. The dynamic area refers to an area in the image, which is used to display and hide relevant information. The information of the operated steps and the completion time of the operated steps will be marked in this dynamic area. Specifically, the staff can see the description of the operation steps and the specific time when each step is completed in a certain part of the image. This marking method is dynamic and can be displayed or hidden in different situations. For example, when the staff views it, a specific step can be displayed or some irrelevant information can be hidden as needed. The defective product situation refers to the unqualified products found through quality inspection. In this case, the server will determine the location of the defective products based on the information provided by the quality inspection equipment. These unqualified products can be located by position coordinates. For example, if a problem is found in the contact point of an electric vehicle instrument during the welding process, the system will generate the coordinate information of the component, accurate to the specific location of the production line. The server will use the spatial coordinate system to mark the location of the defective products. This means that the location of defective products will be represented in the form of coordinates on the actual equipment or virtual model of the production line. Color coding is used to distinguish different quality states. For example, red represents unqualified, green represents qualified, and yellow represents inspection required. For example, if there is a defect in the display screen on the instrument panel of an electric vehicle, the system may mark the specific location of the display screen with red to clearly point out the defective part.

[0055] The server will combine the above content to generate a new image for the staff to view. This image not only shows the current working environment and progress, but also displays dynamic information related to quality inspection, such as which steps have been completed and which parts have quality problems, and uses color markings and coordinates to show the location of defective products. Finally, the server will generate a final image based on the content of the first image and the second image. This image contains all the real-time feedback information and can be displayed to the staff through AR glasses or other devices to help them identify quality problems in a timely manner and make corresponding adjustments.

[0056] S160. Display the second image to the staff through the AR glasses.

[0057] Specifically, the server generates a second image, which contains information such as quality inspection information, the status of the operation steps, the completion time, the coordinates of defective products, etc. The server transmits this second image to the AR glasses worn by the staff and displays it to the staff. This means that the staff can see important information related to the current work in real time and directly without relying on traditional display devices or paper instructions. As a display device, AR glasses superimpose the second image on the actual environment in the staff's field of view through augmented reality technology. When working, the staff can not only see the actual production environment, but also see digital information related to the production environment. For example, when assembling an instrument, the staff can simultaneously see the red mark on the device display, indicating the location of a component that is unqualified. Therefore, by reasonably combining electronic instructions with product traceability, the beneficial implementation of electronic instructions is facilitated.

[0058] In one possible implementation, refer to Figure 2 , Figure 2 Another flow chart of a method for implementing an electronic instruction manual for an electric vehicle instrument provided in an embodiment of the present application specifically includes steps S210 to S230, and the above steps are as follows: S210, performing action recognition on the work image to determine the corresponding production action of the staff; S220, calculating the action similarity between the production action and the preset action corresponding to the work content, and judging whether the key production action included in the production action is consistent with the key production action included in the preset action; S230, if it is determined that the action similarity between the production action and the preset action is greater than or equal to the preset threshold, and the key production action included in the production action is consistent with the key production action included in the preset action, then determining that the production action corresponding to the staff is qualified.

[0059] Specifically, in this step, the server uses AR glasses or other camera equipment to capture the actions of the workers. These actions can be various production operations such as welding, assembly, and testing. Motion recognition technology determines the production tasks currently being performed by the workers by analyzing their body movements, such as hand and body postures. For example, the server may identify the hand movements of the workers through video streaming or real-time image processing to determine whether they are performing welding operations. The server compares the actual actions of the workers with the preset standard actions. Preset actions refer to standardized operating procedures set by enterprises or production lines. These preset actions include specific operating specifications for each step, such as how to use tools correctly, how to perform accurate assembly, etc. The server calculates the similarity between the actual actions and the preset actions. The similarity can be measured by different algorithms, such as time series analysis based on actions, key point detection, such as posture, gesture, etc., or machine learning models. If the similarity between the actual production action and the preset action is greater than or equal to the set threshold, it means that the worker's action is in line with expectations. Key production actions refer to actions that must be strictly performed in specific operations. For example, in a welding process, the angle, pressure, and speed of the welding gun may be key factors. If the staff does not perform these key steps correctly when performing a certain job, the product quality may be affected. The server will also check whether the actual action contains the key production actions that are consistent with the preset actions. If the staff omits these key actions during the operation, the server will identify and prompt. If the similarity between the actual production action and the preset action meets the preset standard, that is, the similarity is greater than or equal to the preset threshold, and the actual action contains the key production actions in the preset action, then the action is considered "qualified". If both conditions are met, the server will confirm that the staff's operation is in compliance with the specifications and will not affect product quality.

[0060] In one possible implementation, if it is determined that the action similarity between the production action and the preset action is greater than or equal to a preset threshold, and the key production action included in the production action is inconsistent with the key production action included in the preset action, then the production action corresponding to the staff is determined to be unqualified, or, if it is determined that the action similarity between the production action and the preset action is less than the preset threshold, then the production action corresponding to the staff is determined to be unqualified, and abnormal action alarm information is generated; the abnormal action alarm information is displayed to the staff through AR glasses.

[0061] Specifically, even if the server detects that the worker's actions are highly similar to the standard actions, the server still needs to check whether there are omissions or inconsistencies in key production actions. For example, if the standard operation requires the hand to maintain a stable angle during welding, and the actual operator does not do this, even if the action similarity is high, it will be judged as unqualified. If the similarity is lower than the threshold, that is, the worker's operation is significantly different from the preset standard action, or the key action is inconsistent, that is, the worker does not perform the key action in the standard operation, the server will determine that the production action is "unqualified". The server will generate abnormal action alarm information to remind the worker that his operation does not meet the specifications and may affect product quality. The abnormal action alarm information will be displayed to the worker in real time through AR glasses. AR glasses use augmented reality technology to directly superimpose the alarm information in the worker's field of view, such as in the form of eye-catching red logos, text descriptions or symbols to indicate unqualified operations. In this way, the staff can promptly discover and correct operational errors to ensure the accuracy and quality of the production process.

[0062] The present application also provides a device for implementing an electronic instruction book for an electric vehicle instrument, referring to Figure 3 , Figure 3 A module schematic diagram of an electronic instruction manual implementation device for an electric vehicle instrument provided in an embodiment of the present application, wherein the device is a server, and the server includes an acquisition module 31 and a processing module 32, wherein the acquisition module 31 acquires the process position and work content of the staff in the production work of the electric vehicle instrument, and the staff wears AR glasses; the processing module 32 determines the electronic instruction content from the electronic instruction manual according to the process position and the work content, and generates a first image; the processing module 32 displays the first image to the staff through the AR glasses; the acquisition module 31 receives quality inspection information for the electric vehicle instrument sent by the inspection equipment, the quality inspection information includes information on the operated steps, the completion time of the operated steps, and the defective product situation, and the quality inspection information is used to indicate whether the quality of the electric vehicle instrument is qualified; the processing module 32 marks the quality inspection information to the first image to generate a second image; the processing module 32 displays the second image to the staff through the AR glasses.

[0063] In a possible implementation, the acquisition module 31 acquires the process position and work content of the staff in the production of electric vehicle instruments, specifically including: the acquisition module 31 acquires the position information of the AR glasses; the processing module 32 determines the first position of the staff according to the position information; the acquisition module 31 acquires the working image of the staff taken by the AR glasses; the processing module 32 determines the environment in which the staff is located from the working image and obtains the second position; the processing module 32 determines the process position by combining the first position and the second position; the processing module 32 performs image feature recognition on the working image to determine the work content.

[0064] In a possible implementation, the processing module 32 determines the electronic guidance content from the electronic instruction book according to the process location and the work content, and generates a first image, which specifically includes: the processing module 32 determines the electronic guidance content according to the process location and the work content; the processing module 32 performs text conversion and image conversion on the electronic guidance content to generate voice information and action information; the processing module 32 inputs the voice information and action information into the initial digital human model to generate a target digital human containing voice information for explaining and action information for displaying; the processing module 32 generates a first image based on the target digital human.

[0065] In a possible implementation, the acquisition module 31 receives quality inspection information for electric vehicle instruments sent by the inspection equipment, specifically including: the processing module 32 generates quality inspection information after the first inspection link corresponding to the inspection equipment completes the inspection of the electric vehicle instruments; the processing module 32 determines the next related inspection link of the first inspection link from the electronic instruction book, and obtains the second inspection link, and the inspection result corresponding to the first inspection link has a causal relationship with the inspection result corresponding to the second inspection link; the processing module 32 obtains and stores the quality inspection information for electric vehicle instruments sent by the inspection equipment based on the second inspection link, and the inspection equipment corresponding to the second inspection link includes AR glasses.

[0066] In a possible implementation, the processing module 32 marks the quality inspection information into the first image to generate a second image, which specifically includes: the processing module 32 classifies the quality inspection information to obtain the information of the operated steps, the completion time of the operated steps and the defective product situation; the processing module 32 marks the information of the operated steps and the completion time of the operated steps into the dynamic area to obtain the first image content, and the dynamic area is used to display or hide the information of the operated steps and the completion time of the operated steps; the processing module 32 determines the coordinate information of the defective product according to the defective product situation; the processing module 32 uses color coding to mark the coordinate information of the defective product on the electric vehicle instrument in the spatial coordinate system to generate the second image content; the processing module 32 generates the second image according to the first image content and the second image content.

[0067] In one possible implementation, the processing module 32 performs action recognition on the work image to determine the production action corresponding to the staff member; the processing module 32 calculates the action similarity between the production action and the preset action corresponding to the work content, and determines whether the key production action included in the production action is consistent with the key production action included in the preset action; if the processing module 32 determines that the action similarity between the production action and the preset action is greater than or equal to the preset threshold, and the key production action included in the production action is consistent with the key production action included in the preset action, then it is determined that the production action corresponding to the staff member is qualified.

[0068] In one possible implementation, if the processing module 32 determines that the action similarity between the production action and the preset action is greater than or equal to a preset threshold, and the key production action included in the production action is inconsistent with the key production action included in the preset action, then the production action corresponding to the staff member is determined to be unqualified, or, if the processing module 32 determines that the action similarity between the production action and the preset action is less than a preset threshold, then the production action corresponding to the staff member is determined to be unqualified, and abnormal action alarm information is generated; the processing module 32 displays the abnormal action alarm information to the staff member through AR glasses.

[0069] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0070] The present application also provides an electronic device, referring to Figure 4 , Figure 4 The electronic device may include: at least one processor 41 , at least one network interface 44 , a user interface 43 , a memory 45 , and at least one communication bus 42 .

[0071] The communication bus 42 is used to realize the connection and communication between these components.

[0072] The user interface 43 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 43 may also include a standard wired interface and a wireless interface.

[0073] The network interface 44 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0074] Among them, the processor 41 may include one or more processing cores. The processor 41 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 45, and calling data stored in the memory 45. Optionally, the processor 41 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 41 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 41, and it can be implemented separately through a chip.

[0075] Among them, the memory 45 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 45 includes a non-transitory computer-readable storage medium. The memory 45 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 45 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory 45 may also be optionally at least one storage device located away from the aforementioned processor 41. As Figure 4 As shown, the memory 45 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program for implementing a method for an electronic instruction book for an electric vehicle instrument.

[0076] exist Figure 4In the electronic device shown, the user interface 43 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 41 can be used to call an application program stored in the memory 45 for implementing a method for an electronic instruction manual for an electric vehicle instrument. When executed by one or more processors, the electronic device executes one or more methods in the above-mentioned embodiments.

[0077] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0078] The present application also provides a computer-readable storage medium, which stores instructions. When executed by one or more processors, the electronic device executes one or more of the methods described in the above embodiments.

[0079] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0080] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0081] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0082] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0083] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0084] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, it will be easy for those skilled in the art to think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure. The description and examples are regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for implementing an electronic instruction manual for an electric vehicle instrument, characterized in that: The method comprises: Obtaining the process location and work content of a worker in the production of electric vehicle instruments, wherein the worker wears AR glasses; According to the process position and the work content, determine the electronic instruction content from the electronic instruction book to generate a first image; Displaying the first image to the staff member through the AR glasses; Receiving quality inspection information for the electric vehicle instrument sent by the inspection device, the quality inspection information including information of the operated steps, completion time of the operated steps and defective product conditions, the quality inspection information is used to indicate whether the quality of the electric vehicle instrument is qualified; Annotating the quality detection information into the first image to generate a second image; The second image is displayed to the staff member through the AR glasses.

2. The method for implementing the electronic instruction book of electric vehicle instrument according to claim 1, characterized in that: The obtaining of the process position and work content of the staff in the production of electric vehicle instruments specifically includes: Obtaining location information of the AR glasses; Determining a first position of the staff member according to the position information; Acquire a working image of the staff member captured by the AR glasses; Determine the environment where the worker is located from the work image to obtain a second position; Determine the process position by combining the first position and the second position; Image feature recognition is performed on the work image to determine the work content.

3. The method for implementing the electronic instruction book of electric vehicle instrument according to claim 1, characterized in that: The step of determining electronic instruction content from the electronic instruction book according to the process position and the work content and generating the first image specifically includes: Determining the electronic guidance content according to the process location and the work content; Performing text conversion and image conversion on the electronic guidance content to generate voice information and action information; Inputting the voice information and the action information into an initial digital human model to generate a target digital human including information for explaining the voice information and displaying the action information; The first image is generated according to the target digital human.

4. The method for implementing the electronic instruction book of electric vehicle instrument according to claim 1, characterized in that: The quality inspection information for the electric vehicle instrument sent by the receiving inspection device specifically includes: After the first detection link corresponding to the detection device detects the electric vehicle instrument, quality detection information is generated; Determine the next associated detection link of the first detection link from the electronic instruction book to obtain a second detection link, wherein the detection result corresponding to the first detection link and the detection result corresponding to the second detection link have a causal relationship; Based on the second detection link, quality detection information on the electric vehicle instrument sent by the detection device is obtained and stored, and the detection device corresponding to the second detection link includes the AR glasses.

5. The method for implementing the electronic instruction book of electric vehicle instrument according to claim 1, characterized in that: The step of marking the quality detection information into the first image to generate the second image specifically includes: Classify and process the quality inspection information to obtain the information of the operated steps, the completion time of the operated steps, and the defective product situation; Marking the information of the operated steps and the completion time of the operated steps in a dynamic area to obtain a first image content, wherein the dynamic area is used to display or hide the information of the operated steps and the completion time of the operated steps; According to the defective product situation, determine the coordinate information of the defective product; In the spatial coordinate system, the coordinate information of the defective product is marked on the electric vehicle instrument in a color coding manner to generate a second image content; The second image is generated according to the first image content and the second image content.

6. The method for implementing the electronic instruction book of electric vehicle instrument according to claim 2, characterized in that: The method further comprises: Performing action recognition on the work image to determine the production action corresponding to the worker; Calculating the action similarity between the production action and the preset action corresponding to the work content, and determining whether the key production action included in the production action is consistent with the key production action included in the preset action; If it is determined that the action similarity between the production action and the preset action is greater than or equal to a preset threshold, and the key production actions included in the production action are consistent with the key production actions included in the preset action, then it is determined that the production action corresponding to the staff member is qualified.

7. The method for implementing the electronic instruction book of electric vehicle instrument according to claim 6 is characterized in that: The method further comprises: If it is determined that the action similarity between the production action and the preset action is greater than or equal to the preset threshold, and the key production action included in the production action is inconsistent with the key production action included in the preset action, then it is determined that the production action corresponding to the worker is unqualified, or, If it is determined that the action similarity between the production action and the preset action is less than a preset threshold, the production action corresponding to the worker is determined to be unqualified, and abnormal action alarm information is generated; The abnormal action alarm information is displayed to the staff through the AR glasses.

8. A device for implementing electronic instruction manual for electric vehicle instrument, characterized in that: The device comprises an acquisition module (31) and a processing module (32), wherein: The acquisition module (31) is used to acquire the process position and work content of a worker in the production of electric vehicle instruments, wherein the worker wears AR glasses; The processing module (32) is used to determine the electronic instruction content from the electronic instruction book according to the process position and the work content, and generate a first image; The processing module (32) is further used to display the first image to the staff member through the AR glasses; The acquisition module (31) is further used to receive quality inspection information for the electric vehicle instrument sent by the inspection device, the quality inspection information including information on the operated steps, completion time of the operated steps and defective product conditions, and the quality inspection information is used to indicate whether the quality of the electric vehicle instrument is qualified; The processing module (32) is further used to mark the quality detection information into the first image to generate a second image; The processing module (32) is also used to display the second image to the staff through the AR glasses.

9. An electronic device, characterized in that: The electronic device comprises a processor (41), a memory (45), a user interface (43) and a network interface (44), wherein the memory (45) is used to store instructions, the user interface (43) and the network interface (44) are both used to communicate with other devices, and the processor (41) is used to execute the instructions stored in the memory (45) so that the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is performed.

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