Aluminum alloy workpiece data acquisition and analysis method, device and system

Abstract

The invention relates to the technical field of production detection, in particular to an aluminum alloy workpiece data acquisition and analysis method, device and system, and the method comprises the steps: conveying a to-be-detected aluminum alloy workpiece which is engraved with a two-dimensional code through laser through an assembly line; scanning the two-dimensional code on the aluminum alloy workpiece to obtain a scanning image; comparing the size of the two-dimensional code in the scanned image with a preset standard size to detect whether the two-dimensional code is complete; decoding data obtained based on the scanned image is compared with a preset rule base so as to confirm whether the two-dimensional code follows a correct coding specification or not; checking whether the two-dimensional code has a repeated marking phenomenon or not based on decoding data obtained by scanning the image; when it is detected that the two-dimensional code is incompletely marked, the marking rule is wrong or marking is repeated, an alarm notice is sent out. Therefore, the workpiece information can be automatically detected, corresponding problems can be found in time, and the working efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of production detection technology, and in particular to a method, device and system for collecting and analyzing data of an aluminum alloy workpiece. Background Art

[0002] Aluminum alloys have been widely used in many industries due to their light weight, high strength, good conductivity and corrosion resistance, especially in aerospace, automobile manufacturing, architectural decoration, electronics and electrical appliances.

[0003] In the production process of aluminum alloy workpieces, in order to ensure that each production link can be effectively monitored and managed, it is usually necessary to mark relevant information on the workpiece. This information is not only crucial for quality control, but also helps track production progress, optimize process flow, and improve the response speed of after-sales service. However, the traditional information marking inspection method mainly relies on manual sampling, which has obvious limitations, specifically in the following aspects:

[0004] Inefficiency: Manual sampling requires a lot of human resources, especially when the production line is large and the product variety is wide, the workload of the inspectors will increase significantly. This model is not only time-consuming and labor-intensive, but also easily causes production bottlenecks and affects overall production efficiency.

[0005] Highly subjective: The results of manual inspections are largely dependent on the experience and personal judgment of the inspector, and there may be large differences between different inspectors. This may lead to inconsistent inspection results and make it difficult to ensure that all workpieces meet the same standards.

[0006] Error-prone: Long manual inspections can easily cause fatigue to inspectors, increasing the probability of missed or mis-inspected inspections. Once key information is omitted or recorded incorrectly, it may lead to serious quality problems and even affect the safety and reliability of the final product.

[0007] Difficult to trace: When a product has a problem, it is often difficult to quickly and accurately find the root cause of the problem if only manually recorded information is relied upon. This not only prolongs the time to solve the problem, but may also cause greater losses due to the failure to take timely measures. Summary of the invention

[0008] The object of the present invention is to provide a method, device and system for collecting and analyzing data of an aluminum alloy workpiece, so as to automatically detect workpiece information, thereby timely discovering corresponding problems and improving work efficiency.

[0009] To achieve the above-mentioned object, in a first aspect, the present invention provides a method for collecting and analyzing data of an aluminum alloy workpiece, comprising conveying an aluminum alloy workpiece to be inspected and having a laser-engraved two-dimensional code through an assembly line;

[0010] Scan the QR code on the aluminum alloy workpiece to obtain a scanned image;

[0011] Compare the size of the QR code in the scanned image with the preset standard size to detect whether the QR code is complete;

[0012] The decoded data obtained based on the scanned image is compared with the preset rule library to confirm whether the QR code follows the correct encoding specification;

[0013] Check whether the QR code has repeated marking based on the decoded data obtained from the scanned image;

[0014] When it is detected that the QR code is incompletely marked, the marking rules are wrong, or the marking is repeated, an alarm notification will be issued.

[0015] Wherein, after issuing an alarm notification when it is detected that the two-dimensional code is incompletely marked, the marking rules are wrong, or the marking is repeated, the method also includes using a pushing mechanism to remove the problematic workpiece from the conveyor line.

[0016] The specific steps of scanning the two-dimensional code on the aluminum alloy workpiece to obtain the scanned image include:

[0017] Set the shooting parameters of the QR code reading device;

[0018] Provide fill light to the shooting area;

[0019] Aim the QR code reading device at the QR code on the aluminum alloy workpiece to obtain a scanned image.

[0020] The specific steps of comparing the size of the two-dimensional code in the scanned image with the preset standard size to detect whether the two-dimensional code is complete include:

[0021] Determine the theoretical size of the QR code based on the standard specifications of the QR code to be marked;

[0022] Preprocessing the scanned QR code image;

[0023] Calculate the actual width and height of the QR code based on the edge detection result of the QR code image;

[0024] Set the tolerance range and compare the measured actual size of the QR code with the preset standard size to detect whether the QR code is complete.

[0025] The specific steps of calculating the actual width and height of the two-dimensional code based on the edge detection result of the two-dimensional code image include:

[0026] Convert the color QR code image to grayscale image;

[0027] Use Gaussian filtering to remove noise from grayscale images;

[0028] Use edge detection algorithms such as Canny to identify edges in grayscale images;

[0029] Apply contour finding algorithm to extract all closed contours from the edge detected image;

[0030] Use the minimum area rectangle to determine the exact location and orientation of the QR code;

[0031] Calculate the width and height of the minimum area rectangle to get the actual size of the QR code.

[0032] The specific steps of comparing the decoded data obtained based on the scanned image with the preset rule base to confirm whether the two-dimensional code complies with the correct encoding specification include:

[0033] Establish a rule base containing all relevant coding rules;

[0034] Applying a two-dimensional code decoding algorithm to decode the scanned image;

[0035] Extracting key information of the QR code from the decoded data, the key information including version number, error correction level, data type and data content;

[0036] The extracted key information of the QR code is compared item by item with the corresponding rules in the preset rule library. If all the compared items comply with the provisions in the rule library, it is considered that the QR code follows the correct encoding specification.

[0037] The specific steps of checking whether the two-dimensional code has repeated marking based on the decoded data obtained from the scanned image include:

[0038] Create a QR code database for aluminum alloy workpieces;

[0039] Applying a two-dimensional code decoding algorithm to decode the scanned image;

[0040] Each time a new QR code is scanned, the database is first queried to see if the same QR code data already exists; if the query result is empty, it means that the QR code is new, and the QR code data is stored in the aluminum alloy workpiece QR code database; if the query result is not empty, it means that the QR code already exists in the database, that is, there is a duplicate marking phenomenon.

[0041] In a second aspect, the present invention further provides an aluminum alloy workpiece data acquisition and analysis device, including a conveying module, a scanning module, a size judgment module, a coding judgment module, a repeated marking judgment module and an alarm module:

[0042] The conveying module is used to convey the aluminum alloy workpiece to be inspected with the laser-engraved QR code through the assembly line;

[0043] The scanning module is used to scan the two-dimensional code on the aluminum alloy workpiece to obtain a scanned image;

[0044] The size judgment module is used to compare the size of the QR code in the scanned image with a preset standard size to detect whether the QR code is complete;

[0045] The coding judgment module is used to compare the decoded data obtained based on the scanned image with a preset rule library to confirm whether the QR code complies with the correct coding specification;

[0046] The repeated marking judgment module is used to check whether there is repeated marking in the two-dimensional code based on the decoded data obtained by scanning the image;

[0047] The alarm module is used to issue an alarm notification when it is detected that the two-dimensional code is not fully marked, the marking rule is wrong, or the marking is repeated.

[0048] In a third aspect, the present invention further provides an aluminum alloy workpiece data acquisition and analysis system, comprising the aluminum alloy workpiece data acquisition and analysis device described above.

[0049] A method, device and system for data collection and analysis of aluminum alloy workpieces of the present invention, first, the aluminum alloy workpieces to be detected are placed on the production line. Two-dimensional codes have been pre-engraved on these workpieces using laser technology. Laser engraving can not only provide high-precision identification, but also has strong durability and corrosion resistance, and is suitable for long-term use in industrial environments. As the workpiece moves along the production line, it will pass through a specially set scanning area, in which a high-precision image acquisition device is installed to capture the two-dimensional code image on the surface of the workpiece. This process needs to ensure that the image clarity is high enough for subsequent processing. The acquired two-dimensional code scan image will be transmitted to a computer system, and the size of the two-dimensional code in the image will be measured by special software, and compared with the preset standard size. If it is found that there is a significant difference between the actual size and the standard, it may mean that there is a problem with the two-dimensional code during the engraving process, such as incomplete engraving or poor engraving quality. Next, the system will decode the scanned two-dimensional code image and extract the information content contained therein. Then, this information is matched with a pre-established rule library to check whether the two-dimensional code is encoded according to the established format and rules. This step helps ensure that all QR codes can correctly represent the required information. In addition, the decoded data needs to be further analyzed to determine whether there are multiple identical QR codes on the same workpiece, that is, repeated marking. This situation may be caused by errors in the production process and must be identified and handled in a timely manner. Throughout the inspection process, once any non-conformity is found - whether it is a QR code size discrepancy, an incorrect encoding rule, or repeated marking - the system will immediately trigger an alarm mechanism and send a notification to the operator. This allows the problem to be quickly located and appropriate corrective measures to be taken to prevent defective products from flowing into the next process or the final product. Through the above methods, the management effectiveness of workpiece production can be improved and production efficiency can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0051] Figure 1 The present invention is a flow chart of a method for collecting and analyzing aluminum alloy workpiece data.

[0052] Figure 2 The present invention is a flow chart of scanning a two-dimensional code on an aluminum alloy workpiece to obtain a scanned image.

[0053] Figure 3It is a flow chart of the present invention for comparing the size of a two-dimensional code in a scanned image with a preset standard size to detect whether the two-dimensional code is complete.

[0054] Figure 4 It is a flow chart of calculating the actual width and height of a two-dimensional code based on the edge detection result of a two-dimensional code image of the present invention.

[0055] Figure 5 It is a flowchart of the present invention for comparing the decoded data obtained based on the scanned image with a preset rule library to confirm whether the two-dimensional code complies with the correct encoding specification.

[0056] Figure 6 It is a flow chart of the present invention for checking whether a two-dimensional code has repeated marking based on decoded data obtained from a scanned image. DETAILED DESCRIPTION

[0057] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0058] First embodiment

[0059] See also Figure 1 to Figure 6 The present invention provides a method for collecting and analyzing data of an aluminum alloy workpiece, comprising:

[0060] S101 conveys aluminum alloy workpieces with laser-engraved QR codes to be inspected through the assembly line;

[0061] The workpiece first goes through a laser engraving process to accurately engrave a QR code on its surface. Subsequently, these aluminum alloy workpieces with QR codes are placed on the assembly line and transported by the assembly line system at a predetermined speed and path until they reach the designated inspection position. This process not only improves the efficiency of workpiece transmission, but also ensures the stability and safety of the workpiece during transmission, providing a good foundation for subsequent QR code recognition and information reading.

[0062] S102 scans the two-dimensional code on the aluminum alloy workpiece to obtain a scanned image;

[0063] The specific steps include:

[0064] S201 sets the shooting parameters of the QR code reading device;

[0065] First, adjust the focal length of the camera according to the size of the QR code and the flatness of the workpiece surface to ensure that the QR code image is clearly visible. Adjust the exposure time and gain value to adapt to different lighting conditions to avoid the image being too bright or too dark. Set the appropriate resolution to ensure that the details of the QR code image can be accurately captured, while also considering the processing speed requirements.

[0066] S202 provides supplementary lighting to the shooting area;

[0067] Check the natural lighting conditions in the shooting area. If the light is insufficient, you need to add auxiliary light. Choose the appropriate light source type, such as LED light or ring light, to provide uniform and stable lighting. Adjust the angle and intensity of the light to avoid shadows or reflections that affect the recognition of the QR code.

[0068] S203: Aim the two-dimensional code reading device at the two-dimensional code on the aluminum alloy workpiece to obtain a scanned image.

[0069] Fix the QR code reader in an appropriate position to ensure that the camera can be vertically aligned with the QR code to reduce distortion. Use the display or real-time preview function to adjust the position and angle of the device so that the QR code is completely within the shooting area. Trigger the shooting command to obtain a high-definition image of the QR code.

[0070] S103 compares the size of the QR code in the scanned image with a preset standard size to detect whether the QR code is complete;

[0071] The specific steps include:

[0072] S301 determines the theoretical size of the two-dimensional code according to the standard specification of the two-dimensional code to be marked;

[0073] Refer to the international or internal standards of the QR code to obtain the size specifications of the QR code, including side length, module size, etc. Record the standard dimensions of the QR code, such as the theoretical width and height of the QR code, and the size of each module. Use these dimensions as a benchmark for subsequent testing to compare actual measurement results.

[0074] S302 pre-processes the scanned two-dimensional code image;

[0075] Read the scanned QR code image from the storage device. Convert the color QR code image to a grayscale image to reduce the amount of calculation and simplify subsequent processing. Use Gaussian filtering, median filtering and other methods to remove image noise and improve the accuracy of edge detection.

[0076] S303 calculates the actual width and height of the two-dimensional code based on the edge detection result of the two-dimensional code image;

[0077] The specific steps include:

[0078] S401 converts the color QR code image into a grayscale image;

[0079] Convert color images to grayscale for subsequent processing.

[0080] S402 uses Gaussian filtering to remove noise in the grayscale image;

[0081] Use Gaussian filter to remove noise from the image and improve the accuracy of edge detection.

[0082] S403 uses edge detection algorithms such as Canny to identify edges in grayscale images;

[0083] Use the Canny algorithm or other edge detection algorithms to identify the edges in the grayscale image and highlight the outline of the QR code.

[0084] S404 applies a contour search algorithm to extract all closed contours from the edge-detected image;

[0085] Use a contour search algorithm (such as the findContours function in OpenCV) to extract all closed contours from the edge-detected image. Filter out the contour that is most likely to be a QR code from all the extracted contours, which can usually be determined by checking whether the four corner points of the contour are close to a square.

[0086] S405 uses a minimum area rectangle to determine the precise position and orientation of the QR code;

[0087] Use a minimum area rectangle (such as the minAreaRect function in OpenCV) to determine the exact position and orientation of the QR code, ensuring that the four corners of the QR code are accurately identified.

[0088] S406 calculates the width and height of the minimum area rectangle to obtain the actual size of the two-dimensional code.

[0089] By calculating the width and height of the minimum area rectangle, the actual size of the QR code is obtained. These sizes will be used for subsequent comparison and verification.

[0090] S304 sets a tolerance range, and compares the measured actual size of the two-dimensional code with a preset standard size to detect whether the two-dimensional code is complete.

[0091] According to actual needs, set a reasonable tolerance range. For example, you can set a tolerance range of ±5% to allow a certain error. Compare the measured actual size of the QR code with the preset standard size. If the actual size is within the set tolerance range, the QR code is considered complete; otherwise, the QR code is considered incomplete. Record the test results, including the actual size of the QR code and the conclusion of whether it is complete, for subsequent quality control and data analysis.

[0092] S104 compares the decoded data obtained based on the scanned image with a preset rule library to confirm whether the QR code complies with the correct encoding specification;

[0093] The specific steps include:

[0094] S501 establishes a rule base including all relevant coding rules;

[0095] Collect and organize QR code encoding rules, including international standards (such as ISO / IEC 18004) and industry standards. Clarify the specific content of each rule, such as the range of version numbers, error correction level options, supported data types, etc. Organize these rules into a structured rule base for subsequent comparison and verification. The rule base can be a database table, configuration file, or a dedicated rule management platform.

[0096] S502 applies a two-dimensional code decoding algorithm to decode the scanned image;

[0097] Select a suitable QR code decoding algorithm, such as ZXing (Zebra Crossing), Libdmtx, etc. These algorithms can efficiently extract the QR code data from the image. Use the selected decoding algorithm to decode the scanned QR code image and convert the QR code data in the image into readable text or binary format.

[0098] S503 extracts key information of the QR code from the decoded data, wherein the key information includes a version number, an error correction level, a data type, and data content;

[0099] Analyze the decoded data and extract the key information of the QR code. This key information usually includes:

[0100] Version number: Indicates the size and complexity of the QR code.

[0101] Error correction level: Indicates the error correction capability of the QR code, usually there are four levels: L, M, Q, and H.

[0102] Data Type: Indicates the type of data stored in the QR code, such as numbers, alphanumerics, bytes, etc.

[0103] Data content: the specific information actually stored in the QR code, such as product number, website address, text, etc.

[0104] S504 compares the extracted key information of the QR code with the corresponding rules in the preset rule library item by item. If all the compared items meet the requirements in the rule library, it is considered that the QR code complies with the correct encoding specification.

[0105] Check whether the extracted version number is within the range specified by the rule base. For example, the standard stipulates that the version number should be between 1 and 40. Verify whether the extracted error correction level complies with the provisions in the rule base. For example, the standard stipulates that the error correction level should be one of L, M, Q, and H. Confirm whether the extracted data type is in the list of types supported by the rule base. For example, the data types supported by the standard include numbers, alphanumerics, bytes, etc. Check whether the data content meets specific format requirements. For example, if the data content is a product number, it is necessary to verify whether its format is correct; if it is a URL, it is necessary to verify whether it complies with the URL format. If all comparison items comply with the provisions in the rule base, it is considered that the QR code follows the correct encoding specifications; if any one does not comply with the regulations, it is considered that the QR code has encoding errors or is not standardized.

[0106] S105 checks whether the two-dimensional code has repeated marking based on the decoded data obtained from the scanned image;

[0107] The specific steps include:

[0108] S601 creates a QR code database for aluminum alloy workpieces;

[0109] Determine the table structure of the database, including the unique identifier of the QR code, decoded data, marking time, corresponding workpiece information and other fields. Select a suitable database management system, such as MySQL, PostgreSQL, SQLite, etc., and select the most suitable system based on actual needs and resources. Create database tables and initialize necessary indexes and constraints to ensure efficient storage and query of data.

[0110] S602 applies a two-dimensional code decoding algorithm to decode the scanned image;

[0111] Select an efficient QR code decoding algorithm, such as ZXing (Zebra Crossing), Libdmtx, etc. These algorithms can quickly and accurately extract the QR code data from the image. Use the selected decoding algorithm to decode the scanned QR code image and convert the QR code data in the image into readable text or binary format. Check whether the decoding result is valid and ensure that the decoded data is complete and correct.

[0112] S603 Each time a new QR code is scanned, it first queries whether the same QR code data already exists in the database; if the query result is empty, it means that the QR code is new, and the QR code data is stored in the aluminum alloy workpiece QR code database; if the query result is not empty, it means that the QR code already exists in the database, that is, there is a duplicate marking phenomenon.

[0113] Extract the unique identifier or key information of the QR code from the decoding result, such as the text content of the QR code. Use the extracted unique identifier or key information to query whether the same QR code data already exists in the database. Write an SQL query statement, such as SELECT * FROM qr_code_database WHERE unique_identifier = 'extracted unique identifier'.

[0114] If the query result is empty, it means that the QR code is new. The newly scanned QR code data is stored in the database, including the unique identification of the QR code, decoding data, marking time, corresponding workpiece information, etc. Record the storage log of the new QR code for subsequent tracking and auditing.

[0115] If the query result is not empty, it means that the QR code already exists in the database, that is, there is a duplicate marking phenomenon. Record the duplicate marking event, including the duplicate QR code data, scanning time, operator information, etc. Trigger an alarm or notification mechanism to remind relevant personnel to pay attention to the duplicate marking phenomenon so that timely measures can be taken.

[0116] S106 issues an alarm notification when it is detected that the two-dimensional code is not fully engraved, the marking rule is wrong, or the marking is repeated.

[0117] In the previous step, if any of the following problems are detected in the QR code, an alarm notification will be triggered immediately:

[0118] Incomplete marking: Part of the QR code is missing or damaged, making it impossible to fully decode.

[0119] Marking rule error: The key information of the QR code, such as version number, error correction level, data type, etc., does not conform to the preset encoding specifications.

[0120] Duplicate marking: The QR code already exists in the database, indicating duplicate marking.

[0121] Generate detailed alarm information based on the specific problems detected, including:

[0122] Problem type: Incomplete marking, incorrect marking rules, or repeated marking.

[0123] Artifact Number: The artifact number or unique identifier where the problem occurred.

[0124] Detection time: The specific time when the problem was detected.

[0125] Operator information: the name or work number of the current operator (if any).

[0126] Detailed description: Describe the problem in detail, such as which part of the QR code is missing, which rules are not met, etc.

[0127] Sending an alarm notification can display a red warning sign on the production line's operation interface and pop up an alarm information window to attract the operator's attention. It can also play a preset alarm sound, such as a beep or voice prompt, to ensure that the operator can respond quickly.

[0128] S107 uses a push mechanism to remove problematic workpieces from the conveyor line.

[0129] When a problem artifact is detected, the system marks the artifact and passes its location information to the push mechanism.

[0130] Use a robotic arm to grab the problem workpiece from the conveyor line and move it to the designated defective product area. Install a cylinder push rod at a specific position on the conveyor line. When the problem workpiece reaches this position, the cylinder push rod pushes the workpiece out of the conveyor line. Use an electric push rod to push the problem workpiece out of the conveyor line and also move it to the defective product collection area.

[0131] After the push mechanism completes the action, the system will confirm that the workpiece has been successfully removed and update the workpiece status information. The removed workpiece information is recorded in the system, including the workpiece number, removal time, removal reason, etc., for subsequent tracking and analysis. After the problematic workpiece is removed, the conveyor line continues to operate normally to ensure that the production process is not affected.

[0132] Through the above steps, it can be ensured that when the QR code is detected to be incomplete, the marking rules are wrong, or the marking is repeated, an alarm notification can be issued in time, and the push mechanism can be used to remove the problematic workpiece from the conveyor line. This not only helps to improve production efficiency and product quality, but also reduces the subsequent processing costs and customer complaints caused by problematic workpieces.

[0133] Second embodiment

[0134] The present invention also provides an aluminum alloy workpiece data acquisition and analysis device, comprising a conveying module, a scanning module, a size judgment module, a coding judgment module, a repeated marking judgment module and an alarm module: the conveying module is used to convey the aluminum alloy workpiece to be detected with a laser-engraved two-dimensional code through an assembly line; the scanning module is used to scan the two-dimensional code on the aluminum alloy workpiece to obtain a scanned image; the size judgment module is used to compare the size of the two-dimensional code in the scanned image with a preset standard size to detect whether the two-dimensional code is complete; the coding judgment module is used to compare the decoded data obtained based on the scanned image with a preset rule library to confirm whether the two-dimensional code follows the correct coding specification; the repeated marking judgment module is used to check whether the two-dimensional code has repeated marking based on the decoded data obtained from the scanned image; the alarm module is used to issue an alarm notification when it is detected that the two-dimensional code is incompletely marked, the marking rule is wrong, or the marking is repeated.

[0135] In this embodiment, the conveying module conveys the aluminum alloy workpiece to be inspected through the assembly line. A workpiece placement area is set at the starting point of the assembly line, and the operator places the aluminum alloy workpiece to be inspected at the designated position. The conveying speed of the assembly line is adjusted by the motor and the controller to ensure that the workpiece stays at each inspection station for a sufficient time.

[0136] The scanning module uses a high-resolution, high-speed industrial camera to ensure that the QR code image can be clearly captured. Appropriate fill light equipment is set in the scanning area to ensure that the brightness and contrast of the QR code image are appropriate. The camera is aimed at the QR code on the workpiece, captures a high-quality image, and transmits the image data to the subsequent processing module.

[0137] The size judgment module compares the size of the QR code in the scanned image with the preset standard size to detect whether the QR code is complete. Specifically, the theoretical size of the QR code is determined according to the international standard or internal standard of the QR code. The scanned QR code image is grayed and denoised to improve the image quality. The outline of the QR code is identified using edge detection algorithms such as Canny. The actual width and height of the QR code are calculated using the minimum area rectangle. The calculated actual size is compared with the preset standard size to determine whether the QR code is complete.

[0138] The coding judgment module compares the decoded data obtained based on the scanned image with the preset rule base to confirm whether the QR code follows the correct coding specifications. Specifically, a rule base containing all relevant coding rules is established, including version number, error correction level, data type, etc. An efficient QR code decoding algorithm (such as ZXing) is used to decode the scanned image to extract the key information of the QR code. The version number, error correction level, data type and data content of the QR code are extracted from the decoded data. The extracted key information of the QR code is compared item by item with the corresponding rules in the rule base to determine whether the QR code follows the correct coding specifications.

[0139] The duplicate marking judgment module creates a database containing all marked QR code data, recording the unique identifier and related information of each QR code. Each time a new QR code is scanned, the unique identifier or key information of the QR code is extracted using a decoding algorithm. The database is queried to see if the same QR code data already exists. If the query result is empty, it means that the QR code is new, and its data is stored in the database; if the query result is not empty, it means that there is a duplicate marking phenomenon, and the relevant event is recorded and an alarm is generated.

[0140] The alarm module will trigger an alarm immediately if any problem is detected in the size judgment module, coding judgment module and repeated marking judgment module. Detailed alarm information will be generated, including problem type, workpiece number, detection time, operator information, etc.

[0141] Third embodiment

[0142] The present invention further provides an aluminum alloy workpiece data acquisition and analysis system, comprising an aluminum alloy workpiece data acquisition and analysis device in the second embodiment.

[0143] The aluminum alloy workpiece data acquisition and analysis system provided by the present invention is a comprehensive solution, which aims to comprehensively improve the data acquisition and analysis capabilities in the production process of aluminum alloy workpieces. The system not only covers hardware equipment, but also includes software platforms and data management modules to ensure the automation and intelligence of the entire process from workpiece transportation, QR code scanning, size judgment, coding judgment, repeated marking judgment to alarm notification.

[0144] The data management platform centrally manages all collected data and provides functions such as data storage, query, analysis and report generation.

[0145] Use high-performance database systems (such as MySQL, PostgreSQL, Oracle, etc.) to store all workpiece data and test results. Perform regular data backup to ensure data security and integrity. Provide flexible data query functions, support query by workpiece number, test time, test results and other conditions. Integrate data analysis tools to perform statistical analysis on the collected data and generate various reports and charts to help managers understand production status and quality issues. Support data export function, conveniently export data to Excel, CSV and other formats for use by other systems or tools.

[0146] What is disclosed above is only a preferred embodiment of the present invention, and it certainly cannot be used to limit the scope of rights of the present invention. Ordinary technicians in this field can understand that all or part of the processes of the above embodiment and equivalent changes made according to the claims of the present invention still fall within the scope of the invention.

Claims

1. A method for collecting and analyzing data of aluminum alloy workpieces. It is characterized in that The method comprises: conveying an aluminum alloy workpiece to be inspected and having a laser-engraved QR code through an assembly line; Scan the QR code on the aluminum alloy workpiece to obtain a scanned image; Compare the size of the QR code in the scanned image with the preset standard size to detect whether the QR code is complete; The decoded data obtained based on the scanned image is compared with the preset rule library to confirm whether the QR code follows the correct encoding specification; Check whether the QR code has repeated marking based on the decoded data obtained from the scanned image; When it is detected that the QR code is incompletely marked, the marking rules are wrong, or the marking is repeated, an alarm notification will be issued.

2. The method for collecting and analyzing data of an aluminum alloy workpiece according to claim 1, characterized in that: After issuing an alarm notification when it is detected that the two-dimensional code is incompletely marked, the marking rule is wrong, or the marking is repeated, the method also includes using a pushing mechanism to remove the problematic workpiece from the conveyor line.

3. The method for collecting and analyzing data of an aluminum alloy workpiece according to claim 2, characterized in that: The specific steps of scanning the two-dimensional code on the aluminum alloy workpiece to obtain the scanned image include: Set the shooting parameters of the QR code reading device; Provide fill light to the shooting area; Aim the QR code reading device at the QR code on the aluminum alloy workpiece to obtain a scanned image.

4. The method for collecting and analyzing data of an aluminum alloy workpiece according to claim 3, characterized in that: The specific steps of comparing the size of the two-dimensional code in the scanned image with the preset standard size to detect whether the two-dimensional code is complete include: Determine the theoretical size of the QR code based on the standard specifications of the QR code to be marked; Preprocessing the scanned QR code image; Calculate the actual width and height of the QR code based on the edge detection result of the QR code image; Set the tolerance range and compare the measured actual size of the QR code with the preset standard size to detect whether the QR code is complete.

5. The method for collecting and analyzing data of an aluminum alloy workpiece according to claim 4, characterized in that: The specific steps of calculating the actual width and height of the two-dimensional code based on the edge detection result of the two-dimensional code image include: Convert the color QR code image to grayscale image; Use Gaussian filtering to remove noise from grayscale images; Use edge detection algorithms such as Canny to identify edges in grayscale images; Apply contour finding algorithm to extract all closed contours from the edge detected image; Use the minimum area rectangle to determine the exact location and orientation of the QR code; Calculate the width and height of the minimum area rectangle to get the actual size of the QR code.

6. The method for collecting and analyzing data of an aluminum alloy workpiece according to claim 5, characterized in that: The specific steps of comparing the decoded data obtained based on the scanned image with the preset rule library to confirm whether the QR code complies with the correct encoding specification include: Establish a rule base containing all relevant coding rules; Applying a two-dimensional code decoding algorithm to decode the scanned image; Extracting key information of the QR code from the decoded data, the key information including version number, error correction level, data type and data content; The extracted key information of the QR code is compared item by item with the corresponding rules in the preset rule library. If all the compared items comply with the provisions in the rule library, it is considered that the QR code follows the correct encoding specification.

7. The method for collecting and analyzing data of an aluminum alloy workpiece according to claim 6, characterized in that: The specific steps of checking whether the two-dimensional code has repeated marking based on the decoded data obtained from the scanned image include: Create a QR code database for aluminum alloy workpieces; Applying a two-dimensional code decoding algorithm to decode the scanned image; Each time a new QR code is scanned, the database is first queried to see if the same QR code data already exists; if the query result is empty, it means that the QR code is new, and the QR code data is stored in the aluminum alloy workpiece QR code database; if the query result is not empty, it means that the QR code already exists in the database, that is, there is a duplicate marking phenomenon.

8. An aluminum alloy workpiece data collection and analysis device, applied to an aluminum alloy workpiece data collection and analysis method according to any one of claims 1 to 7, characterized in that: It includes conveying module, scanning module, size judgment module, encoding judgment module, repeated marking judgment module and alarm module: The conveying module is used to convey the aluminum alloy workpiece to be inspected with the laser-engraved QR code through the assembly line; The scanning module is used to scan the two-dimensional code on the aluminum alloy workpiece to obtain a scanned image; The size judgment module is used to compare the size of the QR code in the scanned image with a preset standard size to detect whether the QR code is complete; The coding judgment module is used to compare the decoded data obtained based on the scanned image with a preset rule library to confirm whether the QR code complies with the correct coding specification; The repeated marking judgment module is used to check whether there is repeated marking in the two-dimensional code based on the decoded data obtained by scanning the image; The alarm module is used to issue an alarm notification when it is detected that the two-dimensional code is not fully marked, the marking rule is wrong, or the marking is repeated.

9. An aluminum alloy workpiece data acquisition and analysis system, characterized in that: It includes the aluminum alloy workpiece data acquisition and analysis device as described in claim 8.

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