A platform and method for online detection of variable QR code printing quality level

Abstract

The present invention belongs to the field of printing quality detection, and is a platform and method for online detection of variable two-dimensional code printing quality grades, including a front-end detection device, an industrial computer, and a software management platform. The front-end detection device is communicatively connected to the industrial computer, and the software management platform is deployed on the industrial computer and the intelligent terminal. The industrial computer controls the front-end detection device to perform automatic detection, and the front-end detection device sends the two-dimensional code quality data to the industrial computer through real-time detection, and displays and alarms through the software management platform. The two-dimensional code quality grade detection system platform of the present invention adopts machine vision and automatic control devices to realize the real-time capture of the position data of the online two-dimensional code grade detection equipment, and transmits the quality grade detection results to the production printing machine and workshop quality-related personnel in real time through the machine computer; the introduction of a precise fixed point code retrieval system can realize the precise movement of the two-dimensional code detection equipment and adapt to the detection position of the two-dimensional code of the cigarette label with different spacing.

Description

Technical Field

[0001] The present invention belongs to the field of printing quality detection, and in particular relates to a platform and method for online detection of variable two-dimensional code printing quality levels. Background Art

[0002] During the cigarette label printing process, variable QR codes need to be printed. During the printing process, variable QR codes may have quality problems due to various reasons, such as deformation, displacement, and unclearness. These products with quality defects cannot be distinguished by the naked eye or ordinary scanning tools. Therefore, it is necessary to test the quality of variable QR codes. At this stage, the cigarette label printing line uses offline variable QR code printing quality grade detection equipment to perform offline detection and report on variable QR code defects in cigarette label printing. This detection method is to conduct sampling inspection on the paper after printing is completed, and use QR code printing quality grade detection equipment to manually scan each QR code on the sample, and check on the computer to see if the data meets the requirements. This is an offline post-test. When workers find that there are quality problems with the QR code, they will feedback to the machine captain, team leader, and quality specialist. At this time, the production line has printed a large number of unqualified products, resulting in a large number of scrapped products.

[0003] Therefore, the existing QR code detection method cannot provide accurate detection and early warning of the real-time variable QR code printing quality level on the production line, and cannot provide real-time feedback of the variable QR code printing quality level data information. The product quality data of the production work order not only has the problems of large manual detection investment and low data real-time performance, but also cannot monitor and detect the variable QR code printing quality level on the production line in real time. Production problems over a period of time cannot be discovered and solved in time, resulting in material waste, and the detection data cannot be associated with the work order. Summary of the Invention

[0004] The purpose of the present invention is to provide a platform and method for online detection of variable two-dimensional code printing quality level to solve the above-mentioned technical problems.

[0005] To solve the above technical problems, the specific technical solutions of the present invention for an online platform and method for detecting the quality grade of variable two-dimensional code printing are as follows:

[0006] A platform for online detection of variable QR code printing quality grades includes a front-end detection device, an industrial computer, and a software management platform. The front-end detection device is communicatively connected to the industrial computer, and the software management platform is deployed on the industrial computer and an intelligent terminal. The industrial computer controls the front-end detection device to perform automatic detection. The front-end detection device sends QR code quality data to the industrial computer through real-time detection, and displays and issues alarms through the software management platform.

[0007] Furthermore, the front-end detection device includes a door-type frame, which is arranged across the paper output of the printing press. The door-type frame is provided with a slide rail mechanism, and a QR code level acquisition device is arranged on the slide rail mechanism. The lens of the QR code level acquisition device is downward, and the QR code level acquisition device slides back and forth on the slide rail mechanism to detect the QR code on the passing paper. A color mark sensor and multiple page number recognition cameras are fixedly installed on the door-type frame. The color mark sensor is used to identify the color mark on the paper and determine whether the paper is in place. The page number recognition camera is used to identify the number of rows and columns of the QR code currently being detected, that is, the number of the QR code on the paper.

[0008] Furthermore, the slide rail mechanism includes a motor, a guide rail, a sliding member, and a displacement sensor. The guide rail is mounted on a door-shaped frame, the sliding member slides on the guide rail, the motor is fixed to the sliding member for driving the sliding member, and the displacement sensor is mounted on the sliding member for detecting the sliding distance and position of the sliding member. The QR code level acquisition device is fixedly mounted on the sliding member.

[0009] Furthermore, there are preferably three page number recognition cameras, which are fixed at different positions of the door-shaped frame respectively, and the page number recognition cameras also include visual defect detection of QR codes.

[0010] Furthermore, an alarm light is provided on the door-shaped frame, and an alarm is issued through the alarm light when the quality inspection fails.

[0011] Furthermore, a light source is provided below the door-shaped frame, and the light source is used to provide illumination when the QR code level acquisition device and the page number recognition camera are shooting.

[0012] The present invention also discloses a method for detecting an online variable two-dimensional code printing quality grade platform, comprising the following steps:

[0013] Step 1: System integration and calibration: Build an integrated QR code quality grade inspection equipment system platform, including the integration of software and hardware modules, adjust the position and parameters of the slide rail system, and ensure that the front-end inspection device moves accurately to the inspection position;

[0014] Step 2: Image acquisition and preprocessing: Start the QR code quality grade detection equipment and begin to capture the image of the cigarette label QR code;

[0015] Step 3: QR code recognition and quality grade determination. The QR code grade acquisition device applies the QR code recognition algorithm to the pre-processed image to identify the QR code. The grade determination algorithm is used to determine the quality grade of the identified QR code.

[0016] Step 4: Fluctuation warning processing: Based on the result of the grade judgment, if the quality grade is greater than 2.0, the industrial computer controls the alarm light to display green. If the quality grade is less than 2.0, the core algorithm of the QR code quality grade detection value fluctuation warning platform is triggered to perform warning processing, including triggering the alarm program and alarm upgrade processing;

[0017] Step 5: After completing one QR code detection, analyze the QR code position arrangement according to the paper specifications collected in advance, delay T time, control the QR code level acquisition device to move to the position of the next QR code, and repeat steps 2-4 until the detection of each QR code on the paper is completed.

[0018] Step 6: Data analysis and decision-making: Analyze the collected QR code quality grade detection data, upload the QR code quality grade detection data to the software management platform, provide a digital quantitative basis, and make decisions and adjustments based on the data analysis results to improve production efficiency and quality control level.

[0019] Furthermore, the step 2 uses an image processing algorithm, wherein collecting an image of the cigarette label QR code includes the following steps:

[0020] Step 2.1: The color mark sensor recognizes the color mark on the paper;

[0021] Step 2.1: The industrial computer determines whether the paper has passed according to the signal of the color mark sensor. If so, it controls the page number recognition camera and the QR code level acquisition device to capture the QR code on the paper. Otherwise, it waits for the next color mark sensor signal.

[0022] Step 2.3: The page number recognition camera captures the current captured image, determines the position of the currently captured QR code, and detects visual defects of the QR code.

[0023] Furthermore, the step 5 only needs to complete the QR code detection at each position of the paper before a paper tray is finished, and the QR code positions can be corresponding on different papers.

[0024] Furthermore, step 5 includes a precise fixed-point code retrieval system algorithm, and the steps are as follows:

[0025] Step 5.1: First, define a function S(n) to represent the time it takes to capture a square on the cigarette mark, where n is the number of the square to be captured. Assume that S(n) = t, which means that a square has been successfully captured.

[0026] Step 5.2: Then, define a function R(r) to represent the process of shooting a row, where r is the number of the row to be shot. Assume that R(r) means that shooting a row requires shooting n grids continuously:

[0027] ,

[0028] Step 5.3: Next, define a function D(m) to represent the delay time t' after a line is captured, where m is the number of lines on the paper, and m-1 is the number of delays. Assume D(1) = 50, which means each delay is 50 seconds.

[0029] Step 5.4: Finally, define a function P(p) to represent the entire photographing process, where p is the number of the paper to be photographed. Assume that P(p) = ∑_{r=1}^{3} (R(r) + D(r-1)), which means that it is necessary to photograph m lines of paper on a cigarette label, and delay 50 seconds after each line is photographed:

[0030] .

[0031] The platform and method for online detection of variable two-dimensional code printing quality grade of the present invention have the following advantages:

[0032] The two-dimensional code quality grade detection system platform of the present invention adopts machine vision and automatic control devices to realize real-time capture of the position data of the online two-dimensional code grade detection equipment, and transmits the quality grade detection results to the production printing machine and workshop quality-related personnel in real time through the machine computer; the introduction of precise fixed point code retrieval system can realize the precise movement of the two-dimensional code detection equipment and adapt to the detection positions of the two-dimensional codes on cigarette labels with different spacings.

[0033] At the same time, based on real-time monitoring and analysis of QR code detection values, an early warning platform algorithm for fluctuations in QR code detection values has been introduced. When conditions are not met, early warning processing can be carried out. The system also has flexible multi-level early warning capabilities, and can set different alarm procedures according to different situations to ensure timely alarms in abnormal situations.

[0034] 1. The real-time and data-based quantitative basis method of QR code quality grade detection is realized. The QR code quality grade value is captured in real time through online automatic collection to form an effective judgment record; and the data is transmitted and fed back to the production printing machine and workshop office through the industrial computer, realizing the transmission and docking of data between instruments and machines.

[0035] 2. Improved the automation level of QR code quality grade data collection, achieved continuous value acquisition and automatic data judgment, and provided data support for long-term production data stability and continuous quality traceability.

[0036] 3. A code retrieval system based on precise fixed points has been developed, which uses slide rails to help the front-end detection device move to adapt to the detection position of QR codes on cigarette labels with different spacing. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1This is a schematic diagram of a large cigarette label product;

[0038] Figure 2 It is a structural schematic diagram of the front-end detection device of the present invention;

[0039] Figure 3 This is a control flow chart of the front-end detection device of the present invention;

[0040] Figure 4 This is a flow chart of the variable two-dimensional code printing quality level platform detection process of the present invention;

[0041] Explanation of the marks in the figure: 1. Door frame; 2. Slide rail mechanism; 21. Motor; 22. Guide rail; 23. Sliding part; 24. Displacement sensor; 25. QR code level acquisition device; 26. Page number recognition camera; 27. Color mark sensor; 28. Warning light; 29. Light source. DETAILED DESCRIPTION

[0042] In order to better understand the purpose, structure and function of the present invention, the following is a further detailed description of an online platform and method for detecting the quality level of variable two-dimensional code printing in conjunction with the accompanying drawings.

[0043] like Figure 1 As shown, after printing, the entire cigarette label includes multiple products in an array, each with a variable QR code. For example, an 800mm*700mm paper plane is divided into 3 rows and 6 columns, with each grid containing a 20mm*20mm QR code square block. Color marks are placed on the edge of the paper for registration and identification.

[0044] The platform for online testing of variable QR code printing quality grades comprises a front-end testing device, an industrial computer, and a software management platform. The front-end testing device establishes a communication connection with the industrial computer via the RS485 protocol, and the software management platform is deployed on the industrial computer and a smart terminal. The industrial computer controls the front-end testing device to perform automatic testing. The front-end testing device transmits QR code quality data to the industrial computer through real-time testing, and the software management platform displays and issues alarms.

[0045] like Figure 2As shown, the front-end detection device includes a door-shaped frame 1, which is arranged across the paper output of the printing press. The door-shaped frame 1 has a slide rail mechanism 2, which includes a motor 21, a guide rail 22, a slider 23, and a displacement sensor 24. The guide rail 22 is arranged on the door-shaped frame 1, and the slider 23 is slidably arranged on the guide rail 22. The motor 21 is fixed to the slider 23 to drive the slider 23 to move. The driving structure here can adopt any mechanism that can drive linear motion in the prior art and is not limited here. The displacement sensor 24 is arranged on the slider to detect the movement distance and position of the slider 23. A QR code level acquisition device 25 is fixedly installed on the slider 23. The QR code level acquisition device 25 has a downward-facing lens and is used to detect the QR code on the passing paper.

[0046] A color mark sensor 27 is fixedly mounted on the door frame 1 . The color mark sensor 27 is used to identify the color mark on the paper and determine whether the paper is in place.

[0047] The portal frame 1 is also fixedly mounted with multiple page number recognition cameras 26, preferably three in number, each mounted at a different location on the portal frame 1. The page number recognition cameras 26 are used to identify the row and column number of the QR code being inspected, i.e., the number of the QR code on the paper. They also perform basic inspections such as visual defect detection for QR codes (missing prints, image defects, image distortion, etc.).

[0048] The door frame 1 is also provided with an alarm light 28 , which will sound an alarm when the quality inspection fails.

[0049] A light source 29 is provided below the door-shaped frame 1 , and the light source 29 is used to provide illumination when the two-dimensional code level acquisition device 25 and the page number recognition camera 26 are shooting.

[0050] As shown in FIG3 , the control flow of the front-end detection device of the present invention is as follows:

[0051] Step 1: Connect the front-end detection device to the power supply;

[0052] Step 2: System initialization;

[0053] Step 3: The industrial computer sends the command to the front-end detection device, which recognizes and parses the serial port command;

[0054] Step 4: Control the motor to run, stop or calibrate according to the instructions; control the alarm light to sound an alarm according to the instructions;

[0055] Step 5: Send the data back to the industrial computer.

[0056] like Figure 4 As shown, the overall process of the online variable two-dimensional code printing quality grade detection platform of the present invention includes the following steps:

[0057] Step 1: System Integration and Calibration. Build an integrated QR code quality grade inspection equipment system platform, including the integration of software and hardware modules. Adjust the position and parameters of the slide system to ensure that the front-end inspection device moves accurately to the inspection position.

[0058] Step 2: Image acquisition and preprocessing. Start the QR code quality grade detection device and begin capturing images of the cigarette label QR code. Use image processing algorithms (edge detection: Sobel operator, Canny edge detector, threshold algorithm) to preprocess the captured image to improve recognition rate and clarity. Capturing the cigarette label QR code image includes the following steps:

[0059] Step 2.1: The color mark sensor 27 identifies the color mark on the paper.

[0060] Step 2.1: The industrial computer determines whether a paper has passed according to the signal of the color mark sensor 27. If so, it controls the page number recognition camera 26 and the QR code level acquisition device 25 to take a picture of the QR code on the paper. Otherwise, it waits for the next signal of the color mark sensor 27.

[0061] Step 2.3: The page number recognition camera 26 captures the current captured image, determines the position of the currently captured QR code, and performs basic inspections such as visual defect detection on the QR code.

[0062] Step 3: QR Code Recognition and Quality Grade Determination. The QR code grade acquisition device 25 applies a QR code recognition algorithm to the preprocessed image to identify the QR code. The quality grade of the identified QR code is determined using the grade determination algorithm, including metrics such as clarity, recognition rate, error tolerance, reflectivity, and decoding speed. This QR code recognition and quality grade determination process includes submodules such as the image processing algorithm, the QR code recognition algorithm, and the quality grade determination algorithm.

[0063] Step 4: Fluctuation Warning Processing. Based on the quality grade determination result, if the quality grade is greater than 2.0, the industrial computer controls alarm light 28 to illuminate green. If the quality grade is less than 2.0, the core algorithm of the QR code quality grade detection value fluctuation warning platform is triggered, and warning processing is performed, including triggering the alarm program and alarm escalation. After the alarm program is triggered, the industrial computer controls alarm light 28 to illuminate red, issuing an alarm reminder. The alarm information is then sent to the machine leader, team leader, and quality specialist via the software management platform. At the same time, unqualified paper is removed from the paper feed below the printing press.

[0064] Step 5: After completing a QR code inspection using a precise fixed-point code capture system, the QR code positional arrangement is analyzed based on the previously collected paper specifications. After a delay of T, the QR code level acquisition device 25 is controlled to move to the next QR code location. Steps 2-4 are repeated until every QR code on the paper is inspected. The device only needs to complete the QR code inspection for each position on the paper before the paper tray is exhausted. This can be for corresponding QR code locations on different sheets of paper. For example, a sheet of paper measuring 800mm x 700mm is divided into 3 rows and 6 columns, with each grid containing a 20mm x 20mm square QR code. On a production line moving at 120m / s, with the sheets moving in parallel columns, the QR code level acquisition device 25 captures the paper, capturing each grid at a time. This requires six consecutive captures to complete one row, followed by a 50-second delay to capture the second row. Six consecutive captures are then repeated, and finally, a 50-second delay is added to capture the last row.

[0065] Because the paper feeding and the QR code level acquisition device 25 mobile shooting process are dynamic, precise control calculation is required. The algorithm steps of the precise fixed point code acquisition system are as follows:

[0066] Step 5.1: First, define a function S(n) to represent the time it takes to capture a single cigarette square, where n is the number of the square to be captured. In this example, we can assume that S(n) = t, indicating the time it takes to successfully capture a single square.

[0067] Step 5.2: Next, define a function R(r) to represent the process of capturing a row, where r is the row number. In this example, we can assume that R(r) represents the process of capturing n grids in a row.

[0068] ,

[0069] Step 5.3: Next, define a function D(m) to represent the delay time t' after capturing a line, where m is the number of lines and m-1 is the number of delays. In this example, we can assume D(1) = 50, indicating a 50-second delay.

[0070] Step 5.4: Finally, define a function P(p) to represent the entire image capture process, where p is the number of the paper to be captured. In this example, we can assume that P(p) = ∑_{r=1}^{3} (R(r) + D(r-1)), indicating that a cigarette label requires capturing m rows, with a 50-second delay after each row.

[0071] .

[0072] Step 6: Data Analysis and Decision-Making. Analyze the collected QR code quality grade test data and upload it to the software management platform to provide a quantified basis. Based on the data analysis results, make decisions and adjustments to improve production efficiency and quality control.

[0073] It will be understood that the present invention is described by way of some embodiments, and it will be appreciated by those skilled in the art that various changes or equivalent substitutions may be made to these features and embodiments without departing from the spirit and scope of the present invention. In addition, under the teachings of the present invention, these features and embodiments may be modified to adapt to specific circumstances and materials without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are intended to be protected by the present invention.

Claims

1. A detection method for an online detection platform for variable two-dimensional code printing quality grade, the online detection platform for variable two-dimensional code printing quality grade comprising a front-end detection device, an industrial control computer and a software management platform, the front-end detection device being communicatively connected to the industrial control computer, the software management platform being deployed on the industrial control computer and an intelligent terminal, the industrial control computer controlling the front-end detection device to perform automatic detection, the front-end detection device sending the two-dimensional code quality data to the industrial control computer through real-time detection, and displaying and alarming through the software management platform; the front-end detection device comprising a door-type frame (1), the door-type frame (1) being arranged across the paper output of the printing press, the door-type frame (1) has a slide rail mechanism (2), a two-dimensional code level acquisition device (25) is set on the slide rail mechanism (2), the two-dimensional code level acquisition device (25) has a lens facing downward, and the two-dimensional code level acquisition device (25) slides back and forth on the slide rail mechanism (2) for detecting the two-dimensional code on the passing paper, and a color mark sensor (27) and a plurality of page number recognition cameras (26) are fixedly installed on the door-shaped frame (1), the color mark sensor (27) is used to recognize the color mark on the paper and judge whether the paper is in place, and the page number recognition camera (26) is used to recognize the number of rows and columns of the currently detected two-dimensional code, that is, the number of the two-dimensional code on the paper; it is characterized in that The detection method comprises the following steps: Step 1: System integration and calibration: Build an integrated QR code quality grade inspection equipment system platform, including the integration of software and hardware modules, adjust the position and parameters of the slide rail system, and ensure that the front-end inspection device moves accurately to the inspection position; Step 2: Image acquisition and preprocessing: Start the QR code quality grade detection equipment and begin to capture the image of the cigarette label QR code; Step 3: QR code recognition and quality grade judgment: The QR code grade acquisition device (25) applies a QR code recognition algorithm to the pre-processed image to recognize the QR code, and uses a grade judgment algorithm to judge the quality grade of the recognized QR code; Step 4: Fluctuation warning processing: According to the result of the grade judgment, if the quality grade is greater than 2.0, the industrial computer controls the alarm light (28) to display green. If the quality grade is less than 2.0, the core algorithm of the QR code quality grade detection value fluctuation warning platform is triggered to perform warning processing, including triggering the alarm program and alarm upgrade processing; Step 5: After completing the detection of a QR code, the QR code position arrangement is analyzed according to the paper specifications collected in advance, a delay of T time is applied, and the QR code level acquisition device (25) is controlled to move to the position of the next QR code, and steps 2-4 are repeated until the detection of each QR code on the paper is completed; Step 6: Data analysis and decision-making: Analyze the collected QR code quality grade detection data, upload the QR code quality grade detection data to the software management platform, provide a digital quantitative basis, and make decisions and adjustments based on the data analysis results to improve production efficiency and quality control level.

2. The detection method according to claim 1, wherein The slide rail mechanism (2) comprises a motor (21), a guide rail (22), a sliding member (23) and a displacement sensor (24); the guide rail (22) is arranged on the door-shaped frame (1); the sliding member (23) is slidably arranged on the guide rail (22); the motor (21) is fixed on the sliding member (23) for driving the sliding member (23) to move; the displacement sensor (24) is arranged on the sliding member (23) for detecting the moving distance and position of the sliding member (23); and the two-dimensional code level acquisition device (25) is fixedly mounted on the sliding member (23).

3. The detection method according to claim 1, wherein There are three page number recognition cameras (26), which are respectively fixed at different positions of the door-shaped frame (1). The page number recognition cameras (26) also include a visual defect detection function for QR codes.

4. The detection method according to claim 1, wherein The door-shaped frame (1) is also provided with an alarm light (28), and when the quality inspection fails, an alarm is issued through the alarm light (28).

5. The detection method according to claim 1, wherein A light source (29) is provided below the door-shaped frame (1), and the light source (29) is used to provide illumination when the two-dimensional code level acquisition device (25) and the page number recognition camera (26) are shooting.

6. The detection method according to claim 1, characterized in that Step 2 uses an image processing algorithm, wherein collecting an image of a cigarette label QR code includes the following steps: Step 2.1: The color mark sensor (27) identifies the color mark on the paper; Step 2.1: The industrial computer determines whether the paper has passed according to the signal of the color mark sensor (27). If so, it controls the page number recognition camera (26) and the QR code level acquisition device (25) to take a picture of the QR code on the paper. Otherwise, it waits for the next signal of the color mark sensor (27); Step 2.3: The page number recognition camera (26) captures the current captured image, determines the position of the currently captured QR code, and performs visual defect detection on the QR code.

7. The detection method according to claim 1, characterized in that The step 5 only needs to complete the QR code detection at each position of the paper before the paper tray is finished, and the QR code positions can be corresponding to different papers.

8. The detection method according to claim 1, wherein Step 5 includes the precise fixed point code retrieval system algorithm, and the steps are as follows: Step 5.1: First, define a function S(n) to represent the time it takes to capture a square on the cigarette mark, where n is the number of the square to be captured. Assume that S(n) = t, which means that a square has been successfully captured. Step 5.2: Then, define a function R(r) to represent the process of shooting a row, where r is the number of the row to be shot. Assume that R(r) means that shooting a row requires shooting n grids continuously: ， Step 5.3: Next, define a function D(m) to represent the delay time t' after a line is captured, where m is the number of lines on the paper, and m-1 is the number of delays. Assume D(1) = 50, which means each delay is 50 seconds. Step 5.4: Finally, define a function P(p) to represent the entire photographing process, where p is the number of the paper to be photographed. Assume that P(p) = ∑_{r=1}^{3} (R(r) + D(r-1)), which means that it is necessary to photograph m lines of paper on a cigarette label, and delay 50 seconds after each line is photographed: 。

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