EPE pearl wool package detection system

Abstract

The invention discloses an EPE pearl wool package detection system. The system comprises a packaging device, and a data acquisition module, a data processing module, a data transmission module, a visualization module and a control module which are arranged on the packaging device; wherein the data acquisition module comprises an environment monitoring module which is used for monitoring a production environment; the optical sensing module is used for detecting packaging parameters of the EPE pearl wool in real time; the data processing module is used for analyzing and processing the data acquired by the data acquisition module, generating graphs and reports and transmitting the graphs and reports to the visualization module; the data transmission module is communicated with the data acquisition module, the data processing module, the visualization module and the control module; the visualization module is used for displaying the information in a visual form; the control module is used for providing a human-computer interaction interface. According to the EPE pearl wool packaging control system, comprehensive and real-time monitoring and control over the EPE pearl wool packaging process are achieved by integrating the environment monitoring module, the optical sensing module, the data processing module, the data transmission module, the visualization module and the control module.

Description

Technical Field

[0001] The invention belongs to the technical field of packaging, and in particular relates to an EPE pearl cotton packaging detection system. Background Art

[0002] EPE pearl cotton (Expanded Polyethylene) is a packaging material with good cushioning, shockproof, moisture-proof and other properties. It is widely used in the packaging protection of electronic, electrical appliances, handicrafts, furniture and other products. With the continuous advancement of production automation and intelligence, packaging quality inspection has gradually become an important link to ensure production quality and product safety. However, the existing EPE pearl cotton packaging quality inspection usually relies on manual inspection, which mainly has the following problems:

[0003] First, manual inspection is difficult to ensure the consistency and accuracy of inspection. In long-term production, manual operation will inevitably lead to omissions or misjudgments, especially when detailed inspection is required. It is difficult for manual operation to maintain a high degree of concentration, resulting in fluctuations in product quality. In addition, due to the flexible, light and deformable characteristics of EPE pearl cotton materials, manual measurement and observation are often difficult to obtain accurate data, which further affects the judgment of packaging quality.

[0004] Secondly, manual inspection is inefficient and cannot meet the needs of rapid production in modern industry. In large-scale, assembly-line production, relying on manual inspection is not only time-consuming and labor-intensive, but may also cause production bottlenecks, affect overall production efficiency, and make it difficult to achieve efficient management of production. At the same time, manual inspection requires a large amount of labor resources, which increases labor costs and management costs. Especially in the context of labor shortage or rising costs, higher requirements are placed on corporate cost control. Summary of the invention

[0005] To solve the above problems, the present invention provides an EPE pearl cotton packaging detection system, which realizes comprehensive and real-time monitoring and control of the EPE pearl cotton packaging process by integrating environmental monitoring, optical sensing, data processing, data transmission, visualization and control modules.

[0006] The technical solution provided by the present invention is as follows:

[0007] An EPE pearl cotton packaging detection system includes a packaging device, a data acquisition module, a data processing module, a data transmission module, a visualization module and a control module arranged on the packaging device;

[0008] Data acquisition module, including environmental monitoring module, used to monitor the production environment; optical sensing module, used to detect the packaging parameters of EPE pearl cotton in real time;

[0009] The data processing module is used to analyze and process the data collected by the data acquisition module, and generate graphics and reports to transmit to the visualization module;

[0010] The data transmission module uses wired or wireless transmission to connect the data acquisition module, the data processing module, the visualization module and the control module;

[0011] Visualization module, used to display information in a visual form;

[0012] The control module is used to provide a human-computer interaction interface for operators to control the equipment.

[0013] In some embodiments, the environment monitoring module integrates a temperature and humidity sensor, an air quality sensor, and a noise sensor to monitor the temperature, humidity, and air quality of the production environment, and transmits the monitoring data to the data processing module.

[0014] In some embodiments, the optical sensing module includes an industrial camera and a laser rangefinder. The industrial camera is used to capture packaging images, and the laser rangefinder is used to measure the size of the EPE pearl cotton and transmit the data to the data processing module.

[0015] In some embodiments, the data processing module includes environmental data processing and image processing;

[0016] Environmental data processing includes data organization, classification and charting;

[0017] Image processing includes the following steps:

[0018] S1: De-noising the captured image;

[0019] S2: convert the image into a grayscale image, perform binarization on the grayscale image, and convert the image into a binary image using a threshold segmentation method;

[0020] S3: Use edge detection algorithm to perform edge detection on the denoised image to identify edge features in the image, use contour extraction algorithm to obtain the outer contour of the package, and perform shape feature analysis;

[0021] S4: Defect detection algorithms are used to identify air bubbles, scratches, and wrinkles;

[0022] S5: Determine whether the defect is qualified or not according to the set area threshold and provide feedback.

[0023] In some embodiments, the denoising process uses Gaussian filtering or median filtering.

[0024] In some embodiments, the threshold segmentation method uses the Otsu algorithm.

[0025] In some implementations, the edge detection algorithm is a Canny edge detection algorithm.

[0026] In some embodiments, the data transmission of the data transmission module adopts one or more of LAN, Internet or 5G network.

[0027] In some embodiments, the visualization module includes a device human-machine interface, a tablet computer, a smart phone, a computer, or a factory sign.

[0028] In some embodiments, the control module includes an alarm system, which is electrically connected to the data processing module and automatically issues an alarm when a packaging defect or an environmental abnormality is detected.

[0029] In summary, the beneficial effects of the present invention are:

[0030] (1) The system of the present invention adopts high-precision sensors such as industrial cameras and laser rangefinders, combined with advanced image processing algorithms, to accurately detect packaging size, shape characteristics and surface defects, avoiding misjudgments and omissions in manual inspection, and greatly improving inspection accuracy and consistency.

[0031] (2) The system of the present invention integrates automated detection and real-time data feedback functions, and can continuously perform detection and quality judgment without human intervention, significantly shortening the detection time and improving overall production efficiency. It is particularly suitable for packaging quality control of large-scale production lines. At the same time, the system supports real-time display of detection data. Operators can view data through a variety of channels such as human-machine interface and mobile devices. Management can also remotely monitor and view production reports to provide data support for decision-making. At the same time, the system has an alarm function, which can promptly alarm when packaging defects or environmental abnormalities are found to ensure production quality and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flow chart of the system of the present invention. DETAILED DESCRIPTION

[0033] In order to deepen the understanding of the present invention, the present invention will be further described in detail below in conjunction with examples. The following examples are only used to explain the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0034] like Figure 1 As shown, the present invention discloses an EPE pearl cotton packaging detection system, which aims to improve packaging quality, production efficiency and operational safety. The system integrates packaging equipment, data acquisition module, data processing module, data transmission module, visualization module and control module, and realizes automatic detection and control through a variety of sensing technologies, data processing and image analysis methods.

[0035] The packaging equipment of this embodiment is prior art, wherein the conveying system includes a conveyor belt and a positioning device to ensure the precise positioning of the EPE pearl cotton during the packaging process. The conveyor belt speed is adjustable to adapt to different production rhythms. The robotic arm system is equipped with an automated robotic arm for precise assembly and handling of the EPE pearl cotton. The control system of the robotic arm is commanded by a control module, and the action can be adjusted in real time according to sensor feedback. The shaping device ensures that the EPE pearl cotton will not deform during the packaging process to meet the final packaging quality requirements.

[0036] The environmental monitoring module in the data acquisition module is used to monitor the key parameters of the packaging environment, including temperature and humidity sensors, air quality sensors and noise sensors installed on the device. Temperature and humidity sensor: accurately measures the temperature and humidity of the production environment, and transmits the data to the data processing module to determine in real time whether the environment meets production requirements. The air quality sensor monitors the dust concentration and harmful gas components in the air, especially the volatile organic compound (VOC) content, to ensure the safety of the production environment. The noise sensor detects the noise level in the workshop to ensure that it meets the health standards of workers and helps reduce the impact of noise on detection accuracy.

[0037] The optical sensing module is installed at multiple locations of the packaging equipment, and the packaging process is monitored in real time using industrial cameras and laser rangefinders. Among them, the industrial camera: captures high-definition images of EPE pearl cotton to support subsequent shape detection and defect analysis. The image is acquired through a high-resolution sensor to ensure the clarity of image details. The laser rangefinder: is used to measure the thickness and edge size of EPE pearl cotton, and transmit the data to the data processing module in real time. The ranging data accuracy can reach 0.01 mm, ensuring high-precision dimensional control.

[0038] The data processing module is the core of data analysis and processing. It performs multi-step processing based on the collected environmental data and image data. This module mainly includes environmental data processing and image processing.

[0039] In environmental data processing, by classifying and organizing environmental data such as temperature, humidity, air quality and noise, visual data for real-time analysis is generated, such as line graphs, bar graphs, etc. For environmental parameters that exceed the preset range, the system will automatically send a prompt to the control module.

[0040] Image processing involves multiple steps to detect surface defects on packaging. The specific processing steps are as follows:

[0041] S1: Denoising

[0042] To improve the recognition of the image, the system uses Gaussian filtering or median filtering to remove noise from the image and keep the edge details clear.

[0043] Specifically, a Gaussian filter is used, and the filter window size is set to k×k. For example, when k=5, the standard deviation σ of the Gaussian filter is 1.5.

[0044]

[0045] Among them, G(x,y) represents the filter value at the position (x,y), which controls the image denoising.

[0046] S2: Grayscale and Binarization

[0047] The image is converted into a grayscale image to reduce the amount of data and increase the processing speed. The grayscale image is converted into a binary image through the Otsu algorithm to make the contrast between the background and the foreground more obvious, which is convenient for subsequent feature extraction.

[0048] The grayscale formula is:

[0049] Igray=0.299·R+0.587·G+0.114·B

[0050] Among them, Igray represents the pixel value of the grayscale image, which is obtained by converting the values ​​of the weighted red, green, and blue channels; R, G, B represent the pixel values ​​of the red, green, and blue channels in the color image.

[0051] The Otsu algorithm is used to automatically select the binarization threshold T. The threshold calculation formula is as follows:

[0052]

[0053] in, is the inter-class variance under threshold t, which represents the difference between foreground and background pixel intensities. T represents the binarization threshold calculated by the Otsu algorithm, which is used to distinguish foreground from background.

[0054] S3: Edge Detection

[0055] The Canny edge detection algorithm is used to identify the edges of the packaging image, and the contour extraction algorithm is used to obtain the outline of the EPE pearl cotton. This embodiment uses the FindContours function to identify the edges in the image and generate a contour map of the packaging. For the extracted contour, the system calculates its shape features such as area, perimeter, aspect ratio, etc., which are used to judge the integrity and symmetry of the packaging.

[0056] Canny edge detection parameters:

[0057] Set the low threshold (Tlow): 50; low threshold (Thigh): 150;

[0058] Tlow is the low threshold in the Canny edge detection algorithm, which is used to determine the minimum value of the edge strength; Thigh is the high threshold in the Canny edge detection algorithm, which is used to determine the maximum value of the edge strength.

[0059] Gradient calculation: Use the Sobel operator to calculate the horizontal and vertical gradients of the image to detect edge locations.

[0060] Contour area calculation:

[0061] The contour area A is calculated by the coordinates of the contour points. If (xi, yi) are the points on the contour, the area A calculation formula is:

[0062]

[0063] Among them, A represents the area of ​​the contour, which means the size of the area calculated by the contour points; n represents the number of points on the contour, which is used to calculate the area.

[0064] Calculation of contour aspect ratio R:

[0065]

[0066] Among them, L max and W max are the maximum length and width of the contour, respectively

[0067] S4: Defect Detection

[0068] The system automatically identifies surface defects such as bubbles, scratches, wrinkles, etc. This process uses a specific defect detection algorithm to determine the defect area and record its location by analyzing the grayscale difference.

[0069] For the detection of bubbles, scratches and wrinkles, a specific area or length threshold T can be introduced. areat and T lengtht .

[0070] Specifically, the system analyzes the irregular areas of the contour to identify whether there are bubbles on the packaging surface. If the detected small area is within the set bubble threshold range, it is marked as a bubble defect.

[0071] That is, if the detected contour area A satisfies A <T area_bubble , it is judged as a bubble defect. For example, suppose T area_bubble =10mm 2 .

[0072] T area_bubble Indicates the area threshold of bubble defects. If the detected bubble area is smaller than this value, it is judged as a bubble defect.

[0073] The system analyzes the thin and long edge features in the image, identifies straight lines or curves, and marks them as scratch defects if their length exceeds the set threshold.

[0074] Detect straight lines through Hough transform. If the length L of a straight line satisfies L> tlength_scratch , it is judged as a scratch defect. For example, suppose T length_scratch =5mm.

[0075] T length_scratch Indicates the length threshold of the scratch defect. If the detected scratch length is greater than this value, it is determined to be a scratch defect.

[0076] The system identifies wrinkle features by analyzing the smoothness and symmetry of the contour. If the detected contour has obvious undulations and does not conform to the normal contour, it is marked as a wrinkle defect.

[0077] Use the smoothness of the contour to judge wrinkles. If the curvature change rate K of the contour satisfies K>T curvature , it is judged as a wrinkle defect. The curvature K is calculated as:

[0078]

[0079] Among them, x ′ and ′ are the derivatives of the contour at a certain point, x ″ and ″ is the second-order derivative; T curvature represents the curvature threshold, which is used to judge the sensitivity of wrinkle defects; K represents the curvature of the contour, which indicates the smoothness of the contour change and reflects whether there are wrinkles.

[0080] S5: Defect Judgment

[0081] By calculating the area or length threshold of the defect area, the package is judged to be qualified according to the preset area or length threshold. The processing results will be fed back to the control module, and an alarm will be issued when an unqualified defect is detected.

[0082] After the inspection is completed, the system outputs feedback in real time based on the defect detection results:

[0083] If the characteristic value V of a certain type of defect detected satisfies V>T defect , it is judged as unqualified and an alarm is triggered.

[0084] The alarm signal is transmitted to the operator through the production line controller, and the robot arm removes the defective products.

[0085] Where V represents the characteristic value of a certain type of defect, usually area, length or curvature, which is used to determine whether the product is qualified; T defectIndicates the judgment threshold of the defect characteristic value. If the characteristic value exceeds this value, it is judged as unqualified.

[0086] In order to analyze the data, the test results are recorded in the following form:

[0087] The inspection information of each product is stored as {timestamp, defect type, defect area, defect location}.

[0088] Output defect rate statistics regularly, the calculation formula is:

[0089]

[0090] Among them, N defect is the number of defective products, N totaln is the total number of inspected products; D is the defect rate, which means the proportion of unqualified products to the total number of inspected products, expressed in percentage.

[0091] Furthermore, the data transmission module adopts a wired or wireless connection method to realize data transmission between modules. Transmission solutions such as LAN, Internet or 5G network can be used to meet the needs of different production environments. The feature of this module is that it supports multi-protocol concurrency, ensures real-time data transmission, and avoids low detection efficiency due to network delays.

[0092] In a preferred embodiment, the visualization module integrates multiple terminal devices to provide intuitive production information display, including equipment human-machine interface, tablet computer, smart phone and factory signboard and other display devices. The operator can view various parameters in the production process through the human-machine interface, including environmental data, packaging size and defect analysis images, and the interface can provide operation guidance.

[0093] Of course, the data can also be displayed on the factory dashboard to centrally display the production environment and equipment operating status, ensuring that operators and managers can grasp the production dynamics at the first time.

[0094] In this embodiment, the control module is the interactive center of the system, including the human-machine interactive interface and the alarm system to ensure accurate control and timely feedback of the production process. The core functions of the control module are as follows:

[0095] Real-time control: Operators can adjust the speed, pressure and other parameters of packaging equipment through the interactive interface to ensure production stability. At the same time, the module can be remotely controlled so that operators can make quick adjustments when abnormalities occur.

[0096] Alarm system: When the system detects packaging defects or environmental abnormalities, the alarm system will automatically sound an audible and visual alarm, and an alarm message will pop up on the display screen to prompt the operator to handle it immediately. The alarm content can also be transmitted to the remote terminal in real time through the data transmission module.

[0097] Safety protection: The control module integrates production safety protection measures, such as automatic shutdown function when temperature and humidity exceed the standard, automatic prompt function when air quality is unqualified, and chain shutdown protection when packaging defects are found. The system can effectively reduce the impact of environmental abnormalities on production quality.

[0098] The operation process of this system is as follows:

[0099] After powering on, the control module checks the status of each sensor and the communication connection to ensure that all modules are in normal working condition.

[0100] The packaging equipment starts running, and the data acquisition module collects environmental data and image data of the packaging process in real time.

[0101] The data transmission module transmits the collected data to the data processing module, which analyzes and processes the data. The image processing module detects surface defects of the product and generates corresponding inspection reports.

[0102] The visualization module displays various detection information in real time, and the operator can control the equipment through the human-computer interaction interface.

[0103] When unqualified products or environmental abnormalities are detected, the control module activates the alarm system and displays the alarm information on the operation interface, prompting the operator to make adjustments.

[0104] After production is completed, the system generates complete production records and reports for analysis and archiving.

[0105] It should be noted that the implementation methods not shown or described in the drawings or the main text of the specification are all forms known to ordinary technicians in the relevant technical field and are not described in detail. In addition, the above definitions of each element and method are not limited to the various specific structures, shapes or methods mentioned in the embodiments.

[0106] It should also be noted that the directional terms mentioned in the embodiments, such as "up", "down", "front", "back", "left", "right", "inside", "outside", etc., are only for reference to the directions of the drawings and are not intended to limit the scope of protection of this application.

[0107] The above description shows and describes the preferred embodiments of the present invention. As mentioned above, it should be understood that the present invention is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the invention concept described herein through the above teachings or the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art do not depart from the spirit and scope of the present invention, and should be within the scope of protection of the claims attached to the present invention.

Claims

1. An EPE pearl cotton packaging detection system, characterized in that: It includes packaging equipment, a data acquisition module, a data processing module, a data transmission module, a visualization module and a control module arranged on the packaging equipment; Data acquisition modules, including environmental monitoring modules, are used to monitor the production environment; Optical sensing module, used to detect the packaging parameters of EPE pearl cotton in real time; The data processing module is used to analyze and process the data collected by the data acquisition module, and generate graphics and reports to transmit to the visualization module; The data transmission module uses wired or wireless transmission to connect the data acquisition module, the data processing module, the visualization module and the control module; Visualization module, used to display information in a visual form; The control module is used to provide a human-computer interaction interface for operators to control the equipment.

2. The EPE pearl cotton packaging detection system according to claim 1 is characterized in that: The environmental monitoring module integrates temperature and humidity sensors, air quality sensors and noise sensors to monitor the temperature, humidity and air quality of the production environment, and transmits the monitoring data to the data processing module.

3. The EPE pearl cotton packaging detection system according to claim 1 is characterized in that: The optical sensing module includes an industrial camera and a laser rangefinder. The industrial camera is used to collect packaging images, and the laser rangefinder is used to measure the size of EPE pearl cotton and transmit the data to the data processing module.

4. The EPE pearl cotton packaging detection system according to claim 1 is characterized in that: The data processing module includes environmental data processing and image processing; Environmental data processing includes data organization, classification and charting; Image processing includes the following steps: S1: De-noising the captured image; S2: convert the image into a grayscale image, perform binarization on the grayscale image, and convert the image into a binary image using a threshold segmentation method; S3: Use edge detection algorithm to perform edge detection on the denoised image to identify edge features in the image, use contour extraction algorithm to obtain the outer contour of the package, and perform shape feature analysis; S4: Defect detection algorithms are used to identify air bubbles, scratches, and wrinkles; S5: Determine whether the defect is qualified or not according to the set area or length threshold, and provide feedback.

5. The EPE pearl cotton packaging detection system according to claim 4 is characterized in that: The denoising process uses Gaussian filtering or median filtering.

6. The EPE pearl cotton packaging detection system according to claim 4 is characterized in that: The threshold segmentation method uses Otsu algorithm.

7. The EPE pearl cotton packaging detection system according to claim 4 is characterized in that: The edge detection algorithm is the Canny edge detection algorithm.

8. The EPE pearl cotton packaging detection system according to claim 1 is characterized in that: The data transmission of the data transmission module adopts one or more of LAN, Internet or 5G network.

9. The EPE pearl cotton packaging detection system according to claim 1, characterized in that: The visualization module includes the equipment human-machine interface, tablet computer, smart phone, computer or factory signboard.

10. The EPE pearl cotton packaging detection system according to claim 1, characterized in that: The control module includes an alarm system which is electrically connected to the data processing module and automatically issues an alarm when a packaging defect or an environmental anomaly is detected.

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