Cigarette carton glue point detection device and detection method

Abstract

The invention discloses a cigarette carton glue point detection device and method, and the device comprises an industrial camera which is used for collecting carton paper glue point images; the camera parameter adjustment module is used for setting industrial camera parameters and triggering conditions and sending images; the image processing module is used for receiving the image and processing the image so as to judge whether the glue point is qualified or not, and when the glue point is judged to be qualified, an NG signal is sent out; the optocoupler signal processing module is used for converting the NG signal into an electric signal; and the Beckhoff controller receives the electric signal and performs logic control on the industrial personal computer. The invention aims to provide the cigarette carton glue point detection device and the detection method, which can be used for carrying out single and global detection on the glue points, so that the rejection missing rate is reduced, and the stability of the packaging process is improved.

Description

Technical Field

[0001] The present invention relates to the field of detection technology, and particularly to a cigarette strip box glue point detection device and a detection method. Background Art

[0002] The M779 type strip packing machine completes the packing of cigarette strip packs through the cooperation of components such as a small box conveyor belt, a cigarette strip pusher, a hot melt adhesive spraying system, a folding turret 1, a film conveying device, a folding turret 2, and a film heat sealer. In the strip box packing process, a hot melt adhesive spraying device is used to complete the glue point gluing process of the strip box paper. During the gluing process, due to problems such as the aging of the glue spraying nozzle, the quality of the hot melt adhesive, and carbon deposition in the glue supply pipe in the hot melt adhesive system, it is easy to produce glue shortage defects. Therefore, it is necessary to detect the glue points of the strip box paper during the packing process. At present, visual detection has been widely used in industrial detection. For example, a cigarette strip box glue point image detection system with the publication number CN120028333A includes: an industrial control computer, a visual acquisition device, and a PLC controller; the visual acquisition device is used to acquire images of the strip box glue points on both sides of the strip box. In this device, the points where the glue is sprayed onto the strip box wrapping paper through the glue spraying nozzle are generally circular. Only the minimum circumscribed circle of the glue spraying point contour needs to be generated, and the area ratio of the circumscribed circle to the connected domain inside the contour is calculated to know whether the glue spraying point is approximately circular. If the ratio is too large, it means the shape is irregular. This device is used to detect whether the glue spraying amount is too large or too small, that is, only to detect a single glue point. However, during the packing process, multiple glue points usually need to be applied on the strip box paper. In the above patent, only a single glue point is detected. That is, as long as there are glue points with a sufficient area on a single strip box paper, regardless of the number and offset of the glue points, they are all determined to be qualified products. This will cause many unqualified papers to be missed, which is not conducive to the adhesion effect during the packing process. To overcome this technical defect, the present invention provides a cigarette strip box glue point detection device and a detection method. Summary of the Invention

[0003] The purpose of the present invention is to provide a cigarette strip box glue point detection device and a detection method, which can perform single and global detection of the glue points, thereby reducing the missed rejection rate and improving the stability of the packing process.

[0004] To solve the above technical problems, the present invention adopts the following technical solutions:

[0005] A cigarette strip box glue point detection device includes:

[0006] An industrial camera, which is used to collect images of the strip box paper glue points;

[0007] A camera parameter adjustment module, which is used to set the parameters and trigger conditions of the industrial camera and send the images.

[0008] The image processing module is used to receive and process images to determine whether the glue dots are qualified. When the glue dots are qualified, an NG signal is issued.

[0009] Optocoupler signal processing module, which is used to convert NG signals into electrical signals;

[0010] Beckhoff controllers accept electrical signals and perform logic control on industrial control computers.

[0011] Furthermore, the number of industrial cameras is two, one of which is mounted on the turret folding guide rail bracket for detecting adhesive dots on the outer side of the strip box paper, and the other is mounted on the wire groove bracket above the turret for detecting adhesive dots on the inner side of the strip box paper.

[0012] Furthermore, it also includes two LED light sources located above the turret, allowing the two LED light sources to illuminate the outside and inside of the carton paper.

[0013] On the other hand, based on the above-mentioned cigarette carton adhesive spot detection device, the present invention also provides a cigarette carton adhesive spot detection method, including:

[0014] S1. Two industrial cameras and two LED light sources are installed at the turret of the packaging machine so that the industrial cameras can capture the glue dots on the inside and outside of the carton paper. The I / O terminals of the industrial cameras are connected to the optical coupler signal processing module, and the communication network cable of the industrial cameras is connected to the camera parameter adjustment module.

[0015] S2. Set camera parameters and trigger conditions in the camera parameter adjustment module to acquire clearer and more stable images and send them.

[0016] S3. The image processing module processes and judges the acquired image, and outputs the judgment result. If the output judgment result is an NG signal, the next step is executed.

[0017] S4 and NG signals are transmitted to the Beckhoff controller via the camera output and optocoupler signal processing module. The Beckhoff controller then performs logic control on the industrial computer. The logic control includes controlling the rejection mechanism to reject unqualified paper strips, triggering system fault alarms, and counting the number of unqualified paper strips.

[0018] Furthermore, in step S2, the camera parameters and trigger conditions are set in the camera parameter adjustment module. The industrial camera used to photograph the outer adhesive dots has a focal length of 0.1mm, an aperture of f / 16, and an exposure time of 20000; the industrial camera used to photograph the inner adhesive dots has a focal length of 0.3mm, an aperture of f / 16, and an exposure time of 20000.

[0019] Furthermore, in step S3, the processing and judgment of the acquired image by the image processing module specifically includes:

[0020] S3a. Filter the acquired image and extract the features of the glue dots;

[0021] S3b. Design the first matching algorithm and the second matching algorithm. In the first matching algorithm, the pixels in the area within the planned circular window are self - learned, and the feature values obtained through this training are used as templates to quickly match the features within the circular window in the subsequently acquired images. The measurement result being 4 indicates qualification. In the second matching algorithm, the features of the four glue dots included in the planned rectangular window are trained, making the four glue dots a whole. The feature values obtained through this training are used as templates to quickly match the four glue dots in the subsequently acquired images. The measurement result being 1 indicates qualification;

[0022] S3c. Perform a logical "AND" operation on the first matching algorithm and the second matching algorithm, that is, an NG signal will be sent only when the measurement results of both the first matching algorithm and the second matching algorithm are unqualified;

[0023] S3d. Detect the consecutive number of NG signals. If the consecutive number of NG signals is 3 times, trigger the system fault alarm.

[0024] Furthermore, in step S2, the camera parameter adjustment module is the MVS software deployed on the PC side, and in step S3, the image processing module is the VISIONMASTER software deployed on the PC side.

[0025] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0026] The present invention can use an industrial camera to take real - time photos of the surface of the strip box paper during the packaging process, and process the acquired photos to determine whether the glue dots on the strip box paper are qualified. When unqualified, corresponding operations such as rejection and statistics are performed through the industrial control computer. In the present invention, a camera parameter adjustment module is also provided, through which the parameters of the camera can be conveniently adjusted and triggered. By adjusting and debugging the parameters on this module, it is possible to more easily find the parameters of clear and easy - to - process photos. During the use of the present invention, the image processing module processes the image. The processing process includes two matching algorithms. The first matching algorithm can use the feature value of one point to search for and match the subsequent four independent glue dots. The second matching algorithm can regard the four glue dots as a whole to match whether this whole exists in the subsequent images. Performing a logical "AND" operation on the two algorithms enables the detection method to consider both the size of the glue dots and the quantity and displacement of the glue dots to perform local and overall detection of the glue dots, thereby reducing the missed rejection rate and making the detection more stable. Brief Description of the Drawings

[0027] Figure 1This is a structural block diagram of the cigarette carton adhesive dot detection device according to the present invention.

[0028] Figure 2 This is a schematic diagram showing the installation location of an industrial camera.

[0029] Figure 3 This is a schematic diagram of the cigarette carton adhesive spot detection method according to the present invention.

[0030] Figure 4 This is a schematic diagram of the window interface for matching the features of a single glue dot within a circular window using the first matching algorithm.

[0031] Figure 5 This is a schematic diagram of the window interface for matching four glue dots within a rectangular window using the second matching algorithm. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0033] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0034] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0035] Please see Figure 1 This invention provides a device for detecting adhesive dots on cigarette cartons, comprising:

[0036] Industrial cameras are used to capture images of adhesive dots on carton paper.

[0037] In practical use, the industrial camera selected is a Hikvision industrial camera, model: MV-CA060-11GM. This camera is monochrome, [resolution missing], and supports Ethernet programming. (Reference...) Figure 2 The industrial camera described herein consists of two units. One unit is mounted on the turret folding guide rail bracket for detecting adhesive dots on the outer side of the carton paper, and the other unit is mounted on the wire groove bracket above the turret for detecting adhesive dots on the inner side of the carton paper. In addition, two LED light sources are included, which are located above the turret and illuminate the outer and inner sides of the carton paper to provide lighting for the industrial camera's shooting.

[0038] The camera parameter adjustment module is used to set the parameters and trigger conditions of the industrial camera and send the images.

[0039] The image processing module is used to receive and process images to determine whether the glue dots are qualified. When the glue dots are qualified, an NG signal is issued.

[0040] In practical use, the camera parameter adjustment module and the image processing module can be deployed on the same terminal device, such as on a PC. In this embodiment, the camera parameter adjustment module is the MVS software deployed on the PC, and the image processing module is the VISIONMASTER software deployed on the PC.

[0041] Optocoupler signal processing module, which is used to convert NG signals into electrical signals;

[0042] In practical applications, the optocoupler signal processing module used is the PHOENIX CONTACT PLC-BSC-24DC / 21.

[0043] Beckhoff controllers accept electrical signals and perform logic control on industrial control computers.

[0044] In practical use, Beckhoff uses the EL2018 controller.

[0045] On the other hand, please see Figure 3 Based on the above-mentioned cigarette carton adhesive spot detection device, the present invention also provides a method for detecting cigarette carton adhesive spots, including:

[0046] S1. Two industrial cameras and two LED light sources are installed at the turret of the packaging machine so that the industrial cameras can capture the glue dots on the inside and outside of the carton paper. The I / O terminals of the industrial cameras are connected to the optical coupler signal processing module, and the communication network cable of the industrial cameras is connected to the camera parameter adjustment module.

[0047] It should be noted that the outer camera is one station different from the inner camera in the photographing station. The solution is to create a new program block in the Beckhoff controller and compile the program to implement the function of a shift register for the photographing trigger signal of the outer camera. The trigger signal of the outer camera is shifted backward by one station compared to the inner camera and then triggers the photographing, ensuring that the inner camera and the outer camera are triggered successively with a difference of one station, and ensuring that the photos taken by the two cameras are of the same cigarette rod.

[0048] S2. Set the camera parameters and trigger conditions in the camera parameter adjustment module so as to obtain relatively clear and stable pictures and send the pictures.

[0049] Specifically, when setting the camera parameters and trigger conditions in the camera parameter adjustment module, the focal length of the industrial camera for photographing the outer glue dots is 0.1 mm, the aperture is f / 16, and the exposure time is 20,000; the focal length of the industrial camera for photographing the inner glue dots is 0.3 mm, the aperture is f / 16, and the exposure time is 20,000.

[0050] S3. Process and judge the acquired pictures through the image processing module, output the judgment result, and execute the next step if the output judgment result is an NG signal.

[0051] In the prior art, the image processing module usually processes image data with one algorithm. From the actual operation situation, since a set of detection algorithms directly determine the output result, if the sensitivity of the algorithm is adjusted too high or the glue dot morphology is distorted (which mostly occurs when the equipment speed changes), a large number of false rejections will occur. In addition, only processing with one algorithm will also lead to missed judgment situations. Therefore, in step S3, when processing and judging the acquired pictures through the image processing module, it specifically includes:

[0052] S3a. Perform filtering processing on the acquired image and extract the features of the glue dots.

[0053] S3b. Design the first matching algorithm and the second matching algorithm. As shown in Figure 4 , in the first matching algorithm, self-learning is performed on the pixels in the area within the planned circular window, and the feature values obtained through this training are used as templates to quickly match the features within the circular window in the subsequently acquired images. When the measurement result is 4, it is qualified. This algorithm mainly detects the specific morphology of each glue dot and whether it exists; as shown in Figure 5 , in the second matching algorithm, the features encompassing four glue dots in the planned rectangular window are trained, making the four glue dots as a whole, and the feature values obtained through this training are used as templates to quickly match the four glue dots in the subsequently acquired images. When the measurement result is 1, it is qualified. This algorithm mainly detects the overall glue application situation of the strip box glue dots, such as whether there is lack of glue or whether the positions of the glue dots are offset, etc.

[0054] S3c: Perform a logical AND operation on the first matching algorithm and the second matching algorithm, that is, an NG signal will only be issued when the measurement results of both the first matching algorithm and the second matching algorithm are unqualified.

[0055] S3d: Detect the number of consecutive NG signals. If the number of consecutive NG signals is 3, trigger a system fault alarm.

[0056] S4 and NG signals are transmitted to the Beckhoff controller via the camera output and optocoupler signal processing module. The Beckhoff controller then performs logic control on the industrial computer. This logic control includes controlling the rejection mechanism to reject non-conforming paper strips, triggering system fault alarms, and counting the number of non-conforming paper strips.

[0057] Taking the Hongtashan Classic 100 cigarettes produced by the B1#FOCKE FX2 production line in the Packaging Workshop 2 of the Yuxi Cigarette Factory of Hongta Group as an example, after the successful installation and commissioning of the carton paper glue shortage detection system, a one-month effect verification was carried out. Actual testing was conducted on the machine, using the B1#FOCKE FX2 production line in the Packaging Workshop 2 as the experimental subject, with weekly testing experiments. The two sets of data are shown in the table below:

[0058] Table 1: Effectiveness Experiment of Removing Glue Defects from Carton Paper

[0059]

[0060]

[0061] Table 2: Experimental rate of incorrect rejection due to glue deficiency in box paper

[0062]

[0063] Therefore, after a month and a sample size of 112,000 pieces, the visual detection system for missing glue spots on carton paper showed a missed count of 1, with a detection rate of 99.5%, which is higher than the target value of 95%. The false rejection rate of the visual detection system for missing glue spots on carton paper was 2.1%, indicating good detection performance.

[0064] Although the invention has been described herein with reference to several illustrative embodiments, it should be understood that many other modifications and implementations can be devised by those skilled in the art, which will fall within the scope and spirit of the principles disclosed herein. More specifically, various modifications and improvements can be made to the components or layout of the subject matter arrangement within the scope of the disclosure, drawings, and claims. Besides modifications and improvements to the components or layout, other uses will be apparent to those skilled in the art.

Claims

1. A device for detecting adhesive dots on cigarette cartons, characterized in that, Comprising: An industrial camera, which is used to collect images of the glue dots on the strip carton paper; A camera parameter adjustment module, which is used to set the parameters and triggering conditions of the industrial camera and send the images; An image processing module, which is used to receive the images and process the images to judge whether the glue dots are qualified, and send out an NG signal when judged to be qualified; An opto-coupler signal processing module, which is used to convert the NG signal into an electrical signal; A Beckhoff controller, which receives the electrical signal and conducts logical control on the industrial control computer.

2. The cigarette carton adhesive dot detection device according to claim 1, characterized in that: The number of the industrial cameras is 2, one of which is installed on the turret folding guide rail bracket for detecting the glue dots on the outer side of the strip carton paper, and the other is installed on the wire groove bracket above the turret for detecting the glue dots on the inner side of the strip carton paper.

3. The cigarette carton adhesive dot detection device according to claim 1, characterized in that: It further includes LED light sources, the number of which is two and located above the turret, so that the two LED light sources can irradiate the outer side and the inner side of the strip carton paper.

4. A method for detecting adhesive dots on cigarette cartons, characterized in that, Comprising: S1. At the turret of the packaging machine, two industrial cameras and two LED light sources are arranged, so that the industrial cameras can capture the glue dots on the inner side and the outer side of the strip carton paper, connect the I / O ends of the industrial cameras into the opto-coupler signal processing module, and connect the communication network cables of the industrial cameras into the camera parameter adjustment module; S2. Set the camera parameters and triggering conditions in the camera parameter adjustment module, so as to obtain clearer and more stable pictures and send the pictures; S3. Process and judge the acquired pictures through the image processing module, output the judgment result, and execute the next step if the output judgment result is an NG signal; S4. The NG signal is transmitted to the Beckhoff controller through the output end of the camera and the opto-coupler signal processing module, and the industrial control computer is logically controlled through the Beckhoff controller. The logical control includes controlling the rejection mechanism to reject the unqualified strip carton paper, triggering the system fault alarm, and counting the number of unqualified strip carton papers.

5. The method for detecting adhesive dots on cigarette cartons according to claim 1, characterized in that: In step S2, when setting the camera parameters and triggering conditions in the camera parameter adjustment module, among them, the focal length of the industrial camera for shooting the outer glue dots is 0.1 mm, the aperture is f / 16, and the exposure time is 20,000; the focal length of the industrial camera for shooting the inner glue dots is 0.3 mm, the aperture is f / 16, and the exposure time is 20,000.

6. The method for detecting adhesive dots in cigarette cartons according to claim 1, characterized in that: In the said step S3, when processing and judging the acquired pictures through the image processing module, it specifically includes: S3a. Perform filtering processing on the acquired images and extract the features of the glue dots; S3b. Design the first matching algorithm and the second matching algorithm. Among them, in the first matching algorithm, the pixels in the area within the planned circular window are self-learned, and the feature values obtained through this training are used as templates to quickly match the features within the circular window in the subsequent acquired images. The measurement result is qualified when it is 4; in the second matching algorithm, the features including four glue dots in the planned rectangular window are trained, so that the four glue dots are taken as a whole, and the feature values obtained through this training are used as templates to quickly match the four glue dots in the subsequent acquired images. The measurement result is qualified when it is 1; S3c. Perform a logical "AND" processing on the first matching algorithm and the second matching algorithm, that is, an NG signal will be sent out only when the measurement results of both the first matching algorithm and the second matching algorithm are unqualified; S3d: Detect the number of consecutive NG signals. If the number of consecutive NG signals is 3, trigger a system fault alarm.

7. The method for detecting adhesive dots on cigarette cartons according to claim 1, characterized in that: In step S2, the camera parameter adjustment module is the MVS software deployed on the PC. In step S3, the image processing module is the VISIONMASTER software deployed on the PC.

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