Real-time online detection method and system for glue coating on dispensing nozzles

Abstract

The present invention relates to the field of glue dispensing technology, and in particular to a real-time online detection method for glue coating on a glue dispensing nozzle and a detection system thereof. The method comprises: before glue dispensing, moving the nozzle to a glue coating detection platform for image acquisition to obtain a first image, and obtaining a first circle center coordinate and four detection areas after processing; starting a process based on a preset number of glue dispensing times, moving the nozzle after glue dispensing to the glue coating detection platform for image acquisition to obtain a second image; processing the second image to obtain a target area of ​​the nozzle after glue dispensing, and detecting whether the current state of the nozzle is normal based on the target area; if normal, mapping four detection areas on the target area through affine transformation based on the first circle center coordinate, and segmenting the areas to obtain four target detection areas; if abnormal, an alarm is issued; respectively extracting glue from the four target detection areas to obtain corresponding glue areas, adding up the areas of all glue areas and comparing them with a preset value, and detecting glue coating on the glue dispensing nozzle according to the comparison result.

Description

Technical Field

[0001] The present invention relates to the technical field of glue dispensing, and in particular to a real-time online detection method for glue coating on a glue dispensing nozzle and a detection system thereof. Background Art

[0002] In the dispensing industry, glue sticking to the nozzle is a relatively common problem. When the viscosity of the glue is high and the fluidity is poor, it is easy for the glue to remain at the nozzle and gradually accumulate to form glue sticking. If the inner diameter of the nozzle is too small, the outlet shape is irregular, or the inner wall is not smooth, the chance of glue sticking to the wall will increase. If the dispensing pressure is too high or the speed is too fast, the glue will form a large impact force in the nozzle, causing the glue to splash and stick to the nozzle. On the contrary, if the pressure is too low or the speed is too slow, the glue will not flow smoothly and it will easily accumulate at the nozzle. Continuous and long-term dispensing operations will cause the nozzle to contact with the glue for a long time, increasing the possibility of glue sticking. Moreover, if the dispensing frequency is too high, the nozzle will not have enough time to empty the residual glue, which will also cause glue sticking.

[0003] To address these issues, existing technologies utilize high-resolution cameras and advanced image processing algorithms to monitor nozzle glue buildup, achieving high-precision detection and accurately identifying even the smallest amount of glue buildup on the nozzle. Furthermore, laser detection technology uses a laser beam to scan the nozzle surface and detect the presence of glue buildup based on changes in reflected light, offering non-contact, high-precision performance. These solutions typically require stopping the machine to inspect the needle for glue buildup and are not integrated into the dispensing process, impacting the dispenser's efficiency and yield. When inspecting glue buildup on nozzles, the color contrast between the glue and the nozzle or surrounding environment is extremely low, making it difficult for the human eye or standard visual inspection systems to clearly distinguish the boundary between the glue and the background, making it difficult to accurately identify glue buildup. Furthermore, glue absorbs light strongly and can reflect unevenly. This can result in unclear brightness differences between the glue-covered area and the surrounding area during image acquisition, complicating image processing and analysis and prone to misjudgments or omissions. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art.

[0005] To this end, the present invention provides a real-time online detection method for glue coating on a dispensing nozzle, which has high detection accuracy, high efficiency and high yield rate of dispensing products.

[0006] According to an embodiment of the present invention, a real-time online detection method for glue coating on a dispensing nozzle comprises the following steps:

[0007] S1, before dispensing glue, move the nozzle to the glue coating detection platform, collect an image of the nozzle to obtain a first image, process the first image to obtain the first center coordinates (x1, y1) of the nozzle before dispensing glue and four detection areas;

[0008] S2, starting a glue-coating detection process based on a preset number of glue dispensing times, moving the nozzle after glue dispensing to the glue-coating detection platform for image acquisition to obtain a second image;

[0009] S3, processing the second image based on a Blob analysis method to obtain a target area of ​​the nozzle after dispensing, and detecting whether the current state of the nozzle is normal based on the target area;

[0010] If the current nozzle status is normal, then based on the first circle center coordinate (x1, y1), the four detection areas are mapped on the target area through affine transformation, and the area segmentation is performed to obtain the four target detection areas of the nozzle after dispensing, and then proceed to the next step. If the current nozzle status is abnormal, an alarm is issued to remind that manual processing is required;

[0011] S4, extracting glue from the four target detection areas to obtain corresponding glue areas, adding up the areas of all glue areas and comparing them with a preset value, and performing glue hanging detection on the glue dispensing nozzle according to the comparison result.

[0012] The beneficial effect of the present invention is that the real-time online detection method for glue hanging on the glue dispensing nozzle of the present invention first obtains the center coordinates and detection area of ​​the nozzle before glue dispensing, then obtains the nozzle image after glue dispensing, processes the nozzle image after glue dispensing, and combines the affine transformation technology to obtain the target detection area, performs glue extraction on each target detection area, obtains the glue area of ​​different target detection areas, and then calculates the area of ​​all glue areas. The glue hanging detection of the glue dispensing nozzle is performed based on the area of ​​all glue areas. The accuracy of the glue hanging detection of the nozzle is high, and while ensuring the accuracy of the detection, the glue of the four target detection areas can be extracted together, thereby improving the detection efficiency. In addition, since the glue hanging detection process is started based on the preset number of glue dispensing times, the glue hanging on the nozzle can be discovered in time, the yield rate of the glue dispensing product is improved, and the life cycle of the nozzle can be better maintained and monitored.

[0013] According to one embodiment of the present invention, in step S1, the first image is processed by a Blob analysis method to extract the first circle center coordinates (x1, y1);

[0014] The first image is displayed through a human-computer interaction interface, and area division is performed to obtain four detection areas, which are the nozzle port area, the nozzle side wall area, the nozzle plane area, and the nozzle out-of-plane area.

[0015] According to one embodiment of the present invention, in step S3, mapping the four detection areas on the target area through affine transformation based on the center coordinates of the nozzle specifically includes:

[0016] The second image is processed by Blob analysis to extract the center coordinates (xi, yi) of the nozzle after dispensing;

[0017] Positioning the second image based on the first circle center coordinates (x1, y1) and the center coordinates (xi, yi) of the nozzle after dispensing;

[0018] The first circle center coordinate (x1, y1) is mapped to the second image to obtain the affine transformation matrix for glue detection and positioning. The calculation formula is expressed as:

[0019]

[0020] Among them, the rotation matrix R and the translation vector T;

[0021] The four detection areas are mapped on the target area through the affine transformation matrix of the glue detection positioning, and the area segmentation is performed to obtain the four target detection areas of the nozzle after dispensing. The four target detection areas correspond one-to-one to the four detection areas, namely: the nozzle port target detection area, the nozzle side wall target detection area, the nozzle plane target detection area and the nozzle out of the plane target detection area.

[0022] According to one embodiment of the present invention, the glue extraction from the four target detection areas in step S4 includes: glue extraction from the nozzle port target detection area, glue extraction from the nozzle side wall target detection area, glue extraction from the nozzle plane target detection area, and glue extraction from the nozzle beyond the plane target detection area.

[0023] According to one embodiment of the present invention, extracting glue from the target detection area of ​​the nozzle port includes:

[0024] Extracting a bright ring at the nozzle port through grayscale threshold segmentation based on the reflective properties of the glue. Determining whether the nozzle port target detection area is glued based on the roundness of the bright ring. If glue is present, extracting the glue from the nozzle port target detection area based on the grayscale value of the glue outside the bright ring to obtain a first glue area.

[0025] The number of pixels in the first glue area is calculated to obtain the area of ​​the first glue area.

[0026] According to one embodiment of the present invention, extracting glue from the target detection area on the nozzle side wall includes:

[0027] Extracting a dark area of ​​the nozzle side wall target detection area by dynamic threshold segmentation, and processing the dark area by morphological operation, wherein the processed dark area is the second glue area; or

[0028] Extracting the glue-free area of ​​the nozzle sidewall target detection area through dynamic threshold segmentation, connecting all glue-free areas by combining global threshold segmentation and morphological operation, and then subtracting all glue-free areas from the nozzle sidewall to obtain a second glue area;

[0029] The number of pixels in the second glue area is calculated to obtain the area of ​​the second glue area.

[0030] According to one embodiment of the present invention, the glue extraction from the plane target detection area of ​​the nozzle and the glue extraction from the nozzle beyond the plane target detection area include:

[0031] The nozzle plane target detection area and the bright area where the nozzle exceeds the plane target detection area are extracted respectively by global threshold segmentation to obtain the third glue area and the fourth glue area;

[0032] The number of pixels in the third glue region and the fourth glue region are respectively calculated to obtain the area of ​​the third glue region and the area of ​​the fourth glue region.

[0033] According to one embodiment of the present invention, if the total area of ​​all glue areas is greater than a preset value, it is determined that the current nozzle is glued, an alarm is issued, and a manual eraser is prompted or an eraser unit is controlled to erase the glue.

[0034] According to one embodiment of the present invention, processing the first image by using a Blob analysis method to extract the first circle center coordinates (x1, y1) specifically includes:

[0035] performing sharpening processing on the first image, and filtering the sharpened image using a low-pass filter;

[0036] Performing enhancement processing on the filtered image to obtain an enhanced image;

[0037] Binarizing the enhanced image to obtain a region with the largest area;

[0038] The largest area is processed through morphological operations and regional morphological operations to obtain the target area;

[0039] Calculate the maximum inscribed circle of the target area and obtain the first center coordinate (x1, y1) through the area_center operator.

[0040] According to an embodiment of the present invention, a real-time online detection system for glue coating on a dispensing nozzle includes:

[0041] A glue detection platform is configured for image acquisition;

[0042] A host computer, the host computer is connected to the glue coating detection platform, and the host computer is configured to execute the above-mentioned real-time online detection method for glue coating on the glue dispensing nozzle;

[0043] The glue detection platform includes: an industrial camera, an industrial lens, a corner prism and a ring-shaped shadowless light source;

[0044] The industrial camera, the industrial lens and the corner prism are coaxially arranged in sequence;

[0045] The corner prism and the annular shadowless light source are arranged opposite to each other;

[0046] When the glue coating of the dispensing nozzle is detected online in real time, the dispensing nozzle is moved to the annular shadowless light source so that the axis of the dispensing nozzle and the axis of the annular shadowless light source are in the same straight line.

[0047] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0048] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The present invention will be further described below with reference to the accompanying drawings and examples.

[0050] Figure 1 It is a schematic diagram of the method flow of embodiment 1 of the present invention.

[0051] Figure 2 This is a schematic diagram of the detection area division according to the first embodiment of the present invention.

[0052] Figure 3 This is a second image schematic diagram of the first embodiment of the present invention.

[0053] Figure 4 Schematic diagram of the target detection area image of the nozzle port according to the first embodiment of the present invention.

[0054] Figure 5 Schematic diagram of the bright ring of the nozzle port in embodiment 1 of the present invention.

[0055] Figure 6 It is a structural diagram of the glue coating detection platform of the second embodiment of the present invention.

[0056] Figure 7 Schematic diagram of a computer device according to a third embodiment of the present invention.

[0057] In the figure: 11, industrial camera; 12, industrial lens; 13, corner prism; 14, annular shadowless light source; 10, computer equipment; 1002, processor; 1004 memory; 1006, transmission device. DETAILED DESCRIPTION

[0058] The present invention will now be described in further detail with reference to the accompanying drawings, which are simplified schematic diagrams that illustrate the basic structure of the present invention in a schematic manner.

[0059] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, features defined as "first" or "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0060] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0061] Example 1

[0062] The embodiment of the present application provides a real-time online detection method for glue coating on a dispensing nozzle, such as Figure 1 As shown, the method includes the following steps:

[0063] S1, before dispensing glue, move the nozzle to the glue detection platform, collect the image of the nozzle, obtain the first image, process the first image, obtain the first center coordinates (x1, y1) of the nozzle before dispensing glue and four detection areas; further, process the first image by Blob analysis method, extract the first center coordinates (x1, y1); display the first image through the human-computer interaction interface, and divide the area to obtain four detection areas, such as Figure 2As shown, the four detection areas are the nozzle port area, the nozzle side wall area, the nozzle plane area and the nozzle out-of-plane area.

[0064] S2, based on the preset number of dispensing times, starts the glue-hanging detection process, moves the nozzle after dispensing glue to the glue-hanging detection platform for image acquisition, and obtains the second image, see Figure 3 As shown in the figure, if the preset number of dispensing times is 3, the glue hanging detection is started when the nozzle is detected to have dispensed glue 3 times, thus realizing real-time online detection and avoiding manual start-up process, which improves detection efficiency.

[0065] S3, based on the Blob analysis method, processes the second image to obtain the target area of ​​the nozzle after dispensing, and detects whether the current status of the nozzle is normal based on the target area; if the current status of the nozzle is normal, then based on the first circle center coordinate (x1, y1), four detection areas are mapped on the target area through affine transformation, and the area is segmented to obtain the four target detection areas of the nozzle after dispensing, and proceed to the next step. If the current status of the nozzle is abnormal, an alarm is issued to remind that manual processing is required.

[0066] S4, extracting glue from the four target detection areas to obtain corresponding glue areas, adding up the areas of all glue areas and comparing them with a preset value, and performing glue detection on the dispensing nozzle based on the comparison result.

[0067] In this embodiment, in step S3, the nozzle may not appear in the second image due to motion control or mechanical errors. The state of the current nozzle is detected based on the target area, that is, whether the current nozzle is in the second image is determined. The target area of ​​the nozzle is extracted through threshold segmentation, and the area of ​​the target area is determined to determine whether it is in a reasonable position.

[0068] Furthermore, mapping the detection area on the target area through affine transformation based on the center coordinates of the nozzle specifically includes:

[0069] The second image is processed by Blob analysis method to extract the center coordinates (xi, yi) of the nozzle after dispensing.

[0070] The positioning of the second image is completed based on the first circle center coordinates (x1, y1) and the center coordinates of the nozzle after dispensing (xi, yi).

[0071] Map the coordinates of the first circle center (x1, y1) to the second image to obtain the affine transformation matrix for glue detection and positioning. The affine transformation matrix for glue detection and positioning is a rigid affine transformation calculated based on the point correspondence and two corresponding angles, that is, a transformation consisting of a rotation matrix R and a translation vector T, and returns it as a homogeneous transformation matrix HomMat2D. The calculation formula for the affine transformation matrix for glue detection and positioning is expressed as:

[0072]

[0073] Among them, the rotation matrix R and the translation vector T.

[0074] Through the glue hanging detection positioning affine transformation matrix, four detection areas are mapped on the target area, and the area is segmented to obtain the four target detection areas of the nozzle after dispensing. The four target detection areas correspond one-to-one to the four detection areas, namely: nozzle port target detection area, nozzle side wall target detection area, nozzle plane target detection area, and nozzle out-of-plane target detection area.

[0075] In this embodiment, glue extraction from the four target inspection areas in step S4 includes: extracting glue from the nozzle port target inspection area, extracting glue from the nozzle sidewall target inspection area, extracting glue from the nozzle plane target inspection area, and extracting glue from the nozzle protruding from the plane target inspection area. During glue extraction, the four target inspection areas can be processed simultaneously, increasing the glue extraction speed and, therefore, the inspection efficiency.

[0076] Specifically, Figure 4 The nozzle port target detection area is shown, and glue extraction from the nozzle port target detection area includes:

[0077] According to the reflection characteristics of the glue, the bright ring of the nozzle port is extracted by grayscale threshold segmentation, such as Figure 5 As shown, whether the nozzle port target detection area is glued is determined based on the roundness of the bright ring. If glue is attached, the glue in the nozzle port target detection area is extracted according to the grayscale value of the glue outside the bright ring to obtain the first glue area.

[0078] The number of pixels in the first glue area is calculated to obtain the area of ​​the first glue area.

[0079] It should be noted that the bright ring of normal glue in the nozzle is close to a standard circle, while the bright ring is elliptical when glue is applied to the nozzle port. The roundness of the bright ring is obtained by the ratio of the area of ​​the bright ring and the area of ​​the approximate minimum circumscribed circle of the bright ring obtained by the smallest_circle operator. If the roundness value of the bright ring is closer to 1, the shape of the area is closer to a circle, and the target detection area of ​​the nozzle port is not glued; otherwise, the target detection area of ​​the nozzle port is glued.

[0080] Glue extraction from the target inspection area on the nozzle side wall includes:

[0081] When there is little glue on the nozzle side wall, the dark area of ​​the nozzle side wall target detection area is extracted by dynamic threshold segmentation, and the dark area is processed by morphological operation. The processed dark area is the second glue area; or when there is a lot of glue on the nozzle side wall, the area without glue distribution in the nozzle side wall target detection area is extracted by dynamic threshold segmentation, and all glue-free areas are connected by combining global threshold segmentation and morphological operation, and then the second glue area is obtained by subtracting all glue-free areas from the nozzle side wall area.

[0082] The number of pixels in the second glue region is calculated to obtain the area of ​​the second glue region.

[0083] Morphological operations can eliminate the interference of impurities and residual glue marks on the side wall itself, thereby improving detection accuracy.

[0084] Glue extraction from the nozzle plane target detection area and glue extraction from the nozzle beyond the plane target detection area include:

[0085] The nozzle plane target detection area and the bright area where the nozzle exceeds the plane target detection area are extracted respectively by global threshold segmentation to obtain the third glue area and the fourth glue area.

[0086] The number of pixels in the third glue region and the fourth glue region are respectively calculated to obtain the area of ​​the third glue region and the area of ​​the fourth glue region.

[0087] Add the area of ​​the first glue area, the area of ​​the second glue area, the area of ​​the third glue area and the area of ​​the fourth glue area to obtain the total area of ​​the glue area. If the total area of ​​the glue area is greater than the preset value, the current nozzle is glued and an alarm is issued, prompting manual wiping or controlling the wiping unit to rub the glue.

[0088] In this embodiment, processing the first image by using the Blob analysis method to extract the first circle center coordinates (x1, y1) specifically includes the following steps:

[0089] The first image is sharpened, and the sharpened image is filtered using a low-pass filter.

[0090] The filtered image is enhanced to obtain an enhanced image.

[0091] The image is enhanced by binarization to obtain the largest area.

[0092] The largest area is processed through morphological operations and regional morphological operations to obtain the target area.

[0093] Calculate the maximum inscribed circle of the target area and obtain the first center coordinates (x1, y1) through the area_center operator. Further, calculate the maximum inscribed circle of the target area through the halcon operator.

[0094] It should be noted that the steps for obtaining the center coordinates (xi, yi) of the nozzle after dispensing are the same as those for obtaining the first center coordinates (x1, y1). For the sake of brevity, they will not be repeated here.

[0095] This embodiment is applicable to the detection of glue hanging from glue nozzles of other colors except transparent glue nozzles, such as black, white, etc. It is only necessary to adapt the corresponding light source on the glue hanging detection platform so that the glue can be quickly imaged and the glue can be highlighted in the collected image, which can improve the detection accuracy and efficiency.

[0096] The real-time online detection method for glue sticking on the dispensing nozzle of this embodiment first obtains the center coordinates and detection area of ​​the nozzle before dispensing, then obtains the nozzle image after dispensing, processes the nozzle image after dispensing, and combines affine transformation technology to obtain the target detection area, performs glue extraction on each target detection area, obtains the glue area of ​​different target detection areas, and then calculates the area of ​​all glue areas. The glue sticking detection of the dispensing nozzle is performed based on the area of ​​all glue areas. The accuracy of the nozzle glue sticking detection is high, and while ensuring the detection accuracy, the glue of the four target detection areas can be extracted together, thereby improving the detection efficiency. In addition, since the glue sticking detection process is started based on the preset number of glue dispensing times, the nozzle glue sticking can be detected in a timely manner, which improves the yield rate of the dispensing product and can better maintain and monitor the life cycle of the nozzle.

[0097] Example 2

[0098] The present invention provides a real-time online detection system for glue coating on a dispensing nozzle, the system comprising:

[0099] The glue detection platform is configured for image acquisition.

[0100] The host computer is connected to the glue hanging detection platform, and the host computer is configured to execute the above-mentioned real-time online detection method for glue hanging on the dispensing nozzle.

[0101] Further, such as Figure 6 As shown, the glue detection platform includes: an industrial camera 11, an industrial lens 12, a corner prism 13 and an annular shadowless light source 14.

[0102] The industrial camera 11, the industrial lens 12 and the corner prism 13 are coaxially arranged in sequence.

[0103] The corner prism 13 and the annular shadowless light source 14 are arranged opposite to each other.

[0104] When the glue application of the glue dispensing nozzle is detected online in real time, the glue dispensing nozzle is moved to the annular shadowless light source 14 so that the axis of the glue dispensing nozzle and the axis of the annular shadowless light source 14 are in the same straight line.

[0105] For example, if the glue to be detected is black glue, the color adapted by the annular shadowless light source 14 is red, so that the black glue can be quickly imaged, the glue can be highlighted in the collected image, and the color contrast between the black glue and the nozzle or the surrounding environment can be improved.

[0106] The foregoing Figure 1 The various variations and specific examples of the real-time online detection method for glue coating on a dispensing nozzle in Example 1 are also applicable to a real-time online detection system for glue coating on a dispensing nozzle in this embodiment. Through the above detailed description of the real-time online detection method for glue coating on a dispensing nozzle, those skilled in the art can clearly know the implementation method of a real-time online detection system for glue coating on a dispensing nozzle in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here.

[0107] Example 3

[0108] An embodiment of the present application provides a computer device, which includes a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by the processor to implement a real-time online detection method for glue coating on a dispensing nozzle as provided in the above method embodiment.

[0109] Figure 7 The hardware structure diagram of a device for implementing a real-time online detection method for glue coating on a dispensing nozzle provided in an embodiment of the present application is shown. The device can participate in or include the device or system provided in an embodiment of the present application. Figure 7 As shown, the computer device 10 may include one or more processors 1002 (the processor may include but is not limited to a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 1004 for storing data, and a transmission device 1006 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, a power supply and / or a camera. It will be understood by those skilled in the art that Figure 7 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 7 More or fewer components than shown, or with Figure 7 Different configurations shown.

[0110] It should be noted that the one or more processors and / or other data processing circuits described above may generally be referred to herein as "data processing circuitry". The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuitry may be a single independent processing module, or may be incorporated in whole or in part into any of the other components of the computer device 10 (or mobile device). As described in the embodiments of the present application, the data processing circuitry serves as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0111] The memory 1004 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to a real-time online detection method for glue coating on a dispensing nozzle in an embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 1004, that is, implementing one of the above methods. The memory 1004 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 1004 may further include a memory remotely located relative to the processor, and these remote memories may be connected to the computer device 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0112] Transmission device 1006 is configured to receive or transmit data via a network. A specific example of the aforementioned network may include a wireless network provided by the communications provider of computer device 10. In one embodiment, transmission device 1006 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, transmission device 1006 may be a radio frequency (RF) module configured to communicate with the Internet wirelessly.

[0113] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer device 10 (or mobile device).

[0114] Example 4

[0115] An embodiment of the present application also provides a computer-readable storage medium, which can be set in a server to store at least one instruction or at least one program related to a real-time online detection method for glue coating on a dispensing nozzle in a method embodiment. The at least one instruction or the at least one program is loaded and executed by the processor to implement a real-time online detection method for glue coating on a dispensing nozzle provided in the above method embodiment.

[0116] Optionally, in this embodiment, the storage medium may be located in at least one of a plurality of network servers in a computer network. Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk, or an optical disk.

[0117] Example 5

[0118] An embodiment of the present invention further provides a computer program product or computer program, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform a method for real-time online detection of glue coating on a dispensing nozzle provided in various optional embodiments described above.

[0119] It should be noted that the order of the embodiments of the present application described above is for descriptive purposes only and does not represent the superiority or inferiority of the embodiments. The above description is of specific embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0120] The various embodiments in this application are described in a progressive manner. Similar portions between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the device, equipment, and storage medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simple. For relevant portions, refer to the descriptions of the method embodiments.

[0121] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, which may be a read-only memory, a disk, or an optical disk, etc.

[0122] With the above-described preferred embodiments of the present invention as a guide, and with reference to the above description, relevant personnel are fully capable of making various changes and modifications without departing from the technical spirit of this invention. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A real-time online detection method for glue coating on a dispensing nozzle, characterized in that: The method comprises the following steps: S1, before dispensing glue, move the nozzle to the glue coating detection platform, collect an image of the nozzle to obtain a first image, process the first image to obtain the first center coordinates (x1, y1) of the nozzle before dispensing glue and four detection areas; S2, starting a glue-coating detection process based on a preset number of glue dispensing times, moving the nozzle after glue dispensing to the glue-coating detection platform for image acquisition to obtain a second image; S3, processing the second image based on a Blob analysis method to obtain a target area of ​​the nozzle after dispensing, and detecting whether the current state of the nozzle is normal based on the target area; If the current nozzle status is normal, then based on the first circle center coordinate (x1, y1), the four detection areas are mapped on the target area through affine transformation, and the area segmentation is performed to obtain the four target detection areas of the nozzle after dispensing, and then proceed to the next step; if the current nozzle status is abnormal, an alarm is issued to remind that manual processing is required; The acquisition process of the four target detection areas of the nozzle after dispensing includes: The second image is processed by Blob analysis to extract the center coordinates (xi, yi) of the nozzle after dispensing; Positioning the second image based on the first circle center coordinates (x1, y1) and the center coordinates (xi, yi) of the nozzle after dispensing; The first circle center coordinate (x1, y1) is mapped to the second image to obtain the affine transformation matrix for glue detection and positioning. The calculation formula of the affine transformation matrix is ​​expressed as: Among them, the rotation matrix R and the translation vector T; The four detection areas are mapped on the target area by the affine transformation matrix of the glue detection positioning, and the area segmentation is performed to obtain four target detection areas of the nozzle after dispensing. The four target detection areas correspond to the four detection areas one by one, namely: the nozzle port target detection area, the nozzle side wall target detection area, the nozzle plane target detection area, and the nozzle out of the plane target detection area; S4, extracting glue from the four target detection areas to obtain corresponding glue areas, adding up the areas of all glue areas and comparing them with a preset value, and performing glue hanging detection on the glue dispensing nozzle according to the comparison result.

2. The real-time online detection method for glue coating on a dispensing nozzle according to claim 1, characterized in that: In step S1, the first image is processed by a Blob analysis method to extract the first circle center coordinates (x1, y1); The first image is displayed through a human-computer interaction interface, and area division is performed to obtain four detection areas, which are the nozzle port area, the nozzle side wall area, the nozzle plane area, and the nozzle out-of-plane area.

3. The real-time online detection method for glue coating on a dispensing nozzle according to claim 1, characterized in that: Extracting glue from the four target detection areas in step S4 includes extracting glue from the nozzle port target detection area, extracting glue from the nozzle sidewall target detection area, extracting glue from the nozzle plane target detection area, and extracting glue from the nozzle out-of-plane target detection area.

4. The real-time online detection method for glue coating on a dispensing nozzle according to claim 3, characterized in that: Extracting glue from the target detection area of ​​the nozzle port includes: Extracting a bright ring at the nozzle port through grayscale threshold segmentation based on the reflective properties of the glue. Determining whether the nozzle port target detection area is glued based on the roundness of the bright ring. If glue is present, extracting the glue from the nozzle port target detection area based on the grayscale value of the glue outside the bright ring to obtain a first glue area. The number of pixels in the first glue area is calculated to obtain the area of ​​the first glue area.

5. The real-time online detection method for glue coating on a dispensing nozzle according to claim 3, characterized in that: Extracting glue from the target detection area on the nozzle side wall includes: Extracting a dark area of ​​the nozzle side wall target detection area by dynamic threshold segmentation, and processing the dark area by morphological operation, wherein the processed dark area is the second glue area; or Extracting the glue-free area of ​​the nozzle sidewall target detection area through dynamic threshold segmentation, connecting all glue-free areas by combining global threshold segmentation and morphological operation, and then subtracting all glue-free areas from the nozzle sidewall to obtain a second glue area; The number of pixels in the second glue area is calculated to obtain the area of ​​the second glue area.

6. The real-time online detection method for glue coating on a dispensing nozzle according to claim 3, characterized in that: Extracting glue from the plane target detection area of ​​the nozzle and extracting glue from the nozzle beyond the plane target detection area includes: The nozzle plane target detection area and the bright area where the nozzle exceeds the plane target detection area are extracted respectively by global threshold segmentation to obtain the third glue area and the fourth glue area; The number of pixels in the third glue region and the fourth glue region are respectively calculated to obtain the area of ​​the third glue region and the area of ​​the fourth glue region.

7. The real-time online detection method for glue coating on a dispensing nozzle according to claim 1, characterized in that: If the total area of ​​all glue areas is greater than the preset value, it is determined that the current nozzle is glued, an alarm is issued, and a manual operation is prompted to erase the glue or the glue erasing unit is controlled to erase the glue.

8. The real-time online detection method for glue coating on a dispensing nozzle according to claim 1, characterized in that: Processing the first image by using the Blob analysis method to extract the first circle center coordinates (x1, y1) specifically includes: performing sharpening processing on the first image, and filtering the sharpened image using a low-pass filter; Performing enhancement processing on the filtered image to obtain an enhanced image; Binarizing the enhanced image to obtain a region with the largest area; The largest area is processed through morphological operations and regional morphological operations to obtain the target area; Calculate the maximum inscribed circle of the target area and obtain the first center coordinate (x1, y1) through the area_center operator.

9. A real-time online detection system for glue coating on a dispensing nozzle, characterized in that: A glue detection platform is configured for image acquisition; A host computer, the host computer being connected to the glue coating detection platform, the host computer being configured to execute the real-time online detection method for glue coating on a dispensing nozzle according to any one of claims 1 to 8; The glue detection platform comprises: an industrial camera (11), an industrial lens (12), a corner prism (13) and an annular shadowless light source (14); The industrial camera (11), the industrial lens (12), and the corner prism (13) are coaxially arranged in sequence; The corner prism (13) and the annular shadowless light source (14) are arranged relative to each other; When the glue-coating of the glue dispensing nozzle is detected online in real time, the glue dispensing nozzle is moved onto the annular shadowless light source (14) so ​​that the axis of the glue dispensing nozzle and the axis of the annular shadowless light source (14) are in the same straight line.

Images