Dispensing path planning recognition system based on image recognition

Abstract

The invention provides a dispensing path planning recognition system based on image recognition. The dispensing path planning recognition system comprises an image acquisition module, an image processing module, a dispensing area recognition module, a pose recognition module and a path planning module, wherein a signal transmitting end of the image acquisition module is connected with a signal receiving end of the image processing module. According to the invention, the image of the LED circuit board is acquired through the image acquisition module, then the image is sent to the image processing module, the image processing module carries out denoising, contrast enhancement processing and image quality optimization on the image data of the LED circuit board, and then the features of pins and electronic components in the circuit board are extracted from the image. Compared with a traditional image processing technology, the method has the advantages that the image processing effect is improved, the image quality is optimized, fine elements or pins can be recognized, and a foundation can be laid for follow-up path planning.

Description

Technical Field

[0001] The present invention relates to a dispensing path planning and recognition system, specifically a dispensing path planning and recognition system based on image recognition, and belongs to the technical field of PCB processing. Background Art

[0002] LED circuit board glue dispensing is a crucial process in the manufacturing process of LED products. It mainly involves adding an appropriate amount of glue to the connection between LED components and circuit boards to achieve functions such as fixation, sealing, waterproofing, dustproofing, and corrosion resistance, thereby improving the performance and reliability of LED products.

[0003] Through dispensing, a stable connection between LED components and circuit boards can be ensured to prevent them from falling off due to vibration or impact. A protective film can also be formed to prevent the invasion of external pollutants such as moisture and dust, protecting circuit boards and components from damage. It can also enhance the seismic, vibration, waterproof, dustproof, and corrosion-resistant properties of LED products and extend their service life.

[0004] At present, when dispensing glue, the LED components and circuit boards are placed on the workbench of the dispensing machine, and then the dispensing machine is operated to dispense glue according to the set parameters. During the dispensing process, attention should be paid to controlling the accuracy of the glue output and the dispensing position.

[0005] In the existing technology, some traditional dispensing machine systems have integrated image processing technology, but due to factors such as algorithm complexity, image resolution or light source stability, the recognition accuracy cannot reach the ideal level, especially for tiny components or pins, which are more difficult to recognize; Moreover, many dispensing machines can only dispense glue according to preset tracks, which means that they need to be manually programmed or set according to the design drawings of the circuit board before production. This method is not only time-consuming and labor-intensive, but also unable to adapt to minor changes in the circuit board design or unexpected situations during the production process; Therefore, a dispensing path planning and recognition system based on image recognition is proposed. Summary of the invention

[0006] In view of this, the present invention provides a dispensing path planning and recognition system based on image recognition to solve or alleviate the technical problems existing in the prior art and at least provide a beneficial option.

[0007] The technical solution of the embodiment of the present invention is implemented as follows: a dispensing path planning and recognition system based on image recognition includes an image acquisition module, an image processing module, a dispensing area recognition module, a posture recognition module and a path planning module: The signal sending end of the image acquisition module is connected to the signal receiving end of the image processing module, the signal sending end of the image processing module is connected to the signal receiving end of the dispensing area identification module, the signal sending end of the dispensing area identification module is connected to the signal receiving end of the posture recognition module, the signal sending end of the posture recognition module is connected to the signal receiving end of the path planning module, and the signal sending end of the path planning module is connected to the dispensing machine; The image acquisition module is used to capture the image data of the LED circuit board in real time, and then send the image data to the image processing module; The image processing module is used to perform denoising and contrast enhancement processing on the image data of the LED circuit board to optimize the image quality, and then extract the pins and electronic component features in the circuit board from the image to determine the position and posture of the electronic components or pins on the LED circuit board; The glue dispensing area recognition module is used to calibrate the boundary of the area where glue dispensing is required according to the image processing results, identify the pin position characteristics and electronic component edge characteristics in the area, and provide a basis for path planning; The posture recognition module is used to identify the precise posture information of the LED circuit board based on feature point sampling; The path planning module is used to plan the optimal dispensing path using a path planning algorithm according to the workpiece's posture information and preset dispensing requirements.

[0008] Further preferably, the path planning algorithm comprises the following steps: Step 1: receiving the preset dispensing requirements input by the user, and parsing the input preset dispensing requirements; Step 2: Compare and analyze the posture information of the LED circuit board with the preset dispensing requirements; Step 3: Process the three-dimensional point cloud of the precise posture information of the LED circuit board, project it to the XOY plane, and obtain the edge contour point set through the convex hull algorithm; Step 4: Use the offset algorithm to offset the edge contour point by a fixed distance along the normal vector direction to determine the precise location of the dispensing; Step 5: Back-project the offset contour to the 3D point cloud to obtain the 3D dispensing path; Step 6: Further optimize the parameters of the generated preliminary path to obtain the optimal glue path.

[0009] Further preferably, in step one, the preset dispensing requirements include dispensing position, shape, size, speed and pressure parameters.

[0010] Further preferably, in step six, the optimized parameters include the length, speed and pressure of the path.

[0011] Further preferably, the image processing module includes a preprocessing module; The preprocessing module is used to perform denoising on the collected LED circuit board image, and use median filtering to eliminate or reduce the impact of noise on image quality; The preprocessing module is also used to enhance the contrast of the LED circuit board image by a histogram equalization method; The preprocessing module is also used to convert the color LED circuit board image into a grayscale image, and the grayscale image only contains brightness information but no color information.

[0012] Further preferably, the image processing module also includes a feature extraction module: The feature extraction module is used to extract the component edge and pin edge information on the LED circuit board image through an edge detection algorithm, segment the image into different areas or objects, perform shape analysis on the segmented objects, and extract shape features.

[0013] Further preferably, the image processing module further includes a template matching module: The template matching module is used to compare the preprocessed image with the template using a matching algorithm, calculate the similarity between each position in the image and the template, and find the position with the highest similarity as the matching result, and determine the position and posture of a specific component or pin on the circuit board based on the matching result.

[0014] Further preferably, the signal receiving end of the dispensing machine is connected to a monitoring feedback module, the signal sending end of the monitoring feedback module is connected to a dynamic adjustment module, and the signal sending end of the dynamic adjustment module is connected to the signal receiving end of the path planning module.

[0015] Further preferably, the monitoring feedback module is used to monitor the dispensing process of the dispensing machine in real time using a monitoring device, and when a path deviation occurs, the monitoring image data is sent to the dynamic adjustment module.

[0016] Further preferably, the dynamic adjustment module is used to dynamically adjust the dispensing path according to real-time image feedback, and then send the adjusted dispensing path to the path planning module.

[0017] The embodiment of the present invention has the following advantages due to the adoption of the above technical solution: 1. The present invention collects the image of the LED circuit board through the image acquisition module, and then sends the image to the image processing module. The image processing module performs denoising and contrast enhancement processing on the image data of the LED circuit board to optimize the image quality, and then extracts the pins and electronic component features in the circuit board from the image to determine the position and posture of the electronic components or pins on the LED circuit board. Compared with traditional image processing technology, the image processing effect is improved, the image quality is optimized, and subtle components or pins can be identified, thereby laying a good foundation for subsequent path planning.

[0018] 2. By setting up a path planning module, the present invention can use the path planning algorithm to plan the optimal glue dispensing path. The path planning module realizes the planning and execution of the optimal glue dispensing path through the steps of workpiece posture recognition, preset glue dispensing requirement analysis, path planning algorithm application, path execution and monitoring feedback, etc., thereby ensuring the accuracy and efficiency of glue dispensing and being able to adapt to slight changes in circuit board design or emergencies in the production process.

[0019] The above summary is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present invention will be readily apparent by reference to the accompanying drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 It is a structural diagram of the dispensing path planning and recognition system based on image recognition of the present invention; Figure 2 This is a flow chart of the steps of the path planning algorithm of the present invention. DETAILED DESCRIPTION

[0022] In the following, only some exemplary embodiments are briefly described. As those skilled in the art will appreciate, the described embodiments may be modified in various ways without departing from the spirit or scope of the present invention. Therefore, the drawings and descriptions are considered to be exemplary and non-restrictive in nature.

[0023] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0024] like Figure 1-2As shown, an embodiment of the present invention provides a dispensing path planning and recognition system based on image recognition, including an image acquisition module, an image processing module, a dispensing area recognition module, a posture recognition module and a path planning module: The signal sending end of the image acquisition module is connected to the signal receiving end of the image processing module, the signal sending end of the image processing module is connected to the signal receiving end of the dispensing area recognition module, the signal sending end of the dispensing area recognition module is connected to the signal receiving end of the posture recognition module, the signal sending end of the posture recognition module is connected to the signal receiving end of the path planning module, and the signal sending end of the path planning module is connected to the dispensing machine; The system is equipped with a computer processing unit, which is responsible for computing tasks such as image processing, recognition algorithm operation and path planning; The image acquisition module is used to capture the image data of the LED circuit board in real time, and then send the image data to the image processing module. The image acquisition module is a high-definition camera or an industrial camera with high sensitivity, high resolution and fast response capabilities to capture clear images of the workpiece to be dispensed. At the same time, a suitable light source is configured to ensure uniform lighting and no shadows during the image acquisition process, thereby improving image quality. The image processing module is used to perform denoising and contrast enhancement on the image data of the LED circuit board to optimize the image quality, and then extract the pins and electronic component features in the circuit board from the image to determine the position and posture of the electronic components or pins on the LED circuit board; The glue dispensing area recognition module is used to calibrate the boundaries of the area where glue dispensing is required based on the image processing results, identify the pin position features and electronic component edge features in the area, and provide a basis for path planning; The posture recognition module is used to identify the precise posture information of the LED circuit board based on feature point sampling. Through posture recognition, the precise position, posture and possible other related information of the workpiece, such as surface curvature, tilt angle, etc., can be obtained; The path planning module is used to plan the optimal dispensing path using the path planning algorithm according to the workpiece posture information and the preset dispensing requirements; The path planning module plans and executes the optimal glue dispensing path through steps such as workpiece posture recognition, preset glue dispensing requirement analysis, path planning algorithm application, path execution and monitoring feedback, ensuring the accuracy and efficiency of glue dispensing.

[0025] In one embodiment, the path planning algorithm comprises the following steps: Step 1: receiving the preset dispensing requirements input by the user, and parsing the input preset dispensing requirements, the preset dispensing requirements including the dispensing position, shape, size, speed and pressure parameters; Step 2: Compare and analyze the posture information of the LED circuit board with the preset dispensing requirements; Step 3: Process the three-dimensional point cloud of the precise posture information of the LED circuit board, project it to the XOY plane, and obtain the edge contour point set through the convex hull algorithm; Step 4: Use the offset algorithm to offset the edge contour point by a fixed distance along the normal vector direction to determine the precise location of the dispensing; Step 5: Back-project the offset contour to the 3D point cloud to obtain the 3D dispensing path; Step 6: Further optimize the parameters of the generated preliminary path to obtain the optimal glue path. The optimized parameters include the length, speed and pressure of the path.

[0026] In one embodiment, the image processing module includes a pre-processing module; The preprocessing module is used to perform denoising on the collected LED circuit board image, and use median filtering to eliminate or reduce the impact of noise on image quality; The pre-processing module is also used to enhance the contrast of the LED circuit board image through a histogram equalization method to improve the visual effect of the image and the accuracy of subsequent processing; The preprocessing module is also used to convert the color LED circuit board image into a grayscale image. The grayscale image only contains brightness information but not color information, which makes subsequent feature extraction and template matching more efficient.

[0027] Furthermore, the image processing module can improve the image quality and enhance the efficiency and accuracy of subsequent processing.

[0028] In one embodiment, the image processing module further includes a feature extraction module: The feature extraction module is used to extract the component edge and pin edge information on the LED circuit board image through the edge detection algorithm, segment the image into different areas or objects, perform shape analysis on the segmented objects, extract shape features, and then extract information useful for subsequent processing from the preprocessed image.

[0029] In one embodiment, the image processing module further includes a template matching module: The template matching module is used to compare the preprocessed image with the template using a matching algorithm, calculate the similarity between each position in the image and the template, and find the position with the highest similarity as the matching result. Based on the matching result, the position and posture of a specific component or pin on the circuit board are determined; Template matching is a technology that searches for the area in an image that is most similar to a given template. In the LED circuit board dispensing path planning and recognition system, template matching is often used to compare the preprocessed image with the preset template to identify specific components or pins on the circuit board.

[0030] In one embodiment, the signal receiving end of the dispensing machine is connected to a monitoring feedback module, the signal sending end of the monitoring feedback module is connected to a dynamic adjustment module, and the signal sending end of the dynamic adjustment module is connected to the signal receiving end of the path planning module; The monitoring feedback module is used to monitor the dispensing process of the dispensing machine in real time using a monitoring device, and when a path deviation occurs, the monitoring image data is sent to the dynamic adjustment module; The dynamic adjustment module is used to dynamically adjust the dispensing path according to real-time image feedback, and then send the adjusted dispensing path to the path planning module; During the dispensing process, the system is able to monitor image feedback in real time and make dynamic adjustments as needed, which ensures that dispensing accuracy and stability are maintained even in complex and changing production environments.

[0031] When the present invention is working: an image of an LED circuit board is collected by an image acquisition module, and then the image is sent to an image processing module, and the image data of the LED circuit board is denoised and contrast enhanced by the image processing module to optimize the image quality, and then the pins and electronic component features in the circuit board are extracted from the image, the position and posture of the electronic components or pins on the LED circuit board are determined, and the area marks requiring glue are calibrated by a glue spotting area recognition module, and the precise posture information of the LED circuit board is recognized by a posture recognition module, and then the path planning module realizes the planning and execution of the optimal glue spotting path through the steps of workpiece posture recognition, preset glue spotting requirement analysis, path planning algorithm application, path execution and monitoring feedback, etc., to ensure the accuracy and efficiency of glue spotting.

[0032] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of various changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. The dispensing path planning and recognition system based on image recognition includes an image acquisition module, an image processing module, a dispensing area recognition module, a posture recognition module and a path planning module, and is characterized by: The signal sending end of the image acquisition module is connected to the signal receiving end of the image processing module, the signal sending end of the image processing module is connected to the signal receiving end of the dispensing area identification module, the signal sending end of the dispensing area identification module is connected to the signal receiving end of the posture recognition module, the signal sending end of the posture recognition module is connected to the signal receiving end of the path planning module, and the signal sending end of the path planning module is connected to the dispensing machine; The image acquisition module is used to capture the image data of the LED circuit board in real time, and then send the image data to the image processing module; The image processing module is used to perform denoising and contrast enhancement processing on the image data of the LED circuit board to optimize the image quality, and then extract the pins and electronic component features in the circuit board from the image to determine the position and posture of the electronic components or pins on the LED circuit board; The glue dispensing area recognition module is used to calibrate the boundary of the area where glue dispensing is required according to the image processing results, identify the pin position characteristics and electronic component edge characteristics in the area, and provide a basis for path planning; The posture recognition module is used to identify the precise posture information of the LED circuit board based on feature point sampling; The path planning module is used to plan the optimal dispensing path using a path planning algorithm according to the workpiece's posture information and preset dispensing requirements.

2. The dispensing path planning and recognition system based on image recognition according to claim 1 is characterized in that: The path planning algorithm comprises the following steps: Step 1: receiving the preset dispensing requirements input by the user, and parsing the input preset dispensing requirements; Step 2: Compare and analyze the posture information of the LED circuit board with the preset dispensing requirements; Step 3: Process the three-dimensional point cloud of the precise posture information of the LED circuit board, project it to the XOY plane, and obtain the edge contour point set through the convex hull algorithm; Step 4: Use the offset algorithm to offset the edge contour point by a fixed distance along the normal vector direction to determine the precise location of the dispensing; Step 5: Back-project the offset contour to the 3D point cloud to obtain the 3D dispensing path; Step 6: Further optimize the parameters of the generated preliminary path to obtain the optimal glue path.

3. The dispensing path planning and recognition system based on image recognition according to claim 2 is characterized in that: In step one, the preset dispensing requirements include dispensing position, shape, size, speed and pressure parameters.

4. The dispensing path planning and recognition system based on image recognition according to claim 2 is characterized in that: In step six, the optimized parameters include path length, speed, and pressure.

5. The dispensing path planning and recognition system based on image recognition according to claim 1 is characterized in that: The image processing module includes a preprocessing module; The preprocessing module is used to perform denoising on the collected LED circuit board image, and use median filtering to eliminate or reduce the impact of noise on image quality; The preprocessing module is also used to enhance the contrast of the LED circuit board image by a histogram equalization method; The preprocessing module is also used to convert the color LED circuit board image into a grayscale image, and the grayscale image only contains brightness information but no color information.

6. The dispensing path planning and recognition system based on image recognition according to claim 5 is characterized in that: The image processing module also includes a feature extraction module: The feature extraction module is used to extract the component edge and pin edge information on the LED circuit board image through an edge detection algorithm, segment the image into different areas or objects, perform shape analysis on the segmented objects, and extract shape features.

7. The dispensing path planning and recognition system based on image recognition according to claim 6 is characterized in that: The image processing module also includes a template matching module: The template matching module is used to compare the preprocessed image with the template using a matching algorithm, calculate the similarity between each position in the image and the template, and find the position with the highest similarity as the matching result, and determine the position and posture of a specific component or pin on the circuit board based on the matching result.

8. The dispensing path planning and recognition system based on image recognition according to claim 1 is characterized in that: The signal receiving end of the dispensing machine is connected to a monitoring feedback module, the signal sending end of the monitoring feedback module is connected to a dynamic adjustment module, and the signal sending end of the dynamic adjustment module is connected to the signal receiving end of the path planning module.

9. The dispensing path planning and recognition system based on image recognition according to claim 8, characterized in that: The monitoring feedback module is used to monitor the dispensing process of the dispensing machine in real time using a monitoring device, and when a path deviation occurs, the monitoring image data is sent to the dynamic adjustment module.

10. The dispensing path planning and recognition system based on image recognition according to claim 9, characterized in that: The dynamic adjustment module is used to dynamically adjust the dispensing path according to real-time image feedback, and then send the adjusted dispensing path to the path planning module.

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