Positioning method for rapid laser repair of MicroLED array

Abstract

The invention relates to the technical field of MicroLED array laser repair, and discloses a positioning method for rapid laser repair of a MicroLED array. Comprising the following steps: 1) constructing a coordinate reference system in an equipment imaging view field, setting coordinate axes according to horizontal and vertical directions by taking a fixed angle and a boundary of an array as reference original points, and adjusting the unit length and the coverage range of the coordinate system for Micro LED arrays with different sizes and specifications to ensure that the whole array area is covered; according to the positioning method for rapid laser repair of the Micro LED array, the actual physical position of a positioning system and the actual physical position of the Micro LED array can be better matched, positioning errors caused by an inaccurate coordinate system are reduced, the result of each time of positioning can be compared and corrected by positioning a defect area for multiple times, and the positioning accuracy is improved. Error accumulation possibly generated by single-time positioning is effectively reduced, especially when a complex Micro LED array is processed, multiple times of positioning can continuously optimize the positioning result, and the finally determined defect position is more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of MicroLED array laser repair, and in particular to a positioning method for rapid laser repair of a MicroLED array. Background Art

[0002] Micro LED array refers to a high-density LED array formed by assembling self-luminous micron-sized LEDs as light-emitting pixel units on a driving panel. The main application directions of Micro LED arrays include TVs, computer monitors, mobile phone screens, tablets, wearable devices, etc., which can provide high-quality, high-contrast, and high-resolution display effects, bringing users a better visual experience.

[0003] In the field of modern display technology, MicroLED arrays are rapidly becoming a strong competitor for the next generation of display technology with their excellent performance. However, in the manufacturing process of MicroLED arrays, various defects are inevitable due to the complexity of the process and the challenges of the technology. These defects may originate from multiple links, such as crystal defects in the epitaxial growth process, lithography deviations in the chip manufacturing process, chip offset or damage during mass transfer, and contamination in the packaging process. Common defects include pixel failure, uneven brightness, color deviation, etc. According to industry statistics, the defect rate in the manufacturing process of MicroLED arrays is still at a high level, which not only seriously affects the yield rate of the product, but also leads to a significant increase in production costs, limiting the large-scale commercial application of MicroLED technology. Laser repair technology, as an effective defect repair method, provides a feasible solution to solve the defect problem of MicroLED arrays. By precisely controlling the energy and action position of the laser, defective MicroLED chips can be repaired, such as repairing electrical defects such as open circuits and short circuits, and adjusting optical properties such as brightness and color. However, the key premise of laser repair is to be able to quickly and accurately locate the defect position in the MicroLED array.

[0004] Although existing technologies can obtain image information of MicroLED arrays, it is difficult to accurately determine the specific location of defects when faced with high-density, tiny-sized MicroLED pixels due to limitations in resolution and accuracy, especially for sub-pixel-level defect positioning. Although positioning methods based on electrical detection can detect pixels with abnormal electrical performance, the detection speed is slow and it is difficult to achieve rapid repair. In complex array structures, interference and crosstalk of electrical signals will also affect the accuracy of positioning. In addition, the structural and process characteristics of MicroLED arrays make defect positioning more complicated. The pixel size is tiny and the spacing is extremely narrow. MicroLED arrays of different batches and specifications differ in structure and parameters, which places higher requirements on the versatility and adaptability of positioning methods.

[0005] It can be seen that a positioning method for rapid laser repair of MicroLED arrays is needed to solve the problem that the existing positioning method mentioned in the above background technology is difficult to accurately determine the specific location of the defect. Summary of the invention

[0006] The object of the present invention is to provide a positioning method for rapid laser repair of a MicroLED array to solve the problems raised in the above-mentioned background technology.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: A positioning method for laser rapid repair of MicroLED arrays, comprising: 1) constructing a coordinate reference system within the imaging field of view of the device, taking a fixed angle and boundary of the array as the reference origin, setting the coordinate axis in the horizontal and vertical directions, and adjusting the unit length and coverage of the coordinate system for MicroLED arrays of different sizes and specifications to ensure that the entire array area is covered; 2) Use high-resolution optical imaging equipment to perform comprehensive scanning and imaging of the MicroLED array. Based on the preset image analysis algorithm, the system identifies potential defect areas with dark pixels, abnormal brightness, color deviation and other problems, and performs preliminary defect identification and marking; 3) For the initially marked defective areas, a sub-pixel positioning algorithm is used for accurate positioning; 4) Multimodal data fusion positioning: introduce electrical detection data, use machine learning algorithms to process multimodal data, and more accurately determine the true location of defects; 5) Perform coordinate conversion and calibration operations. According to the geometric relationship between the imaging device and the laser processing equipment, establish a conversion model between the coordinate systems of the two. Convert the image coordinate system of the imaging device to the motion coordinate system of the laser processing equipment to ensure that the laser beam accurately irradiates the defect position.

[0008] Preferably, the reference origin in 1) is selected from a physical mark in the Micro LED array that is easily identifiable, including a cross mark preset in the process, a specific electrode structure, a package boundary corner point or others, and the optical feature extraction includes: acquiring the array image through a high-resolution industrial camera and automatically identifying the coordinates of the reference point using an image processing algorithm.

[0009] Preferably, laser ranging can be used to assist positioning between 2) and 3), and a confocal laser sensor or a white light interferometer can be used to measure the surface height of the MicroLED to compensate for substrate warping or assembly tilt.

[0010] Preferably, the 3) performs sub-pixel interpolation processing on the collected array image, such as bicubic interpolation, to improve the positioning accuracy to 0.1 pixel level.

[0011] Preferably, the above 4) can also introduce optical image data and other data. In the electrical detection data, the locations of electrical performance anomalies such as open circuits and short circuits can be determined through electrical detection, and these electrical anomaly locations can be compared and fused for analysis with the defect locations identified in the optical image.

[0012] Preferably, in 5), the laser device and the coordinate system need to be calibrated, and the mechanical calibration of the laser device includes: S1: Use laser interferometer or grating ruler to verify the accuracy of the X, Y, and Z axes of the equipment's motion platform to ensure that the step error is less than ±1μm; S2: Correcting the optical path deviation of the device, including by aligning the laser focus with the center of the field of view of the vision system; Multiple coordinate systems include: S1: Equipment coordinate system, with the origin of the laser galvanometer or motion platform as the reference; S2: visual coordinate system, the mapping relationship between the camera imaging plane and pixel coordinates; S3: Workpiece coordinate system, the actual physical coordinates of the MicroLED array, and the multi-coordinate system is realized through coordinate transformation matrices such as affine transformation or perspective transformation.

[0013] Compared with the prior art, the beneficial effects achieved by the present invention are: First, by precisely adjusting the reference coordinate system, the present invention can make the positioning system more closely match the actual physical position of the Micro LED array, thereby reducing the positioning error caused by the inaccurate coordinate system. Multiple positioning of the defective area can compare and correct the results of each positioning, effectively reducing the error accumulation that may be caused by a single positioning. Especially when dealing with complex Micro LED arrays, multiple positioning can continuously optimize the positioning results, making the final defect position more accurate. Multimodal data fusion positioning combines data obtained by different types of sensors or detection methods, such as optical image data, electrical detection data, laser scanning data, etc. Each type of data contains different aspects of information about the Micro LED array. Fusion of these data can accurately determine the defect position from multiple dimensions, making up for the shortcomings of a single data source in positioning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0016] See also Figure 1 ,A positioning method for laser rapid repair of MicroLED arrays,1) Construct a coordinate reference system within the imaging field of view of the device, and use a fixed angle or boundary of the array as the reference origin. The reference origin is preferably selected at a position with high mechanical stability (such as the edge of the substrate or a fixed pad) to avoid reference offset due to thermal expansion or vibration. The coordinate axes are set in the horizontal and vertical directions, just like determining the origin and direction on a map, to provide a basic reference for subsequent positioning. For MicroLED arrays of different sizes and specifications, adjust the unit length and coverage of the coordinate system to ensure that the entire array area is covered. For example, a small-sized array may use a unit length of microns, while a large-sized array may use a unit length of millimeters; 2) Use high-resolution optical imaging equipment, including high-precision imaging equipment such as high-resolution optical microscopes and CCD cameras, in combination with microscopic optical systems (such as long working distance objectives) to ensure that the microscopic details of the Micro LED array can be captured (the pixel resolution must reach the sub-micron level), and perform comprehensive scanning and imaging of the Micro LED array. The system identifies potential defect areas with dark pixels, abnormal brightness, color deviation and other problems based on the preset image analysis algorithm, and performs preliminary defect identification and marking. Once the location where the defect may exist is found, the system will automatically make preliminary marks on the image and record the approximate location information of these areas in the image for more accurate positioning analysis later. For example, the suspected defective pixels or areas are marked with frames or dots of specific colors on the image, and the defect contrast is enhanced by specific wavelength illumination (such as blue light or ultraviolet light). For example, the dark pixel (Dead Pixel) is dark when powered on, while the bright pixel (Bright Pixel) continues to emit light. The short-circuit area may generate infrared signals due to heating caused by leakage current; 3) For the initially marked defective areas, image preprocessing can be performed first, such as noise reduction (such as Gaussian filtering), contrast enhancement, and background homogenization. A single Micro LED unit can be located through edge detection (such as the Canny algorithm) or threshold segmentation (Otsu algorithm). A machine learning model (such as a convolutional neural network CNN) is used to distinguish defect types (dark spots, bright spots, color deviation, etc.), mark the coordinates, and then output the results to generate a list of defect coordinates. A sub-pixel level positioning algorithm is used for precise positioning. It can be a sub-pixel positioning algorithm based on edge detection. It uses the grayscale variation characteristics of the defect edge in the image and interpolates the edge pixels to improve the positioning accuracy to the sub-pixel level. Or a sub-pixel positioning method based on template matching, first create a template image of a standard Micro LED pixel, and then match it in the image containing the defect. Based on the matching similarity and position deviation, the exact position of the defect is calculated. These algorithms can improve the positioning accuracy from the pixel level to the sub-pixel level, greatly improving the accuracy of positioning, so that repair work can be carried out more accurately at the defect location; 4) Multimodal data fusion positioning: introduce electrical detection data, use machine learning algorithms to process multimodal data, and more accurately determine the true location of defects. Electrical detection can determine the locations of electrical performance anomalies such as open circuits and short circuits. These electrical anomaly locations are compared and fused with the defect locations identified in the optical image. Use machine learning algorithms to process multimodal data, combine the advantages of different data, and more accurately determine the true location of defects, effectively reducing positioning errors caused by the limitations of a single detection method. 5) Perform coordinate conversion and calibration operations. According to the geometric relationship between the imaging device and the laser processing equipment, establish a conversion model between the coordinate systems of the two. Convert the image coordinate system of the imaging device to the motion coordinate system of the laser processing equipment to ensure that the laser beam accurately irradiates the defect position. You can use a standard calibration plate with feature points of known coordinates engraved on it. Use the imaging device and the laser processing equipment to measure the calibration plate and obtain the coordinate data of the two in their respective coordinate systems, so as to accurately calculate the coordinate conversion parameters and ensure the accuracy of the coordinate conversion. Provide a reliable position basis for subsequent laser repair. Perform dynamic positioning adjustments during the conversion and establish a real-time feedback mechanism.

[0017] In this embodiment, the coordinate system can also be verified and corrected before converting the coordinates and laser equipment, including selecting multiple test points in the array (such as normally operating Micro LED units), verifying the coordinate accuracy through laser marking or electrical testing, and recalibrating or enabling the compensation algorithm if the deviation exceeds a threshold (such as ±2μm).

[0018] In this embodiment, the optimization in the positioning method also includes environmental control and software collaboration, such as operating in a constant temperature (±0.1°C) and shock-proof (optical vibration isolation platform) environment, reducing external interference, and realizing an automated calibration process through host computer software (such as LabVIEW or a customized Python tool chain).

[0019] In this embodiment, the precise reference coordinate system and multiple positioning mechanism help the system to lock the defect area more quickly. The system can use the previous positioning information and adjustment experience to find the target more quickly in the subsequent positioning, reduce the time cost of searching and positioning, and improve the overall repair efficiency. Multimodal data fusion provides more comprehensive array information, which can not only accurately find the defect location, but also understand the environment around the defect and other related information, which helps to plan a more reasonable laser repair path, avoid unnecessary movement and operation, and further save repair time. Due to more accurate positioning, the defect can be repaired accurately at one time, reducing repeated repairs caused by inaccurate positioning. Repeated repairs not only waste time, but may also cause additional damage to the Micro LED array. Therefore, reducing repeated repairs can significantly improve repair efficiency.

[0020] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the principles and spirit of the present application. The scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A positioning method for rapid laser repair of MicroLED arrays, characterized by: include: 1) Construct a coordinate reference system within the imaging field of view of the device, using a fixed angle or boundary of the array as the reference origin, and set the coordinate axes in the horizontal and vertical directions. For Micro LED arrays of different sizes and specifications, adjust the unit length and coverage of the coordinate system to ensure that the entire array area is covered; 2) Use high-resolution optical imaging equipment to perform comprehensive scanning and imaging of the MicroLED array. Based on the preset image analysis algorithm, the system identifies potential defect areas with dark pixels, abnormal brightness, color deviation and other problems, and performs preliminary defect identification and marking; 3) For the initially marked defective areas, a sub-pixel positioning algorithm is used for accurate positioning; 4) Multimodal data fusion positioning: introduce electrical detection data, use machine learning algorithms to process multimodal data, and more accurately determine the true location of defects; 5) Perform coordinate conversion and calibration operations. According to the geometric relationship between the imaging device and the laser processing equipment, establish a conversion model between the coordinate systems of the two. Convert the image coordinate system of the imaging device to the motion coordinate system of the laser processing equipment to ensure that the laser beam accurately irradiates the defect position.

2. A positioning method for rapid laser repair of a MicroLED array according to claim 1, characterized in that: The reference origin in 1) is selected from easily identifiable physical marks in the Micro LED array, including cross marks preset in the process, specific electrode structures, package boundary corners or others. The optical feature extraction includes: acquiring array images through a high-resolution industrial camera and automatically identifying the coordinates of the reference points using an image processing algorithm.

3. The positioning method for rapid laser repair of a MicroLED array according to claim 1, characterized in that: Laser ranging can be used to assist positioning between 2) and 3), and a confocal laser sensor and a white light interferometer can be used to measure the surface height of the MicroLED to compensate for substrate warping or assembly tilt.

4. The positioning method for rapid laser repair of a MicroLED array according to claim 1, characterized in that: The 3) sub-pixel interpolation processing is performed on the acquired array image, such as bicubic interpolation, to improve the positioning accuracy to 0.1 pixel level.

5. The positioning method for rapid laser repair of a MicroLED array according to claim 1, characterized in that: The above 4) can also introduce optical image data and other data. In the electrical detection data, the locations of electrical performance anomalies such as open circuits and short circuits can be determined through electrical detection, and these electrical anomaly locations can be compared and fused for analysis with the defect locations identified in the optical image.

6. The positioning method for rapid laser repair of a MicroLED array according to claim 1, characterized in that: In 5), the laser equipment and coordinate system need to be calibrated. The mechanical calibration of the laser equipment includes: S1: Use laser interferometer or grating ruler to verify the accuracy of the X, Y, and Z axes of the equipment's motion platform to ensure that the step error is less than ±1μm; S2: Correcting the optical path deviation of the device, including by aligning the laser focus with the center of the field of view of the vision system; Multiple coordinate systems include: S1: Equipment coordinate system, with the origin of the laser galvanometer or motion platform as the reference; S2: visual coordinate system, the mapping relationship between the camera imaging plane and pixel coordinates; S3: Workpiece coordinate system, the actual physical coordinates of the MicroLED array, and the multi-coordinate system is realized through coordinate transformation matrices such as affine transformation or perspective transformation.

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