A position deviation correction device for LED chip mounter

Abstract

The application relates to the surface mounting technology field and relates to a position deviation correction device for an LED chip mounter, which comprises: an LED chip mounter, a high-definition camera set is arranged in the detection area to form a four-square focusing camera array, wherein the high-definition camera set comprises four high-definition cameras, a correction mounter is determined based on the four-square focusing camera array and the LED chip mounter, an element image sequence set of a preparation mounter is obtained based on a preset shooting interval, environment weight analysis is performed on the optimized image sequence set, left and right light flash weights and upper and lower light flash weights are obtained, binocular vision analysis is performed on the optimized image sequence set based on a camera calibration parameter group set, the left and right light flash weights and the upper and lower light flash weights, deviation correction is performed on the preparation mounter based on a chip center coordinate and a chip diagonal angle, a target mounter is obtained, and deviation correction of the LED chip mounter is completed. The application can improve the accuracy and automation degree of deviation correction and improve the component mounting quality.

Description

Technical Field

[0001] This invention relates to the field of surface mount technology, and more particularly to a position deviation correction device for an LED chip mounter. Background Technology

[0002] In modern electronics manufacturing, LED pick-and-place machines are one of the core pieces of equipment, undertaking the crucial task of accurately mounting tiny LED components onto PCB circuit boards. To ensure mounting accuracy, the coordinates and angles of the components must be made to perfectly match the preset values ​​during the placement process. Therefore, accurately obtaining the position information of the components before placement and correcting for deviations is a key technical challenge for improving the yield and efficiency of pick-and-place.

[0003] Currently, the correction of component position deviation in the existing LED chip mounting process mainly involves detecting the adsorbed component using a single camera or simple image processing, and then performing angle and center correction based on the identified center position and diagonal angle.

[0004] While existing methods and devices can correct positional deviations of LED components, their single-camera structure cannot acquire complete three-dimensional positional information, making it difficult to identify and eliminate image errors caused by abnormal vibrations during the placement process. Furthermore, single-camera systems have limited viewing angles and are easily affected by factors such as lighting changes and reflections, leading to unstable recognition. Therefore, there is an urgent need for a deviation correction device that combines multi-angle and binocular vision to improve the accuracy and automation of deviation correction and enhance component placement quality. Summary of the Invention

[0005] This invention provides a position deviation correction device and a computer-readable storage medium for LED chip mounters. Its main purpose is to improve the accuracy and automation of deviation correction and improve the component mounting quality.

[0006] To achieve the above objectives, the present invention provides a position deviation correction device for an LED chip mounter, comprising:

[0007] The LED chip mounting mechanism has been identified. This mechanism includes a feeding area, a testing area, a mounting area, a motion guide rail, and a mounting device. The motion guide rail comprises a feeding section, a testing section, and a mounting section, all located directly above the feeding area, testing area, and mounting area, respectively. The mounting device is mounted on the motion guide rail. The feeding area includes multiple chip elements. The testing area includes a testing platform. The mounting device includes a nozzle and a rotary motor, with the rotary motor connected to the nozzle.

[0008] A high-definition camera set is acquired, and a four-way focusing camera array is constructed in the detection area using the high-definition camera set. The high-definition camera set includes four high-definition cameras. A correction patch mechanism is identified based on the four-way focusing camera array and the LED patch mechanism.

[0009] The camera calibration of the four-way focusing camera array is performed using a pre-built calibration board to obtain a set of camera calibration parameters;

[0010] When a pre-built placement instruction is received, the placement device in the placement mechanism is prepared for calibration, thus obtaining the placement mechanism preparation.

[0011] The component image sequence set of the preparation patching mechanism is obtained based on a preset shooting interval. The component image sequence set includes: left image sequence, right image sequence, upper image sequence and lower image sequence.

[0012] Image optimization is performed on the component image sequence set based on the camera calibration parameter set to obtain an optimized image sequence set;

[0013] Environmental weight analysis is performed on the optimized image sequence set to obtain the left and right flash weights and the up and down flash weights. Based on the camera calibration parameter set, the left and right flash weights and the up and down flash weights, binocular vision analysis is performed on the optimized image sequence set to obtain the component coordinate sequence and the component angle sequence.

[0014] Vibration characteristic analysis was performed on the component coordinate sequence and component angle sequence to obtain the patch center coordinates and patch diagonal angles;

[0015] Based on the center coordinates and diagonal angles of the LED chip mounter, the deviation of the prepared mounting mechanism is corrected to obtain the target mounting mechanism, thus completing the deviation correction of the LED chip mounter.

[0016] Optionally, the construction of a four-way focusing camera array in the detection area using a high-definition camera set includes:

[0017] Confirm the target stopping point and sliding direction in the detection section of the motion guide rail;

[0018] Confirm the detection plane of the detection platform, and determine the detection center point on the detection plane of the detection area based on the target stopping point;

[0019] Obtain a transmissive backlight source, wherein the transmissive backlight source includes: a light-emitting surface;

[0020] Based on the detection center point and the target dwell point, the transmission backlight is installed on the detection plane of the detection platform to obtain the installed backlight. The emitting surface of the installed backlight is parallel to the detection plane, and the point corresponding to the geometric center of the emitting surface, the detection center point, and the target dwell point are all located on the same straight line.

[0021] A calibration three-dimensional coordinate system is constructed using the detection center point and the sliding direction. The detection center point is used as the origin of the calibration three-dimensional coordinate system, the sliding direction is used as the positive x-axis of the calibration three-dimensional coordinate system, and the direction from the detection center point to the target stopping point is used as the positive z-axis.

[0022] The left, right, top, and bottom coordinates are determined based on the preset interval distance;

[0023] The left, right, top, and bottom installation points are identified on the detection plane based on the left, right, top, and bottom coordinates, respectively.

[0024] Extract high-definition cameras from the high-definition camera set, and perform the following operations on the extracted high-definition cameras:

[0025] Based on the left mounting point, the high-definition camera is mounted on the detection plane of the detection platform to obtain the left-side camera, wherein the line connecting the left mounting point and the optical center of the left-side camera is perpendicular to the detection plane.

[0026] The right-side camera was identified based on the right mounting point and the high-definition camera set; the upper-side camera was identified based on the upper mounting point and the high-definition camera set; and the lower-side camera was identified based on the lower mounting point and the high-definition camera set.

[0027] A four-way focusing camera array was identified based on the installation of a backlight, a top camera, a bottom camera, a left camera, and a right camera.

[0028] Optionally, the step of using a pre-built calibration board to calibrate the four-way focusing camera array to obtain a set of camera calibration parameters includes:

[0029] The calibration position set is identified on the detection section of the motion guide rail, wherein the calibration position set includes: multiple calibration positions;

[0030] For each calibration location in the calibration location set, perform the following operation:

[0031] The calibration board is placed at the calibration position to obtain the target calibration board. The left-side camera in the four-way focusing camera array is used to take a picture of the target calibration board to obtain a left-side image.

[0032] A pre-built corner detector is used to identify multiple left corner points and multiple left two-dimensional coordinates in a left-side image, wherein each left corner point corresponds one-to-one with its left two-dimensional coordinate.

[0033] Multiple left-position three-dimensional coordinates were identified in the calibrated three-dimensional coordinate system based on multiple left-position corner points, where each left-position corner point corresponds one-to-one with a left-position three-dimensional coordinate.

[0034] By pairing and combining multiple left-position two-dimensional coordinates and multiple left-position three-dimensional coordinates, a set of left-position calibration coordinates is obtained.

[0035] The left calibration coordinate set is summarized to obtain multiple left calibration coordinate sets. The multiple left calibration coordinate sets are analyzed using a pre-built camera calibrator to obtain the left calibration parameter set. The left calibration parameter set includes: left intrinsic parameter matrix and left distortion parameter. The left intrinsic parameter matrix includes: horizontal focal length, vertical focal length, x-coordinate of principal point and y-coordinate of principal point.

[0036] The right-side calibration parameter set is determined based on the corner point identifier, camera calibrator, calibration position set, calibration board, and the right-side camera in the four-way focusing camera array. The upper-side calibration parameter set is determined based on the corner point identifier, camera calibrator, calibration position set, calibration board, and the upper-side camera in the four-way focusing camera array. The lower-side calibration parameter set is determined based on the corner point identifier, camera calibrator, calibration position set, calibration board, and the lower-side camera in the four-way focusing camera array.

[0037] The camera calibration parameter set is obtained by summarizing the left-side calibration parameter set, the right-side calibration parameter set, the upper-side calibration parameter set, and the lower-side calibration parameter set.

[0038] Optionally, the calibration preparation of the patch assembly in the calibration patch assembly mechanism to obtain a prepared patch assembly mechanism includes:

[0039] Move the placement device in the calibration placement mechanism to the feeding section of the motion guide rail to obtain the waiting placement device;

[0040] The pick-and-place device uses a nozzle in the waiting pick-and-place device to pick up and place components in the feed area of ​​the calibration pick-and-place mechanism, thereby obtaining a pick-and-place device, wherein the pick-and-place device includes: a pick-and-place element;

[0041] The adsorption patch device is moved to the target stopping point of the detection section in the motion guide rail to obtain the stopping patch device;

[0042] The preparation mechanism for patch placement is determined based on the dwell patch placement device and the calibration patch placement mechanism.

[0043] Optionally, the step of optimizing the image sequence set of components based on the camera calibration parameter set to obtain an optimized image sequence set includes:

[0044] The distortion of multiple left-position element images in the left-position image sequence of the element image sequence set is corrected using the left-position distortion parameters and the left-position intrinsic parameter matrix in the left-position calibration parameter set of the camera calibration parameter set, resulting in multiple corrected left-position images.

[0045] For each of the multiple corrected left-side images, perform the following operation:

[0046] Perform a grayscale conversion operation on the corrected left-side image to obtain a grayscale left-side image, wherein the grayscale left-side image includes: multiple grayscale pixels;

[0047] By summarizing the grayscale left-side images, multiple grayscale left-side images are obtained. Based on the left-side image sequence and the multiple grayscale left-side images, the left-side grayscale image sequence is determined.

[0048] A right-level grayscale image sequence is obtained from the right-level image sequence of the right-level calibration parameter set and the component image sequence set of the camera calibration parameter set; an upper-level grayscale image sequence is obtained from the upper-level image sequence of the upper-level calibration parameter set and the component image sequence set of the camera calibration parameter set; and a lower-level grayscale image sequence is obtained from the lower-level image sequence of the lower-level calibration parameter set and the component image sequence set of the camera calibration parameter set.

[0049] By summing the left-side grayscale image sequence, right-side grayscale image sequence, upper-side grayscale image sequence, and lower-side grayscale image sequence, an optimized image sequence set is obtained.

[0050] Optionally, the step of performing environmental weight analysis on the optimized image sequence set to obtain left-right flare weights and up-down flare weights includes:

[0051] For each left-hand grayscale image in the optimized image sequence set, perform the following operation:

[0052] Calculate the mean gray level based on multiple gray level pixels in the grayscale left-side image;

[0053] Summarize the grayscale averages to obtain multiple grayscale averages;

[0054] The standard deviation of the left-side brightness is calculated based on multiple gray-level means, where the variance of the left-side brightness is the standard deviation of multiple gray-level means.

[0055] The standard deviation of right-side brightness is obtained from the right-side grayscale image sequence of the optimized image sequence set; the standard deviation of upper-side brightness is obtained from the upper-side grayscale image sequence of the optimized image sequence set; and the standard deviation of lower-side brightness is obtained from the lower-side grayscale image sequence of the optimized image sequence set.

[0056] The sum standard deviation is calculated based on the standard deviations of the left, right, upper, and lower luminance, where the sum standard deviation is the sum of the standard deviations of the left, right, upper, and lower luminance.

[0057] The left and right flicker weights are calculated based on the standard deviations of the left, right, and total brightness, as shown in the following formula:

[0058]

[0059] Where, μ12 The left and right flicker weights are σ1 and σ2, respectively, representing the standard deviations of the left and right brightness levels. x The sum of standard deviations;

[0060] The upper and lower flicker weights are calculated based on the upper luminance standard deviation, the lower luminance standard deviation, and the sum standard deviation.

[0061] Optionally, the step of performing binocular visual analysis on the optimized image sequence set based on the camera calibration parameter set, left and right flash weights, and up and down flash weights to obtain the component coordinate sequence and component angle sequence includes:

[0062] Extract the j-th gray-level left image, j-th gray-level right image, j-th gray-level upper image, and j-th gray-level lower image from the left gray-level image sequence, right gray-level image sequence, upper gray-level image sequence, and lower gray-level image sequence of the optimized image sequence set, respectively, where the initial value of j is 1;

[0063] The edge recognition algorithm is used to perform edge recognition on the j-th grayscale left-side image to obtain the edge pixel set;

[0064] Perform the following operation on each edge pixel in the edge pixel set:

[0065] Based on the edge pixels, multiple neighboring pixels were identified in the j-th grayscale left-side image;

[0066] For each of a plurality of neighboring pixels, perform the following operation:

[0067] Determine whether a neighboring pixel is an edge pixel in the edge pixel set;

[0068] If a neighboring pixel is an edge pixel in the edge pixel set, then the neighboring pixel is recorded as a marked pixel.

[0069] The marked pixels are summarized to obtain multiple marked pixels. The number of marks is determined based on the multiple marked pixels. The number of marks is the number of marked pixels among the multiple marked pixels. The number of neighbors is determined based on multiple neighboring pixels.

[0070] Calculate the marking ratio based on the number of markings and the number of adjacent markings;

[0071] Compare the marking ratio with a preset ratio threshold. If the marking ratio is greater than or equal to the ratio threshold, then the edge pixel corresponding to the marking ratio is taken as the target pixel.

[0072] Summarize the target pixels to obtain multiple target pixels;

[0073] Identify the center pixel in the j-th grayscale left-side image, where the center pixel is the grayscale pixel located at the geometric center of the j-th grayscale left-side image;

[0074] A first planar coordinate system is constructed in the j-th grayscale left-side image with the center pixel as the origin. The direction from the first grayscale pixel at the top left corner of the j-th grayscale left-side image to the first grayscale pixel at the top right corner of the j-th grayscale left-side image is taken as the positive direction of the horizontal axis of the first planar coordinate system. The direction from the first grayscale pixel at the top left corner of the j-th grayscale left-side image to the first grayscale pixel at the bottom left corner of the j-th grayscale left-side image is taken as the positive direction of the vertical axis of the first planar coordinate system. The length of the grayscale pixel is taken as the unit length of the first planar coordinate system.

[0075] Based on the first plane coordinate system, multiple target pixels are screened by quadrant to obtain multiple first pixels and multiple third pixels. The first pixels are target pixels located in the first quadrant of the first plane coordinate system, and the third pixels are target pixels located in the third quadrant of the first plane coordinate system.

[0076] For each of the multiple first pixels, perform the following operation:

[0077] Confirm the first pixel coordinates of the first pixel point in the first plane coordinate system, and calculate the edge distance based on the first pixel coordinates;

[0078] Sum the edge distances to obtain multiple edge distances, and mark the first pixel coordinate corresponding to the largest edge distance among the multiple edge distances as the j-th left-side top coordinate;

[0079] The j-th left-side coordinate is obtained based on multiple third-pixel points and the first planar coordinate system.

[0080] Based on the j-th grayscale right-side image, obtain the j-th right-side top coordinate and the j-th right-side bottom coordinate; based on the j-th grayscale upper image, obtain the j-th upper-side coordinate and the j-th upper-side bottom coordinate; based on the j-th grayscale lower image, obtain the j-th lower-side top coordinate and the j-th lower-side bottom coordinate.

[0081] The j-th upper depth distance is calculated based on the interval distance, camera calibration parameter set, left and right flash weights, up and down flash weights, j-th left upper coordinate, j-th right upper coordinate, j-th upper upper coordinate, and j-th lower upper coordinate.

[0082] Calculate the j-th upper horizontal distance based on the j-th left upper coordinate, the j-th upper depth distance, and the left upper calibration parameter set in the camera calibration parameter set set;

[0083] Calculate the j-th upper vertical distance based on the j-th left upper coordinate, the j-th upper depth distance, and the left upper calibration parameter set in the camera calibration parameter set set;

[0084] The three-dimensional coordinates of the j-th upper corner are constructed based on the j-th upper depth distance, the j-th upper horizontal distance, and the j-th upper vertical distance;

[0085] The j-th lower corner 3D coordinates are obtained based on the interval distance, camera calibration parameter set, left and right flash weights, up and down flash weights, j-th left lower coordinate, j-th right lower coordinate, j-th upper lower coordinate, and j-th lower lower coordinate.

[0086] Calculate the center's three-dimensional coordinates based on the three-dimensional coordinates of the j-th upper corner and the j-th lower corner;

[0087] Calculate the diagonal vector of the element based on the three-dimensional coordinates of the j-th upper corner and the j-th lower corner;

[0088] Calculate the diagonal angle of the component based on the component's diagonal vector and the preset horizontal axis unit vector;

[0089] Let J = j + 1, take J as j, and return to the steps of extracting the j-th gray-level left image, the j-th gray-level right image, the h-th gray-level upper image and the j-th gray-level lower image from the left gray-level image sequence, the right gray-level image sequence, the upper gray-level image sequence and the lower gray-level image sequence of the optimized image sequence set respectively, until J = M, where M is the number of left gray-level images in the left gray-level image sequence;

[0090] By summarizing the three-dimensional coordinates of the center, multiple three-dimensional coordinates of the center are obtained. By summarizing the diagonal angles of the elements, multiple diagonal angles of the elements are obtained. The element coordinate sequence is determined based on the left grayscale image sequence and multiple three-dimensional coordinates of the center. The element angle sequence is determined based on the left grayscale image sequence and multiple diagonal angles of the elements.

[0091] Optionally, the formula for calculating the j-th upper depth distance is as follows:

[0092]

[0093] in, For the j-th depth distance, μ 34 For the upper and lower light flicker weights, f x1 f x2 f y3 and f y4 These are the horizontal focal lengths of the left and right calibration parameter groups, the vertical focal lengths of the upper and lower calibration parameter groups, respectively, within the camera calibration parameter set. Let x be the x-coordinate of the j-th left-hand coordinate. Let x be the x-coordinate of the j-th right-hand coordinate. Let be the ordinate of the j-th upper coordinate. d0 is the ordinate of the j-th lower coordinate, d0 is the interval distance, and || indicates taking the absolute value.

[0094] Optionally, the vibration characteristic analysis of the component coordinate sequence and component angle sequence to obtain the patch center coordinates and patch diagonal angle includes:

[0095] Extract the k-th center 3D coordinate from the component coordinate sequence, where the initial value of k is 2;

[0096] Based on the k-th center three-dimensional coordinates, the k-1-th center three-dimensional coordinates are determined in the component coordinate sequence. The k-th center three-dimensional coordinates are adjacent to and lag behind the k-1-th center three-dimensional coordinates in the component coordinate sequence.

[0097] The vibration distance is calculated based on the three-dimensional coordinates of the k-th center and the (k-1)-th center.

[0098] Let K = k + 1, take K as k, and return to the step of extracting the kth center three-dimensional coordinate from the component coordinate sequence until K = M;

[0099] Summarize the vibration distances to obtain multiple vibration distances, and take the k-th center three-dimensional coordinates corresponding to the smallest vibration distance among the multiple vibration distances as the patch center coordinates;

[0100] Confirm the position of the chip center coordinates in the component coordinate sequence, and extract the chip diagonal angle from the chip diagonal angle based on the position.

[0101] To achieve the above objectives, the present invention also provides a position deviation correction system for an LED chip mounter, comprising:

[0102] The LED placement mechanism confirmation module confirms the LED placement mechanism, which includes: a feeding area, a detection area, a placement area, a motion guide rail, and a placement device. The motion guide rail includes: a feeding section, a detection section, and a placement section, which are located directly above the feeding area, detection area, and placement area, respectively. The placement device is mounted on the motion guide rail. The feeding area includes: multiple placement elements. The detection area includes: a detection platform. The placement device includes: a nozzle and a rotary motor, wherein the rotary motor is connected to the nozzle.

[0103] A camera array construction module is used to acquire a high-definition camera set and construct a four-way focusing camera array in the detection area using the high-definition camera set. The high-definition camera set includes four high-definition cameras. A calibration patch mechanism is identified based on the four-way focusing camera array and the LED patch mechanism. The four-way focusing camera array is calibrated using a pre-constructed calibration board to obtain a set of camera calibration parameters.

[0104] The component image acquisition module is used to prepare the patching device in the patching mechanism for calibration when a pre-constructed patching instruction is received, thereby obtaining a prepared patching mechanism. Based on a preset shooting interval, it acquires a set of component image sequences of the prepared patching mechanism. The set of component image sequences includes: left image sequence, right image sequence, upper image sequence and lower image sequence. Based on a set of camera calibration parameters, it optimizes the component image sequence set to obtain an optimized image sequence set.

[0105] The chip image correction module is used to perform environmental weight analysis on the optimized image sequence set to obtain the left and right flash weights and the up and down flash weights. Based on the camera calibration parameter set, the left and right flash weights, and the up and down flash weights, the optimized image sequence set is subjected to binocular visual analysis to obtain the component coordinate sequence and the component angle sequence. Vibration feature analysis is performed on the component coordinate sequence and the component angle sequence to obtain the chip center coordinates and the chip diagonal angle. Based on the chip center coordinates and the chip diagonal angle, the deviation correction is performed on the prepared chip placement mechanism to obtain the target chip placement mechanism, thus completing the deviation correction of the LED chip placement machine.

[0106] To address the above problems, the present invention also provides an electronic device, the electronic device comprising:

[0107] Memory, storing at least one instruction;

[0108] The processor executes the instructions stored in the memory to implement the position deviation correction system for LED chip mounters described above.

[0109] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the aforementioned position deviation correction system for an LED chip mounter.

[0110] To address the problems described in the background art, this invention provides an LED chip mounting mechanism. This mechanism includes a feeding area, a detection area, a mounting area, a motion guide rail, and a mounting device. The motion guide rail comprises a feeding section, a detection section, and a mounting section, each located directly above the feeding area, detection area, and mounting area, respectively. The mounting device is mounted on the motion guide rail. The feeding area includes multiple chip components, the detection area includes a detection platform, and the mounting device includes a nozzle and a rotary motor, with the rotary motor connected to the nozzle. This invention, by pre-defining a complete LED chip mounting mechanism, provides a systematic working environment for subsequent component mounting, improving the automation level of component mounting. A high-definition camera set is acquired, and a four-way focusing camera array is constructed in the detection area using the high-definition camera set. The high-definition camera set includes four high-definition cameras. A calibration patch mechanism is identified based on the four-way focusing camera array and the LED patch mechanism. This embodiment of the invention improves the detection area of ​​the LED patch mechanism by constructing a four-way focusing camera array within the detection area of ​​the LED patch mechanism using the high-definition camera set, replacing a single camera with a multi-camera array to optimize the accuracy of position deviation detection and improve the deviation correction effect. The four-way focusing camera array is calibrated using a pre-constructed calibration board to obtain a set of camera calibration parameters. This embodiment of the invention obtains necessary intrinsic parameters by calibrating the four-way focusing camera array before formal calibration. The matrix and distortion coefficients facilitate subsequent image optimization based on the distortion coefficients, and the two-dimensional position information in the image is converted into the three-dimensional position information of the components based on the intrinsic parameter matrix, improving the accuracy of deviation correction. When a pre-constructed placement instruction is received, the placement device in the correction placement mechanism is prepared for correction, resulting in a prepared placement mechanism. Based on a preset shooting interval, a set of component image sequences for the prepared placement mechanism is acquired. The component image sequence set includes: left-side image sequence, right-side image sequence, upper-side image sequence, and lower-side image sequence. The component image sequence set is optimized based on the camera calibration parameter set to obtain an optimized image sequence set. It can be seen that the embodiments of the present invention automatically perform the placement process and acquire the placement mechanism by receiving the placement instruction. The component image sequence set improves the automation level of deviation correction, and image optimization based on the camera calibration parameter set improves the accuracy of deviation correction. Environmental weight analysis is performed on the optimized image sequence set to obtain left-right and up-down flash weights. Based on the camera calibration parameter set, left-right and up-down flash weights, binocular vision analysis is performed on the optimized image sequence set to obtain the component coordinate sequence and component angle sequence. It can be seen that the embodiments of the present invention, by performing environmental weight analysis and binocular vision analysis, effectively improve the accuracy of deviation correction by acquiring the three-dimensional coordinates and angle information of components through binocular vision while considering environmental influences. Vibration characteristic analysis is then performed on the component coordinate sequence and component angle sequence.By obtaining the center coordinates and diagonal angles of the LED chip mount, this embodiment of the invention analyzes the vibration of the component by tracking the temporal changes of the three-dimensional coordinates in the component coordinate sequence. This effectively filters out coordinates and angles with smaller vibration amplitudes, eliminating errors caused by dynamic factors such as vibration. This results in more stable and reliable center coordinates and diagonal angles, improving the accuracy of deviation correction. Based on the center coordinates and diagonal angles, deviation correction is performed on the preparation mounting mechanism to obtain the target mounting mechanism, completing the deviation correction of the LED chip mounter. Therefore, this embodiment of the invention automatically corrects the deviation of the adsorbed components in the preparation mounting mechanism using the center coordinates and diagonal angles, improving the automation level of deviation correction and ultimately improving the component mounting quality. Thus, this invention can improve the accuracy and automation of deviation correction, thereby improving the component mounting quality. Attached Figure Description

[0111] Figure 1 This is a schematic flowchart of a position deviation correction device for an LED chip mounter provided in an embodiment of the present invention;

[0112] Figure 2 This is a functional block diagram of a position deviation correction device for an LED chip mounter provided in an embodiment of the present invention;

[0113] Figure 3 This is a schematic diagram of the structure of an electronic device for implementing the position deviation correction system for an LED chip mounter, according to an embodiment of the present invention.

[0114] Explanation of reference numerals in the attached figures:

[0115] 10. Electronic device; 11. Processor; 12. Memory; 13. Bus.

[0116] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0117] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0118] This application provides a position deviation correction device for an LED pick-and-place machine. The executing entity of the position deviation correction device for the LED pick-and-place machine includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the position deviation correction device for the LED pick-and-place machine can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0119] Reference Figure 1 The diagram shown is a schematic flow chart of a position deviation correction device for an LED pick-and-place machine according to an embodiment of the present invention. In this embodiment, the position deviation correction device for an LED pick-and-place machine includes:

[0120] S1. Identify the LED chip mounting mechanism, which includes: a feeding area, a detection area, a mounting area, a motion guide rail, and a mounting device. The motion guide rail includes: a feeding section, a detection section, and a mounting section, which are located directly above the feeding area, the detection area, and the mounting area, respectively. The mounting device is installed on the motion guide rail. The feeding area includes: multiple chip elements. The detection area includes: a detection platform. The mounting device includes: a nozzle and a rotary motor, wherein the rotary motor is connected to the nozzle.

[0121] It should be explained that an LED chip mounting mechanism is a type of LED chip mounting machine, and it includes: a feeding area, a testing area, a mounting area, a motion guide, and mounting devices. The feeding area is a hopper within the LED chip mounting mechanism that stores multiple chip components, specifically chip LEDs. The testing area is the region within the LED chip mounting mechanism used to correct the position of the chip components adsorbed on the mounting devices. The testing area includes a testing platform, a mechanical platform located within the testing area, used to subsequently support a quad-focusing camera array, thereby using the quad-focusing camera array to correct the position of the chip components adsorbed on the mounting devices transferred to the testing area. The mounting area is the working area within the LED chip mounting mechanism used to mount the chip components adsorbed on the mounting devices onto the circuit board pads. The motion guide rail is a guide rail that provides a linear path for the movement of the chip mounter. It is mounted upside down on top of the LED chip mounter mechanism, with the side containing the slider facing downwards, directly opposite the feeding area, inspection area, and mounting area. The chip mounter is mounted below the slider, with its nozzle facing downwards, enabling it to mount components from bottom to top and perform mounting operations from top to bottom. The motion guide rail includes a feeding section, an inspection section, and a mounting section. The feeding section is the section of the motion guide rail located directly above the feeding area; the inspection section is the section of the motion guide rail located directly above the inspection area; and the mounting section is the section of the motion guide rail located directly above the mounting area. The chip mounting device is a device used to adsorb chip components in an LED chip mounting mechanism. It includes a suction nozzle and a rotating motor. The suction nozzle adsorbs the chip components by negative pressure adsorption. The rotating motor is connected to the suction nozzle through an internal rotating rod. The rotating motor drives the rotating rod to rotate, thereby causing the chip components on the suction nozzle to rotate synchronously, thereby correcting the device posture and making it conform to a specific mounting orientation.

[0122] S2. Obtain a high-definition camera set and construct a four-way focusing camera array in the detection area using the high-definition camera set. The high-definition camera set includes four high-definition cameras. The correction patch mechanism is identified based on the four-way focusing camera array and the LED patch mechanism.

[0123] It should be explained that the high-definition camera set consists of four high-definition cameras, and the high-definition camera is an industrial camera with a pixel resolution of 5 million or more. Optionally, a Christie 12.3-megapixel color USB 3.0 camera can be used as the high-definition camera.

[0124] Specifically, the method of constructing a four-way focusing camera array in the detection area using a high-definition camera set includes:

[0125] Confirm the target stopping point and sliding direction in the detection section of the motion guide rail;

[0126] Confirm the detection plane of the detection platform, and determine the detection center point on the detection plane of the detection area based on the target stopping point;

[0127] Obtain a transmissive backlight source, wherein the transmissive backlight source includes: a light-emitting surface;

[0128] Based on the detection center point and the target dwell point, the transmission backlight is installed on the detection plane of the detection platform to obtain the installed backlight. The emitting surface of the installed backlight is parallel to the detection plane, and the point corresponding to the geometric center of the emitting surface, the detection center point, and the target dwell point are all located on the same straight line.

[0129] A calibration three-dimensional coordinate system is constructed using the detection center point and the sliding direction. The detection center point is used as the origin of the calibration three-dimensional coordinate system, the sliding direction is used as the positive x-axis of the calibration three-dimensional coordinate system, and the direction from the detection center point to the target stopping point is used as the positive z-axis.

[0130] Based on a preset interval, the left, right, top, and bottom coordinates are determined. The left, right, top, and bottom coordinates are shown below:

[0131] P1=(―d0,0,0),P2=(d0,0,0),P3=(0,―d0,0),P4=(0,d0,0)

[0132] Where P1, P2, P3 and P4 are the left coordinate, right coordinate, top coordinate and bottom coordinate, respectively, and d0 is the interval distance;

[0133] The left, right, top, and bottom installation points are identified on the detection plane based on the left, right, top, and bottom coordinates, respectively.

[0134] Extract high-definition cameras from the high-definition camera set, and perform the following operations on the extracted high-definition cameras:

[0135] Based on the left mounting point, the high-definition camera is mounted on the detection plane of the detection platform to obtain the left-side camera, wherein the line connecting the left mounting point and the optical center of the left-side camera is perpendicular to the detection plane.

[0136] The right-side camera was identified based on the right mounting point and the high-definition camera set; the upper-side camera was identified based on the upper mounting point and the high-definition camera set; and the lower-side camera was identified based on the lower mounting point and the high-definition camera set.

[0137] A four-way focusing camera array was identified based on the installation of a backlight, a top camera, a bottom camera, a left camera, and a right camera.

[0138] It should be understood that the operation process of the LED chip mounting mechanism is as follows: After the mounting device picks up the chip element from the feeding area, it is transported to the detection area via a motion guide rail for positional deviation correction. After correction, it is transported back to the mounting area via the motion guide rail for mounting. Therefore, the target stopping point refers to the position where the mounting device stops on the detection section of the motion guide rail when it is transported to the detection area for positional deviation correction. The specific stopping position is manually set by the staff of the LED chip mounting factory. The sliding direction refers to the direction of the instantaneous speed of the mounting device when it is transported to the target stopping point via the motion guide rail.

[0139] It is understood that the detection plane refers to the upper surface of the detection platform. The determination of the detection center point based on the target dwell point on the detection plane of the detection area means: determining a point on the detection plane that is aligned with the target dwell point in a direction perpendicular to the detection plane, and taking this point as the detection center point. That is, the detection center point is the point corresponding to the projection of the target dwell point on the detection plane, and the line connecting the detection center point and the target dwell point is perpendicular to the detection plane.

[0140] It should be explained that the transmissive backlight is a type of LED backlight, and the shape of the light-emitting surface of the transmissive backlight is square. When the transmissive backlight is installed on the detection plane of the detection platform, the light-emitting surface of the transmissive backlight is parallel to the detection plane and placed with the light-emitting surface facing upwards.

[0141] Understandably, the interval distance is the distance between the position of the subsequent installation of the high-definition camera and the detection center point, which is manually set by the staff of the LED chip assembly factory. Specifically, the following conditions must be met: when the high-definition camera is located at the left, right, upper, or lower coordinates corresponding to the interval distance, the image captured by the high-definition camera must include the image corresponding to the target stopping point, so as to ensure that the high-definition camera can capture the chip assembly device located at the target stopping point when performing deviation correction. In addition, the interval distance must be greater than half of the side length of the light-emitting surface of the transmission backlight, so as to ensure that the installation position of the high-definition camera does not coincide with the transmission backlight.

[0142] It should be understood that the determination of the left installation point, right installation point, upper installation point, and lower installation point on the detection plane based on the left coordinate, right coordinate, upper coordinate, and lower coordinate respectively means that the points corresponding to the left coordinate, right coordinate, upper coordinate, and lower coordinate on the detection plane are respectively used as the left installation point, right installation point, upper installation point, and lower installation point.

[0143] It is understood that the methods for identifying the right-side camera based on the right mounting point and the high-definition camera set, the methods for identifying the upper-side camera based on the upper mounting point and the high-definition camera set, and the methods for identifying the lower-side camera based on the lower mounting point and the high-definition camera set are all the same as the methods for obtaining the left-side camera using the left mounting point and the high-definition camera set, and will not be described again here. It should be noted that when the high-definition camera is mounted on the detection plane of the detection platform, the shooting direction of the high-definition camera is perpendicular to the detection platform and upwards.

[0144] It should be understood that the four-way focusing camera array confirmed by installing a backlight, upper camera, lower camera, left camera and right camera means that when it is confirmed that the backlight, upper camera, lower camera, left camera and right camera are all installed on the detection plane of the detection platform, the backlight, upper camera, lower camera, left camera and right camera together form the four-way focusing camera array.

[0145] It is understood that the determination of the calibration patch mechanism based on the quad-focus camera array and LED patch mechanism means that when it is confirmed that the quad-focus camera array has been constructed in the detection area of ​​the LED patch mechanism, the LED patch mechanism at this time is used as the calibration patch mechanism.

[0146] It should be understood that existing LED chip mounting mechanisms typically use a single camera for position deviation detection. However, the embodiments of the present invention improve the detection area of ​​the LED chip mounting mechanism by constructing a four-way focusing camera array to optimize the accuracy of position deviation detection and improve the effect of deviation correction.

[0147] S3. Use the pre-built calibration board to calibrate the four-way focusing camera array to obtain the camera calibration parameter set.

[0148] In detail, the process of calibrating a quad-focus camera array using a pre-built calibration board to obtain a set of camera calibration parameters includes:

[0149] The calibration position set is identified on the detection section of the motion guide rail, wherein the calibration position set includes: multiple calibration positions;

[0150] For each calibration location in the calibration location set, perform the following operation:

[0151] The calibration board is placed at the calibration position to obtain the target calibration board. The left-side camera in the four-way focusing camera array is used to take a picture of the target calibration board to obtain a left-side image.

[0152] A pre-built corner detector is used to identify multiple left corner points and multiple left two-dimensional coordinates in a left-side image, wherein each left corner point corresponds one-to-one with its left two-dimensional coordinate.

[0153] Multiple left-position three-dimensional coordinates were identified in the calibrated three-dimensional coordinate system based on multiple left-position corner points, where each left-position corner point corresponds one-to-one with a left-position three-dimensional coordinate.

[0154] By pairing and combining multiple left-side two-dimensional coordinates and multiple left-side three-dimensional coordinates, a left-side calibration coordinate set is obtained, as shown below:

[0155]

[0156] in, and These represent the first left-hand two-dimensional coordinate among multiple left-hand two-dimensional coordinates, and the left-hand three-dimensional coordinates corresponding to the first left-hand two-dimensional coordinate among multiple left-hand three-dimensional coordinates. and These represent the second left-hand 2D coordinate among multiple left-hand 2D coordinates, and the corresponding left-hand 3D coordinates of the second left-hand 2D coordinate in multiple left-hand 3D coordinates. and These represent the i-th left-hand two-dimensional coordinate among multiple left-hand two-dimensional coordinates, and the corresponding left-hand three-dimensional coordinates of the i-th left-hand two-dimensional coordinate in multiple left-hand three-dimensional coordinates. and These are the nth left-position two-dimensional coordinates among multiple left-position two-dimensional coordinates and the corresponding left-position three-dimensional coordinates of the nth left-position two-dimensional coordinates in multiple left-position three-dimensional coordinates;

[0157] The left calibration coordinate set is summarized to obtain multiple left calibration coordinate sets. The multiple left calibration coordinate sets are analyzed using a pre-built camera calibrator to obtain the left calibration parameter set. The left calibration parameter set includes: left intrinsic parameter matrix and left distortion parameter. The left intrinsic parameter matrix includes: horizontal focal length, vertical focal length, x-coordinate of principal point and y-coordinate of principal point.

[0158] The right-side calibration parameter set is determined based on the corner point identifier, camera calibrator, calibration position set, calibration board, and the right-side camera in the four-way focusing camera array. The upper-side calibration parameter set is determined based on the corner point identifier, camera calibrator, calibration position set, calibration board, and the upper-side camera in the four-way focusing camera array. The lower-side calibration parameter set is determined based on the corner point identifier, camera calibrator, calibration position set, calibration board, and the lower-side camera in the four-way focusing camera array.

[0159] The camera calibration parameter set is obtained by summarizing the left-side calibration parameter set, the right-side calibration parameter set, the upper-side calibration parameter set, and the lower-side calibration parameter set.

[0160] It should be explained that confirming the calibration position set on the detection section of the motion guide rail means arbitrarily selecting multiple different positions on the detection section of the motion guide rail as multiple calibration positions, and these multiple calibration positions constitute the calibration position set. The left-view image refers to an image obtained by taking a picture of the calibration plate using a left-view camera.

[0161] Understandably, a corner point is the intersection of lines on the chessboard grid of the calibration board, and a left corner point is the point on the left-side image corresponding to a corner point on the calibration board. The left-side two-dimensional coordinates refer to the coordinates of the left-side corner point in the pixel coordinate system of the left-side image. The corner detector is a corner detection function in OpenCV: `cv2.findChessboardCorners`.

[0162] For example, the left-side image is first read using the cv2.imread function in OpenCV and converted into image data. Then, the image data is passed to the corner detection function: cv2.findChessboardCorners. This function will automatically detect multiple corners in the image and output the pixel coordinates corresponding to the multiple corners. The multiple corners are the multiple left-side corners, and the pixel coordinates are the left-side two-dimensional coordinates. The above process is existing technology and will not be described in detail here.

[0163] It should be understood that determining multiple left-side 3D coordinates based on multiple left-side corner points in the calibration 3D coordinate system means: sequentially determining the coordinates of the corresponding point in reality for each of the multiple left-side corner points in the calibration 3D coordinate system, and summing these coordinates to obtain multiple left-side 3D coordinates. Since the calibration position corresponding to the calibration plate is known, and the positions of the corner points on the calibration plate are also fixed, the corresponding point in reality can be found through the left-side corner points, and this point can be mapped to the calibration 3D coordinate system to determine the left-side 3D coordinates.

[0164] Understandably, the camera calibrator is a camera calibration function in OpenCV: cv2.calibrateCamera.

[0165] For example, inputting the left-side calibration coordinate set into the OpenCV camera calibration function will automatically analyze the correspondence between the left-side 2D coordinates and left-side 3D coordinates in the left-side calibration coordinate set, and output the intrinsic parameter matrix and distortion coefficients. This process is existing technology and will not be elaborated further here. The left-side calibration parameter set consists of the left-side intrinsic parameter matrix and the left-side distortion parameters, which refer to the left-side camera's intrinsic parameter matrix and distortion coefficients, respectively. The principal point is the intersection of the optical axis and the image plane in the camera imaging system. The x and y coordinates of the principal point can be obtained through the camera's intrinsic parameter matrix. The left-side intrinsic parameter matrix is: f x That is, the horizontal focal length, f y That is, the vertical focal length, c x That is, the x-coordinate of the principal point, c y That is, the ordinate of the principal point.

[0166] It should be understood that the methods for determining the right calibration parameter set based on the corner identifier, camera calibrator, calibration position set, calibration board, and the right camera in the four-way focusing camera array, the methods for determining the upper calibration parameter set based on the corner identifier, camera calibrator, calibration position set, calibration board, and the upper camera in the four-way focusing camera array, and the methods for determining the lower calibration parameter set based on the corner identifier, camera calibrator, calibration position set, calibration board, and the lower camera in the four-way focusing camera array are all the same as the method for obtaining the left calibration parameter set using the corner identifier, camera calibrator, calibration position set, calibration board, and the left camera in the four-way focusing camera array, and will not be described again here.

[0167] S4. When a pre-built placement instruction is received, the placement device in the placement mechanism is prepared for calibration to obtain the placement mechanism.

[0168] It should be explained that the placement instruction is initiated by the staff of the LED SMD factory. For example, Xiao Zhang is a staff member of the LED SMD factory and now needs to use the calibration placement mechanism to place the SMD components onto the circuit board pads, so he initiates the placement instruction.

[0169] In detail, the calibration preparation of the patch assembly in the calibration patch assembly mechanism to obtain the prepared patch assembly mechanism includes:

[0170] Move the placement device in the calibration placement mechanism to the feeding section of the motion guide rail to obtain the waiting placement device;

[0171] The pick-and-place device uses a nozzle in the waiting pick-and-place device to pick up and place components in the feed area of ​​the calibration pick-and-place mechanism, thereby obtaining a pick-and-place device, wherein the pick-and-place device includes: a pick-and-place element;

[0172] The adsorption patch device is moved to the target stopping point of the detection section in the motion guide rail to obtain the stopping patch device;

[0173] The preparation mechanism for patch placement is determined based on the dwell patch placement device and the calibration patch placement mechanism.

[0174] It should be explained that the adsorption and patching device refers to the device waiting for patching after the nozzle has adsorbed the patch element in the feeding area. The adsorption and patching element is the patch element that has been adsorbed by the nozzle on the adsorption and patching device.

[0175] Understandably, the phrase "using the nozzle in the waiting placement device to pick up surface mount components in the feed area of ​​the calibration placement mechanism" means that the nozzle in the waiting placement device picks up a surface mount component from among multiple surface mount components in the feed area. The phrase "confirming the preparation placement mechanism based on the dwell placement device and the calibration placement mechanism" means that when it is confirmed that the placement device in the calibration placement mechanism has been converted into a dwell placement device, the calibration placement mechanism at this time is the preparation placement mechanism.

[0176] S5. Based on a preset shooting interval, acquire a set of component image sequences for the preparation patching mechanism, wherein the set of component image sequences includes: left image sequence, right image sequence, upper image sequence and lower image sequence.

[0177] Specifically, the acquisition of the component image sequence set for the patching mechanism based on a preset shooting interval includes:

[0178] Based on the shooting interval and the four-way focusing camera array in the preparation and placement mechanism, the adsorption and placement elements on the stationary placement device in the preparation and placement mechanism are photographed to obtain a left image sequence, a right image sequence, an upper image sequence and a lower image sequence. The left image sequence, right image sequence, upper image sequence and lower image sequence correspond to the left camera, right camera, upper camera and lower camera in the four-way focusing camera array, respectively. The left image sequence, right image sequence, upper image sequence and lower image sequence each include: multiple left element images, multiple right element images, multiple upper element images and multiple lower element images.

[0179] By summing the left-side image sequence, right-side image sequence, upper-side image sequence, and lower-side image sequence, a set of component image sequences is obtained.

[0180] For example, if the shooting interval is every 0.05 seconds, the left, right, upper, and lower cameras in the four-way focusing camera array simultaneously capture images of the adsorbed chip element every 0.05 seconds. When the shooting time reaches a preset time threshold, shooting stops, and the images captured by the left, right, upper, and lower cameras are summarized to obtain multiple images of the left, right, upper, and lower components. These images are then sorted in ascending order of shooting time to obtain a sequence of left, right, upper, and lower images. The time threshold and shooting interval are manually set by the LED chip factory staff.

[0181] S6. Based on the camera calibration parameter set, perform image optimization on the component image sequence set to obtain an optimized image sequence set.

[0182] In detail, the step of optimizing the image sequence set of components based on the camera calibration parameter set to obtain an optimized image sequence set includes:

[0183] The distortion of multiple left-position element images in the left-position image sequence of the element image sequence set is corrected using the left-position distortion parameters and the left-position intrinsic parameter matrix in the left-position calibration parameter set of the camera calibration parameter set, resulting in multiple corrected left-position images.

[0184] For each of the multiple corrected left-side images, perform the following operation:

[0185] Perform a grayscale conversion operation on the corrected left-side image to obtain a grayscale left-side image, wherein the grayscale left-side image includes: multiple grayscale pixels;

[0186] By summarizing the grayscale left-side images, multiple grayscale left-side images are obtained. Based on the left-side image sequence and the multiple grayscale left-side images, the left-side grayscale image sequence is determined.

[0187] A right-level grayscale image sequence is obtained from the right-level image sequence of the right-level calibration parameter set and the component image sequence set of the camera calibration parameter set; an upper-level grayscale image sequence is obtained from the upper-level image sequence of the upper-level calibration parameter set and the component image sequence set of the camera calibration parameter set; and a lower-level grayscale image sequence is obtained from the lower-level image sequence of the lower-level calibration parameter set and the component image sequence set of the camera calibration parameter set.

[0188] By summing the left-side grayscale image sequence, right-side grayscale image sequence, upper-side grayscale image sequence, and lower-side grayscale image sequence, an optimized image sequence set is obtained.

[0189] For example, after inputting multiple left-side element images, left-side distortion parameters, and left-side intrinsic parameter matrices into OpenCV, the distortion correction function in OpenCV, cv2.initUndistortRectifyMap, can be used to automatically correct the distortion of each left-side element image in the multiple left-side element images in sequence to obtain multiple corrected left-side images. The above process is existing technology and will not be described in detail here.

[0190] It should be explained that performing grayscale conversion on the corrected left-side image means converting every pixel in the corrected left-side image to grayscale. Furthermore, the technique of performing grayscale conversion on the corrected left-side image to obtain a grayscale left-side image is existing technology and will not be elaborated upon here. Grayscale pixels are pixels in the grayscale left-side image.

[0191] It should be understood that the determination of the left grayscale image sequence based on the left image sequence and multiple grayscale left images means: sorting multiple grayscale left images according to the order of the left element images corresponding to the grayscale left images in the left image sequence to obtain the left grayscale image sequence.

[0192] It is understood that the methods for obtaining right-level grayscale image sequences based on the right-level calibration parameter set and the right-level image sequence of the component image sequence set, the methods for obtaining upper-level grayscale image sequences based on the upper-level calibration parameter set and the upper-level image sequence of the component image sequence set, and the methods for obtaining lower-level grayscale image sequences based on the lower-level calibration parameter set and the lower-level image sequence of the component image sequence set are all the same as the methods for obtaining left-level grayscale image sequences using the left-level calibration parameter set and the left-level image sequence of the component image sequence set, and will not be described again here.

[0193] S7. Perform environmental weight analysis on the optimized image sequence set to obtain the left and right flash weights and the up and down flash weights. Based on the camera calibration parameter set, the left and right flash weights and the up and down flash weights, perform binocular vision analysis on the optimized image sequence set to obtain the component coordinate sequence and the component angle sequence.

[0194] In detail, the environmental weight analysis of the optimized image sequence set to obtain the left-right flare weights and the up-down flare weights includes:

[0195] For each left-hand grayscale image in the optimized image sequence set, perform the following operation:

[0196] The mean gray level is calculated from multiple gray-level pixels in the left-side gray-level image. The calculation formula is as follows:

[0197]

[0198] in, G is the grayscale mean. i Let m be the gray value of the i-th gray pixel among a plurality of gray pixels, and m be the number of gray pixels among the plurality of gray pixels.

[0199] Summarize the grayscale averages to obtain multiple grayscale averages;

[0200] The standard deviation of the left-side brightness is calculated based on multiple gray-level means, where the variance of the left-side brightness is the standard deviation of multiple gray-level means.

[0201] The standard deviation of right-side brightness is obtained from the right-side grayscale image sequence of the optimized image sequence set; the standard deviation of upper-side brightness is obtained from the upper-side grayscale image sequence of the optimized image sequence set; and the standard deviation of lower-side brightness is obtained from the lower-side grayscale image sequence of the optimized image sequence set.

[0202] The sum standard deviation is calculated based on the standard deviations of the left, right, upper, and lower luminance, where the sum standard deviation is the sum of the standard deviations of the left, right, upper, and lower luminance.

[0203] The left and right flicker weights are calculated based on the standard deviations of the left, right, and total brightness, as shown in the following formula:

[0204]

[0205] Where, μ 12 The left and right flicker weights are σ1 and σ2, respectively, representing the standard deviations of the left and right brightness levels. x The sum of standard deviations;

[0206] The upper and lower flicker weights are calculated based on the upper luminance standard deviation, the lower luminance standard deviation, and the sum standard deviation.

[0207] It is understood that the methods for obtaining the right-side brightness standard deviation based on the right-side grayscale image sequence of the optimized image sequence set, the methods for obtaining the upper-side brightness standard deviation based on the upper-side grayscale image sequence of the optimized image sequence set, and the methods for obtaining the lower-side brightness standard deviation based on the lower-side grayscale image sequence of the optimized image sequence set are all the same as the methods for obtaining the left-side brightness standard deviation using the left-side grayscale image sequence of the optimized image sequence set, and will not be described again here.

[0208] It should be understood that the left and right flicker weights reflect the degree of brightness fluctuation in multiple images captured by the left and right cameras. The larger the left and right flicker weights, the smaller the brightness fluctuation in the multiple images captured by the left and right cameras. The method for calculating the upper and lower flicker weights based on the upper brightness standard deviation, the lower brightness standard deviation, and the sum standard deviation is the same as the method for calculating the left and right flicker weights based on the left brightness standard deviation, the right brightness standard deviation, and the sum standard deviation, and will not be repeated here.

[0209] It is understandable that changes in external brightness or fluctuations in the brightness of the light-emitting device in the LED patch structure will affect the image captured by the four-way focusing camera array, thereby affecting the accuracy of subsequent edge recognition. Therefore, this embodiment of the invention calculates the left and right flash weights and the up and down flash weights, so as to facilitate the subsequent allocation of the depth distance weights based on the left and right flash weights and the up and down flash weights, thereby improving the accuracy of the three-dimensional coordinates of the recognition element.

[0210] In detail, the step of performing binocular visual analysis on the optimized image sequence set based on the camera calibration parameter set, left and right flash weights, and up and down flash weights to obtain the component coordinate sequence and component angle sequence includes:

[0211] Extract the j-th gray-level left image, h-th gray-level right image, h-th gray-level upper image, and j-th gray-level lower image from the left gray-level image sequence, right gray-level image sequence, upper gray-level image sequence, and lower gray-level image sequence of the optimized image sequence set, respectively, where the initial value of h is 1;

[0212] The edge recognition algorithm is used to perform edge recognition on the h-th grayscale left-side image to obtain the edge pixel set;

[0213] Perform the following operation on each edge pixel in the edge pixel set:

[0214] Based on the edge pixels, multiple neighboring pixels were identified in the h-th grayscale left-side image;

[0215] For each of a plurality of neighboring pixels, perform the following operation:

[0216] Determine whether a neighboring pixel is an edge pixel in the edge pixel set;

[0217] If a neighboring pixel is an edge pixel in the edge pixel set, then the neighboring pixel is recorded as a marked pixel.

[0218] The marked pixels are summarized to obtain multiple marked pixels. The number of marks is determined based on the multiple marked pixels. The number of marks is the number of marked pixels among the multiple marked pixels. The number of neighbors is determined based on multiple neighboring pixels.

[0219] The marker ratio is calculated based on the number of markers and the number of adjacent markers, using the following formula:

[0220]

[0221] Where, γ x To indicate the scale, N k and N l These represent the number of markers and the number of neighbors, respectively.

[0222] Compare the marking ratio with a preset ratio threshold. If the marking ratio is greater than or equal to the ratio threshold, then the edge pixel corresponding to the marking ratio is taken as the target pixel.

[0223] Summarize the target pixels to obtain multiple target pixels;

[0224] Identify the center pixel in the j-th grayscale left-side image, where the center pixel is the grayscale pixel located at the geometric center of the j-th grayscale left-side image;

[0225] A first planar coordinate system is constructed in the j-th grayscale left-side image with the center pixel as the origin. The direction from the first grayscale pixel at the top left corner of the j-th grayscale left-side image to the first grayscale pixel at the top right corner of the j-th grayscale left-side image is taken as the positive direction of the horizontal axis of the first planar coordinate system. The direction from the first grayscale pixel at the top left corner of the j-th grayscale left-side image to the first grayscale pixel at the bottom left corner of the j-th grayscale left-side image is taken as the positive direction of the vertical axis of the first planar coordinate system. The length of the grayscale pixel is taken as the unit length of the first planar coordinate system.

[0226] Based on the first plane coordinate system, multiple target pixels are screened by quadrant to obtain multiple first pixels and multiple third pixels. The first pixels are target pixels located in the first quadrant of the first plane coordinate system, and the third pixels are target pixels located in the third quadrant of the first plane coordinate system.

[0227] For each of the multiple first pixels, perform the following operation:

[0228] Determine the first pixel coordinates of the first pixel in the first plane coordinate system, and calculate the edge distance based on the first pixel coordinates. The calculation formula is as follows:

[0229]

[0230] Among them, D x x is the edge distance. m Let y be the x-coordinate of the first pixel. m The ordinate of the first pixel.

[0231] Sum the edge distances to obtain multiple edge distances, and mark the first pixel coordinate corresponding to the largest edge distance among the multiple edge distances as the j-th left-side top coordinate;

[0232] The j-th left-side coordinate is obtained based on multiple third-pixel points and the first planar coordinate system.

[0233] Based on the j-th grayscale right-side image, obtain the j-th right-side top coordinate and the j-th right-side bottom coordinate; based on the j-th grayscale upper image, obtain the j-th upper-side coordinate and the j-th upper-side bottom coordinate; based on the j-th grayscale lower image, obtain the j-th lower-side top coordinate and the j-th lower-side bottom coordinate.

[0234] The j-th upper depth distance is calculated based on the interval distance, camera calibration parameter set, left and right flash weights, up and down flash weights, j-th left upper coordinate, j-th right upper coordinate, j-th upper upper coordinate, and j-th lower upper coordinate.

[0235] The j-th horizontal distance is calculated based on the j-th left-side coordinate, the j-th upper depth distance, and the left-side calibration parameter set of the camera calibration parameter set. The calculation formula is as follows:

[0236]

[0237] in, For the j-th horizontal distance, f is the x-coordinate of the j-th left-hand coordinate. x1 and c x1 These are the horizontal focal length and the x-coordinate of the principal point in the left-position calibration parameter set, respectively. The depth distance is the j-th dimension.

[0238] The j-th upper vertical distance is calculated based on the j-th left upper coordinate, the j-th upper depth distance, and the left calibration parameter set of the camera calibration parameter set. The calculation formula is as follows:

[0239]

[0240] in, For the j-th vertical distance, f is the ordinate of the j-th left coordinate. y1 and c y1 These are the vertical focal length and the ordinate of the principal point in the left-position calibration parameter group, respectively.

[0241] The j-th upper corner 3D coordinates are constructed based on the j-th upper depth distance, j-th upper horizontal distance, and j-th upper vertical distance, as shown below:

[0242]

[0243] in, Let j be the three-dimensional coordinates of the j-th upper corner;

[0244] The j-th lower corner 3D coordinates are obtained based on the interval distance, camera calibration parameter set, left and right flash weights, up and down flash weights, j-th left lower coordinate, j-th right lower coordinate, j-th upper lower coordinate, and j-th lower lower coordinate.

[0245] The center's three-dimensional coordinates are calculated based on the three-dimensional coordinates of the j-th upper corner and the j-th lower corner, as shown below:

[0246]

[0247] in, Centered on three-dimensional coordinates, and These are the x-axis, y-axis, and z-axis coordinates of the j-th lower corner in three-dimensional coordinates, respectively.

[0248] The diagonal vector of the element is calculated based on the three-dimensional coordinates of the j-th upper corner and the j-th lower corner, as shown below:

[0249]

[0250] in, The element's diagonal vector;

[0251] The diagonal angle of the component is calculated based on the component's diagonal vector and the preset horizontal axis unit vector, using the following formula:

[0252]

[0253] Where, θ x The diagonal angle of the element is denoted by arccosine, and × is the cross product of the exponent.

[0254] Let J = j + 1, take J as j, and return to the steps of extracting the j-th gray-level left image, the j-th gray-level right image, the j-th gray-level upper image and the j-th gray-level lower image from the left gray-level image sequence, the right gray-level image sequence, the upper gray-level image sequence and the lower gray-level image sequence of the optimized image sequence set respectively, until J = M, where M is the number of left gray-level images in the left gray-level image sequence;

[0255] By summarizing the three-dimensional coordinates of the center, multiple three-dimensional coordinates of the center are obtained. By summarizing the diagonal angles of the elements, multiple diagonal angles of the elements are obtained. The element coordinate sequence is determined based on the left grayscale image sequence and multiple three-dimensional coordinates of the center. The element angle sequence is determined based on the left grayscale image sequence and multiple diagonal angles of the elements.

[0256] It should be explained that identifying multiple neighboring pixels based on edge pixels in the j-th grayscale left-side image means: establishing a 3×3 pixel window centered on the edge pixel in the j-th grayscale left-side image, taking the grayscale pixels within the pixel window as the neighboring pixels, and summing up the neighboring pixels to obtain multiple neighboring pixels. The method for determining the number of neighbors based on multiple neighboring pixels is the same as the method for determining the number of markers based on multiple marker pixels, and will not be repeated here.

[0257] Optionally, the edge recognition algorithm is the Canny operator, and the technique of using a pre-constructed edge recognition algorithm to perform edge recognition on the j-th grayscale left-side image to obtain the edge pixel set is existing technology and will not be elaborated here. The edge pixel set refers to the set of multiple pixels in the j-th grayscale left-side image that meet the detection conditions of the Canny operator and are located at positions with significant changes in grayscale gradient. In reality, the multiple pixels usually correspond to multiple points located at the boundary between the adsorption patch element and the background of the external environment.

[0258] It should be understood that the ratio threshold is manually set by the staff of the LED chip factory, and optionally, the ratio threshold is 50%. This embodiment of the invention compares the marked ratio with the preset ratio threshold to filter out isolated pixels that are misidentified during edge recognition, thus avoiding misjudging individual pixels without connectivity as valid edges and improving the accuracy of edge pixel recognition.

[0259] It is understood that the process of quadrant-based sieving of multiple target pixels using the first plane coordinate system to obtain multiple first pixels and multiple third pixels refers to: designating all target pixels located in the first quadrant of the first plane coordinate system as first pixels, and designating all target pixels located in the third quadrant of the first plane coordinate system as third pixels, and summing the first and third pixels to obtain multiple first pixels and multiple third pixels. The method for obtaining the j-th left-lower coordinate based on multiple third pixels and the first plane coordinate system is the same as the method for obtaining the j-th left-upper coordinate using multiple first pixels and the first plane coordinate system, and will not be repeated here. The methods for obtaining the j-th right upper coordinate and j-th right lower coordinate based on the j-th grayscale right image, the methods for obtaining the j-th upper upper coordinate and j-th upper lower coordinate based on the j-th grayscale upper image, and the methods for obtaining the j-th lower upper coordinate and j-th lower lower coordinate based on the j-th grayscale lower image are all the same as the methods for obtaining the j-th left upper coordinate and j-th left lower coordinate using the j-th grayscale left image, and will not be described again here.

[0260] It should be explained that the j-th upper corner 3D coordinates and j-th lower corner 3D coordinates refer to the 3D coordinates of the upper right and lower left corner vertices of the side of the adsorbed patch element facing the four-way focusing camera array in the calibration 3D coordinate system when capturing the j-th grayscale left-position image. The j-th upper depth distance, j-th upper horizontal distance, and j-th upper vertical distance refer to the z-axis, x-axis, and y-axis coordinates of the j-th upper corner 3D coordinates, respectively. The method for obtaining the j-th lower corner 3D coordinates based on the interval distance, camera calibration parameter set, left and right flash weights, upper and lower flash weights, j-th left lower coordinate, j-th right lower coordinate, j-th upper upper coordinate, and j-th lower lower coordinate is the same as the method for obtaining the j-th upper corner 3D coordinate using the interval distance, camera calibration parameter set, left and right flash weights, upper and lower flash weights, j-th left upper coordinate, j-th right upper coordinate, j-th upper upper coordinate, and j-th lower upper coordinate, and will not be repeated here.

[0261] It should be understood that the central three-dimensional coordinates refer to the three-dimensional coordinates of the geometric center point of the side of the adsorption patch element facing the four-way focusing camera array in the calibration three-dimensional coordinate system. The horizontal axis unit vector is (1, 0, 0). In this embodiment of the invention, the direction of the horizontal axis unit vector reflects the sliding direction. The element diagonal angle refers to the angle between the direction from the lower left corner vertex to the upper right corner vertex of the side of the adsorption patch element facing the four-way focusing camera array and the sliding direction. By calculating the central three-dimensional coordinates and the element diagonal angle, it is convenient to compare the central three-dimensional coordinates with the target coordinates to correct the offset of the center point of the adsorption patch element, and to compare the element diagonal angle with the target angle to correct the angular offset of the adsorption patch.

[0262] For example, during the first execution, the first-ranked grayscale left image, the first-ranked grayscale right image, the first-ranked grayscale upper image, and the first-ranked grayscale lower image are extracted from the left-ranked grayscale image sequence, the right-ranked grayscale image sequence, the upper-ranked grayscale image sequence, and the lower-ranked grayscale image sequence of the optimized image sequence set, respectively. A set of center three-dimensional coordinates and element diagonal angles are obtained. Let J = j + 1 = 2, and return to the step of extracting the j-th grayscale left image and the j-th grayscale right image from the left-ranked grayscale image sequence, the right-ranked grayscale image sequence, the upper-ranked grayscale image sequence, and the lower-ranked grayscale image sequence of the optimized image sequence set, respectively. The steps for obtaining the j-th grayscale upper image and the j-th grayscale lower image are as follows: extract the second grayscale left image, the second grayscale right image, the second grayscale upper image, and the second grayscale lower image from the left grayscale image sequence, the right grayscale image sequence, the upper grayscale image sequence, and the lower grayscale image sequence of the optimized image sequence set again, until J = the number of left grayscale images in the left grayscale image sequence, that is, all images in the left grayscale image sequence have been extracted. Summarize all the center three-dimensional coordinates in the loop process to obtain multiple center three-dimensional coordinates, and summarize the diagonal angles of the elements to obtain multiple element diagonal angles.

[0263] It is understood that the method for determining the component coordinate sequence based on the left-side grayscale image sequence and multiple center three-dimensional coordinates, and the method for determining the component angle sequence based on the left-side grayscale image sequence and multiple component diagonal angles are the same as the method for determining the left-side grayscale image sequence based on the left-side image sequence and multiple grayscale left-side images, and will not be described again here.

[0264] In detail, the formula for calculating the j-th upper depth distance is as follows:

[0265]

[0266] in, For the j-th depth distance, μ 34 For the upper and lower light flicker weights, f x1 f x2 f y3 and f y4 These are the horizontal focal lengths of the left and right calibration parameter groups, the vertical focal lengths of the upper and lower calibration parameter groups, respectively, within the camera calibration parameter set. Let x be the x-coordinate of the j-th left-hand coordinate. Let x be the x-coordinate of the j-th right-hand coordinate. Let be the ordinate of the j-th upper coordinate. d0 is the ordinate of the j-th lower coordinate, d0 is the interval distance, and || indicates taking the absolute value.

[0267] S8. Perform vibration characteristic analysis on the component coordinate sequence and component angle sequence to obtain the patch center coordinates and patch diagonal angles.

[0268] In detail, the vibration characteristic analysis of the component coordinate sequence and component angle sequence to obtain the patch center coordinates and patch diagonal angle includes:

[0269] Extract the k-th center 3D coordinate from the component coordinate sequence, where the initial value of k is 2;

[0270] Based on the k-th center three-dimensional coordinates, the k-1-th center three-dimensional coordinates are determined in the component coordinate sequence. The k-th center three-dimensional coordinates are adjacent to and lag behind the k-1-th center three-dimensional coordinates in the component coordinate sequence.

[0271] The vibration distance is calculated based on the three-dimensional coordinates of the k-th center and the (k-1)-th center, using the following formula:

[0272] d kx =|Z k ―Z k―1 |

[0273] Where, d kx Z is the vibration distance. k and Z k―1 These are the z-axis coordinates of the k-th center three-dimensional coordinates and the (k-1)-th center three-dimensional coordinates, respectively;

[0274] Let K = k + 1, take K as k, and return to the step of extracting the kth center three-dimensional coordinate from the component coordinate sequence until K = M;

[0275] Summarize the vibration distances to obtain multiple vibration distances, and take the k-th center three-dimensional coordinates corresponding to the smallest vibration distance among the multiple vibration distances as the patch center coordinates;

[0276] Confirm the position of the chip center coordinates in the component coordinate sequence, and extract the chip diagonal angle from the chip diagonal angle based on the position.

[0277] For example, if the ordinal number of the patch center coordinate in the component coordinate sequence is 3, then the sorting position is 3, and the third component diagonal angle is extracted from the patch diagonal angle, and the third component diagonal angle is used as the patch diagonal angle.

[0278] It should be understood that since the adsorption patch element takes a picture immediately after sliding to the target stopping point on the motion guide rail, the adsorption patch element will vibrate slightly during this process. This causes slight deviations between multiple center three-dimensional coordinates in the element coordinate sequence, making it difficult to accurately determine the true position of the geometric center point of the side of the adsorption patch element facing the four-way focusing camera array. Therefore, this embodiment of the invention analyzes the changes in the z-axis coordinate of the center three-dimensional coordinates corresponding to the adsorption patch element, and takes the center three-dimensional coordinate with the smallest vibration amplitude as the patch center coordinate, that is, the three-dimensional coordinate corresponding to the true position of the geometric center point of the side of the adsorption patch element facing the four-way focusing camera array, and uses it for subsequent calibration, thereby improving the accuracy of position deviation calibration.

[0279] S9. Based on the center coordinates of the chip mounter and the diagonal angle of the chip mounter, the deviation of the chip mounter mechanism is corrected to obtain the target chip mounter mechanism, thus completing the deviation correction of the LED chip mounter.

[0280] Specifically, the step of correcting the deviation of the prepared placement mechanism based on the center coordinates and diagonal angle of the patch to obtain the target placement mechanism includes:

[0281] Calculate the x-axis deviation distance, y-axis deviation distance and z-axis deviation distance based on the preset target coordinates and patch center coordinates; calculate the deviation angle based on the preset target angle and patch diagonal angle.

[0282] The preparation patching mechanism is corrected based on the three-dimensional coordinate difference and deviation angle to obtain the target patching mechanism.

[0283] It should be explained that the target angle is related to the model of the surface mount element. When the surface mount element is in the correct mounting position, the long side of its bottom surface should be parallel to the sliding direction. At this time, the target angle is the angle formed between the long side of the bottom surface of the surface mount element and its bottom diagonal. The target coordinates are related to the internal structure of the LED surface mount mechanism. For example, after the LED surface mount factory workers manually calibrate the surface mount device, they move the manually calibrated device to the target stopping point in the detection section of the motion guide rail. At this time, the three-dimensional coordinates of the geometric center point of the surface mount element facing the four-way focusing camera array in the calibration three-dimensional coordinate system are the target coordinates.

[0284] Understandably, the x-axis deviation distance is obtained by subtracting the x-axis coordinate of the patch center from the x-axis coordinate of the target coordinate; the y-axis deviation distance is obtained by subtracting the y-axis coordinate of the patch center from the y-axis coordinate of the target coordinate; and the z-axis deviation distance is obtained by subtracting the z-axis coordinate of the patch center from the z-axis coordinate of the target coordinate. The deviation angle is obtained by subtracting the diagonal angle of the patch from the target angle.

[0285] For example, when the deviation angle is obtained, the rotating motor in the adsorption and placement device can be used to drive the nozzle to rotate counterclockwise by the deviation angle to correct the angle of the adsorbed component. When the x-axis deviation distance, y-axis deviation distance, and z-axis deviation distance are obtained, if all three are positive, the placement mechanism can move the x-axis deviation distance in the positive direction of the x-axis of the calibration three-dimensional coordinate system, the y-axis deviation distance in the positive direction of the y-axis of the calibration three-dimensional coordinate system, and the z-axis deviation distance in the positive direction of the z-axis of the calibration three-dimensional coordinate system from the original preset bonding position when the adsorbed component is subsequently placed onto the circuit board pad. This determines a new bonding position, realizes the position error correction of the center point of the component before placement, and improves the placement accuracy.

[0286] To address the problems described in the background art, this invention provides an LED chip mounting mechanism. This mechanism includes a feeding area, a detection area, a mounting area, a motion guide rail, and a mounting device. The motion guide rail comprises a feeding section, a detection section, and a mounting section, each located directly above the feeding area, detection area, and mounting area, respectively. The mounting device is mounted on the motion guide rail. The feeding area includes multiple chip components, the detection area includes a detection platform, and the mounting device includes a nozzle and a rotary motor, with the rotary motor connected to the nozzle. This invention, by pre-defining a complete LED chip mounting mechanism, provides a systematic working environment for subsequent component mounting, improving the automation level of component mounting. A high-definition camera set is acquired, and a four-way focusing camera array is constructed in the detection area using the high-definition camera set. The high-definition camera set includes four high-definition cameras. A calibration patch mechanism is identified based on the four-way focusing camera array and the LED patch mechanism. This embodiment of the invention improves the detection area of ​​the LED patch mechanism by constructing a four-way focusing camera array within the detection area of ​​the LED patch mechanism using the high-definition camera set, replacing a single camera with a multi-camera array to optimize the accuracy of position deviation detection and improve the deviation correction effect. The four-way focusing camera array is calibrated using a pre-constructed calibration board to obtain a set of camera calibration parameters. This embodiment of the invention obtains necessary intrinsic parameters by calibrating the four-way focusing camera array before formal calibration. The matrix and distortion coefficients facilitate subsequent image optimization based on the distortion coefficients, and the two-dimensional position information in the image is converted into the three-dimensional position information of the components based on the intrinsic parameter matrix, improving the accuracy of deviation correction. When a pre-constructed placement instruction is received, the placement device in the correction placement mechanism is prepared for correction, resulting in a prepared placement mechanism. Based on a preset shooting interval, a set of component image sequences for the prepared placement mechanism is acquired. The component image sequence set includes: left-side image sequence, right-side image sequence, upper-side image sequence, and lower-side image sequence. The component image sequence set is optimized based on the camera calibration parameter set to obtain an optimized image sequence set. It can be seen that the embodiments of the present invention automatically perform the placement process and acquire the placement mechanism by receiving the placement instruction. The component image sequence set improves the automation level of deviation correction, and image optimization based on the camera calibration parameter set improves the accuracy of deviation correction. Environmental weight analysis is performed on the optimized image sequence set to obtain left-right and up-down flash weights. Based on the camera calibration parameter set, left-right and up-down flash weights, binocular vision analysis is performed on the optimized image sequence set to obtain the component coordinate sequence and component angle sequence. It can be seen that the embodiments of the present invention, by performing environmental weight analysis and binocular vision analysis, effectively improve the accuracy of deviation correction by acquiring the three-dimensional coordinates and angle information of components through binocular vision while considering environmental influences. Vibration characteristic analysis is then performed on the component coordinate sequence and component angle sequence.By obtaining the center coordinates and diagonal angles of the LED chip mount, this embodiment of the invention analyzes the vibration of the component by tracking the temporal changes of the three-dimensional coordinates in the component coordinate sequence. This effectively filters out coordinates and angles with smaller vibration amplitudes, eliminating errors caused by dynamic factors such as vibration. This results in more stable and reliable center coordinates and diagonal angles, improving the accuracy of deviation correction. Based on the center coordinates and diagonal angles, deviation correction is performed on the preparation mounting mechanism to obtain the target mounting mechanism, completing the deviation correction of the LED chip mounter. Therefore, this embodiment of the invention automatically corrects the deviation of the adsorbed components in the preparation mounting mechanism using the center coordinates and diagonal angles, improving the automation level of deviation correction and ultimately improving the component mounting quality. Thus, this invention can improve the accuracy and automation of deviation correction, thereby improving the component mounting quality.

[0287] like Figure 2 The diagram shown is a functional block diagram of a position deviation correction system for an LED chip mounter provided in an embodiment of the present invention.

[0288] The position deviation correction system 100 for an LED pick-and-place machine described in this invention can be installed in an electronic device 1. Depending on the functions implemented, the position deviation correction system 100 for an LED pick-and-place machine may include a pick-and-place mechanism confirmation module 101, a camera array construction module 102, a component image acquisition module 103, and a pick-and-place image correction module 104. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and which are stored in the memory of the electronic device.

[0289] The LED mounting mechanism confirmation module 101 confirms the LED mounting mechanism, which includes: a feeding area, a detection area, a mounting area, a motion guide rail, and a mounting device. The motion guide rail includes: a feeding section, a detection section, and a mounting section, which are located directly above the feeding area, the detection area, and the mounting area, respectively. The mounting device is installed on the motion guide rail. The feeding area includes: multiple mounting elements. The detection area includes: a detection platform. The mounting device includes: a nozzle and a rotary motor, wherein the rotary motor is connected to the nozzle.

[0290] The camera array construction module 102 is used to acquire a high-definition camera set and construct a four-way focusing camera array in the detection area using the high-definition camera set. The high-definition camera set includes four high-definition cameras. A calibration patch mechanism is identified based on the four-way focusing camera array and the LED patch mechanism. The four-way focusing camera array is calibrated using a pre-constructed calibration board to obtain a set of camera calibration parameters.

[0291] The component image acquisition module 103 is used to prepare the patching device in the patching mechanism for calibration when a pre-constructed patching instruction is received, to obtain a prepared patching mechanism, and to acquire a component image sequence set of the prepared patching mechanism based on a preset shooting interval. The component image sequence set includes: a left image sequence, a right image sequence, a top image sequence, and a bottom image sequence. The component image sequence set is optimized based on a camera calibration parameter set to obtain an optimized image sequence set.

[0292] The patch image correction module 104 is used to perform environmental weight analysis on the optimized image sequence set to obtain the left and right flash weights and the up and down flash weights. Based on the camera calibration parameter set, the left and right flash weights, and the up and down flash weights, the optimized image sequence set is subjected to binocular visual analysis to obtain the component coordinate sequence and the component angle sequence. Vibration feature analysis is performed on the component coordinate sequence and the component angle sequence to obtain the patch center coordinates and the patch diagonal angle. Based on the patch center coordinates and the patch diagonal angle, the deviation correction is performed on the prepared patching mechanism to obtain the target patching mechanism, thus completing the deviation correction of the LED patching machine.

[0293] In detail, the modules in the position deviation correction system 100 for an LED chip mounter described in this embodiment of the invention employ the same methods as described above during use. Figure 1 The same technical means are used for the position deviation correction device for LED chip mounters described in the article, and can produce the same technical effect, so they will not be repeated here.

[0294] like Figure 3 The diagram shown is a structural schematic of an electronic device 1 for implementing a position deviation correction system for an LED chip mounter, according to an embodiment of the present invention.

[0295] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a position deviation correction system program for an LED chip mounter.

[0296] The memory 11 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the electronic device 1. Furthermore, the memory 11 includes both internal storage units and external storage devices of the electronic device 1. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 1, such as code for a position deviation correction system program for an LED chip mounter, but also to temporarily store data that has been output or will be output.

[0297] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., a position deviation correction system program for an LED chip mounter) and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0298] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0299] Figure 3 Only electronic devices with components are shown; it will be understood by those skilled in the art that... Figure 3The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0300] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0301] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the electronic device 1 and other electronic devices.

[0302] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired or wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 1 and to display a visual user interface.

[0303] The position deviation correction system program for the LED chip mounter stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When run in the processor 10, it can achieve the following:

[0304] The LED chip mounting mechanism has been identified. This mechanism includes a feeding area, a testing area, a mounting area, a motion guide rail, and a mounting device. The motion guide rail comprises a feeding section, a testing section, and a mounting section, all located directly above the feeding area, testing area, and mounting area, respectively. The mounting device is mounted on the motion guide rail. The feeding area includes multiple chip elements. The testing area includes a testing platform. The mounting device includes a nozzle and a rotary motor, with the rotary motor connected to the nozzle.

[0305] A high-definition camera set is acquired, and a four-way focusing camera array is constructed in the detection area using the high-definition camera set. The high-definition camera set includes four high-definition cameras. A correction patch mechanism is identified based on the four-way focusing camera array and the LED patch mechanism.

[0306] The camera calibration of the four-way focusing camera array is performed using a pre-built calibration board to obtain a set of camera calibration parameters;

[0307] When a pre-built placement instruction is received, the placement device in the placement mechanism is prepared for calibration, thus obtaining the placement mechanism preparation.

[0308] The component image sequence set of the preparation patching mechanism is obtained based on a preset shooting interval. The component image sequence set includes: left image sequence, right image sequence, upper image sequence and lower image sequence.

[0309] Image optimization is performed on the component image sequence set based on the camera calibration parameter set to obtain an optimized image sequence set;

[0310] Environmental weight analysis is performed on the optimized image sequence set to obtain the left and right flash weights and the up and down flash weights. Based on the camera calibration parameter set, the left and right flash weights and the up and down flash weights, binocular vision analysis is performed on the optimized image sequence set to obtain the component coordinate sequence and the component angle sequence.

[0311] Vibration characteristic analysis was performed on the component coordinate sequence and component angle sequence to obtain the patch center coordinates and patch diagonal angles;

[0312] Based on the center coordinates and diagonal angles of the LED chip mounter, the deviation of the prepared mounting mechanism is corrected to obtain the target mounting mechanism, thus completing the deviation correction of the LED chip mounter.

[0313] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figures 1 to 3 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0314] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0315] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following:

[0316] The LED chip mounting mechanism has been identified. This mechanism includes a feeding area, a testing area, a mounting area, a motion guide rail, and a mounting device. The motion guide rail comprises a feeding section, a testing section, and a mounting section, all located directly above the feeding area, testing area, and mounting area, respectively. The mounting device is mounted on the motion guide rail. The feeding area includes multiple chip elements. The testing area includes a testing platform. The mounting device includes a nozzle and a rotary motor, with the rotary motor connected to the nozzle.

[0317] A high-definition camera set is acquired, and a four-way focusing camera array is constructed in the detection area using the high-definition camera set. The high-definition camera set includes four high-definition cameras. A correction patch mechanism is identified based on the four-way focusing camera array and the LED patch mechanism.

[0318] The camera calibration of the four-way focusing camera array is performed using a pre-built calibration board to obtain a set of camera calibration parameters;

[0319] When a pre-built placement instruction is received, the placement device in the placement mechanism is prepared for calibration, thus obtaining the placement mechanism preparation.

[0320] The component image sequence set of the preparation patching mechanism is obtained based on a preset shooting interval. The component image sequence set includes: left image sequence, right image sequence, upper image sequence and lower image sequence.

[0321] Image optimization is performed on the component image sequence set based on the camera calibration parameter set to obtain an optimized image sequence set;

[0322] Environmental weight analysis is performed on the optimized image sequence set to obtain the left and right flash weights and the up and down flash weights. Based on the camera calibration parameter set, the left and right flash weights and the up and down flash weights, binocular vision analysis is performed on the optimized image sequence set to obtain the component coordinate sequence and the component angle sequence.

[0323] Vibration characteristic analysis was performed on the component coordinate sequence and component angle sequence to obtain the patch center coordinates and patch diagonal angles;

[0324] Based on the center coordinates and diagonal angles of the LED chip mounter, the deviation of the prepared mounting mechanism is corrected to obtain the target mounting mechanism, thus completing the deviation correction of the LED chip mounter.

[0325] In the embodiments provided by this invention, it should be understood that the disclosed devices, systems, and apparatuses can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and actual implementations may have other classification methods.

[0326] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0327] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0328] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0329] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A position deviation correction device for an LED chip mounter, characterized in that, The device includes: The LED chip mounting mechanism has been identified. This mechanism includes a feeding area, a testing area, a mounting area, a motion guide rail, and a mounting device. The motion guide rail comprises a feeding section, a testing section, and a mounting section, all located directly above the feeding area, testing area, and mounting area, respectively. The mounting device is mounted on the motion guide rail. The feeding area includes multiple chip elements. The testing area includes a testing platform. The mounting device includes a nozzle and a rotary motor, with the rotary motor connected to the nozzle. A high-definition camera set is acquired, and a four-way focusing camera array is constructed in the detection area using the high-definition camera set. The high-definition camera set includes four high-definition cameras. A correction patch mechanism is identified based on the four-way focusing camera array and the LED patch mechanism. The camera calibration of the four-way focusing camera array is performed using a pre-built calibration board to obtain a set of camera calibration parameters; When a pre-built placement instruction is received, the placement device in the placement mechanism is prepared for calibration, thus obtaining the placement mechanism preparation. The component image sequence set of the preparation patching mechanism is obtained based on a preset shooting interval. The component image sequence set includes: left image sequence, right image sequence, upper image sequence and lower image sequence. Image optimization is performed on the component image sequence set based on the camera calibration parameter set to obtain an optimized image sequence set; Environmental weight analysis is performed on the optimized image sequence set to obtain the left and right flash weights and the up and down flash weights. Based on the camera calibration parameter set, the left and right flash weights and the up and down flash weights, binocular vision analysis is performed on the optimized image sequence set to obtain the component coordinate sequence and the component angle sequence. Vibration characteristic analysis was performed on the component coordinate sequence and component angle sequence to obtain the patch center coordinates and patch diagonal angles; Based on the center coordinates and diagonal angles of the LED chip mounter, the deviation of the prepared mounting mechanism is corrected to obtain the target mounting mechanism, thus completing the deviation correction of the LED chip mounter.

2. The position deviation correction device for an LED chip mounter as described in claim 1, characterized in that, The method of constructing a four-way focusing camera array in the detection area using a high-definition camera set includes: Confirm the target stopping point and sliding direction in the detection section of the motion guide rail; Confirm the detection plane of the detection platform, and determine the detection center point on the detection plane of the detection area based on the target stopping point; Obtain a transmissive backlight source, wherein the transmissive backlight source includes: a light-emitting surface; Based on the detection center point and the target dwell point, the transmission backlight is installed on the detection plane of the detection platform to obtain the installed backlight. The emitting surface of the installed backlight is parallel to the detection plane, and the point corresponding to the geometric center of the emitting surface, the detection center point, and the target dwell point are all located on the same straight line. A calibration three-dimensional coordinate system is constructed using the detection center point and the sliding direction. The detection center point is used as the origin of the calibration three-dimensional coordinate system, the sliding direction is used as the positive x-axis of the calibration three-dimensional coordinate system, and the direction from the detection center point to the target stopping point is used as the positive z-axis. The left, right, top, and bottom coordinates are determined based on the preset interval distance; The left, right, top, and bottom installation points are identified on the detection plane based on the left, right, top, and bottom coordinates, respectively. Extract high-definition cameras from the high-definition camera set, and perform the following operations on the extracted high-definition cameras: Based on the left mounting point, the high-definition camera is mounted on the detection plane of the detection platform to obtain the left-side camera, wherein the line connecting the left mounting point and the optical center of the left-side camera is perpendicular to the detection plane. The right-side camera was identified based on the right mounting point and the high-definition camera set; the upper-side camera was identified based on the upper mounting point and the high-definition camera set; and the lower-side camera was identified based on the lower mounting point and the high-definition camera set. A four-way focusing camera array was identified based on the installation of a backlight, a top camera, a bottom camera, a left camera, and a right camera.

3. The position deviation correction device for an LED chip mounter as described in claim 2, characterized in that, The process of calibrating a quad-focus camera array using a pre-built calibration board yields a set of camera calibration parameters, including: The calibration position set is identified on the detection section of the motion guide rail, wherein the calibration position set includes: multiple calibration positions; For each calibration location in the calibration location set, perform the following operation: The calibration board is placed at the calibration position to obtain the target calibration board. The left-side camera in the four-way focusing camera array is used to take a picture of the target calibration board to obtain a left-side image. A pre-built corner detector is used to identify multiple left corner points and multiple left two-dimensional coordinates in a left-side image, wherein each left corner point corresponds one-to-one with its left two-dimensional coordinate. Multiple left-position three-dimensional coordinates were identified in the calibrated three-dimensional coordinate system based on multiple left-position corner points, where each left-position corner point corresponds one-to-one with a left-position three-dimensional coordinate. By pairing and combining multiple left-position two-dimensional coordinates and multiple left-position three-dimensional coordinates, a set of left-position calibration coordinates is obtained. The left calibration coordinate set is summarized to obtain multiple left calibration coordinate sets. The multiple left calibration coordinate sets are analyzed using a pre-built camera calibrator to obtain the left calibration parameter set. The left calibration parameter set includes: left intrinsic parameter matrix and left distortion parameter. The left intrinsic parameter matrix includes: horizontal focal length, vertical focal length, x-coordinate of principal point and y-coordinate of principal point. The right-side calibration parameter set is determined based on the corner point identifier, camera calibrator, calibration position set, calibration board, and the right-side camera in the four-way focusing camera array. The upper-side calibration parameter set is determined based on the corner point identifier, camera calibrator, calibration position set, calibration board, and the upper-side camera in the four-way focusing camera array. The lower-side calibration parameter set is determined based on the corner point identifier, camera calibrator, calibration position set, calibration board, and the lower-side camera in the four-way focusing camera array. The camera calibration parameter set is obtained by summarizing the left-side calibration parameter set, the right-side calibration parameter set, the upper-side calibration parameter set, and the lower-side calibration parameter set.

4. The position deviation correction device for an LED chip mounter as described in claim 3, characterized in that, The calibration preparation of the patch device in the calibration patching mechanism, to obtain a prepared patching mechanism, includes: Move the placement device in the calibration placement mechanism to the feeding section of the motion guide rail to obtain the waiting placement device; The pick-and-place device uses a nozzle in the waiting pick-and-place device to pick up and place components in the feed area of ​​the calibration pick-and-place mechanism, thereby obtaining a pick-and-place device, wherein the pick-and-place device includes: a pick-and-place element; The adsorption patch device is moved to the target stopping point of the detection section in the motion guide rail to obtain the stopping patch device; The preparation mechanism for patch placement is determined based on the dwell patch placement device and the calibration patch placement mechanism.

5. The position deviation correction device for an LED chip mounter as described in claim 4, characterized in that, The process of optimizing the image sequence set of components based on the camera calibration parameter set to obtain an optimized image sequence set includes: The distortion of multiple left-position element images in the left-position image sequence of the element image sequence set is corrected using the left-position distortion parameters and the left-position intrinsic parameter matrix in the left-position calibration parameter set of the camera calibration parameter set, resulting in multiple corrected left-position images. For each of the multiple corrected left-side images, perform the following operation: Perform a grayscale conversion operation on the corrected left-side image to obtain a grayscale left-side image, wherein the grayscale left-side image includes: multiple grayscale pixels; By summarizing the grayscale left-side images, multiple grayscale left-side images are obtained. Based on the left-side image sequence and the multiple grayscale left-side images, the left-side grayscale image sequence is determined. A right-level grayscale image sequence is obtained from the right-level image sequence of the right-level calibration parameter set and the component image sequence set of the camera calibration parameter set; an upper-level grayscale image sequence is obtained from the upper-level image sequence of the upper-level calibration parameter set and the component image sequence set of the camera calibration parameter set; and a lower-level grayscale image sequence is obtained from the lower-level image sequence of the lower-level calibration parameter set and the component image sequence set of the camera calibration parameter set. By summing the left-side grayscale image sequence, right-side grayscale image sequence, upper-side grayscale image sequence, and lower-side grayscale image sequence, an optimized image sequence set is obtained.

6. The position deviation correction device for an LED chip mounter as described in claim 5, characterized in that, The environmental weight analysis of the optimized image sequence set to obtain left-right flare weights and up-down flare weights includes: For each left-hand grayscale image in the optimized image sequence set, perform the following operation: Calculate the mean gray level based on multiple gray level pixels in the grayscale left-side image; Summarize the grayscale averages to obtain multiple grayscale averages; The standard deviation of the left-side brightness is calculated based on multiple gray-level means, where the variance of the left-side brightness is the standard deviation of multiple gray-level means. The standard deviation of right-side brightness is obtained from the right-side grayscale image sequence of the optimized image sequence set; the standard deviation of upper-side brightness is obtained from the upper-side grayscale image sequence of the optimized image sequence set; and the standard deviation of lower-side brightness is obtained from the lower-side grayscale image sequence of the optimized image sequence set. The sum standard deviation is calculated based on the standard deviations of the left, right, upper, and lower luminance, where the sum standard deviation is the sum of the standard deviations of the left, right, upper, and lower luminance. The left and right flicker weights are calculated based on the standard deviations of the left, right, and total brightness, as shown in the following formula: Where, μ 12 The left and right flicker weights are σ1 and σ2, respectively, representing the standard deviations of the left and right brightness levels. x The sum of standard deviations; The upper and lower flicker weights are calculated based on the upper luminance standard deviation, the lower luminance standard deviation, and the sum standard deviation.

7. The position deviation correction device for an LED chip mounter as described in claim 6, characterized in that, The optimized image sequence set is analyzed using binocular vision based on the camera calibration parameter set, left and right flash weights, and up and down flash weights to obtain the component coordinate sequence and component angle sequence, including: Extract the j-th gray-level left image, j-th gray-level right image, j-th gray-level upper image, and j-th gray-level lower image from the left gray-level image sequence, right gray-level image sequence, upper gray-level image sequence, and lower gray-level image sequence of the optimized image sequence set, respectively, where the initial value of j is 1; The edge recognition algorithm is used to perform edge recognition on the j-th grayscale left-side image to obtain the edge pixel set; Perform the following operation on each edge pixel in the edge pixel set: Based on the edge pixels, multiple neighboring pixels were identified in the j-th grayscale left-side image; For each of a plurality of neighboring pixels, perform the following operation: Determine whether a neighboring pixel is an edge pixel in the edge pixel set; If a neighboring pixel is an edge pixel in the edge pixel set, then the neighboring pixel is recorded as a marked pixel. The marked pixels are summarized to obtain multiple marked pixels. The number of marks is determined based on the multiple marked pixels. The number of marks is the number of marked pixels among the multiple marked pixels. The number of neighbors is determined based on multiple neighboring pixels. Calculate the marking ratio based on the number of markings and the number of adjacent markings; Compare the marking ratio with a preset ratio threshold. If the marking ratio is greater than or equal to the ratio threshold, then the edge pixel corresponding to the marking ratio is taken as the target pixel. Summarize the target pixels to obtain multiple target pixels; Identify the center pixel in the j-th grayscale left-side image, where the center pixel is the grayscale pixel located at the geometric center of the j-th grayscale left-side image; A first planar coordinate system is constructed in the j-th grayscale left-side image with the center pixel as the origin. The direction from the first grayscale pixel at the top left corner of the j-th grayscale left-side image to the first grayscale pixel at the top right corner of the j-th grayscale left-side image is taken as the positive direction of the horizontal axis of the first planar coordinate system. The direction from the first grayscale pixel at the top left corner of the j-th grayscale left-side image to the first grayscale pixel at the bottom left corner of the j-th grayscale left-side image is taken as the positive direction of the vertical axis of the first planar coordinate system. The length of the grayscale pixel is taken as the unit length of the first planar coordinate system. Based on the first plane coordinate system, multiple target pixels are screened by quadrant to obtain multiple first pixels and multiple third pixels. The first pixels are target pixels located in the first quadrant of the first plane coordinate system, and the third pixels are target pixels located in the third quadrant of the first plane coordinate system. For each of the multiple first pixels, perform the following operation: Confirm the first pixel coordinates of the first pixel point on the first plane coordinate system, and calculate the edge distance based on the first pixel coordinates; Sum the edge distances to obtain multiple edge distances, and mark the first pixel coordinate corresponding to the largest edge distance among the multiple edge distances as the j-th left top coordinate; The j-th left-side coordinate is obtained based on multiple third-pixel points and the first planar coordinate system. Based on the j-th grayscale right-side image, obtain the j-th right-side top coordinate and the j-th right-side bottom coordinate; based on the j-th grayscale upper image, obtain the j-th upper-side coordinate and the j-th upper-side bottom coordinate; based on the j-th grayscale lower image, obtain the j-th lower-side top coordinate and the j-th lower-side bottom coordinate. The j-th upper depth distance is calculated based on the interval distance, camera calibration parameter set, left and right flash weights, up and down flash weights, j-th left upper coordinate, j-th right upper coordinate, j-th upper upper coordinate, and j-th lower upper coordinate. Calculate the j-th upper horizontal distance based on the j-th left upper coordinate, the j-th upper depth distance, and the left upper calibration parameter set in the camera calibration parameter set set; Calculate the j-th upper vertical distance based on the j-th left upper coordinate, the j-th upper depth distance, and the left upper calibration parameter set in the camera calibration parameter set set; The three-dimensional coordinates of the j-th upper corner are constructed based on the j-th upper depth distance, the j-th upper horizontal distance, and the j-th upper vertical distance; The j-th lower corner 3D coordinates are obtained based on the interval distance, camera calibration parameter set, left and right flash weights, up and down flash weights, j-th left lower coordinate, j-th right lower coordinate, j-th upper lower coordinate, and j-th lower lower coordinate. Calculate the center's three-dimensional coordinates based on the three-dimensional coordinates of the j-th upper corner and the j-th lower corner; Calculate the diagonal vector of the element based on the three-dimensional coordinates of the j-th upper corner and the j-th lower corner; Calculate the diagonal angle of the component based on the component's diagonal vector and the preset horizontal axis unit vector; Let J = j + 1, take J as j, and return to the steps of extracting the j-th gray-level left image, the j-th gray-level right image, the j-th gray-level upper image and the j-th gray-level lower image from the left gray-level image sequence, the right gray-level image sequence, the upper gray-level image sequence and the lower gray-level image sequence of the optimized image sequence set respectively, until J = M, where M is the number of left gray-level images in the left gray-level image sequence; By summarizing the three-dimensional coordinates of the center, multiple three-dimensional coordinates of the center are obtained. By summarizing the diagonal angles of the elements, multiple diagonal angles of the elements are obtained. The element coordinate sequence is determined based on the left grayscale image sequence and multiple three-dimensional coordinates of the center. The element angle sequence is determined based on the left grayscale image sequence and multiple diagonal angles of the elements.

8. The position deviation correction device for an LED chip mounter as described in claim 7, characterized in that, The formula for calculating the j-th upper depth distance is as follows: in, For the j-th depth distance, μ 34 For the upper and lower light flicker weights, f x1 f x2 f y3 and f y4 These are the horizontal focal lengths of the left and right calibration parameter groups, the vertical focal lengths of the upper and lower calibration parameter groups, respectively, within the camera calibration parameter set. Let x be the x-coordinate of the j-th left-hand coordinate. Let x be the x-coordinate of the j-th right-hand coordinate. Let be the ordinate of the j-th upper coordinate. d0 is the ordinate of the j-th lower coordinate, d0 is the interval distance, and || indicates taking the absolute value.

9. The position deviation correction device for an LED chip mounter as described in claim 8, characterized in that, The vibration characteristic analysis of the component coordinate sequence and component angle sequence to obtain the patch center coordinates and patch diagonal angles includes: Extract the k-th center 3D coordinate from the component coordinate sequence, where the initial value of k is 2; Based on the k-th center three-dimensional coordinates, the k-1-th center three-dimensional coordinates are determined in the component coordinate sequence. The k-th center three-dimensional coordinates are adjacent to and lag behind the k-1-th center three-dimensional coordinates in the component coordinate sequence. The vibration distance is calculated based on the three-dimensional coordinates of the k-th center and the (k-1)-th center. Let K = k + 1, take K as k, and return to the step of extracting the kth center three-dimensional coordinate from the component coordinate sequence until K = M; Summarize the vibration distances to obtain multiple vibration distances, and take the k-th center three-dimensional coordinates corresponding to the smallest vibration distance among the multiple vibration distances as the patch center coordinates; Confirm the position of the chip center coordinates in the component coordinate sequence, and extract the chip diagonal angle from the chip diagonal angle based on the position.

10. A position deviation correction system for an LED chip mounter, characterized in that, The system includes: The LED placement mechanism confirmation module confirms the LED placement mechanism, which includes: a feeding area, a detection area, a placement area, a motion guide rail, and a placement device. The motion guide rail includes: a feeding section, a detection section, and a placement section, which are located directly above the feeding area, detection area, and placement area, respectively. The placement device is mounted on the motion guide rail. The feeding area includes: multiple placement elements. The detection area includes: a detection platform. The placement device includes: a nozzle and a rotary motor, wherein the rotary motor is connected to the nozzle. A camera array construction module is used to acquire a high-definition camera set and construct a four-way focusing camera array in the detection area using the high-definition camera set. The high-definition camera set includes four high-definition cameras. A calibration patch mechanism is identified based on the four-way focusing camera array and the LED patch mechanism. The four-way focusing camera array is calibrated using a pre-constructed calibration board to obtain a set of camera calibration parameters. The component image acquisition module is used to prepare the patching device in the patching mechanism for calibration when a pre-constructed patching instruction is received, thereby obtaining a prepared patching mechanism. Based on a preset shooting interval, it acquires a set of component image sequences of the prepared patching mechanism. The set of component image sequences includes: left image sequence, right image sequence, upper image sequence and lower image sequence. Based on a set of camera calibration parameters, it optimizes the component image sequence set to obtain an optimized image sequence set. The chip image correction module is used to perform environmental weight analysis on the optimized image sequence set to obtain the left and right flash weights and the up and down flash weights. Based on the camera calibration parameter set, the left and right flash weights, and the up and down flash weights, the optimized image sequence set is subjected to binocular visual analysis to obtain the component coordinate sequence and the component angle sequence. Vibration feature analysis is performed on the component coordinate sequence and the component angle sequence to obtain the chip center coordinates and the chip diagonal angle. Based on the chip center coordinates and the chip diagonal angle, the deviation correction is performed on the prepared chip placement mechanism to obtain the target chip placement mechanism, thus completing the deviation correction of the LED chip placement machine.

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