CN114723758B - Production quality detection method for full-automatic connection of MiniLED thin plate - Google Patents

Production quality detection method for full-automatic connection of MiniLED thin plate Download PDF

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CN114723758B
CN114723758B CN202210649474.3A CN202210649474A CN114723758B CN 114723758 B CN114723758 B CN 114723758B CN 202210649474 A CN202210649474 A CN 202210649474A CN 114723758 B CN114723758 B CN 114723758B
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陈星�
吴建明
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Huizhou Welgao Electronics Co ltd
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Abstract

The invention relates to the field of image processing, in particular to a production quality detection method for full-automatic connection of a MiniLED sheet, which comprises the steps of collecting an unwelded gray image, a welding wire gray image and a welding spot gray image in real time; obtaining the matching degree of each circle in the unwelded gray level image and the standard circle; determining a corresponding welding area according to the circle center and the radius of each circle and the welding rule; determining a welding line in a corresponding welding area image in the welding line gray level image, and calculating a welding line quality evaluation index; meanwhile, calculating similar indexes of each welding spot image and a standard welding spot template image and obtaining the change degree of the lamp beads; and weighting and summing the matching degree, the welding wire quality evaluation index, the similar index and the change degree to obtain a comprehensive production quality index, and judging whether the MiniLED sheet is qualified. The scheme of the invention can monitor the quality of the process flow of the whole production line, thereby realizing the quality detection of the MiniLED sheet.

Description

Production quality detection method for full-automatic connection of MiniLED thin plate
Technical Field
The invention relates to the field of image processing, in particular to a production quality detection method for full-automatic connection of MiniLED sheets.
Background
Currently, mini LEDs are one of the important technical trends in the display industry, and have the advantages of thin film, miniaturization, array, high brightness and low cost as a display technology for LED to Micro LEDs transition. The conventional Mini LED production line in China at present is in the technical discussion and research and development stage, a matched detection equipment manufacturer is not moved in a large scale, and the applied Mini LED detection equipment part is imported equipment, so that the manufacturing cost is high, and the detection cost is high.
Therefore, it is particularly important to provide a quality inspection of the MiniLED sheet during the production process.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a production quality detection method for full-automatic connection of MiniLED sheets, and the adopted technical scheme is as follows:
the technical scheme of the production quality detection method for the full-automatic connection of the MiniLED thin plate provided by the invention comprises the following steps of:
acquiring an unwelded gray level image, a welding line gray level image and a welding point gray level image in real time;
performing edge detection on the unwelded gray level image to obtain edge pixel points, and performing Hough circle detection on the edge pixel points to obtain the circle centers and corresponding radiuses of a plurality of circles; calculating the difference between the radius of each circle and the radius of the standard circle, and determining the matching degree of each circle and the standard circle according to the difference; meanwhile, determining a corresponding welding area according to the circle center and the radius of each circle and the welding rule;
the welding areas correspond to the welding line gray level images one by one, the corresponding welding area images in the welding line gray level images are determined, edge pixel points of the welding area images are extracted, hough line detection is carried out on the edge pixel points, and corresponding K lines are obtained; classifying all the straight lines to obtain straight line groups of different categories; calculating the difference between one pixel point and the adjacent pixel point on the straight line; taking the mean value of the differences of all the pixel points as the confidence coefficient of the corresponding straight line, and when the confidence coefficient is greater than a set threshold value, all the straight lines in the corresponding straight line group are bonding lines; calculating a welding wire quality evaluation index according to the number of welding wires in each straight line group and the width of the welding wire area;
extracting welding spot images in the welding spot gray level images, calculating the similarity between each welding spot image and a standard welding spot template image, and obtaining the similarity index of the welding spot gray level images; electrifying the welded MiniLED sheet to obtain the change degree of the lamp beads;
and weighting and summing the matching degree, the welding wire quality evaluation index, the similar index and the change degree to obtain a comprehensive production quality index, and when the comprehensive production quality index is greater than a set threshold value, determining that the MiniLED sheet is qualified.
Further, the surface images of the MiniLED sheet in different processes in the production process are collected in real time, the surface images which are not welded, the surface images of the welding wires and the surface images of the welding points are obtained, and the surface images are subjected to gray processing to obtain corresponding gray images.
Further, the difference obtaining method comprises the following steps: acquiring the length and the angle of each straight line; classifying all the straight lines based on the lengths and the angles to obtain straight line groups of different classes; determining the LBP value of each pixel point according to the number of the pixel points of each straight line in each straight line group and the corresponding gray value; obtaining the hue value of the pixel point of each straight line; and calculating the difference between one pixel point and the adjacent pixel point on the straight line based on the LBP value and the hue value of the pixel point.
Further, the wire bonding quality evaluation index is as follows:
Figure 596206DEST_PATH_IMAGE002
wherein, U represents the width of the welding area,
Figure DEST_PATH_IMAGE003
representing the average distance between all bonding wires, F is the number of bonding wires in the straight line group,
Figure 247374DEST_PATH_IMAGE004
is as followsfStrip bonding wire and the firstf+1 distance between adjacent bonding wires.
Further, the method also comprises the step of correcting the confidence coefficient:
arbitrarily taking a certain line in the category
Figure DEST_PATH_IMAGE005
Adjacent straight lines thereof are
Figure 553590DEST_PATH_IMAGE006
，
Figure DEST_PATH_IMAGE007
；
Obtaining straight lines
Figure 680946DEST_PATH_IMAGE008
On pixel point S respectively reaches adjacent straight lines
Figure DEST_PATH_IMAGE009
、
Figure 269185DEST_PATH_IMAGE010
Of (2) is
Figure DEST_PATH_IMAGE011
，
Figure 772978DEST_PATH_IMAGE012
；
Calculating the difference between the two distances, and determining the confidence level according to the difference between the two distances
Figure DEST_PATH_IMAGE013
Adjusting to obtain a new confidence:
Figure DEST_PATH_IMAGE015
wherein the content of the first and second substances,
Figure 261597DEST_PATH_IMAGE016
is a firstkConfidence of the line.
Further, the degree of change is:
Figure 559855DEST_PATH_IMAGE018
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE019
is in a position before power-on
Figure 946974DEST_PATH_IMAGE020
The gray value of the lamp bead of (1),
Figure DEST_PATH_IMAGE021
is at a position after being electrified
Figure 113513DEST_PATH_IMAGE020
The gray value of the rear lamp bead is,
Figure 4108DEST_PATH_IMAGE022
is the number of lines of the lamp beads,
Figure DEST_PATH_IMAGE023
the number of the rows of the lamp beads.
The invention has the beneficial effects that:
according to the scheme of the invention, the gray level image of the non-welding part, the gray level image of the welding wire and the gray level image of the welding spot are collected in real time; obtaining the matching degree of each circle in the unwelded gray level image and the standard circle; determining a corresponding welding area according to the circle center and the radius of each circle and the welding rule; determining the welding lines in the corresponding welding area image in the welding line gray level image, and calculating a welding line quality evaluation index; meanwhile, calculating similar indexes of each welding spot image and a standard welding spot template image and obtaining the change degree of the lamp beads; carrying out weighted summation on the matching degree, the welding wire quality evaluation index, the similar index and the change degree to obtain a comprehensive production quality index, and judging whether the MiniLED sheet is qualified or not; the scheme of the invention can monitor the quality of the process flow of the whole production line, thereby realizing the quality detection of the MiniLED sheet.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions and advantages of the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a method flowchart of the full-automatic online production quality detection method for MiniLED thin plates.
Detailed Description
To further explain the technical means and effects of the present invention adopted to achieve the predetermined objects, the following detailed description of the embodiments, structures, characteristics and effects thereof according to the present invention will be made with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" refers to not necessarily the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The invention aims at the following scenes: detecting the production quality of the MiniLED sheet produced on the factory production line; the brightness, contrast and color gamut of the display and the viewing experience of the user are influenced by the quality of the MiniLED sheet; therefore, the invention collects the thin plate images on each flow in the production process in real time through the image processing technology, thereby completing the detection of the final production quality.
Specifically, the method for detecting the production quality of the MiniLED sheet by full-automatic wire connection provided by the present invention is described with reference to fig. 1, and includes the following steps:
step 1, acquiring an unwelded gray image, a welding line gray image and a welding point gray image in real time.
In the embodiment, the surface image of the MiniLED sheet in the production process is acquired in the form of a fixed light source by a high-resolution camera, the acquired image is often an RGB image, and a weighted graying method is adopted to perform graying processing on the RGB image to obtain a corresponding grayscale image.
It should be noted that the acquired images are images corresponding to various process flows in a full-automatic production line, such as a surface image of a sheet before welding, a welding line image after automatic wiring, and a gray scale image after welding of a welded electronic component.
Step 2, performing edge detection on the unwelded gray image to obtain edge pixel points, and performing Hough circle detection on the edge pixel points to obtain the circle centers and corresponding radiuses of a plurality of circles; calculating the difference between the radius of each circle and the radius of the standard circle, and determining the matching degree of each circle and the standard circle according to the difference; and meanwhile, determining a corresponding welding area according to the circle center and the radius of each circle and the welding rule.
In the embodiment, firstly, extracting edge pixel points of each welding area is to perform canny operator detection on images which are not welded, and detect edge information; secondly, hough circle detection is carried out on the edge pixel points, and N records are assumed to exist for each obtained circle center (A), (B)
Figure 627594DEST_PATH_IMAGE024
，
Figure DEST_PATH_IMAGE025
，
Figure 423381DEST_PATH_IMAGE026
) The sheet meeting the specification should have the center of M welding areas and the coordinate is (
Figure DEST_PATH_IMAGE027
，
Figure 534556DEST_PATH_IMAGE028
) The circle radius is R.
Then, matching the detected N circle centers, wherein the circle centers are matched according to the distance, namely the detected circle center (W) is matched with the circle center (W) with the minimum Euclidean distance to the circle center on the standard template (c)
Figure DEST_PATH_IMAGE029
) And (3) performing correlation, and calculating the similarity C between the detected circle center radius and the correlated circle center radius:
Figure DEST_PATH_IMAGE031
wherein, R is the radius of the standard circle,
Figure 233653DEST_PATH_IMAGE026
for the m-th circle center detected, m =1,2,3, \8230, N.
In this embodiment, a specific method for determining the corresponding welding area is as follows:
and connecting each detected circle center (assumed to be the circle center W at this time) with the circle center adjacent in the horizontal and vertical directions (the projection length in the horizontal or vertical direction with the circle center W is minimum) to obtain a line segment L, selecting a line segment center E point, selecting a point with the length of d/2 from the E point along the W point direction as a point B if the distance between welding areas in production requirements is d, and obtaining a line segment EB. Each circle center can obtain 4 line segments, and the area formed by the 4 line segments is the welding area of the circle center.
It should be noted that, in the above, the position information of each welding area is obtained, and the overall abnormal degree of the welding area in production is detected, and the greater the similarity C is, the better the quality is; thus, positional information of each welding area is obtained.
Step 3, enabling the welding areas to correspond to the welding line gray level images one by one, determining the corresponding welding area images in the welding line gray level images, extracting edge pixel points of the welding area images, and performing Hough line detection on the edge pixel points to obtain K corresponding lines; classifying all the straight lines to obtain straight line groups of different categories; calculating the difference between one pixel point and the adjacent pixel point on the straight line; taking the mean value of the differences of all the pixel points as the confidence coefficient of the corresponding straight line, and when the confidence coefficient is greater than a set threshold value, all the straight lines in the corresponding straight line group are bonding lines; and calculating the quality evaluation index of the welding wires according to the number of the welding wires in each straight line group and the width of the welding wire area.
In this embodiment, the welding area image in the welding line grayscale image corresponds to the welding area obtained in step 2 one to one, and the difference is that the welding area image includes the welding line that has been automatically wired, and the welding area is an area that is not wired.
The method comprises the following steps of analyzing each welding area image, namely detecting the welding area image by using a canny operator again to obtain edge pixel points, detecting Hough straight line of the edge pixel points to detect straight lines in the welding area image, judging whether the detected straight lines are welding lines or not due to the fact that interference straight lines exist inside the welding area image, and the specific process is as follows:
assuming that K straight lines are detected by hough line detection, the length L and angle of each straight line are obtained as y = ax + b
Figure 201609DEST_PATH_IMAGE032
(clockwise from horizontal).
First according to the angle
Figure 94479DEST_PATH_IMAGE032
And calculating the similarity xs between the straight lines and the L, and performing primary clustering.
Figure DEST_PATH_IMAGE033
I in the formula represents the ith straight line, j represents the jth straight line, i =1,2,3 \ 8230, K, j =1,2,3 \ 8230, K, however
Figure 806083DEST_PATH_IMAGE034
. And setting a threshold value T, judging xs, and if xs is greater than the threshold value T, indicating that the ith straight line and the jth straight line belong to the same straight line, otherwise, indicating that the ith straight line and the jth straight line belong to different straight lines.
Calculating confidence of each straight line
Figure 999167DEST_PATH_IMAGE013
：
Firstly, counting the number of pixels on a straight line as Z and the gray value of the pixels;
secondly, calculating the LBP value of each pixel point according to the gray value A of each pixel point;
the LBP value in the above is a value that has been converted into a decimal, and since LBP (local binary pattern) is a well-known technique, the acquisition process is not described in detail.
Then, performing HSV space transformation on the welding line gray image to obtain the hue value H of each pixel point;
and finally, calculating the difference between a certain pixel point and the adjacent pixel point on the straight line so as to represent the confidence coefficient Y of the pixel point as the bonding wire pixel point:
Figure 138024DEST_PATH_IMAGE036
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE037
for the LBP value of the z-th pixel,
Figure 659135DEST_PATH_IMAGE038
the LBP value of the z +1 th pixel point,
Figure DEST_PATH_IMAGE039
for the LBP value of the z-1 th pixel,
Figure 908851DEST_PATH_IMAGE040
is the tone value of the z-th pixel,
Figure DEST_PATH_IMAGE041
the tone value of the z +1 th pixel point,
Figure 690862DEST_PATH_IMAGE042
the hue value of the Z +1 th pixel point, wherein Z =1,2,3, \ 8230;, Z. Recalculating confidence of linear integral
Figure 827052DEST_PATH_IMAGE013
：
Figure 897776DEST_PATH_IMAGE044
Wherein, the first and the second end of the pipe are connected with each other,
Figure DEST_PATH_IMAGE045
the confidence of the z-th pixel point on the straight line.
Further, in order to ensure that the accuracy is improved, the method further comprises the step of correcting the confidence coefficient of the whole acquired straight line, and the method comprises the following steps:
1) Arbitrarily taking a certain line in the category
Figure 747921DEST_PATH_IMAGE005
Adjacent straight lines thereof are
Figure 587701DEST_PATH_IMAGE006
，
Figure 396257DEST_PATH_IMAGE007
；
2) Obtaining straight lines
Figure 688698DEST_PATH_IMAGE008
The upper pixel point, assumed to be the S point: (
Figure 545795DEST_PATH_IMAGE046
，
Figure DEST_PATH_IMAGE047
) And calculating the distance D:
Figure DEST_PATH_IMAGE049
then can obtain
Figure 928497DEST_PATH_IMAGE011
，
Figure 376796DEST_PATH_IMAGE012
Respectively representing the distance from the point S to two adjacent straight lines;
3) Calculating distance difference, wherein the smaller the difference, the greater the confidence should be, based on which, the relative confidence
Figure 422113DEST_PATH_IMAGE013
And (6) adjusting.
Figure 817322DEST_PATH_IMAGE050
For is to
Figure DEST_PATH_IMAGE051
Performing normalization processing, and setting threshold
Figure 694011DEST_PATH_IMAGE052
Confidence of the line
Figure DEST_PATH_IMAGE053
Is greater than
Figure 578791DEST_PATH_IMAGE054
If so, the straight line can be considered as a bonding line, otherwise, the straight line is not a bonding line.
Based on the bonding wire determined in the above, the specific process of the quality evaluation index of the bonding wire in this embodiment for the bonding wire is as follows:
obtaining the width U of each welding line area image on the thin plate, evaluating the production quality of the welding lines in the welding line area images, and obtaining the number of the same type of welding lines in each straight line group as F, wherein F is less than or equal to K; calculating the distance D between any two adjacent bonding wires, if F bonding wires exist, namely F-1D values exist, then the bonding wire quality evaluation PG of the bonding wire area image is as follows:
Figure DEST_PATH_IMAGE055
in the formula U represents the width of the strip,
Figure 783507DEST_PATH_IMAGE003
representing the average distance of all bond wires. The larger PG, the better the quality of the weld area.
The quality evaluation index of the medium bonding wire is calculated on the premise of judging whether the medium bonding wire is a bonding wire, so that the quality of the bonding wire under the process can be accurately evaluated, and the influence of other factors is avoided.
Step 4, extracting welding spot images in the welding spot gray level images, calculating the similarity between each welding spot image and the standard welding spot template image, and obtaining the similarity index of the welding spot gray level images; and electrifying the welded MiniLED sheet to obtain the change degree of the lamp beads.
The welding spot gray level image in this embodiment is an image after welding is completed, wherein the welding spot gray level image includes a lamp bead and a welding spot.
In this embodiment, detecting the welding spot in the welding spot gray image specifically includes: and (3) carrying out median filtering processing on the welded welding spot gray level image to reduce noise interference, then segmenting the welding spots by an otsu Dajin threshold value method, and processing each welding spot image on the assumption that P welding spots are obtained.
Carrying out template matching on the welding spot image and a standard welding spot template image to calculate similarity V; p welding points obtain P V, and the overall similarity is calculated
Figure 982407DEST_PATH_IMAGE056
：
Figure 385707DEST_PATH_IMAGE058
Wherein, the first and the second end of the pipe are connected with each other,
Figure DEST_PATH_IMAGE059
is as followspThe similarity of individual solder joints. Wherein the greater the similarity, the better the quality of the weld spot and the better the quality of the weld area.
The process of obtaining the change degree of the lamp bead is as follows:
and electrifying the welded thin plate to obtain the gray images of the surface of the thin plate before and after electrifying, differentiating the images, and when the images are differentiated, proving that the LED in the welding area is in normal operation, otherwise, indicating that the quality of the welding area does not meet the standard.
For the area where the lamp beads normally run, before and after the lamp beads are electrified, the image gray level changes greatly due to the fact that the lamp beads are lightened, and the change degree of the image gray level changes greatly as a production quality evaluation index py:
Figure DEST_PATH_IMAGE061
wherein the content of the first and second substances,
Figure 471081DEST_PATH_IMAGE019
is in a position before power-on
Figure 22148DEST_PATH_IMAGE020
The gray value of the lamp bead of (1),
Figure 759160DEST_PATH_IMAGE021
is at a position after being electrified
Figure 282545DEST_PATH_IMAGE020
The gray value of the rear lamp bead,
Figure 40285DEST_PATH_IMAGE062
is the number of lines of the lamp beads,
Figure 16332DEST_PATH_IMAGE023
the number of the rows of the lamp beads.
And 5, carrying out weighted summation on the matching degree, the welding wire quality evaluation index, the similar index and the change degree to obtain a comprehensive production quality index, and when the comprehensive production quality index is greater than a set threshold value, determining that the MiniLED sheet is qualified.
The comprehensive production quality indexes in the embodiment are as follows:
Figure 353772DEST_PATH_IMAGE064
wherein in the formula
Figure DEST_PATH_IMAGE065
，
Figure 997243DEST_PATH_IMAGE066
，
Figure DEST_PATH_IMAGE067
，
Figure 20825DEST_PATH_IMAGE068
Is a weight, wherein
Figure DEST_PATH_IMAGE069
The normalized average similarity of the nth weld area on the board to the standard weld area is characterized,
Figure 77643DEST_PATH_IMAGE070
a normalized quality assessment average of the bond wires within the bond area is characterized,
Figure DEST_PATH_IMAGE071
the normalized quality assessment of the solder joint is characterized,
Figure 953195DEST_PATH_IMAGE072
the normalized quality condition of the welded lamp beads is represented.
In the invention is provided with
Figure DEST_PATH_IMAGE073
，
Figure 451172DEST_PATH_IMAGE074
，
Figure DEST_PATH_IMAGE075
，
Figure 894923DEST_PATH_IMAGE068
=0.1, which can be modified according to specific requirements.
Four indexes are obtained for N welding areas
Figure 796627DEST_PATH_IMAGE069
，
Figure 679132DEST_PATH_IMAGE070
,
Figure 31616DEST_PATH_IMAGE076
，
Figure 911847DEST_PATH_IMAGE071
The four indexes are normalized, and the welding region py =0 which cannot normally operate has been described.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.

Claims (6)

1. A production quality detection method for full-automatic connection of MiniLED sheets is characterized by comprising the following steps:
acquiring an unwelded gray level image, a welding line gray level image and a welding point gray level image in real time;
performing edge detection on the unwelded gray image to obtain edge pixel points, and performing Hough circle detection on the edge pixel points to obtain the circle centers and corresponding radiuses of a plurality of circles; calculating the difference between the radius of each circle and the radius of the standard circle, and determining the matching degree of each circle and the standard circle according to the difference; meanwhile, determining a corresponding welding area according to the circle center and the radius of each circle and the welding rule;
the welding areas correspond to the welding line gray level images one by one, the corresponding welding area images in the welding line gray level images are determined, edge pixel points of the welding area images are extracted, hough line detection is carried out on the edge pixel points, and corresponding K lines are obtained; classifying all the straight lines to obtain straight line groups of different categories; calculating the difference between one pixel point and the adjacent pixel point on each straight line; taking the mean value of the differences of all the pixel points as the confidence coefficient of the corresponding straight line, and when the confidence coefficient is greater than a set threshold value, all the straight lines in the corresponding straight line group are bonding lines; calculating a welding wire quality evaluation index according to the number of welding wires in each straight line group and the width of the welding wire area;
extracting welding spot images in the welding spot gray level images, calculating the similarity between each welding spot image and the standard welding spot template image, and obtaining the similarity index of the welding spot gray level images; electrifying the welded MiniLED sheet to obtain the change degree of the lamp beads;
respectively carrying out normalization processing on the matching degree, the welding wire quality evaluation index, the similar index and the change degree, carrying out weighted summation on the normalized matching degree, the welding wire quality evaluation index, the similar index and the change degree to obtain a comprehensive production quality index, and when the comprehensive production quality index is greater than a set threshold value, determining that the MiniLED sheet is qualified;
the comprehensive production quality indexes are as follows:
Figure FDA0003759785010000011
wherein u in the formula 1 ，u 2 ，u 3 ，u 4 Is a weight, C n ' normalized matching degree of nth welding area and standard welding area, PG n ' is a normalized wire quality assessment indicator of the wire bond within the bond area,
Figure FDA0003759785010000012
and py' is a similar index of the normalized welding spot, and is the normalized change degree of the welded lamp bead.
2. The method for detecting the production quality of the MiniLED sheet in the full-automatic connection mode according to claim 1, wherein the surface images of the MiniLED sheet in different processes in the production process are collected in real time to obtain the surface images which are not welded, the surface images of the welding wires and the surface images of the welding points, and the surface images are subjected to gray processing to obtain corresponding gray images.
3. The method for detecting the production quality of the MiniLED sheet in the full-automatic line connection manner according to claim 1, wherein the difference obtaining method comprises the following steps: acquiring the length and the angle of each straight line; classifying all the straight lines based on the lengths and the angles to obtain straight line groups of different classes; determining the LBP value of each pixel point according to the number of the pixel points of each straight line in each straight line group and the corresponding gray value; obtaining the hue value of the pixel point of each straight line; and calculating the difference between one pixel point and the adjacent pixel point on the straight line based on the LBP value and the hue value of the pixel point.
4. The method for detecting the production quality of the full-automatic MiniLED sheet connection line of claim 1, wherein the wire bonding quality evaluation indexes are as follows:
Figure FDA0003759785010000021
wherein U represents the width of the welding zone,
Figure FDA0003759785010000022
representing the average distance between all bonding wires, F being the number of bonding wires in the straight line group, D f The distance between the f-th bonding wire and the f + 1-th adjacent bonding wire.
5. The method for detecting the production quality of the MiniLED thin plate in the full-automatic connection mode according to claim 1, further comprising the step of correcting the confidence coefficient:
arbitrarily take a certain line y in the category k ＝a k x+b k Adjacent straight lines thereof are y k+1 ＝a k+1 x+b k+1 ，
y k-1 ＝a k-1 x+b k-1 ；
Obtaining a straight line y k To adjacent straight lines y respectively k+1 、y k-1 Distance D of k+1 ，D k-1 ；
Calculating the difference between the two distances, and determining the confidence level according to the difference between the two distances
Figure FDA0003759785010000023
Adjusting to obtain a new confidence:
Figure FDA0003759785010000024
wherein the content of the first and second substances,
Figure FDA0003759785010000025
the confidence of the k-th line.
6. The method for detecting the production quality of the MiniLED thin plate full-automatic connection line of claim 1, wherein the variation degree is as follows:
Figure FDA0003759785010000026
wherein A is 1(i′，j′) Is the gray value A of the lamp bead with the position (i ', j') before electrification 2(i′，j′) The gray value of the lamp bead at the position (i ', j') after the lamp bead is electrified, M 'is the row number of the lamp bead, and N' is the column number of the lamp bead.
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