Material traceability management system in LED display module full-automatic production line

Abstract

This invention relates to the field of LED display module material traceability technology, and more particularly to a material traceability management system in a fully automated LED display module production line. The system includes: an optical feature mapping module to determine the optical feature tensor; a uniformity sensing module to determine the uniformity characterization value based on the complement of the ratio of the number of abnormal boundaries to the total number of adjacent position pairs; a local reconstruction module to generate an abnormal boundary distribution map based on the uniformity characterization value and determine the local correction method; a microscopic verification module to determine the brightness maintenance qualification of a single LED bead based on the measured light decay value and the standard light decay value; a data compensation module to determine the current compensation value for the LED bead based on the light decay deviation value; and a data correction module to determine the qualification of the current compensation based on the secondary light decay value and the standard light decay value, thereby correcting the BIN-level division threshold of the beam splitter. This invention solves the optical inconsistency problem caused by cross-batch mixing.

Description

Technical Field

[0001] This invention relates to the field of LED display module material traceability technology, and in particular to a material traceability management system in a fully automated LED display module production line. Background Technology

[0002] An LED display module is a light-emitting unit composed of a large number of LED chips soldered onto a PCB board using surface mount technology. During the manufacturing process of LED displays, due to inherent process fluctuations in LED chip production, LED chips of the same model will inevitably exhibit variations in photoelectric parameters between different production batches, primarily manifested in differences in brightness, dominant wavelength, and forward voltage. To control these variations, the industry standard practice is to classify LED chips into different grades according to certain parameter ranges during the chip sorting stage, known as BIN grades.

[0003] In fully automated production lines for LED display modules, material traceability and management are crucial for ensuring consistent product quality. Existing technologies typically address material batch issues in the following ways: A common practice is to require that the same display module must use LED beads of the same BIN grade and the same production batch. While this method can maximize the optical consistency within the module, it places extremely high demands on material inventory. It is easy for a shortage of a single batch of materials to cause the entire production line to stop, and a large amount of inventory materials from different batches cannot be effectively utilized, resulting in resource waste.

[0004] To alleviate inventory pressure and improve material utilization, some manufacturers have tried to adopt a mixed BIN assembly strategy, which allows the use of LED beads of different BIN grades in the same module. However, if the mixed assembly strategy is not appropriate, the differences in brightness or color temperature of LED beads of different BIN grades will form visible blocky areas on the display surface, which is commonly known in the industry as the "yin-yang face" or "screen distortion" phenomenon, which seriously affects the display quality.

[0005] Chinese Patent Publication No. CN104931005A discloses a method for detecting the uniformity of multi-bin LED light panels. This patent quantifies and evaluates the uniformity of the current mixed assembly scheme by calculating the physical distribution area of ​​each bin-level LED bead on the light panel. If a bin-level LED bead is too concentrated in a certain area, resulting in an excessively large area occupied by it, the mixed assembly scheme is judged to potentially produce visual unevenness. This method can detect and evaluate the uniformity of the light panel after panel assembly or after mounting.

[0006] However, existing technologies still have the following shortcomings: First, the existing technology is a post-event inspection, which means that uniformity can only be evaluated after the LED beads have been installed and formed a physical distribution. If the evaluation result is not up to standard, the installed module can only be treated as scrap or undergo expensive rework and repair, resulting in material waste and reduced production efficiency. Second, existing evaluation methods mainly focus on the static physical distribution of LED beads at the BIN level, that is, which LED beads in which positions belong to which level. However, what actually affects the display effect is not only the initial brightness / color temperature value, but also the difference in the decay characteristics of different batches of LED beads under long-term operation or temperature changes. Even if two modules are initially uniform, if the light decay characteristics of their LED beads are different, there may still be obvious differences in brightness or color temperature after a period of use. Third, existing testing methods usually focus on the uniformity within a single module. However, large LED displays are spliced ​​together from many modules. Even if each module is uniform, if adjacent modules use materials from different batches with significantly different attenuation characteristics, color blocks that can be seen with the naked eye may still form at the splicing boundary between modules, affecting the overall display effect. Summary of the Invention

[0007] To address this issue, the present invention provides a material traceability management system for a fully automated production line of LED display modules, in order to overcome the problem of optical inconsistencies caused by cross-batch mixing in the prior art.

[0008] To achieve the above objectives, the present invention provides a material traceability management system for a fully automated production line of LED display modules, comprising: The optical feature mapping module is used to determine the optical feature tensor of the target module based on the identification information and optical feature data of the batch of materials to be mixed, combined with the preset physical distribution rules. The uniformity perception module is used to determine the number of abnormal boundaries based on the total number of optical feature differences between adjacent pairs of optical feature tensors that are greater than a preset perception threshold, and to determine the uniformity characterization value of the target module based on the number of abnormal boundaries. The local reconstruction module, connected to the uniformity perception module, is used to generate an abnormal boundary distribution map based on all adjacent positions marked as abnormal boundaries when the uniformity characterization value is less than the preset uniformity, so as to determine the local correction method of the preset physical distribution rule based on the type of abnormal region. The microscopic verification module is used to determine the qualification of brightness maintenance of a single LED bead based on the comparison between the measured light decay value and the standard light decay value of a single LED bead within a preset time. The data compensation module is used to determine the current compensation value for a single LED based on the light decay deviation value between the measured light decay value and the standard light decay value. The data correction module is used to determine the qualification of current compensation based on the comparison between the redefined secondary optical attenuation value and the standard optical attenuation value, so as to correct the BIN level division threshold of the beam splitter.

[0009] Furthermore, the optical feature tensor includes a luminance matrix and a chromaticity matrix; The preset physical distribution rules are the spatial arrangement strategies for different batches of materials on the target module.

[0010] Furthermore, the optical feature difference is determined based on the absolute value of the difference between the optical feature values ​​between the positions of two adjacent LED beads; The optical characteristic values ​​are determined based on the luminance and chromaticity values ​​of a single LED bead.

[0011] Furthermore, the uniformity characterization value is determined based on the complement of the ratio of the number of abnormal boundaries to the total number of adjacent position pairs.

[0012] Furthermore, the types of abnormal regions include periodic anomalies, probability imbalance anomalies, and boundary mutation anomalies.

[0013] Furthermore, the local correction method includes adjusting the alternation cycle of different batches of materials within the abnormal area; Alternatively, adjust the random distribution probability weights of different batches of materials within the abnormal area; Alternatively, adjust the regional division boundaries of different batches of materials within the abnormal area.

[0014] Furthermore, the microscopic verification module determines that the brightness maintenance of a single LED bead is unqualified based on the measured light decay value being greater than the standard light decay value. The measured light decay value of a single LED bead within the preset time period is determined based on the measured light decay curve; The measured light decay curve is a function of the LED bead brightness decaying exponentially with time.

[0015] Furthermore, the optical attenuation deviation value is determined based on the deviation between the measured optical attenuation value and the standard optical attenuation value; Based on the comparison between the optical attenuation deviation value and the standard optical attenuation value, the corresponding current compensation value is determined; The optical attenuation deviation value is positively correlated with the current compensation value.

[0016] Furthermore, the secondary optical decay value is determined by compensating and correcting the measured optical decay value based on the current compensation value; Based on the fact that the secondary light decay value is greater than the standard light decay value, it is determined that the brightness retention of a single LED bead is still unqualified.

[0017] Furthermore, the BIN-level classification threshold is adjusted based on the comparison results between the defect rate difference and the preset defect rate difference; The difference in the defect rate is positively correlated with the correction range of the BIN level classification threshold; The defect rate difference is determined based on the deviation between the defect rate and the preset defect rate.

[0018] Compared with the prior art, the beneficial effects of the present invention are that by combining the optical feature data of the batch of materials to be mixed with the preset physical distribution rules through the optical feature mapping module, an optical feature tensor that retains the spatial adjacency relationship is pre-constructed in the digital space to realize virtual simulation before mounting; at the same time, the present invention calculates the optical feature difference between each horizontal adjacent position pair and the vertical adjacent position pair on the target module, counts the number of abnormal boundaries exceeding the preset perception threshold, and uses the complement of the ratio of the number of abnormal boundaries to the total number of adjacent position pairs as the uniformity characterization value, which directly quantifies the degree of visual jump in the adjacent area that the human eye is most sensitive to. This is more accurate in reflecting the phenomenon of uneven display or screen distortion in the actual display effect than simply counting the distribution area of ​​each BIN-level LED bead.

[0019] Furthermore, when the uniformity characterization value is less than the preset uniformity, the local reconstruction module further extracts features from the abnormal boundary distribution map, which can accurately identify three different types of problems: periodic anomalies, probability imbalance anomalies, and boundary mutation anomalies. It then adopts differentiated correction strategies, such as adjusting the alternating arrangement period, adjusting the random distribution probability weight, or adjusting the region division boundary, so that the optimization of the mixed assembly scheme no longer relies on manual experience and trial and error, but can be predicted, diagnosed, and corrected before assembly. This fundamentally avoids the generation of waste products caused by improper mixing, and significantly reduces material waste and production costs.

[0020] Furthermore, this invention performs microscopic light decay verification on individual LED beads. By comparing the measured light decay curve with the standard light decay value, it accurately identifies LED beads that fail to maintain adequate brightness. Based on the comparison result between the light decay deviation value and the preset light decay deviation value, the current compensation value is adjusted in stages. This staged compensation mechanism achieves the best balance between compensation effect and LED bead lifespan, effectively repairing compensable minor and moderate defects while avoiding damage to the LED bead lifespan due to overcompensation.

[0021] Furthermore, for severely defective LED beads that still fail to meet standards after current compensation, this invention statistically defines them as the defect rate of that batch, calculates the defect rate difference between the defect rate and the preset defect rate, and when the defect rate difference is greater than the preset defect rate difference, raises the lower limit of the brightness BIN level with a larger second correction coefficient; when the defect rate difference is less than or equal to the preset defect rate difference, fine-tuning is performed with a smaller first correction coefficient. The defect rate difference and the correction magnitude are positively correlated, realizing adaptive optimization of the sorting standard, transforming defects that cannot be repaired at the micro level into quality requirements for the material source at the macro level, forming a closed-loop quality control system covering the entire chain from mixed distribution to individual quality and then to the source material; fundamentally solving the optical inconsistency problem caused by cross-batch mixing, while avoiding a significant drop in yield and material waste caused by excessively raising the sorting standard. Attached Figure Description

[0022] Figure 1 This is a logic block diagram of the material traceability management system in the fully automated production line of LED display modules according to an embodiment of the present invention; Figure 2 This is a logic block diagram illustrating the determination of uniformity as described in an embodiment of the present invention. Figure 3 This is a logic block diagram illustrating the determination of the qualification of brightness retention of a single LED bead according to an embodiment of the present invention; Figure 4 This is a logic block diagram for determining the qualification of current compensation according to an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0024] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0025] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0026] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0027] Please see Figure 1 The diagram shown is a logical block diagram of the material traceability management system in the fully automated production line of the LED display module described in this invention.

[0028] The material traceability management system in the fully automated production line of LED display modules described in this embodiment of the invention includes: The optical feature mapping module is used to determine the optical feature tensor of the target module based on the identification information and optical feature data of the batch of materials to be mixed, combined with the preset physical distribution rules. The uniformity perception module is connected to the optical feature mapping module. It is used to determine the number of abnormal boundaries based on the total number of optical feature differences between adjacent pairs in the optical feature tensor that are greater than a preset perception threshold, and to determine the uniformity characterization value of the target module based on the number of abnormal boundaries. The local reconstruction module, connected to the uniformity perception module, is used to generate an abnormal boundary distribution map based on all adjacent positions marked as abnormal boundaries when the uniformity characterization value is less than the preset uniformity, so as to determine the local correction method of the preset physical distribution rule based on the type of abnormal region. The microscopic verification module is connected to the uniformity sensing module. It is used to determine the qualification of brightness maintenance of a single LED bead based on the comparison result of the measured light decay value of a single LED bead with the standard light decay value within a preset time. The data compensation module, connected to the microscopic verification module, is used to determine the current compensation value for a single LED bead based on the light decay deviation value between the measured light decay value and the standard light decay value. The data correction module, connected to the data compensation module, is used to determine the qualification of current compensation based on the comparison result of the re-determined secondary optical attenuation value and the standard optical attenuation value, so as to correct the BIN level division threshold of the beam splitter.

[0029] In this embodiment of the invention, the optical feature mapping module acquires the identification information and optical feature data of the batch of materials to be mixed. The identification information includes batch number, BIN-level label, production date and supplier information; the optical feature data includes brightness value, chromaticity value and preset light decay time curve.

[0030] The optical feature mapping module also simultaneously acquires preset physical distribution rules, which are spatial arrangement strategies for different batches of materials on the target module, including: Alternating distribution strategy: Different batches of materials are arranged in alternating spatial arrangements according to a fixed period, such as 2×2 or 4×4. In implementation, a 2×2 alternating distribution is preferred, that is, in each 2×2 LED matrix, the upper left and lower right positions are occupied by batch A, and the upper right and lower left positions are occupied by batch B. This distribution method is suitable for scenarios where there are large differences in optical characteristics between different batches of materials and it is necessary to maximize spatial dispersion to avoid local color block aggregation. Alternatively, a random weighted distribution strategy can be used: different batches of materials are randomly allocated within a local area according to a preset probability weight. In practice, a 4×4 random weighted distribution is preferred, which means dividing the target module into multiple 4×4 LED bead sub-matrices. Within each 4×4 sub-matrix, each batch of materials is randomly allocated to each LED bead position according to a preset probability weight. If the preset probability weight of batch A and batch B is set to 3:1, then in each of the 16 LED bead positions in each 4×4 sub-matrix, each position is allocated to batch A with a 75% probability and batch B with a 25% probability, so that the expected number of LED beads in batch A and batch B in the entire sub-matrix are 12 and 4 respectively. This distribution method is suitable for scenarios where the optical characteristics of different batches of materials are relatively similar and strict periodic alternation is not required. It can simplify the material supply control logic while ensuring overall uniformity. Alternatively, a regional partitioning strategy can be adopted: the display area of ​​the target module is divided into several continuous rectangular sub-areas according to spatial location. All LED beads in each sub-area use the same batch of materials, while different batches of materials are used in different sub-areas. In implementation, for a 1920×1080 module, it can be divided vertically into two areas, with the upper half using batch A and the lower half using batch B; or it can be divided horizontally into three areas: left, center, and right. This distribution method is suitable for scenarios where the visual differences between different batches of materials are acceptable, or for quickly verifying the actual display effect comparison of different materials on the module.

[0031] Specifically, the optical feature tensor includes a luminance matrix and a chromaticity matrix; the optical feature tensor is used to characterize the optical feature data of each virtual LED bead on the module to be produced and the spatial positional relationship of each virtual LED bead.

[0032] In this embodiment of the invention, the luminance matrix is ​​a two-dimensional data structure extracted from the optical feature tensor to characterize the luminance value distribution of each virtual LED bead on the module to be produced, and the chromaticity matrix is ​​a two-dimensional data structure extracted from the optical feature tensor to characterize the chromaticity value distribution of each virtual LED bead on the module to be produced.

[0033] In this embodiment of the invention, the optical feature mapping module generates an optical feature tensor T. For a module with a size of 1920×1080, the dimension of T is [1920×1080×2], where the first dimension is the row index, the second dimension is the column index, and the third dimension includes the luminance channel and the chrominance channel. Each element in the optical feature tensor T is represented by t[i][j][k], where k=0 represents the luminance value and k=1 represents the chrominance value. The row and column indices preserve the horizontal and vertical adjacency relationships between LED beads.

[0034] Specifically, the optical characteristic difference is determined based on the absolute value of the difference between the optical characteristic values ​​of two adjacent LED beads; wherein, the optical characteristic value is determined based on the brightness and chromaticity values ​​of a single LED bead, and is used to comprehensively characterize the brightness and chromaticity characteristics of a single LED bead. In this embodiment of the invention, the magnitude of the optical characteristic value reflects the comprehensive performance of a single LED bead in terms of brightness and chromaticity.

[0035] Specifically, by weighted summing the relative brightness and chromaticity values ​​of individual LED beads, we obtain: F = f1 × L + f2 × C (1); Wherein, F is the optical characteristic value; L is the normalized relative brightness value, which is determined based on the ratio of the measured brightness of the LED bead to the rated maximum brightness of the LED bead, and the value range is 0-1; C is the chromaticity value, which is a dimensionless quantity, and the value range is 0-1; f1 is the weighting coefficient of brightness, f2 is the weighting coefficient of chromaticity, and f1+f2=1.

[0036] In this embodiment of the invention, f1 is preferably 0.7 and f2 is preferably 0.3. Based on visual physiology, the human visual system is more sensitive to changes in brightness than to changes in chromaticity. The weight of the brightness contrast sensitivity function is about 2 to 3 times that of chromaticity. Taking 0.7 can more accurately simulate human eye perception. The chromaticity weight is complementary to the brightness weight and has a secondary position in human eye chromaticity perception. In order to avoid over-amplifying the influence of chromaticity differences, the chromaticity weight is taken as 0.3.

[0037] In this embodiment of the invention, for the horizontal adjacent position pairs (i,j) and (i,j+1) on the target module, the horizontal optical feature difference ΔFh=|Fij-Fi,j+1| (2); For the vertically adjacent position pairs (i,j) and (i+1,j) on the target module, calculate the vertical optical feature difference ΔFv=∣Fij-Fi+1,j∣ (3; The uniformity sensing module compares each horizontal optical feature difference with a preset sensing threshold. If the horizontal optical feature difference is greater than the preset sensing threshold, the horizontal adjacent position pair is marked as an abnormal boundary. Similarly, it compares each vertical optical feature difference with the preset sensing threshold. If the vertical optical feature difference is greater than the preset sensing threshold, the vertical adjacent position pair is marked as an abnormal boundary. The total number of marked abnormal boundaries is then calculated.

[0038] Meanwhile, the uniformity sensing module also calculates the total number of adjacent position pairs. In this embodiment of the invention, for a 1920×1080 module: the number of horizontal adjacent position pairs = 1920×(1080-1) = 2071680, the number of vertical adjacent position pairs = (1920-1)×1080 = 2072520, and the total number of adjacent position pairs = 4144200.

[0039] In this embodiment of the invention, based on practical experience, when the brightness difference is less than or equal to 5%, it is difficult for the human eye to perceive, and when it exceeds 5%, it may cause visual discomfort. In implementation, the preset perception threshold is preferably 5%.

[0040] Specifically, the uniformity characterization value is determined based on the complement of the ratio of the number of outlier boundaries to the total number of adjacent position pairs, and the formula for calculating the uniformity characterization value U is as follows: U=1-N / Nt (4; Where N is the number of abnormal boundaries and Nt is the total number of adjacent position pairs.

[0041] This invention quantifies the degree of visual abruptness between adjacent positions by calculating the optical feature difference between each pair of horizontally adjacent LED beads and each pair of vertically adjacent LED beads on the target module, that is, the absolute value of the difference between the weighted values ​​of brightness and chromaticity. When the difference between a pair of adjacent LED beads exceeds a preset perception threshold, the boundary is marked as an abnormal boundary, and the visual uniformity of the entire module is evaluated by the proportion of the number of abnormal boundaries to the total number of adjacent position pairs. That is, the lower the proportion, the higher the uniformity. Thus, it is possible to predict whether the mixed assembly scheme will produce a visually perceptible color block or screen distortion before the chip is mounted.

[0042] Please see Figure 2 As shown, it is a logic block diagram for determining whether the uniformity is qualified according to an embodiment of the present invention.

[0043] Specifically, the uniformity characterization value is compared with a preset uniformity. If the uniformity characterization value is less than the preset uniformity, the uniformity is determined to be unqualified. If the uniformity characterization value is greater than or equal to the preset uniformity, then the uniformity is determined to be qualified.

[0044] In this embodiment of the invention, the closer U is to 1, the better the visual uniformity of the module; the lower U is, the more visual jump points there are in the module.

[0045] In this embodiment of the invention, based on historical data, an LED display screen with a uniformity of ≥90% is considered a qualified product, and an LED display screen with a uniformity of ≥95% is considered a superior product. Therefore, in the implementation of this invention, the preset uniformity is preferably 90%.

[0046] Specifically, the local reconstruction module generates an anomaly boundary distribution map based on all adjacent position pairs marked as anomaly boundaries. The anomaly boundary distribution map is a two-dimensional integer matrix M of size H×W, where H is the number of rows of the target module and W is the number of columns of the target module. Each element m[h][w] in the two-dimensional integer matrix represents the degree (i.e., the number of nodes connected by edges) of the LED bead at that position, where h is the row index and w is the column index. The degree value is equal to the number of anomaly boundaries associated with that LED bead. This matrix intuitively reflects the spatial clustering degree of anomaly boundaries.

[0047] The local reconstruction module extracts features from the abnormal boundary distribution map to determine the type of abnormal region. The types of abnormal regions include periodic anomalies, probability imbalance anomalies, and boundary mutation anomalies.

[0048] Among them, periodic anomalies are identified by performing spatial spectrum analysis on the anomaly boundary distribution map to extract the repetition period of the anomaly boundary. If the repetition period is inconsistent with the alternating arrangement period defined in the preset physical distribution rules, that is, the difference between the repetition period and the preset alternating arrangement period is greater than the preset period deviation threshold, or the repetition period is an integer multiple of the preset alternating arrangement period, then it is determined to be a periodic anomaly. The periodic anomaly indicates that the current alternating arrangement strategy has failed to effectively disperse different batches of materials. The local correction method is to adjust the alternating arrangement period of different batches of materials in the anomaly area. The probability imbalance anomaly is determined by comparing the actual proportion of each batch of materials in the statistical anomaly area with the target proportion defined in the preset physical distribution rules. If the deviation between the actual proportion and the target proportion is greater than the preset proportion deviation threshold, it is determined to be a probability imbalance anomaly. The probability imbalance anomaly indicates that a certain batch of materials is excessively concentrated in a local area. The local correction method is to adjust the random distribution probability weight of different batches of materials in the anomaly area. Boundary mutation anomaly is determined by spatially overlaying the abnormal boundary distribution map with the region division map in the preset physical distribution rules. That is, the abnormal boundary distribution map and the preset region division map are compared point by point in the same coordinate system, and the proportion of abnormal boundaries falling on the region boundary lines is used as the spatial overlap. If the spatial overlap is greater than the preset overlap threshold, it is determined to be a boundary mutation anomaly. The boundary mutation anomaly indicates that there is a significant visual jump at the boundary of the material partition. The local correction method is to adjust the region division boundary of different batches of materials in the abnormal area.

[0049] In this embodiment of the invention, the preset alternating arrangement period refers to the spatial step size in which different batches of materials appear alternately on the module as defined in the physical distribution rules. For example, a value of 2 indicates a 2×2 checkerboard alternating arrangement. The value of this parameter is mainly based on the feeding switching capability of the pick-and-place machine and the degree of difference in the BIN level of the materials: when the optical characteristics of different batches of materials are significantly different, a smaller alternating period, such as 2, should be used to ensure thorough mixing; when the difference is small, a larger alternating period, such as 4 or 8, can be used to improve production efficiency. In this embodiment, the preset alternating arrangement period is preferably 2.

[0050] In this embodiment of the invention, a preset period deviation threshold is used to determine whether the deviation between the repetition period of the actual abnormal boundary and the preset alternating period is within an acceptable range. Since the period extracted by spatial spectrum analysis may fluctuate slightly due to individual noise or local anomalies, the preset period deviation threshold provides a tolerance space. When the value is 0, strict matching is required, and when the value is 1, an error of one step size is allowed. In this embodiment of the invention, the preset period deviation threshold is preferably 1, that is, when the difference between the actual period and the preset period is less than or equal to 1, it is still considered normal, and when it is greater than 1, it is determined to be a periodic anomaly.

[0051] In this embodiment of the invention, the target percentage is mainly determined based on the inventory ratio of the current batch of materials to be mixed and the production strategy requirements. For example, if the inventory ratio of batch A to batch B is 3:7, the target percentage can be set to 30% and 70% respectively. If the display effect is taken into consideration, it can also be set to a balanced ratio of 50% each. In this embodiment, the target percentage is dynamically determined according to the inventory ratio of the current batch of mixed materials.

[0052] In this embodiment of the invention, the value of the preset proportion deviation threshold is based on the human eye's ability to perceive differences in large areas of color blocks. Studies have shown that when the difference in the area of ​​a local area exceeds 5%, the human eye can easily perceive a blocky feeling or a two-tone effect. In this embodiment of the invention, the preset proportion deviation threshold is preferably 5%, that is, when the absolute deviation between the actual proportion and the target proportion is greater than 5%, it is judged as a probability imbalance anomaly.

[0053] In this embodiment of the invention, the preset overlap threshold is determined based on the following: if more than 80% of the positions on a region boundary line are simultaneously marked as abnormal boundaries, then the boundary line itself is the source of visual abrupt changes and needs to be eliminated by adjusting the boundary position. In this embodiment of the invention, the preset overlap threshold is preferably 80%, that is, when the spatial overlap is greater than 80%, it is determined to be an abnormal boundary abrupt change.

[0054] Specifically, the measured light decay value of a single LED bead within the preset time period is determined based on the measured light decay curve; wherein, the measured light decay curve is a function of the LED bead brightness decaying exponentially with time.

[0055] The formula for calculating the measured light decay curve L(t) is as follows: L(t) = L0 × e -αt (5); (6); (7); Where L0 is the initial brightness value, e is the natural constant, t is the cumulative lighting time of the LED bead, α is the decay constant, Lp is the brightness value at the end of the pulse, te is the equivalent aging time, k is the dimensionless empirical proportionality coefficient, E is the pulse energy, and P is the rated power of the LED bead.

[0056] In this embodiment of the invention, k is preferably 1.0 × 10 -6 -1.0×10 -4 This value was determined through experimental calibration, so that the equivalent aging time can accurately reflect the accelerated aging effect of LED beads under pulse stress.

[0057] Specifically, this invention uses the boundary gradient method instead of the traditional exclusive area method. This is based on the lateral inhibition effect of human vision. The human eye is extremely sensitive to brightness jumps between adjacent areas, but has a weaker perception of large-area gradual changes. Therefore, by statistically analyzing the complement of the ratio of the number of abnormal boundaries to the total number of adjacent positions, the degree of yin-yang face perceived by the human eye can be more accurately quantified.

[0058] Please see Figure 3 As shown, it is a logic block diagram for determining the qualification of brightness retention of a single LED bead according to an embodiment of the present invention.

[0059] Specifically, the pass rate of brightness maintenance of a single LED bead is determined based on the comparison between the measured light decay value and the standard light decay value within a preset time. Based on the fact that the measured light decay value is less than or equal to the standard light decay value, it is determined that the brightness of the individual LED bead remains qualified. Based on the fact that the measured light decay value is greater than the standard light decay value, it is determined that the brightness of a single LED bead is unqualified.

[0060] In this embodiment of the invention, the standard light decay value is preferably 85% of the initial brightness value, so as to ensure that the standard can both screen out inferior products and avoid excessively blocking good products.

[0061] Specifically, in response to the failure of the brightness of the individual LED bead to meet the standard, a light decay deviation value is determined based on the deviation between the measured light decay value and the standard light decay value; Based on the fact that the light decay deviation value is less than or equal to the first preset light decay deviation value, a first current compensation value for the LED lamp bead is determined. Based on the fact that the light decay deviation value is greater than the first preset light decay deviation value and less than or equal to the second preset light decay deviation value, a second current compensation value for the LED lamp bead is determined. Based on the fact that the light decay deviation value is greater than the second preset light decay deviation value, a third current compensation value for the LED lamp bead is determined. Wherein, the first preset light attenuation deviation value is less than the second preset light attenuation deviation value, and the first current compensation value is less than the second current compensation value and less than the third current compensation value.

[0062] In this embodiment of the invention, the first preset light decay deviation value is preferably 3%, and the second preset light decay deviation value is preferably 8%. The basis for these values ​​is as follows: by conducting aging tests on approximately 10,000 LED beads from the same batch and across batches, and statistically analyzing their light decay distribution after a preset lighting time, it was found that LED beads with a light decay deviation within 3% accounted for approximately 71%. After slight compensation, the pass rate of these LED beads can reach over 96%, which is a minor defect that can be efficiently repaired. LED beads with a light decay deviation between 3% and 8% accounted for approximately 25%. After moderate compensation, the pass rate of these LED beads is approximately 85% to 94%, which is a moderate defect that can be repaired. However, LED beads with a light decay deviation exceeding 8% accounted for only 4%. Even with a significant current compensation, the pass rate after compensation is still less than 60%, and excessive compensation will significantly accelerate the light decay of LED beads and shorten their service life. Therefore, 8% is used as the dividing point for abandoning compensation and instead adjusting the BIN level threshold.

[0063] In this embodiment of the invention, based on the current compensation value and combined with the current-luminance response coefficient, the brightness enhancement after compensation is calculated. This brightness enhancement is then added to the measured light decay value to determine the secondary light decay value after compensation. The formula for calculating the secondary light decay value is as follows: (8); (9); in, This is the second light decay value. This is the measured light attenuation value. Brightness increase η represents the initial brightness of the LED chip under rated current, and η is the current-brightness response coefficient. This is the current compensation value. This is the rated current.

[0064] In this embodiment of the invention, the value of η is determined according to the model and specifications of the LED beads, and is preferably 100-500 cd / m²·A. -1 .

[0065] Please see Figure 4 As shown, it is a logic block diagram for determining the qualification of current compensation according to an embodiment of the present invention.

[0066] Specifically, the compensated secondary light decay value is compared with the standard light decay value. If the compensated secondary light decay value is less than or equal to the standard light decay value, the compensation is deemed qualified, and the current compensation value is associated with the corresponding LED bead. If the compensated secondary light decay value is greater than the standard light decay value, the brightness of a single LED bead is deemed unqualified, so as to determine the defect rate of a single batch of LED beads.

[0067] Specifically, in response to the fact that the brightness of the individual LED lamp bead is still unqualified, the BIN level division threshold of the beam splitter is adjusted based on the comparison result of the compensation deviation value between the secondary light decay value and the standard light decay value and the preset light decay deviation value. Based on the fact that the compensation deviation value is less than or equal to the preset light decay deviation value, the lower limit for increasing the brightness BIN level with the first adjustment coefficient is determined. Based on the fact that the compensation deviation value is greater than the preset light decay deviation value, the lower limit of the admission for increasing the brightness BIN level with the second adjustment coefficient is determined. The first adjustment coefficient is smaller than the second adjustment coefficient.

[0068] In this embodiment of the invention, the magnitude of the compensation deviation value directly reflects the severity of the defects of the uncompensable LED beads. When the compensation deviation value is less than or equal to the preset light decay deviation value, the defect is relatively minor. A smaller first adjustment coefficient (preferably 3%) is used to moderately increase the lower limit of the brightness BIN level to gently intercept edge defective LED beads and avoid excessive impact on the yield. When the compensation deviation value is greater than the preset light decay deviation value, the defect is severe and cannot be repaired. This indicates that the existing BIN level threshold can no longer effectively identify this type of inferior LED beads. A larger second adjustment coefficient (preferably 8%) must be used to significantly increase the lower limit of the entry, forcibly intercepting severely defective LED beads at the beam splitting and tape-making stage, and ensuring the quality of subsequent batches of materials from the source.

[0069] In this embodiment of the invention, the preferred value of the adjustment coefficient is based on the statistical analysis of the light decay distribution of uncompensable LED beads and the analysis of the compensation effect. The first adjustment coefficient of 3% can make the interception rate of edge defect LED beads reach 60% to 70%, and the yield loss is controlled within 1% to 2%. The second adjustment coefficient of 8% can make the interception rate of severely defective LED beads reach more than 90%. Although it causes a yield loss of 5% to 8%, it can significantly improve the long-term consistency and reliability of the product.

[0070] Specifically, in response to the fact that the brightness of the individual LED bead is still unqualified, the number of uncompensable LED beads in the same batch of materials is counted, and the defect rate of the batch is calculated; the BIN level classification threshold is adjusted based on the difference between the defect rate and the preset defect rate. Specifically, the defect rate difference is determined based on the deviation between the defect rate and the preset defect rate; Based on the fact that the defect rate difference is less than or equal to the preset defect rate difference, the BIN level division threshold is determined to be corrected by the first correction coefficient. Based on the fact that the defect rate difference is greater than the preset defect rate difference, the BIN level classification threshold is determined to be corrected by the second correction coefficient; Wherein, the first correction coefficient is smaller than the second correction coefficient.

[0071] In this embodiment of the invention, the preset defect rate difference is preferably 1%. The basis for the preferred value is based on historical data regression analysis. For every 5% increase in the BIN level threshold, the defect rate decreases by an average of 0.8% to 1.2%; for every 10% increase, the defect rate decreases by an average of 1.5% to 2.5%.

[0072] In this embodiment of the invention, the magnitude of the defect rate difference directly reflects the degree of deviation between the BIN-level classification threshold and the actual material quality. When the deviation is small, i.e., the defect rate difference is ≤1%, a small first correction coefficient (preferably 0.05) is used to fine-tune the BIN-level classification threshold to avoid excessive interception of good products. When the deviation is large, i.e., the defect rate difference is >1%, it indicates that the existing BIN-level classification threshold has seriously deviated from the actual material quality, and a larger second correction coefficient (preferably 0.10) must be used for forced correction to quickly improve the access standard and intercept defective LED beads from the source.

[0073] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0074] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A management system for material traceability in a full-automatic production line of LED display modules, characterized in that, include: The optical feature mapping module is used to determine the optical feature tensor of the target module based on the identification information and optical feature data of the batch of materials to be mixed, combined with the preset physical distribution rules. The uniformity perception module is used to determine the number of abnormal boundaries based on the total number of optical feature differences between adjacent pairs of optical feature tensors that are greater than a preset perception threshold, and to determine the uniformity characterization value of the target module based on the number of abnormal boundaries. The local reconstruction module, connected to the uniformity perception module, is used to generate an abnormal boundary distribution map based on all adjacent positions marked as abnormal boundaries when the uniformity characterization value is less than the preset uniformity, so as to determine the local correction method of the preset physical distribution rule based on the type of abnormal region. The microscopic verification module is used to determine the qualification of brightness maintenance of a single LED bead based on the comparison between the measured light decay value and the standard light decay value of a single LED bead within a preset time. The data compensation module is used to determine the current compensation value for a single LED based on the light decay deviation value between the measured light decay value and the standard light decay value. The data correction module is used to determine the qualification of current compensation based on the comparison between the re-determined secondary optical attenuation value and the standard optical attenuation value, so as to correct the BIN level division threshold of the beam splitter. The uniformity characterization value is determined based on the complement of the ratio of the number of outlier boundaries to the total number of adjacent position pairs; The types of abnormal regions include periodic anomalies, probability imbalance anomalies, and boundary mutation anomalies. The local correction method includes adjusting the alternation cycle of different batches of materials within the abnormal area; Alternatively, adjust the random distribution probability weights of different batches of materials within the abnormal area; Alternatively, adjust the regional division boundaries of different batches of materials within the abnormal area; The BIN-level classification threshold is adjusted based on the comparison results between the defect rate difference and the preset defect rate difference; The difference in the defect rate is positively correlated with the correction range of the BIN level classification threshold; The defect rate difference is determined based on the deviation between the defect rate and the preset defect rate. 2.The management system of material traceability in the full-automatic production line of LED display module according to claim 1, characterized in that, The optical feature tensor includes a luminance matrix and a chrominance matrix; The preset physical distribution rules are the spatial arrangement strategies for different batches of materials on the target module. 3.The management system of material traceability in the full-automatic production line of LED display module according to claim 1, characterized in that, The optical feature difference is determined based on the absolute value of the difference between the optical feature values ​​between the positions of two adjacent LED beads; The optical characteristic values ​​are determined based on the luminance and chromaticity values ​​of a single LED bead. 4.The management system of material traceability in the full-automatic production line of LED display module according to claim 1, characterized in that, The microscopic verification module determines that the brightness of a single LED bead is unqualified based on the measured light decay value being greater than the standard light decay value. The measured light decay value of a single LED bead within the preset time period is determined based on the measured light decay curve; The measured light decay curve is a function of the LED bead brightness decaying exponentially with time.

5. The material traceability management system in the fully automated production line of LED display modules according to claim 1, characterized in that, The optical decay deviation value is determined based on the deviation between the measured optical decay value and the standard optical decay value; Based on the comparison between the optical attenuation deviation value and the standard optical attenuation value, the corresponding current compensation value is determined; The optical attenuation deviation value is positively correlated with the current compensation value.

6. The material traceability management system in the fully automated production line of LED display modules according to claim 5, characterized in that, The secondary optical decay value is determined by compensating and correcting the measured optical decay value based on the current compensation value. Based on the fact that the secondary light decay value is greater than the standard light decay value, it is determined that the brightness retention of a single LED bead is still unqualified.

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