Micro-led display pixel array brightness consistency online correction system based on optical detection

Abstract

The present application relates to the technical field of LED brightness chromaticity adjustment, and particularly relates to a Micro-LED display pixel array brightness consistency online correction system based on optical detection, which expands the detection dimension from steady-state amplitude to transient time domain response space by fusing optical and electrical dual-domain data, breaks the appearance degeneracy of LED sidewall leakage and TFT degradation on the steady-state brightness by using transient-steady deviation degree and frequency domain phase response slope, and accurately identifies abnormal pixels and their physical roots online; the abnormal detection module issues cause-driven correction instructions based on actual abnormal types, so that the equipment control module can implement accurate compensation for real defects, avoids compensation parameter invalidation and display non-uniformity aggravation caused by misjudgment of TFT degradation as LED leakage or vice versa, and simultaneously corrects Micro-LED manufacturing equipment working parameters and detection parameters through feedback, so as to suppress the generation of similar defects from the source. The present application significantly improves the accuracy, effectiveness and production line yield of Micro-LED display pixel array brightness consistency online correction.

Description

Technical Field

[0001] This invention relates to the field of LED brightness and color adjustment technology, and specifically to an online correction system for the brightness consistency of a Micro-LED display pixel array based on optical detection. Background Technology

[0002] Brightness uniformity of Micro-LED pixel arrays is a core indicator determining display quality. Pixel-level brightness deviations will create fixed pattern noise perceptible to the human eye in the displayed image, directly affecting product yield and viewing experience. Therefore, brightness uniformity correction has significant technical value.

[0003] However, when abnormal pixels appear, the non-radiative recombination of charge carriers caused by leakage current in the LED epitaxial sidewalls and the insufficient injection current caused by threshold voltage drift or mobility degradation of the driving backplane TFT exhibit significant overlap in their manifestations in the core observation dimension of steady-state luminance. Both result in low pixel brightness, and their steady-state response characteristics highly overlap in numerical ranges. Traditional optical detection methods relying on single-frame steady-state brightness images, as well as electrical measurement methods relying on lumped parameters such as forward voltage drop and quiescent current, cannot distinguish between these two physical mechanisms under online detection conditions.

[0004] Because the root cause of anomalies cannot be accurately identified during the detection phase, subsequent brightness correction cannot be tailored to the actual defect type. Mistaking TFT degradation for LED leakage, or vice versa, will cause compensation parameters to fail and may even exacerbate display unevenness. Therefore, there is an urgent need in the market for a system that can overcome the aforementioned apparent degeneracy, separate the two types of defect characteristics in the transient time-domain response space, and implement cause-driven brightness uniformity correction accordingly.

[0005] Chinese patent CN121789589A discloses a method and system for brightness and color consistency correction of LED splicing screens. The method first identifies the characteristics of module batches and divides them into correction zones, collecting original brightness and color data from both the high grayscale linear zone and the low grayscale nonlinear zone. Next, it calculates the geometric intersection of the original color gamuts of all zones to determine the largest common target color gamut, physically eliminating metamerism caused by mixing multiple batches. Subsequently, a nonlinear two-order correction model is constructed, generating a set of correction coefficients including a principal linear transformation matrix and low grayscale nonlinear bias terms. During system operation, the linear matrix is ​​dynamically invoked based on the input grayscale, and bias compensation is superimposed. This invention solves the problems of visual color difference across batches in splicing screens and color temperature drift and speckle under low grayscale, achieving high-fidelity display consistency across the entire grayscale level. However, its correction targets large-scale spatial non-uniformity and does not involve the identification of the physical mechanism of pixel-level micro-defects. It cannot solve the problem of brightness degeneracy caused by LED sidewall leakage and TFT degradation at the single-pixel level. How to achieve accurate identification and cause-driven correction of two types of pixel-level defects, LED sidewall leakage and TFT degradation, under online detection conditions remains a key problem that urgently needs to be solved in the field of Micro-LED display technology. Summary of the Invention

[0006] This invention provides an online correction system for the brightness consistency of a Micro-LED display pixel array based on optical detection, which overcomes the problem in the prior art that it is impossible to distinguish between two types of pixel-level defects, namely LED sidewall leakage and TFT degradation, making it difficult to achieve online correction of the brightness consistency of the Micro-LED display pixel array based on abnormal causes.

[0007] This invention provides an online brightness uniformity correction system for Micro-LED display pixel arrays based on optical detection, comprising: The acquisition module is used to acquire optical image data, photon detection data, DC characteristic data, and AC electrical data; A calculation module, connected to the acquisition module, is used to determine the brightness deviation of each pixel, the standard instantaneous stable brightness ratio, and the abnormal instantaneous stable brightness ratio based on the optical image data, and to determine the frequency domain phase response slope based on the AC electrical data. An anomaly detection module, connected to the calculation module, is used to determine abnormal pixels based on the pixel brightness deviation, and to determine the anomaly type based on the standard instantaneous stable brightness ratio and the abnormal instantaneous stable brightness ratio, and to determine the actual anomaly type based on the frequency domain phase response slope when the anomaly is determined to be a feature overlap anomaly, and to issue a correction command and a detection parameter correction command based on the actual anomaly type. The equipment control module, which is connected to the anomaly detection module, is used to control the operation of the Micro-LED manufacturing equipment, correct the abnormal pixels based on the correction instructions of the anomaly detection module, and modify the operating parameters of the Micro-LED manufacturing equipment and the detection parameters of the anomaly detection module based on the instructions of the anomaly detection module.

[0008] Furthermore, the anomaly detection module is also used to determine a true grayscale map based on the dark field background image, flat field calibration image and LED image in the optical image data, and to determine the average grayscale value of the LED screen based on the true grayscale map, and to determine several pixel grayscale ratios based on the ratio of each pixel in the true grayscale map to the average grayscale value of the LED screen. The anomaly detection module is also used to determine the consistency of each pixel based on the pixel grayscale ratio, and to determine that the pixel brightness is consistent when the pixel grayscale ratio is within the preset grayscale ratio range, or to determine that the pixel is an abnormal pixel when the pixel grayscale ratio is not within the preset grayscale ratio range, and to determine the type of anomaly based on the standard instantaneous stable brightness ratio and the abnormal instantaneous stable brightness ratio.

[0009] Furthermore, the anomaly detection module is also used to determine the instantaneous stability deviation based on the standard instantaneous stable brightness ratio and the abnormal instantaneous stable brightness ratio; The anomaly detection module is also used to determine the cause of the anomaly based on the instantaneous stability deviation, and to determine the occurrence of a single anomaly when the instantaneous stability deviation is less than or equal to the preset instantaneous stability deviation, and to determine the cause of the anomaly based on the preset rules; or to determine the occurrence of a feature overlap anomaly when the instantaneous stability deviation is greater than the preset instantaneous stability deviation, and to determine the actual anomaly type based on the frequency domain phase response slope.

[0010] Furthermore, the anomaly detection module is also used to determine the frequency domain phase response slope based on the impedance amplitude data, impedance phase data and the endpoint frequency of the impedance analyzer sweep range in the AC electrical data, and to determine the actual anomaly type based on the frequency domain phase response slope. The anomaly detection module is also used to determine the actual anomaly type based on the frequency domain phase response slope, and, when the frequency domain phase response slope is less than or equal to the preset frequency domain phase response slope, to determine that the current anomaly is an LED sidewall leakage anomaly, and to determine the specific cause of the anomaly based on the photon arrival time sequence data in the photon detection data; or, when the frequency domain phase response slope is greater than the preset frequency domain phase response slope, to determine that the current anomaly is a TFT driving anomaly, and to determine the specific cause of the anomaly based on the drain current data and drain voltage data in the AC electrical data.

[0011] Furthermore, the anomaly detection module is also used to determine the zero-delay coherence based on the photon arrival time series data in the photon detection data; The anomaly detection module is also used to determine the specific cause of the anomaly based on the zero-delay coherence, and to determine LED epitaxial sidewall leakage when the zero-delay coherence is less than or equal to a preset zero-delay coherence, obtain the coordinates of the abnormal pixel and issue a laser sidewall annealing command, or to determine an LED epitaxial sidewall leakage and TFT drift composite anomaly when the zero-delay coherence is greater than a preset zero-delay coherence, and to correct the brightness gain coefficient in the Demura compensation lookup table inside the Micro-LED display pixel array driver IC based on the ratio of the preset frequency domain phase response slope to the frequency domain phase response slope.

[0012] Furthermore, the anomaly detection module is also used to determine the impedance slope ratio based on the ratio of the preset frequency domain phase response slope to the frequency domain phase response slope, and to increase the brightness gain coefficient based on the impedance slope ratio, wherein the increase in the brightness gain coefficient is proportional to the impedance slope ratio.

[0013] Furthermore, the anomaly detection module is also used to determine the difference in brightness gain coefficient based on the difference in brightness gain coefficient before and after correction, and to reduce the adjacent brightness gain coefficients in the Demura compensation lookup table of the adjacent pixels of the abnormal pixel based on the difference in brightness gain coefficient, and the reduction of the adjacent brightness gain coefficients is proportional to the difference in brightness gain coefficient.

[0014] Furthermore, the anomaly detection module is also used to determine the subthreshold slope based on the drain current data and the drain voltage data in the DC characteristic data; The anomaly detection module is also used to determine the specific cause of the anomaly based on the subthreshold slope, and to determine TFT threshold voltage drift when the subthreshold slope is less than or equal to the preset subthreshold slope, and to correct the PWM duty cycle of the abnormal pixel driver IC based on the ratio of the minimum value in the preset grayscale ratio range to the pixel grayscale ratio, or to determine TFT drift channel mobility degradation when the subthreshold slope is greater than the preset subthreshold slope, to mark the abnormal pixel and perform redundant replacement.

[0015] Furthermore, the anomaly detection module is also used to determine a negative grayscale offset ratio based on the ratio of the minimum value of the preset grayscale ratio range to the pixel grayscale ratio, and to increase the PWM duty cycle based on the negative grayscale offset ratio, wherein the increase in the PWM duty cycle is proportional to the negative grayscale offset ratio.

[0016] Furthermore, the anomaly detection module is also used to determine a number of anomalies based on the number of times various anomalies occur per unit time. The anomaly detection module is also used to determine whether the production line equipment is abnormal based on the number of anomalies, and to determine that the production line equipment is working normally and maintain monitoring when the number of anomalies is less than the preset anomaly number threshold, or to determine that the production line equipment is working abnormally when the number of anomalies is greater than or equal to the preset anomaly number threshold, and to output the corresponding production line equipment maintenance notice based on the type of anomaly.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention simultaneously acquires optical image data, photon detection data, DC characteristic data, and AC electrical data through the acquisition module; the calculation module determines the brightness deviation of each pixel, the standard transient stable brightness ratio, and the abnormal transient stable brightness ratio based on the optical image data, thus expanding the detection dimension from steady-state amplitude to transient time-domain response space. By utilizing the time response characteristic of the ratio between transient brightness and steady-state brightness, the high degree of overlap between LED sidewall leakage and TFT degradation in the steady-state brightness value range is broken; at the same time, the frequency domain phase response slope is determined based on the AC electrical data, and the differential frequency domain characteristics of the phase slope increase or remain normal are achieved by utilizing the pure resistive bypass compression phase transition introduced by LED sidewall leakage and the enhanced capacitive characteristics of TFT degradation, when the feature overlap is abnormal. This enables accurate identification of the two types of defects. The anomaly detection module determines the actual anomaly type and issues a cause-driven correction command. The equipment control module performs precise compensation for the real defects rather than blind compensation based on steady-state brightness, thereby avoiding misjudging TFT degradation as LED leakage or vice versa, which would lead to the failure of compensation parameters and the aggravation of display unevenness. At the same time, by correcting the operating parameters and detection parameters of the Micro-LED manufacturing equipment through feedback, the generation of similar defects is suppressed from the source. Ultimately, it achieves accurate identification and cause-driven correction of two types of pixel-level defects, LED sidewall leakage and TFT degradation, under online detection conditions.

[0018] Furthermore, a true grayscale map is determined by jointly processing the dark field background image, the flat field calibration image, and the LED image. The ratio of each pixel to the average grayscale value of the LED screen is used as a consistency judgment index, which eliminates the influence of the overall brightness fluctuation of the panel on the detection results. The judgment is made in the form of a ratio rather than an absolute grayscale value, which ensures the process adaptability of the detection threshold. This allows all pixels that deviate from the normal luminous level to be marked as abnormal candidate points at once, providing a reliable data basis for the accurate judgment of the subsequent anomaly types.

[0019] Furthermore, by determining the instantaneous stability deviation by comparing the standard instantaneous stable brightness ratio with the abnormal instantaneous stable brightness ratio, the judgment dimension is shifted from the absolute value space of steady-state brightness to the time response relationship space between transient and steady states. For ordinary anomalies without time dependence, the instantaneous stability deviation approaches zero. However, for coupled anomalies with time-dependent defects such as LED sidewall leakage or insufficient TFT driving, the instantaneous stability deviation increases significantly. This fundamentally breaks the apparent degeneracy of LED sidewall leakage and insufficient TFT driving in steady-state brightness, achieving accurate differentiation of anomalies with overlapping features. This lays a stable foundation for subsequent determination of actual anomaly types based on the frequency domain phase response slope.

[0020] Furthermore, by using impedance amplitude data, impedance phase data, and the endpoint frequencies of the impedance analyzer's sweep range, the frequency domain phase response slope was determined. Utilizing the characteristics of the purely resistive bypass introduced by LED sidewall leakage, which does not produce phase delay under AC excitation and compresses the overall system phase transition, thus reducing the phase slope, and the characteristics of increased channel resistance when TFT driving is insufficient, which enhances capacitive characteristics and maintains a normal or increased phase slope, the two types of defects were effectively distinguished from the electrical port without depending on the light emission state. This provides an accurate basis for subsequent implementation of differentiated correction strategies for different anomaly types.

[0021] Furthermore, by determining the zero-delay coherence through photon arrival time-series data, and utilizing the characteristics of normal LEDs where photons exhibit a moderate clustering effect dominated by bimolecular recombination, and where the trapping and release process of the sidewall with SRH nonradiative recombination centers enhances photon time jitter leading to a super-clustering effect, the quantum statistical characteristics of the recombination process are directly detected. This parameter measures the essential properties of the light emission process and is not affected by fluctuations in the absolute value of the driving current. Based on this, when leakage current is detected in the LED epitaxial sidewall, the coordinates of the abnormal pixels can be obtained to issue a laser sidewall annealing command to achieve physical repair. When recombination anomalies are detected, the brightness gain coefficient in the Demura compensation lookup table can be corrected based on the ratio of the preset frequency domain phase response slope to the actual frequency domain phase response slope, thus realizing an organic combination of physical repair and electrical compensation.

[0022] Furthermore, the impedance slope ratio is determined by the ratio of the preset frequency domain phase response slope to the actual frequency domain phase response slope of the abnormal pixel. Based on this ratio, the brightness gain coefficient is increased in a way that is proportional to the impedance slope ratio. This establishes a quantitative mapping relationship between the degree of leakage and the compensation amplitude. The greater the deviation, the more severe the leakage and the corresponding increase in the compensation amplitude. This ensures that the compensation intensity is precisely matched with the severity of the defect, avoiding the problems of insufficient or excessive compensation. It also ensures that the brightness correction of LED sidewall leakage-type anomalies has a clear physical basis and quantifiable adjustment accuracy.

[0023] Furthermore, the difference in brightness gain coefficient is determined by the difference between the brightness gain coefficient before and after correction. Based on this difference, the adjacent brightness gain coefficients in the Demura compensation lookup table of the abnormal pixel are reduced, and the reduction is proportional to the difference in brightness gain coefficients. This difference directly reflects the increment of the abnormal pixel driving current relative to the original value and the degree of aggravation of optical waveguide crosstalk caused by it. By establishing the correlation between the gain increment and the neighborhood weight, the adjacent brightness gain coefficients of the adjacent pixels are reduced in the opposite direction while compensating for the leakage loss of a single pixel. This effectively offsets the excess light energy that propagates laterally to the neighborhood through the high refractive index medium in the panel after the abnormal pixel is brightened, and maintains the overall brightness uniformity of the local area.

[0024] Furthermore, by using drain current and drain voltage data to determine the subthreshold slope, and utilizing the characteristics that simple threshold voltage drift only shifts the overall transfer characteristic curve while the subthreshold slope remains unchanged, while the increased number of dangling bonds at the channel interface causes mobility degradation, which flattens the curve and significantly increases the subthreshold slope, the two mechanisms of TFT degradation are accurately separated. Based on this, when judging TFT threshold voltage drift, electrical compensation can be implemented by modifying the PWM duty cycle; when judging channel mobility degradation, abnormal pixels are marked for redundant replacement. This avoids misjudging irreversible mobility degradation as compensable threshold drift, which would lead to compensation failure, and ensures that the correction strategy is accurately matched with the repairability of the defect.

[0025] Furthermore, the negative grayscale offset ratio is determined by the ratio of the minimum value of the preset grayscale ratio range to the pixel grayscale ratio. Based on this ratio, the PWM duty cycle is reduced, and the reduction is proportional to the negative grayscale offset ratio. This ratio directly quantifies the actual deviation multiple of the dark pixel below the normal brightness boundary, so that the adjustment amount of the PWM duty cycle is determined by the actual deviation of the current grayscale value of the pixel relative to the normal range. This achieves a one-to-one correspondence between brightness deviation and compensation amount, ensuring that there is a clear quantitative basis and predictable compensation accuracy when correcting the duty cycle for insufficient brightness caused by TFT threshold voltage drift.

[0026] Furthermore, by statistically analyzing the number of occurrences of various anomalies within a unit of time, isolated defect events of individual pixels are aggregated into statistical signals in the time dimension. When the frequency of occurrence of a certain type of defect exceeds the preset statistical control upper limit, it is determined that the corresponding manufacturing equipment parameters have deviated from the stable working range. Based on the type of anomaly, a maintenance notice for the corresponding production line equipment is output, extending the detection system from single-pixel diagnosis to production line-level process quality control. This enables predictive maintenance of key process equipment such as ICP dry etching machines, PECVD film deposition equipment, and ELA excimer laser annealing equipment, making yield management predictable and proactive, and suppressing the generation of batch defects from the source. Attached Figure Description

[0027] Figure 1This is a block diagram of the online brightness uniformity correction system for Micro-LED display pixel array based on optical detection in an embodiment of the present invention; Figure 2 This is a flowchart illustrating the process of determining the consistency of pixels based on their grayscale ratio in an embodiment of the present invention. Figure 3 This is a flowchart illustrating the process of determining the cause of anomalies based on transient stability deviation in an embodiment of the present invention; Figure 4 This is a flowchart illustrating how the brightness gain coefficient is increased based on the impedance slope ratio in an embodiment of the present invention. Detailed Implementation

[0028] 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.

[0029] 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.

[0030] Please see Figure 1 The diagram shown is a block diagram of an online brightness uniformity correction system for a Micro-LED display pixel array based on optical detection, as described in this embodiment of the invention. The online brightness uniformity correction system for a Micro-LED display pixel array based on optical detection includes... The acquisition module is used to acquire optical image data, photon detection data, DC characteristic data, and AC electrical data; A calculation module, connected to the acquisition module, is used to determine the brightness deviation of each pixel, the standard instantaneous stable brightness ratio, and the abnormal instantaneous stable brightness ratio based on the optical image data, and to determine the frequency domain phase response slope based on the AC electrical data. An anomaly detection module, which is connected to the calculation module, is used to determine abnormal pixels based on the pixel brightness deviation, and to determine the anomaly type based on the instantaneous stability deviation, and to determine the actual anomaly type based on the frequency domain phase response slope when the anomaly is determined to be a feature overlap anomaly, and to issue a correction command and a detection parameter correction command based on the actual anomaly type. The equipment control module, which is connected to the anomaly detection module, is used to control the operation of the Micro-LED manufacturing equipment, correct the abnormal pixels based on the correction instructions of the anomaly detection module, and modify the operating parameters of the Micro-LED manufacturing equipment and the detection parameters of the anomaly detection module based on the instructions of the anomaly detection module.

[0031] The optical image data refers to two-dimensional spatial light intensity distribution data acquired by globally synchronous exposure of the Micro-LED display pixel array using a high-resolution area array CMOS camera, including LED images, dark field background images, and flat field calibration images. The photon detection data refers to the data obtained by performing quantum optical measurements on the emission of a single pixel using a single-photon detector and a time-correlated single-photon counting module, including photon arrival time series, detector dark count series, hyperspectral data cube, and wavelength calibration series; The DC characteristic data refers to the steady-state electrical data obtained by applying a DC scanning voltage to the TFT of the target pixel through the source measurement unit and simultaneously measuring the drain current, including drain current data and drain voltage data. The AC electrical data refers to the current and voltage response data collected in the time or frequency domain by a high-speed sampling circuit or impedance analyzer after applying an AC or pulse excitation signal to the target pixel, including the total current wave of the abnormal pixel, the background current wave of the abnormal pixel, the excitation voltage waveform, the impedance amplitude data, and the impedance phase data. The LED image, dark background image, and flat calibration image can be acquired by a high-resolution area array CMOS camera. When acquiring the dark background image, all light sources are turned off, and a completely black image is taken using the same exposure time and gain as the formal test. When acquiring the flat calibration image, a Micro-LED display pixel array with absolutely uniform brightness is placed at the detection position, and an image is taken using the same exposure time and gain as the formal test. The dark background image and flat calibration image can be taken once per shift or once per day and then stored in the system. The photon arrival time sequence and detector dark count sequence can be acquired by using a fixed HBT optical path in conjunction with two single-photon detectors and a TCSPC module as an overall optical engine. The abnormal pixel total current waveform, abnormal pixel background current waveform, and excitation voltage waveform can be acquired by a high-speed sampling circuit to obtain the current of the data line in the column where the target pixel is located. Impedance amplitude data and impedance phase data can be acquired by an impedance analyzer through the data line impedance analyzer of the column where the target pixel is located. The drain current data and the drain voltage data can be measured by the source measurement unit; The process by which the calculation module determines the brightness deviation of each pixel based on the optical image data includes: The pixel grayscale values ​​of each pixel in the LED image, the dark background image, and the flat calibration image are obtained respectively. Then, the true grayscale value of each pixel is calculated based on the true grayscale formula. in, The true brightness of the pixel at position (i, j) Let be the grayscale value of the pixel at position (i, j) in the LED image. Let be the gray value of the pixel at position (i, j) in the dark background image. Let be the gray value of the pixel at position (i, j) in the flat field calibration image; The true grayscale value of each pixel in the LED image, dark background image, and flat calibration image is traversed to obtain a true grayscale map. The average grayscale value of the LED screen is determined based on the true grayscale map. Furthermore, the grayscale ratio of several pixels is determined based on the ratio of each pixel in the true grayscale map to the average grayscale value of the LED screen. The process of determining the standard transient stable luminance ratio and the abnormal transient stable luminance ratio based on optical image data includes: A standard pixel is defined as the pixel whose grayscale ratio is equal to the midpoint of a preset grayscale ratio range among n pixels. Obtain the standard pixel coordinates, and turn on the TFT switch of the normal pixel based on the drive backplane row selection signal. Write a voltage pulse signal with amplitude and pulse width to the data line of the pixel, wherein the value of the writing amplitude is 3~5V and the value of the pulse width is 100~500μs. The average luminance within the first acquisition time window after the rising edge of the acquisition pulse ends is recorded as the standard transient pixel luminance Lnt; the TFT continues to be turned on, and the average luminance within the first acquisition time window when the acquisition pulse stabilizes is recorded as the standard steady-state pixel luminance Lns, and the TFT switch of that pixel is turned off. The primary standard transient-steady-state luminance ratio is determined based on the ratio of pixel luminance Lnt at the standard transient moment to pixel luminance Lns at the standard steady-state moment. The standard transient-steady-state luminance ratio STR is determined by iterating through each standard pixel and using the average value of the primary standard transient-steady-state luminance ratios of each standard pixel. The transient pixel luminance and the steady-state pixel luminance of the abnormal pixel are obtained in the same way and denoted as the abnormal transient pixel luminance Nnt and the abnormal steady-state pixel luminance Nns, respectively. The abnormal transient steady-state luminance ratio ATR is determined based on the ratio of the abnormal transient pixel luminance Nnt to the abnormal steady-state pixel luminance Nns. Furthermore, the anomaly detection module is also used to determine a true grayscale map based on the dark field background image, flat field calibration image and LED image in the optical image data, and to determine the average grayscale value of the LED screen based on the true grayscale map, and to determine several pixel grayscale ratios based on the ratio of each pixel in the true grayscale map to the average grayscale value of the LED screen. The anomaly detection module is also used to determine the consistency of each pixel based on the pixel grayscale ratio, and to determine that the pixel brightness is consistent when the pixel grayscale ratio is within the preset grayscale ratio range, or to determine that the pixel is an abnormal pixel when the pixel grayscale ratio is not within the preset grayscale ratio range, and to determine the type of anomaly based on the standard instantaneous stable brightness ratio and the abnormal instantaneous stable brightness ratio.

[0032] The pixel grayscale ratio reflects the deviation of a single pixel's true grayscale after flat-field correction from the average grayscale value of the entire screen. This parameter is a direct quantitative indicator of pixel luminous intensity consistency. By using a uniform ratio threshold, all pixels that deviate from the normal luminous level can be marked as abnormal candidate points at once. The judgment is made in the form of a ratio rather than an absolute grayscale value, eliminating the influence of overall panel brightness fluctuations on the detection results and ensuring the process adaptability of the detection threshold.

[0033] Please see Figure 2 As shown, this is a flowchart illustrating the process of determining the consistency of pixels based on their grayscale ratio in an embodiment of the present invention. The process of determining the consistency of pixels based on their grayscale ratio in this embodiment includes: The anomaly detection module determines the true grayscale map based on the dark background image, flat calibration image, and LED image in the optical image data. The anomaly detection module determines the average grayscale value of the LED screen based on the real grayscale map. The anomaly detection module determines a grayscale ratio (PGR) for several pixels based on the ratio of each pixel in the real grayscale map to the average grayscale value of the LED screen. i ,i=1,2,3,······,n; The pixel grayscale ratio PGR i Compared with the preset grayscale ratio range PGR1, when the pixel grayscale is lower or higher than 6% of the full screen average, the human eye perceives slight dark spots or bright spots. Therefore, the preset grayscale ratio range PGR1 is set to [0.94, 1.06]. If the pixel grayscale ratio PGR i If the pixel brightness falls within the preset grayscale ratio range PGR1, then the pixel brightness is determined to be consistent. If the pixel grayscale ratio PGR i If a pixel does not fall within the preset grayscale ratio range PGR1, it is determined to be an abnormal pixel, and the type of abnormality is determined based on the standard instantaneous stable brightness ratio and the abnormal instantaneous stable brightness ratio.

[0034] Furthermore, the anomaly detection module is also used to determine the instantaneous stability deviation based on the standard instantaneous stable brightness ratio and the abnormal instantaneous stable brightness ratio; The anomaly detection module is also used to determine the cause of the anomaly based on the instantaneous stability deviation, and to determine the occurrence of a single anomaly when the instantaneous stability deviation is less than or equal to the preset instantaneous stability deviation, and to determine the cause of the anomaly based on the preset rules; or to determine the occurrence of a feature overlap anomaly when the instantaneous stability deviation is greater than the preset instantaneous stability deviation, and to determine the actual anomaly type based on the frequency domain phase response slope.

[0035] In this scheme, the overlapping anomalies refer to the high degeneracy of two types of defects—LED sidewall leakage and insufficient TFT driving—in terms of steady-state brightness. Under pulse driving conditions, the luminance of a Micro-LED display pixel transitions from the transient value at the arrival of the driving pulse to the steady-state value after full charging. This dynamic process reflects the time-response characteristics of carrier injection, transport, and recombination within the pixel. For normal pixels or ordinary anomalous pixels without time-dependent defects, the ratio between transient and steady-state brightness is determined by the time constant of the driving circuit and the capacitive load of the pixel itself, and this ratio remains constant among all pixels without time-evolutionary defects. In other words, if a pixel's defect is a common anomaly that does not evolve over time, such as a fixed attenuation type, an obstruction type, or a complete open circuit type, then the transient-steady-state brightness ratio of that pixel is completely consistent with that of a normal pixel. However, when a pixel has coupled anomalies such as LED epitaxial sidewall leakage or TFT threshold voltage drift and mobility degradation, the physical effects of the defect itself are time-dependent. The parasitic parallel conductive path introduced by LED sidewall leakage does not have the same shunting ratio for carriers at the rising edge of the driving pulse and in the steady state. Insufficient TFT driving capability leads to a change in the charging rate of the pixel capacitor. Both of these will disrupt the original fixed ratio between transient brightness and steady-state brightness. Therefore, the transient-steady-state brightness ratio of the tested pixel will deviate from the reference ratio determined by the normal pixel, and this deviation will only occur when there is a time-dependent defect. The transient-steady-state deviation reflects the time response characteristics of the pixel to the driving pulse. If the defect of the tested pixel is not time-dependent, the abnormal transient-steady-state brightness ratio (ATR) is consistent with that of the normal pixel, and the transient-steady-state deviation is close to zero. Conversely, if the defect itself evolves over time, the abnormal transient-steady-state brightness ratio (ATR) will deviate from the reference ratio of the normal pixel, and the transient-steady-state deviation will be significantly greater than zero. Through the transient-steady-state deviation, this invention can shift the judgment dimension from the absolute value space of steady-state brightness to the transient-steady-state time response relationship space, fundamentally breaking the apparent simplification of LED sidewall leakage and TFT insufficient driving in steady-state brightness, and realizing accurate differentiation of feature overlap anomalies, thus laying a stable foundation for subsequent judgment and correction.

[0036] Please see Figure 3As shown, this is a flowchart illustrating the process of determining the cause of an anomaly based on the instantaneous stability deviation in an embodiment of the present invention. The process of determining the cause of an anomaly based on the instantaneous stability deviation in an embodiment of the present invention includes: The instantaneous stability deviation is determined based on the standard instantaneous stable luminance ratio (STR) and the abnormal instantaneous stable luminance ratio (ATR). Transient stability deviation TSD = ( -1) 2 ; The instantaneous stability deviation (TSD) is compared with the preset instantaneous stability deviation (TSD1). Under ideal conditions, the theoretical value of the instantaneous stability deviation (TSD) for normal pixels or ordinary abnormal pixels without time-dependent defects is zero. However, in actual optical inspection systems, non-ideal factors such as detector noise, quantization error, and slight jitter of the driving waveform will cause inherent fluctuations in the brightness measurement value of normal pixels. To ensure that the judgment threshold can effectively separate the small TSD value caused by measurement noise from the significant TSD value caused by time-dependent defects, the threshold should be tens to hundreds of times the noise baseline as a safety margin. Accordingly, the preset instantaneous stability deviation (TSD) is set in the range of 0.01 to 0.05 to avoid normal pixels being misjudged as coupling abnormalities due to an excessively low threshold, while ensuring that transient-steady-state ratio shifts caused by LED sidewall leakage or insufficient TFT driving (usually the instantaneous stability deviation (TSD) is on the order of 0.1 or higher) can be reliably detected. If the instantaneous stability deviation TSD is less than or equal to the preset instantaneous stability deviation range TSD1, then a single abnormality is determined, and the cause of the abnormality is determined based on the preset rules. The preset rules are not limited and can be set by technicians according to their needs. If the instantaneous stability deviation (TSD) is greater than the preset instantaneous stability deviation range (TSD1), then a feature overlap anomaly is determined, and the actual anomaly type is determined based on the frequency domain phase response slope.

[0037] Furthermore, the anomaly detection module is also used to determine the frequency domain phase response slope based on the impedance amplitude data, impedance phase data and the endpoint frequency of the impedance analyzer sweep range in the AC electrical data, and to determine the actual anomaly type based on the frequency domain phase response slope. The anomaly detection module is also used to determine the actual anomaly type based on the frequency domain phase response slope, and, when the frequency domain phase response slope is less than or equal to the preset frequency domain phase response slope, to determine that the current anomaly is an LED sidewall leakage anomaly, and to determine the specific cause of the anomaly based on the photon arrival time sequence data in the photon detection data; or, when the frequency domain phase response slope is greater than the preset frequency domain phase response slope, to determine that the current anomaly is a TFT driving anomaly, and to determine the specific cause of the anomaly based on the drain current data and drain voltage data in the DC characteristic data.

[0038] The frequency domain phase response slope reflects how quickly the phase angle of the current lagging behind the voltage changes with frequency under AC excitation. This parameter characterizes the relative dominance of capacitive and resistive elements in the pixel equivalent circuit. LED sidewall leakage introduces a purely resistive bypass, which does not produce phase delay under AC excitation, thus compressing the overall phase transition of the system and significantly reducing the phase slope. When the TFT is underdriven, the increased channel resistance enhances the capacitive characteristics, and the phase slope remains normal or increases. By extracting this frequency domain feature, defect types can be distinguished from the electrical ports without depending on the luminous state.

[0039] Specifically, the process by which the anomaly detection module determines the actual anomaly type based on the frequency domain phase response slope includes: The anomaly detection module determines the frequency domain phase response slope DIP based on the impedance amplitude data, impedance phase data and the endpoint frequency of the frequency sweep range of the impedance analyzer in the AC electrical data. The frequency domain phase response slope DIP is compared with the preset frequency domain phase response slope DIP1. The equivalent circuit of a normal pixel includes a series network of LED junction capacitance and TFT channel resistance. The phase transitions from about -85° at low frequency to about -5° at high frequency, spanning three decibels. The phase slope is about (85-5) / 3≈27 degrees / decade, and in practice it is usually 30-50 degrees / dec. When there is an ohmic leakage channel on the LED sidewall, the purely resistive bypass does not produce phase delay under AC excitation. The overall phase transition of the system is compressed, and the frequency domain phase response slope DIP is reduced to below 20 degrees / dec. Therefore, the preset frequency domain phase response slope DIP1∈[20, 30° / dec] is set. If the frequency domain phase response slope DIP is less than or equal to the preset frequency domain phase response slope DIP1, the current anomaly is determined to be an LED sidewall leakage anomaly, and the specific cause of the anomaly is determined based on the photon arrival time series data in the photon detection data. If the frequency domain phase response slope DIP is greater than the preset frequency domain phase response slope DIP1, the current anomaly is determined to be a TFT driving anomaly, and the specific cause of the anomaly is determined based on the drain current data and drain voltage data in the DC characteristic data.

[0040] Furthermore, the anomaly detection module is also used to determine the zero-delay coherence based on the photon arrival time series data in the photon detection data; The anomaly detection module is also used to determine the specific cause of the anomaly based on the zero-delay coherence, and to determine LED epitaxial sidewall leakage when the zero-delay coherence is less than or equal to a preset zero-delay coherence, obtain the coordinates of the abnormal pixel, and issue a laser sidewall annealing command; or, to determine an anomaly of LED epitaxial sidewall leakage and TFT drift combined when the zero-delay coherence is greater than a preset zero-delay coherence, and to correct the brightness gain coefficient in the Demura compensation lookup table inside the Micro-LED display pixel array driver IC based on the ratio of the preset frequency domain phase response slope to the frequency domain phase response slope.

[0041] The Demura compensation lookup table is a set of correction parameters stored independently for each pixel inside the driver IC. It is used to eliminate the unevenness of brightness and color between pixels. It typically includes a brightness gain coefficient, a color correction coefficient, and a grayscale offset. The brightness gain coefficient is used to correct the brightness deviation of the pixel. The value range of the brightness gain coefficient is usually selected from 0.9-1.1.

[0042] Zero-delay second-order coherence reflects the temporal statistical law of photon emission during the light emission process, that is, the ratio of the probability of photons arriving at the detector in pairs to the random probability. In normal LEDs, bimolecular recombination is dominant, and photons exhibit a moderate clustering effect. However, when SRH nonradiative recombination centers exist on the sidewalls, the trapping and releasing process disrupts the thermodynamic equilibrium distribution of charge carriers, increasing photon timing jitter and abnormally raising the clustering effect at zero delay to a super-clustered state. This parameter directly detects the quantum statistical characteristics of the recombination process and serves as a quantum optical fingerprint for confirming SRH nonradiative recombination. Its advantage lies in measuring the essential properties of the light emission process, unaffected by fluctuations in the absolute value of the driving current.

[0043] Specifically, the process by which the anomaly detection module determines the specific cause of the anomaly based on the zero-delay coherence includes: The anomaly detection module collects photon arrival time-series data based on the acquisition module. The duration of continuous acquisition depends on the cumulative number of photons in a single TCSPC module, and the cumulative number of photons must be greater than or equal to 10. 6 One photon; Generate a histogram of events based on the TCSPC module; Determining the second-order correlation of photons based on the event histogram , in, The time difference between the arrival times of photons recorded by the two single-photon detectors. For a coincidence count with a time difference of τ, These are the total photon counts for the first and second paths, respectively. To match the time resolution (bin width) of the event histogram. Total collection time; The second-order photon correlation degree with τ=0 is denoted as the zero-delay coherence degree ZCD; The zero-delay coherence ZCD is compared with the preset zero-delay coherence ZCD1. Normal LED light emission is dominated by bimolecular recombination, and the carriers are distributed in thermodynamic equilibrium. The photons exhibit a moderate clustering effect, and the typical range of zero-delay coherence ZCD is 1.1~1.3. When there are significant SRH nonradiative recombination centers on the sidewalls, the trap-release process enhances the time jitter of photon emission, resulting in a super-clustering effect. The zero-delay coherence ZCD increases significantly to above 1.5. In order to avoid normal pixels being misjudged as leakage due to statistical fluctuations, the preset zero-delay coherence ZCD1∈(1.3, 1.5] is set. If the zero-delay coherence ZCD is less than or equal to the preset zero-delay coherence ZCD1, then the LED epitaxial sidewall leakage is determined, the abnormal pixel coordinates are obtained, and a laser sidewall annealing command is issued. If the zero-delay coherence ZCD is greater than the preset zero-delay coherence ZCD1, then the LED epitaxial sidewall leakage and TFT drift recombination are determined to be abnormal. Based on the ratio of the preset frequency domain phase response slope to the frequency domain phase response slope, the brightness gain coefficient in the Demura compensation lookup table inside the Micro-LED display pixel array driver IC is corrected.

[0044] Furthermore, the anomaly detection module is also used to determine the impedance slope ratio based on the ratio of the preset frequency domain phase response slope to the frequency domain phase response slope, and to increase the brightness gain coefficient based on the impedance slope ratio, wherein the increase in the brightness gain coefficient is proportional to the impedance slope ratio.

[0045] The impedance slope ratio reflects the relative degree to which the frequency domain phase response slope of the abnormal pixel deviates from the preset normal reference value. This parameter directly quantifies the degree to which the ohmic leakage channel of the LED sidewall compresses the capacitive characteristics of the pixel's equivalent circuit. The greater the deviation, the more severe the leakage. Using it as the basis for adjusting the brightness gain coefficient, a quantitative mapping relationship between the degree of leakage and the compensation amplitude is established, so that the compensation intensity is accurately matched with the severity of the defect.

[0046] Please see Figure 4 As shown, this is a flowchart illustrating the process of increasing the brightness gain coefficient based on the impedance slope ratio in an embodiment of the present invention. The process of the anomaly detection module increasing the brightness gain coefficient based on the impedance slope ratio in this embodiment of the present invention includes: The anomaly detection module determines the impedance slope ratio (DIPR) based on the ratio of the preset frequency domain phase response slope to the frequency domain phase response slope. The impedance slope ratio DIPR is compared with the first preset impedance slope ratio DIPR1 and the second preset impedance slope ratio DIPR2. Generally, it is considered that if the frequency domain phase response slope deviates from the normal value by less than 20%, the leakage is slight and only a small increase in gain is needed. If the deviation reaches 20%-40%, the leakage is considered moderate and a moderate amount of compensation is needed. If it is greater than 40%, it is considered that a relatively serious leakage has occurred. Therefore, the first preset impedance slope ratio DIPR1∈(1,1.2] and the second preset impedance slope ratio DIPR2∈(1.2,1.4) are set. In a Micro-LED display pixel array, the brightness gain coefficient of a normal pixel is usually between 0.95 and 1.05. If the impedance slope ratio DIPR is less than or equal to the first preset impedance slope ratio DIPR1, the brightness gain coefficient is corrected using the first brightness gain correction threshold α1. The corrected brightness gain coefficient BGF' = BGF × α1, where the first brightness gain correction threshold α1 is set to 1.04. If the impedance slope ratio DIPR is greater than the first preset impedance slope ratio DIPR1 and less than or equal to the second preset impedance slope ratio DIPR2, then the brightness gain coefficient is corrected using the second brightness gain correction threshold α2. The corrected brightness gain coefficient BGF' = BGF × α2, where the second brightness gain correction threshold α2 is set to 1.1. If the impedance slope ratio DIPR is greater than the second preset impedance slope ratio DIPR2, then the brightness gain coefficient is corrected using the third brightness gain correction threshold α3. The corrected brightness gain coefficient BGF' = BGF × α3, where the third brightness gain correction threshold α3 is set to 1.18.

[0047] Furthermore, the anomaly detection module is also used to determine the difference in brightness gain coefficient based on the difference in brightness gain coefficient before and after correction, and to reduce the adjacent brightness gain coefficients in the Demura compensation lookup table of the adjacent pixels of the abnormal pixel based on the difference in brightness gain coefficient, and the reduction of the adjacent brightness gain coefficients is proportional to the difference in brightness gain coefficient. The adjacent pixels refer to four pixels that are directly adjacent to the abnormal pixel in the row or column direction and share a pixel boundary.

[0048] The difference in brightness gain coefficient reflects the increase in the driving current of the pixel relative to the original value after the gain coefficient is increased to compensate for leakage loss. This increase directly determines the degree of aggravation of optical waveguide crosstalk. The adjacent brightness gain coefficients of adjacent pixels need to be reduced in the opposite direction according to this difference to offset the excess light energy that propagates laterally to the neighborhood through the high refractive index medium in the panel after the abnormal pixel brightens. By establishing the correlation between the gain increment and the neighborhood weight, the overall brightness uniformity of the local area can be maintained while compensating for a single pixel.

[0049] Specifically, the process by which the anomaly detection module reduces the adjacent luminance gain coefficients of the neighboring pixels in the Demura compensation lookup table based on the difference in luminance gain coefficients includes: The anomaly detection module determines the brightness gain coefficient difference (BGFD) based on the difference between the brightness gain coefficients before and after correction. The brightness gain coefficient difference BGFD is compared with the first preset brightness gain coefficient difference BGFD1 and the second preset brightness gain coefficient difference BGFD2. In actual engineering, the essence of optical waveguide crosstalk is that after a certain pixel emits light, it propagates laterally to the adjacent pixels through the high refractive index planarization layer inside the panel. Whenever the gain is increased to 10%, the interference causes the neighborhood to brighten by about 3%, which can be perceived by the human eye. Therefore, the first preset brightness gain coefficient difference BGFD1 is set to [0.09, 0.1] and the second preset brightness gain coefficient difference BGFD2 is set to (0.1, 0.18]. If the brightness gain coefficient difference BGFD is less than or equal to the first preset brightness gain coefficient difference BGFD1, then the adjacent brightness gain coefficient is corrected using the first adjacent brightness gain coefficient correction threshold β1, and the corrected adjacent brightness gain coefficient LW'=β1×LW, wherein the first adjacent brightness gain coefficient correction threshold β1 is set to 0.98. If the brightness gain coefficient difference BGFD is greater than the first preset brightness gain coefficient difference BGFD1 and less than or equal to the second preset brightness gain coefficient difference BGFD2, then the adjacent brightness gain coefficient is corrected using the second adjacent brightness gain coefficient correction threshold β2. The corrected adjacent brightness gain coefficient LW' = β2 × LW, where the second adjacent brightness gain coefficient correction threshold β2 is set to 0.95. If the difference in brightness gain coefficients BGFD is greater than the second preset difference in brightness gain coefficients BGFD2, then the adjacent brightness gain coefficients are corrected using the third adjacent brightness gain coefficient correction threshold β3. The corrected adjacent brightness gain coefficient LW' = β3 × LW, where the third adjacent brightness gain coefficient correction threshold β3 is set to 0.9.

[0050] Furthermore, the anomaly detection module is also used to determine the subthreshold slope based on the drain current data and the drain voltage data in the DC characteristic data; The anomaly detection module is also used to determine the specific cause of the anomaly based on the subthreshold slope, and to determine TFT threshold voltage drift when the subthreshold slope is less than or equal to a preset subthreshold slope, to determine a correction range based on the pixel grayscale ratio and the endpoint of the preset grayscale ratio range, and to correct the PWM duty cycle of the abnormal pixel driver IC based on the ratio of the minimum value in the preset grayscale ratio range to the pixel grayscale ratio, or to determine TFT drift channel mobility degradation when the subthreshold slope is greater than the preset subthreshold slope, to mark the abnormal pixel and perform redundant replacement.

[0051] The subthreshold slope reflects the ability of the TFT to regulate the drain current by the gate voltage in the subthreshold region. Physically, it is a direct characterization of the quality of the gate oxide layer and the channel interface. This parameter can separate two mechanisms of TFT degradation: simple threshold voltage drift only shifts the overall transfer characteristic curve, while the subthreshold slope remains unchanged; however, mobility degradation caused by an increase in dangling bonds at the channel interface will flatten the curve and significantly increase the subthreshold slope. By determining whether the subthreshold slope exceeds a preset threshold, it is possible to determine whether the TFT degradation is reversible, thereby deciding whether to perform electrical compensation or redundant replacement.

[0052] Specifically, the process by which the anomaly detection module determines the specific cause of the anomaly based on the subthreshold slope includes: The anomaly detection module determines the subthreshold slope SS based on the drain current data and drain voltage data in the DC characteristic data. The process includes: Obtain the coordinates of the abnormal pixel, select the data line and scan line where the target pixel is located using the switch matrix, turn on the scan line, turn on the TFT of the target pixel, set the drain voltage of the source measurement unit to 5V, and increase the gate voltage step by step from 0V, with the step increase voltage value ranging from 0.01-0.1V. Measure the drain current after each step, and stop scanning when the gate voltage is reached. Turn off the TFT to obtain a set of corresponding gate voltage sequence and drain current sequence. Based on the gate voltage sequence as the horizontal axis and the drain current sequence as the vertical axis, obtain the subthreshold characteristic curve of the TFT. The subthreshold region in the subthreshold characteristic curve is determined. There is no limitation on the method of determining the subthreshold region. For example, you can first traverse all data points and filter out the points with current in the range of 1pA-1nA. Then, filter out the regions among these points where the number of consecutive points is greater than or equal to 5 and the drain current increases strictly with voltage. These are recorded as the subthreshold region. Determine the maximum slope of each line segment in the subthreshold region, and determine the subthreshold slope based on the maximum slope; The subthreshold slope SS is compared with the preset subthreshold slope SS1. The subthreshold slope of a normal low-temperature polycrystalline silicon TFT is usually between 0.2 and 0.5 V / dec, and the ideal room temperature limit is about 0.06 V / dec. However, actual devices will degrade due to the influence of interface states. When SS > 1.0 V / dec, it indicates that the dangling bond density at the channel interface increases significantly and the gate voltage control capability is severely degraded. This is a clear sign of mobility degradation. In order to ensure that the abnormality is captured in the early stage of degradation, the preset subthreshold slope SS1 is set to [0.9, 1]. If the subthreshold slope SS is less than or equal to the preset subthreshold slope SS1, then the TFT threshold voltage drift is determined, and the PWM duty cycle of the abnormal pixel driver IC is corrected based on the ratio of the minimum value in the preset grayscale ratio range to the pixel grayscale ratio. If the subthreshold slope SS is greater than the preset subthreshold slope SS1, then the TFT drift channel mobility is determined to be degraded, abnormal pixels are marked and redundant replacements are performed.

[0053] Furthermore, the anomaly detection module is also used to determine a negative grayscale offset ratio based on the ratio of the minimum value of the preset grayscale ratio range to the pixel grayscale ratio, and to increase the PWM duty cycle based on the negative grayscale offset ratio, wherein the increase in the PWM duty cycle is proportional to the negative grayscale offset ratio.

[0054] The negative grayscale offset ratio reflects the degree of deviation of the pixel grayscale ratio from the preset minimum normal range after the TFT threshold voltage drift is determined. The ratio of the minimum range to the grayscale ratio gives the multiple by which the dark spot is lower than the normal level. This is used as the basis for adjusting the PWM duty cycle, so that the compensation amount is directly determined by the actual deviation of the current grayscale value of the pixel from the normal boundary, realizing a one-to-one correspondence between brightness deviation and compensation amount.

[0055] Specifically, the process by which the anomaly detection module corrects the PWM duty cycle includes: The negative grayscale offset ratio FGO is determined based on the ratio of the minimum value of the preset grayscale ratio range to the pixel grayscale ratio. The negative grayscale offset ratio FGO is compared with the set first preset negative grayscale offset ratio FGO1 and second preset negative grayscale offset ratio FGO2. When the pixel grayscale is lower than 6% of the average value of the whole screen, the human eye perceives a slight dark spot, while when the pixel grayscale is lower than 12% of the average value of the whole screen, the human eye can perceive a significant dark spot. Therefore, the first preset negative grayscale offset ratio FGO1 is set to (1, 1.06] and the second preset negative grayscale offset ratio FGO2 is set to (1.06, 1.12]. If the negative grayscale offset ratio FGO is less than or equal to the first preset negative grayscale offset ratio FGO1, then the PWM duty cycle DC is corrected using the fourth duty cycle correction threshold λ4. The corrected PWM duty cycle DC' = DC × λ4, where the fourth duty cycle correction threshold λ4 is set to 1.03. If the negative grayscale offset ratio FGO is greater than the first preset negative grayscale offset ratio FGO1 and less than or equal to the second preset negative grayscale offset ratio FGO2, then the PWM duty cycle DC is corrected using the fifth duty cycle correction threshold λ5. The corrected PWM duty cycle DC' = DC × λ5, where the fifth duty cycle correction threshold λ5 is set to 1.07. If the negative grayscale offset ratio FGO is greater than the second preset negative grayscale offset ratio FGO2, then the PWM duty cycle DC is corrected using the sixth duty cycle correction threshold λ6. The corrected PWM duty cycle DC' = DC × λ6, where the sixth duty cycle correction threshold λ6 is set to 1.14.

[0056] Furthermore, the anomaly detection module is also used to determine the number of anomalies based on the number of times various anomalies occur per unit time. The anomaly detection module is also used to determine whether the production line equipment is abnormal based on the number of anomalies, and to determine that the production line equipment is working normally and maintain monitoring when the number of anomalies is less than the preset anomaly number threshold, or to determine that the production line equipment is working abnormally when the number of anomalies is greater than or equal to the preset anomaly number threshold, and to output the corresponding production line equipment maintenance notice based on the type of anomaly.

[0057] The number of anomalies reflects the frequency of occurrence of various types of defects per unit time. This parameter aggregates isolated defect events of individual pixels into a statistical signal over time. When the frequency of occurrence of a certain type of defect exceeds the upper limit of statistical control, it indicates that the corresponding manufacturing equipment parameters have deviated from the stable operating range. By monitoring the changing trend of the number of anomalies, the detection system extends from single-pixel diagnosis to production line-level process quality control, making yield management predictive and proactive.

[0058] Specifically, the process by which the anomaly detection module determines whether the production line equipment is abnormal based on the number of anomalies includes: The anomaly detection module determines a number of anomalies NAi based on the number of times various anomalies occur per unit time. The unit time is not limited in principle, but can be set to 24h-42h. The number of anomalies NAi is compared with the preset number of anomalies NAi set for the anomaly type. In principle, the specific value of the preset number of anomalies NAi is not limited. Technical personnel can set it according to historical data or actual requirements, which will not be elaborated here. If the number of abnormalities NAi is less than the preset number of abnormalities NAi, the production line equipment is determined to be working normally, and monitoring is maintained. If the number of abnormalities NAi is greater than or equal to the preset number of abnormalities NAi, the production line equipment is determined to be malfunctioning. A corresponding production line equipment maintenance notice is then output based on the type of abnormality. This output based on the type of abnormality includes, but is not limited to: LED sidewall leakage output troubleshooting ICP dry etching machine; TFT threshold voltage drift output troubleshooting for PECVD film deposition equipment; TFT channel mobility degradation output requires maintenance of ELA excimer laser annealing equipment; Metal hard short-circuit output troubleshooting of lithography machines / developing equipment; ESD soft damage output inspection and maintenance line electrostatic discharge protection system; Optical waveguide crosstalk output troubleshooting and coating / developing machine; Troubleshooting QD color conversion failure output for inkjet printing equipment, etc., will not be elaborated here.

[0059] This invention proposes an online brightness consistency correction system for Micro-LED display pixel arrays based on optical detection. The system comprises an acquisition module, a calculation module, an anomaly detection module, and a device control module. The acquisition module acquires optical image data, photon detection data, DC characteristic data, and AC electrical data. The calculation module determines the brightness deviation of each pixel, the standard transient stable brightness ratio, and the abnormal transient stable brightness ratio based on the optical image data, and determines the frequency domain phase response slope based on the AC electrical data. The anomaly detection module first filters abnormal pixels by pixel grayscale ratio, and then expands the detection dimension from steady-state amplitude to transient time-domain response space using transient stability deviation, breaking the apparent overlap of the two types of defects in steady-state brightness. For anomalies with overlapping features, the frequency domain phase response slope is further used to accurately identify LED sidewall leakage anomalies and TFT driving anomalies. In the LED sidewall leakage anomaly branch, the system determines the specific leakage degree through zero-delay coherence and performs laser sidewall annealing physical repair or corrects the brightness gain coefficient in the Demura compensation lookup table based on the impedance slope ratio. Simultaneously, it adjusts the brightness gain coefficients of adjacent pixels inversely through the difference in brightness gain coefficients to suppress optical waveguide crosstalk. In the TFT driving anomaly branch, the system distinguishes between TFT threshold voltage drift and channel mobility degradation through subthreshold slope, and implements PWM duty cycle electrical compensation or redundancy replacement accordingly. Furthermore, by statistically analyzing the number of occurrences of various anomalies per unit time, the system extends single-pixel diagnosis to production line-level process quality control, providing feedback to correct manufacturing equipment operating parameters and detection parameters, thus suppressing the generation of similar defects at the source. This invention achieves accurate identification and cause-driven correction of two types of pixel-level defects—LED sidewall leakage and TFT degradation—under online detection conditions, avoiding compensation parameter failure and exacerbated display unevenness caused by misjudgment. It significantly improves the accuracy, effectiveness, and production line yield of online correction of brightness consistency in Micro-LED display pixel arrays.

[0060] 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.

Claims

1. An online calibration system for brightness uniformity of a Micro-LED display pixel array based on optical detection, characterized in that, include, The acquisition module is used to acquire optical image data, photon detection data, DC characteristic data, and AC electrical data; A calculation module, connected to the acquisition module, is used to determine the brightness deviation of each pixel, the standard instantaneous stable brightness ratio, and the abnormal instantaneous stable brightness ratio based on the optical image data, and to determine the frequency domain phase response slope based on the AC electrical data. An anomaly detection module, connected to the calculation module, is used to determine an abnormal pixel when the pixel brightness deviation does not fall within the set preset grayscale ratio range, and to determine the instantaneous stability deviation based on the standard instantaneous stable brightness ratio and the abnormal instantaneous stable brightness ratio, and to determine the anomaly type based on the instantaneous stability deviation. The anomaly detection module is also used to determine a single anomaly when the instantaneous stability deviation is less than or equal to a preset instantaneous stability deviation, or to determine a feature overlap anomaly when the instantaneous stability deviation is greater than a preset instantaneous stability deviation, to determine the actual anomaly type based on the frequency domain phase response slope, to determine the current anomaly as an LED sidewall leakage anomaly when the frequency domain phase response slope is less than or equal to a preset frequency domain phase response slope, to determine the zero-delay coherence based on the photon arrival time sequence data in the photon detection data, and to determine the specific cause of the anomaly based on the zero-delay coherence, to determine LED epitaxial sidewall leakage when the zero-delay coherence is less than or equal to a preset zero-delay coherence, or to determine an LED epitaxial sidewall leakage and TFT drift composite anomaly when the zero-delay coherence is greater than a preset zero-delay coherence; Alternatively, when the frequency domain phase response slope is greater than the preset frequency domain phase response slope, the current anomaly is determined to be a TFT driving anomaly. The subthreshold slope is determined based on the DC characteristic data, and the specific cause of the anomaly is determined based on the subthreshold slope. Also, when the subthreshold slope is less than or equal to the preset subthreshold slope, the TFT threshold voltage is determined to be drifting. Or, when the subthreshold slope is greater than the preset subthreshold slope, the TFT drift channel mobility is determined to be degraded. The anomaly detection module is also used to issue correction instructions and detection parameter correction instructions based on the actual anomaly type; The equipment control module, which is connected to the anomaly detection module, is used to control the operation of the Micro-LED manufacturing equipment, correct the abnormal pixels based on the correction instructions of the anomaly detection module, and modify the operating parameters of the Micro-LED manufacturing equipment and the detection parameters of the anomaly detection module based on the instructions of the anomaly detection module.

2. The Micro-LED display pixel array brightness uniformity online correction system according to claim 1, characterized in that, The anomaly detection module is also used to determine a true grayscale map based on the dark field background image, flat field calibration image and LED image in the optical image data, and to determine the average grayscale value of the LED screen based on the true grayscale map, and to determine several pixel grayscale ratios based on the ratio of each pixel in the true grayscale map to the average grayscale value of the LED screen. The anomaly detection module is also used to determine the consistency of each pixel based on the pixel grayscale ratio, and to determine that the pixel brightness is consistent when the pixel grayscale ratio is within the preset grayscale ratio range, or to determine that the pixel is an abnormal pixel when the pixel grayscale ratio is not within the preset grayscale ratio range, and to determine the type of anomaly based on the instantaneous stability deviation.

3. The Micro-LED display pixel array brightness uniformity online correction system according to claim 2, characterized in that, The anomaly detection module is also used to determine the cause of the anomaly based on the instantaneous stability deviation, and to determine the occurrence of a single anomaly when the instantaneous stability deviation is less than or equal to the preset instantaneous stability deviation, and to determine the cause of the anomaly based on the preset rules; or to determine the occurrence of a feature overlap anomaly when the instantaneous stability deviation is greater than the preset instantaneous stability deviation, and to determine the actual anomaly type based on the frequency domain phase response slope.

4. The Micro-LED display pixel array brightness uniformity online correction system according to claim 3, characterized in that, The anomaly detection module is also used to determine the frequency domain phase response slope based on the impedance amplitude data, impedance phase data and the endpoint frequency of the frequency sweep range of the impedance analyzer in the AC electrical data, and to determine the actual anomaly type based on the frequency domain phase response slope. The anomaly detection module is also used to determine the actual anomaly type based on the frequency domain phase response slope, and, when the frequency domain phase response slope is less than or equal to the preset frequency domain phase response slope, to determine that the current anomaly is an LED sidewall leakage anomaly, and to determine the specific cause of the anomaly based on the photon arrival time sequence data in the photon detection data; or, when the frequency domain phase response slope is greater than the preset frequency domain phase response slope, to determine that the current anomaly is a TFT driving anomaly, and to determine the specific cause of the anomaly based on the drain current data and drain voltage data in the DC characteristic data.

5. The Micro-LED display pixel array brightness uniformity online correction system according to claim 4, characterized in that, The anomaly detection module is also used to determine the specific cause of the anomaly based on the zero-delay coherence, and to determine LED epitaxial sidewall leakage when the zero-delay coherence is less than or equal to the preset zero-delay coherence, obtain the coordinates of the abnormal pixel, and issue a laser sidewall annealing command; or, to determine an anomaly of LED epitaxial sidewall leakage and TFT drift combined when the zero-delay coherence is greater than the preset zero-delay coherence, and to correct the brightness gain coefficient in the Demura compensation lookup table inside the Micro-LED display pixel array driver IC based on the ratio of the preset frequency domain phase response slope to the frequency domain phase response slope.

6. The Micro-LED display pixel array brightness uniformity online correction system according to claim 5, characterized in that, The anomaly detection module is also used to determine the impedance slope ratio based on the ratio of the preset frequency domain phase response slope to the frequency domain phase response slope, and to increase the brightness gain coefficient based on the impedance slope ratio, wherein the increase in the brightness gain coefficient is proportional to the impedance slope ratio.

7. The Micro-LED display pixel array brightness uniformity online correction system according to claim 6, characterized in that, The anomaly detection module is also used to determine the difference in brightness gain coefficient based on the difference in brightness gain coefficient before and after correction, and to reduce the adjacent brightness gain coefficients in the Demura compensation lookup table of the adjacent pixels of the abnormal pixel based on the difference in brightness gain coefficient, and the reduction of the adjacent brightness gain coefficients is proportional to the difference in brightness gain coefficient.

8. The Micro-LED display pixel array brightness uniformity online correction system according to claim 4, characterized in that, The anomaly detection module is also used to determine the specific cause of the anomaly based on the subthreshold slope, and to determine TFT threshold voltage drift when the subthreshold slope is less than or equal to the preset subthreshold slope, and to correct the PWM duty cycle of the abnormal pixel driver IC based on the ratio of the minimum value in the preset grayscale ratio range to the pixel grayscale ratio, or to determine TFT drift channel mobility degradation when the subthreshold slope is greater than the preset subthreshold slope, to mark the abnormal pixel and perform redundant replacement.

9. The Micro-LED display pixel array brightness uniformity online correction system according to claim 4, characterized in that, The anomaly detection module is also used to determine a negative grayscale offset ratio based on the ratio of the minimum value of the preset grayscale ratio range to the pixel grayscale ratio, and to increase the PWM duty cycle based on the negative grayscale offset ratio, wherein the increase in the PWM duty cycle is proportional to the negative grayscale offset ratio.

10. The Micro-LED display pixel array brightness uniformity online correction system according to claim 4, characterized in that, The anomaly detection module is also used to determine a number of anomalies based on the number of times various anomalies occur per unit time. The anomaly detection module is also used to determine whether the production line equipment is abnormal based on the number of anomalies, and to determine that the production line equipment is working normally and maintain monitoring when the number of anomalies is less than the preset anomaly number threshold, or to determine that the production line equipment is working abnormally when the number of anomalies is greater than or equal to the preset anomaly number threshold, and to output the corresponding production line equipment maintenance notice based on the type of anomaly.

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