Method and device for diagnosing response time abnormity of liquid crystal display panel

Abstract

The invention belongs to the technical field of liquid crystal display, and particularly relates to a diagnosis method and device for response time abnormity of a liquid crystal display panel, and the method comprises the steps: building a corresponding relation between a pixel position and a code through single-pixel-level addressing, and synchronously collecting a driving micro-electric parameter, a light response micro-parameter and a liquid crystal molecule micro-state parameter of each pixel; based on qualified panel sample data of the same model, constructing a pixel-level coupling association reference library comprising a standard value, a single-parameter deviation threshold value and a coupling association degree threshold value; and an abnormal micro-region is positioned, an abnormal core cause is analyzed and judged in combination with coupling correlation degree, and finally a diagnosis result is output. The device comprises a high-precision motion platform, a pixel-level precise addressing module, a customized micro-sensing detection module and the like, and non-contact synchronous acquisition and precise analysis are realized. According to the invention, pixel-level anomaly positioning and cause accurate determination can be realized, the refinement degree and reliability of diagnosis are improved, and industrial large-scale detection requirements are met.

Description

Diagnostic method and device for abnormal response time of liquid crystal display panel Technical Field

[0001] This invention belongs to the field of liquid crystal display technology, specifically relating to a diagnostic method and apparatus for abnormal response time of liquid crystal display panels. Background Technology

[0002] In the manufacturing and use of LCD panels, abnormal response time is one of the core issues affecting display quality, directly leading to problems such as image ghosting and stuttering, severely reducing product yield and user experience. Traditional diagnostic methods mostly rely on macroscopic inspection techniques, which can only determine whether there is an abnormality in the overall panel, but cannot accurately locate abnormal micro-areas at the single pixel level, making it difficult to meet the requirements of high-precision inspection.

[0003] In the existing technology, some diagnostic methods only collect a single type of parameter (such as photoresponse parameters or electrical parameters for analysis), ignoring the coupling relationship between the driving circuit, the state of liquid crystal molecules and the photoresponse output, which leads to inaccurate determination of the cause of the abnormality and often results in misdiagnosis or missed diagnosis.

[0004] Meanwhile, traditional diagnostic methods lack standardized benchmark libraries, parameter threshold settings are highly subjective, and the consistency and accuracy of test data are insufficient, resulting in low diagnostic efficiency. Therefore, a diagnostic method and device for abnormal response time of liquid crystal display panels are needed. Summary of the Invention

[0005] In view of the above-mentioned shortcomings in the prior art, the present invention provides a method and apparatus for diagnosing abnormal response time of liquid crystal display panels, so as to solve the problems in the background art.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: a diagnostic method for abnormal response time of liquid crystal display panels, comprising the following steps: Step 1: performing single-pixel-level addressing of the pixel array of the panel under test, assigning a unique addressing code to each pixel, and establishing a correspondence between pixel position and addressing code; Step 2: outputting pixel-level independent driving pulse signals to the panel under test based on the addressing codes, and collecting pixel driving micro-electrical parameters, pixel light response micro-parameters, and pixel liquid crystal molecule micro-state parameters of each pixel region through a micro-nano level non-contact sensing unit, with the acquisition timing synchronized with the driving pulse signal; Step 3: acquiring pixel three-parameter data of qualified panel samples of the same model, calculating the standard value and single-parameter deviation threshold of the pixel three-parameter data, and calculating the pixel driving micro-electrical parameters and pixel light response micro-parameters, image... Step 4: The coupling correlation degree between the pixel optical response micro-parameters and the pixel liquid crystal molecule micro-state parameters is determined, and a pixel-level coupling correlation benchmark library is constructed based on this. Step 5: The pixel optical response micro-parameters of each collected pixel are compared with the standard values ​​of pixel optical response micro-parameters in the benchmark library to identify micro-regions with abnormal response times, mark their physical locations, and extract the pixel three-parameter data of the abnormal micro-regions. Step 6: The pixel three-parameter data of the abnormal micro-regions are input into the coupling correlation model to calculate the coupling correlation degree between the pixel driving micro-electrical parameters and the pixel optical response micro-parameters, and between the pixel optical response micro-parameters and the pixel liquid crystal molecule micro-state parameters. The results are compared with the coupling correlation threshold in the benchmark library to determine the core cause of the abnormality according to the rules. The diagnostic results include the addressing code of the abnormal micro-region, physical location, core cause, and degree of deviation of the parameter indicators.

[0007] Furthermore, the pixel driving micro-electrical parameters in step 2 include the input voltage, conduction current, and pulse response delay time of a single pixel driving terminal; the pixel optical response micro-parameters include the grayscale rise time, grayscale fall time, and optical response waveform distortion rate of a single pixel; and the pixel liquid crystal molecule micro-state parameters include the deflection angle, deflection response speed, and molecule arrangement uniformity of liquid crystal molecules within a single pixel.

[0008] Furthermore, the standard value in step 3 is the arithmetic mean of the same index among qualified samples of the same model, calculated using the following formula: in, The standard value for the same indicator among qualified samples of the same model. The number of qualified sample panels, This represents the total number of pixels on a single panel. This is the feature value of a certain indicator collected from the m-th pixel in the k-th sample panel.

[0009] Furthermore, the correlation coefficient is calculated using the Pearson correlation coefficient method, and the calculation formula is as follows: in, The correlation coefficient, or coupling degree, between the two types of parameters. These are the feature acquisition values ​​for two types of pixel parameters, respectively. , These are the standard mean values ​​of the two types of pixel parameters, respectively.

[0010] Furthermore, the rules for determining the core cause of the anomaly in step 5 are as follows: if the deviation between the pixel driving micro-electrical parameters and the corresponding standard values ​​in the reference library exceeds the single parameter deviation threshold and the correlation between the driving and photoresponse parameters is lower than the corresponding coupling correlation threshold, it is determined to be a pixel driving micro-circuit fault; if the deviation between the pixel liquid crystal molecule micro-state parameters and the corresponding standard values ​​in the reference library exceeds the single parameter deviation threshold and the correlation between the photoresponse and molecule state parameters is lower than the corresponding coupling correlation threshold, it is determined to be a pixel-level liquid crystal molecule micro-defect; if only the deviation between the pixel photoresponse micro-parameters and the corresponding standard values ​​in the reference library exceeds the single parameter deviation threshold and the correlation between the two types of parameters is not lower than the corresponding coupling correlation threshold, it is determined to be a pixel-level liquid crystal cell thickness micro-deviation.

[0011] Furthermore, the formula for calculating the single-parameter deviation threshold is as follows: in, For the single-parameter deviation threshold of the indicator, denoted as the standard deviation of the parameter index.

[0012] Furthermore, in step 5, the deviation of the parameter index is the relative deviation between the actual collected values ​​of the three pixel parameters and the corresponding standard values ​​in the benchmark library.

[0013] Furthermore, the pixel-level coupling correlation benchmark library is stored according to addressing codes. Each addressing code corresponds to the associated storage of three-parameter standard values, single-parameter deviation thresholds, and drive-light response and light response-molecular state coupling correlation thresholds. A diagnostic device for abnormal response time of a liquid crystal display panel includes a high-precision motion platform, a pixel-level precise addressing module, a submicron-level coaxial alignment module, a customized micro-sensor detection module, an ultra-high frequency synchronous acquisition and signal conditioning module, a pixel-level coupling correlation benchmark library module, a micro-region anomaly preliminary judgment module, a coupling correlation analysis and cause localization module, and a precise diagnostic result output module. The high-precision motion platform realizes coarse positioning of the panel under test and the detection module. The pixel-level precise addressing module realizes single-pixel-level addressing, code allocation, and mapping of physical coordinates to addressing codes, and outputs pixel-level independent drive pulse signals. The submicron-level coaxial alignment module... The module works in conjunction with a high-precision motion platform to achieve secondary positioning, completing sub-micron level alignment between the detection module and the target single pixel. The customized micro-sensor detection module integrates a microelectrode probe, a microscale photodetector, and a laser micro-direction finding sensor to achieve non-contact acquisition of all indicators. The ultra-high frequency synchronous acquisition and signal conditioning module realizes synchronous acquisition, conditioning, and digital conversion of sensor signals. The pixel-level coupling correlation benchmark library module stores sample standard values, single-parameter deviation thresholds, and coupling correlation degree thresholds, supporting rapid retrieval of benchmark parameters by addressing code. The micro-region anomaly preliminary judgment module determines abnormal micro-regions according to rules and extracts full feature data. The coupling correlation analysis and cause localization module calculates the actual coupling correlation degree and determines the core cause according to rules. The accurate diagnosis result output module parses the diagnostic data to realize the visualization display, data export, and printing of diagnostic results.

[0014] Furthermore, the customized micro-sensing detection module adopts a multi-physics field coaxial integrated probe design, integrating the microelectrode probe, microscale photodetector, and laser micro-direction finding sensor along the same optical axis or central axis to ensure the spatial consistency of the detection of electrical, optical, and molecular state parameters in the same pixel area.

[0015] Furthermore, the ultra-high frequency synchronous acquisition and signal conditioning module is equipped with a synchronous clock generator. The trigger signal of the synchronous clock generator is connected to the drive pulse signal source, and when the rising edge of the drive pulse signal is detected, all acquisition channels are simultaneously triggered to start data acquisition.

[0016] Compared with existing technologies, this invention has the following advantages: 1. This invention achieves spatiotemporal synchronous and precise acquisition of three core parameters of a single pixel-level micro-area driving micro-electrical, optical response, and liquid crystal molecule micro-state by combining pixel-level precise addressing, submicron-level coaxial alignment, and micro-nano-level non-contact sensing units. This breaks through the technical limitations of traditional whole-screen coarse-grained detection, effectively capturing easily masked pixel-level hidden anomalies, providing complete and reliable parameter data support for the precise tracing of the causes of pixel-level micro-area response time anomalies, and significantly improving the accuracy and coverage of liquid crystal display panel response time anomaly detection; 2. By constructing a pixel-level coupled correlation benchmark library, and combining the quantitative judgment method of parameter deviation exceeding the threshold with the coupling correlation analysis of the Pearson correlation coefficient method, a system is established... The system employs a dual-core anomaly determination rule based on parameter deviation and coupling correlation, enabling unique and precise localization of three core causes: pixel-driven microcircuit faults, pixel-level liquid crystal molecule micro-defects, and pixel-level liquid crystal cell thickness micro-deviations. This solves the technical problems of ambiguous anomaly cause determination and high rates of false positives and false negatives in traditional technologies, significantly improving the accuracy and reliability of locating anomalies in the response time of pixel-level micro-areas of LCD panels. Furthermore, by quantifying parameter deviation into relative deviations and clarifying the determination criteria, the system outputs complete diagnostic results including the precise location of the abnormal micro-area, the core cause, quantified parameter deviation data, and correlation impact analysis. This provides a clear pixel-level targeted repair basis for LCD panel anomaly repair, replacing the traditional whole-screen unified repair method, and significantly improving panel repair efficiency and reducing repair costs. Attached Figure Description

[0017] Figure 1 is a schematic diagram of the diagnostic method for abnormal response time of liquid crystal display panel according to the present invention; Detailed Description of Embodiments To enable those skilled in the art to better understand the present invention, the technical solution of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0018] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual images. They should not be construed as limiting the scope of this application. To better illustrate the embodiments of the present invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual dimensions of the product. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0019] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "inner," and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present application. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0020] In the description of this invention, unless otherwise explicitly specified and limited, the term "connection" or similar designation indicating a connection between components should be interpreted broadly. For example, it can refer to a fixed connection, a detachable connection, or an integral part; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can refer to the internal communication between two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0021] Example 1: As shown in Figure 1, the diagnostic method for abnormal response time of a liquid crystal display panel according to the present invention includes the following steps: Step 1: Perform single-pixel level addressing on the pixel array of the panel under test, assign a unique addressing code to each pixel, and establish a correspondence between pixel position and addressing code; specifically, perform single-pixel level row and column matrix precise addressing on the pixel array of the liquid crystal display panel under test, and assign a unique addressing code to each pixel. ,in, For line numbers, Column numbers are positive integers; establish pixel physical coordinates. Addressing coding The correspondence is such that the addressing accuracy meets the single-pixel level detection requirements, enabling independent driving and detection positioning of any single pixel.

[0022] Step 2: Based on addressing encoding, output pixel-level independent driving pulse signals to the panel under test. Through a micro-nano level non-contact sensing unit, collect the pixel driving micro-electrical parameters, pixel photoresponse micro-parameters, and pixel liquid crystal molecule micro-state parameters of each pixel area, and the acquisition timing is synchronized with the driving pulse signal. Further, the pixel driving micro-electrical parameters in Step 2 include the input voltage, conduction current, and pulse response delay time of a single pixel driving end; the pixel photoresponse micro-parameters include the grayscale rise time, grayscale fall time, and photoresponse waveform distortion rate of a single pixel; the pixel liquid crystal molecule micro-state parameters include the deflection angle, deflection response speed, and molecule uniformity of liquid crystal molecules within a single pixel.

[0023] Pixel-driven micro-electrical parameters It reflects the electrical signal transmission characteristics of the pixel driving circuit and represents the real-time electrical parameters of the pixel driving end, including three core quantization indicators; the input voltage of the pixel driving end. (Unit: V), directly reflects the voltage supply capability of the driving circuit; pixel driving terminal conduction current. (Unit: A), directly reflects the loop conduction characteristics of the driving circuit; pixel driving end pulse response delay time. (Unit: ns), reflecting the signal transmission delay characteristics of the driving circuit.

[0024] Pixel light response micro-parameters It reflects the light output characteristics of a pixel after being excited by a driving electrical signal, and is a real-time light parameter of the pixel display area, including three core quantitative indicators: grayscale rise time. (Unit: ms) refers to the light intensity response time of a pixel from grayscale 0 to grayscale 255, which is the core indicator of response time anomalies; grayscale descent time (Unit: ms) refers to the light intensity response time of a pixel dropping from grayscale 255 to grayscale 0, which is the core indicator of response time anomalies; light response waveform distortion rate. (Dimensionless) reflects the degree of deviation between the pixel light intensity response waveform and the standard square wave, and characterizes the stability of the light response.

[0025] Pixel liquid crystal molecule microstate parameters It reflects the microscopic motion state of liquid crystal molecules within a pixel after being driven by an electrical signal, and is a molecular dynamics parameter of the pixel liquid crystal layer, including three core quantitative indicators: average deflection angle of liquid crystal molecules. (Unit: °), reflecting the degree of deflection of liquid crystal molecules under the influence of an electric field, is the core microscopic indicator of electroluminescence; liquid crystal molecule deflection response speed (Unit: ° / ns), reflecting the deflection rate of liquid crystal molecules as the driving electric field changes, directly determining the photoresponse time; uniformity of liquid crystal molecule arrangement. , which is the standard deviation of the deflection angle of liquid crystal molecules at different positions within a pixel, reflects the consistency of the molecular arrangement. The smaller the standard deviation, the higher the uniformity.

[0026] Specifically, based on addressing coding to drive the target pixel, a sub-micron coaxial alignment system is used to achieve coaxial confocal alignment of the microelectrode probe, microscale photodetector, laser micro-direction finding sensor, and target single pixel. Then, a non-contact synchronous acquisition architecture is used for acquisition, with the acquisition timing strictly synchronized with the rising edge of the driving pulse signal, and the synchronization delay meeting pixel-level detection requirements. The microelectrode probe acquires the target pixel's... Microscale photodetectors collect target pixels The laser micro-direction finding sensor acquires target pixel data based on the principle of polarized light interference. All parameters acquired are digitized and quantized values, stored in temporary data units and associated with corresponding addressing codes.

[0027] Step 3: Obtain pixel three-parameter data from qualified panel samples of the same model, calculate the standard values ​​and single-parameter deviation thresholds of the pixel three-parameter data, and calculate the coupling correlation between pixel driving micro-electrical parameters and pixel photoresponse micro-parameters, and between pixel photoresponse micro-parameters and pixel liquid crystal molecule micro-state parameters. Based on this, determine the coupling correlation threshold and construct a pixel-level coupling correlation benchmark library; select a number of qualified liquid crystal display panel samples of the same model. For each pixel of each sample, steps 1-2 are performed to collect the three-parameter data of all sample pixels. A pixel-level coupled benchmark library is constructed based on sample statistical training. All sample training formulas, formula parameters, and statistical rules are publicly disclosed as follows: Furthermore, the standard value is the arithmetic mean of the same index among qualified samples of the same model, calculated using the following formula: in, The standard value for the same indicator among qualified samples of the same model, such as Sample standard value , Sample standard value ; The number of qualified sample panels, This represents the total number of pixels on a single panel. The value of a certain indicator feature of the m-th pixel in the k-th sample panel; The number is the sample panel number. ; This refers to the pixel number within a single panel. Calculate the pixel three-parameter data according to the above formulas. The standard values ​​of all nine quantitative indicators are obtained by taking the sample standard values ​​of each indicator: .

[0028] Furthermore, for qualified samples of the same model, the sample standard deviation is calculated for the same quantization index of all pixels. And three times the standard deviation is used as the single-parameter deviation threshold for this indicator, calculated as follows: in, The single-parameter deviation threshold of the indicator reflects the natural fluctuation range of the indicator in qualified samples; is the standard deviation of the parameter index, and is the critical value for anomaly detection of the index.

[0029] Specifically, the determination of the single-parameter deviation threshold (3 times the standard deviation) is based on the following criteria: The single-parameter deviation threshold is used to determine whether the pixel parameters of the panel under test are within the normal process fluctuation range. Its determination is based on the Laida criterion in statistics, i.e. Principles, here The same values ​​are represented as standard deviations, and the specific determination process is as follows: Under the assumption of a normal distribution, in large-scale industrial production, various physical characteristic parameters of liquid crystal display panels (such as driving voltage, light response time, molecular deflection angle, etc.) are usually affected by a large number of independent and small random factors. According to the central limit theorem, the parameter collection values ​​of these qualified products generally follow or approximately follow a normal distribution.

[0030] Standard deviation Describes the sample data relative to the arithmetic mean (standard value) The degree of dispersion of ). The smaller the value, the more the parameters are concentrated around the standard value, and the more stable the process. A larger value indicates greater parameter fluctuation. This represents a probability coverage of 3 standard deviations, based on the probability characteristics of a normal distribution: values ​​falling within the interval... The probability of the value falling within the range is approximately 68.27%; the value falling within the range... The probability of it falling within the range is approximately 95.45%; the value falls within the range The probability of the data point falling within the range of the standard value is approximately 99.73%. Based on the characteristics of a normal distribution, the data point falls within a range to the left and right of the standard value. Range (i.e., deviation not exceeding) The probability within the range is 99.73%. Therefore, the threshold for deviation is directly set to... This means that any deviation exceeding this limit is considered an extremely low probability event (occurring with a probability of only 0.27%), and is thus judged as an abnormal defect.

[0031] When the measured value of a certain pixel parameter in the panel under test exceeds When the deviation falls within a certain range, according to the Raida criterion, there is sufficient reason to believe that the deviation is no longer a normal random process fluctuation, but is caused by systematic errors or specific abnormal factors (such as short circuits in the driving circuit, abnormal cell thickness, etc.). Therefore, using three times the standard deviation as the single-parameter deviation threshold can sensitively and accurately capture true abnormal pixels while greatly eliminating normal process interference.

[0032] Based on the deviation, three times the standard deviation of the statistical data of qualified samples is used as the single-parameter deviation threshold for this indicator; this threshold is a limit value reflecting the maximum permissible deviation. It represents the limit of deviation of a single pixel parameter value from the standard value under normal process fluctuations. The actual value of a certain indicator of a pixel parameter in the panel under test is calculated. Compared with standard value the absolute deviation between , directly compare this absolute deviation with the single-parameter deviation threshold ; that is, if the absolute deviation is less than or equal to the single-parameter deviation threshold , it is determined that the pixel parameter is within the normal process fluctuation range and is regarded as qualified; if the absolute deviation is greater than the single-parameter deviation threshold , it is determined that the deviation degree of the pixel parameter exceeds the limit allowed by the normal process and is regarded as abnormal, that is, deviating from the standard.

[0033] Furthermore, calculate the single-parameter deviation thresholds of all 9 quantization indexes in the pixel three-parameter data respectively according to the above formula, and obtain the threshold set of each index: . ]>

[0034] Furthermore, first calculate, in the qualified samples, the and of the same pixel and of the same pixel, to reflect the linear coupling correlation strength between the two types of parameters; the coupling correlation degree is calculated using the Pearson correlation coefficient method, calculate the coupling correlation degree and , and of the same pixel , and the calculation formula is as follows: Among them, is the correlation coefficient between the two types of parameters, that is, the coupling correlation degree whose result naturally takes values in , and this conclusion can be verified by both mathematical inequality derivation and physical meaning interpretation, which belongs to the prior art The closer it is to 1, the stronger the linear coupling correlation between the two types of parameters is the acquisition value of the th feature of the type of pixel parameter is the acquisition value of the th feature of the type of pixel parameter is the standard value mean of the

[0035] Specifically, is the standard value mean of the is ​The standard mean of the pixel parameters is the arithmetic mean of the standard values ​​of the three original core indicator samples of the corresponding pixel parameters. The general calculation formula is: ;in, For this type of parameter The sample standard values ​​of the original core indicators are retrieved from the pixel-level coupled and correlated benchmark library.

[0036] When calculating yes for Three indicators , for Three indicators Expanding to a 9-dimensional feature set for association calculation improves association accuracy. yes for Three indicators , for Three indicators The feature set is expanded to a 9-dimensional feature set for association calculation, which improves the accuracy of association.

[0037] Specifically, the purpose of calculating the coupling correlation degree is to accurately reflect the driving microelectronics. With light response Photoresponse With molecular state The overall coupling relationship provides a reliable quantitative basis for locating the causes of anomalies, rather than a local correlation analysis between single indicators; using only 3D calculation will result in the loss of correlation information and the obscuring of the overall coupling relationship by local biases. Expanding to 9D can fundamentally solve this problem; firstly, 3 indicators ( Input voltage, On current, Pulse delay is not independent; rather, they influence each other and collectively reflect the overall operating state of the driving microcircuit (e.g., an abnormal input voltage will simultaneously cause deviations in conduction current and pulse delay); similarly, , The three indicators together reflect the overall characteristics of pixel light response and pixel liquid crystal molecule microstate. However, a one-to-one calculation in 3D ignores the interactions between indicators within a single parameter class, making it impossible to analyze coupling relationships based on the overall characteristics of the parameters. A 9-dimensional feature set can completely cover this type of interaction; secondly, the 9-dimensional feature set... All indicators and Full cross-match of all indicators can reflect Any indicator pair The coupling effect of arbitrary indicators is mitigated to avoid the problem of misjudging the overall coupling relationship due to the matching deviation of a single indicator in 3D one-to-one calculation. Similarly, , The same applies to LCD panels; thirdly, minor environmental interferences (such as temperature and vibration) during LCD panel testing may cause slight deviations in the collected values ​​of individual indicators. In 3D calculations, these local deviations directly affect the correlation results. (In LCD panels...) and , The role of this is a multi-parameter coordinated physical process; the voltage, current, and delay of the driving circuit jointly determine the deflection state of the liquid crystal molecules, which in turn synchronously affect the rise time, fall time, and waveform distortion rate of the photoresponse, rather than a single driving index corresponding to a single photoresponse index. The full cross-correlation of the 9-dimensional feature set perfectly matches the multi-parameter coordinated characteristics of this physical process, ensuring the physical rationality of the calculation results.

[0038] In a specific implementation, the expansion process only replicates the 3-dimensional indicators of the same type of parameters in equal dimensions to form 9 dimensions, without adding or modifying any data, thus ensuring the authenticity of the original collected data. Based on the three original indicators, it is expanded to nine dimensions by repeating the process three times consecutively. Each indicator corresponds to three other indicators, achieving full cross-coverage. The original indicators are expanded as follows: Based on the expansion, a standard value set of 9-dimensional index benchmark library is obtained: The actual collected values ​​of the 9-dimensional indicators corresponding to the sample: .

[0039] Using the same extended logic, we can obtain , The original index extension set: , According to the extension , The standard value set of the 9-dimensional indicator benchmark library: , ,as well as , Actual collected values ​​of the 9-dimensional indicators corresponding to the sample: .

[0040] .

[0041] Substituting the above parameters into the Pearson correlation coefficient formula yields the coupling degree. , .

[0042] Furthermore, for all qualified sample pixels , Sort them in ascending order and take the quantile of 0.9 as the coupling correlation threshold. .

[0043] Coupling correlation threshold Determination basis; this value is comprehensively determined based on large-sample statistical laws, the physical principle of electro-optical variation of liquid crystal panels, industry process characteristics, and multiple sets of comparative experiments. Specifically, The sample size is much larger than the minimum effective sample size of statistical analysis, which can fully reflect the natural coupling correlation law of the three parameters of pixels of the same model panel and avoid small-sample statistical deviation; due to the slight differences in manufacturing processes, even for qualified panels, the parameter coupling correlation between different pixels will fluctuate within a certain range, but this fluctuation usually follows a specific statistical distribution law. Under normal circumstances, there should be a strong positive correlation between the parameters of qualified pixels, and the correlation degree values are usually high and concentrated in a certain range; the lower quantile 0.9 means that the correlation coefficient between the parameters of 90% of the qualified pixels ≥ 0.9, and only 10% of the qualified pixels show Normal fluctuations. Although the samples with the lowest 10% of the values belong to qualified panels, their coupling is relatively weak, representing the worst but acceptable limit state of coupling allowed by the process. Using this as the threshold can accurately divide normal coupling correlation and abnormal coupling breakage; the electro-optical variation principle of liquid crystal panels determines the strong linear correlation of driving electrical signal → liquid crystal molecule deflection → light response output. Qualified pixels Generally fall within the range of 0.9 - 1.0, and this threshold highly matches the inherent physical characteristics of the panel.

[0044] Furthermore, a pixel-level coupling correlation benchmark library classified and stored by addressing coding is constructed. Each addressing coding in the benchmark library corresponds to the storage of: sample standard values of 9 quantization indexes, single-parameter deviation thresholds of 9 quantization indexes, and coupling correlation thresholds to provide a quantitative basis for subsequent abnormal determination and cause analysis.

[0045] Step 4: Compare each pixel light response microparameter collected with the pixel light response microparameter standard value in the benchmark library, determine the micro-region with abnormal response time, mark its physical position, and extract the pixel three-parameter data of this abnormal micro-region; compare the actual collected value of the quantization index of the pixel light response microparameter to be measured with the sample standard value of the quantization index corresponding to the pixel light response microparameter in the benchmark library If it meets , it is determined that this index deviates from the standard; for the three indexes of the pixel light response microparameter to be measured perform the above comparison one by one. If any one index deviates from the standard, it is determined that the pixel to be measured is a micro-region with abnormal response time; is the core characterization parameter of abnormal response time. Based on this as the initial judgment basis, accurate screening of abnormalities can be achieved.

[0046] ​For the pixels in the identified abnormal micro-regions, mark the physical location coordinates corresponding to their addressing codes. And extract the three parameters of the pixel. , , The actual collected values ​​of all nine quantitative indicators are used for subsequent causal identification.

[0047] Step 5: Input the pixel three-parameter data of the abnormal micro-region into the coupling correlation model, calculate the coupling correlation degree between the pixel driving micro-electrical parameters and the pixel photoresponse micro-parameters, and between the pixel photoresponse micro-parameters and the pixel liquid crystal molecule micro-state parameters, compare it with the coupling correlation degree threshold in the benchmark library, and determine the core cause of the abnormality according to the rules; output the diagnostic results including the abnormal micro-region addressing code, physical location, core cause, and degree of deviation of parameter indicators.

[0048] For pixel three-parameter data of abnormal micro-regions, first... , The individual quantitative indicators are compared one by one, and then the coupling correlation analysis is performed. The core causes of the anomalies are determined by combining the rules, as follows: First, according to the comparison rules in step 4, the individual quantitative indicators are compared one by one. Three indicators , Three indicators Compare each indicator with the corresponding indicator in the benchmark library to determine... , Whether the indicators deviate from the standards.

[0049] Then, based on the Pearson correlation coefficient formula, the actual coupling correlation degree of this anomalous micro-region is calculated. Substituting the pixel three-parameter data after the extended logic into the formula, we get the calculation formula as follows: in, The first micro-electrical parameter of the pixel drive of the test board The collected values ​​of each feature, The first of the micro-parameters of the pixel light response of the test board The collected values ​​of each feature, The first test of the microstate parameters of the pixel liquid crystal molecules on the test board The collected values ​​of each feature, as described above. ; The average value of the pixel-driven micro-electrical parameters is the standard value of the pixel-driven micro-electrical parameters of qualified panels of the same model in the benchmark library. , , The arithmetic mean is obtained; that is ; The standard mean value of the pixel light response micro-parameters is obtained from the pixel driving micro-electrical parameters of qualified panels of the same model in the benchmark library. , , The arithmetic mean is obtained; The standard average value of the micro-state parameters of the pixel liquid crystal molecules is derived from the pixel driving micro-electrical parameters of qualified panels of the same model in the benchmark library. , , The arithmetic mean is obtained.

[0050] Combination , The deviation of the indicator from the actual coupling correlation is determined according to the judgment rules for the core causes of the anomaly; if the pixel-driven microelectronic parameters If any of the indicators deviates from the standard, and If the core cause of the anomaly is determined to be a fault in the pixel driving microcircuit, the abnormal driving signal leads to a break in the coupling correlation, which in turn causes abnormal light response; if the pixel liquid crystal molecule microstate parameters If any of the indicators deviates from the standard, and If the core cause of the anomaly is determined to be a micro-defect in the pixel liquid crystal molecules, the abnormal micro-state of the liquid crystal molecules leads to the breakage of the coupling correlation, which in turn causes the abnormal light response; if only the pixel light response micro-parameters are present... If any of the indicators deviates from the standard, , None of the indicators deviated from the standards, and , If the core cause of the abnormality is determined to be a slight deviation in the thickness of the liquid crystal cell at the pixel level, the cell thickness deviation is a physical structural deviation that does not disrupt the coupling relationship between electricity, molecules and light, but directly leads to abnormal light response time.

[0051] Furthermore, the rules for determining the core cause of the anomaly are as follows: if the deviation of the pixel driving micro-electrical parameters from the corresponding standard values ​​in the reference library exceeds the single parameter deviation threshold and the correlation between the driving and photoresponse parameters is lower than the corresponding coupling correlation threshold, it is determined to be a pixel driving micro-circuit fault; if the deviation of the pixel liquid crystal molecule micro-state parameters from the corresponding standard values ​​in the reference library exceeds the single parameter deviation threshold and the correlation between the photoresponse and molecule state parameters is lower than the corresponding coupling correlation threshold, it is determined to be a pixel-level liquid crystal molecule micro-defect; if only the deviation of the pixel photoresponse micro-parameters from the corresponding standard values ​​in the reference library exceeds the single parameter deviation threshold and the correlation between the two types of parameters is not lower than the corresponding coupling correlation threshold, it is determined to be a pixel-level liquid crystal cell thickness micro-deviation.

[0052] Furthermore, the deviation of the parameter index is the relative deviation between the actual collected values ​​of the three pixel parameters and the corresponding standard values ​​in the benchmark library, and the calculation formula is as follows: in, The degree of deviation of the parameter index, These are the actual collected values ​​of the parameter indicators. These are the sample standard values ​​of the corresponding parameter indicators in the benchmark library, which intuitively reflect the deviation of the indicators.

[0053] Specifically, the criterion for determining relative deviation is based on the single-parameter deviation threshold of that parameter in the benchmark library. Corresponding relative deviation of the benchmark The core judgment criterion is the relative deviation of a certain parameter index. When this happens, the indicator is deemed to deviate from the standard; The formula is obtained through calculation as follows: in, This represents the relative deviation corresponding to a single parameter deviation threshold. If multiple indicators deviate from the standard, the deviation level is determined by the magnitude of the relative deviation.

[0054] when When is the general deviation, when When this occurs, it is judged as a serious anomaly, indicating that the parameter deviation has significantly affected the panel response time, and the cause corresponding to this indicator needs to be investigated and repaired first. The 50% judgment value is determined as follows: liquid crystal molecule deflection, driving microcircuit operation, and light response output all have inherent physical operating ranges. When the relative deviation of the parameter exceeds 50%, it has broken through the normal physical operating threshold of the pixel, which will directly lead to irreversible and significant degradation of the liquid crystal molecule deflection characteristics and driving electrical signal transmission characteristics. After investigation... A large sample statistical analysis of 500 qualified LCD panels of different models showed that the deviations of various parameters of qualified pixels caused by natural process fluctuations and environmental interference were all controlled within the reference relative deviation corresponding to the single parameter deviation threshold. Within this range, and with a maximum deviation not exceeding 30%, the 50% judgment value far exceeds the deviation range of normal industry processes, enabling precise differentiation between ordinary deviations and severe anomalies; correlation experiments were conducted on the influence of parameter deviations and response times on different models of LCD panels, and the statistical results show that when When the parameter deviation has a small impact on pixel response time, the panel display effect is not significantly degraded; when At this time, parameter deviation is strongly correlated with pixel response time degradation, and the panel shows obvious display abnormalities such as ghosting and frame skipping. 50% is the critical value for the abrupt change in the correlation between parameter deviation and response time.

[0055] A diagnostic device for abnormal response time of a liquid crystal display panel includes a high-precision motion platform, a pixel-level precise addressing module, a submicron-level coaxial alignment module, a customized micro-sensor detection module, an ultra-high frequency synchronous acquisition and signal conditioning module, a pixel-level coupling correlation reference library module, a micro-area anomaly preliminary judgment module, a coupling correlation analysis and cause localization module, and a precise diagnostic result output module. The high-precision motion platform achieves coarse positioning of the panel under test and the detection module, serving as the basic support unit for the device and achieving coarse positioning of the panel under test and the detection module with positioning accuracy meeting single-pixel-level detection requirements. The panel under test is fixed by vacuum adsorption to ensure panel flatness and avoid physical damage to the panel during the positioning process.

[0056] The pixel-level precise addressing module realizes single-pixel-level addressing, encoding allocation, and mapping of physical coordinates to addressing codes, and outputs pixel-level independent driving pulse signals; adapted to step 1 of the method, it realizes single-pixel-level row and column matrix addressing, unique addressing code allocation, and establishes a one-to-one mapping between pixel physical coordinates and addressing codes; it can output pixel-level independent driving pulse signals to realize independent driving of any single pixel.

[0057] The submicron-level coaxial alignment module works with a high-precision motion platform to achieve secondary positioning, completing the submicron-level alignment between the detection module and the target single pixel; it also works with the high-precision motion platform to achieve coarse positioning plus fine alignment in secondary positioning; it adopts a coaxial confocal architecture, with the laser optical path of the laser micro-direction sensor as the central optical path, so that the effective detection or focusing areas of the three types of sensors converge at the geometric center of the target pixel, achieving submicron-level precise alignment and avoiding cross-pixel detection and signal interference.

[0058] The customized micro-sensing detection module integrates a microelectrode probe, a microscale photodetector, and a laser micro-orientation sensor, enabling non-contact acquisition of all indicators. It is compatible with step 2 of the method and serves as the core detection unit of the device. The integrated microelectrode probe, microscale photodetector, and laser micro-orientation sensor utilize a coaxial confocal architecture and feature electromagnetic shielding and signal isolation design to prevent interference between electrical and optical signals. The effective detection or focusing areas of all three types of sensors match the single-pixel size of the panel, achieving… , , All quantitative indicators are collected non-contactly.

[0059] The ultra-high frequency synchronous acquisition and signal conditioning module realizes the synchronous acquisition, conditioning, and digital conversion of sensor signals; it is the core signal processing unit of the device; it includes a global clock generation unit, a low-jitter clock distribution unit, a heterogeneous signal conditioning circuit, and a high-speed data transmission unit; it adopts a global clock synchronization, heterogeneous signal conditioning, and parallel data transmission method to ensure the synchronous acquisition accuracy and signal integrity of three heterogeneous sensor signals, the acquisition timing is strictly synchronized with the rising edge of the drive pulse signal, and the synchronization delay meets the pixel-level detection requirements; it converts the acquired analog signals into digital quantized values ​​and transmits them to subsequent modules.

[0060] The pixel-level coupling correlation benchmark library module stores sample standard values, single-parameter deviation thresholds, and coupling correlation thresholds, and supports rapid retrieval of benchmark parameters by addressing code. The pixel-level coupling correlation benchmark library module is the core data storage unit of the device. It uses high-speed storage media and stores all quantitative index sample standard values, single-parameter deviation thresholds, and coupling correlation thresholds of qualified samples of the same model according to addressing code. It supports rapid retrieval of corresponding benchmark parameters by addressing code, and the retrieval response time meets the detection efficiency requirements.

[0061] The micro-region anomaly initial judgment module identifies abnormal micro-regions according to rules and extracts pixel three-parameter feature data; it has a built-in single-index comparison algorithm that compares the pixels to be tested according to the method steps. The actual collected values ​​of the indicators are compared with the corresponding parameters in the benchmark library to automatically identify micro-regions with abnormal response times; the addressing codes and physical locations of abnormal pixels are marked, their full feature data is extracted and transmitted to subsequent modules.

[0062] The coupling correlation analysis and causal localization module calculates the actual coupling correlation degree and determines the core cause according to rules. This module is the core analysis unit of the device. It incorporates a Pearson correlation coefficient calculation algorithm and core cause determination rules. First, it calculates the actual coupling correlation degree of the abnormal micro-region according to the formula in step 3 of the method, and then determines the core cause according to the determination rules in step 5 of the method. , The system automatically and accurately determines the core cause of any deviation from the target indicators. The module has a built-in iteratively optimized coupling correlation model that can recalculate the standard values ​​of the samples, the single-parameter deviation threshold, and the coupling correlation threshold based on the actual qualified or abnormal sample data, thereby achieving dynamic updates of the benchmark library and improving the device's adaptability to different panel models.

[0063] The accurate diagnosis result output module parses the diagnostic data to realize the visualization display, data export, and printing of the diagnostic results; it includes a data parsing unit and a visualization display output unit; the data parsing unit calculates the degree of index deviation according to the formula in step 6 of the method and parses the addressing code and physical coordinates of abnormal pixels; the visualization display output unit realizes the visualization display of diagnostic results, data format export, and printing output, and the output information is complete, quantitative, and intuitive, meeting the needs of actual detection and repair.

[0064] Furthermore, the customized micro-sensing detection module adopts a multi-physics field coaxial integrated probe design, integrating the microelectrode probe, microscale photodetector, and laser micro-direction finding sensor along the same optical axis or central axis to ensure the spatial consistency of the detection of electrical, optical, and molecular state parameters in the same pixel area.

[0065] Furthermore, the ultra-high frequency synchronous acquisition and signal conditioning module is equipped with a synchronous clock generator. The trigger signal of the synchronous clock generator is connected to the drive pulse signal source, and when the rising edge of the drive pulse signal is detected, all acquisition channels are simultaneously triggered to start data acquisition.

[0066] The above are merely embodiments of the present invention. The circuits, electronic components, and modules involved are all prior art, fully achievable by those skilled in the art, and require no further explanation. The content protected by this application does not involve improvements to the software and methods. Commonly known structures and characteristics in the solutions are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are able to access all prior art in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, under the guidance of this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent.

Claims

1. A method for diagnosing abnormal response time of a liquid crystal display panel, characterized in that: The process includes the following steps: Step 1: Perform single-pixel-level addressing on the pixel array of the panel under test, assign a unique addressing code to each pixel, and establish a correspondence between pixel position and addressing code; Step 2: Output pixel-level independent driving pulse signals to the panel under test based on the addressing codes, and simultaneously collect pixel driving micro-electrical parameters, pixel photoresponse micro-parameters, and pixel liquid crystal molecule micro-state parameters for each pixel region through a micro-nano level non-contact sensing unit; Step 3: Obtain pixel three-parameter data from qualified panel samples of the same model, calculate the standard values ​​and single-parameter deviation thresholds of the pixel three-parameter data, and calculate the pixel driving micro-electrical parameters and pixel photoresponse micro-parameters, and the pixel photoresponse micro-parameters and image... Step 4: The coupling correlation degree of the micro-state parameters of the liquid crystal molecules is determined, and the coupling correlation degree threshold is determined accordingly to construct a pixel-level coupling correlation benchmark library; Step 5: The collected micro-parameters of the light response of each pixel are compared with the standard values ​​of the micro-parameters of the light response of pixels in the benchmark library to identify micro-regions with abnormal response times, mark their physical locations, and extract the pixel three-parameter data of the abnormal micro-regions; Step 6: The pixel three-parameter data of the abnormal micro-regions are input into the coupling correlation model to calculate the coupling correlation degree of the pixel three-parameters, compare it with the coupling correlation threshold in the benchmark library, and determine the core cause of the abnormality according to the rules; The diagnostic results include the addressing code of the abnormal micro-region, physical location, core cause, and degree of deviation of the parameter indicators.

2. The diagnostic method for abnormal response time of a liquid crystal display panel as described in claim 1, characterized in that: The pixel driving micro-electrical parameters in step 2 include the input voltage, conduction current, and pulse response delay time of a single pixel driving terminal; the pixel optical response micro-parameters include the grayscale rise time, grayscale fall time, and optical response waveform distortion rate of a single pixel; and the pixel liquid crystal molecule micro-state parameters include the deflection angle, deflection response speed, and molecule uniformity of liquid crystal molecules within a single pixel.

3. The diagnostic method for abnormal response time of a liquid crystal display panel as described in claim 1, characterized in that: The standard value in step 3 is the arithmetic mean of the same indicator among qualified samples of the same model, and the calculation formula is: in, The standard value for the same indicator among qualified samples of the same model. The number of qualified sample panels, This represents the total number of pixels on a single panel. This is the feature value of a certain indicator collected from the m-th pixel in the k-th sample panel.

4. The diagnostic method for abnormal response time of a liquid crystal display panel as described in claim 1, characterized in that: The coupling correlation degree in step 3 is calculated using the Pearson correlation coefficient method, and the calculation formula is as follows: in, The correlation coefficient, or coupling degree, between the two types of parameters. These are the feature acquisition values ​​for two types of pixel parameters, respectively. 、 These are the standard mean values ​​of the two types of pixel parameters, respectively.

5. The diagnostic method for abnormal response time of a liquid crystal display panel as described in claim 1, characterized in that: The rule for determining the core cause of the abnormality in step 5 is that if the deviation between the pixel driving micro-electrical parameters and the corresponding standard values ​​in the benchmark library exceeds the single parameter deviation threshold and the correlation between the driving-light response parameters is lower than the corresponding coupling correlation threshold, it is determined to be a pixel driving micro-circuit fault. If the deviation between the micro-state parameters of the pixel liquid crystal molecules and the corresponding standard values ​​in the reference library exceeds the single parameter deviation threshold and the correlation between the light response and the molecular state parameters is lower than the corresponding coupling correlation threshold, it is determined to be a pixel-level liquid crystal molecule micro-defect. If the deviation between the pixel light response micro-parameter and the corresponding standard value in the reference library exceeds the single parameter deviation threshold and the correlation between the two types of parameters is not lower than the corresponding coupling correlation threshold, it is determined to be a pixel-level liquid crystal cell thickness micro-deviation.

6. The diagnostic method for abnormal response time of a liquid crystal display panel as described in claim 1, characterized in that: The formula for calculating the single-parameter deviation threshold in step 3 is as follows: in, For the single-parameter deviation threshold of the indicator, denoted as the standard deviation of the parameter index.

7. The diagnostic method for abnormal response time of a liquid crystal display panel as described in claim 1, characterized in that: The deviation of the parameter index in step 5 is the relative deviation between the actual collected values ​​of the three pixel parameters and the corresponding standard values ​​in the benchmark library.

8. A diagnostic device for abnormal response time of a liquid crystal display panel, applicable to the diagnostic method for abnormal response time of a liquid crystal display panel as described in any one of claims 1-7, characterized in that: The system includes a high-precision motion platform, a pixel-level precise addressing module, a sub-micron level coaxial alignment module, a customized micro-sensor detection module, an ultra-high frequency synchronous acquisition and signal conditioning module, a pixel-level coupling correlation benchmark library module, a micro-region anomaly preliminary judgment module, a coupling correlation analysis and cause localization module, and a precise diagnostic result output module. The high-precision motion platform is used for coarse positioning of the panel under test and the detection module. The pixel-level precise addressing module is used for single-pixel level addressing, encoding allocation, and mapping of physical coordinates to addressing codes, outputting pixel-level independent drive pulse signals. The sub-micron level coaxial alignment module works in conjunction with the high-precision motion platform to achieve secondary positioning, completing sub-micron level alignment between the detection module and the target single pixel. The customized micro-sensor detection module... The measurement module integrates a microelectrode probe, a microscale photodetector, and a laser micro-direction finding sensor to achieve non-contact acquisition of all indicators. The ultra-high frequency synchronous acquisition and signal conditioning module realizes synchronous acquisition, conditioning, and digital conversion of sensor signals. The pixel-level coupling correlation benchmark library module stores sample standard values, single-parameter deviation thresholds, and coupling correlation degree thresholds, and supports rapid retrieval of benchmark parameters by addressing code. The micro-region anomaly preliminary judgment module is used to determine abnormal micro-regions according to rules and extract full feature data. The coupling correlation analysis and cause localization module calculates the actual coupling correlation degree and determines the core cause according to rules. The precise diagnosis result output module is used to parse diagnostic data and realize the visualization display, data export, and printing of diagnostic results.

9. The diagnostic device for abnormal response time of a liquid crystal display panel as described in claim 8, characterized in that: The customized microsensor detection module adopts a multi-physics field coaxial integrated probe design, which integrates microelectrode probes, microscale photodetectors and laser micro-direction finding sensors along the same optical axis or central axis to ensure the spatial consistency of the detection of electrical, optical and molecular state parameters in the same pixel area.

10. The diagnostic device for abnormal response time of a liquid crystal display panel as described in claim 8, characterized in that: The ultra-high frequency synchronous acquisition and signal conditioning module is equipped with a synchronous clock generator. The trigger signal of the synchronous clock generator is connected to the drive pulse signal source, and when the rising edge of the drive pulse signal is detected, all acquisition channels are simultaneously triggered to start data acquisition.

Images