CN116453437B - Display screen module testing method, device, equipment and storage medium - Google Patents

Display screen module testing method, device, equipment and storage medium Download PDF

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CN116453437B
CN116453437B CN202310713323.4A CN202310713323A CN116453437B CN 116453437 B CN116453437 B CN 116453437B CN 202310713323 A CN202310713323 A CN 202310713323A CN 116453437 B CN116453437 B CN 116453437B
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CN116453437A (en
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倪正华
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Shenzhen Ostar Display Electronics Co ltd
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    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G3/00—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes
    • G09G3/006—Electronic inspection or testing of displays and display drivers, e.g. of LED or LCD displays
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M11/00—Testing of optical apparatus; Testing structures by optical methods not otherwise provided for
    • G01M11/02—Testing optical properties
    • G—PHYSICS
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    • G06F—ELECTRIC DIGITAL DATA PROCESSING
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    • G06F18/15—Statistical pre-processing, e.g. techniques for normalisation or restoring missing data
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    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The invention relates to the technical field of display screens, and discloses a method, a device, equipment and a storage medium for testing a display screen module, which are used for realizing intelligent analysis of parameters of the display screen module and improving the testing accuracy of the display screen module. The method comprises the following steps: classifying and extracting display characteristic parameters of the standard test data to generate a display characteristic association curve; performing display anomaly analysis on the display characteristic association curve to obtain a brightness and color anomaly value pair, and generating a target anomaly vector according to the brightness and color anomaly value pair; inputting the target abnormal vector into a display screen abnormal analysis model to perform display screen abnormal analysis, so as to obtain a display screen abnormal analysis result; extracting characteristic parameters of the reaction speed, and verifying analysis results of abnormal analysis results of the display screen according to the characteristic parameters of the reaction speed to obtain target verification results; and generating a display screen abnormality processing strategy according to the target verification result and the display screen abnormality analysis result.

Description

Display screen module testing method, device, equipment and storage medium
Technical Field
The present invention relates to the field of display technologies, and in particular, to a method, an apparatus, a device, and a storage medium for testing a display module.
Background
At present, with the continuous development of technology, display screen technology has become an integral part of various electronic devices. However, the complexity and variety of display screens has also led to increasing difficulty in testing the display screens. In order to improve the production efficiency and quality control level of display screen modules, more comprehensive and accurate testing methods are always sought.
The existing scheme tests and analyzes the display screen module, such as an observation method, a colorimeter, an optical passive tester and the like. These techniques, while capable of providing certain test data and analysis results, have some drawbacks. For example, observations require manual testing, and the reliability of the test results depends on the experience and skill of the tester. Although the colorimeter and the optical passive tester can automatically perform the test, the test accuracy needs to be further improved, especially in a complex test environment.
Disclosure of Invention
The invention provides a method, a device, equipment and a storage medium for testing a display screen module, which are used for realizing intelligent analysis of parameters of the display screen module and improving the testing accuracy of the display screen module.
The first aspect of the present invention provides a method for testing a display screen module, where the method for testing a display screen module includes:
based on preset test time and test parameters, performing test analysis on the target display screen module to obtain original test data, and performing data standardization processing on the original test data to obtain standard test data;
classifying and extracting the display characteristic parameters of the standard test data to obtain brightness display characteristic parameters and color display characteristic parameters, and generating a display characteristic association curve according to the brightness display characteristic parameters and the color display characteristic parameters;
performing display anomaly analysis on the display characteristic association curve to obtain a brightness and color anomaly value pair, and generating a target anomaly vector according to the brightness and color anomaly value pair;
inputting the target abnormal vector into a preset display screen abnormal analysis model to perform display screen abnormal analysis, so as to obtain a display screen abnormal analysis result;
extracting reaction speed characteristic parameters in the standard test data, and verifying analysis results of the display screen abnormality analysis results according to the reaction speed characteristic parameters to obtain target verification results;
And generating a display screen abnormality processing strategy of the target display screen module according to the target verification result and the display screen abnormality analysis result.
With reference to the first aspect, in a first implementation manner of the first aspect of the present invention, the performing test analysis on the target display screen module based on the preset test time and the test parameter to obtain original test data, and performing data normalization processing on the original test data to obtain standard test data includes:
acquiring size data, thickness data and bending radian corresponding to a target display screen module to be tested;
setting test time and test parameters according to the size data, the thickness data and the bending radian;
based on the test time and the test parameters, testing and analyzing the target display screen module, and acquiring original test data through a preset parameter acquisition device;
and carrying out missing value interpolation and outlier removal on the original test data to obtain standard test data.
With reference to the first aspect, in a second implementation manner of the first aspect of the present invention, the classifying and extracting the display feature parameters of the standard test data to obtain a brightness display feature parameter and a color display feature parameter, and generating a display feature association curve according to the brightness display feature parameter and the color display feature parameter includes:
Acquiring a brightness characteristic parameter range and a color characteristic parameter range corresponding to the standard test data;
searching the brightness display characteristic parameters from the standard test data according to the brightness characteristic parameter range, and inquiring the color display characteristic parameters in the standard test data according to the color characteristic parameter range;
constructing a first discrete distribution diagram corresponding to the brightness display characteristic parameter and a second discrete distribution diagram corresponding to the color display characteristic parameter;
performing data alignment on the first discrete distribution map and the second discrete distribution map to generate a target discrete distribution map;
and carrying out association value calculation on the target discrete distribution diagram to obtain a target association value set, and generating a display characteristic association curve according to the target association value set.
With reference to the first aspect, in a third implementation manner of the first aspect of the present invention, the performing display anomaly analysis on the display feature association curve to obtain a luminance and color anomaly value pair, and generating a target anomaly vector according to the luminance and color anomaly value pair includes:
extracting turning points of the display characteristic association curves to obtain a plurality of curve turning points;
Comparing the curve turning points with the brightness characteristic parameter range and the color characteristic parameter range respectively to obtain a comparison result;
determining corresponding display abnormal points from the plurality of curve turning points according to the comparison result, and acquiring time stamp data of each display abnormal point;
determining corresponding pairs of luminance and color outliers based on the display outliers and the timestamp data;
and carrying out vector conversion on the brightness and color abnormal value pairs to generate a target abnormal vector.
With reference to the first aspect, in a fourth implementation manner of the first aspect of the present invention, inputting the target anomaly vector into a preset display screen anomaly analysis model to perform display screen anomaly analysis, to obtain a display screen anomaly analysis result, includes:
inputting the target abnormal vector into a preset display screen abnormal analysis model, wherein the display screen abnormal analysis model comprises: the first threshold circulation network, the second threshold circulation network and the full connection layer;
performing feature extraction and probability prediction on the target abnormal vector through the display screen abnormal analysis model to obtain an abnormal probability value;
and generating a display screen abnormality analysis result of the target display screen module according to the abnormality probability value and a preset standard range value.
With reference to the first aspect, in a fifth implementation manner of the first aspect of the present invention, the extracting a reaction speed feature parameter from the standard test data, and verifying an analysis result of the display screen abnormal analysis result according to the reaction speed feature parameter, to obtain a target verification result, includes:
extracting characteristic parameters related to the reaction speed from the standard test data to obtain the characteristic parameters of the reaction speed, wherein the characteristic parameters of the reaction speed comprise switching time, pixel response time and reaction time;
comparing and verifying the characteristic parameters of the reaction speed with the abnormal analysis results of the display screen, and acquiring the abnormal value position in the display characteristic association curve;
taking the reaction speed characteristic parameter as an index, and checking whether the abnormal value position is consistent with a bad item in the reaction speed characteristic parameter;
and if the results are consistent, determining that the display screen abnormality analysis result is correct, and generating a target verification result.
With reference to the first aspect, in a sixth implementation manner of the first aspect of the present invention, the generating a display screen exception handling policy of the target display screen module according to the target verification result and the display screen exception analysis result includes:
Searching for an abnormal reason and an abnormal position according to the target verification result and the display screen abnormality analysis result, wherein the abnormal reason and the abnormal position comprise: component damage, loose circuit connections, and poor signal response;
generating a display screen abnormality processing strategy of the target display screen module according to the abnormality cause and the abnormality position, wherein the display screen abnormality processing strategy comprises: repair or replacement of damaged components, welding or replacement of terminals for loose circuits, and adjustment of the signal generator settings or replacement of signal sources for poor signal response may be performed.
The second aspect of the present invention provides a testing device for a display screen module, where the testing device for a display screen module includes:
the testing module is used for carrying out testing analysis on the target display screen module based on preset testing time and testing parameters to obtain original testing data, and carrying out data standardization processing on the original testing data to obtain standard testing data;
the classification module is used for classifying and extracting the display characteristic parameters of the standard test data to obtain brightness display characteristic parameters and color display characteristic parameters, and generating a display characteristic association curve according to the brightness display characteristic parameters and the color display characteristic parameters;
The processing module is used for carrying out display anomaly analysis on the display characteristic association curve to obtain a brightness and color anomaly value pair, and generating a target anomaly vector according to the brightness and color anomaly value pair;
the analysis module is used for inputting the target abnormal vector into a preset display screen abnormal analysis model to perform display screen abnormal analysis, so as to obtain a display screen abnormal analysis result;
the verification module is used for extracting the characteristic parameters of the reaction speed in the standard test data, and verifying the analysis result of the display screen abnormality analysis result according to the characteristic parameters of the reaction speed to obtain a target verification result;
and the generating module is used for generating a display screen abnormality processing strategy of the target display screen module according to the target verification result and the display screen abnormality analysis result.
A third aspect of the present invention provides a test apparatus for a display screen module, including: a memory and at least one processor, the memory having instructions stored therein; and the at least one processor calls the instruction in the memory so that the test equipment of the display screen module executes the test method of the display screen module.
A fourth aspect of the present invention provides a computer readable storage medium having instructions stored therein, which when run on a computer, cause the computer to perform the method of testing a display screen module as described above.
In the technical scheme provided by the invention, the standard test data is subjected to display characteristic parameter classification and extraction to generate a display characteristic association curve; performing display anomaly analysis on the display characteristic association curve to obtain a brightness and color anomaly value pair, and generating a target anomaly vector according to the brightness and color anomaly value pair; inputting the target abnormal vector into a display screen abnormal analysis model to perform display screen abnormal analysis, so as to obtain a display screen abnormal analysis result; extracting characteristic parameters of the reaction speed, and verifying analysis results of abnormal analysis results of the display screen according to the characteristic parameters of the reaction speed to obtain target verification results; according to the method and the device, accurate and comparable test results are obtained through comprehensive performance test and data standardization processing according to target verification results and display screen abnormality analysis results, so that the production efficiency and quality control level of the display screen module are improved, then, through the display characteristic association curve and display abnormality analysis, deeper and comprehensive abnormality detection and analysis can be carried out on the display screen module, and through the target verification results and the display screen abnormality processing strategies, intelligent analysis of parameters of the display screen module is realized, and the test accuracy of the display screen module is improved.
Drawings
FIG. 1 is a schematic diagram of an embodiment of a testing method of a display module according to the present invention;
FIG. 2 is a flow chart of generating a display characteristic association curve in an embodiment of the present invention;
FIG. 3 is a flow chart of generating a target anomaly vector in an embodiment of the present invention;
FIG. 4 is a flowchart of display screen anomaly analysis in an embodiment of the present invention;
FIG. 5 is a schematic diagram of an embodiment of a testing apparatus for a display module according to an embodiment of the invention;
fig. 6 is a schematic diagram of an embodiment of a testing apparatus for a display module according to an embodiment of the invention.
Detailed Description
The embodiment of the invention provides a method, a device, equipment and a storage medium for testing a display screen module, which are used for realizing intelligent analysis of parameters of the display screen module and improving the testing accuracy of the display screen module. The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
For easy understanding, the following describes a specific flow of an embodiment of the present invention, referring to fig. 1, and an embodiment of a method for testing a display screen module in an embodiment of the present invention includes:
s101, performing test analysis on a target display screen module based on preset test time and test parameters to obtain original test data, and performing data standardization processing on the original test data to obtain standard test data;
it can be understood that the execution body of the present invention may be a testing device of a display screen module, and may also be a terminal or a server, which is not limited herein. The embodiment of the invention is described by taking a server as an execution main body as an example.
Specifically, the server determines the time and parameters of the test to ensure that the test can be accurately performed on the target display screen module, and further, the test instrument is used for testing the target display screen module, and each test result is recorded. For example, indexes such as brightness, contrast, resolution, response time and the like of a display screen can be tested, test results are recorded through an instrument, recorded values of each test index are arranged to obtain original test data, subsequent data processing and analysis are convenient, and it is noted that the test data are required to be subjected to standardized processing because the test instruments possibly have different differences in precision, range and the like, so that the test data are comparable, and the subsequent analysis is convenient. For example, the test data may be subjected to average calculation, numerical scaling, and the like to obtain standard test data.
For example, assume that the screen brightness and resolution of a certain handset need to be tested: presetting test time and parameters: the test can be continued for 30 minutes under indoor conditions, and the two indexes of brightness and resolution can be tested. And testing the mobile phone screen by using a measuring instrument, and recording the result of each test. For example, the brightness of the screen can be tested under different light conditions, corresponding values on the testing instrument are recorded, meanwhile, the resolution is tested, and the testing result is recorded. The records of each test are sorted to obtain original test data, for example, 10 brightness test results and 10 resolution test results. And carrying out average value calculation on the test data to obtain average brightness and average resolution, and simultaneously carrying out operations such as numerical scaling and the like to obtain standard test data.
S102, classifying and extracting display characteristic parameters of standard test data to obtain brightness display characteristic parameters and color display characteristic parameters, and generating a display characteristic association curve according to the brightness display characteristic parameters and the color display characteristic parameters;
specifically, the server classifies and extracts the brightness display characteristic parameters and the color display characteristic parameters from the original test data, classifies and marks the extracted parameters respectively for convenient subsequent processing, trains and learns the standard test data, establishes classification and extraction algorithms for the brightness and color display characteristic parameters, for example, extracts the brightness parameters by detecting the change of pixel intensity, obtains the color parameters by using color space conversion, establishes a corresponding data association relation model based on the brightness and color display characteristic parameters, and generates a display characteristic association curve by using the model. For this purpose, a logarithmic factor decomposition method, a polar moment method or a neural network method can be selected to establish a correlation model between the brightness and color display characteristic parameters, and the original test data is preprocessed, including noise filtering and outlier processing. And (3) carrying out standardization processing on the data to eliminate the difference between different data sources, and using the standardized data for classification and extraction.
S103, carrying out display anomaly analysis on the display characteristic association curve to obtain a brightness and color anomaly value pair, and generating a target anomaly vector according to the brightness and color anomaly value pair;
the server first performs anomaly detection on the display characteristic association curve to find atypical parts, marks positions and values of anomaly data points by using an anomaly detection method, analyzes anomalies based on the marked data, and may select a z-score anomaly detection method or an IQR anomaly detection method to find anomaly data, extract values in brightness and color value pairs of the marked anomaly data points, and store the brightness and color value pairs in a list of corresponding brightness anomaly value pairs and color anomaly value pairs. For example, for an image, its display characteristic association curve includes 50 points, 5 of which are marked as outliers. The 5 outliers can extract the values in the luminance and color value pairs to generate a corresponding outlier value pair list, average the luminance and color outlier value pairs to generate two target outliers, namely a luminance target outlier and a color target outlier, and combine the luminance and color target outliers into one vector, namely a target outlier vector, for example, for the 5 luminance outlier value pairs and the color outlier pairs, average the values respectively to obtain a luminance target outlier and a color target outlier, and then combine the two target outliers into one vector, namely a target outlier vector.
When this step is performed, for a display characteristic association curve, the z-score anomaly detection method is used to find anomaly points therein, label their positions and values, for these labeled anomaly data points, extract the values in their brightness and color value pairs to generate brightness anomaly value pairs and color anomaly value pair lists, respectively, for each list, add up all the values and divide by the corresponding list length to obtain brightness and color target anomaly values, and finally the server combines the brightness and color target anomaly values into a binary group as a target anomaly vector and returns.
S104, inputting the target abnormal vector into a preset display screen abnormal analysis model to perform display screen abnormal analysis, and obtaining a display screen abnormal analysis result;
specifically, in a preset model library, an abnormal analysis model conforming to the characteristics of the current display screen is selected.
Determining model input, output and parameters, inputting a target abnormal vector into the model, running the model, and generating a display screen abnormal analysis result, for example, a classifier, a neural network or a support vector machine and other models can be selected to realize abnormal analysis.
It should be noted that, in the embodiment of the present invention, an anomaly analysis model suitable for the current display screen is selected from a preset model library. In this step, the input, output and parameters of the model need to be determined, the target anomaly vector is input into the model, the model is executed, and the display anomaly analysis results generated by the processing model are analyzed to determine the type and intensity of the display anomaly, for example, if display anomaly sample data has been collected, these data can be used to train a support vector machine anomaly detection model. After training is completed, the model may be run with the target anomaly vector as input. Finally, according to the output of the model, the abnormal type and intensity of the display screen are evaluated.
In the step of the invention, an abnormality analysis model which is least influenced by the characteristics of the current display screen (object to be analyzed) is selected from the existing model library, basic information such as input, output and parameters of the model is confirmed, a target abnormality vector is used as input into the model, and the model is executed. And trimming and standardizing the non-zero output data (abnormal score), and judging the abnormal type and intensity of the display screen according to the result of model analysis and domain knowledge.
S105, extracting characteristic parameters of the reaction speed in the standard test data, and verifying analysis results of abnormal analysis results of the display screen according to the characteristic parameters of the reaction speed to obtain target verification results;
specifically, the server extracts reaction speed characteristic parameters such as reaction time and accuracy from standard test data, classifies and marks the extracted characteristic parameters for convenient subsequent processing, establishes a specific reaction speed model based on the reaction speed characteristic parameters, for example, can acquire the reaction time and accuracy of a user under different test conditions from the standard test data, classifies the reaction time and accuracy, establishes a proper model based on the characteristics, correlates the obtained characteristic parameters with a display screen abnormality analysis result, calculates a target verification score according to the established reaction speed model by using the characteristic parameters such as the reaction time and accuracy, determines whether the abnormal condition exists on the display screen according to the verification score, for example, can correlate the generated display screen abnormality analysis result with the generated reaction speed characteristic parameters, input the generated display screen abnormality analysis result with the generated reaction speed characteristic parameters into the specific reaction speed model, and calculates a target verification score by using the model. If the score exceeds a preset threshold, the display screen abnormality may be confirmed.
In the step of the invention, the server extracts reaction speed characteristic parameters such as reaction time and accuracy from standard test data, classifies and marks the reaction speed characteristic parameters, establishes a proper reaction speed model based on the reaction speed characteristic parameters, correlates the obtained display screen abnormal analysis result with the reaction speed characteristic parameters to form a verification data set, calculates a target verification score of each data point in the verification data set by using the reaction speed model, determines the verification result according to the score and a preset threshold value, and judges whether the display screen has abnormal conditions, for example, for a certain detection task, standard test data can be collected and the two characteristic parameters of the reaction time and the accuracy can be extracted from the standard test data. An appropriate model is then built based on these two parameters. It is assumed that abnormality analysis has been performed for a certain display screen and abnormality data is acquired. The anomaly data can be associated with the two characteristic parameters and constitute a validation data set. Then, a target verification score for verifying the data point is calculated using the speculative model. And finally, determining a verification result according to the score and a threshold value, and judging whether the display screen has abnormal conditions or not.
S106, generating a display screen abnormality processing strategy of the target display screen module according to the target verification result and the display screen abnormality analysis result.
Specifically, the reaction speed characteristic parameters and the display screen abnormality analysis result are integrated, the integrated data are subjected to data cleaning and preprocessing, such as removing low-quality data points or performing data smoothing processing, a machine learning algorithm such as regression or classification model is used for generating a correlation model of the target verification result and the display screen abnormality analysis result, for example, a multiple regression analysis method can be used for integrating the target verification result and the display screen abnormality analysis result, and then a model is trained for predicting the display screen abnormality condition.
By using the existing knowledge and prior experience, generating a display screen abnormality processing strategy according to the model prediction result, and generating an execution guide of a specific strategy according to different types and grades of the abnormality strategy, for example, if the display screen abnormality analysis result is a software error, the problem can be solved by using upgrading or debugging software. And if the hardware is in fault, performing troubleshooting according to a fault removal flow.
In the step of the invention, the server integrates the reaction speed characteristic parameters and the display screen abnormality analysis results, uses the integrated data to train a correlation model or expert system, uses the model or expert system to predict the relation between the target verification result and the display screen abnormality analysis results, determines the display screen abnormality processing strategy, generates a specific execution guide according to different types and grades of the strategy, operates specific conditions, such as processing abnormal data of a certain display screen, integrates the abnormal data with the reaction speed characteristic parameters, and uses a stepwise regression model to predict the relation between the target verification result and the abnormality analysis results. After the model result is obtained, the type and degree of the display screen abnormality can be judged, and a corresponding abnormality processing strategy is generated based on the prediction result. If the display screen abnormality degree is light, the processing can be performed based on a self-repairing strategy. If the display screen abnormality is serious, a more complex troubleshooting procedure is adopted to deal with the problem.
In the embodiment of the invention, the standard test data is classified and extracted with display characteristic parameters to generate a display characteristic association curve; performing display anomaly analysis on the display characteristic association curve to obtain a brightness and color anomaly value pair, and generating a target anomaly vector according to the brightness and color anomaly value pair; inputting the target abnormal vector into a display screen abnormal analysis model to perform display screen abnormal analysis, so as to obtain a display screen abnormal analysis result; extracting characteristic parameters of the reaction speed, and verifying analysis results of abnormal analysis results of the display screen according to the characteristic parameters of the reaction speed to obtain target verification results; according to the method and the device, accurate and comparable test results are obtained through comprehensive performance test and data standardization processing according to target verification results and display screen abnormality analysis results, so that the production efficiency and quality control level of the display screen module are improved, then, through the display characteristic association curve and display abnormality analysis, deeper and comprehensive abnormality detection and analysis can be carried out on the display screen module, and through the target verification results and the display screen abnormality processing strategies, intelligent analysis of parameters of the display screen module is realized, and the test accuracy of the display screen module is improved.
In a specific embodiment, the process of executing step S101 may specifically include the following steps:
(1) Acquiring size data, thickness data and bending radian corresponding to a target display screen module to be tested;
(2) Setting test time and test parameters according to the size data, the thickness data and the bending radian;
(3) Based on the test time and the test parameters, carrying out test analysis on the target display screen module, and acquiring original test data through a preset parameter acquisition device;
(4) And carrying out missing value interpolation and outlier removal on the original test data to obtain standard test data.
Specifically, the server acquires size data, thickness data and bending radian data from the target display screen module, cleans and processes the data, and ensures data quality, for example, measures the size, thickness and bending radian data of the target display screen module through an instrument or equipment. Then, the collected data are sorted and cleaned to improve the data quality, corresponding test parameters are selected according to the size data, the thickness data and the bending radian data, the test time is set, test equipment and test environments are prepared in advance, necessary calibration and adjustment are performed, for example, required test parameters such as current amplitude, frequency and the like are set according to the characteristics of the display screen module. These parameters are then configured into the test equipment and the test time is set as appropriate. Before testing, the testing device is prepared, necessary calibration and adjustment are performed, the target display screen module is placed in the testing device, a testing program is started, original testing data are collected in the testing analysis process, testing parameters and testing time are recorded, and for example, the target display screen module can be placed in the testing device, and the testing program is started. In the test analysis process, recording original test data, including test parameters and test time, so as to facilitate subsequent processing and analysis, carrying out missing value interpolation and outlier removal on the original test data to ensure the continuity and reliability of the data, and preprocessing and standardizing the data according to the characteristics and requirements of the data to obtain standard test data, wherein the missing value and outlier in the original test data are processed through an interpolation algorithm or a statistical method, for example. Then, preprocessing and standardization are performed based on the characteristics and requirements of the data to obtain standard test data.
In the embodiment of the invention, size data, thickness data and bending radian data are obtained from a target display screen module, the data are cleaned and processed, corresponding test parameters are selected according to the size data, the thickness data and the bending radian data, test time is set, the target display screen module is placed in test equipment, a test program is started, the test parameters and the test time are recorded in the test process, original test data are collected, missing value interpolation and outlier removal are carried out on the original test data, data preprocessing and standardization are carried out, and standard test data are obtained, for example, standard test data of a certain display screen module are collected. Firstly, acquiring size data, thickness data and bending radian data of the module, setting test parameters based on the data, and starting a test program. During the test, test parameters and test time are recorded and raw test data is collected. And finally, processing the original test data, removing the missing values and outliers, and preprocessing and normalizing to obtain standard test data.
In a specific embodiment, as shown in fig. 2, the process of executing step S102 may specifically include the following steps:
S201, acquiring a brightness characteristic parameter range and a color characteristic parameter range corresponding to standard test data;
s202, searching brightness display characteristic parameters from standard test data according to the brightness characteristic parameter range, and inquiring color display characteristic parameters in the standard test data according to the color characteristic parameter range;
s203, constructing a first discrete distribution diagram corresponding to the brightness display characteristic parameter and a second discrete distribution diagram corresponding to the color display characteristic parameter;
s204, performing data alignment on the first discrete distribution diagram and the second discrete distribution diagram to generate a target discrete distribution diagram;
s205, performing association value calculation on the target discrete distribution graph to obtain a target association value set, and generating a display characteristic association curve according to the target association value set.
Specifically, the server obtains the characteristic parameters of brightness and color from the standard test data, analyzes and screens the obtained characteristic parameters to obtain the range of the characteristic parameters, for example, the characteristic parameters of brightness and color including parameters of brightness, color temperature, hue and the like can be obtained from the standard test data. And then screening and calculating the parameters according to the distribution and the condition of the characteristic parameters, searching the data meeting the conditions from the standard test data based on the range of the characteristic parameters, constructing a discrete distribution diagram of the brightness and the color characteristic parameters based on the obtained data, carrying out data alignment on the discrete distribution diagram, and generating a target discrete distribution diagram, wherein the data meeting the conditions can be searched from the standard test data based on the brightness and the color characteristic parameter range obtained in the first step. These data are then processed and analyzed to construct discrete profiles of luminance and color characterization parameters. Finally, the discrete profiles are data aligned to generate a target discrete profile.
The correlation value of each data point is calculated based on the target discrete distribution map, the correlation value is analyzed and processed, a characteristic correlation curve is generated and its regularity and correlation are determined, for example, the correlation value of each data point can be calculated based on the target discrete distribution map obtained in the second step. The correlation values are then analyzed and processed to generate a characteristic correlation curve. Finally, the regularity and relevance of the characteristic association curve needs to be determined for subsequent use, for example, for a brightness and color characteristic parameter extraction task of a display screen, the range of characteristic parameters is first obtained from standard test data. Then, based on these ranges, qualified data is found in the standard test data, and a discrete distribution map of luminance and color characteristic parameters is constructed. These discrete profiles are then data aligned to generate a target discrete profile. Finally, calculating the association value of each data point based on the target discrete distribution diagram, and generating a characteristic association curve according to the association value.
In a specific embodiment, as shown in fig. 3, the process of executing step S103 may specifically include the following steps:
s301, extracting turning points of the display characteristic association curves to obtain a plurality of curve turning points;
S302, comparing a plurality of curve turning points with a brightness characteristic parameter range and a color characteristic parameter range respectively to obtain a comparison result;
s303, determining corresponding display abnormal points from a plurality of curve turning points according to the comparison result, and acquiring time stamp data of each display abnormal point;
s304, determining corresponding brightness and color abnormal value pairs according to the display abnormal points and the time stamp data;
s305, vector conversion is carried out on the brightness and color abnormal value pairs, and a target abnormal vector is generated.
Specifically, the server processes and analyzes the display characteristic association curve, processes and analyzes the association curve, for example, by curve fitting, analysis and other methods, to extract the turning points on the curve, respectively compares the turning points of the curve with the brightness and color characteristic parameter ranges, determines the turning points meeting the conditions according to the comparison result, for example, can respectively compare the turning points of the curve with the brightness and color characteristic parameter ranges, determines the turning points meeting the conditions according to the comparison result, determines the display abnormal points meeting the conditions according to the comparison result of the turning points, obtains the timestamp data of each display abnormal point, for example, determines the display abnormal point meeting the conditions according to the comparison result of the turning points, and obtains the timestamp data of each abnormal point, determines the corresponding brightness and color abnormal value pair based on the display abnormal point, for example, determines the corresponding brightness and color abnormal value pair according to the position and characteristic parameter ranges of the display abnormal point, carries out vector conversion on the brightness and color abnormal value pair, for example, can carry out vector conversion on the brightness and color abnormal value pair, and can firstly detect the abnormal value pair of the display abnormal points, for example, and can carry out the correlation vector analysis on the abnormal characteristic of the display abnormal points, and the association vector is generated. And then, comparing the turning points with the characteristic parameter ranges respectively, determining abnormal points meeting the conditions, and acquiring time stamp data of each abnormal point. Next, based on the outliers and the range of characteristic parameters, corresponding pairs of luminance and color outliers are determined. Finally, vector conversion is performed on the anomaly points and the numerical value pairs to generate a target anomaly vector as an anomaly detection result.
In a specific embodiment, as shown in fig. 4, the process of executing step S104 may specifically include the following steps:
s401, inputting a target abnormal vector into a preset display screen abnormal analysis model, wherein the display screen abnormal analysis model comprises: the first threshold circulation network, the second threshold circulation network and the full connection layer;
s402, carrying out feature extraction and probability prediction on the target abnormal vector through a display screen abnormal analysis model to obtain an abnormal probability value;
s403, generating a display screen abnormality analysis result of the target display screen module according to the abnormality probability value and the preset standard range value.
Specifically, the server presets a first threshold circulation network, a second threshold circulation network and a full connection layer, and constructs a model input and output structure, for example, the first threshold circulation network, the second threshold circulation network and the full connection layer may be preset, and simultaneously constructs an input and output structure of the model, inputs a target abnormal vector into the display screen abnormal analysis model, performs feature extraction and expansion on the abnormal vector based on a model architecture, for example, may input the target abnormal vector into the display screen abnormal analysis model. Then, based on the model architecture, feature extraction and expansion are performed on the abnormal vector for subsequent probability prediction and analysis, probability prediction of the full connection layer is performed on the vector after feature extraction, and the probability of occurrence of the abnormality is judged according to the probability prediction result, for example, probability prediction can be performed on the vector after feature extraction through the full connection layer, so that the probability of occurrence of the abnormality is obtained. And judging whether the current abnormality reaches an alarm value or has a certain risk according to the probability predicted by the model, and determining whether the current abnormality needs further analysis or processing based on a preset standard range value. And combining the model output result and the standard range value to generate a display screen abnormality analysis result of the target display screen module. For example, based on a preset standard range value, it may be determined whether the current anomaly requires further analysis or processing. And then, combining the model output result and the standard range value to generate an abnormal analysis result of the target display screen module. For example, for a display screen abnormality analysis task, a target abnormality vector is input into a preset display screen abnormality analysis model, and feature extraction and expansion are performed. And then, carrying out probability prediction on the vector after feature extraction through the full connection layer so as to determine the probability of occurrence of the current abnormality. Based on the preset standard range value, it can be determined whether the current anomaly requires further analysis or processing. And finally, combining the model output result and the standard range value to generate an abnormality analysis result of the target display screen module so as to guide subsequent abnormality processing and maintenance.
In a specific embodiment, the process of executing step S105 may specifically include the following steps:
(1) Extracting characteristic parameters related to the reaction speed from standard test data to obtain the characteristic parameters of the reaction speed, wherein the characteristic parameters of the reaction speed comprise switching time, pixel response time and reaction time;
(2) Comparing and verifying the characteristic parameters of the reaction speed with the abnormal analysis results of the display screen, and acquiring the abnormal value position in the display characteristic association curve;
(3) Taking the characteristic reaction speed parameter as an index, and checking whether the position of the abnormal value is consistent with the bad item in the characteristic reaction speed parameter;
(4) If the results are consistent, determining that the display screen abnormality analysis result is correct, and generating a target verification result.
Specifically, characteristic parameters related to the reaction speed, such as switching time, pixel response time and reaction time, are extracted from the standard test data, and the characteristic parameters related to the reaction speed, such as switching time, pixel response time and reaction time, can be extracted from the standard test data according to the characteristic parameter extraction rule. And then, according to the specified characteristic extraction rule, obtaining a reaction speed characteristic parameter, comparing and verifying the reaction speed characteristic parameter with the display screen abnormality analysis result, and obtaining the position of the abnormal value by utilizing the display characteristic association curve, for example, comparing and verifying the reaction speed characteristic parameter with the display screen abnormality analysis result. Meanwhile, the position of the abnormal value can be obtained by using the display characteristic association curve for subsequent detection and analysis, the reaction speed characteristic parameter is taken as an index, whether the position of the abnormal value is consistent with the bad item in the reaction speed characteristic parameter is checked, the consistency and reliability of the detection result are determined, for example, the reaction speed characteristic parameter is taken as the index, and whether the position of the abnormal value is consistent with the bad item in the reaction speed characteristic parameter is checked. Through such checking, consistency and reliability of the detection result can be determined to ensure effectiveness of subsequent operations, if the results are consistent, the display screen abnormality analysis result is determined to be correct, and a target verification result is generated, if the results are inconsistent, abnormality analysis error information is returned, for example, if the detection results are consistent, the display screen abnormality analysis result can be determined to be correct, and the target verification result is generated. If the inspection results are inconsistent, an abnormality analysis error message is returned, and the subsequent abnormality detection and analysis are prompted, for example, for a display screen abnormality verification task, characteristic parameters related to the reaction speed, such as switching time, pixel response time and reaction time, are firstly extracted from standard test data. And then comparing and verifying the characteristic parameters of the reaction speed with the abnormal analysis results of the display screen, and acquiring the abnormal value position in the display characteristic association curve. Then, with the reaction rate characteristic parameter as an index, it is checked whether the abnormal value position coincides with the bad item in the reaction rate characteristic parameter. If the results are consistent, determining that the display screen abnormality analysis result is correct, and generating a target verification result. If the results are inconsistent, returning an abnormality analysis error message, and prompting the subsequent abnormality detection and analysis.
In a specific embodiment, the process of executing step S106 may specifically include the following steps:
(1) Searching for an abnormal reason and an abnormal position according to the target verification result and the display screen abnormal analysis result, wherein the abnormal reason and the abnormal position comprise: component damage, loose circuit connections, and poor signal response;
(2) Generating a display screen abnormality processing strategy of the target display screen module according to the abnormality reason and the abnormality position, wherein the display screen abnormality processing strategy comprises: repair or replacement of damaged components, welding or replacement of terminals for loose circuits, and adjustment of the signal generator settings or replacement of signal sources for poor signal response may be performed.
Specifically, the abnormal reason and the abnormal position are searched according to the target verification result and the display screen abnormality analysis result, which elements such as component damage, loose circuit connection and poor signal response are included in the abnormal position and the abnormal reason are determined, and for example, the abnormal position and the abnormal reason of the display screen are searched according to the target verification result and the display screen abnormality analysis result. Then, it can be determined which elements the abnormality location and the abnormality cause include, such as component damage, loose circuit connection, and poor signal response, and according to the abnormality cause and the abnormality location, a display abnormality processing policy of the target display module is generated, the display abnormality processing policy including: repair or replacement of damaged components, welding or replacement of lugs for loose circuits, and adjustment of signal generator settings or replacement of signal sources for poor signal response, for example, display abnormality treatment strategies for target display modules may be generated based on abnormality causes and abnormality locations. The strategy includes repairing or replacing damaged components, welding or replacing connector lugs for loose circuits, and adjusting the signal generator settings or replacing signal sources for poor signal response, for example, for a display screen exception handling task, the exception cause and exception position need to be searched according to target verification results and display screen exception analysis results. The location of the anomaly and the cause of the anomaly may then be determined to include which elements, such as component damage, loose circuit connections, and poor signal response. Next, a display abnormality handling strategy for the target display module is generated based on the cause of the abnormality and the location of the abnormality, such as repairing or replacing the damaged component, welding or replacing the connector lug for the loose circuit, and adjusting the setting of the signal generator or replacing the signal source for the poor signal response. The abnormality processing strategy can help to rapidly and accurately process the abnormality of the display screen, and save maintenance cost and time while ensuring the normal operation of the display screen.
The method for testing the display screen module in the embodiment of the present invention is described above, and the device for testing the display screen module in the embodiment of the present invention is described below, referring to fig. 5, where an embodiment of the device for testing the display screen module in the embodiment of the present invention includes:
the testing module 501 is configured to perform testing analysis on the target display screen module based on a preset testing time and testing parameters to obtain original testing data, and perform data standardization processing on the original testing data to obtain standard testing data;
the classification module 502 is configured to classify and extract the display characteristic parameters of the standard test data to obtain a brightness display characteristic parameter and a color display characteristic parameter, and generate a display characteristic association curve according to the brightness display characteristic parameter and the color display characteristic parameter;
a processing module 503, configured to perform display anomaly analysis on the display characteristic association curve to obtain a luminance and color anomaly value pair, and generate a target anomaly vector according to the luminance and color anomaly value pair;
the analysis module 504 is configured to input the target abnormal vector into a preset display screen abnormal analysis model to perform display screen abnormal analysis, so as to obtain a display screen abnormal analysis result;
The verification module 505 is configured to extract a reaction speed characteristic parameter in the standard test data, and perform analysis result verification on the display screen abnormal analysis result according to the reaction speed characteristic parameter, so as to obtain a target verification result;
and the generating module 506 is configured to generate a display screen abnormality processing policy of the target display screen module according to the target verification result and the display screen abnormality analysis result.
Through the cooperative cooperation of the components, classifying and extracting display characteristic parameters of standard test data to generate a display characteristic association curve; performing display anomaly analysis on the display characteristic association curve to obtain a brightness and color anomaly value pair, and generating a target anomaly vector according to the brightness and color anomaly value pair; inputting the target abnormal vector into a display screen abnormal analysis model to perform display screen abnormal analysis, so as to obtain a display screen abnormal analysis result; extracting characteristic parameters of the reaction speed, and verifying analysis results of abnormal analysis results of the display screen according to the characteristic parameters of the reaction speed to obtain target verification results; according to the method and the device, accurate and comparable test results are obtained through comprehensive performance test and data standardization processing according to target verification results and display screen abnormality analysis results, so that the production efficiency and quality control level of the display screen module are improved, then, through the display characteristic association curve and display abnormality analysis, deeper and comprehensive abnormality detection and analysis can be carried out on the display screen module, and through the target verification results and the display screen abnormality processing strategies, intelligent analysis of parameters of the display screen module is realized, and the test accuracy of the display screen module is improved.
The testing device of the display screen module in the embodiment of the present invention is described in detail from the perspective of the modularized functional entity in fig. 5, and the testing device of the display screen module in the embodiment of the present invention is described in detail from the perspective of hardware processing in the following.
Fig. 6 is a schematic structural diagram of a display screen module testing device according to an embodiment of the present invention, where the display screen module testing device 600 may have a relatively large difference due to different configurations or performances, and may include one or more processors (central processing units, CPU) 610 (e.g., one or more processors) and a memory 620, and one or more storage media 630 (e.g., one or more mass storage devices) storing application programs 633 or data 632. Wherein the memory 620 and the storage medium 630 may be transitory or persistent storage. The program stored on the storage medium 630 may include one or more modules (not shown), each of which may include a series of instruction operations in the test device 600 of the display screen module. Still further, the processor 610 may be configured to communicate with the storage medium 630 to execute a series of instruction operations in the storage medium 630 on the test device 600 of the display module.
The display module testing apparatus 600 may also include one or more power supplies 640, one or more wired or wireless network interfaces 650, one or more input/output interfaces 660, and/or one or more operating systems 631, such as Windows Serve, macOS X, unix, linux, freeBSD, and the like. It will be appreciated by those skilled in the art that the display screen module test device structure shown in fig. 6 does not constitute a limitation of the display screen module test device and may include more or fewer components than shown, or may combine certain components, or may have a different arrangement of components.
The invention also provides a testing device of the display screen module, which comprises a memory and a processor, wherein the memory stores computer readable instructions, and when the computer readable instructions are executed by the processor, the processor executes the steps of the testing method of the display screen module in the embodiments.
The present invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium, or may be a volatile computer readable storage medium, where instructions are stored in the computer readable storage medium, where the instructions, when executed on a computer, cause the computer to perform the steps of the method for testing a display screen module.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (randomacceS memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (5)

1. The testing method of the display screen module is characterized by comprising the following steps of:
based on preset test time and test parameters, performing test analysis on the target display screen module to obtain original test data, and performing data standardization processing on the original test data to obtain standard test data;
classifying and extracting the display characteristic parameters of the standard test data to obtain brightness display characteristic parameters and color display characteristic parameters, and generating a display characteristic association curve according to the brightness display characteristic parameters and the color display characteristic parameters, wherein the method specifically comprises the following steps: acquiring a brightness characteristic parameter range and a color characteristic parameter range corresponding to the standard test data; searching the brightness display characteristic parameters from the standard test data according to the brightness characteristic parameter range, and inquiring the color display characteristic parameters in the standard test data according to the color characteristic parameter range; constructing a first discrete distribution diagram corresponding to the brightness display characteristic parameter and a second discrete distribution diagram corresponding to the color display characteristic parameter; performing data alignment on the first discrete distribution map and the second discrete distribution map to generate a target discrete distribution map; performing association value calculation on the target discrete distribution graph to obtain a target association value set, and generating a display characteristic association curve according to the target association value set;
Performing display anomaly analysis on the display characteristic association curve to obtain a brightness and color anomaly value pair, and generating a target anomaly vector according to the brightness and color anomaly value pair, wherein the method specifically comprises the following steps of: extracting turning points of the display characteristic association curves to obtain a plurality of curve turning points; comparing the curve turning points with the brightness characteristic parameter range and the color characteristic parameter range respectively to obtain a comparison result; determining corresponding display abnormal points from the plurality of curve turning points according to the comparison result, and acquiring time stamp data of each display abnormal point; determining corresponding pairs of luminance and color outliers based on the display outliers and the timestamp data; vector conversion is carried out on the brightness and color abnormal value pairs to generate a target abnormal vector;
inputting the target abnormal vector into a preset display screen abnormal analysis model to perform display screen abnormal analysis to obtain a display screen abnormal analysis result, wherein the method specifically comprises the following steps of: inputting the target abnormal vector into a preset display screen abnormal analysis model, wherein the display screen abnormal analysis model comprises: the first threshold circulation network, the second threshold circulation network and the full connection layer; performing feature extraction and probability prediction on the target abnormal vector through the display screen abnormal analysis model to obtain an abnormal probability value; generating a display screen abnormality analysis result of the target display screen module according to the abnormality probability value and a preset standard range value;
Extracting reaction speed characteristic parameters in the standard test data, and verifying analysis results of the display screen abnormal analysis results according to the reaction speed characteristic parameters to obtain target verification results, wherein the method specifically comprises the following steps of: extracting characteristic parameters related to the reaction speed from the standard test data to obtain the characteristic parameters of the reaction speed, wherein the characteristic parameters of the reaction speed comprise switching time, pixel response time and reaction time; comparing and verifying the characteristic parameters of the reaction speed with the abnormal analysis results of the display screen, and acquiring the abnormal value position in the display characteristic association curve; taking the reaction speed characteristic parameter as an index, and checking whether the abnormal value position is consistent with a bad item in the reaction speed characteristic parameter; if the results are consistent, determining that the display screen abnormality analysis result is correct, and generating a target verification result;
generating a display screen abnormality processing strategy of the target display screen module according to the target verification result and the display screen abnormality analysis result, wherein the display screen abnormality processing strategy specifically comprises the following steps: searching for an abnormal reason and an abnormal position according to the target verification result and the display screen abnormality analysis result, wherein the abnormal reason and the abnormal position comprise: component damage, loose circuit connections, and poor signal response; generating a display screen abnormality processing strategy of the target display screen module according to the abnormality cause and the abnormality position, wherein the display screen abnormality processing strategy comprises: repair or replacement of damaged components, welding or replacement of terminals for loose circuits, and adjustment of the signal generator settings or replacement of signal sources for poor signal response may be performed.
2. The method for testing a display screen module according to claim 1, wherein the testing analysis is performed on the target display screen module based on the preset testing time and the testing parameters to obtain original testing data, and the data normalization processing is performed on the original testing data to obtain standard testing data, including:
acquiring size data, thickness data and bending radian corresponding to a target display screen module to be tested;
setting test time and test parameters according to the size data, the thickness data and the bending radian;
based on the test time and the test parameters, testing and analyzing the target display screen module, and acquiring original test data through a preset parameter acquisition device;
and carrying out missing value interpolation and outlier removal on the original test data to obtain standard test data.
3. The utility model provides a testing arrangement of display screen module, its characterized in that, testing arrangement of display screen module includes:
the testing module is used for carrying out testing analysis on the target display screen module based on preset testing time and testing parameters to obtain original testing data, and carrying out data standardization processing on the original testing data to obtain standard testing data;
The classification module is used for classifying and extracting the display characteristic parameters of the standard test data to obtain brightness display characteristic parameters and color display characteristic parameters, and generating a display characteristic association curve according to the brightness display characteristic parameters and the color display characteristic parameters, and specifically comprises the following steps: acquiring a brightness characteristic parameter range and a color characteristic parameter range corresponding to the standard test data; searching the brightness display characteristic parameters from the standard test data according to the brightness characteristic parameter range, and inquiring the color display characteristic parameters in the standard test data according to the color characteristic parameter range; constructing a first discrete distribution diagram corresponding to the brightness display characteristic parameter and a second discrete distribution diagram corresponding to the color display characteristic parameter; performing data alignment on the first discrete distribution map and the second discrete distribution map to generate a target discrete distribution map; performing association value calculation on the target discrete distribution graph to obtain a target association value set, and generating a display characteristic association curve according to the target association value set;
the processing module is used for carrying out display anomaly analysis on the display characteristic association curve to obtain a brightness and color anomaly value pair, and generating a target anomaly vector according to the brightness and color anomaly value pair, and specifically comprises the following steps: extracting turning points of the display characteristic association curves to obtain a plurality of curve turning points; comparing the curve turning points with the brightness characteristic parameter range and the color characteristic parameter range respectively to obtain a comparison result; determining corresponding display abnormal points from the plurality of curve turning points according to the comparison result, and acquiring time stamp data of each display abnormal point; determining corresponding pairs of luminance and color outliers based on the display outliers and the timestamp data; vector conversion is carried out on the brightness and color abnormal value pairs to generate a target abnormal vector;
The analysis module is used for inputting the target abnormal vector into a preset display screen abnormal analysis model to perform display screen abnormal analysis, and obtaining a display screen abnormal analysis result, and specifically comprises the following steps: inputting the target abnormal vector into a preset display screen abnormal analysis model, wherein the display screen abnormal analysis model comprises: the first threshold circulation network, the second threshold circulation network and the full connection layer; performing feature extraction and probability prediction on the target abnormal vector through the display screen abnormal analysis model to obtain an abnormal probability value; generating a display screen abnormality analysis result of the target display screen module according to the abnormality probability value and a preset standard range value;
the verification module is used for extracting the characteristic parameters of the reaction speed in the standard test data, and verifying the analysis result of the display screen abnormal analysis result according to the characteristic parameters of the reaction speed to obtain a target verification result, and specifically comprises the following steps: extracting characteristic parameters related to the reaction speed from the standard test data to obtain the characteristic parameters of the reaction speed, wherein the characteristic parameters of the reaction speed comprise switching time, pixel response time and reaction time; comparing and verifying the characteristic parameters of the reaction speed with the abnormal analysis results of the display screen, and acquiring the abnormal value position in the display characteristic association curve; taking the reaction speed characteristic parameter as an index, and checking whether the abnormal value position is consistent with a bad item in the reaction speed characteristic parameter; if the results are consistent, determining that the display screen abnormality analysis result is correct, and generating a target verification result;
The generating module is used for generating a display screen abnormality processing strategy of the target display screen module according to the target verification result and the display screen abnormality analysis result, and specifically comprises the following steps: searching for an abnormal reason and an abnormal position according to the target verification result and the display screen abnormality analysis result, wherein the abnormal reason and the abnormal position comprise: component damage, loose circuit connections, and poor signal response; generating a display screen abnormality processing strategy of the target display screen module according to the abnormality cause and the abnormality position, wherein the display screen abnormality processing strategy comprises: repair or replacement of damaged components, welding or replacement of terminals for loose circuits, and adjustment of the signal generator settings or replacement of signal sources for poor signal response may be performed.
4. The utility model provides a test equipment of display screen module, its characterized in that, test equipment of display screen module includes: a memory and at least one processor, the memory having instructions stored therein;
the at least one processor invoking the instructions in the memory to cause the test equipment of the display screen module to perform the method of testing a display screen module of any of claims 1-2.
5. A computer readable storage medium having instructions stored thereon, which when executed by a processor, implement a method of testing a display screen module according to any of claims 1-2.
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