A method and system for optimizing the display of a liquid crystal display screen

Abstract

The present invention relates to the technical field of data processing and optimization, and particularly relates to a method and system for optimizing the display of a liquid crystal display screen. The method includes the following steps: using a sensor to collect display data of the liquid crystal display screen to obtain the display data of the liquid crystal display screen; preprocessing the display data of the liquid crystal display screen to obtain standard display data of the liquid crystal display screen; performing multi-dimensional feature recognition on the standard display data of the liquid crystal display screen to obtain multi-dimensional display feature data; extracting key display information from the multi-dimensional display feature data to obtain key display information; the present invention realizes the analysis of specific environmental conditions through data processing technology, image recognition technology and intelligent control technology to obtain the abnormal display situation of the liquid crystal display screen caused by environmental influence; and dynamically adjusts the display optimization of the abnormal display situation of the liquid crystal display screen, thereby improving the display effect of the liquid crystal display screen.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing and optimization, and particularly to a method and system for optimizing the display of a liquid crystal display screen. Background Art

[0002] A liquid crystal display screen is a digital and character display device developed based on a series of electro-optical effects such as the dynamic scattering and phase change of liquid crystals; early liquid crystal display screens were designed based on current control to achieve the display purpose; with the introduction of color management technology, liquid crystal displays can display higher-resolution image information; for example, the liquid crystal display ADS Pro technology enables liquid crystal displays to have performance in high ambient light contrast, full viewing angle without color deviation, high refresh rate, and dynamic picture optimization; furthermore, it reduces the light reflectivity of the display screen and realizes light adaptability and picture quality performance. However, existing methods for optimizing the display of liquid crystal display screens do not consider the abnormal conditions that occur in the display performance of liquid crystal display screens under specific environmental conditions, and it is difficult to dynamically optimize and adjust the abnormal conditions that occur, resulting in poor display effects of liquid crystal display screens. Summary of the Invention

[0003] Based on this, it is necessary to provide a method and system for optimizing the display of a liquid crystal display screen to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for optimizing the display of a liquid crystal display screen, the method includes the following steps:

[0005] Step S1: Use a sensor to collect display data of the liquid crystal display screen to obtain liquid crystal display screen display data; preprocess the liquid crystal display screen display data to obtain standard liquid crystal display screen display data; perform multi-dimensional feature recognition on the standard liquid crystal display screen display data to obtain multi-dimensional display feature data; extract key display information from the multi-dimensional display feature data to obtain key display information;

[0006] Step S2: Obtain liquid crystal display screen environment data; extract display response characteristics from the key display information according to the liquid crystal display screen environment data to generate display response characteristic data; perform response anomaly analysis on the multi-dimensional display feature data through the display response characteristic data to obtain display response anomaly data;

[0007] Step S3: Determine the display color of the key display information according to the liquid crystal display screen environment data to obtain display color data; combine the display color data to record the real-time display brightness of the key display information to generate display brightness data; measure the display viewing angle of the multi-dimensional display feature data according to the display brightness data and the display color data to obtain display viewing angle data; perform viewing angle anomaly detection on the display viewing angle data to obtain viewing angle anomaly data;

[0008] Step S4: Perform intelligent response optimization on the display response abnormal data to generate response abnormal optimization data; perform adaptive adjustment on the viewing angle abnormal data to obtain viewing angle abnormal adjustment data; construct a liquid crystal display optimization model based on the response abnormal optimization data and the viewing angle abnormal adjustment data to generate a liquid crystal display optimization model; perform display optimization on the liquid crystal display according to the liquid crystal display optimization model to obtain a liquid crystal display optimization report.

[0009] The present invention uses sensors to collect display data of a liquid crystal display screen, ensuring the originality and accuracy of the data; preprocesses the collected display data of the liquid crystal display screen and converts it into standard display data of the liquid crystal display screen, which can remove noise and outliers in the data and improve the quality of the data; performs multi-dimensional feature recognition on the standard display data of the liquid crystal display screen, which can comprehensively capture the performance characteristics of the display screen; extracts key display information from the multi-dimensional display feature data to obtain key display information, focusing on the core elements of the display screen performance and providing an accurate target for optimization. Obtains the environmental data of the liquid crystal display screen, provides specific environmental information for the display screen performance analysis, and ensures the accuracy of the display screen performance analysis; extracts the display response characteristics of the key display information according to the environmental data of the liquid crystal display screen, which can identify the response characteristics of the display screen in different environments and provide a basis for the subsequent optimization of the display screen; performs response anomaly analysis on the multi-dimensional display feature data through the display response feature data, which can timely detect the abnormal response of the display screen. Determines the display color of the key display information according to the environmental data of the liquid crystal display screen, clarifying the relevant situation of the display screen color; combines the display color data to record the real-time display brightness of the key display information, which can monitor the brightness of the display screen in real time; calculates the display viewing angle of the multi-dimensional display feature data according to the display brightness data and the display color data, which can evaluate the viewing angle performance of the display screen and provide a data basis for the subsequent viewing angle display optimization; performs viewing angle anomaly detection on the display viewing angle data, which can identify the viewing angle anomaly of the display screen. Performs intelligent response optimization on the display response anomaly data, which can optimize the abnormal response through intelligent algorithms and improve the performance of the display screen in terms of response; performs adaptive adjustment on the viewing angle anomaly data and adjusts the viewing angle anomaly through adaptive technology, improving the performance of the display screen in terms of viewing angle display; constructs a liquid crystal display screen display optimization model according to the response anomaly optimization data and the viewing angle anomaly adjustment data to generate a liquid crystal display screen display optimization model, which can optimize the display of the liquid crystal display screen; optimizes the display of the liquid crystal display screen according to the liquid crystal display screen display optimization model to obtain a liquid crystal display screen display optimization report, which can achieve an overall improvement in the display screen performance and provide a detailed record of the optimization results in the form of a report. Therefore, the present invention analyzes specific environmental conditions through data processing technology, image recognition technology, and intelligent control technology to obtain the abnormal display situation of the liquid crystal display screen caused by environmental impacts; and dynamically adjusts the display optimization of the abnormal display situation of the liquid crystal display screen, thereby improving the display effect of the liquid crystal display screen.

[0010] Preferably, step S2 includes the following steps:

[0011] Step S21: Use sensors to obtain the environmental data of the liquid crystal display screen, including the display screen environmental temperature feature and the display screen environmental humidity feature;

[0012] Step S22: Extract the display screen environmental humidity characteristics from the liquid crystal display screen environmental data to obtain the display screen environmental humidity data; measure the environmental humidity level for the display screen environmental humidity data to generate the environmental humidity level data;

[0013] Step S23: Extract the display brightness characteristics from the key display information based on the environmental humidity level data to generate the display brightness characteristic data; identify the brightness change for the display brightness characteristic data to obtain the display brightness change data; identify the response time characteristics for the display brightness change data to generate the response time characteristic data; perform a power consumption response detection on the response time characteristic data to obtain the response power consumption characteristic data; integrate the response time characteristic data and the response power consumption characteristic data to obtain the display response characteristic data;

[0014] Step S24: Perform a response anomaly analysis on the multi-dimensional display characteristic data through the display response characteristic data to obtain the display response anomaly data.

[0015] The present invention uses a sensor to obtain the liquid crystal display screen environmental data, including the display screen environmental temperature characteristics and the display screen environmental humidity characteristics, ensuring comprehensive monitoring of the display screen working environment; extracting the display screen environmental humidity characteristics from the liquid crystal display screen environmental data can refine the environmental data and clarify the influence of humidity on the display screen performance; measuring the environmental humidity level for the display screen environmental humidity data enables quantification of the specific influence of humidity on the display screen performance; extracting the display brightness characteristics from the key display information based on the environmental humidity level data converts the influence of environmental humidity into specific characteristics of the display screen brightness, providing a basis for brightness adjustment; identifying the brightness change for the display brightness characteristic data can monitor the real-time change of the display screen brightness, providing dynamic data support for brightness control; identifying the response time characteristics for the display brightness change data can evaluate the relationship between the display screen response speed and the brightness change, providing a data basis for response speed optimization; performing a power consumption response detection on the response time characteristic data can identify the relationship between power consumption and response time; integrating the response time characteristic data and the response power consumption characteristic data to obtain the display response characteristic data, this step synthesizes the data of response time and power consumption, providing comprehensive data analysis for the energy efficiency optimization of the display screen; performing a response anomaly analysis on the multi-dimensional display characteristic data through the display response characteristic data can identify the anomalies existing in the response of the display screen, providing key data for fault diagnosis and performance optimization.

[0016] Preferably, step S24 includes the following steps:

[0017] Step S241: Extract the pixel characteristics of the liquid crystal display screen from the multi-dimensional display feature data to obtain the pixel characteristics of the liquid crystal display screen; mark the gray scale state of the pixel points for the pixel characteristics of the liquid crystal display screen to generate pixel gray scale state data;

[0018] Step S242: Identify the state type of the pixel gray scale state data to obtain the gray scale state type data; measure the type conversion time of the gray scale state type data through the display response feature data to generate the gray scale state conversion time; record the display picture ghosting of the multi-dimensional display feature data according to the gray scale state conversion time to obtain the display picture ghosting information; detect the abnormal display time of the display picture ghosting information to generate the time abnormal response data;

[0019] Step S243: Monitor the state power consumption of the multi-dimensional display feature data according to the gray scale state type data to obtain the state type power consumption data; compare the state type power consumption data with the preset state type power consumption data. If the state type power consumption data is greater than the preset state type power consumption data, mark the state type power consumption data as the power consumption abnormal response data;

[0020] Step S244: Integrate the time abnormal response data and the power consumption abnormal response data to obtain the display response abnormal data.

[0021] The present invention extracts the pixel characteristics of the liquid crystal display screen from the multi-dimensional display feature data, which can clarify the characteristics of each pixel point in the display screen; marks the gray scale state of the pixel points for the pixel characteristics of the liquid crystal display screen, and provides data support for the gray scale performance of the display screen by marking the pixel points with different gray scale states; identifies the state type of the pixel gray scale state data, and provides structured data for understanding the gray scale performance of the display screen by classifying the gray scale states of the pixel points; measures the type conversion time of the gray scale state type data through the display response feature data to quantify the conversion speed of the pixel gray scale state and provide time data for the evaluation of the display screen response speed; records the display picture ghosting of the multi-dimensional display feature data according to the gray scale state conversion time, which can identify and analyze the performance of the display screen in dynamic pictures; detects the abnormal display time of the display picture ghosting information, which can timely discover the abnormal situation of the display screen in time response; monitors the state power consumption of the multi-dimensional display feature data according to the gray scale state type data, specifically by monitoring the power consumption in different gray scale states, so as to evaluate the energy efficiency performance of the display screen in different display states; compares the state type power consumption data with the preset state type power consumption data. If the state type power consumption data is greater than the preset state type power consumption data, mark the state type power consumption data as the power consumption abnormal response data; by comparing the actual power consumption with the preset value, the power consumption abnormality can be identified; integrating the time abnormal response data and the power consumption abnormal response data can comprehensively evaluate the response performance of the display screen.

[0022] Preferably, step S3 includes the following steps:

[0023] Step S31: Extract the display environment temperature characteristics from the liquid crystal display environment data to obtain the display environment temperature data; calculate the degree of the environment temperature for the display environment temperature data to generate the environment temperature degree data; identify the display color characteristics of the key display information according to the environment temperature degree data to obtain the display color data;

[0024] Step S32: Based on the display color data, perform real-time monitoring of the display brightness characteristics data to obtain the display brightness monitoring data; map the brightness parameters for the display brightness monitoring data to generate the display brightness mapping parameters; record the real-time parameters for the display brightness mapping parameters to generate the display brightness data;

[0025] Step S33: Extract the display brightness distribution characteristics from the display brightness data to obtain the display brightness distribution characteristics; partition the brightness according to the display brightness distribution characteristics to generate the display brightness area information; mark the color difference for the display color data through the display brightness area information to generate the display color difference data;

[0026] Step S34: Based on the display color difference data, perform a measurement of the display viewing angle for the multi-dimensional display characteristics data to obtain the display viewing angle data; perform an abnormal detection of the viewing angle for the display viewing angle data to obtain the viewing angle abnormal data.

[0027] The present invention extracts the display ambient temperature characteristics from the ambient data of the liquid crystal display, capable of capturing the temperature conditions of the environment where the display is located; calculates the degree of ambient temperature for the ambient temperature data of the display, clearly quantifying the degree of ambient temperature, enabling the understanding of the performance changes of the display under different temperature conditions; identifies the display color characteristics of the key display information based on the ambient temperature degree data, capable of identifying the characteristics of the display color according to the change of ambient temperature, providing a basis for the adjustment and optimization of color accuracy; conducts real-time monitoring of the display brightness characteristics data based on the display color data, capable of monitoring the brightness change of the display in real time; maps the brightness parameters for the display brightness monitoring data, so that through mapping the brightness parameters, the monitoring data can be converted into parameters available for analysis and adjustment; records the real-time parameters of the display brightness mapping parameters, and by recording the brightness parameters, the real-time change of the display brightness can be traced; extracts the display brightness distribution characteristics from the display brightness data, capable of identifying the distribution characteristics of the display brightness, providing a data basis for the analysis of brightness uniformity; divides the display brightness distribution characteristics into brightness zones according to the display brightness distribution characteristics, and specifically through the zonal brightness distribution, the brightness characteristics of different regions of the display can be identified; marks the color differences for the display color data based on the display brightness region information, capable of marking the color differences according to the different brightness regions, providing detailed data support for the optimization of color consistency; calculates the display viewing angle for the multi-dimensional display characteristics data based on the display color difference data, capable of calculating the viewing angle of the display according to the color difference data; detects the viewing angle abnormality for the display viewing angle data, capable of detecting whether there is an abnormality in the display at different viewing angles.

[0028] Preferably, step S34 includes the following steps:

[0029] Step S341: Set the display observation points for the multi-dimensional display characteristics data based on the display color difference data to obtain the display observation point data; simulate the display angles for the multi-dimensional display characteristics data according to the display observation point data to generate the display angle simulation data;

[0030] Step S342: Use a camera to collect the display images of the display angle simulation data to obtain the simulated angle display image information; enhance the image features of the simulated angle display image information to generate the simulated angle feature enhanced image; record the display parameters of the simulated angle feature enhanced image to obtain the simulated angle display parameter information;

[0031] Step S343: Identify the display brightness status of the analog angle display parameter information to obtain the analog angle brightness status data; perform visible brightness feature marking on the analog angle brightness status data to generate visible brightness feature data; determine the display color status of the analog angle display parameter information according to the visible brightness feature data to generate analog angle color status data; perform visible color feature marking on the analog angle color status data to obtain visible color feature data;

[0032] Step S344: Identify the display visible angle parameters of the display angle analog data based on the visible brightness feature data and the visible color feature data to obtain the display visible angle parameters; perform angle measurement on the display visible angle parameters to obtain the display visible angle data;

[0033] Step S345: Detect the brightness display anomaly of the multi-dimensional display feature data according to the display visible angle data to generate visible brightness display anomaly data; combine the visible brightness display anomaly data and the display visible angle data to detect the visible color display anomaly of the multi-dimensional display feature data to obtain visible color display anomaly data;

[0034] Step S346: Integrate the visible brightness display anomaly data and the visible color display anomaly data to generate visible angle anomaly data.

[0035] The present invention sets display observation points for multi-dimensional display feature data based on display color difference data, which can clarify the observation data points of the display screen; performs display angle simulation on the multi-dimensional display feature data according to the display observation point data, which can show the performance of the display screen at different viewing angles and provides simulation data support for the optimization of the viewing angle performance of the display screen; uses a camera to collect display images of the display angle simulation data, and verifies the accuracy of the simulation data through actual image collection, providing empirical data for the evaluation of the display image quality of the display screen; enhances the image features of the display images at the simulated angles, specifically by enhancing the image features, improving the clarity and recognizability of the images; records the display parameters of the images with enhanced features at the simulated angles, enhancing the display parameters of the images, providing detailed data records for the adjustment and optimization of the display screen parameters; identifies the display brightness status of the display parameter information at the simulated angles, which can identify the brightness status at different display angles; marks the visible brightness features of the brightness status data at the simulated angles, which can identify and optimize the brightness performance of the display screen and provides a data basis for brightness uniformity; determines the display color status of the display parameter information at the simulated angles according to the visible brightness feature data, which can determine the color status at different display angles; marks the visible color features of the color status data at the simulated angles, which can identify and optimize the color performance of the display screen; identifies the display visible angle parameters of the display angle simulation data based on the visible brightness feature data and the visible color feature data, which can clarify the visible angle parameters of the display screen and provides key parameters for the evaluation of the viewing angle performance of the display screen; calculates the angles of the display visible angle parameters, and can quantify the viewing angle performance of the display screen by calculating the visible angle parameters; detects the brightness display anomalies of the multi-dimensional display feature data according to the display visible angle data, which can detect the anomalies in the brightness of the display screen; combines the visible brightness display anomaly data and the display visible angle data to detect the visible color display anomalies of the multi-dimensional display feature data, which can detect the anomalies in the color of the display screen; integrates the visible brightness display anomaly data and the visible color display anomaly data, which can comprehensively evaluate the anomalies in the viewing angle performance of the display screen.

[0036] Preferably, step S4 includes the following steps:

[0037] Step S41: Perform intelligent response optimization on the display response anomaly data to generate response anomaly optimization data;

[0038] Step S42: Perform adaptive adjustment on the visible angle anomaly data to obtain visible angle anomaly adjustment data;

[0039] Step S43: Construct a display optimization model for the liquid crystal display screen based on the response anomaly optimization data and the viewing angle anomaly adjustment data to obtain a preliminary display optimization model for the liquid crystal display screen; and use the response anomaly optimization data and the viewing angle anomaly adjustment data to train the preliminary display optimization model for the liquid crystal display screen to obtain a trained display optimization model for the liquid crystal display screen;

[0040] Step S44: Conduct model cross-validation evaluation on the trained display optimization model for the liquid crystal display screen to obtain model evaluation data; adjust the model parameters of the trained display optimization model for the liquid crystal display screen through the model evaluation data to obtain a display optimization model for the liquid crystal display screen;

[0041] Step S45: Optimize the display of the liquid crystal display screen according to the display optimization model for the liquid crystal display screen to obtain a display optimization report for the liquid crystal display screen.

[0042] The present invention conducts intelligent response optimization on the display response anomaly data, which can optimize the anomalies in the display response, improve the response speed and stability of the liquid crystal display screen; conducts adaptive adjustment on the viewing angle anomaly data, adjusts the anomalies in the viewing angle through adaptive technology, optimizes the color and brightness performance of the liquid crystal display screen at different viewing angles, and improves the viewing angle performance of the display screen; constructs a display optimization model for the liquid crystal display screen based on the response anomaly optimization data and the viewing angle anomaly adjustment data to obtain a preliminary display optimization model for the liquid crystal display screen, providing a basis for subsequent training and optimization; uses the response anomaly optimization data and the viewing angle anomaly adjustment data to train the preliminary display optimization model for the liquid crystal display screen to obtain a trained display optimization model for the liquid crystal display screen, enabling the optimization model to better adapt to the actual display requirements and improving the practicality and effectiveness of the model; conducts model cross-validation evaluation on the trained display optimization model for the liquid crystal display screen to obtain model evaluation data, evaluates the performance of the model through cross-validation, and ensures the accuracy and generalization ability of the model; adjusts the model parameters of the trained display optimization model for the liquid crystal display screen through the model evaluation data, further optimizes the performance of the model by adjusting the model parameters, and ensures the high efficiency and accuracy of the model in practical applications; optimizes the display of the liquid crystal display screen according to the display optimization model for the liquid crystal display screen to obtain a display optimization report for the liquid crystal display screen. This step adjusts the display screen using the optimized model, achieving an improvement in the performance of the display screen.

[0043] Preferably, step S41 includes the following steps:

[0044] Step S411: Calculate the duration of the time anomaly response for the display response anomaly data to obtain time anomaly duration data; correlate the time anomaly duration data with the environmental humidity degree data to generate humidity anomaly time data;

[0045] Step S412: Extract pixel conversion features from the pixel features of the liquid crystal display screen according to the humidity anomaly time data to obtain pixel conversion feature data; record the conversion voltage for the pixel conversion feature data to obtain pixel conversion voltage values; calculate the duration value for the time anomaly duration data to generate an anomaly duration value;

[0046] Step S413: Map the anomaly duration value and the pixel conversion voltage value to obtain a time anomaly - pixel conversion value; based on the time anomaly - pixel conversion value, intelligently increase the pixel conversion voltage of the liquid crystal display screen data to generate pixel conversion voltage optimization measures;

[0047] Step S414: Measure the power consumption anomaly degree of the display response anomaly data to obtain power consumption anomaly degree data; match the power consumption anomaly degree data with the environmental humidity degree data to generate humidity - power consumption situation data; identify the display state of the multi - dimensional display feature data according to the humidity - power consumption situation data to obtain display state data; extract the standby state from the display state data to generate standby display state data; extract the working state from the display state data to generate working display state data;

[0048] Step S415: Based on the standby display state data and the humidity - power consumption situation data, reduce the backlight brightness of the liquid crystal display screen to obtain backlight brightness optimization measures; based on the working display state data and the humidity - power consumption situation data, lower the display refresh rate of the liquid crystal display screen to obtain display refresh rate optimization measures; integrate the backlight brightness optimization measures and the display refresh rate optimization measures to perform power consumption anomaly response optimization measures;

[0049] Step S416: Integrate the pixel conversion voltage optimization measures and the power consumption anomaly response optimization measures to obtain response anomaly optimization data.

[0050] The present invention calculates the duration of abnormal time response for display response abnormal data, which can quantify the duration of display response abnormality and provide data support in the time dimension for subsequent analysis; correlates the abnormal time duration data with the environmental humidity degree data to identify the impact of humidity change on display response; extracts pixel conversion feature for the pixel characteristics of the liquid crystal display screen according to the humidity abnormal time data to analyze the specific impact of humidity change on pixel conversion; records the conversion voltage for the pixel conversion feature data, so as to record the voltage change under different humidity conditions and provide basic data for optimizing voltage adjustment; calculates the numerical value of the duration for the abnormal time duration data to further quantify the impact of abnormal duration; maps the numerical value of abnormal duration to the pixel conversion voltage numerical value to analyze the relationship between time and voltage through mapping; based on the time anomaly-pixel conversion numerical value, intelligently improves the pixel conversion voltage of the liquid crystal display screen display data, so that the voltage setting can be optimized through intelligent algorithm to improve the display performance. Measures the abnormal power consumption degree for the display response abnormal data to obtain the abnormal power consumption degree data, which can quantify the power consumption of the display screen in the abnormal state; matches the abnormal power consumption degree data with the environmental humidity degree data to analyze the impact of humidity on power consumption through matching; identifies the display state for the multi-dimensional display feature data according to the humidity power consumption situation data to clarify the display state under different humidity conditions; extracts the standby state for the display state data to identify the performance of the liquid crystal display screen in the standby state; extracts the working state for the display state data to clarify the performance of the liquid crystal display screen in the working state; reduces the backlight brightness of the liquid crystal display screen based on the standby display state data and the humidity power consumption situation data to effectively reduce power consumption and optimize energy efficiency; reduces the display refresh rate of the liquid crystal display screen based on the working display state data and the humidity power consumption situation data to further reduce power consumption and optimize the display performance; integrates the backlight brightness optimization measures and the display refresh rate optimization measures for power consumption abnormal response optimization measures; integrates the pixel conversion voltage optimization measures and the power consumption abnormal response optimization measures to obtain the response abnormal optimization data.

[0051] Preferably, step S42 includes the following steps:

[0052] Step S421: Extract the abnormal display brightness parameter for the viewing angle abnormal data to obtain the abnormal display brightness parameter; correlate the abnormal display brightness parameter with the environmental temperature degree data to generate the temperature abnormal brightness data;

[0053] Step S422: Calculate the brightness difference between the temperature abnormal brightness data and the preset visible display brightness to obtain the visible display brightness difference data; perform dynamic compensation for the display brightness difference on the liquid crystal display screen based on the visible display brightness difference data to generate the display brightness adjustment measure;

[0054] Step S423: Extract the abnormal display color features from the abnormal visual angle data to obtain the abnormal display color features; pair the abnormal display color features with the ambient temperature degree data to generate temperature abnormal color data;

[0055] Step S424: Perform display color accuracy detection on the temperature abnormal color data to obtain abnormal display color accuracy data; extract the display screen color richness from the abnormal display color accuracy data to generate abnormal display color richness; perform display color adaptive correction on the liquid crystal display screen based on the abnormal display color richness to generate display color accuracy correction measures;

[0056] Step S425: Integrate the display brightness adjustment measures and the display color accuracy correction measures to obtain the abnormal visual angle adjustment data.

[0057] The present invention extracts the abnormal display brightness parameters from the abnormal visual angle data to clarify the brightness abnormality of the display screen at different viewing angles; corresponds the abnormal display brightness parameters with the ambient temperature degree data. Specifically, by associating the brightness abnormality with the ambient temperature, the influence of temperature on the display brightness can be identified; calculate the brightness difference between the temperature abnormal brightness data and the preset visible display brightness to obtain the visible display brightness difference data; perform dynamic compensation of the display brightness difference on the liquid crystal display screen based on the visible display brightness difference data, which optimizes the brightness performance of the display screen under different temperature conditions and improves the display quality; extract the abnormal display color features from the abnormal visual angle data, which can clarify the color abnormality of the display screen at different viewing angles and provide accurate data support for color adjustment; pair the abnormal display color features with the ambient temperature degree data, which can clarify the influence of temperature on the display color and provide a basis for subsequent color optimization; perform display color accuracy detection on the temperature abnormal color data, which can identify the color accuracy problem of the display screen under different temperature conditions and provide data support for color correction; extract the display screen color richness from the abnormal display color accuracy data to clarify the color performance ability of the display screen; perform display color adaptive correction on the liquid crystal display screen based on the abnormal display color richness, which optimizes the color performance of the display screen and improves the color accuracy and visual effect; integrate the display brightness adjustment measures and the display color accuracy correction measures to improve the performance of the display screen at different viewing angles and achieve the optimization of the display performance.

[0058] Preferably, step S45 includes the following steps:

[0059] Step S451: Conduct real-time display monitoring on the liquid crystal display screen to obtain display monitoring data of the screen; extract the abnormal display response monitoring situation from the display monitoring data of the screen to obtain the abnormal display response monitoring situation; extract the abnormal viewing angle monitoring situation from the display monitoring data of the screen to obtain the abnormal viewing angle monitoring situation;

[0060] Step S452: Execute pixel conversion voltage optimization measures based on the liquid crystal display screen display optimization model for the abnormal display response monitoring situation to generate pixel conversion voltage execution data; execute power consumption abnormal response optimization measures through the liquid crystal display screen display optimization model for the abnormal display response monitoring situation to generate power consumption optimization measure execution data;

[0061] Step S453: Execute display brightness adjustment measures based on the liquid crystal display screen display optimization model for the abnormal viewing angle monitoring situation to generate display brightness adjustment execution data; execute display color accuracy correction measures based on the liquid crystal display screen display optimization model for the abnormal viewing angle monitoring situation to generate display color accuracy correction execution data;

[0062] Step S454: Integrate the pixel conversion voltage execution data, power consumption optimization measure execution data, display brightness adjustment execution data, and display color accuracy correction execution data to obtain a liquid crystal display screen display optimization report.

[0063] According to the quality control strategy model, the present invention conducts real-time display monitoring on the liquid crystal display screen, which can continuously track the display performance; extracting the abnormal display response monitoring situation from the display monitoring data of the screen can extract the abnormality in the response time of the screen, providing specific abnormal data for the optimization of the response speed; extracting the abnormal viewing angle monitoring situation from the display monitoring data of the screen can identify the performance abnormality of the screen at different viewing angles, providing specific abnormal data for the optimization of the viewing angle performance; executing pixel conversion voltage optimization measures based on the liquid crystal display screen display optimization model for the abnormal display response monitoring situation improves the response speed and display quality of the screen; executing power consumption abnormal response optimization measures through the liquid crystal display screen display optimization model for the abnormal display response monitoring situation enables the reduction of energy consumption by optimizing the power consumption abnormal response, improving the energy efficiency ratio of the screen; executing display brightness adjustment measures based on the liquid crystal display screen display optimization model for the abnormal viewing angle monitoring situation enables the optimization of the abnormal viewing angle by adjusting the display brightness; executing display color accuracy correction measures based on the liquid crystal display screen display optimization model for the abnormal viewing angle monitoring situation improves the color accuracy and consistency of the screen; integrating the pixel conversion voltage execution data, power consumption optimization measure execution data, display brightness adjustment execution data, and display color accuracy correction execution data provides an execution data of comprehensive optimization measures and a display screen performance optimization report.

[0064] In this specification, a liquid crystal display optimization system is provided for implementing the above-mentioned liquid crystal display optimization method. The liquid crystal display optimization system includes:

[0065] A liquid crystal display data acquisition module, which is used to collect display data of the liquid crystal display by using a sensor to obtain liquid crystal display data; preprocess the liquid crystal display data to obtain standard liquid crystal display data; perform multi-dimensional feature recognition on the standard liquid crystal display data to obtain multi-dimensional display feature data; extract key display information from the multi-dimensional display feature data to obtain key display information;

[0066] A display response anomaly analysis module, which is used to obtain liquid crystal display environment data; extract display response characteristics from the key display information according to the liquid crystal display environment data to generate display response characteristic data; perform response anomaly analysis on the multi-dimensional display feature data through the display response characteristic data to obtain display response anomaly data;

[0067] A viewing angle anomaly detection module, which is used to determine the display color of the key display information according to the liquid crystal display environment data to obtain display color data; combine the display color data to record the real-time display brightness of the key display information to generate display brightness data; calculate the display viewing angle of the multi-dimensional display feature data according to the display brightness data and the display color data to obtain display viewing angle data; perform viewing angle anomaly detection on the display viewing angle data to obtain viewing angle anomaly data;

[0068] A liquid crystal display optimization model module, which is used to perform intelligent response optimization on the display response anomaly data to generate response anomaly optimization data; perform adaptive adjustment on the viewing angle anomaly data to obtain viewing angle anomaly adjustment data; construct a liquid crystal display optimization model according to the response anomaly optimization data and the viewing angle anomaly adjustment data to generate a liquid crystal display optimization model; perform display optimization on the liquid crystal display according to the liquid crystal display optimization model to obtain a liquid crystal display optimization report.

[0069] The present invention displays a data acquisition module through a liquid crystal display screen, and uses sensors to collect display data of the liquid crystal display screen, ensuring the originality and accuracy of the data; preprocesses the collected display data of the liquid crystal display screen and converts it into standard display data of the liquid crystal display screen, which can remove noise and outliers in the data and improve the quality of the data; performs multi-dimensional feature recognition on the standard display data of the liquid crystal display screen, which can comprehensively capture the performance characteristics of the display screen; extracts key display information from the multi-dimensional display feature data to obtain key display information, focusing on the core elements of the display screen performance and providing an accurate target for optimization. Through the display response anomaly analysis module, the environmental data of the liquid crystal display screen is obtained, providing specific environmental information for the display screen performance analysis and ensuring the accuracy of the display screen performance analysis; extracting display response characteristics from the key display information according to the environmental data of the liquid crystal display screen can identify the response characteristics of the display screen under different environments, providing a basis for the subsequent optimization of the display screen; performing response anomaly analysis on the multi-dimensional display feature data through the display response feature data can timely detect the abnormal response of the display screen. Through the viewing angle anomaly detection module, the display color is determined for the key display information according to the environmental data of the liquid crystal display screen, clarifying the relevant situation of the display screen color; combining the display color data to record the real-time display brightness of the key display information can monitor the brightness of the display screen in real time; calculating the display viewing angle of the multi-dimensional display feature data according to the display brightness data and the display color data can evaluate the viewing angle performance of the display screen, providing a data basis for the subsequent viewing angle display optimization; performing viewing angle anomaly detection on the display viewing angle data can identify the viewing angle anomaly of the display screen. Through the liquid crystal display screen display optimization model module, intelligent response optimization is performed on the display response anomaly data, which can optimize the abnormal response through intelligent algorithms and improve the performance of the display screen in terms of response; performing adaptive adjustment on the viewing angle anomaly data and adjusting the viewing angle anomaly through adaptive technology improves the performance of the display screen in terms of viewing angle display; constructing a liquid crystal display screen display optimization model according to the response anomaly optimization data and the viewing angle anomaly adjustment data to generate a liquid crystal display screen display optimization model, which can optimize the display of the liquid crystal display screen; optimizing the display of the liquid crystal display screen according to the liquid crystal display screen display optimization model to obtain a liquid crystal display screen display optimization report, which can achieve an overall improvement in the performance of the display screen and provide a detailed record of the optimization results in the form of a report. Therefore, the present invention realizes the analysis of specific environmental conditions through data processing technology, image recognition technology and intelligent control technology to obtain the abnormal display situation of the liquid crystal display screen caused by environmental impact; and performs dynamic display optimization adjustment on the abnormal display situation of the liquid crystal display screen, thereby improving the display effect of the liquid crystal display screen. Brief Description of the Drawings

[0070] Figure 1It is a schematic diagram of the step process of an optimization method for liquid crystal display screen display;

[0071] Figure 2 It is Figure 1 a schematic diagram of the detailed implementation step process of step S3 in

[0072] Figure 3 It is Figure 2 a schematic diagram of the detailed implementation step process of step S34 in

[0073] The realization, functional characteristics and advantages of the purpose of the present invention will be further described with reference to the embodiments and the accompanying drawings. Specific embodiments

[0074] The technical method of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0075] In addition, the accompanying drawings are only schematic diagrams of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor methods and / or microcontroller methods.

[0076] It should be understood that although terms such as "first", "second", etc. may be used here to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit can be called the second unit, and similarly the second unit can be called the first unit. The term "and / or" used here includes any and all combinations of one or more of the listed associated items.

[0077] To achieve the above object, please refer to Figures 1 to 3 a liquid crystal display screen display optimization method, the method includes the following steps:

[0078] Step S1: Use a sensor to collect display data of the liquid crystal display screen to obtain the display data of the liquid crystal display screen; preprocess the display data of the liquid crystal display screen to obtain the standard display data of the liquid crystal display screen; perform multi-dimensional feature recognition on the standard display data of the liquid crystal display screen to obtain multi-dimensional display feature data; extract key display information from the multi-dimensional display feature data to obtain key display information;

[0079] Step S2: Obtain the environmental data of the liquid crystal display screen; extract the display response characteristics of the key display information according to the environmental data of the liquid crystal display screen to generate display response characteristic data; perform response anomaly analysis on the multi-dimensional display feature data through the display response characteristic data to obtain display response anomaly data;

[0080] Step S3: Determine the display color of the key display information according to the environmental data of the liquid crystal display screen to obtain display color data; combine the display color data to record the real-time display brightness of the key display information to generate display brightness data; calculate the display viewing angle of the multi-dimensional display feature data according to the display brightness data and the display color data to obtain display viewing angle data; perform viewing angle anomaly detection on the display viewing angle data to obtain viewing angle anomaly data;

[0081] Step S4: Perform intelligent response optimization on the display response anomaly data to generate response anomaly optimization data; perform adaptive adjustment on the viewing angle anomaly data to obtain viewing angle anomaly adjustment data; construct a display optimization model for the liquid crystal display screen according to the response anomaly optimization data and the viewing angle anomaly adjustment data to generate a display optimization model for the liquid crystal display screen; optimize the display of the liquid crystal display screen according to the display optimization model of the liquid crystal display screen to obtain a display optimization report of the liquid crystal display screen.

[0082] The present invention uses sensors to collect display data of a liquid crystal display screen, ensuring the originality and accuracy of the data; preprocesses the collected display data of the liquid crystal display screen and converts it into standard display data of the liquid crystal display screen, which can remove noise and outliers in the data and improve the quality of the data; performs multi-dimensional feature recognition on the standard display data of the liquid crystal display screen, which can comprehensively capture the performance characteristics of the display screen; extracts key display information from the multi-dimensional display feature data to obtain key display information, focusing on the core elements of the display screen performance and providing an accurate target for optimization. Obtains the environmental data of the liquid crystal display screen, provides specific environmental information for the display screen performance analysis, and ensures the accuracy of the display screen performance analysis; extracts display response characteristics from the key display information according to the environmental data of the liquid crystal display screen, which can identify the response characteristics of the display screen under different environments and provide a basis for the subsequent optimization of the display screen; performs response anomaly analysis on the multi-dimensional display feature data through the display response feature data, which can timely detect the abnormal response of the display screen. Determines the display color of the key display information according to the environmental data of the liquid crystal display screen, clarifying the relevant situation of the display screen color; combines the display color data to record the real-time display brightness of the key display information, which can monitor the brightness of the display screen in real time; measures the display viewing angle of the multi-dimensional display feature data according to the display brightness data and the display color data, which can evaluate the viewing angle performance of the display screen and provide a data basis for the subsequent viewing angle display optimization; performs viewing angle anomaly detection on the display viewing angle data, which can identify the viewing angle anomaly of the display screen. Performs intelligent response optimization on the display response anomaly data, which can optimize the abnormal response through intelligent algorithms and improve the performance of the display screen in terms of response; performs adaptive adjustment on the viewing angle anomaly data and adjusts the viewing angle anomaly through adaptive technology, improving the performance of the display screen in terms of viewing angle display; constructs a liquid crystal display screen display optimization model according to the response anomaly optimization data and the viewing angle anomaly adjustment data to generate a liquid crystal display screen display optimization model, which can optimize the display of the liquid crystal display screen; optimizes the display of the liquid crystal display screen according to the liquid crystal display screen display optimization model to obtain a liquid crystal display screen display optimization report, which can achieve an overall improvement in the performance of the display screen and provide a detailed record of the optimization results in the form of a report. Therefore, the present invention uses data processing technology, image recognition technology, and intelligent control technology to analyze specific environmental conditions to obtain abnormal display situations of the liquid crystal display screen caused by environmental impacts; and dynamically adjusts the display optimization of the abnormal display situations of the liquid crystal display screen, thereby improving the display effect of the liquid crystal display screen.

[0083] In an embodiment of the present invention, refer to Figure 1 As described, it is a schematic diagram of the step flow of a liquid crystal display screen display optimization method of the present invention. In this example, the liquid crystal display screen display optimization method includes the following steps:

[0084] Step S1: Use a sensor to collect display data of the liquid crystal display screen to obtain the display data of the liquid crystal display screen; preprocess the display data of the liquid crystal display screen to obtain the standard display data of the liquid crystal display screen; perform multi-dimensional feature recognition on the standard display data of the liquid crystal display screen to obtain multi-dimensional display feature data; extract key display information from the multi-dimensional display feature data to obtain key display information;

[0085] In an embodiment of the present invention, a spectral radiance meter is used to collect data of the liquid crystal display screen; the collected original data is preprocessed, specifically including normalization processing, centering processing, and noise reduction processing; further, a filter is designed using the interference bandwidth to perform filtering processing outside the interference band, thereby reducing the influence of noise and clutter to obtain the standard display data of the liquid crystal display screen; multi-dimensional feature recognition is performed on the standard display data of the liquid crystal display screen, specifically extracting multi-dimensional feature parameters from the time domain, frequency domain, and transform domain; for example, the moment kurtosis coefficient in the time domain and the average spectral flatness coefficient in the frequency domain are used to extract multi-dimensional feature parameters; based on the multi-dimensional display feature data, classifiers such as decision trees or support vector machines (SVMs) are used to extract key display information; specifically, the multi-dimensional feature recognition technology is used to extract key information from the display data of the liquid crystal display screen; for example, a key information such as display brightness and display color is extracted by judging the multi-dimensional display feature data through an SVM recognizer.

[0086] Step S2: Obtain the environmental data of the liquid crystal display screen; extract the display response characteristics from the key display information according to the environmental data of the liquid crystal display screen to generate display response characteristic data; perform response anomaly analysis on the multi-dimensional display feature data through the display response characteristic data to obtain display response anomaly data;

[0087] In the embodiments of the present invention, environmental sensors such as temperature sensors, humidity sensors, and light intensity sensors are used to monitor the environmental conditions of the liquid crystal display screen in real time. For example, a temperature sensor is used to obtain temperature data, a temperature and humidity sensor is used to obtain humidity data, and a photodiode is used to obtain light intensity data. According to the environmental data of the liquid crystal display screen, image processing technology is used to extract display response characteristics. For example, the OpenCV technology is adopted to detect feature points in the image of the liquid crystal display screen and extract features such as corners and edges. Specifically, the FAST feature detection algorithm is used with a threshold set to 80 to detect key feature points in the image, and the position and intensity information of the feature points are stored. Machine learning algorithms such as support vector machines (SVMs) are used to classify the display response feature data to identify abnormal data. For example, the SVM is used to perform binary classification on the feature data to distinguish normal and abnormal display responses. Specifically, based on the extracted display response feature data, an SVM classifier is constructed, the feature point data is input, and the classification result is output. By analyzing the classification result, abnormal data in the display response such as display tearing is identified.

[0088] Step S3: Determine the display color of the key display information according to the environmental data of the liquid crystal display screen to obtain display color data; combine the display color data to record the real-time display brightness of the key display information to generate display brightness data; calculate the display viewing angle of the multi-dimensional display feature data according to the display brightness data and the display color data to obtain display viewing angle data; perform abnormal detection on the display viewing angle data to obtain viewing angle abnormal data.

[0089] In the embodiments of the present invention, a color measurement instrument is used to accurately measure the color displayed on the liquid crystal display screen and record the LAB values. Specifically, the LAB values of the color are provided, including the L component (brightness), the A component (range from magenta to dark green), and the B component (range from yellow to blue). A photometer is used to monitor the brightness of the liquid crystal display screen in real time and measure the light output intensity of the display screen at different brightness settings. Specifically, when the display shows a series of standard test images, the process of the display brightness changing from 200 cd / m² to 100 cd / m² is recorded. A viewing angle tester is used to measure the color and contrast changes of the liquid crystal display screen at different angles to determine the horizontal and vertical viewing angles. Specifically, the viewing angle of the display is calculated, and the color and contrast data at different angles are recorded. For example, the measured horizontal viewing angle is 178° and the vertical viewing angle is 178°. Computer vision technology such as feature extraction and matching algorithms is used to analyze the display viewing angle data to identify abnormal angle changes. For example, it is found that at a certain angle, the matching degree of the key points in the image drops significantly, indicating that this angle is an abnormal viewing angle point, and viewing angle abnormal data is obtained.

[0090] Step S4: Perform intelligent response optimization on the display response abnormal data to generate optimized response abnormal data; perform adaptive adjustment on the viewing angle abnormal data to obtain adjusted viewing angle abnormal data; construct a liquid crystal display optimization model based on the optimized response abnormal data and the adjusted viewing angle abnormal data, and generate a liquid crystal display optimization model; perform display optimization on the liquid crystal display according to the liquid crystal display optimization model to obtain a liquid crystal display optimization report.

[0091] In the embodiment of the present invention, display optimization technology is adopted. Specifically, the refresh rate of the display is synchronized with the frame rate of the graphics card to reduce screen tearing and stuttering; further, the OverDrive technology is used to increase the driving voltage to improve the pixel response speed and reduce the ghosting phenomenon; the display optimization technology is used again to adaptively adjust the viewing angle of the display screen; the deep learning technology is used to combine the optimized response abnormal data and the adjusted viewing angle abnormal data to construct a liquid crystal display optimization model; the liquid crystal display is optimized according to the liquid crystal display optimization model, and specific optimization measures are executed for different abnormal situations of the display screen, so as to obtain a liquid crystal display optimization report.

[0092] Preferably, step S2 includes the following steps:

[0093] Step S21: Use a sensor to obtain the liquid crystal display environment data, including the display environment temperature feature and the display environment humidity feature;

[0094] Step S22: Extract the display environment humidity feature from the liquid crystal display environment data to obtain the display environment humidity data; calculate the environmental humidity degree for the display environment humidity data to generate environmental humidity degree data;

[0095] Step S23: Extract the display brightness feature of the key display information based on the environmental humidity degree data to generate display brightness feature data; identify the brightness change for the display brightness feature data to obtain display brightness change data; identify the response time feature for the display brightness change data to generate response time feature data; perform a power consumption response detection on the response time feature data to obtain response power consumption feature data; integrate the response time feature data and the response power consumption feature data to obtain display response feature data;

[0096] Step S24: Perform a response abnormality analysis on the multi-dimensional display feature data through the display response feature data to obtain display response abnormal data.

[0097] In the embodiments of the present invention, an environmental sensor, such as a digital temperature sensor and a temperature and humidity sensor, is used to monitor the environmental temperature and humidity conditions where the liquid crystal display is located in real time; a microcontroller is used to read the data of the sensor and extract the environmental humidity characteristics of the display screen. For example, if the humidity reading is 60%RH, this data is recorded as environmental humidity degree data; according to the environmental humidity degree data, an ambient light sensor is used to record the display screen brightness data, and at the same time, the display brightness change is identified through a pulse width modulation signal, and the response time of the display brightness change data is measured, so as to generate response time characteristic data; while changing the display brightness, an electronic load is used to test the power consumption change of the liquid crystal display screen, specifically by comparing the power consumption data before and after the brightness change, generating response power consumption characteristic data; and integrating it with the response time characteristic data to finally generate display response characteristic data; for example, the increase in brightness resulting in the power consumption rising from 2W to 2.5W will be integrated and recorded; the multi-dimensional display characteristic data is subjected to response anomaly analysis through the display response characteristic data, specifically analyzing the response anomaly situation, so as to obtain display response anomaly data.

[0098] Preferably, step S24 includes the following steps:

[0099] Step S241: Extract the pixel characteristics of the liquid crystal display screen from the multi-dimensional display characteristic data to obtain the pixel characteristics of the liquid crystal display screen; mark the gray scale state of the pixel points for the pixel characteristics of the liquid crystal display screen to generate pixel point gray scale state data;

[0100] Step S242: Identify the state type of the pixel point gray scale state data to obtain gray scale state type data; measure the type conversion time of the gray scale state type data through the display response characteristic data to generate the gray scale state conversion time; record the display screen ghosting for the multi-dimensional display characteristic data according to the gray scale state conversion time to obtain display screen ghosting information; perform display time anomaly detection on the display screen ghosting information to generate time anomaly response data;

[0101] Step S243: Monitor the state power consumption of the multi-dimensional display characteristic data according to the gray scale state type data to obtain state type power consumption data; compare the state type power consumption data with the preset state type power consumption data. If the state type power consumption data is greater than the preset state type power consumption data, mark the state type power consumption data as power consumption anomaly response data;

[0102] Step S244: Integrate the time anomaly response data and the power consumption anomaly response data to obtain display response anomaly data.

[0103] In the embodiments of the present invention, a high-resolution camera is used to collect images of the liquid crystal display screen to obtain high-definition image data of the display screen; further, OpenCV technology is used for image processing, including grayscale processing and binaryzation processing. For example, the imread function of OpenCV is used to read the image in grayscale mode and perform local binaryzation processing to highlight the numbers in the display area; through the connected component analysis function of OpenCV, the connected areas in the binaryzation image are identified and the grayscale states are marked. For example, the connected component analysis is performed on the binaryzation image to extract the digital main area and mark the grayscale state data; the state space model identification toolbox of MATLAB is used to analyze the dynamic response of the display screen to identify the ghosting phenomenon; a load analyzer is used to monitor the power consumption of the liquid crystal display screen in different grayscale states, and the real-time monitored power consumption data is compared with a preset power consumption threshold. For example, the preset power consumption threshold is set to 5W, and the power consumption data exceeding the threshold is marked as abnormal; the data fusion technology is used to integrate the time anomaly response data and the power consumption anomaly response data to form complete display response anomaly data.

[0104] As an example of the present invention, refer to Figure 2 As shown, in this example, step S3 includes:

[0105] Step S31: Extract the display screen environmental temperature characteristics from the liquid crystal display screen environmental data to obtain the display screen environmental temperature data; calculate the environmental temperature degree of the display screen environmental temperature data to generate the environmental temperature degree data; identify the display color characteristics of the key display information according to the environmental temperature degree data to obtain the display color data;

[0106] Step S32: Based on the display color data, perform real-time monitoring of the display brightness characteristics data to obtain the display brightness monitoring data; perform brightness parameter mapping on the display brightness monitoring data to generate the display brightness mapping parameters; record the real-time parameters of the display brightness mapping parameters to generate the display brightness data;

[0107] Step S33: Extract the display brightness distribution characteristics from the display brightness data to obtain the display brightness distribution characteristics; perform brightness zoning on the display brightness distribution characteristics according to the display brightness distribution characteristics to generate the display brightness area information; mark the color difference of the display color data through the display brightness area information to generate the display color difference data;

[0108] Step S34: Based on the display color difference data, perform display viewing angle measurement on the multi-dimensional display characteristics data to obtain the display viewing angle data; perform viewing angle anomaly detection on the display viewing angle data to obtain the viewing angle anomaly data.

[0109] In the embodiments of the present invention, feature extraction technology is used to extract the ambient temperature feature of the liquid crystal display screen from the ambient data of the liquid crystal display screen; the microcontroller reads the sensor data to calculate the ambient temperature level, thereby generating ambient temperature level data; a color measuring instrument is used to identify the display color, measure the color characteristics of the liquid crystal display screen, and record the LAB value, specifically providing the LAB value of the color, including the L component (brightness), the A component (range from magenta to dark green), and the B component (range from yellow to blue); at the same time, a sensor is used to monitor the display brightness in real time to obtain display brightness monitoring data; OpenCV is used to process the display brightness monitoring data to extract the display brightness distribution feature; then, the RGB color data is converted to the Lab color space to mark the color difference and generate display color difference data; a viewing angle calculator is used to calculate the viewing angle based on the visible size and the viewing point distance, and based on the display viewing angle data, an anomaly detection algorithm is used to detect the viewing angle anomaly to obtain display color difference data; according to the display color difference data, a viewing angle calculator is used to calculate the viewing angle; the viewing angle data is subjected to anomaly detection to generate viewing angle anomaly data.

[0110] As an example of the present invention, refer to Figure 3 shown, in this example, step S34 includes:

[0111] Step S341: Based on the display color difference data, set the display observation point for the multi-dimensional display feature data to obtain display observation point data; based on the display observation point data, simulate the display angle for the multi-dimensional display feature data to generate display angle simulation data;

[0112] Step S342: Use a camera to collect the display image of the display angle simulation data to obtain the display image information of the simulated angle; enhance the image features of the display image information of the simulated angle to generate the enhanced image of the simulated angle features; record the display parameters of the enhanced image of the simulated angle features to obtain the display parameter information of the simulated angle.

[0113] Step S343: Identify the display brightness state of the display parameter information of the simulated angle to obtain the display brightness state data of the simulated angle; mark the visible brightness features of the display brightness state data of the simulated angle to generate visible brightness feature data; determine the display color state of the display parameter information of the simulated angle according to the visible brightness feature data to generate the display color state data of the simulated angle; mark the visible color features of the display color state data of the simulated angle to obtain the visible color feature data.

[0114] Step S344: Identify the display viewing angle parameters of the display angle simulation data based on the visible brightness feature data and the visible color feature data to obtain the display viewing angle parameters; calculate the angle of the display viewing angle parameters to obtain the display viewing angle data.

[0115] Step S345: Perform brightness display anomaly detection on the multi-dimensional display feature data according to the display visual angle data to generate visual brightness display anomaly data; combine the visual brightness display anomaly data and the display visual angle data to perform visual color display anomaly detection on the multi-dimensional display feature data to obtain visual color display anomaly data;

[0116] Step S346: Integrate the visual brightness display anomaly data and the visual color display anomaly data to generate visual angle anomaly data.

[0117] In the embodiment of the present invention, based on the display color difference data, computer vision technology, such as the OpenCV library, is used to perform visual analysis on the multi-dimensional display feature data to determine the key observation points; the ray tracing algorithm is used to simulate the propagation path of light at different display angles to generate display angle simulation data; the camera is used to collect images of the display angle simulation data through the OpenCV library to obtain simulated angle display image information; image processing techniques, such as histogram equalization and sharpening filtering, are used to enhance the features of the simulated angle display image information to obtain a simulated angle feature-enhanced image; the camera is used to collect images of the display angle simulation data, and through OpenCV technology, histogram equalization and sharpening filters are applied to enhance the image features to obtain a simulated angle feature-enhanced image; based on the simulated angle display parameter information, an image brightness analysis method, such as the image brightness analysis tool in MATLAB, is used to identify the display brightness state; according to the display brightness state data, computer vision technology is used to mark the visual brightness features to obtain visual brightness feature data; specifically, the brightness state of the simulated angle display parameter information is analyzed using MATLAB, and computer vision technology is used to mark the brightness features to obtain visual brightness feature data; based on the visual brightness feature data and the visual color feature data, an angle measurement algorithm is used to identify the visual angle parameters of the display angle simulation data; the angle is measured according to the visual angle parameters; specifically, the visual brightness and color feature data are analyzed to specifically identify the display visual angle parameters; the angle is further measured to obtain the display visual angle data; combining the visual brightness display anomaly data and the display visual angle data, color anomaly detection technology, such as color histogram analysis, is used to perform visual color display anomaly detection on the multi-dimensional display feature data to obtain visual color display anomaly data; the visual brightness display anomaly data and the visual color display anomaly data are integrated to obtain visual angle anomaly data.

[0118] Preferably, step S4 includes the following steps:

[0119] Step S41: Perform intelligent response optimization on the display response anomaly data to generate response anomaly optimization data;

[0120] Step S42: Perform adaptive adjustment on the visual angle abnormal data to obtain the adjusted visual angle abnormal data;

[0121] Step S43: Construct a liquid crystal display optimization model based on the response abnormal optimization data and the adjusted visual angle abnormal data to obtain a pre-model for liquid crystal display optimization; and use the response abnormal optimization data and the adjusted visual angle abnormal data to train the pre-model for liquid crystal display optimization to obtain a trained model for liquid crystal display optimization;

[0122] Step S44: Conduct model cross-validation evaluation on the trained model for liquid crystal display optimization to obtain model evaluation data; adjust the model parameters of the trained model for liquid crystal display optimization based on the model evaluation data to obtain a model for liquid crystal display optimization;

[0123] Step S45: Optimize the display of the liquid crystal display according to the model for liquid crystal display optimization to obtain a report on the optimized display of the liquid crystal display.

[0124] In the embodiment of the present invention, image processing technology, such as the OpenCV library, is used to analyze and optimize the display response abnormal data to obtain the response abnormal optimization data; the response abnormal optimization data is used to perform intelligent display response optimization on the liquid crystal display; the visual angle abnormal data is adaptively adjusted to obtain the adjusted visual angle abnormal data; an adaptive algorithm is used to dynamically adjust the display parameters according to the ambient light and the user's viewing angle; based on the response abnormal optimization data and the adjusted visual angle abnormal data, a machine learning framework, such as the SVM algorithm, is used to construct a pre-model for liquid crystal display optimization; a cross-validation method, such as K-fold cross-validation, is used to train the pre-model for liquid crystal display optimization to improve the generalization ability and stability of the model; specifically, the cross_val_score function in scikit-learn is used to conduct model cross-validation evaluation to obtain model evaluation data; specifically, the cross_val_score function is used to conduct 5-fold cross-validation evaluation on the trained model to obtain evaluation metrics such as the accuracy and recall rate of the model; then, the C parameter and the kernel function parameter of the SVM algorithm are adjusted according to the evaluation results to obtain the best classification performance; according to the optimized model for liquid crystal display optimization, the display of the liquid crystal display is optimized and an optimization report is generated.

[0125] Preferably, step S41 includes the following steps:

[0126] Step S411: Calculate the duration of the abnormal response over time for the display response abnormal data to obtain the abnormal duration data over time; associate the abnormal duration data over time with the ambient humidity degree data to generate the humidity abnormal time data;

[0127] Step S412: Extract pixel conversion features from the pixel features of the liquid crystal display screen according to the humidity anomaly time data to obtain pixel conversion feature data; record the conversion voltage for the pixel conversion feature data to obtain pixel conversion voltage values; calculate the duration value for the time anomaly duration data to generate an anomaly duration value;

[0128] Step S413: Map the anomaly duration value and the pixel conversion voltage value to obtain a time anomaly - pixel conversion value; based on the time anomaly - pixel conversion value, intelligently increase the pixel conversion voltage of the liquid crystal display screen data to generate pixel conversion voltage optimization measures;

[0129] Step S414: Measure the power consumption anomaly degree of the display response anomaly data to obtain power consumption anomaly degree data; match the power consumption anomaly degree data with the environmental humidity degree data to generate humidity - power consumption situation data; identify the display state of the multi - dimensional display feature data according to the humidity - power consumption situation data to obtain display state data; extract the standby state from the display state data to generate standby display state data; extract the working state from the display state data to generate working display state data;

[0130] Step S415: Reduce the backlight brightness of the liquid crystal display screen based on the standby display state data and the humidity - power consumption situation data to obtain backlight brightness optimization measures; lower the display refresh rate of the liquid crystal display screen based on the working display state data and the humidity - power consumption situation data to obtain display refresh rate optimization measures; integrate the backlight brightness optimization measures and the display refresh rate optimization measures to perform power consumption anomaly response optimization measures;

[0131] Step S416: Integrate the pixel conversion voltage optimization measures and the power consumption anomaly response optimization measures to obtain response anomaly optimization data.

[0132] In the embodiments of the present invention, the event-driven programming technology is adopted to record the timestamps of the occurrence and end of the display response anomaly, and the duration is calculated through the difference between the timestamps; the relative humidity sensor is used to combine the environmental humidity degree data with the time anomaly duration data, and the humidity anomaly time data is determined through data correlation analysis; based on the image processing technology, such as the OpenCV technology, the pixel characteristics of the liquid crystal display are analyzed to extract the pixel conversion characteristics; the analog-to-digital converter (ADC) technology is adopted to record the voltage change corresponding to the pixel conversion; the pixel characteristics of the liquid crystal display are analyzed by using OpenCV to extract the pixel conversion characteristic data; and the voltage value corresponding to the pixel conversion characteristic data is recorded to generate the pixel conversion voltage value; through the mapping algorithm, the anomaly duration value is associated with the pixel conversion voltage value; based on the numerical mapping result, the fuzzy logic control technology is adopted to intelligently adjust the pixel conversion voltage; the anomaly duration value and the pixel conversion voltage value are numerically mapped to obtain the time anomaly - pixel conversion value. Then, the fuzzy logic controller is applied to intelligently increase the pixel conversion voltage to generate the pixel conversion voltage optimization measure; the power consumption monitoring technology is used to measure the power consumption anomaly degree of the display response anomaly data; combined with the environmental humidity degree data, the humidity power consumption situation data is determined through data matching analysis; the pattern recognition technology, such as the support vector machine (SVM), is adopted to classify the display state data to extract the standby and working states; based on the standby display state data, the backlight control technology of the liquid crystal display is used to reduce the backlight brightness; according to the working display state data, the refresh rate of the liquid crystal display is adjusted; the pixel conversion voltage optimization measure and the power consumption anomaly response optimization measure are integrated to obtain the response anomaly optimization data.

[0133] Preferably, step S42 includes the following steps:

[0134] Step S421: Extract the abnormal display brightness parameter from the visual angle anomaly data to obtain the abnormal display brightness parameter; correspond the abnormal display brightness parameter to the environmental temperature degree data to generate the temperature anomaly brightness data;

[0135] Step S422: Calculate the brightness difference between the temperature anomaly brightness data and the preset visual display brightness to obtain the visual display brightness difference data; perform dynamic compensation for the display brightness difference on the liquid crystal display based on the visual display brightness difference data to generate the display brightness adjustment measure;

[0136] Step S423: Extract the abnormal display color feature from the visual angle anomaly data to obtain the abnormal display color feature; pair the abnormal display color feature with the environmental temperature degree data to generate the temperature anomaly color data;

[0137] Step S424: Perform display color accuracy detection on the temperature anomaly color data to obtain abnormal display color accuracy data; extract the color richness of the display screen from the abnormal display color accuracy data to generate abnormal display color richness; perform display color adaptive correction on the liquid crystal display screen based on the abnormal display color richness to generate display color accuracy correction measures;

[0138] Step S425: Integrate the display brightness adjustment measures and the display color accuracy correction measures to obtain the abnormal viewing angle adjustment data.

[0139] In the embodiment of the present invention, OpenCV is used to analyze the abnormal viewing angle data of the liquid crystal display screen, extract the parameters of the brightness anomaly area, and record them as abnormal display brightness parameters; combine the ambient temperature degree data, apply the linear mapping algorithm, and use linear or non-linear mapping techniques to correspond the abnormal display brightness parameters with the ambient temperature degree data to generate temperature anomaly brightness data; adopt numerical analysis methods, such as the numerical operation function in MATLAB, to calculate the brightness difference between the temperature anomaly brightness data and the preset visible display brightness. For example, the preset visible display brightness is set to 300 cd / m²; based on the brightness difference data, use the brightness adjustment technology of the display, such as PWM control, to perform dynamic compensation for the display brightness difference of the liquid crystal display screen; apply the method based on color extraction to analyze the abnormal viewing angle data of the liquid crystal display screen, extract the characteristics of the color anomaly area, and record them as abnormal display color characteristics; combine the ambient temperature degree data, and adopt statistical analysis methods, such as correlation analysis, to pair the abnormal display color characteristics with the ambient temperature degree data; use color calibration technology, such as ICC profile, to perform display color accuracy detection on the temperature anomaly color data; adopt image analysis technology, such as color histogram analysis, to extract the color richness of the display screen from the abnormal display color accuracy data; based on the abnormal display color richness, use the adaptive algorithm to perform display color adaptive correction on the liquid crystal display screen; integrate the display brightness adjustment measures and the display color accuracy correction measures to form the abnormal viewing angle adjustment data.

[0140] Preferably, step S45 includes the following steps:

[0141] Step S451: Perform real-time display monitoring on the liquid crystal display screen to obtain display screen display monitoring data; extract the display response anomaly monitoring situation from the display screen display monitoring data to obtain the display response anomaly monitoring situation; extract the abnormal viewing angle monitoring situation from the display screen display monitoring data to obtain the abnormal viewing angle monitoring situation;

[0142] Step S452: Based on the liquid crystal display optimization model, execute pixel conversion voltage optimization measures for the display response anomaly monitoring situation to generate pixel conversion voltage execution data; based on the liquid crystal display optimization model, execute power consumption anomaly response optimization measures for the display response anomaly monitoring situation to generate power consumption optimization measure execution data;

[0143] Step S453: According to the liquid crystal display optimization model, execute display brightness adjustment measures for the viewing angle anomaly monitoring situation to generate display brightness adjustment execution data; based on the liquid crystal display optimization model, execute display color accuracy correction measures for the viewing angle anomaly monitoring situation to generate display color accuracy correction execution data;

[0144] Step S454: Integrate the pixel conversion voltage execution data, power consumption optimization measure execution data, display brightness adjustment execution data, and display color accuracy correction execution data to obtain a liquid crystal display optimization report.

[0145] In the embodiment of the present invention, visual and image processing technologies are adopted to specifically monitor display response anomalies and viewing angle anomalies; an image sensor is used to extract the display response anomaly monitoring situation by analyzing pixel signal changes; based on the viewing angle limitation and improvement technology of the liquid crystal display, the viewing angle anomaly is identified; based on the liquid crystal display optimization model, the pixel conversion voltage of the liquid crystal display is adjusted, and pixel conversion voltage optimization measures are executed to generate pixel conversion voltage execution data; based on the liquid crystal display optimization model, power consumption anomaly response optimization measures are executed on the liquid crystal display to generate power consumption optimization measure execution data; according to the liquid crystal display optimization model, the backlight brightness of the liquid crystal display is adjusted to generate display brightness adjustment execution data; specifically, the display color accuracy is adjusted according to gamma, brightness, contrast, and color to obtain display color accuracy correction execution data; the data fusion technology is used to integrate the pixel conversion voltage execution data, power consumption optimization measure execution data, display brightness adjustment execution data, and display color accuracy correction execution data to obtain a liquid crystal display optimization report.

[0146] In this specification, a liquid crystal display optimization system is provided for executing the above-mentioned liquid crystal display optimization method. The liquid crystal display optimization system includes:

[0147] A liquid crystal display data acquisition module, which is used to collect display data of the liquid crystal display by using a sensor to obtain liquid crystal display data; preprocess the liquid crystal display data to obtain standard liquid crystal display data; perform multi-dimensional feature recognition on the standard liquid crystal display data to obtain multi-dimensional display feature data; extract key display information from the multi-dimensional display feature data to obtain key display information;

[0148] A display response anomaly analysis module, which is used to obtain the environmental data of the liquid crystal display screen; extract the display response characteristics of key display information according to the environmental data of the liquid crystal display screen to generate display response characteristic data; perform response anomaly analysis on the multi-dimensional display characteristic data through the display response characteristic data to obtain display response anomaly data;

[0149] A visual angle anomaly detection module, which is used to determine the display color of key display information according to the environmental data of the liquid crystal display screen to obtain display color data; combine the display color data to record the real-time display brightness of the key display information to generate display brightness data; calculate the display visual angle of the multi-dimensional display characteristic data according to the display brightness data and the display color data to obtain display visual angle data; perform visual angle anomaly detection on the display visual angle data to obtain visual angle anomaly data;

[0150] A liquid crystal display screen display optimization model module, which is used to perform intelligent response optimization on the display response anomaly data to generate response anomaly optimization data; perform adaptive adjustment on the visual angle anomaly data to obtain visual angle anomaly adjustment data; construct a liquid crystal display screen display optimization model according to the response anomaly optimization data and the visual angle anomaly adjustment data to generate a liquid crystal display screen display optimization model; perform display optimization on the liquid crystal display screen according to the liquid crystal display screen display optimization model to obtain a liquid crystal display screen display optimization report.

[0151] The present invention displays a data acquisition module through a liquid crystal display screen, and uses sensors to collect display data of the liquid crystal display screen, ensuring the originality and accuracy of the data; preprocesses the collected display data of the liquid crystal display screen and converts it into standard display data of the liquid crystal display screen, which can remove noise and outliers in the data and improve the quality of the data; performs multi-dimensional feature recognition on the standard display data of the liquid crystal display screen, which can comprehensively capture the performance characteristics of the display screen; extracts key display information from the multi-dimensional display feature data to obtain key display information, enabling focus on the core elements of the display screen performance and providing an accurate target for optimization. Through the display response anomaly analysis module, the environmental data of the liquid crystal display screen is obtained, providing specific environmental information for the display screen performance analysis and ensuring the accuracy of the display screen performance analysis; extracting display response characteristics from the key display information according to the environmental data of the liquid crystal display screen can identify the response characteristics of the display screen in different environments, providing a basis for subsequent optimization of the display screen; performing response anomaly analysis on the multi-dimensional display feature data through the display response feature data can timely detect abnormal responses of the display screen. Through the viewing angle anomaly detection module, the display color is determined for the key display information according to the environmental data of the liquid crystal display screen, clarifying the relevant situation of the display screen color; combining the display color data to record the real-time display brightness of the key display information can monitor the brightness situation of the display screen in real time; calculating the display viewing angle of the multi-dimensional display feature data according to the display brightness data and the display color data can evaluate the viewing angle performance of the display screen, providing a data basis for subsequent viewing angle display optimization; performing viewing angle anomaly detection on the display viewing angle data can identify the viewing angle anomaly of the display screen. Through the liquid crystal display screen display optimization model module, intelligent response optimization is performed on the display response anomaly data, which can optimize the abnormal response through intelligent algorithms and improve the performance of the display screen in terms of response; adaptively adjusting the viewing angle anomaly data and adjusting the viewing angle anomaly through adaptive technology improve the performance of the display screen in terms of viewing angle display; constructing a liquid crystal display screen display optimization model according to the response anomaly optimization data and the viewing angle anomaly adjustment data to generate a liquid crystal display screen display optimization model, which can optimize the display of the liquid crystal display screen; optimizing the display of the liquid crystal display screen according to the liquid crystal display screen display optimization model to obtain a liquid crystal display screen display optimization report, which can achieve an overall improvement in the display screen performance and provide a detailed record of the optimization results in the form of a report. Therefore, the present invention realizes the analysis of specific environmental conditions through data processing technology, image recognition technology and intelligent control technology to obtain the abnormal display situation of the liquid crystal display screen caused by environmental impact; and dynamically adjusts the display optimization of the abnormal display situation of the liquid crystal display screen, thereby improving the display effect of the liquid crystal display screen.

[0152] Therefore, from any perspective, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Thus, all changes falling within the meaning and scope of the equivalent elements of the application documents are intended to be embraced within the present invention.

[0153] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features invented herein.

Claims

1. A method for optimizing the display of a liquid crystal display screen, characterized in that, Including the following steps: Step S1: Use a sensor to collect display data of the liquid crystal display screen to obtain the display data of the liquid crystal display screen; Preprocess the display data of the liquid crystal display screen to obtain standard display data of the liquid crystal display screen; Perform multi-dimensional feature recognition on the standard display data of the liquid crystal display screen to obtain multi-dimensional display feature data; Extract key display information from the multi-dimensional display feature data to obtain key display information; Step S2: Obtain the environmental data of the liquid crystal display screen; Extract the display response characteristics from the key display information to generate display response characteristic data; Perform response anomaly analysis on the multi-dimensional display feature data through the display response characteristic data to obtain display response anomaly data; The environmental data of the liquid crystal display screen includes the environmental temperature of the display screen and the environmental humidity of the display screen; Extract the environmental humidity characteristics of the liquid crystal display screen environment data to obtain the environmental humidity data of the display screen; Calculate the degree of environmental humidity from the environmental humidity data of the display screen to generate the degree of environmental humidity data; Extract the environmental temperature characteristics of the liquid crystal display screen environment data to obtain the environmental temperature data of the display screen; Calculate the degree of environmental temperature from the environmental temperature data of the display screen to generate the degree of environmental temperature data; Step S3: Determine the display color of the key display information to obtain display color data; Combine the display color data to record the real-time display brightness of the key display information to generate display brightness data; Calculate the display viewing angle of the multi-dimensional display feature data according to the display brightness data and the display color data to obtain the display viewing angle data; Perform viewing angle anomaly detection on the display viewing angle data to obtain viewing angle anomaly data; Step S4: Use the degree of environmental humidity data to perform intelligent response optimization on the display response anomaly data to generate response anomaly optimization data; Use the degree of environmental temperature data to perform adaptive adjustment on the viewing angle anomaly data to obtain viewing angle anomaly adjustment data; Construct a liquid crystal display screen display optimization model according to the response anomaly optimization data and the viewing angle anomaly adjustment data to generate a liquid crystal display screen display optimization model; Optimize the display of the liquid crystal display screen according to the liquid crystal display screen display optimization model to obtain a liquid crystal display screen display optimization report.

2. The method for optimizing the display of a liquid crystal display screen according to claim 1, wherein Step S2 includes the following steps: Step S21: Extract the display brightness characteristics from the key display information to generate display brightness characteristic data; Identify the brightness change from the display brightness characteristic data to obtain display brightness change data; Identify the response time characteristics from the display brightness change data to generate response time characteristic data; Perform power consumption response detection on the response time characteristic data to obtain response power consumption characteristic data; Integrate the response time characteristic data and the response power consumption characteristic data to obtain display response characteristic data; Step S22: Perform response anomaly analysis on the multi-dimensional display feature data through the display response characteristic data to obtain display response anomaly data.

3. The method for optimizing the display of a liquid crystal display screen according to claim 2, wherein Step S24 includes the following steps: Step S241: Extract the pixel features of the liquid crystal display screen from the multi-dimensional display feature data to obtain the pixel features of the liquid crystal display screen; mark the gray-scale states of the pixel points for the pixel features of the liquid crystal display screen to generate pixel gray-scale state data; Step S242: Identify the state types of the pixel gray-scale state data to obtain gray-scale state type data; measure the type conversion time of the gray-scale state type data through the display response feature data to generate the gray-scale state conversion time; record the display picture ghosting of the multi-dimensional display feature data according to the gray-scale state conversion time to obtain the display picture ghosting information; detect the abnormal display time of the display picture ghosting information to generate time anomaly response data; Step S243: Monitor the state power consumption of the multi-dimensional display feature data according to the gray-scale state type data to obtain state type power consumption data; compare the state type power consumption data with the preset state type power consumption data. If the state type power consumption data is greater than the preset state type power consumption data, mark the state type power consumption data as power consumption anomaly response data; Step S244: Integrate the time anomaly response data and the power consumption anomaly response data to obtain the display response anomaly data.

4. The method for optimizing the display of a liquid crystal display screen according to claim 1, wherein Step S3 includes the following steps: Step S31: Identify the display color features of the key display information to obtain the display color data; Step S32: Based on the display color data, perform real-time monitoring of the display brightness features of the display brightness feature data to obtain the display brightness monitoring data; perform brightness parameter mapping on the display brightness monitoring data to generate the display brightness mapping parameters; record the real-time parameters of the display brightness mapping parameters to generate the display brightness data; Step S33: Extract the display brightness distribution features from the display brightness data to obtain the display brightness distribution features; partition the display brightness according to the display brightness distribution features to generate the display brightness area information; mark the color differences of the display color data through the display brightness area information to generate the display color difference data; Step S34: Based on the display color difference data, measure the display viewing angle of the multi-dimensional display feature data to obtain the display viewing angle data; detect the abnormal viewing angle of the display viewing angle data to obtain the abnormal viewing angle data.

5. The method for optimizing the display of a liquid crystal display screen according to claim 4, wherein, Step S34 includes the following steps: Step S341: Set the display observation points for the multi-dimensional display feature data based on the display color difference data to obtain the display observation point data; simulate the display angles of the multi-dimensional display feature data according to the display observation point data to generate the display angle simulation data; Step S342: Use the camera to collect the display images of the display angle simulation data to obtain the simulated angle display image information; enhance the image features of the simulated angle display image information to generate the simulated angle feature enhanced image; record the display parameters of the simulated angle feature enhanced image to obtain the simulated angle display parameter information; Step S343: Identify the display brightness status of the analog angle display parameter information to obtain the analog angle brightness status data; Mark the visual brightness characteristics of the analog angle brightness status data to generate visual brightness characteristic data; Determine the display color status of the analog angle display parameter information according to the visual brightness characteristic data to generate analog angle color status data; Mark the visual color characteristics of the analog angle color status data to obtain visual color characteristic data; Step S344: Identify the display visual angle parameters of the display angle analog data based on the visual brightness characteristic data and the visual color characteristic data to obtain the display visual angle parameters; Calculate the angle of the display visual angle parameters to obtain the display visual angle data; Step S345: Detect the brightness display abnormality of the multi-dimensional display characteristic data according to the display visual angle data to generate visual brightness display abnormality data; Combine the visual brightness display abnormality data and the display visual angle data to detect the visual color display abnormality of the multi-dimensional display characteristic data to obtain visual color display abnormality data; Step S346: Integrate the visual brightness display abnormality data and the visual color display abnormality data to generate visual angle abnormality data.

6. The method for optimizing the display of a liquid crystal display screen according to claim 1, wherein Step S4 includes the following steps: Step S41: Optimize the intelligent response to the display response abnormality data to generate response abnormality optimization data; Step S42: Perform adaptive adjustment on the visual angle abnormality data to obtain visual angle abnormality adjustment data; Step S43: Construct a liquid crystal display optimization model according to the response abnormality optimization data and the visual angle abnormality adjustment data to obtain a liquid crystal display optimization pre-model; And use the response abnormality optimization data and the visual angle abnormality adjustment data to train the liquid crystal display optimization pre-model to obtain a liquid crystal display optimization training model; Step S44: Perform model cross-validation evaluation on the liquid crystal display optimization training model to obtain model evaluation data; Adjust the model parameters of the liquid crystal display optimization training model through the model evaluation data to obtain a liquid crystal display optimization model; Step S45: Optimize the display of the liquid crystal display according to the liquid crystal display optimization model to obtain a liquid crystal display optimization report.

7. The method for optimizing the display of a liquid crystal display screen according to claim 6, wherein, Step S41 includes the following steps: Step S411: Calculate the duration of the time abnormality response of the display response abnormality data to obtain the time abnormality duration data; Correlate the time abnormality duration data with the environmental humidity degree data to generate humidity abnormality time data; Step S412: Extract the pixel conversion feature of the liquid crystal display pixel feature according to the humidity abnormality time data to obtain the pixel conversion feature data; Record the conversion voltage of the pixel conversion feature data to obtain the pixel conversion voltage value; Calculate the duration value of the time abnormality duration data to generate the abnormality duration value; Step S413: Numerically map the abnormal duration value and the pixel conversion voltage value to obtain a time anomaly - pixel conversion value; based on the time anomaly - pixel conversion value, intelligently increase the pixel conversion voltage of the liquid crystal display screen display data to generate pixel conversion voltage optimization measures; Step S414: Measure the power consumption anomaly degree of the display response anomaly data to obtain power consumption anomaly degree data; match the power consumption anomaly degree data with the environmental humidity degree data to generate humidity - power consumption situation data; identify the display state of the multi - dimensional display feature data according to the humidity - power consumption situation data to obtain display state data; extract the standby state from the display state data to generate standby display state data; extract the working state from the display state data to generate working display state data; Step S415: Based on the standby display state data and the humidity - power consumption situation data, reduce the backlight brightness of the liquid crystal display screen to obtain backlight brightness optimization measures; based on the working display state data and the humidity - power consumption situation data, lower the display refresh rate of the liquid crystal display screen to obtain display refresh rate optimization measures; integrate the backlight brightness optimization measures and the display refresh rate optimization measures to perform power consumption anomaly response optimization measures; Step S416: Integrate the pixel conversion voltage optimization measures and the power consumption anomaly response optimization measures to obtain response anomaly optimization data.

8. The method for optimizing the display of a liquid crystal display screen according to claim 6, wherein Step S42 includes the following steps: Step S421: Extract abnormal display brightness parameters from the viewing angle anomaly data to obtain abnormal display brightness parameters; correspond the abnormal display brightness parameters with the environmental temperature degree data to generate temperature anomaly brightness data; Step S422: Calculate the brightness difference between the temperature anomaly brightness data and the preset visible display brightness to obtain visible display brightness difference data; based on the visible display brightness difference data, perform dynamic compensation for the display brightness difference of the liquid crystal display screen to generate display brightness adjustment measures; Step S423: Extract abnormal display color characteristics from the viewing angle anomaly data to obtain abnormal display color characteristics; pair the abnormal display color characteristics with the environmental temperature degree data to generate temperature anomaly color data; Step S424: Detect the display color accuracy of the temperature anomaly color data to obtain abnormal display color accuracy data; extract the richness of the display picture color from the abnormal display color accuracy data to generate abnormal display color richness; based on the abnormal display color richness, perform display color adaptive correction on the liquid crystal display screen to generate display color accuracy correction measures; Step S425: Integrate the display brightness adjustment measures and the display color accuracy correction measures to obtain viewing angle anomaly adjustment data.

9. The method for optimizing the display of a liquid crystal display screen according to claim 6, wherein Step S45 includes the following steps: Step S451: Monitor the real - time display of the liquid crystal display screen to obtain display monitoring data of the display screen; extract the display response anomaly monitoring situation from the display monitoring data of the display screen to obtain the display response anomaly monitoring situation; extract the viewing angle anomaly monitoring situation from the display monitoring data of the display screen to obtain the viewing angle anomaly monitoring situation; Step S452: Based on the liquid crystal display optimization model, execute pixel conversion voltage optimization measures for the display response anomaly monitoring situation to generate pixel conversion voltage execution data; execute power consumption anomaly response optimization measures for the display response anomaly monitoring situation through the liquid crystal display optimization model to generate power consumption optimization measure execution data; Step S453: According to the liquid crystal display optimization model, execute display brightness adjustment measures for the viewing angle anomaly monitoring situation to generate display brightness adjustment execution data; execute display color accuracy correction measures for the viewing angle anomaly monitoring situation based on the liquid crystal display optimization model to generate display color accuracy correction execution data; Step S454: Integrate the pixel conversion voltage execution data, power consumption optimization measure execution data, display brightness adjustment execution data, and display color accuracy correction execution data to obtain a liquid crystal display optimization report.

10. An optimized display system for a liquid crystal display screen, characterized in that, For executing the liquid crystal display optimization method as described in Claim 1, the liquid crystal display optimization system includes: A liquid crystal display data acquisition module, configured to use sensors to collect display data of the liquid crystal display to obtain liquid crystal display data; preprocess the liquid crystal display data to obtain standard liquid crystal display data; perform multi-dimensional feature recognition on the standard liquid crystal display data to obtain multi-dimensional display feature data; extract key display information from the multi-dimensional display feature data to obtain key display information; A display response anomaly analysis module, configured to obtain liquid crystal display environment data; extract display response features from the key display information to generate display response feature data; perform response anomaly analysis on the multi-dimensional display feature data through the display response feature data to obtain display response anomaly data; A viewing angle anomaly detection module, configured to determine the display color of the key display information to obtain display color data; combine the display color data to record the real-time display brightness of the key display information to generate real-time display brightness data; calculate the display viewing angle of the multi-dimensional display feature data based on the display brightness data and the display color data to obtain display viewing angle data; perform viewing angle anomaly detection on the display viewing angle data to obtain viewing angle anomaly data; A liquid crystal display optimization model module, configured to perform intelligent response optimization on the display response anomaly data to generate response anomaly optimization data; perform adaptive adjustment on the viewing angle anomaly data to obtain viewing angle anomaly adjustment data; construct a liquid crystal display optimization model based on the response anomaly optimization data and the viewing angle anomaly adjustment data to generate a liquid crystal display optimization model; perform display optimization on the liquid crystal display according to the liquid crystal display optimization model to obtain a liquid crystal display optimization report.

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