A Comprehensive Evaluation Method for AMOLED Display Performance Based on Multi-Criterion Decision Analysis

Abstract

This invention relates to the field of display performance evaluation technology, and provides a comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis. The method involves constructing a display performance evaluation index system; preprocessing the data and standardizing the preprocessed data; determining the weights of the indicators using the analytic hierarchy process (AHP) based on their importance and contribution; constructing a total utility function using multi-attribute utility theory to obtain the total utility function of the overall display performance of the AMOLED product; constructing a similarity metric analysis model using standardized index data to obtain the similarity between the product's display performance and the optimal product; and combining the total utility function with the similarity score to obtain a comprehensive evaluation score for the product's performance. This invention solves the problems of poor adaptability and flexibility in previous evaluation methods, achieving a comprehensive, objective, and accurate evaluation of AMOLED display performance.

Description

Technical Field

[0001] This invention relates to the field of display performance evaluation technology, and in particular to a comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis. Background Technology

[0002] With the rapid development of mobile devices and high-end TVs, users' demands for displays are no longer limited to basic display functions, but include higher brightness, wider color gamut, faster response speed, and a better visual experience. In the smartphone field, high-end flagship phones primarily use OLED screens, while LCD screens are commonly found in mid-to-low-end models. As under-display cameras and under-display fingerprint unlocking technologies mature, the penetration rate of OLED panels in mobile phones will further increase. AMOLED technology, due to its superior picture quality, ultra-thin design, wide operating temperature range, outdoor visibility, ultra-low power consumption, and eye-friendly characteristics, is gradually becoming the mainstream display technology. In particular, the emergence of Hybrid AMOLED technology combines the advantages of flexible and rigid AMOLED technologies, achieving a near-flexible AMOLED panel's thinness while overcoming the shortcomings of flexible AMOLED screens, such as edge wrinkling, unevenness, and lower strength and reliability, when enlarged.

[0003] To adapt to the development of OLED display products and update technological levels, existing technologies specify methods for evaluating the performance of OLED displays, including performance definitions and testing and evaluation methods for performance indicators, applicable to both rigid and flexible OLED displays. Evaluation methods cover key indicators such as brightness, contrast ratio, chromaticity, and color gamut. For example, brightness testing is conducted in a dark room, using photometry equipment to measure the brightness in the direction normal to the center of the emitting surface. Contrast ratio measurement involves measuring the brightness of full white and full black field signals. With the development of new technologies such as flexible displays, high dynamic range (HDR), and high refresh rates, existing evaluation methods need to be updated to adapt to these new technologies. For example, testing flexible OLEDs needs to consider factors such as bending angle and the number of bends, all of which affect the display characteristics and lifespan of the display. Organizations such as the International Electrotechnical Commission (IEC) are developing OLED display testing standards to ensure the quality and performance of OLED display products. These standards include tests for brightness, contrast ratio, viewing angle, response time, color accuracy, and lifespan. Testing methods need to consider the screen's performance under different environmental conditions, such as temperature, humidity, and light intensity, to ensure that the screen maintains good display performance under various environments.

[0004] AMOLED and OLED are both organic light-emitting diode technologies, but they differ in structure and performance: AMOLED is an active-matrix organic light-emitting diode technology that uses an active matrix drive, with each pixel controlled by an independent thin-film transistor, offering higher resolution, faster response times, and lower power consumption. AMOLED screens are typically used in high-end smartphones and televisions because they can display deeper blacks and more vibrant colors, while also being very thin and flexible. OLED usually refers to passive-matrix OLED technology, which lacks a TFT backplane, so each pixel cannot be individually controlled, resulting in slower response times and higher power consumption. OLED screens are typically used in smaller devices, such as early mobile devices and low-end products. Therefore, existing evaluation methods for AMOLED products largely replicate those for ordinary OLED products, lacking the feature acquisition of brightness and color uniformity across the entire screen, which does not match the display uniformity required for AMOLED products. Furthermore, there is a lack of blue light testing parameters for products under different display modes, and a lack of consideration for eye protection, failing to comprehensively evaluate the performance of AMOLED products. Summary of the Invention

[0005] This invention aims to at least solve one of the technical problems existing in related technologies. To this end, this invention provides a comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis, which solves the problems of poor adaptability and flexibility of previous evaluation methods, and achieves a comprehensive, objective, and accurate evaluation of AMOLED display performance.

[0006] This invention provides a comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis, comprising:

[0007] S1: Construct an AMOLED display performance evaluation index system based on brightness, chromaticity, and blue light indicators;

[0008] S2: Based on the AMOLED display performance evaluation index system, preprocess and standardize the brightness index data, color index data, and blue light index data of AMOLED products to obtain standardized index data.

[0009] S3: Based on the importance and contribution of the luminance index, chromaticity index, and blue light index, the weights of the luminance index, chromaticity index, and blue light index are determined using the analytic hierarchy process (AHP).

[0010] S4: Based on the weights of brightness, chromaticity, and blue light indicators, as well as standardized indicator data, a total utility function is constructed using multi-attribute utility theory to obtain the total utility value of the overall display performance of AMOLED products.

[0011] S5: Construct a similarity measurement analysis model using standardized index data, select a set of AMOLED product parameters under optimal conditions as a reference sequence, and use the similarity measurement analysis model to calculate the similarity coefficient between the actual product parameters and the reference sequence; average the similarity coefficients to obtain the similarity between the display performance of the AMOLED product and the optimal AMOLED product;

[0012] S6: Combine the total utility value of the overall display performance of the AMOLED product with the similarity between the display performance of the AMOLED product and the best AMOLED product to obtain a comprehensive evaluation score of the AMOLED product performance.

[0013] The comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis provided by the present invention further includes step S1,

[0014] Brightness metrics include average brightness of a full white field, average brightness of a full black field, contrast ratio, and brightness uniformity.

[0015] Colorimetric indicators include color gamut coverage and colorimetric uniformity;

[0016] Blue light indicators include blue light radiance, blue light peak wavelength, color temperature, radiance, circadian rhythm factor, and blue light hazard efficiency.

[0017] According to the present invention, a comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis further includes, in step S2, the preprocessing comprising removing outliers and calculating the mean of the dataset. and standard deviation ,lie in Data outside of these categories is considered outlier.

[0018] According to the comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis provided by the present invention, step S2 further includes a standardization process comprising min-max standardization, which scales the utility value of each index to the interval [0, 1], and the calculation expression is:

[0019]

[0020] in, As an indicator, The utility value of the indicator. The minimum value of the indicator. This represents the maximum value of the indicator.

[0021] According to the comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis provided by the present invention, step S2 further includes a standardization process, wherein the standardization process includes 0-1 standardization, and the 0-1 standardization restricts the utility value of each index to the interval [0, 1] by adding upper and lower limits, and the calculation expression is:

[0022]

[0023] in, As an indicator, The utility value of the indicator. The minimum value of the indicator. The maximum value of the indicator. To find the maximum value function, This is a function that takes the minimum value.

[0024] The comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis provided by the present invention further includes step S3,

[0025] The performance indicators of AMOLED products are classified and hierarchized according to their influencing factors;

[0026] By collecting industry experts' judgments and market data, natural language processing technology is used to extract keywords and sentiment from expert opinions, and the importance of each indicator is quantified.

[0027] Cluster analysis is used to identify potential correlations and dependencies between indicators, thereby obtaining objective indicator weights.

[0028] The comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis provided by the present invention further includes step S4,

[0029] Using the weights of the luminance, chromaticity, and blue light indices obtained from the analytic hierarchy process, three separate utility functions are constructed for the three indices: luminance, chromaticity, and blue light.

[0030] The expression for calculating the overall luminance utility function is as follows:

[0031]

[0032] in, To optimize overall brightness, The effect of the average value of the full white field brightness. The average value of the full white field is used as the weight. The effect of the average value of the full black field. The average value of the brightness in a completely black field is weighted. For brightness and contrast effect, For brightness and contrast weights, For the effect of brightness uniformity, Weight for brightness uniformity;

[0033] The expression for calculating the overall chromaticity utility function is:

[0034]

[0035] in, To comprehensively utilize chromaticity, For color gamut coverage utility, As the color gamut coverage weight, For the effect of color uniformity, Weight for color uniformity;

[0036] The formula for calculating the overall blue light utility function is as follows:

[0037]

[0038] in, To optimize the effects of blue light, For blue light radiation specificity, the specificity is as follows: The weighting is based on the proportion of blue light radiation. For the peak wavelength effect of blue light, Weighting of blue light peak wavelength For blue light color temperature effect, Weighting for blue light color temperature. For blue light radiance effect, Blue light radiance weighting, For rhythmic factor effect, For rhythm factor weights, To mitigate the harmful effects of blue light. Weighting of blue light hazard efficiency;

[0039] The expression for calculating the total utility function, constructed based on multi-attribute utility theory, is as follows:

[0040]

[0041] in, The total utility value is calculated based on the multi-attribute utility theory. For the total weight of brightness, For total chromaticity weight, This represents the total weight of blue light.

[0042] According to the comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis provided by the present invention, step S5 further includes the following expression for calculating the similarity coefficient:

[0043]

[0044] in, For the first The product parameter sequence number The similarity coefficient of each data point The resolution coefficient, For the reference sequence The parameter values ​​for each data point For the first The product parameter sequence in the first... Parameter values ​​for each data point; In order to seek The minimum value function, In order to seek Maximum value function;

[0045] The similarity coefficients are averaged to obtain the similarity score for each product. The calculation expression is as follows:

[0046]

[0047] in, It is the number of indicators. This represents the similarity calculated based on the similarity metric analysis model.

[0048] The comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis provided by the present invention further includes, in step S6, the comprehensive evaluation score of each AMOLED product performance is obtained by a weighted average, and the calculation expression is:

[0049]

[0050] in, The overall performance score for AMOLED products. The total utility value is calculated based on the multi-attribute utility theory. The similarity is calculated based on the similarity metric analysis model. For the weights of the multi-attribute utility theory, The weights are used for similarity metric analysis models.

[0051] The present invention provides a comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis, which further includes selecting the AMOLED product with the highest comprehensive evaluation score as the optimal option.

[0052] The above-described one or more technical solutions in the embodiments of the present invention have at least one of the following technical effects:

[0053] This invention provides a comprehensive performance evaluation method for AMOLED displays based on multi-criteria decision analysis. This method not only considers key performance indicators such as brightness, chromaticity, and blue light, but also ensures the scientific rigor and accuracy of the evaluation process through standardization and weight allocation. By implementing this method, a comprehensive score is generated for each AMOLED product, reflecting its overall performance across multiple dimensions. This comprehensive evaluation provides manufacturers, suppliers, and consumers with a reliable decision support tool to help them select the best-performing AMOLED products. This method is highly dynamic and adaptable, capable of flexibly adjusting to the introduction of new technologies and market changes, ensuring the timeliness and forward-looking nature of the evaluation system.

[0054] In practical applications, this invention provides a powerful decision support tool that makes selecting the optimal AMOLED product simple and accurate: the comprehensive evaluation score provides decision-makers with a clear indicator, enabling a comprehensive, objective and accurate evaluation of AMOLED display performance, helping them to quickly identify the best-performing product among multiple alternatives.

[0055] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0056] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0057] Figure 1 This is a flowchart illustrating a comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis provided by the present invention. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention. The following embodiments are used to illustrate this invention but cannot be used to limit the scope of this invention.

[0059] In the description of the embodiments of the present invention, it should be noted that the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0060] like Figure 1 As shown, a comprehensive evaluation method for AMOLED display performance based on multi-criteria decision analysis includes:

[0061] S1: Construct an AMOLED display performance evaluation index system based on brightness, chromaticity, and blue light indicators;

[0062] The performance evaluation system for AMOLED displays includes brightness, colorimetry, and blue light metrics.

[0063] Brightness metrics include average brightness of a full white field, average brightness of a full black field, contrast ratio, and brightness uniformity.

[0064] Brightness is an indicator that measures the luminous intensity of a screen. Too low brightness makes it difficult to distinguish screen details, especially in bright environments, and the screen will appear dim. Too high brightness will cause eye fatigue and discomfort.

[0065] Colorimetric metrics include color gamut coverage and color uniformity. Colorimetric measures the accuracy and range of colors displayed by a monitor.

[0066] Colorimetric index is an indicator that measures the accuracy and range of colors displayed by a monitor;

[0067] Blue light indicators include blue light radiance, blue light peak wavelength, color temperature, radiance, circadian rhythm factor, and blue light hazard efficiency.

[0068] The blue light index is used to comprehensively assess the impact of blue light from AMOLED products on the eyes.

[0069] The purpose of this step is to establish an evaluation framework to ensure the comprehensiveness and systematic nature of the evaluation.

[0070] S2: Based on the AMOLED display performance evaluation index system, preprocess and standardize the brightness index data, color index data, and blue light index data of AMOLED products to obtain standardized index data.

[0071] The purpose of preprocessing is to ensure the quality and consistency of the data, providing an accurate data foundation for subsequent analysis; the purpose of standardization is to eliminate the influence of different indicator units and make the data comparable.

[0072] Preprocessing includes removing outliers and calculating the mean of the data. and standard deviation And define a threshold as the mean plus or minus 3 standard deviations. ,lie in Data outside of these categories is considered outlier.

[0073] Standardization processes include min-max standardization or 0-1 standardization;

[0074] Min-max standardization scales the utility value of each indicator to the interval [0, 1]; the calculation expression is:

[0075]

[0076] in, As an indicator, The utility value of the indicator. The minimum value of the indicator. The maximum value of the indicator.

[0077] The normalized calculation expression for the average luminance of full white (LW) is as follows:

[0078]

[0079] in, The effect of the average value of the full white field brightness. The average brightness of a full white field. This represents the minimum value of the average brightness of a full white field. This represents the maximum value of the average brightness of a full white field.

[0080] The normalized calculation expression for the average luminance of a completely black field (Luminance Black, LB) is as follows:

[0081]

[0082] in, The effect of the average value of the full black field. The average brightness of a completely black field. The minimum average value of the brightness in a completely black field. This represents the maximum value of the average brightness of a completely black field.

[0083] The standardized calculation expression for luminance-to-contrast ratio (CR) is:

[0084]

[0085] in, For brightness and contrast effect, For brightness contrast, This represents the minimum brightness-to-contrast ratio. This represents the maximum brightness contrast ratio.

[0086] The standardized calculation expression for luminance uniformity (LU) is as follows:

[0087]

[0088] in, For the effect of brightness uniformity, For brightness uniformity, This represents the minimum value for brightness uniformity. This represents the maximum value for brightness uniformity.

[0089] Color gamut coverage (CG), the standardized calculation expression is:

[0090]

[0091] in, For color gamut coverage utility, For color gamut coverage, This represents the minimum color gamut coverage. This represents the maximum color gamut coverage.

[0092] The standardized calculation expression for chromaticity uniformity (CU) is as follows:

[0093]

[0094] in, For the effect of color uniformity, For color uniformity, This represents the minimum value for color uniformity. This represents the maximum value for color uniformity.

[0095] The standardized calculation expression for the Blue Light Ratio (BLR) is as follows:

[0096]

[0097] in, For blue light radiation specificity, the specificity is as follows: Blue light radiation ratio This represents the minimum blue light radiance. This represents the maximum value of the blue light radiance.

[0098] The standardized calculation expression for blue light peak wavelength (BLPW) is as follows:

[0099]

[0100] in, For the peak wavelength effect of blue light, The peak wavelength of blue light This represents the minimum peak wavelength of blue light. This represents the maximum value of the blue light peak wavelength.

[0101] The standardized calculation expression for blue light color temperature (CT) is:

[0102]

[0103] in, For blue light color temperature effect, It is the blue light color temperature. This is the minimum blue light color temperature. This represents the maximum blue light color temperature.

[0104] The standardized calculation expression for blue light radiant luminance (RF) is as follows:

[0105]

[0106] in, For blue light radiance effect, Blue light radiance, This represents the minimum blue light radiance. This represents the maximum blue light radiance.

[0107] The standardized calculation expression for the Circadian Factor (KC) is as follows:

[0108]

[0109] in, For rhythmic factor effect, As a rhythm factor, This is the minimum value of the rhythm factor. This represents the maximum value of the rhythm factor.

[0110] Blue Light Hazard Efficiency (BLHE) is calculated using the standardized formula:

[0111]

[0112] in, To mitigate the harmful effects of blue light. To reduce the risk of blue light damage This represents the minimum efficiency for minimizing blue light hazard. This represents the maximum efficiency for blue light hazard prevention;

[0113] 0-1 standardization restricts the utility value of each indicator to the [0,1] interval by adding upper and lower limits. The calculation expression is as follows:

[0114]

[0115] in, As an indicator, The utility value of the indicator. The minimum value of the indicator. The maximum value of the indicator. To find the maximum value function, This is a function that takes the minimum value.

[0116] S3: Based on the importance and contribution of the luminance index, chromaticity index, and blue light index, the weights of the luminance index, chromaticity index, and blue light index are determined using the analytic hierarchy process (AHP).

[0117] The performance indicators of AMOLED products are classified and hierarchized according to their influencing factors;

[0118] By collecting industry experts' judgments and market data, natural language processing technology is used to extract keywords and sentiment from expert opinions, and the importance of each indicator is quantified.

[0119] Cluster analysis is used to identify potential correlations and dependencies between indicators, thereby obtaining objective indicator weights.

[0120] The weights of each indicator are mainly derived from expert and market experience, and are artificially generated data.

[0121] The purpose of this step is to determine the relative importance of each indicator in the evaluation system, so as to provide a reasonable basis for the comprehensive evaluation.

[0122] S4: Based on the weights of brightness, chromaticity, and blue light indicators, as well as standardized indicator data, a total utility function is constructed using multi-attribute utility theory to obtain the total utility value of the overall display performance of AMOLED products.

[0123] Using the weights of each indicator obtained from the analytic hierarchy process, three separate utility functions are constructed for the three indicators of brightness, chromaticity, and blue light.

[0124] The expression for calculating the overall luminance utility function is as follows:

[0125]

[0126] in, To optimize overall brightness, The average value of the full white field is used as the weight. The average value of the brightness in a completely black field is weighted. For brightness and contrast weights, Weight for brightness uniformity;

[0127] The expression for calculating the overall chromaticity utility function is:

[0128]

[0129] in, To comprehensively utilize chromaticity, As the color gamut coverage weight, Weight for color uniformity;

[0130] The formula for calculating the overall blue light utility function is as follows:

[0131]

[0132] in, To optimize the effects of blue light, The weighting is based on the proportion of blue light radiation. Weighting of blue light peak wavelength Weighting of blue light color temperature For blue light radiance weight, For rhythm factor weights, Weighting of blue light hazard efficiency;

[0133] The expression for calculating the total utility function, constructed based on multi-attribute utility theory, is as follows:

[0134]

[0135] in, The total utility value is calculated based on the multi-attribute utility theory. For the total weight of brightness, For total chromaticity weight, This represents the total weight of blue light.

[0136] By combining the effects of various indicators in this way, a utility function reflecting the overall performance of the AMOLED screen is obtained.

[0137] S5: Construct a similarity measurement analysis model using standardized index data, select a set of AMOLED screen parameters under optimal conditions as a reference sequence, and use the similarity measurement analysis model to calculate the similarity coefficient between the actual product parameters and the reference sequence; average the similarity coefficients to obtain the similarity between the display performance of the AMOLED product and the optimal AMOLED product;

[0138] The expression for calculating the similarity coefficient is:

[0139]

[0140] in, For the first The product parameter sequence number The similarity coefficient of each data point The resolution coefficient, For the reference sequence The parameter values ​​for each data point For the first The product parameter sequence in the first... Parameter values ​​for each data point; In order to seek The minimum value function, In order to seek Maximum value function;

[0141] The similarity coefficients are averaged to obtain the similarity score for each product. The calculation expression is as follows:

[0142]

[0143] in, It is the number of indicators. This represents the similarity calculated based on the similarity metric analysis model.

[0144] The similarity between different comparison sequences is compared. The higher the similarity, the closer the sequence is to the reference sequence. In other words, the higher the similarity, the better the display performance.

[0145] The purpose of this step is to assess the similarity between the display performance of the AMOLED product and the ideal state, providing a dynamic similarity analysis for comprehensive evaluation.

[0146] S6: Combine the total utility value of the overall display performance of the AMOLED product with the similarity between the display performance of the AMOLED product and the best AMOLED product to obtain a comprehensive evaluation score of the AMOLED product performance.

[0147] The overall performance score for each AMOLED product is obtained by weighted averaging, and the calculation formula is as follows:

[0148]

[0149] in, The overall performance score for AMOLED products. The total utility value is calculated based on the multi-attribute utility theory. The similarity is calculated based on the similarity metric analysis model. For the weights of the multi-attribute utility theory, The weights are used for similarity metric analysis models.

[0150] It reflects multiple factors related to screen performance; It measures the similarity between screen parameters and the ideal state; and This determines the relative importance of each model in the final evaluation; in this way, the evaluation results of the two models are integrated into a comprehensive evaluation score, so as to more comprehensively evaluate the display performance of AMOLED products.

[0151] Example:

[0152] All the indicators and parameters covered in the evaluation system were collected and integrated. Table 1 shows the statistical values ​​of various parameters for AMOLED products 1-3, Table 2 shows the statistical values ​​of various parameters for AMOLED products 4-6, and Table 3 shows the statistical values ​​of various parameters for AMOLED products 7-9.

[0153] Table 1. Parameters of AMOLED Products 1-3

[0154]

[0155] Table 2 AMOLED Product Parameters 4-6

[0156]

[0157] Table 3 AMOLED Product Parameters 7-9

[0158]

[0159] Based on the established evaluation index system, relevant data were collected and preprocessed and standardized. The processed AMOLED product data are shown in Tables 4 to 6.

[0160] Table 4 shows the parameters of AMOLED products 1-3 after data processing.

[0161]

[0162] Table 5. Parameters of AMOLED products 4-6 after data processing

[0163]

[0164] Table 6. Parameters of AMOLED products 7-9 after data processing

[0165]

[0166] The Analytic Hierarchy Process (AHP) is used to assign weights to the various indicators in the comprehensive evaluation model. When calculating the weights, a judgment matrix is ​​constructed based on detailed expert surveys and data analysis, and a consistency check is used to ensure the logical consistency of the expert scores.

[0167] The weights of each parameter under the brightness index are:

[0168] Average brightness for full white field: 0.2785; Average brightness for full black field: 0.1742; Contrast ratio: 0.2512; Brightness uniformity: 0.2961.

[0169] The weights of the parameters under the colorimetric index are as follows: color gamut coverage: 0.5780, colorimetric uniformity: 0.4220;

[0170] The weights of the parameters under the blue light index are as follows: blue light radiance: 0.2384, blue light peak wavelength: 0.1235, color temperature: 0.1678, radiance: 0.1523, rhythm factor: 0.1459, and blue light hazard efficiency: 0.3141.

[0171] Based on the determined weights and processed index data, and combined with multi-attribute utility theory, a utility function reflecting the overall display performance of AMOLED products is constructed.

[0172] Three indicator utility functions are constructed, and the determined weight values ​​of each indicator are substituted into the comprehensive brightness utility function. Therefore, the expression for the comprehensive brightness utility function is:

[0173]

[0174] The expression for calculating the comprehensive chromaticity utility function is:

[0175]

[0176] The expression for calculating the overall blue light utility function is:

[0177]

[0178] For the total weight of brightness, For total chromaticity weight, The total weight of blue light is determined by professional testing and the analytic hierarchy process, resulting in three weights of 0.3450, 0.2317, and 0.4233, respectively.

[0179] The expression for calculating the total utility function is:

[0180]

[0181] The overall utility value of the nine AMOLED products was calculated, and the results are shown in Tables 7 and 8. The final ranking of the utility values ​​obtained by using the multi-utility theory is shown in Table 9.

[0182] Table 7. Overall Utility Values ​​of AMOLED Products 1-5

[0183]

[0184] Table 8. Overall Utility Values ​​of AMOLED Products 6-9

[0185]

[0186] Table 9 shows the final ranking of utility values ​​calculated using the multi-utility theory.

[0187]

[0188] A similarity metric analysis model is established using the processed data. By determining the reference sequence and calculating similarity parameters, the index similarity results are obtained. The first step in establishing the similarity metric analysis model is to determine the reference sequence, and the specific method is as follows:

[0189] Average brightness for full white field: 768.266667 (select the maximum value, as higher brightness generally means better display performance); Average brightness for full black field: 0.00037 (lower full black field brightness means higher contrast and deeper blacks); Contrast ratio: 1732932.330827 (higher contrast ratio means more obvious differences in brightness and darkness, and better detail); Brightness uniformity: 96.466512 (select the maximum value, as higher brightness uniformity means a more consistent screen display with no overly bright or dark areas); Color gamut coverage: 1.182954 (higher color gamut coverage means richer colors); Color uniformity: 0.001703 (select the minimum value, as lower color uniformity means more consistent color display); Blue light radiation ratio: 21.85904 (select the minimum value, as a lower blue light radiation ratio means less potential harm to the eyes); Blue light peak wavelength: 463. 0. Select the maximum value, because the longer the blue light wavelength, the less potential harm to the eyes; Color temperature reference value: 6731.0. The ideal color temperature depends on the application scenario, but a middle value is usually chosen to balance warm and cool tones; Radiance reference value: 0.3084. Select the minimum value, because lower radiance usually means less eye stimulation from the screen; Circadian rhythm factor reference value: 0.9046544. Select the minimum value, because a lower circadian rhythm factor means less impact on the biological clock; Blue light hazard efficiency parameter... The optimal value is 0.0008836114, chosen as the minimum, because a lower blue light hazard efficiency means a smaller potential risk to visual health; the reference sequence is [768.266667, 0.00037, 1732932.330827, 96.466512, 1.182954, 0.001703, 21.85904, 463.0, 6731.0, 0.3084, 0.9046544, 0.0008836114]. After determining the reference sequence, the data is dimensionless, and the similarity coefficient between the reference sequence and the comparison sequence is calculated using the following formula:

[0190] in, This is the resolution coefficient, which is usually taken as 0.5. The value of the difference between the reference sequence and the comparison sequence at the Kth data point is given. The similarity coefficient of the products is calculated and the results are shown in Table 10-12.

[0191] Table 10 Similarity coefficients of the quantitative analysis model for AMOLED products 1-3

[0192]

[0193] Table 11 Similarity coefficients of the quantitative analysis model for AMOLED products 4-6

[0194] Table 12 Similarity coefficients of the quantitative analysis model for AMOLED products 7-9

[0195]

[0196] The similarity coefficients were averaged to obtain the similarity score for each AMOLED product. Finally, the similarity scores for nine products were obtained and ranked. The results show that product number 9 has the highest similarity to the ideal sequence in terms of its index parameters, indicating its optimal display performance. The product similarity results are shown in Table 13.

[0197] Table 13 Product Similarity Results

[0198]

[0199] By integrating multi-attribute utility theory and similarity metric analysis model, a comprehensive evaluation result of AMOLED display performance was obtained. The complete data in Tables 9 and 13 were initialized. Initialization involves dividing the data of a sequence by its initial value. Since the magnitude differences of sequences for the same factor are not significant, dividing by the initial value helps to bring these values ​​to around the order of 1. The initialization results were then summed to obtain the final comprehensive evaluation score, as shown in Table 14. This step provides decision support, helping to select the AMOLED product with the best performance.

[0200] Table 14 Product Comprehensive Evaluation Score

[0201]

[0202] In this embodiment, a comprehensive method for evaluating AMOLED display performance is developed by integrating multi-attribute utility theory and a similarity metric quantitative analysis model. This method not only considers key performance indicators such as brightness, chromaticity, and blue light, but also ensures the scientific rigor and accuracy of the evaluation process through standardization and weight allocation. By implementing this method, a comprehensive score is generated for each AMOLED product, reflecting its overall performance across multiple dimensions. This comprehensive evaluation provides manufacturers, suppliers, and consumers with a reliable decision support tool to help them select the best-performing AMOLED product. Furthermore, this method addresses the limitations of previous evaluation methods in terms of adaptability and flexibility. It allows for adjustments to evaluation indicators and weights based on different needs and application scenarios to adapt to evolving market demands and technological advancements. This achieves a comprehensive, objective, and accurate evaluation of AMOLED display performance.

[0203] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1.A method for comprehensive evaluation of AMOLED display performance based on multi-criteria decision analysis, characterized in that, Comprise: S1: according to the luminance index, chrominance index and blue light index, the AMOLED display performance evaluation index system is constructed; S2: according to the AMOLED display performance evaluation index system, the luminance index data, chrominance index data and blue light index data of the AMOLED product are preprocessed and standardized, and the standardized index data is obtained; S3: according to the importance and contribution degree of the luminance index, chrominance index and blue light index, the weights of the luminance index, chrominance index and blue light index are determined by using the analytic hierarchy process; S4: according to the weights of the luminance index, chrominance index and blue light index and the standardized index data, the total utility function is constructed by using the multi attribute utility theory, and the total utility value of the overall display performance of the AMOLED product is obtained; S5: the standardized index data is used to construct a similarity quantitative analysis model, a group of AMOLED product parameters in the optimal state is selected as a reference sequence, the similarity coefficient between the actual product parameters and the reference sequence is calculated by using the similarity quantitative analysis model;The similarity coefficient is averaged, and the similarity between the display performance of the AMOLED product and the optimal AMOLED product is obtained; S6: the total utility value of the overall display performance of the AMOLED product and the similarity between the display performance of the AMOLED product and the optimal AMOLED product are combined, and the comprehensive evaluation score of the AMOLED product performance is obtained. 2.The AMOLED display performance comprehensive evaluation method based on multi-criteria decision analysis of claim 1, wherein, In S1 step, The luminance index includes the average value of the luminance full white field, the average value of the luminance full black field, the contrast, the luminance uniformity; The chrominance index includes the color gamut coverage, the chroma uniformity; The blue light index includes the blue light radiation ratio, the blue light peak wavelength, the color temperature, the radiant intensity, the rhythm factor and the blue light hazard efficiency. 3.The AMOLED display performance comprehensive evaluation method based on multi-criteria decision analysis of claim 1, characterized in that, In the S2 step, the preprocessing comprises rejecting outliers, calculating the mean value of the data set and the standard deviation Data lying outside of are considered outliers. 4.The method of claim 1, wherein, In S2 step, the standardization processing includes minimum-maximum standardization, which scales the utility value of each index to the interval [0, 1], and the calculation expression is: wherein is an index, is a utility value of the index, is a minimum value of the index, is a maximum value of the index. 5.The method of claim 1, wherein the method further comprises: In S2 step, the standardization processing includes 0-1 standardization, which limits the utility value of each index in the interval [0, 1] by adding upper and lower limits, and the calculation expression is: wherein, is an index, is a utility value of an index, is a minimum value of an index, is a maximum value of an index, is a max function, is a min function. 6.The method of claim 1, wherein the method further comprises: In S3 step, The performance index of the AMOLED product is classified and hierarchical according to its influencing factors; By collecting the judgments of industry experts and market data, the keywords and sentiment tendency in the expert opinions are extracted by using natural language processing technology, and the importance of each index is quantified; Combining clustering analysis to identify the potential association and dependence between indexes, the objective index weight is obtained. 7.The method of claim 1, wherein the method further comprises: determining a performance of the AMOLED display based on the multi-criteria decision analysis. In S4 step, The weights of the luminance index, chrominance index and blue light index obtained by the analytic hierarchy process are used to construct three separate utility functions for the luminance, chrominance and blue light indexes; The calculation expression of the comprehensive luminance utility function is: wherein, is a luminance full white average utility, is a luminance full white average weight, is a luminance full white average weight, is a luminance full black average utility, is a luminance full black average weight, is a luminance contrast utility, is a luminance contrast weight, is a luminance uniformity utility, is a luminance uniformity weight; The calculation expression of the comprehensive chrominance utility function is: wherein, is a color gamut coverage utility, is a color gamut coverage utility, is a color gamut coverage weight, is a color uniformity utility, is a color uniformity weight; The calculation expression of the comprehensive blue light utility function is: wherein, is a blue light utility, is a blue light radiation ratio utility, is a blue light radiation ratio weight, is a blue light peak wavelength utility, is a blue light peak wavelength weight, is a blue light color temperature utility, is a blue light color temperature weight, is a blue light radiometric utility, is a blue light radiometric weight, is a circadian factor utility, is a circadian factor weight, is a blue light hazard efficiency utility, is a blue light hazard efficiency weight; The calculation expression of the total utility function constructed according to the multi attribute utility theory is: wherein, Utotal is the total utility value calculated according to the multi-attribute utility theory, Utotal is the total utility value calculated according to the multi-attribute utility theory, Utotal is the total utility value calculated according to the multi-attribute utility theory, Utotal is the total utility value calculated according to the multi-attribute utility theory. 8.The method of claim 1, wherein, In S5 step, the calculation expression of the similarity coefficient is: wherein is the similarity coefficient for the jth data point of the ith product parameter sequence, is the resolution coefficient, is the parameter value of the jth data point of the reference sequence, is the parameter value of the jth data point of the ith product parameter sequence; is the minimum function for is the maximum function for ​​​​​​​ The similarity of each product is obtained by averaging the similarity coefficient, and the calculation expression is: wherein, is the number of indicators, is the similarity calculated from the similarity quantification analysis model. 9.The method of claim 1, wherein, In the S6 step, the comprehensive evaluation score of each AMOLED product performance is obtained by a weighted average manner, and the calculation expression is: wherein, is a comprehensive evaluation score of the performance of the AMOLED product, is a total utility value calculated according to a multi-attribute utility theory, is a similarity calculated according to a similarity quantification analysis model, is a weight of the multi-attribute utility theory, is a weight of the similarity quantification analysis model. 10.The method of claim 1, wherein, According to the comprehensive evaluation score of the AMOLED product performance, the AMOLED product with the highest score is selected as the optimal option.

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