Cosmetic brush design management system based on personalized customization

Abstract

The invention discloses a cosmetic brush design management system based on personalized customization, relates to the technical field of product orders, and further realizes accurate capture and satisfaction of personalized demands of users through organic cooperation of five modules. Firstly, a user type locking module obtains related cognitive data according to self-evaluation of users and accurately divides the users into different types, so that the subsequent customization process is more accurate and effective. The sample brush data monitoring module provides a rich reference data basis for personalized design by collecting and recording characteristic data of multiple groups of sample brushes and user feedback. The brush hair testing module is used for deeply analyzing and testing the powder grabbing capacity and the releasing capacity of a makeup green hand, so that a powder grabbing capacity coefficient and a releasing capacity coefficient are accurately calculated, and effective screening is carried out according to a set screening threshold value. And finally, the personalized screening module compares and analyzes the two types of cosmetic brush products and screens out cosmetic brush products which relatively meet the requirements of the user.

Description

Technical Field

[0001] The present invention relates to the technical field of product orders, and in particular to a makeup brush design management system based on personalized customization. Background Art

[0002] In recent years, with the rapid development of the beauty and personalized product market, consumers' requirements for makeup tools have gradually shifted from basic functionality to more professional and personalized needs. In the field of makeup tools, makeup brushes, as one of the key application tools, have received widespread attention due to their direct impact on makeup effects. In particular, the demand for personalized customized makeup brushes is growing, and the differences in experience of different users when using makeup brushes make personalized customization an important way to improve user satisfaction.

[0003] Currently, personalized makeup brushes face many challenges. Traditional makeup brush design and production rely on experience and market feedback. In the existing makeup brush market, most products are difficult to meet consumers' increasingly personalized needs. Especially for makeup novices, choosing suitable makeup brushes often faces many problems, because different makeup brushes may be easy to apply or difficult to apply. Novices often have difficulty in controlling the strength of makeup, resulting in too heavy makeup and affecting the overall makeup. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a makeup brush design management system based on personalized customization, which solves the problems in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a makeup brush design management system based on personalized customization, including a user type locking module, a sample brush data monitoring module, a data processing module, a bristle testing module and a personalized screening module; The user type locking module is used to obtain relevant cognitive data and determine the user type based on the user's self-evaluation; The sample brush data monitoring module is used to collect and record relevant characteristic data information of several groups of sample brushes, and collect feedback data of each sample brush according to the user; The data processing module is used to pre-process the relevant characteristic data information and feedback data obtained in the sample brush data monitoring module to construct a personalized design data set, and combine the dimensionless processing technology to eliminate the dimension in the personalized design data set to form a dimensionless form; The brush test module is used to analyze the powder-grabbing properties of the sample brushes based on the personalized design data set when the user type is a makeup novice, so as to construct the powder-grabbing ability coefficient Zfxs of the corresponding sample brushes, and to screen several groups of sample brushes through a pre-set screening threshold Q, and to execute the test command on the screened sample brushes, and to test the release ability coefficient Snxs of the corresponding sample brushes in turn; The personalized screening module is used to compare and analyze the powder grabbing ability coefficient Zfxs of the sample brush with the release ability coefficient Snxs of the corresponding sample brush to screen out the makeup brushes that meet the user's needs and set them as the user's personalized order products.

[0006] Preferably, the user type locking module includes a cognition acquisition unit and a type positioning unit; The cognitive acquisition unit is used to conduct a questionnaire survey on the user in advance to obtain relevant cognitive data of the user based on the user's self-evaluation. The relevant cognitive data includes the user's frequency of use of makeup brushes Spz, years of makeup experience Hnx, usage habits and types of makeup tools.

[0007] Preferably, the type positioning unit is used to extract features from relevant cognitive data to obtain the user's makeup experience years Hnx and usage frequency Spz, and calculate a proficiency value Sz based on the user's makeup experience years Hnx and usage frequency Spz. The proficiency value Sz is obtained by the following formula: ; Wherein, e represents the Euler number, a and b represent the weight values ​​of the frequency of use and years of makeup experience, respectively; A threshold is preset, and the proficiency value Sz is compared with the threshold to determine the makeup type of the current user. The specific determination content is as follows: If the proficiency value Sz exceeds the threshold, it indicates that the makeup type of the current user is an experienced makeup artist; If the proficiency value Sz does not exceed the threshold, it indicates that the current user's makeup type is a makeup novice.

[0008] Preferably, the sample brush data monitoring module includes a brush quality collection unit and a feedback information collection unit; The brush quality collection unit is used to collect and record relevant characteristic data information of several groups of sample brushes, wherein the relevant characteristic data information includes the bristle hardness Smyd, bristle roughness Sccd, bristle density Smd, elastic coefficient Txs and adhesion Ffz of each sample brush; The feedback information collection unit is used to record the user's feedback on each sample brush to obtain feedback data, and the feedback data includes the user's feedback score weight R on the bristle hardness Smyd of each sample brush.

[0009] Preferably, the data processing module includes a preprocessing unit and a standardization unit; The preprocessing unit is used to use data preprocessing technology to identify and eliminate errors, abnormal values ​​and noise data information of the relevant characteristic data information and the feedback data, and perform feature extraction to extract useful feature data therefrom to construct a personalized design data set; The standardization unit is used to standardize the feature data after feature extraction according to the dimensionless processing technology, and use a standardization method to make it have a uniform scale, wherein the standardization method includes Z-score standardization.

[0010] Preferably, the bristle testing module includes a personalized screening unit, a preliminary analysis unit and a matching analysis unit; The personalized screening unit is used to screen out the bristle hardness Smyd that suits the user's preference according to the user's feedback data on each sample brush, and is specifically obtained in the following manner: ; Where i=1, 2, 3, ..., n, n represents the number of sample brushes, It is represented as the bristle hardness of the i-th sample brush, It is represented as the user's feedback rating weight on the bristle hardness of the i-th sample brush.

[0011] Preferably, the preliminary analysis unit is used to screen out sample brushes with the same bristle hardness Smyd as the bristle hardness Smyd that fits the user's preference according to the bristle hardness Smyd obtained in the personalized screening unit, and perform statistics to obtain a set of similar sample brushes, and construct a powder grabbing ability coefficient Zfxs of the corresponding sample brush according to relevant characteristic data information, which is specifically calculated and obtained in the following manner: ; In the formula, Smd represents the bristle density, Sccd represents the bristle roughness, and C represents the correction constant. and are weight values, where 0 < ≤1,0< ≤1, and + =1.

[0012] Preferably, according to the calculation method of obtaining the powder grabbing ability coefficient Zfxs of the corresponding sample brush in the preliminary analysis unit, the powder grabbing ability coefficients Zfxs of multiple groups of sample brushes in the same sample brush set are obtained in sequence, and according to the powder grabbing ability coefficients Zfxs of multiple groups of sample brushes in the same sample brush set, the screening threshold Q is set, and the specific setting content is as follows: The fan grabbing ability coefficients Zfxs of multiple groups of sample brushes in the same sample brush set are calculated by statistical averaging algorithm to obtain the average fan grabbing ability coefficients of the sample brushes in the same sample brush set. And the standard deviation of the powder grabbing ability coefficient of the sample brushes in the same sample brush set ; Based on the average powder grabbing ability coefficient of sample brushes in the same sample brush set And the standard deviation of the powder grabbing ability coefficient of the sample brushes in the same sample brush set , obtain the screening threshold Q; ; Among them, k is a constant, and the specific value is set by the user; The powder-grabbing ability coefficients Zfxs of multiple groups of sample brushes in the same sample brush set are compared with the screening threshold Q to screen out the powder-grabbing ability coefficients Zfxs suitable for makeup novices. If the powder-grabbing ability coefficients Zfxs of the sample brushes in the same sample brush set are ≤ the screening threshold Q, the corresponding sample brushes are marked as suitable sample brushes; if the powder-grabbing ability coefficients Zfxs of the sample brushes in the same sample brush set are > the screening threshold Q, the corresponding sample brushes are temporarily not marked as suitable sample brushes.

[0013] Preferably, the matching analysis unit is used to collect statistics on the matching sample brushes and issue a test command, and test and analyze the matching sample brushes in turn to obtain the release capacity coefficient Snxs of the corresponding sample brush, which is specifically obtained in the following manner: ; Where Txs is the elastic coefficient of the bristles, It is represented as the displacement of the bristle being stretched, and Ffz is represented as the adhesion force.

[0014] Preferably, the personalized screening module includes a comparison unit and a locking unit; The comparison unit is used to compare and analyze the powder grabbing capacity coefficient Zfxs of the sample brush with the release capacity coefficient Snxs of the corresponding sample brush to calculate the powder retention coefficient Fzzs of the corresponding sample brush, which is specifically obtained in the following manner: .

[0015] The locking unit is used to compare the powder retention coefficient Fzzs with the value 1 to screen out makeup brushes that meet the user's requirements. The specific contents are as follows: If the powder retention coefficient Fzzs = 1, it means that the bristles of the corresponding sample brush can balance the ability to grab powder and release powder. At this time, the sample brush is set as a user personalized order product to customize a unique makeup brush for the user; If the powder retention coefficient Fzzs≠the value of 1, it means that the powder captured by the bristles of the corresponding sample brush cannot be effectively released.

[0016] The present invention provides a makeup brush design management system based on personalized customization, which has the following beneficial effects: (1) Through the organic collaboration of five modules, the system further realizes the accurate capture and satisfaction of users' personalized needs. First, the user type locking module obtains relevant cognitive data based on the user's self-evaluation and accurately divides users into different types, making the subsequent customization process more accurate and effective. The sample brush data monitoring module provides a rich reference data basis for personalized design by collecting and recording the characteristic data and user feedback of multiple groups of sample brushes. The brush test module conducts in-depth analysis and testing of the powder grabbing and releasing abilities of makeup novices, so as to accurately calculate the powder grabbing ability coefficient Zfxs and the releasing ability coefficient Snxs, and effectively screen according to the set screening threshold Q. Finally, the personalized screening module compares and analyzes the two to select makeup brush products that relatively meet user needs. The beneficial effect of this system is that it not only enhances the user's personalized customization experience, further ensures the efficiency and comfort of makeup brushes in actual use, but also provides customized product recommendations for different user groups, especially makeup novices, thereby improving user satisfaction. This systematic, data-driven design process not only simplifies the user's selection process, but also enhances the match between products and user needs, further avoiding the subjectivity and uncertainty in the traditional customization process.

[0017] (2) The personalized screening unit can accurately screen out the bristle hardness Smyd that meets the user's preference through the user's feedback data on each sample brush. This personalized screening method uses the user's feedback score weight on the bristle hardness of each sample brush. This method can not only comprehensively consider the user's personalized needs, but also ensure the scientificity and reliability of the screening results through comparative analysis of multiple samples. For makeup novices, this screening process is particularly important because makeup novices' demand for makeup tools is more dependent on personalized guidance and scientific analysis results, thereby reducing confusion and blindness in selection. In short, this process not only improves the matching degree of bristle hardness, but also effectively improves the user's experience and satisfaction. This method further enhances the ability of personalized customization, so that each makeup brush can meet the user's expectations as much as possible, thereby providing users with a higher quality makeup experience.

[0018] (3) Based on the bristle hardness Smyd that suits the user's preferences obtained by the personalized screening unit, the system can further calculate the powder-grabbing ability of each sample brush and mark the qualified sample brushes as matching brushes. This marking process improves the screening accuracy, ensuring that makeup novices can choose suitable brushes, effectively improving the makeup effect and experience.

[0019] (4) Through the matching analysis unit, the system can accurately test the release ability of the matching sample brush and obtain the release ability coefficient Snxs, thus realizing a scientific evaluation of the powder release ability of the sample brush in actual use. Secondly, in the personalized screening module, the powder grabbing ability coefficient Zfxs of the sample brush is combined with the release ability coefficient Snxs to generate the powder retention coefficient Fzzs, so that users can quickly screen out brushes that meet their makeup habits through simple comparison and analysis. When the powder retention coefficient Fzzs is equal to 1, it indicates that the sample brush has reached a balance point between powder grabbing and releasing, and can effectively grab and release powder, thereby achieving a uniform and natural makeup effect. Especially for makeup novices, such a makeup brush is easier to control, reducing the phenomenon of uneven makeup or flying powder, making the makeup process smoother. In addition, the comparison mechanism of the powder retention coefficient Fzzs also enhances the system's personalized customization capabilities. When the powder retention coefficient Fzzs is not equal to 1, the system will intelligently identify the shortcomings of the brush in powder release, such as powder accumulation or loss, and help users avoid using unsuitable brushes through this analysis result. This not only improves the utilization efficiency of powder and reduces unnecessary waste, but also significantly improves the accuracy and effect of makeup. In summary, the system further optimizes the customization process of makeup brushes through the synergy of the matching analysis unit and the personalized screening module, providing a more accurate and scientific brush selection solution, which is especially suitable for makeup novices and improves the overall makeup experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a block diagram of a makeup brush design management system based on personalized customization according to the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Example 1 See also Figure 1, the present invention provides a makeup brush design management system based on personalized customization, including a user type locking module, a sample brush data monitoring module, a data processing module, a bristle testing module and a personalized screening module; The user type locking module is used to obtain relevant cognitive data and determine the user type based on the user's self-evaluation; The sample brush data monitoring module is used to collect and record relevant characteristic data information of several groups of sample brushes, and collect feedback data of each sample brush according to the user; The data processing module is used to pre-process the relevant characteristic data information and feedback data obtained in the sample data monitoring module to construct a personalized design data set, and combine the dimensionless processing technology to eliminate the dimensions in the personalized design data set to form a dimensionless form; in the data processing module, the dimensionless processing technology is used to eliminate the dimension differences and construct a dimensionless personalized design data set, making data analysis more standardized and standardized, ensuring a unified comparison standard between different parameters.

[0023] The brush test module is used to analyze the powder-grabbing properties of the sample brushes based on the personalized design data set when the user type is a makeup novice, so as to construct the powder-grabbing ability coefficient Zfxs of the corresponding sample brushes, and to screen several groups of sample brushes through a pre-set screening threshold Q, and to execute the test command on the screened sample brushes, and to test the release ability coefficient Snxs of the corresponding sample brushes in turn; The personalized screening module is used to compare and analyze the powder grabbing ability coefficient Zfxs of the sample brush with the release ability coefficient Snxs of the corresponding sample brush to screen out the makeup brushes that meet the user's needs and set them as the user's personalized order products.

[0024] During the operation of this system, the system accurately determines the user type based on the user's self-evaluation and cognitive data through the user type locking module, especially for the type of makeup novice, so that the subsequent makeup brush customization is more in line with the actual needs of the user. This module ensures the basis for personalized customization, thereby improving user satisfaction and product applicability. Secondly, the combined use of the sample brush data monitoring module and the data processing module can systematically collect and process a large amount of sample brush data, and eliminate the dimensional differences in the data set through dimensionless processing technology to form standardized and comparable data. This processing method not only improves the efficiency of data analysis, but also ensures the comparability between different bristle characteristics, providing scientific data support for personalized design. Thirdly, the bristle testing module can accurately screen and test different sample brushes by analyzing the powder grabbing ability coefficient Zfxs and release ability coefficient Snxs required by makeup novices. This refined testing process makes it easier for makeup novices to find makeup brushes that can effectively grab powder and moderately release powder, thereby improving the user's makeup experience. Finally, the personalized screening module compares and analyzes the powder grabbing ability coefficient and the release ability coefficient to screen out makeup brushes that meet user needs. The introduction of this module further improves the accuracy and efficiency of personalized customization, allowing the final product to more accurately meet the user's personalized needs, especially for makeup novices, which can significantly reduce the troubles that may be encountered during the purchase and use process.

[0025] Example 2 Please refer to Figure 1 ,Specifically: the user type locking module includes a cognitive acquisition unit and a type positioning unit; The cognitive acquisition unit is used to conduct a questionnaire survey on the user in advance to obtain relevant cognitive data of the user based on the user's self-evaluation. The relevant cognitive data includes the user's frequency of use of makeup brushes Spz, years of makeup experience Hnx, usage habits and types of makeup tools, wherein the types of makeup tools include but are not limited to foundation brushes, concealer brushes, loose powder brushes, blush brushes, contouring brushes, highlight brushes, eye shadow brushes, lip brushes, nose shadow brushes and eyebrow brushes.

[0026] The type positioning unit is used to extract features from relevant cognitive data to obtain the user's makeup experience years Hnx and usage frequency Spz, and calculate the proficiency value Sz based on the user's makeup experience years Hnx and usage frequency Spz. The proficiency value Sz is obtained by the following formula: ; Wherein, e represents the Euler number, which is approximately 2.71828, and a and b represent the weight values ​​of the frequency of use and years of makeup experience, respectively; A threshold is preset, and the proficiency value Sz is compared with the threshold to determine the makeup type of the current user. The specific determination content is as follows: If the proficiency value Sz exceeds the threshold, it indicates that the makeup type of the current user is an experienced makeup artist; If the proficiency value Sz does not exceed the threshold, it indicates that the current user's makeup type is a makeup novice.

[0027] In this embodiment, firstly, through the pre-questionnaire survey of the cognitive acquisition unit, the system can collect and grasp the user's use of makeup brushes in many aspects. This multi-dimensional data collection method ensures the comprehensiveness and accuracy of the user's cognitive data, and lays a solid foundation for the subsequent user type positioning. Secondly, the type positioning unit extracts the features of the relevant cognitive data, estimates the user's proficiency value Sz by using the calculation formula, and compares it with the preset threshold. This exponential model calculation method based on the Euler number can further accurately reflect the user's makeup proficiency, making the system more scientific and accurate in judging the user type, especially for the distinction between makeup novices and experienced makeup artists. This method can effectively avoid subjective misjudgment and further ensure that the makeup brushes recommended by the system in the future can accurately match the user's needs, thereby realizing personalized services for different user types. For makeup novices, the system can give priority to recommending makeup brushes that are easy to master and operate. This intelligent classification method not only improves the user's shopping experience, but also improves the overall efficiency and recommendation accuracy of the system. In short, the system not only enhances the intelligence of the system through the precise user type locking module, but also enables personalized customization services to better meet the actual needs of different users, especially to help makeup novices better master makeup skills in the initial stage.

[0028] Example 3 Please refer to Figure 1 ,Specifically: the sample brush data monitoring module includes a brush quality collection unit and a feedback information collection unit; The brush quality collection unit is used to collect and record relevant characteristic data information of several groups of sample brushes, wherein the relevant characteristic data information includes the bristle hardness Smyd, bristle roughness Sccd, bristle density Smd, elastic coefficient Txs and adhesion Ffz of each sample brush; The bristle hardness Smyd mentioned above can be monitored and obtained by a hardness tester; The bristle roughness Sccd can be measured and obtained by a surface roughness meter; The bristle density Smd can be monitored and obtained by a density analyzer; The adhesion force Ffz can be measured by a tensile testing machine. In the test, the powder is applied to the bristles, and then a tensile force is gradually applied until the powder is detached from the bristles. The force value recorded by the testing machine is the adhesion force. The bristles are mainly subjected to bending during use, and the elastic coefficient Txs of the bristles can be obtained by the following formula: ; Among them, E represents the Young's modulus of the bristle, which represents the rigidity of the bristle under tension or compression, and the unit of Young's modulus is Pascal; L represents the length of the bristle; I represents the moment of inertia value of the bristle cross section.

[0029] The elastic coefficient Txs of the bristles describes the elastic recovery force of the bristles when they are bent. It is often used for softer bristles or in application scenarios where bending is the main feature during makeup application.

[0030] The feedback information collection unit is used to record the user's feedback on each sample brush to obtain feedback data, and the feedback data includes the user's feedback score weight R on the bristle hardness Smyd of each sample brush.

[0031] The feedback score weight R of the bristle hardness Smyd of each sample brush described above reflects the user's preference for different sample brushes. Here, the user's feedback score can be assigned a corresponding numerical value.

[0032] The data processing module includes a preprocessing unit and a standardization unit; The preprocessing unit is used to use data preprocessing technology to identify and eliminate errors, abnormal values ​​and noise data information of the relevant characteristic data information and the feedback data, and perform feature extraction to extract useful feature data therefrom to construct a personalized design data set; The standardization unit is used to standardize the feature data after feature extraction according to the dimensionless processing technology, and use a standardization method to make it have a uniform scale, wherein the standardization method includes Z-score standardization.

[0033] In this embodiment, first, the sample brush data monitoring module records in detail multiple key characteristics of the sample brush through the brush quality collection unit, and the collection of these data provides rich basic information for subsequent personalized design. At the same time, the feedback information collection unit records the user's feedback score weight R for each sample brush, so that the actual use experience of different users can directly affect the optimization of personalized design, and further ensure that the designed makeup brush can meet user needs as much as possible. Secondly, the data processing module pre-processes the collected data through the pre-processing unit, and the system ensures the accuracy and reliability of the data by identifying and eliminating errors, outliers and noise data information. The feature extraction process further optimizes the data, making the personalized design data set more targeted. This step not only improves the data quality, but also provides a reliable basis for subsequent design optimization. Finally, the standardization unit standardizes the processed data through dimensionless processing technology, so that data of different dimensions can be compared and analyzed under a unified scale. In particular, the Z-score standardization method is used to make the data processing process more scientific and standardized, avoiding the analysis deviation caused by the inconsistent data scale. This standardization process greatly improves the accuracy and stability of the system, making the personalized design more accurate, and ultimately achieving higher user satisfaction and better product experience. Overall, the system further improves the accuracy and effectiveness of personalized design of makeup brushes through systematic data collection, precise preprocessing and scientific standardization, especially targeting different needs and feedback of users, so that the final product can better meet the personalized needs of users.

[0034] Example 4 Please refer to Figure 1 ,Specifically: the bristle testing module includes a personalized screening unit, a preliminary analysis unit and a matching analysis unit; The personalized screening unit is used to screen out the bristle hardness Smyd that suits the user's preference according to the user's feedback data on each sample brush, and is specifically obtained in the following manner: ; Where i=1, 2, 3, ..., n, n represents the number of sample brushes, It is represented as the bristle hardness of the i-th sample brush, It is represented as the user's feedback rating weight on the bristle hardness of the i-th sample brush.

[0035] In this embodiment, first, the personalized screening unit effectively performs personalized screening of the bristle hardness Smyd by combining the user's feedback data on each sample brush. By using a mathematical model, the system can accurately screen out the bristle hardness Smyd that meets the user's preferences based on the user's feedback score weight. This screening method not only improves the accuracy of the screening results and user satisfaction, but also allows each user's personalized needs to be fully reflected in the selection of bristle hardness. Especially when there are a large number of sample brushes, the screening process can quickly and efficiently identify the bristle hardness suitable for the user, thereby simplifying the user's selection process. Secondly, using this screening process, the system can dynamically adjust the recommended results of bristle hardness based on different user feedback, making personalized customization more flexible and accurate.

[0036] In short, this data-driven screening mechanism not only enhances the adaptability and response speed of the system, but also improves the user's satisfaction and user experience with the final product. Through the work of the personalized screening unit, users can find makeup brush products that suit their preferences faster and more accurately, further reducing the cost and time of trial and error.

[0037] Example 5 Please refer to Figure 1 Specifically: the preliminary analysis unit is used to screen out sample brushes with the same bristle hardness Smyd as the bristle hardness Smyd that fits the user's preference according to the bristle hardness Smyd obtained in the personalized screening unit, and perform statistics to obtain a set of similar sample brushes, and construct a powder grabbing ability coefficient Zfxs of the corresponding sample brush according to relevant characteristic data information, which is specifically calculated and obtained in the following manner: ; In the formula, Smd represents the bristle density, Sccd represents the bristle roughness, and C represents the correction constant. and are weight values, where 0 < ≤1,0< ≤1, and + = 1. The introduction of the correction constant C further improves the stability and accuracy of the calculation results.

[0038] According to the calculation method of obtaining the powder grabbing ability coefficient Zfxs of the corresponding sample brush in the preliminary analysis unit, the powder grabbing ability coefficients Zfxs of multiple groups of sample brushes in the same sample brush set are obtained in turn, and the screening threshold Q is set according to the powder grabbing ability coefficients Zfxs of multiple groups of sample brushes in the same sample brush set. The specific setting content is as follows: The fan grabbing ability coefficients Zfxs of multiple groups of sample brushes in the same sample brush set are calculated by statistical averaging algorithm to obtain the average fan grabbing ability coefficients of the sample brushes in the same sample brush set. And the standard deviation of the powder grabbing ability coefficient of the sample brushes in the same sample brush set ; Based on the average powder grabbing ability coefficient of sample brushes in the same sample brush set And the standard deviation of the powder grabbing ability coefficient of the sample brushes in the same sample brush set , obtain the screening threshold Q; ; Where k is a constant, usually with a value of 1-3, corresponding to different confidence levels, and the specific value is set by the user (based on actual conditions); The powder-grabbing ability coefficients Zfxs of multiple groups of sample brushes in the same sample brush set are compared with the screening threshold Q to screen out the powder-grabbing ability coefficients Zfxs suitable for makeup novices. If the powder-grabbing ability coefficients Zfxs of the sample brushes in the same sample brush set are ≤ the screening threshold Q, the corresponding sample brushes are marked as suitable sample brushes; if the powder-grabbing ability coefficients Zfxs of the sample brushes in the same sample brush set are > the screening threshold Q, the corresponding sample brushes are temporarily not marked as suitable sample brushes.

[0039] In this embodiment, firstly, the sample brushes whose bristle hardness Smyd matches the user's preference are screened by the preliminary analysis unit, and the powder grabbing ability coefficient Zfxs of the same sample brush set is obtained by statistics and calculation of relevant characteristic data. This process can accurately reflect the performance of different sample brushes in powder grabbing ability, so that the system can scientifically analyze and screen out brushes that are more suitable for makeup novices. Secondly, by setting the screening threshold Q and combining statistical methods to obtain the average powder grabbing ability coefficient and standard deviation of the sample brushes, the system can further effectively screen out brushes suitable for makeup novices in the same sample brush set. The setting method of the screening threshold Q takes into account the distribution of the powder grabbing ability of the sample brushes, and flexibly controls the severity of the screening by adjusting the confidence level, that is, setting the k value. For makeup novices, this screening mechanism can ensure that the recommended brushes are neither too strong in powder grabbing ability, avoiding excessive powder taking at one time, nor too weak, ensuring the makeup effect, thereby improving the user experience and the success rate of makeup. In summary, the system can effectively meet the special needs of makeup novices when using makeup brushes through systematic analysis and threshold screening of the powder-grabbing ability of sample brushes, and realize a more scientific and accurate personalized customization process. This method not only improves the rationality of makeup brush selection, but also enhances users' confidence in and satisfaction with makeup tools.

[0040] Example 6 Please refer to Figure 1Specifically: the matching analysis unit is used to collect statistics on the matching sample brushes and issue a test command, and test and analyze the matching sample brushes in turn to obtain the release capacity coefficient Snxs of the corresponding sample brush, which is obtained specifically in the following manner: ; Where Txs is the elastic coefficient of the bristles, It is represented as the displacement of the bristle being stretched, and Ffz is represented as the adhesion force.

[0041] The personalized screening module includes a comparison unit and a locking unit; The comparison unit is used to compare and analyze the powder grabbing capacity coefficient Zfxs of the sample brush with the release capacity coefficient Snxs of the corresponding sample brush to calculate the powder retention coefficient Fzzs of the corresponding sample brush, which is specifically obtained in the following manner: .

[0042] The locking unit is used to compare the powder retention coefficient Fzzs with the value 1 to screen out makeup brushes that meet the user's requirements. The specific contents are as follows: If the powder retention coefficient Fzzs = 1, it means that the bristles of the corresponding sample brush can balance the ability to grab powder and release powder. At this time, the sample brush is set as a user personalized order product to customize a special makeup brush for the user. At this time, it means that the makeup brush can almost completely release the powder after grabbing it; for novices, such a makeup brush is easier to control and can apply makeup more evenly; If the ratio is too low, powder will easily accumulate on the bristles, making it difficult to apply makeup evenly; if the ratio is too high, powder will easily be lost, resulting in uneven makeup. The closer the ratio is to 1, the higher the powder utilization efficiency, and it also further avoids unnecessary waste.

[0043] If the powder retention coefficient Fzzs≠1, it means that the powder captured by the bristles of the corresponding sample brush has not been effectively released. The powder may be trapped inside the bristles, resulting in uneven makeup. This means that the adsorption force of the bristles is too strong or the release is insufficient, and the makeup is easily accumulated, which is especially difficult for novices to master.

[0044] In this embodiment, first, the matching analysis unit obtains the release capacity coefficient Snxs of the corresponding sample brush by statistics and testing the matching sample brushes, and further accurately evaluates the powder release capacity of each sample brush in actual use through comprehensive calculation of the elastic coefficient Txs of the bristles, the displacement ΔL of the stretched bristles, and the adhesion force Ffz. This process ensures the scientificity and accuracy of the test data and provides a reliable basis for subsequent comparative analysis. Secondly, the comparison unit in the personalized screening module further calculates the powder retention coefficient Fzzs of the sample brush by comparing the powder grabbing capacity coefficient Zfxs with the release capacity coefficient Snxs. The introduction of the powder retention coefficient Fzzs can not only intuitively reflect the balance state of the sample brush between grabbing powder and releasing powder, but also provides key parameters for the customized design of makeup brushes. By comparing with the value 1, the system can quickly screen out makeup brushes that meet user needs. For makeup novices, makeup brushes with a powder retention coefficient Fzzs close to 1 are particularly important because they can achieve uniform distribution of powder during the makeup process, reduce uneven makeup and powder accumulation, and thus improve makeup effects and user experience. Finally, the locking unit locks the sample brush with a retention coefficient of 1 as a relatively good option by determining the powder retention coefficient Fzzs. This type of makeup brush strives to find an ideal balance between grabbing and releasing powder, which can further avoid powder waste while ensuring uniform makeup. It is especially suitable for novice users and can help them better master makeup skills and reduce makeup problems caused by uneven powder release. In summary, through a series of scientific and precise calculations and analyses, the system not only improves the personalized customization capabilities of makeup brushes, but also provides users with a selection of makeup tools that are more in line with actual needs, thereby improving the makeup experience and makeup effects.

[0045] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A makeup brush design and management system based on personalized customization, characterized by: It includes user type locking module, sample brush data monitoring module, data processing module, brush hair testing module and personalized screening module; The user type locking module is used to obtain relevant cognitive data and determine the user type based on the user's self-evaluation; The sample brush data monitoring module is used to collect and record relevant characteristic data information of several groups of sample brushes, and collect feedback data of each sample brush according to the user; The data processing module is used to pre-process the relevant characteristic data information and feedback data obtained in the sample brush data monitoring module to construct a personalized design data set, and combine the dimensionless processing technology to eliminate the dimension in the personalized design data set to form a dimensionless form; The brush test module is used to analyze the powder-grabbing properties of the sample brushes based on the personalized design data set when the user type is a makeup novice, so as to construct the powder-grabbing ability coefficient Zfxs of the corresponding sample brushes, and to screen several groups of sample brushes through a pre-set screening threshold Q, and to execute the test command on the screened sample brushes, and to test the release ability coefficient Snxs of the corresponding sample brushes in turn; The personalized screening module is used to compare and analyze the powder grabbing ability coefficient Zfxs of the sample brush with the release ability coefficient Snxs of the corresponding sample brush to screen out the makeup brushes that meet the user's needs and set them as the user's personalized order products.

2. A cosmetic brush design management system based on personalized customization according to claim 1, characterized in that: The user type locking module includes a cognition acquisition unit and a type positioning unit; The cognitive acquisition unit is used to conduct a questionnaire survey on the user in advance to obtain relevant cognitive data of the user based on the user's self-evaluation. The relevant cognitive data includes the user's frequency of use of makeup brushes Spz, years of makeup experience Hnx, usage habits and types of makeup tools.

3. The cosmetic brush design management system based on personalized customization according to claim 2, characterized in that: The type positioning unit is used to extract features from relevant cognitive data to obtain the user's makeup experience years Hnx and usage frequency Spz, and calculate the proficiency value Sz based on the user's makeup experience years Hnx and usage frequency Spz. The proficiency value Sz is obtained by the following formula: ; Wherein, e represents the Euler number, a and b represent the weight values ​​of the frequency of use and the years of makeup experience, respectively; A threshold is preset, and the proficiency value Sz is compared with the threshold to determine the makeup type of the current user. The specific determination content is as follows: If the proficiency value Sz exceeds the threshold, it indicates that the makeup type of the current user is an experienced makeup artist; If the proficiency value Sz does not exceed the threshold, it indicates that the current user's makeup type is a makeup novice.

4. The cosmetic brush design management system based on personalized customization according to claim 1, characterized in that: The sample brush data monitoring module includes a brush quality collection unit and a feedback information collection unit; The brush quality collection unit is used to collect and record relevant characteristic data information of several groups of sample brushes, wherein the relevant characteristic data information includes the bristle hardness Smyd, bristle roughness Sccd, bristle density Smd, elastic coefficient Txs and adhesion Ffz of each sample brush; The feedback information collection unit is used to record the user's feedback on each sample brush to obtain feedback data, and the feedback data includes the user's feedback score weight R on the bristle hardness Smyd of each sample brush.

5. The cosmetic brush design management system based on personalized customization according to claim 1, characterized in that: The data processing module includes a preprocessing unit and a standardization unit; The preprocessing unit is used to use data preprocessing technology to identify and eliminate errors, abnormal values ​​and noise data information of the relevant characteristic data information and the feedback data, and perform feature extraction to extract useful feature data therefrom to construct a personalized design data set; The standardization unit is used to standardize the feature data after feature extraction according to the dimensionless processing technology, and use a standardization method to make it have a uniform scale, wherein the standardization method includes Z-score standardization.

6. The cosmetic brush design management system based on personalized customization according to claim 4, characterized in that: The bristle testing module includes a personalized screening unit, a preliminary analysis unit and a matching analysis unit; The personalized screening unit is used to screen out the bristle hardness Smyd that suits the user's preference according to the user's feedback data on each sample brush, and is specifically obtained in the following manner: ； Where i=1, 2, 3, ..., n, n represents the number of sample brushes, It is represented as the bristle hardness of the i-th sample brush, It is represented as the user's feedback score weight on the bristle hardness of the i-th sample brush.

7. A cosmetic brush design management system based on personalized customization according to claim 6, characterized in that: The preliminary analysis unit is used to screen out sample brushes with the same bristle hardness Smyd as the bristle hardness Smyd that fits the user's preference according to the bristle hardness Smyd obtained in the personalized screening unit, and perform statistics to obtain a set of similar sample brushes, and construct a powder grabbing ability coefficient Zfxs of the corresponding sample brush according to relevant characteristic data information, which is specifically calculated and obtained in the following manner: ； In the formula, Smd represents the bristle density, Sccd represents the bristle roughness, and C represents the correction constant. and All are weight values.

8. The cosmetic brush design management system based on personalized customization according to claim 7, characterized in that: According to the calculation method of obtaining the powder grabbing ability coefficient Zfxs of the corresponding sample brush in the preliminary analysis unit, the powder grabbing ability coefficients Zfxs of multiple groups of sample brushes in the same sample brush set are obtained in turn, and the screening threshold Q is set according to the powder grabbing ability coefficients Zfxs of multiple groups of sample brushes in the same sample brush set. The specific setting content is as follows: The fan grabbing ability coefficients Zfxs of multiple groups of sample brushes in the same sample brush set are calculated by statistical averaging algorithm to obtain the average fan grabbing ability coefficients of the sample brushes in the same sample brush set. And the standard deviation of the powder grabbing ability coefficient of the sample brushes in the same sample brush set ; Based on the average powder grabbing ability coefficient of sample brushes in the same sample brush set And the standard deviation of the powder grabbing ability coefficient of the sample brushes in the same sample brush set , obtain the screening threshold Q; ； Among them, k is a constant, and the specific value is set by the user; The powder-grabbing ability coefficients Zfxs of multiple groups of sample brushes in the same sample brush set are compared with the screening threshold Q to screen out the powder-grabbing ability coefficients Zfxs suitable for makeup novices. If the powder-grabbing ability coefficients Zfxs of the sample brushes in the same sample brush set are ≤ the screening threshold Q, the corresponding sample brushes are marked as suitable sample brushes; if the powder-grabbing ability coefficients Zfxs of the sample brushes in the same sample brush set are > the screening threshold Q, the corresponding sample brushes are temporarily not marked as suitable sample brushes.

9. The cosmetic brush design management system based on personalized customization according to claim 6, characterized in that: The matching analysis unit is used to collect statistics on the matching sample brushes and issue a test command, and test and analyze the matching sample brushes in turn to obtain the release capacity coefficient Snxs of the corresponding sample brush, which is specifically obtained in the following manner: ； Where Txs is the elastic coefficient of the bristles, It is represented as the displacement of the bristle being stretched, and Ffz is represented as the adhesion force.

10. The cosmetic brush design management system based on personalized customization according to claim 1, characterized in that: The personalized screening module includes a comparison unit and a locking unit; The comparison unit is used to compare and analyze the powder grabbing capacity coefficient Zfxs of the sample brush with the release capacity coefficient Snxs of the corresponding sample brush to calculate the powder retention coefficient Fzzs of the corresponding sample brush, which is specifically obtained in the following manner: ； The locking unit is used to compare the powder retention coefficient Fzzs with the value 1 to screen out makeup brushes that meet the user's requirements. The specific contents are as follows: If the powder retention coefficient Fzzs = 1, it means that the bristles of the corresponding sample brush can balance the ability to grab powder and release powder. At this time, the sample brush is set as a user personalized order product to customize a unique makeup brush for the user; If the powder retention coefficient Fzzs≠the value of 1, it means that the powder captured by the bristles of the corresponding sample brush cannot be effectively released.

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