Glaze performance evaluation method and system based on multiple application scenes

Abstract

The invention relates to the technical field of material science, and particularly discloses a glaze performance evaluation method and system based on multiple application scenarios, and the method comprises the steps: obtaining the original data of the hardness value and wear loss of glaze, carrying out the standardization processing, calculating the hardness distribution index and wear resistance index, and carrying out the comprehensive analysis and classification of the glaze, thereby achieving the evaluation of the performance of the glaze. Qualified glaze and unqualified glaze are distinguished; then carrying out high-temperature stability test on the qualified glaze, and screening out the glaze with high thermal stability; and finally, a particle swarm optimization algorithm is adopted to search for an optimal solution of a hardness value and a wear loss regulation interval, and it is ensured that the glaze shows excellent performance in a changeable application environment. Through the systematic evaluation process, the problems of fuzzy standard, lack of scientific basis, poor performance consistency and low evaluation efficiency in a traditional evaluation method are solved, the consistency and reliability of glaze performance are effectively improved, the product quality is ensured, and the evaluation efficiency is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of material science and technology, and in particular to a glaze performance evaluation method and system based on multiple application scenarios. Background Art

[0002] As a widely used material, the performance of glaze directly affects the quality and service life of the final product. In the fields of ceramics, glass and other surface decoration materials, the hardness and wear resistance of glaze are very important performance indicators. However, there are some shortcomings in the existing glaze performance evaluation methods, which limit the quality and performance consistency of glaze products.

[0003] The existing methods rely on the experience and subjective judgment of technicians and lack a unified quantitative standard, resulting in low consistency and reliability of the evaluation results; manual testing and visual evaluation methods are difficult to ensure the consistency and repeatability of the results and lack scientific quantitative indicators; different batches of glazes have large differences in hardness distribution and wear resistance, which affects the quality stability of the product;

[0004] In order to solve the above technical problems, the present invention processes the original data of glaze hardness value and wear amount to obtain hardness distribution index and wear resistance index, and classifies the glaze into qualified and unqualified categories accordingly. High-temperature stability test is carried out based on qualified glaze to screen out glaze with high thermal stability, and the particle swarm optimization algorithm is used to find the optimal solution of the hardness value and wear amount control range to ensure that the glaze exhibits excellent performance in changing application environments. Summary of the invention

[0005] The purpose of the present invention is to provide a glaze performance evaluation method and system based on multiple application scenarios to solve the above-mentioned problems.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A glaze performance evaluation method based on multiple application scenarios comprises the following steps:

[0008] S1: obtaining raw data of a number of glazes, wherein the raw data includes a glaze hardness value and a glaze wear amount, and processing the raw data to obtain a hardness distribution index and a wear resistance index;

[0009] Among them, the process of obtaining the hardness distribution index is:

[0010] Obtain a number of glazes, and perform hardness tests on each glaze at different positions, and record the hardness value of each glaze as, where i represents the number of hardness values ​​measured, and j represents the number of glazes;

[0011] Standardize the hardness data to eliminate the impact of dimension;

[0012] Calculate the covariance matrix of the standardized hardness values;

[0013] The covariance matrix calculation formula of the hardness value is:

[0014]

[0015] In the formula, C represents the covariance matrix, Z yj represents the average value of the normalized hardness of the jth glaze;

[0016] Perform eigenvalue decomposition on the covariance matrix to obtain the eigenvalue j represents the number of eigenvalues, and j is a positive integer greater than 0;

[0017] Perform eigenvalue decomposition on the covariance matrix to obtain the eigenvector V j , j represents the number of eigenvectors;

[0018] The eigenvalue decomposition calculation formula is:

[0019]

[0020] The hardness distribution index calculation formula is:

[0021]

[0022] In the formula, ω j represents the hardness distribution index of the jth glaze, represents the characteristic value of the jth glaze;

[0023] S2: Comprehensively analyze the hardness distribution index and wear resistance index of the glaze to determine whether the glaze is qualified. According to the analysis results, mark and classify the glaze to classify the glaze into qualified glaze and unqualified glaze;

[0024] S3: Based on qualified glazes, simulate high temperature environment, judge the thermal stability of glazes, and select glazes with high thermal stability;

[0025] S4: The screened glazes with high thermal stability are recorded as glazes suitable for multiple scenarios, the corresponding glaze hardness values ​​and glaze wear amounts are calculated, and the optimal control ranges of the glaze hardness values ​​and glaze wear amounts are calculated.

[0026] As a further solution of the present invention: the raw data is processed to obtain a wear resistance index;

[0027] The process of obtaining the wear resistance index is as follows:

[0028] Wear test is performed on each glaze to obtain multiple sets of wear test data. Each set of data includes: test position, test pressure P b , test time t b and wear amount W b , where b represents b groups of test data, and b is a positive integer greater than 0;

[0029] Standardize or normalize the test position, test pressure and test time to eliminate the dimension effect;

[0030] Extract spatial features, construct position features, and calculate the distance from the bth test point to the center point;

[0031] Analysis of wear volume W b The distribution at different test locations uses the spatial interpolation method to calculate the wear distribution in the entire area;

[0032] The wear resistance index of each glaze was calculated based on the wear distribution over the entire area.

[0033] As a further solution of the present invention: the hardness distribution index and the wear resistance index of the glaze are comprehensively analyzed to obtain the quality coefficient of the glaze and determine whether the glaze is qualified;

[0034] Among them, the process of obtaining the quality coefficient of the glaze is:

[0035] Get several glazes and calculate the wear resistance index τ of each glaze j and hardness distribution index ω j ;

[0036] Wear resistance index τ for each glaze j and hardness distribution index ω j After normalization, the wear resistance index τ j and hardness distribution index ω j Calculate the quality factor of the glaze.

[0037] As a further solution of the present invention: the glazes are marked and classified according to the analysis results, and the glazes are divided into qualified glazes and unqualified glazes, which specifically includes:

[0038] The quality factor Q of all glazes j Compare with the preset glaze quality coefficient threshold to determine whether the glaze is qualified. j If the quality coefficient of the glaze is greater than or equal to the preset glaze quality coefficient threshold, if so, it is recorded as a qualified glaze, otherwise, it is recorded as an unqualified glaze.

[0039] As a further solution of the present invention: based on the qualified glaze, a high temperature environment is simulated to judge the thermal stability of the glaze, and glaze with high thermal stability is screened out;

[0040] The process of selecting the glaze with high thermal stability is as follows:

[0041] According to the results of high temperature tests, a standard threshold is set to determine whether the glaze meets the high thermal stability standard, and the glazes that meet the high thermal stability standard are selected;

[0042] Determine whether the glaze meets the requirements of color change, cracking, adhesion test, gloss change and chemical stability. If so, it is recorded as a glaze with high thermal stability.

[0043] As a further solution of the present invention: the calculation of the optimal control range of the glaze hardness value and the glaze wear amount specifically includes:

[0044] By randomly initializing the position and speed of the particles, defining the fitness function to minimize the hardness distribution index and the wear resistance index, initializing the personal best position and the personal best fitness value, the initial position of each particle is used as the personal best position pb m , the best personal fitness value f(pb m ) is the fitness value of the initial position;

[0045] Initialize the global best position and the global best fitness value. The global best position pb is initially the position of the particle with the best fitness among all particles, and the global best fitness value f(pb) is the fitness value of the particle.

[0046] Iteratively update the particle speed and position, and continuously update the individual and global optimal positions. Finally, when the preset number of iterations is reached or the fitness value is stable, the optimal control range of the hardness value and wear amount is output.

[0047] As a further solution of the present invention: the process of iteratively updating particle speed and position and continuously updating individual and global optimal positions is:

[0048] Update particle speed, the calculation formula for updating particle speed is:

[0049] r m (t+1)=γ*r m +c1*r1*(pb m -k m (t))+c2*r2*(pb(t)-k m (t));

[0050] Where γ is the inertia weight, which is between 0.4 and 0.9, c1 and c2 are acceleration constants, r1 and r2 are random numbers in the interval [0, 1], and t represents the number of iterations to update the particle, which is a positive integer greater than 0;

[0051] Update the particle position, the calculation formula for updating the particle position is:

[0052] k m (t+1)=k m (t)+r m (t+1);

[0053] For each particle’s updated position k m (t+1), calculate the fitness function f(k m (t+1));

[0054] If the particle's new position fitness value is better, update the personal best position and personal best fitness value.

[0055] If the fitness value of a particle's new position is better than the global best fitness value, the global best position and the global best fitness value are updated;

[0056] The maximum number of iterations T is preset. If the maximum number of iterations T is reached or the fitness value is no longer significantly improved, the iteration is stopped;

[0057] The current group optimal position pb(T) is output as the optimal control range of hardness value and wear amount.

[0058] A glaze performance evaluation system based on multiple application scenarios, including:

[0059] A raw data acquisition module, wherein the raw data acquisition module is used to collect raw data of the glaze, wherein the raw data includes a glaze hardness value and a glaze wear amount;

[0060] A raw data analysis module, which is used to process the raw data to obtain a hardness distribution index and a wear resistance index;

[0061] A glaze judging module, wherein the glaze judging module comprehensively analyzes the hardness distribution index and the wear resistance index of the glaze to judge whether the glaze is qualified, and marks and classifies the glaze according to the analysis result, and divides the glaze into qualified glaze and unqualified glaze;

[0062] A glaze screening module, which simulates a high temperature environment based on qualified glazes, determines the thermal stability of the glazes, and screens out glazes with high thermal stability;

[0063] The glaze control interval optimization module is used to record the screened glazes with high thermal stability as glazes suitable for multiple scenarios, calculate the corresponding glaze hardness values ​​and glaze wear amounts, and find the optimal solution for the glaze hardness value and glaze wear amount control interval.

[0064] A glaze performance evaluation system based on multiple application scenarios, wherein the raw data analysis module at least includes:

[0065] A hardness distribution index calculation unit, the hardness distribution index calculation unit is used to calculate the hardness distribution index according to the hardness value distribution of each glaze;

[0066] The wear resistance index calculation unit is used to calculate the wear resistance index according to the wear amount of each glaze.

[0067] Beneficial effects of the present invention:

[0068] (1) The present invention achieves accurate evaluation of glaze performance by introducing two quantitative indicators, hardness distribution index and wear resistance index; the hardness distribution index reflects the uniformity and stability of glaze hardness, while the wear resistance index directly measures the wear resistance of glaze; through the comprehensive analysis of these two indexes, it is possible to effectively judge whether the glaze is qualified and classify it; in addition, the particle swarm optimization algorithm is used to find the optimal solution of the hardness value and wear amount control range, further ensuring the consistency and reliability of glaze performance in multiple application scenarios; this systematic evaluation process not only improves the accuracy and reliability of the evaluation, but also makes the quality control in the production process more scientific;

[0069] (2) The present invention achieves a comprehensive evaluation of glaze performance by introducing scientific means such as hardness distribution index and wear resistance index, as well as high temperature stability test. The calculation of hardness distribution index and wear resistance index is based on standardized hardness test and wear test data, eliminating the influence of dimension, and is deeply analyzed through mathematical tools such as covariance matrix and eigenvalue decomposition. These quantitative indicators can not only reflect the performance of glaze in terms of hardness and wear resistance, but also help identify potential quality problems. In addition, the particle swarm optimization algorithm is used to find the optimal solution of the hardness value and wear amount control range, making the evaluation result more scientific and reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The present invention will be further described below in conjunction with the accompanying drawings.

[0071] Figure 1 This is a flowchart of the specific steps of a glaze performance evaluation method based on multiple application scenarios of the present invention;

[0072] Figure 2 It is a flowchart of judging whether the glaze is qualified in the present invention;

[0073] Figure 3 It is a flowchart of a glaze performance evaluation system based on multiple application scenarios in the present invention. DETAILED DESCRIPTION

[0074] 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.

[0075] Embodiment 1:

[0076] See also Figure 1 As shown, the present invention is a glaze performance evaluation method based on multiple application scenarios, comprising the following steps:

[0077] S1: obtaining raw data of a number of glazes, wherein the raw data includes a glaze hardness value and a glaze wear amount, and processing the raw data to obtain a hardness distribution index and a wear resistance index;

[0078] S2: Comprehensively analyze the hardness distribution index and wear resistance index of the glaze to determine whether the glaze is qualified. According to the analysis results, mark and classify the glaze to classify the glaze into qualified glaze and unqualified glaze;

[0079] S3: Based on qualified glazes, simulate high temperature environment, judge the thermal stability of glazes, and select glazes with high thermal stability;

[0080] S4: The selected glazes with high thermal stability are recorded as glazes suitable for multiple scenarios, the corresponding glaze hardness values ​​and glaze wear amounts are calculated, and the optimal solution for the glaze hardness value and glaze wear amount control range is found.

[0081] Embodiment 2:

[0082] On the basis of Example 1, the hardness value of the glaze is processed to calculate the hardness distribution index of the glaze, specifically including:

[0083] Obtain several glazes and perform hardness tests on each glaze at different locations. The hardness value of each glaze is recorded as H. ij , where i represents the number of hardness values ​​measured, i is a positive integer greater than 0, j represents the number of glazes, j is a positive integer greater than 0;

[0084] The hardness data is standardized to eliminate the influence of dimension, including:

[0085] Get the average hardness value of each glaze, recorded as Hyj ;

[0086] Get the standard deviation of each glaze hardness value, denoted as σ yj ;

[0087] By formula Calculate the standardized hardness value Z ij ;

[0088] Calculate the covariance matrix of the standardized hardness values;

[0089] The covariance matrix calculation formula of the hardness value is:

[0090]

[0091] In the formula, C represents the covariance matrix, Z yj represents the average value of the normalized hardness of the jth glaze;

[0092] Perform eigenvalue decomposition on the covariance matrix to obtain the eigenvalue j represents the number of eigenvalues, and a is a positive integer greater than 0;

[0093] Perform eigenvalue decomposition on the covariance matrix to obtain the eigenvector V j , j represents the number of eigenvectors;

[0094] The eigenvalue decomposition calculation formula is:

[0095]

[0096] The hardness distribution index calculation formula is:

[0097]

[0098] In the formula, ω j represents the hardness distribution index of the jth glaze, represents the characteristic value of the jth glaze, Z yj represents the average value of the normalized hardness value of the jth glaze;

[0099] It should be noted that the hardness distribution index can reflect the uniformity and stability of the glaze hardness distribution, and the smaller the hardness distribution index is, the more uniform and stable the hardness distribution is. By controlling the hardness distribution index, the performance of the glaze can be better optimized to ensure the consistency and reliability of product quality.

[0100] The glaze wear volume is processed and the glaze wear resistance index is calculated, including:

[0101] A wear test is performed on each glaze to obtain multiple sets of wear test data. Each set of data includes: test position (xb ,y b ), test pressure P b , test time t b and wear amount W b , where b represents b groups of test data, and b is a positive integer greater than 0;

[0102] Standardize or normalize the test position, test pressure and test time to eliminate the dimension effect;

[0103] Extract spatial features, specifically:

[0104] Construct position features and calculate the distance from the bth test point to the center point;

[0105] The distance calculation formula of the center point is:

[0106]

[0107] Where, d b Indicates the distance from the bth test point to the center point, x b and b Indicates the position coordinates of the bth test point, x y and yy represent the average values ​​of the position coordinates;

[0108] Analysis of wear volume W b At different test locations (x b ,y b ) and use the spatial interpolation method to calculate the wear distribution in the entire area;

[0109] The wear distribution calculation formula is:

[0110]

[0111] In the formula, W(x b ,y b ) s Indicates the position (x b ,y b ), θ is a preset proportional coefficient, and θ is greater than 0;

[0112] The wear resistance index of each glaze is calculated based on the distribution of wear in the entire area;

[0113] The calculation formula of the wear resistance index of each glaze is:

[0114]

[0115] In the formula, τ j represents the wear resistance index of the jth glaze;

[0116] It should be noted that the wear resistance index directly reflects the wear resistance of the glaze surface. A higher wear resistance index indicates that the glaze is less worn under the same conditions and has better wear resistance. Glazes with a high wear resistance index can still maintain a good appearance and function after long-term use, and are not prone to wear, scratches and other problems. They have higher durability. A high wear resistance index means that the glaze can maintain stable performance in different use environments and conditions, and is not prone to performance degradation due to wear.

[0117] Embodiment 3:

[0118] See also Figure 2 As shown, based on Example 2, several glazes are obtained, and the wear resistance index τ of each glaze is calculated respectively. j and hardness distribution index ω j ;

[0119] Wear resistance index τ for each glaze j and hardness distribution index ω j After normalization, the wear resistance index τ j and hardness distribution index ω j Calculate the quality coefficient of glaze;

[0120] The glaze mass fraction coefficient calculation formula is:

[0121]

[0122] In the formula, Q j represents the quality coefficient of the jth glaze, g1 and g2 are preset proportional coefficients, and both g1 and g2 are greater than 0, ω j represents the hardness distribution index of the jth glaze, τ j represents the wear resistance index of the jth glaze;

[0123] It should be noted that the wear resistance index of the glaze is τ j The quality coefficient Q of the glaze j Proportional relationship, hardness distribution index ω j The quality coefficient Q of the glaze j The quality coefficient of the glaze is directly proportional to j , reflects the performance quality of the glaze, and when the quality coefficient of the glaze Q j The larger it is, the better the quality of the corresponding glaze is and the better the performance of the glaze is.

[0124] The quality factor Q of all glazes j Compare with the preset glaze quality coefficient threshold;

[0125] If the quality factor of the glaze is Q jIf the value is greater than or equal to the preset glaze quality coefficient threshold, it means that the quality of the corresponding glaze is good and is recorded as qualified glaze;

[0126] If the quality factor of the glaze is Q j If the quality coefficient value is less than the preset glaze quality coefficient threshold, it means that the quality of the corresponding glaze is poor and is recorded as unqualified glaze.

[0127] Embodiment 4:

[0128] On the basis of Example 3, based on qualified glaze, a high temperature furnace is used to set a series of temperature gradients, such as gradually increasing from room temperature to the highest temperature that may be encountered in the actual application of the glaze;

[0129] Place qualified glazes in a high temperature environment, keep them at different temperatures for a certain period of time (such as several hours), and observe and record the changes of the glazes at high temperatures (such as color change, cracking, and falling off);

[0130] According to the results of high temperature tests, a standard threshold is set to determine whether the glaze meets the high thermal stability standard, and the glazes that meet the high thermal stability standard are selected;

[0131] The process of setting the standard threshold to judge whether the glaze meets the high thermal stability standard is as follows:

[0132] Color change: evaluate the degree of color change of the glaze before and after high temperature treatment, and conduct quantitative analysis by using a spectrometer. The standard is that the color difference does not exceed the preset color difference unit (such as CIELAB color difference unit ΔE);

[0133] Cracking: Check whether the glaze has cracks. The standard is that there are no visible cracks. If cracks are present, it is considered a glaze with low thermal stability.

[0134] Adhesion test: evaluates whether the glaze is still firmly attached to the substrate after high temperature, and is checked by scraper test. The standard is that there is no peeling or separation;

[0135] Gloss change: measure the gloss change of the glaze surface, the standard is that the gloss reduction does not exceed the preset gloss percentage;

[0136] Chemical stability: evaluates whether the glaze undergoes chemical changes at high temperatures, using techniques such as X-ray diffraction (XRD) or infrared spectroscopy (FTIR). The standard is that no new chemical substances are generated;

[0137] Based on the process of determining whether the glaze meets the high thermal stability standard by setting the standard threshold, all glazes meeting the conditions are obtained and recorded as glazes with high thermal stability.

[0138] It should be noted that: based on the results of high-temperature tests, standard thresholds are set to determine whether the glaze meets the high thermal stability standards, and glazes that meet the high thermal stability standards are selected, effectively selecting glazes with high thermal stability to ensure that the glaze can be used in multiple scenarios.

[0139] Embodiment 5:

[0140] On the basis of Example 4, the selected glaze with high thermal stability is recorded as a glaze suitable for multiple scenarios, the corresponding glaze hardness value and glaze wear amount are calculated, and the optimal solution of the glaze hardness value and glaze wear amount control range is found, specifically including:

[0141] The particle swarm optimization algorithm is used to find the optimal solution for the hardness value and wear control range, including:

[0142] Select the number of particles m, which is tens to hundreds of particles, and randomly initialize the position k of each particle m , where the particle position is a combination of hardness value and wear amount;

[0143] Randomly initialize the velocity r of each particle m , the speed range is limited to the preset range;

[0144] Determine the fitness function and define the fitness function f(x), which is used to evaluate the quality of each particle position;

[0145] The fitness function is a measure of hardness value and wear amount, and the purpose is to make the hardness distribution index and wear resistance index as small as possible;

[0146] Initialize the personal best position and personal best fitness value, and the initial position of each particle is used as the personal best position pb m , the best personal fitness value f(pb m ) is the fitness value of the initial position;

[0147] Initialize the global best position and the global best fitness value. The global best position pb is initially the position of the particle with the best fitness among all particles, and the global best fitness value f(pb) is the fitness value of the particle.

[0148] Update particle speed, the calculation formula for updating particle speed is: m (t+1)=γ*r m +c1*r1*(pb m -k m (t))+c2*r2*(pb(t)-k m (t));

[0149] Where γ is the inertia weight, which is between 0.4 and 0.9, c1 and c2 are acceleration constants, r1 and r2 are random numbers in the interval [0, 1], and t represents the number of iterations to update the particle, which is a positive integer greater than 0;

[0150] Update the particle position, the calculation formula for updating the particle position is:

[0151] k m (t+1)=k m (t)+r m (t+1);

[0152] For each particle’s updated position k m (t+1), calculate the fitness function f(k m (t+1));

[0153] If the fitness value of the particle's new position is better, update the personal best position and personal best fitness value;

[0154] If the fitness value of a particle's new position is better than the global best fitness value, the global best position and the global best fitness value are updated;

[0155] The maximum number of iterations T is preset. If the maximum number of iterations T is reached or the fitness value is no longer significantly improved, the iteration is stopped;

[0156] The current group optimal position pb(T) is output as the optimal control range of hardness value and wear amount.

[0157] It should be noted that we use the particle swarm optimization algorithm to find the optimal solution for the hardness value and wear amount control range of glazes that are suitable for multiple scenarios. By initializing the particle swarm, defining the fitness function and iteratively updating the particle position and velocity, we finally determine the optimal control range of hardness value and wear amount. This method effectively improves the consistency and reliability of glaze performance and ensures product quality.

[0158] Embodiment 6:

[0159] See also Figure 3 As shown, a glaze performance evaluation system based on multiple application scenarios includes:

[0160] A raw data acquisition module, wherein the raw data acquisition module is used to collect raw data of the glaze, wherein the raw data includes a glaze hardness value and a glaze wear amount;

[0161] A raw data analysis module, which is used to process the raw data to obtain a hardness distribution index and a wear resistance index;

[0162] A glaze judging module, wherein the glaze judging module comprehensively analyzes the hardness distribution index and the wear resistance index of the glaze to judge whether the glaze is qualified, and marks and classifies the glaze according to the analysis result, and divides the glaze into qualified glaze and unqualified glaze;

[0163] A glaze screening module, which simulates a high temperature environment based on qualified glazes, determines the thermal stability of the glazes, and screens out glazes with high thermal stability;

[0164] The glaze control interval optimization module is used to record the screened glazes with high thermal stability as glazes suitable for multiple scenarios, calculate the corresponding glaze hardness values ​​and glaze wear amounts, and find the optimal solution for the glaze hardness value and glaze wear amount control interval.

[0165] Working principle of the present invention: The present invention first processes the original data of glaze hardness value and wear amount to obtain hardness distribution index and wear resistance index, and divides the glaze into qualified and unqualified categories accordingly. Subsequently, a high temperature stability test is carried out based on the qualified glaze to screen out glazes with high thermal stability. Finally, a particle swarm optimization algorithm is used to find the optimal solution for the hardness value and wear amount control range to ensure that the glaze exhibits excellent performance in a changing application environment. The technical solution of the present invention not only improves the consistency and reliability of glaze performance, but also solves the problems of vague evaluation standards and lack of scientific basis in traditional methods through a systematic evaluation process, thereby significantly improving product quality.

[0166] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0167] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0168] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0169] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0170] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A glaze performance evaluation method based on multiple application scenarios, characterized in that: The following steps are involved: S1: obtaining raw data of a number of glazes, wherein the raw data includes a glaze hardness value and a glaze wear amount, and processing the raw data to obtain a hardness distribution index and a wear resistance index; Among them, the process of obtaining the hardness distribution index is: Obtain a number of glazes, and perform hardness tests on each glaze at different positions, and record the hardness value of each glaze as, where i represents the number of hardness values ​​measured, and j represents the number of glazes; Standardize the hardness data to eliminate the impact of dimension; Calculate the covariance matrix of the standardized hardness values; The covariance matrix calculation formula of the hardness value is: In the formula, C represents the covariance matrix, Z yj represents the average value of the normalized hardness of the jth glaze; Perform eigenvalue decomposition on the covariance matrix to obtain the eigenvalue j represents the number of eigenvalues, and j is a positive integer greater than 0; Perform eigenvalue decomposition on the covariance matrix to obtain the eigenvector V j , j represents the number of eigenvectors; The eigenvalue decomposition calculation formula is: The hardness distribution index calculation formula is: In the formula, ω j represents the hardness distribution index of the jth glaze, represents the characteristic value of the jth glaze; S2: Comprehensively analyze the hardness distribution index and wear resistance index of the glaze to determine whether the glaze is qualified. According to the analysis results, mark and classify the glaze to classify the glaze into qualified glaze and unqualified glaze; S3: Based on qualified glazes, simulate high temperature environment, judge the thermal stability of glazes, and select glazes with high thermal stability; S4: The screened glazes with high thermal stability are recorded as glazes suitable for multiple scenarios, the corresponding glaze hardness values ​​and glaze wear amounts are calculated, and the optimal control ranges of the glaze hardness values ​​and glaze wear amounts are calculated.

2. A glaze performance evaluation method based on multiple application scenarios according to claim 1, characterized in that: The raw data is processed to obtain a wear resistance index; The process of obtaining the wear resistance index is as follows: Wear test is performed on each glaze to obtain multiple sets of wear test data. Each set of data includes: test position, test pressure P b , test time t b and wear amount W b , where b represents b groups of test data, and b is a positive integer greater than 0; Standardize or normalize the test position, test pressure and test time to eliminate the dimension effect; Extract spatial features, construct position features, and calculate the distance from the bth test point to the center point; Analysis of wear volume W b The distribution at different test locations uses the spatial interpolation method to calculate the wear distribution in the entire area; The wear resistance index of each glaze was calculated based on the wear distribution over the entire area.

3. The glaze performance evaluation method based on multiple application scenarios according to claim 1 is characterized in that: The hardness distribution index and the wear resistance index of the glaze are comprehensively analyzed to obtain the quality coefficient of the glaze and determine whether the glaze is qualified; Among them, the process of obtaining the quality coefficient of the glaze is: Get several glazes and calculate the wear resistance index τ of each glaze j and hardness distribution index ω j ; Wear resistance index τ for each glaze j and hardness distribution index ω j After normalization, the wear resistance index τ j and hardness distribution index ω j Calculate the quality factor of the glaze.

4. The glaze performance evaluation method based on multiple application scenarios according to claim 1 is characterized in that: According to the analysis results, the glazes are marked and classified into qualified glazes and unqualified glazes, which specifically includes: The quality factor Q of all glazes j Compare with the preset glaze quality coefficient threshold to determine whether the glaze is qualified. j If the quality coefficient of the glaze is greater than or equal to the preset glaze quality coefficient threshold, if so, it is recorded as a qualified glaze, otherwise, it is recorded as an unqualified glaze.

5. The glaze performance evaluation method based on multiple application scenarios according to claim 1 is characterized in that: Based on the qualified glaze, a high temperature environment is simulated to judge the thermal stability of the glaze, and glaze with high thermal stability is screened out; The process of selecting the glaze with high thermal stability is as follows: According to the results of high temperature tests, a standard threshold is set to determine whether the glaze meets the high thermal stability standard, and the glazes that meet the high thermal stability standard are selected; Determine whether the glaze meets the requirements of color change, cracking, adhesion test, gloss change and chemical stability. If so, it is recorded as a glaze with high thermal stability.

6. The glaze performance evaluation method based on multiple application scenarios according to claim 1 is characterized in that: The calculation of the optimal control range of the glaze hardness value and the glaze wear amount specifically includes: By randomly initializing the position and speed of the particles, defining the fitness function to minimize the hardness distribution index and the wear resistance index, initializing the personal best position and the personal best fitness value, the initial position of each particle is used as the personal best position pb m , the best personal fitness value f(pb m ) is the fitness value of the initial position; Initialize the global best position and the global best fitness value. The global best position pb is initially the position of the particle with the best fitness among all particles, and the global best fitness value f(pb) is the fitness value of the particle. Iteratively update the particle speed and position, and continuously update the individual and global optimal positions. Finally, when the preset number of iterations is reached or the fitness value is stable, the optimal control range of the hardness value and wear amount is output.

7. The glaze performance evaluation method based on multiple application scenarios according to claim 6 is characterized in that: The process of iteratively updating particle speed and position and continuously updating personal and global optimal positions is: Update particle speed, the calculation formula for updating particle speed is: r m (t+1)=γ*r m +c1*r1*(pb m -k m (t))+c2*r2*(pb(t)-k m (t)); Where γ is the inertia weight, which is between 0.4 and 0.9, c1 and c2 are acceleration constants, r1 and r2 are random numbers in the interval [0,1], and t represents the number of iterations to update the particle, which is a positive integer greater than 0. Update the particle position, the calculation formula for updating the particle position is: k m (t+1)=k m (t)+r m (t+1); For each particle’s updated position k m (t+1), calculate the fitness function f(k m (t+1)); If the particle's new position fitness value is better, update the personal best position and personal best fitness value; If the fitness value of a particle's new position is better than the global best fitness value, the global best position and the global best fitness value are updated; The maximum number of iterations T is preset. If the maximum number of iterations T is reached or the fitness value is no longer significantly improved, the iteration is stopped; The current group optimal position pb(T) is output as the optimal control range of hardness value and wear amount.

8. A glaze performance evaluation system based on multiple application scenarios, characterized in that: A glaze performance evaluation method based on multiple application scenarios as described in any one of claims 1 to 7, comprising: A raw data acquisition module, wherein the raw data acquisition module is used to collect raw data of the glaze, wherein the raw data includes a glaze hardness value and a glaze wear amount; A raw data analysis module, which is used to process the raw data to obtain a hardness distribution index and a wear resistance index; A glaze judging module, wherein the glaze judging module comprehensively analyzes the hardness distribution index and the wear resistance index of the glaze to judge whether the glaze is qualified, and marks and classifies the glaze according to the analysis result, and divides the glaze into qualified glaze and unqualified glaze; A glaze screening module, which simulates a high temperature environment based on qualified glazes, determines the thermal stability of the glazes, and screens out glazes with high thermal stability; The glaze control interval optimization module is used to record the screened glazes with high thermal stability as glazes suitable for multiple scenarios, calculate the corresponding glaze hardness values ​​and glaze wear amounts, and find the optimal solution for the glaze hardness value and glaze wear amount control interval.

9. The glaze performance evaluation system based on multiple application scenarios according to claim 8, characterized in that: The raw data analysis module at least includes: A hardness distribution index calculation unit, the hardness distribution index calculation unit is used to calculate the hardness distribution index according to the hardness value distribution of each glaze; The wear resistance index calculation unit is used to calculate the wear resistance index according to the wear amount of each glaze.

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