CN117538514A - Antifouling test method and system for self-repairing paint - Google Patents
Antifouling test method and system for self-repairing paint Download PDFInfo
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- 230000003373 anti-fouling effect Effects 0.000 title claims abstract description 218
- 239000003973 paint Substances 0.000 title claims abstract description 44
- 238000010998 test method Methods 0.000 title abstract description 12
- 239000000463 material Substances 0.000 claims abstract description 83
- 239000002346 layers by function Substances 0.000 claims abstract description 81
- 238000011156 evaluation Methods 0.000 claims abstract description 73
- 238000012360 testing method Methods 0.000 claims abstract description 65
- 239000010410 layer Substances 0.000 claims abstract description 62
- 239000002689 soil Substances 0.000 claims abstract description 27
- 238000000034 method Methods 0.000 claims abstract description 18
- 238000005065 mining Methods 0.000 claims abstract description 9
- 239000000758 substrate Substances 0.000 claims abstract description 4
- 238000000576 coating method Methods 0.000 claims description 77
- 239000011248 coating agent Substances 0.000 claims description 75
- 239000011148 porous material Substances 0.000 claims description 42
- 238000012544 monitoring process Methods 0.000 claims description 22
- 238000012512 characterization method Methods 0.000 claims description 16
- 239000011159 matrix material Substances 0.000 claims description 14
- 238000013507 mapping Methods 0.000 claims description 12
- 238000012706 support-vector machine Methods 0.000 claims description 10
- 238000004458 analytical method Methods 0.000 claims description 5
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- 238000012935 Averaging Methods 0.000 claims 1
- 238000004364 calculation method Methods 0.000 description 8
- 238000002474 experimental method Methods 0.000 description 5
- 239000000835 fiber Substances 0.000 description 5
- 239000002775 capsule Substances 0.000 description 4
- 229920000642 polymer Polymers 0.000 description 3
- BPQQTUXANYXVAA-UHFFFAOYSA-N Orthosilicate Chemical compound [O-][Si]([O-])([O-])[O-] BPQQTUXANYXVAA-UHFFFAOYSA-N 0.000 description 2
- 239000012620 biological material Substances 0.000 description 2
- 239000011247 coating layer Substances 0.000 description 2
- 239000002131 composite material Substances 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 239000012621 metal-organic framework Substances 0.000 description 2
- 239000002105 nanoparticle Substances 0.000 description 2
- 239000002861 polymer material Substances 0.000 description 2
- 238000012896 Statistical algorithm Methods 0.000 description 1
- 239000003795 chemical substances by application Substances 0.000 description 1
- 238000007621 cluster analysis Methods 0.000 description 1
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- NBVXSUQYWXRMNV-UHFFFAOYSA-N fluoromethane Chemical compound FC NBVXSUQYWXRMNV-UHFFFAOYSA-N 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
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- 230000004048 modification Effects 0.000 description 1
- 229920013657 polymer matrix composite Polymers 0.000 description 1
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- 238000012545 processing Methods 0.000 description 1
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- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/26—Oils; Viscous liquids; Paints; Inks
- G01N33/32—Paints; Inks
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Abstract
The invention provides an antifouling test method and system of self-repairing paint, which relate to the technical field of intelligent test, and the method comprises the following steps: the method comprises the steps of loading substrate material characteristics and surface functional component material characteristics of self-repairing paint, configuring a first-level anti-fouling evaluation factor and a second-level anti-fouling evaluation factor to generate anti-fouling functional layer structure characteristics, mining soil size characteristics and soil quantity characteristics, when a first anti-fouling performance score of a person generated by taking the first-level anti-fouling evaluation factor according to the anti-fouling functional layer structure characteristics, the soil size characteristics and the soil quantity characteristics for evaluation is larger than or equal to a first score threshold value, and when a second anti-fouling performance score generated by taking the second-level anti-fouling evaluation factor according to the anti-fouling functional layer structure characteristics, the soil size characteristics and the soil quantity characteristics for evaluation is larger than or equal to a second score threshold value, marking an anti-fouling test qualified label, solving the technical problem that the traditional anti-fouling test is complex and causes low test efficiency, and realizing the anti-fouling intelligent test of the data layer to improve the test efficiency.
Description
Technical Field
The invention relates to the technical field of intelligent testing, in particular to an antifouling testing method and an antifouling testing system for self-repairing paint.
Background
With the development of scientific technology, in particular to the development of the field of self-repairing coating, the self-repairing coating is a polymer-based composite material and has wide application in a plurality of fields of construction, aerospace, traffic, electronics, sports, military supplies and the like. However, polymer matrix composites are susceptible to damage from impact during processing and use. In addition to the damage to the material caused by the strong impact, it is more common that the material is damaged by micro-damage (microcracks), which is a technical problem that is often difficult to detect visually and requires complicated experiments, resulting in low efficiency of the anti-fouling test.
Disclosure of Invention
The application provides an antifouling test method and an antifouling test system for self-repairing paint, which are used for solving the technical problem that the test efficiency is low due to the fact that a complex experiment is required to be carried out in the traditional antifouling test in the prior art.
In view of the above problems, the present application provides an antifouling test method and system for self-repairing paint.
In a first aspect, the present application provides a method of testing for an antifouling property of a self-healing coating, the method comprising: the characteristic of a base material and the characteristic of a surface functional component material of the self-repairing coating are loaded, wherein the characteristic of the material at least comprises a material type and a material proportion; a first-level anti-fouling evaluation factor and a second-level anti-fouling evaluation factor are configured, wherein the first-level anti-fouling evaluation factor comprises a surface pore diameter and a stain contact area, and the second-level anti-fouling evaluation factor comprises a stain attachment index; according to the characteristics of the matrix material and the characteristics of the surface functional component materials, mapping of the structure prediction channel of the anti-fouling functional layer is executed, and the structure characteristics of the anti-fouling functional layer are generated; excavating stain size characteristics and stain quantity characteristics according to the application scene of the self-repairing coating, wherein the stain size characteristics and the stain quantity characteristics are in one-to-one correspondence; according to the structural characteristics of the antifouling functional layer, the stain size characteristics and the stain quantity characteristics, the first-level antifouling evaluation factors are called for evaluation, and a first antifouling performance score is generated; according to the structural characteristics of the antifouling functional layer, the stain size characteristics and the stain quantity characteristics, the secondary antifouling evaluation factors are called for evaluation, and a second antifouling performance score is generated; and when the first antifouling property score is greater than or equal to a first score threshold value and the second antifouling property score is greater than or equal to a second score threshold value, identifying an antifouling test qualified label for the self-repairing coating.
In a second aspect, the present application provides an antifouling test system for a self-repairing paint, the system comprising: the loading module is used for loading the substrate material characteristics and the surface functional component material characteristics of the self-repairing coating, wherein the material characteristics at least comprise material types and material proportions; the configuration module is used for configuring a primary antifouling evaluation factor and a secondary antifouling evaluation factor, wherein the primary antifouling evaluation factor comprises a surface pore diameter and a stain contact area, and the secondary antifouling evaluation factor comprises a stain attachment index; the mapping module is used for performing mapping of the antifouling function layer structure prediction channel according to the base material characteristics and the surface function component material characteristics to generate an antifouling function layer structure characteristic; the feature mining module is used for mining the size features and the quantity features of the stains according to the application scene of the self-repairing coating, wherein the size features of the stains and the quantity features of the stains are in one-to-one correspondence; the first evaluation module is used for calling the first-level antifouling evaluation factors to evaluate according to the structural characteristics of the antifouling functional layer, the size characteristics of the stains and the quantity characteristics of the stains to generate a first antifouling performance score; the second evaluation module is used for calling the second-level antifouling evaluation factors to evaluate according to the structural characteristics of the antifouling functional layer, the size characteristics of the stains and the quantity characteristics of the stains to generate a second antifouling performance score; the label identification module is used for identifying the anti-fouling test qualified label for the self-repairing coating when the first anti-fouling performance score is greater than or equal to a first score threshold value and the second anti-fouling performance score is greater than or equal to a second score threshold value.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
the application provides an antifouling test method and an antifouling test system for self-repairing paint, which relate to the technical field of intelligent test, solve the technical problem that the traditional antifouling test in the prior art needs to carry out complex experiments to cause low test efficiency, combine big data to monitor the antifouling performance of a data layer, provide reference data for a user to carry out subsequent test, and carry out selective test on paint samples. The intelligent degree of the antifouling test of the self-repairing coating is improved.
Drawings
FIG. 1 is a schematic flow chart of an antifouling test method of a self-repairing paint;
fig. 2 is a schematic structural diagram of an antifouling testing system of the self-repairing coating.
Reference numerals illustrate: the system comprises a loading module 1, a configuration module 2, a mapping module 3, a feature mining module 4, a first evaluation module 5, a second evaluation module 6 and a tag identification module 7.
Detailed Description
The application provides an antifouling test method and an antifouling test system for self-repairing paint, which are used for solving the technical problem that the test efficiency is low due to the fact that a complex experiment is required to be carried out in the traditional antifouling test in the prior art.
Example 1
As shown in fig. 1, an embodiment of the present application provides an antifouling test method of a self-repairing paint, the method including:
step A100: the characteristic of a base material and the characteristic of a surface functional component material of the self-repairing coating are loaded, wherein the characteristic of the material at least comprises a material type and a material proportion;
in the application, the antifouling test method of the self-repairing coating is applied to an antifouling test system of the self-repairing coating, in order to ensure that the self-repairing coating is more accurately subjected to an antifouling test in the later period, the data loading is firstly required to be carried out on the basic material characteristics and the surface functional component material characteristics of the self-repairing coating, the material characteristics of the self-repairing coating can comprise material types, material proportions and the like, the material types can be self-repairing polymer materials, metal organic framework self-repairing materials, biological material self-repairing coatings and nanoparticle self-repairing materials, the material proportions refer to the occupation ratio of different materials under the same material types, the basic material characteristics refer to the self-repairing coating to a polymer-based composite material, the self-repairing coating has a self-repairing function after being damaged, and also has a self-repairing function under certain condition, the surface functional component material characteristics refer to material division according to the repairing types, the self-repairing coating can comprise intrinsic self-repairing coating layers and external self-repairing coating layers, the intrinsic self-repairing coating can comprise self-repairing polymer materials, metal organic framework self-repairing materials, biological material self-repairing coatings and nanoparticle self-repairing coating self-repairing materials, and self-repairing fiber coating self-repairing fiber capsules, and self-repairing fiber capsules can be realized after the self-repairing fiber capsules are assembled, and self-repairing fiber capsules are realized.
Step A200: a first-level anti-fouling evaluation factor and a second-level anti-fouling evaluation factor are configured, wherein the first-level anti-fouling evaluation factor comprises a surface pore diameter and a stain contact area, and the second-level anti-fouling evaluation factor comprises a stain attachment index;
in the application, in order to perform a more intelligent anti-fouling test on the self-repairing coating, the self-repairing coating needs to be subjected to an anti-fouling evaluation, namely, the self-repairing coating is respectively subjected to a first-level anti-fouling evaluation factor and a second-level anti-fouling evaluation factor according to an anti-fouling principle of the self-repairing coating, wherein the first-level anti-fouling evaluation factor is used for performing the anti-fouling evaluation through the size of the surface pore diameter of the self-repairing coating and the size of the contact area of the stains, the larger the surface pore diameter is, the larger the contact area of the stains is, the lower the anti-fouling evaluation factor is, the second-level anti-fouling evaluation factor is judged through the stain attachment index, the stain attachment index is in a proportional relation with the second-level anti-fouling evaluation factor, the stain attachment index is according to the adhesion degree of the stains on the self-repairing coating, and if the adhesion degree is strong, the stain attachment index is high, the second-level anti-fouling evaluation factor is low, the surface performance of the self-repairing coating is improved through introducing functional components, the self-repairing coating can be realized through reducing the contact area of the stains and the self-repairing coating, the anti-adhesion agent or the self-repairing coating is adsorbed on the self-repairing coating surface, the silicate and the surface can be a silicate and/or a film or a fluorocarbon film, the self-repairing coating can be formed, and the self-repairing surface can be smooth, and the self-repairing surface can be further, and the surface can be made, and a smooth, and the stain can be further, and the surface can be made.
Step A300: according to the characteristics of the matrix material and the characteristics of the surface functional component materials, mapping of the structure prediction channel of the anti-fouling functional layer is executed, and the structure characteristics of the anti-fouling functional layer are generated;
further, step a300 of the present application further includes:
step a310: configuring a functional layer structural feature characterization attribute, wherein the functional layer structural feature characterization attribute at least comprises a functional layer pore diameter attribute, an outer layer unit surface area attribute and an outer layer unit gap attribute, and the outer layer unit surface area attribute characterizes the surface area of a structural unit of the functional layer surface which is firstly contacted by stains;
step A320: collecting self-repairing paint antifouling test experimental data, wherein the self-repairing paint antifouling test experimental data comprises a matrix material characteristic calibration data set, a surface functional component material characteristic calibration data set and a functional layer structure characteristic experimental data set;
step a330: and performing supervision of a support vector machine by using the functional layer structure characteristic experimental data set, and performing fitting training by using the base material characteristic calibration data set and the surface functional component material characteristic calibration data set to perform input of the support vector machine so as to generate an antifouling functional layer structure prediction channel.
In this application, in order to improve the efficiency of the antifouling test of the self-repairing paint, it is necessary to use the determined collective material characteristics and the determined surface functional component material characteristics as basic reference data, and the mapping operation of the antifouling functional layer structure prediction channel in the antifouling test system of the self-repairing paint is to configure the functional layer structure characteristic characterization attribute firstly, where the functional layer structure characteristic characterization attribute at least includes a functional layer pore diameter attribute, an outer layer unit surface area attribute and an outer layer unit gap attribute, the functional layer pore diameter attribute is an attribute of the adsorption degree of the stain on the surface of the functional layer in the self-repairing paint, the outer layer unit surface area attribute is an attribute of the structural unit of the surface of the functional layer where the stain first contacts, the outer layer unit gap attribute is a gap for characterizing the stain between the surfaces of the functional layer, further, the historical experimental data of the self-repairing coating anti-fouling test is collected in a historical anti-fouling test period, the experimental data of the anti-fouling test comprises a matrix material characteristic calibration data set, a surface functional component material characteristic calibration data set and a functional layer structure characteristic experimental data set, the matrix material characteristic calibration data set refers to a data set for carrying out corresponding data identification on the material type and the material proportion of the self-repairing coating, the surface functional component material characteristic calibration data set refers to a data set for carrying out identification on the material components of the surface functional layer of the self-repairing coating, the functional layer structure characteristic experimental data set is obtained by summarizing experimental records of different repairing functional structures in the self-repairing surface functional layer, further, the supervision of a support vector machine is carried out by the functional layer structure characteristic experimental data set, the method comprises the steps of executing input of a support vector machine by using a matrix material characteristic calibration data set and a surface functional component material characteristic calibration data set to carry out fitting training, namely, matching and fitting data contained in the support vector machine by using a statistical algorithm, and simultaneously taking a functional layer structure characteristic experimental data set as fitting constraint to obtain rules and trends of the support vector machine, and generating an antifouling functional layer structure prediction channel on the basis, so as to tamp a foundation for carrying out an antifouling test on a self-repairing coating for subsequent realization.
Step A400: excavating stain size characteristics and stain quantity characteristics according to the application scene of the self-repairing coating, wherein the stain size characteristics and the stain quantity characteristics are in one-to-one correspondence;
further, step a400 of the present application further includes:
step A410: collecting spot monitoring transaction information in a preset time zone according to the self-repairing coating application scene, wherein any piece of spot monitoring transaction information in the preset time zone comprises spot type record information and spot size record information;
step a420: and grouping the stain monitoring transaction information in the preset time zone according to the stain size record information to generate a stain monitoring transaction grouping result, wherein the stain monitoring transaction grouping result has stain size characteristics, stain quantity characteristics and stain type characteristics.
In the application, in order to better perform an antifouling test on the self-repairing coating, the application scene of the self-repairing coating is required to be used as a basic background, the soil size characteristics and the soil quantity characteristics of the self-repairing coating are mined, the application scene of the self-repairing coating can be used for building scenes, aerospace scenes, traffic scenes and the like, the soil monitoring transaction information is acquired in a preset time zone based on the application scene of the self-repairing coating, namely, the soil under all scenes of the self-repairing coating application is monitored, when the soil appears, a soil monitoring transaction is correspondingly generated, the soil type and the soil size are correspondingly recorded, and any piece of preset time zone soil monitoring transaction information comprises the pre-soil type record information and the soil size record information, the stain type record information comprises all compound stain types generated by all polymers, the stain size record information comprises length data and width data of stains in the self-repairing paint in an experiment period, and further, the stain monitoring transaction information in a preset time zone is grouped according to cluster analysis according to the stain size record information, namely, the stain sizes in the stain monitoring transaction information in the preset time zone are clustered into a group, the number of groups after grouping is counted, the counted number of groups is recorded as a stain monitoring transaction grouping result, and the stain size characteristic, the stain number characteristic and the stain type characteristic are contained in the stain monitoring transaction grouping result, so that the self-repairing paint is limited in antifouling test.
Step A500: according to the structural characteristics of the antifouling functional layer, the stain size characteristics and the stain quantity characteristics, the first-level antifouling evaluation factors are called for evaluation, and a first antifouling performance score is generated;
further, step a500 of the present application further includes:
step A510: extracting a surface pore diameter value and an outer layer unit surface area value according to the structural characteristics of the antifouling functional layer;
step A520: constructing a first pollution performance scoring function:
；
wherein,characterization of the first antifouling property score,>diameter size characterizing the size of the ith stain, +.>Characterization of the surface pore diameter value, +.>Surface area value of outer layer unit is represented, n represents the number of outer layer units contacted when the largest dimension surface of the ith stain dimension characteristic is attached to the outer layer of the anti-fouling functional layer structure, and +.>Characterizing a contact area ratio threshold, +.>Area of the largest dimension face characterizing the size of the ith stain, +.>A total number of features characterizing the number of stains;
step a530: and carrying out antifouling performance evaluation according to the first antifouling performance scoring function by combining the stain size characteristic and the stain quantity characteristic, and generating the first antifouling performance score.
Further, step a530 of the present application includes:
step A531: extracting structural characteristics of the antifouling functional layer, and extracting a distribution gap value of an outer layer unit;
step a532: and performing outer layer unit distribution on the largest dimension surface of the stain dimension characteristic according to the outer layer unit distribution gap value and the outer layer unit surface area value to generate the outer layer unit quantity.
In the application, in order to perform an antifouling test on the self-repairing coating more accurately, the first-level antifouling evaluation factor configured in the system needs to be subjected to antifouling evaluation by taking the generated antifouling functional layer structural feature, the stain size feature and the stain quantity feature as basic reference parameters, which means that the surface pore diameter value and the surface area value of the outer layer unit of the self-repairing coating can be extracted according to the coating in the self-repairing coating corresponding to the antifouling functional layer structural feature, the surface pore diameter is the size of the microscopic gap of the coating determined after the measurement of the surface area distribution gap value, the larger the surface pore diameter is, the larger the gap value of the outer layer unit distribution is, the larger the microscopic gap of the coating is, and further, the outer layer unit distribution is performed according to the largest size surface in the stain size feature determined in the self-repairing coating, which means that the outer layer surface with the largest size exists in the self-repairing coating is marked, and the number of the outer layer units is recorded after the integration according to the marking quantity.
Further, a first pollution performance scoring function is constructed, and the stain resistance performance is evaluated by combining the stain size characteristic and the stain quantity characteristic with the first pollution performance scoring function, wherein the first pollution performance scoring function is as follows:
；
wherein,characterization of the first antifouling property score,>diameter size characterizing the size of the ith stain, +.>Characterization of the surface pore diameter value, +.>Surface area value of outer layer unit is represented, n represents the number of outer layer units contacted when the largest dimension surface of the ith stain dimension characteristic is attached to the outer layer of the anti-fouling functional layer structure, and +.>Characterizing a contact area ratio threshold, +.>Area of the largest dimension face characterizing the size of the ith stain, +.>A total number of features characterizing the number of stains;
the method comprises the steps of comparing a stain diameter size in stain size characteristics of a self-repairing coating with a surface pore diameter value, then performing a quotient with the total number of the stain number characteristics, determining the ratio of different stain sizes in the number of stains, multiplying the surface area value of an outer layer unit by the number of outer layer units contacted when the largest dimension surface of the i-th stain size characteristic is attached to the outer layer of the anti-fouling functional layer structure, performing a quotient with the area of the largest dimension surface of the i-th stain size characteristic, performing a quotient with the total number of the stain number characteristics when the surface area value is smaller than or equal to a contact area ratio threshold value, determining the area ratio of the outer layer units where the stains are located, and finally summing the surface area values and outputting a first anti-fouling performance score so as to serve as reference data when the self-repairing coating is subjected to anti-fouling test in the later period.
Step A600: according to the structural characteristics of the antifouling functional layer, the stain size characteristics and the stain quantity characteristics, the secondary antifouling evaluation factors are called for evaluation, and a second antifouling performance score is generated;
further, step a600 of the present application further includes:
step a610: extracting a stain type feature having the stain size feature less than or equal to a surface pore diameter value;
step a620: traversing the stain type features, taking the surface pore diameter value, the matrix material features and the surface functional component material features as constraints, and searching a stain passing rate set, wherein the stain passing rate refers to the ratio of the number of stains which enter the paint through the functional layer and enter the paint through the functional layer, wherein the number of stains is of the same type and the size of the stains is smaller than or equal to the surface pore diameter value, to the preset number;
step a630: and carrying out average analysis on the soil passing rate set to generate a soil comprehensive passing rate, wherein the second antifouling property score is equal to 1 minus the soil comprehensive passing rate.
Further, step a630 of the present application includes:
step a631: traversing the stain type features, and calculating a set of stain type weights based on the stain quantity features, wherein the stain type weights refer to a ratio of a number of occupied stain types in the stain quantity features to a total number of stain quantities;
step a632: and calculating a weighted average value according to the stain type weight set and the stain passing rate set, and generating the comprehensive stain passing rate.
In the application, the stain-proofing evaluation factor is evaluated by using the stain-proofing functional layer structure feature, the stain size feature and the stain quantity feature in the same way, namely, after the stain size is compared with the surface pore diameter value, when the stain size feature is smaller than or equal to the surface pore diameter value, the stain type feature of the current stain is extracted, wherein the stain type feature can be dry stain, wet stain, oily stain and the like, the surface pore diameter value, the matrix material feature and the surface functional component material feature are further used as traversing boundary constraint, the stain type feature is traversed, namely, the surface pore diameter value, the matrix material feature and the surface functional component material feature are compared and accessed to the stain in each feature data node in the stain type feature, searching a set of the pass rate of the stains on the basis, wherein the pass rate of the stains refers to the ratio of the quantity of the stains which enter the interior of the paint through the functional layer and have the size smaller than or equal to the surface pore diameter value to the preset quantity, further, carrying out average analysis on the set of the pass rate of the stains refers to firstly carrying out one traversal access on each feature data contained in the characteristics of the stain types, calculating the weight of each stain type based on the ratio of the stain types in the characteristics of the stain types, summarizing the stain types with the weight as a weight set of the stain types, wherein the weight of the stain types refers to the ratio of the occupied quantity of the stain types in the characteristics of the stain types to the total quantity of the stains, carrying out weighted average calculation according to the weight set of the stain types to the total quantity of the stain types, the weighting calculation needs to be based on a large amount of data summarization and accurately determine weights, and then the targeted calculation is performed, and for example, the weight ratio of the stain type weight set to the stain passing rate set may be a first influence coefficient: and if the second influence coefficient is 4:6, the influence parameters after the weighted calculation process are respectively 0.4 for the first influence parameter and 0.6 for the second influence parameter, the final value obtained after the average value is obtained according to the weighted calculation result to generate the comprehensive pass rate of the stains, and the second antifouling performance score is obtained by subtracting the comprehensive pass rate of the stains from 1, so that the accuracy of the antifouling test of the self-repairing coating is improved in the later stage.
Step A700: and when the first antifouling property score is greater than or equal to a first score threshold value and the second antifouling property score is greater than or equal to a second score threshold value, identifying an antifouling test qualified label for the self-repairing coating.
In this application, in order to improve the accuracy of the result after the self-repairing coating performs the anti-fouling test, it is necessary to compare and judge the first anti-fouling performance score with the first scoring threshold value, and the second anti-fouling performance score with the second scoring threshold value, where the first scoring threshold value is obtained by demarcating the pore diameter and the stain contact area of the upper surface of the self-repairing coating in the historical period, and the second scoring threshold value is obtained by demarcating the stain attachment index in the historical period, and there are 4 cases as follows:
when the first antifouling performance score is smaller than the first score threshold and the second antifouling performance score is smaller than the second score threshold, the stain contact area in the current self-repairing paint is larger than the surface pore diameter, the current stain attachment index is higher than the preset index, stains are difficult to remove, and at the moment, the antifouling test of the self-repairing paint is unqualified;
when the first antifouling property score is smaller than the first score threshold and the second antifouling property score is larger than or equal to the second score threshold, the stain contact area in the current self-repairing paint is larger than the surface pore diameter, and the antifouling test of the self-repairing paint is failed;
when the first antifouling performance score is greater than or equal to the first score threshold and the second antifouling performance score is less than the second score threshold, the current stain attachment index is higher than the preset index, stains are difficult to remove, and at the moment, the antifouling test of the self-repairing coating is unqualified;
when the first antifouling performance score is greater than or equal to the first score threshold and the second antifouling performance score is greater than or equal to the second score threshold, the current self-repairing paint is considered to be smaller than the surface pore diameter in the contact area of the stains, the current stain attachment index is lower than the preset index, the current stains can be blocked, at the moment, the antifouling test of the self-repairing paint is qualified, and meanwhile, the self-repairing paint is marked with a qualified label of the antifouling test.
In summary, the method for testing the self-repairing paint according to the embodiment of the application at least has the following technical effects that the method for testing the self-repairing paint combines big data to monitor the anti-fouling performance of a data layer, can provide reference data for a user to perform subsequent testing, and can selectively test paint samples. The intelligent degree of the antifouling test of the self-repairing coating is improved.
Example two
Based on the same inventive concept as the antifouling test method of a self-repairing paint in the foregoing embodiments, as shown in fig. 2, the present application provides an antifouling test system of a self-repairing paint, the system comprising:
the loading module 1 is used for loading the substrate material characteristics and the surface functional component material characteristics of the self-repairing coating, wherein the material characteristics at least comprise material types and material proportions;
the configuration module 2 is used for configuring a primary antifouling evaluation factor and a secondary antifouling evaluation factor, wherein the primary antifouling evaluation factor comprises a surface pore diameter and a stain contact area, and the secondary antifouling evaluation factor comprises a stain attachment index;
the mapping module 3 is used for performing mapping of the antifouling function layer structure prediction channel according to the base material characteristics and the surface function component material characteristics to generate an antifouling function layer structure characteristic;
the feature mining module 4 is used for mining the size features and the quantity features of the stains according to the application scene of the self-repairing coating, wherein the size features of the stains and the quantity features of the stains are in one-to-one correspondence;
the first evaluation module 5 is configured to invoke the first-level antifouling evaluation factor according to the structural feature of the antifouling functional layer, the size feature of the stains and the number feature of the stains to evaluate, so as to generate a first antifouling performance score;
the second evaluation module 6 is configured to invoke the second-level anti-fouling evaluation factor to evaluate according to the structural feature of the anti-fouling functional layer, the size feature of the stains and the number feature of the stains, and generate a second anti-fouling performance score;
the label identification module 7 is configured to identify a label passing the anti-fouling test for the self-repairing coating when the first anti-fouling performance score is greater than or equal to a first score threshold and the second anti-fouling performance score is greater than or equal to a second score threshold.
Further, the system further comprises:
the attribute configuration module is used for configuring a functional layer structural feature characterization attribute, wherein the functional layer structural feature characterization attribute at least comprises a functional layer pore diameter attribute, an outer layer unit surface area attribute and an outer layer unit gap attribute, and the outer layer unit surface area attribute characterizes the surface area of a structural unit of the functional layer surface which is firstly contacted by stains;
the data acquisition module is used for acquiring self-repairing paint antifouling test experimental data and comprises a matrix material characteristic calibration data set, a surface functional component material characteristic calibration data set and a functional layer structure characteristic experimental data set;
and the fitting training module is used for performing supervision of the support vector machine by using the functional layer structure characteristic experimental data set, performing fitting training by using the matrix material characteristic calibration data set and the surface functional component material characteristic calibration data set to perform input of the support vector machine, and generating an antifouling functional layer structure prediction channel.
Further, the system further comprises:
the first extraction module is used for extracting a surface pore diameter value and an outer layer unit surface area value according to the structural characteristics of the antifouling functional layer;
a function module for constructing a first pollution performance scoring function:
；
wherein,characterization of the first antifouling property score,>diameter size characterizing the size of the ith stain, +.>Characterization of the surface pore diameter value, +.>Surface area value of outer layer unit is represented, n represents the number of outer layer units contacted when the largest dimension surface of the ith stain dimension characteristic is attached to the outer layer of the anti-fouling functional layer structure, and +.>Characterizing a contact area ratio threshold, +.>Area of the largest dimension face characterizing the size of the ith stain, +.>A total number of features characterizing the number of stains;
and the score generation module is used for carrying out antifouling performance evaluation according to the first antifouling performance score function and combining the stain size characteristics and the stain quantity characteristics to generate the first antifouling performance score.
Further, the system further comprises:
the second extraction module is used for extracting structural features of the anti-fouling functional layer and extracting outer layer unit distribution gap values;
and the outer layer unit distribution module is used for carrying out outer layer unit distribution on the largest dimension surface of the stain size characteristic according to the outer layer unit distribution gap value and the outer layer unit surface area value to generate the outer layer unit quantity.
Further, the system further comprises:
the first judging module is used for extracting the stain type characteristics with the stain size characteristics smaller than or equal to the surface pore diameter value;
the traversing module is used for traversing the stain type characteristics, taking the surface pore diameter value, the base material characteristics and the surface functional component material characteristics as constraints, and searching a stain passing rate set, wherein the stain passing rate refers to the ratio of the number of stains which enter the paint through the functional layer to the preset number, wherein the number of stains is of the same type and the size of the stains is smaller than or equal to the surface pore diameter value;
and the average analysis module is used for carrying out average analysis on the stain passing rate set to generate a stain comprehensive passing rate, wherein the second antifouling property score is equal to 1 minus the stain comprehensive passing rate.
Further, the system further comprises:
a first calculation module for traversing the stain type features, calculating a set of stain type weights based on the stain quantity features, wherein the stain type weights refer to a ratio of a number of occupied stain types in the stain quantity features to a total number of stain quantities;
and the second calculation module is used for carrying out weighted average calculation according to the stain type weight set and the stain passing rate set to generate the comprehensive stain passing rate.
Further, the system further comprises:
the information acquisition module is used for acquiring stain monitoring transaction information in a preset time zone according to the self-repairing coating application scene, wherein any piece of stain monitoring transaction information in the preset time zone comprises stain type record information and stain size record information;
the grouping module is used for grouping the stain monitoring transaction information in the preset time zone according to the stain size recording information to generate a stain monitoring transaction grouping result, wherein the stain monitoring transaction grouping result has stain size characteristics, stain quantity characteristics and stain type characteristics.
The foregoing detailed description of the method for testing the self-repairing paint will clearly be known to those skilled in the art, and the device disclosed in the embodiments is relatively simple to describe, and the relevant points refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A method for testing the stain resistance of a self-healing coating, comprising:
the characteristic of a base material and the characteristic of a surface functional component material of the self-repairing coating are loaded, wherein the characteristic of the material at least comprises a material type and a material proportion;
a first-level anti-fouling evaluation factor and a second-level anti-fouling evaluation factor are configured, wherein the first-level anti-fouling evaluation factor comprises a surface pore diameter and a stain contact area, and the second-level anti-fouling evaluation factor comprises a stain attachment index;
according to the characteristics of the matrix material and the characteristics of the surface functional component materials, mapping of the structure prediction channel of the anti-fouling functional layer is executed, and the structure characteristics of the anti-fouling functional layer are generated;
excavating stain size characteristics and stain quantity characteristics according to the application scene of the self-repairing coating, wherein the stain size characteristics and the stain quantity characteristics are in one-to-one correspondence;
according to the structural characteristics of the antifouling functional layer, the stain size characteristics and the stain quantity characteristics, the first-level antifouling evaluation factors are called for evaluation, and a first antifouling performance score is generated;
according to the structural characteristics of the antifouling functional layer, the stain size characteristics and the stain quantity characteristics, the secondary antifouling evaluation factors are called for evaluation, and a second antifouling performance score is generated;
and when the first antifouling property score is greater than or equal to a first score threshold value and the second antifouling property score is greater than or equal to a second score threshold value, identifying an antifouling test qualified label for the self-repairing coating.
2. The method of claim 1, wherein performing mapping of the predicted channels of the anti-fouling functional layer structure based on the base material characteristics and the surface functional component material characteristics, generating the anti-fouling functional layer structure characteristics, previously comprises:
configuring a functional layer structural feature characterization attribute, wherein the functional layer structural feature characterization attribute at least comprises a functional layer pore diameter attribute, an outer layer unit surface area attribute and an outer layer unit gap attribute, and the outer layer unit surface area attribute characterizes the surface area of a structural unit of the functional layer surface which is firstly contacted by stains;
collecting self-repairing paint antifouling test experimental data, wherein the self-repairing paint antifouling test experimental data comprises a matrix material characteristic calibration data set, a surface functional component material characteristic calibration data set and a functional layer structure characteristic experimental data set;
and performing supervision of a support vector machine by using the functional layer structure characteristic experimental data set, and performing fitting training by using the base material characteristic calibration data set and the surface functional component material characteristic calibration data set to perform input of the support vector machine so as to generate an antifouling functional layer structure prediction channel.
3. The method of claim 2, wherein invoking the first order stain resistance evaluation factor to evaluate based on the stain resistance functional layer structural feature, the stain size feature and the stain quantity feature, generates a first stain resistance performance score comprising:
extracting a surface pore diameter value and an outer layer unit surface area value according to the structural characteristics of the antifouling functional layer;
constructing a first pollution performance scoring function:
；
wherein,characterization of the first antifouling property score,>diameter size characterizing the size of the ith stain, +.>Characterization of the surface pore diameter value, +.>Surface area value of outer layer unit is represented, n represents the number of outer layer units contacted when the largest dimension surface of the ith stain dimension characteristic is attached to the outer layer of the anti-fouling functional layer structure, and +.>Characterizing a contact area ratio threshold, +.>Area of the largest dimension face characterizing the size of the ith stain, +.>A total number of features characterizing the number of stains;
and carrying out antifouling performance evaluation according to the first antifouling performance scoring function by combining the stain size characteristic and the stain quantity characteristic, and generating the first antifouling performance score.
4. The method of claim 3, wherein performing an anti-fouling performance assessment in combination with the stain size feature and the stain quantity feature according to the first fouling performance scoring function to generate the first anti-fouling performance score comprises:
extracting structural characteristics of the antifouling functional layer, and extracting a distribution gap value of an outer layer unit;
and performing outer layer unit distribution on the largest dimension surface of the stain dimension characteristic according to the outer layer unit distribution gap value and the outer layer unit surface area value to generate the outer layer unit quantity.
5. The method of claim 1, wherein invoking the secondary stain resistance evaluation factor to evaluate based on the stain resistance functional layer structural feature, the stain size feature and the stain quantity feature, generates a second stain resistance performance score comprising:
extracting a stain type feature having the stain size feature less than or equal to a surface pore diameter value;
traversing the stain type features, taking the surface pore diameter value, the matrix material features and the surface functional component material features as constraints, and searching a stain passing rate set, wherein the stain passing rate refers to the ratio of the number of stains which enter the paint through the functional layer and enter the paint through the functional layer, wherein the number of stains is of the same type and the size of the stains is smaller than or equal to the surface pore diameter value, to the preset number;
and carrying out average analysis on the soil passing rate set to generate a soil comprehensive passing rate, wherein the second antifouling property score is equal to 1 minus the soil comprehensive passing rate.
6. The method of claim 5, wherein averaging the set of soil pass rates to generate a soil integrated pass rate, wherein the second anti-soil performance score is equal to 1 minus the soil integrated pass rate comprises:
traversing the stain type features, and calculating a set of stain type weights based on the stain quantity features, wherein the stain type weights refer to a ratio of a number of occupied stain types in the stain quantity features to a total number of stain quantities;
and calculating a weighted average value according to the stain type weight set and the stain passing rate set, and generating the comprehensive stain passing rate.
7. The method of claim 1, wherein mining the stain size feature and the stain quantity feature according to the self-healing paint application scenario comprises:
collecting spot monitoring transaction information in a preset time zone according to the self-repairing coating application scene, wherein any piece of spot monitoring transaction information in the preset time zone comprises spot type record information and spot size record information;
and grouping the stain monitoring transaction information in the preset time zone according to the stain size record information to generate a stain monitoring transaction grouping result, wherein the stain monitoring transaction grouping result has stain size characteristics, stain quantity characteristics and stain type characteristics.
8. An antifouling test system for a self-repairing paint, comprising:
the loading module is used for loading the substrate material characteristics and the surface functional component material characteristics of the self-repairing coating, wherein the material characteristics at least comprise material types and material proportions;
the configuration module is used for configuring a primary antifouling evaluation factor and a secondary antifouling evaluation factor, wherein the primary antifouling evaluation factor comprises a surface pore diameter and a stain contact area, and the secondary antifouling evaluation factor comprises a stain attachment index;
the mapping module is used for performing mapping of the antifouling function layer structure prediction channel according to the base material characteristics and the surface function component material characteristics to generate an antifouling function layer structure characteristic;
the feature mining module is used for mining the size features and the quantity features of the stains according to the application scene of the self-repairing coating, wherein the size features of the stains and the quantity features of the stains are in one-to-one correspondence;
the first evaluation module is used for calling the first-level antifouling evaluation factors to evaluate according to the structural characteristics of the antifouling functional layer, the size characteristics of the stains and the quantity characteristics of the stains to generate a first antifouling performance score;
the second evaluation module is used for calling the second-level antifouling evaluation factors to evaluate according to the structural characteristics of the antifouling functional layer, the size characteristics of the stains and the quantity characteristics of the stains to generate a second antifouling performance score;
the label identification module is used for identifying the anti-fouling test qualified label for the self-repairing coating when the first anti-fouling performance score is greater than or equal to a first score threshold value and the second anti-fouling performance score is greater than or equal to a second score threshold value.
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