A method for preparing a composite high-hardness coating

Abstract

The present invention relates to the field of coating technology, and in particular to a method for preparing a composite high-hardness coating, comprising: obtaining the floating characteristics of a single dry granular material in the preparation raw material and the floating difference value of each dry granular material in a dispersant of standard viscosity; determining the viscosity base value and maximum thickness of the composite coating based on the floating characteristics and floating difference value of each dry granular material; determining the basic ratio of each dry granular material in the preparation raw material based on the viscosity base value and the maximum thickness; preparing the composite coating based on the basic ratio, and obtaining the fluidity-hardening curve of the composite coating; judging whether the prepared composite coating meets the preset standard based on the fluidity-hardening curve, if not, detecting the distribution characteristics of each dry granular material in the hardened composite coating; adjusting the viscosity base value and / or adjusting the coating hardening time based on the distribution characteristics of each dry granular material. The present invention can improve the hardness of the composite coating and ensure the coating quality.

Description

Technical Field

[0001] The invention relates to the technical field of coatings, and in particular to a method for preparing a composite high-hardness coating. Background Art

[0002] In the field of industrial production, such as machinery manufacturing, automobile manufacturing, aerospace and other industries, equipment and parts are subject to various forms of friction, wear and impact during operation. For example, the pistons, cylinder inner walls and other parts of automobile engines are subject to extremely intense friction with each other during high-speed operation. Traditional ordinary hardness coatings are difficult to meet the requirements of these parts for hardness, wear resistance and impact resistance, resulting in scratches and wear on the surface of the parts, which in turn affects the accuracy and service life of the equipment, and increases maintenance costs and downtime.

[0003] The preparation process of some coatings with good comprehensive performance is often more complicated, which not only requires special equipment and technology, but also requires strict control of various parameters in the preparation process, such as temperature, pressure, reaction time, etc. For example, some composite coatings prepared by chemical vapor deposition (CVD) or physical vapor deposition (PVD) methods have low production efficiency, high technical requirements for operators, and it is difficult to ensure hardness requirements and coating quality. Although some existing high-hardness coatings can provide a certain hardness, they often have deficiencies in other properties. For example, some high-hardness coatings sacrifice the quality of the coating while pursuing hardness improvement. This makes the coating prone to cracking and peeling when impacted by external forces, and cannot provide long-lasting and effective protection for the coated object. In some application scenarios that need to withstand vibration or deformation, such as automobile bodies, aerospace structures, etc., this high-hardness coating with a single performance cannot meet actual needs.

[0004] In summary, existing coatings have many deficiencies in hardness and coating quality, and cannot meet the growing demand for coatings in modern industry and daily life. Therefore, it is of great practical significance to develop a composite high-hardness coating preparation method with simple preparation process, high hardness and good coating quality. Summary of the invention

[0005] To this end, the present invention provides a method for preparing a composite high-hardness coating, which is used to overcome the problems in the prior art that the coating has low hardness and is difficult to ensure the coating quality.

[0006] To achieve the above object, the present invention provides a method for preparing a composite high-hardness coating, comprising:

[0007] Step S1, obtaining the floating characteristics of a single dry granular material in the preparation raw material and the floating difference values ​​of each dry granular material in a dispersant of standard viscosity, wherein the floating characteristics include floating time and floating height;

[0008] Step S2, determining the viscosity base value and maximum thickness of the composite coating based on the floating characteristics and floating difference values ​​of each of the dry particulate materials;

[0009] Step S3, determining the basic proportion of each of the dry granular materials in the raw material for preparation based on the basic viscosity value and the maximum thickness;

[0010] Step S4, preparing a composite coating based on the basic ratio, and obtaining a fluidity-hardening curve of the composite coating;

[0011] Step S5, judging whether the prepared composite coating meets the preset standard based on the fluidity-hardening curve, and if not, detecting the distribution characteristics of each of the dry particulate materials in the hardened composite coating, wherein the distribution characteristics include particle size characteristics and uniformity characteristics;

[0012] Step S6, adjusting the viscosity base value and / or adjusting the coating hardening time based on the distribution characteristics of each of the dry particulate materials.

[0013] Furthermore, in the step S1, it includes:

[0014] Step S11, determining a time difference value corresponding to each dry granular material based on the floating time of each dry granular material;

[0015] Step S12, determining a height difference value corresponding to each dry granular material based on the floating height of each dry granular material;

[0016] Step S13, determining a floating difference value corresponding to a single type of dry granular material based on each of the time difference values ​​and each of the height difference values.

[0017] Furthermore, in the step S2, it includes:

[0018] Step S21, determining the floating index of the dry granular material based on each of the floating characteristics and the floating difference value;

[0019] Step S22, determining the basic viscosity value and the maximum thickness of the composite coating based on the floating index.

[0020] Furthermore, in the step S22, it includes:

[0021] Step S221, determining a basic viscosity value of the composite coating based on the floating index and the standard viscosity;

[0022] Step S222, determining the maximum thickness of the composite coating based on the floating index and the viscosity base value.

[0023] Furthermore, in the step S3, it includes:

[0024] Step S31, determining a proportionality coefficient based on the viscosity base value and the maximum thickness;

[0025] Step S32, determining the basic proportion of each dry granular material in the raw material based on the proportion coefficient and the floating difference value of each dry granular material.

[0026] Furthermore, in the step S5, it includes:

[0027] Step S51, determining a key change region based on the fluidity-hardening curve;

[0028] Step S52: judging whether the prepared composite coating meets a preset standard based on the duration of the key change region and the key flow index corresponding to the key change region.

[0029] Furthermore, in the step S52, it includes:

[0030] Based on the comparison result of the duration with the preset duration and the comparison result of the key flow index with the preset flow index, it is judged whether the prepared composite coating meets the preset standard.

[0031] Furthermore, in step S6, it includes:

[0032] Step S61, determining a particle size characteristic coefficient based on the particle size characteristic of each of the dry granular materials, and determining a uniformity characteristic coefficient based on the uniformity characteristic of each of the dry granular materials;

[0033] Step S62, adjusting the viscosity base value and / or adjusting the coating curing time based on the particle size characteristic coefficient and the uniformity characteristic coefficient.

[0034] Furthermore, in the step S62, it includes:

[0035] The particle size characteristic coefficient is compared with a preset particle size characteristic coefficient, and the uniformity characteristic coefficient is compared with a preset uniformity characteristic coefficient, and the viscosity base value and / or the coating curing time are adjusted according to the comparison results.

[0036] Furthermore, after step S6, the method further includes: determining an effective thickness threshold of the coating based on the distribution characteristics of each of the dry particulate materials.

[0037] Compared with the prior art, the beneficial effect of the present invention is that the present invention can clarify the motion characteristics of different dry granular materials in the dispersant of standard viscosity by obtaining the floating characteristics and floating difference values ​​of a single dry granular material in the preparation raw material in the dispersant of standard viscosity. The viscosity base value and maximum thickness of the composite coating are determined based on the floating characteristics and floating difference values ​​of each dry granular material, and the basic ratio of each dry granular material in the preparation raw material is determined based on this, so that accurate proportioning can be achieved. The appropriate granular material ratio helps to form a tight and orderly structure in the coating, enhance the interaction between particles, and thus improve the hardness and coating quality of the coating. By judging whether the prepared composite coating meets the preset standard based on the fluidity-hardening curve of the composite coating, and adjusting it when it does not meet the standard, the appropriate fluidity can ensure that the coating can be evenly spread during the construction process, fill the tiny pores on the surface of the substrate, and form a smooth coating, and the appropriate hardening speed can enable the coating to reach the required hardness and performance within a suitable time. If the fluidity does not match the hardening speed, surface defects such as sagging, orange peel, and poor drying may occur. By analyzing and adjusting based on the fluidity-hardening curve, the coating quality and overall performance can be effectively improved. By adjusting the viscosity base value and / or adjusting the coating hardening time based on the distribution characteristics of each dry particulate material, the uniform distribution of the dry particulate material in the coating can be ensured, and the difference in coating performance caused by local aggregation or uneven dispersion of particles can be avoided, thereby improving the coating hardness and coating quality.

[0038] Furthermore, the present invention determines the floating difference value corresponding to a single type of dry granular material by determining the time difference value and the height difference value corresponding to each dry granular material, thereby completely describing the floating characteristics of each dry granular material from two dimensions of time and space, and can accurately distinguish their differences, providing a detailed basis for the subsequent determination of the basic proportion of each dry granular material, thereby improving the hardness of the coating and the coating quality.

[0039] Furthermore, the present invention determines the basic viscosity value of the composite coating based on the floating index and the standard viscosity, which can accurately match the characteristics of the dry particulate material in the coating, and determines the maximum thickness based on the floating index and the basic viscosity value, which can improve the accuracy of determining the maximum thickness.

[0040] Furthermore, the present invention determines a proportionality coefficient based on a basic viscosity value and a maximum thickness, and determines a basic proportion of each dry granular material in the preparation raw material based on the proportionality coefficient and the floating difference value of each dry granular material. Since the basic viscosity value and the maximum thickness reflect the key performance requirements of the coating during construction and use, the proportionality coefficient determined based on this can combine the key performance requirements with the floating difference value of the dry granular material, and can accurately adjust the proportion of each dry granular material so that each dry granular material can play the best role in the coating, thereby comprehensively optimizing the performance of the coating and improving the coating quality.

[0041] Furthermore, the fluidity-hardening curve of the present invention can dynamically display the transition process of the coating from liquid to solid. The determination of the key change area focuses on the stage where the fluidity in the curve changes significantly. This area reflects the key process of the coating curing reaction. Whether the prepared composite coating meets the preset standards is judged based on the duration of the key change area and the key flow indicators corresponding to the key change area, which can improve the accuracy of judgment and ensure the quality of the coating.

[0042] Furthermore, the present invention adjusts the basic viscosity value and / or the hardening time of the coating according to the particle size characteristics and uniformity characteristics of each dry granular material. By adjusting the basic viscosity value, the rheological properties of the coating can be improved to prevent sagging; adjusting the hardening time can enable the coating to form a uniform structure during the drying process, avoid cracking due to uneven internal stress, and ensure the hardness and quality of the coating.

[0043] Furthermore, the present invention determines the effective thickness threshold according to the distribution characteristics of each dry particulate material, thereby ensuring that within the thickness range, the distribution of the dry particulate material is relatively stable, thereby ensuring the hardness of the coating and the quality of the coating. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 The flowchart of the preparation method of the composite high-hardness coating according to the embodiment of the present invention;

[0045] Figure 2 Schematic diagram of the process of step S1 of the embodiment of the present invention;

[0046] Figure 3 Schematic diagram of the process of step S2 of the embodiment of the present invention;

[0047] Figure 4 Schematic diagram of the process of step S3 of the embodiment of the present invention;

[0048] Figure 5 This is a logical judgment diagram for judging whether the prepared composite coating meets the preset standard according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0050] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0051] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0052] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0053] See also Figure 1 As shown, it is an embodiment of the present invention Figure 1 The present invention provides a method for preparing a composite high-hardness coating, comprising:

[0054] Step S1, obtaining the floating characteristics of a single dry granular material in the preparation raw material and the floating difference values ​​of each dry granular material in a dispersant of standard viscosity, wherein the floating characteristics include floating time and floating height;

[0055] In implementation, a single dry granular material can be slowly and evenly added to a dispersant of standard viscosity, and the floating time (the average of the time interval between the start time of floating when all particles float) and the floating height (the average of the lengths between the end point of floating of all particles and the start point of floating) are detected. The detection method and equipment are not limited. This is a prior art and will not be described in detail here. The actual implementer can set the standard viscosity according to the actual situation or based on the average viscosity of the dispersant in the preparation raw material that has passed the qualification test in historical data. Preferably, the standard viscosity value range is set to 200mPa·s to 300mPa·s.

[0056] It is understood that the preparation raw materials also include dry granules, dispersants, film-forming substances, and curing agents, wherein the dry granules are the main substances that affect the hardness of the coating, and the dry granules can be inorganic non-metallic particles, metal and metal oxide particles or ceramic particles, such as quartz sand, corundum, iron powder, titanium dioxide, silicon nitride, zirconium oxide, etc. The film-forming substance can be a high-performance resin, such as epoxy resin, polyurethane resin or acrylic resin, etc., and the corresponding curing agent can be matched according to the selected main film-forming substance. For example, for epoxy resin, an amine curing agent can be selected, such as ethylenediamine, diethylenetriamine, etc., and the dispersant can be an inorganic dispersant (such as polyphosphate) or an organic dispersant (such as fatty acid salt, sulfonate, block copolymer, etc.). Preferably, the total dry granules account for 20% to 40%, the film-forming substance accounts for 40% to 60%, the curing agent accounts for 5% to 10%, and the dispersant is 1% to 3% of the total mass of the dry granules.

[0057] See also Figure 2 As shown, it is a flow chart of step S1 of an embodiment of the present invention; specifically, in step S1, it includes:

[0058] Step S11, determining a time difference value corresponding to each dry granular material based on the floating time of each dry granular material;

[0059] Step S12, determining a height difference value corresponding to each dry granular material based on the floating height of each dry granular material;

[0060] Step S13, determining a floating difference value corresponding to a single type of dry granular material based on each of the time difference values ​​and each of the height difference values.

[0061] In a specific embodiment, the floating time of each dry granular material is T=T1, T2, ..., T j ,…,T m ; j = 1, 2, ..., m, m is the type of dry granular material in the preparation raw material, T j is the floating time of the jth dry granular material, then T j The corresponding time difference value TC j For: TC j =(T j -avg(T)) / TA,TA=sqrt((∑ m j＝1 (T j -avg(T)) 2 ) / m), avg() is a preset average value determination function, sqrt() is a preset square root determination function; the floating height of each dry granular material is H=H1, H2, ..., H j , …, H m ;H jis the floating height of the jth dry granular material, then H j The corresponding height difference value HC j For: HC j =(H j -avg(H)) / HA,HA=sqrt((∑ m j＝1 (H j -avg(H)) 2 ) / m), avg() is the preset average value determination function, sqrH() is the preset square root determination function, so the floating difference value SC corresponding to the jth dry granular material is j =TC j ×HC j .

[0062] The present invention determines the floating difference value corresponding to a single type of dry granular material by determining the time difference value and the height difference value corresponding to each dry granular material. The floating characteristics of each dry granular material are completely characterized from the two dimensions of time and space, and the differences can be accurately distinguished. This provides a detailed basis for the subsequent determination of the basic proportion of each dry granular material, thereby improving the hardness of the coating and the coating quality.

[0063] Step S2, determining the viscosity base value and maximum thickness of the composite coating based on the floating characteristics and floating difference values ​​of each of the dry particulate materials;

[0064] See also Figure 3 As shown, it is a flow chart of step S2 of an embodiment of the present invention; specifically, in step S2, it includes:

[0065] Step S21, determining the floating index of the dry granular material based on each of the floating characteristics and the floating difference value;

[0066] In a specific embodiment, the floating index SZ of the dry granular material is SZ=a1×TB+a2×HB+a3×SB, wherein the floating time TC of the dry granular material is T1, T2, ..., T j ,…,T m ;Floating height of dry granular material HC=HC1,HC2,…,HC j ,…,HC m ; The floating difference of dry granular material SC = SC1, SC2, ..., SC j ,…,SC m TB=(∑ m j＝1 (TC j -avg(TC)) 2 ) / m,HB=(∑ m j＝1 (HC j-avg(HC)) 2 ) / m,SB=(∑ m j＝1 (SC j -avg(SC)) 2 ) / m, a1, a2 and a3 are weight coefficients corresponding to TB, HB and SB respectively. The actual implementers can set a1, a2 and a3 according to the actual situation or based on the floating characteristics and floating difference values ​​that have passed the qualification test in the historical data. Preferably, a1=0.3, a2=0.3, a3=0.4.

[0067] Step S22, determining the basic viscosity value and the maximum thickness of the composite coating based on the floating index.

[0068] Specifically, in step S22, it includes:

[0069] Step S221, determining a basic viscosity value of the composite coating based on the floating index and the standard viscosity;

[0070] Step S222, determining the maximum thickness of the composite coating based on the floating index and the viscosity base value.

[0071] In implementation, the basic viscosity value is determined according to the product of the square root of the floating index and the standard viscosity; a number of training samples are generated according to the floating index and the basic viscosity value corresponding to several types of dry particulate materials in composite coatings that have passed the qualification test in historical data, and the maximum thickness of the composite coating is used as the sample label of the corresponding training sample to obtain a first training sample set; the initial neural network model is trained according to the first training sample set to obtain a first neural network model; the floating index and the basic viscosity value are input into the first neural network model to obtain the maximum thickness of the composite coating output by the first neural network model.

[0072] The present invention determines the basic viscosity value of the composite coating based on the floating index and the standard viscosity, can accurately match the characteristics of the dry particulate material in the coating, and determines the maximum thickness based on the floating index and the basic viscosity value, which can improve the accuracy of determining the maximum thickness.

[0073] Step S3, determining the basic proportion of each of the dry granular materials in the raw material for preparation based on the basic viscosity value and the maximum thickness;

[0074] See also Figure 4 As shown, it is a flow chart of step S3 of an embodiment of the present invention; specifically, in step S3, it includes:

[0075] Step S31, determining a proportionality coefficient based on the viscosity base value and the maximum thickness;

[0076] Step S32, determining the basic proportion of each dry granular material in the raw material based on the proportion coefficient and the floating difference value of each dry granular material.

[0077] In a specific implementation, the first comparison value is determined based on the ratio of the viscosity base value to the viscosity threshold value, the second comparison value is determined based on the ratio of the standard thickness to the maximum thickness, and the product of the first comparison value and the second comparison value determines the proportional coefficient BX. Then, the basic proportions corresponding to each dry granular material are: GJ1, GJ2, ..., GJ j , …, GJ m， Among them, GJ j =(BX+SC j ) / (∑ m j＝1 SC j ), the actual implementer can set the viscosity threshold according to the actual viscosity requirement of the composite coating or based on the average of the maximum viscosity of the composite coating that has passed the qualification test in historical data, and the actual implementer can set the standard thickness according to the actual situation or based on the average of the maximum thickness of the composite coating that has passed the qualification test in historical data. Preferably, the viscosity threshold value range is set to 100mPa·s~250mPa·s, and the standard thickness value range is set to 80μm~150μm.

[0078] The present invention determines a proportionality coefficient based on a basic viscosity value and a maximum thickness, and determines a basic proportion of each dry granular material in the preparation raw material based on the proportionality coefficient and a floating difference value of each dry granular material. Since the basic viscosity value and the maximum thickness reflect the key performance requirements of the coating during construction and use, the proportionality coefficient determined based on this can combine the key performance requirements with the floating difference value of the dry granular material, and can accurately adjust the proportion of each dry granular material so that each dry granular material can play the best role in the coating, thereby comprehensively optimizing the performance of the coating and improving the coating quality.

[0079] Step S4, preparing a composite coating based on the basic ratio, and obtaining a fluidity-hardening curve of the composite coating;

[0080] It can be understood that during the preparation and drying process of the composite coating, a rheometer and other equipment is used to measure in real time the flow index of the composite coating (the inverse of the viscosity can be used as the flow index) as a function of time, thereby drawing a fluidity-hardening curve. The curve has time as the horizontal axis and the flow index as the vertical axis, reflecting the dynamic changes in the fluidity of the coating from a flowable state to a gradual hardening process.

[0081] Step S5, judging whether the prepared composite coating meets the preset standard based on the fluidity-hardening curve, and if not, detecting the distribution characteristics of each of the dry particulate materials in the hardened composite coating, wherein the distribution characteristics include particle size characteristics and uniformity characteristics;

[0082] See also Figure 5 As shown, it is a logical judgment diagram for judging whether the prepared composite coating meets the preset standard in an embodiment of the present invention; specifically, in the step S5, it includes:

[0083] Step S51, determining a key change region based on the fluidity-hardening curve;

[0084] Step S52: judging whether the prepared composite coating meets a preset standard based on the duration of the key change region and the key flow index corresponding to the key change region.

[0085] Specifically, in step S52, it includes:

[0086] Based on the comparison result of the duration with the preset duration and the comparison result of the key flow index with the preset flow index, it is judged whether the prepared composite coating meets the preset standard.

[0087] In a specific embodiment, the key change region is determined according to the change in the slope of the fluidity-hardening curve. If the slope of the fluidity-hardening curve is greater than a preset slope threshold, the region where the slope of the fluidity-hardening curve is greater than the preset slope threshold is determined as the key change region. If the duration of the key change region is less than the preset duration, and the key flow index is greater than the preset flow index, the prepared composite coating is judged to meet the preset standard; wherein the maximum flow index in the key change region is determined as the key flow index. It can be understood that the actual implementation personnel can set the preset slope threshold according to the actual situation or based on the mean of the sudden change slope corresponding to the fluidity-hardening curve of the composite coating that has passed the qualification test in the historical data; the actual implementation personnel can set the preset flow index according to the mean of the maximum flow index in the hardening process of the composite coating in the historical data. Preferably, the preset slope threshold value range is set to -10 (1 / (mPa·s) / min) to -5 (1 / (mPa·s) / min), and the preset flow index value range is set to 0.005 to 0.01 (1 / mPa·s).

[0088] The fluidity-hardening curve of the present invention can dynamically display the transition process of the coating from liquid to solid. The determination of the key change area focuses on the stage where the fluidity in the curve changes significantly. This area reflects the key process of the coating curing reaction. The duration of the key change area is less than the preset duration, indicating that the stage time of the significant change is relatively short, and the key flow index is greater than the preset flow index, indicating that the fluidity of the composite coating in the key change area is relatively large. In the early stage of drying, the impact of the key change area on the uniformity of the composite coating is controllable, and will not affect the final coating quality and coating hardness, which meets the preset standards. Judging whether the prepared composite coating meets the preset standards based on the duration of the key change area and the key flow index corresponding to the key change area can improve the judgment accuracy and ensure the coating quality.

[0089] Step S6, adjusting the viscosity base value and / or adjusting the coating hardening time based on the distribution characteristics of each of the dry particulate materials.

[0090] Specifically, step S6 includes:

[0091] Step S61, determining a particle size characteristic coefficient based on the particle size characteristic of each of the dry granular materials, and determining a uniformity characteristic coefficient based on the uniformity characteristic of each of the dry granular materials;

[0092] Step S62, adjusting the viscosity base value and / or adjusting the coating curing time based on the particle size characteristic coefficient and the uniformity characteristic coefficient.

[0093] Specifically, in step S62, it includes:

[0094] The particle size characteristic coefficient is compared with a preset particle size characteristic coefficient, and the uniformity characteristic coefficient is compared with a preset uniformity characteristic coefficient, and the viscosity base value and / or the coating curing time are adjusted according to the comparison results.

[0095] Specifically, if the particle size characteristic coefficient is greater than the preset particle size characteristic coefficient, and the uniformity characteristic coefficient is less than the preset uniformity characteristic coefficient, the viscosity base value is adjusted; otherwise, the coating hardening time is adjusted.

[0096] In a specific embodiment, the average particle size of the dry granular material is used as the particle size characteristic, and the particle density of the dry granular material in the composite coating is used as the uniformity characteristic. The particle size characteristics of each dry granular material are: LD = LD1, LD2, ..., LD j ,…,LD m , uniformity characteristics of each dry granular material: JY = JY1, JY2, ..., JY j , …, JY m , then the particle size characteristic coefficient is min(LD) / (∑ mj＝1 LD j ), the uniformity characteristic coefficient is max(JY) / (∑ m j＝1 JY j ), min() is a preset minimum value determination function, and max() is a preset maximum value determination function. The particle size ratio is determined according to the ratio of the particle size characteristic coefficient to the preset particle size characteristic coefficient, the uniformity ratio is determined according to the ratio of the uniformity characteristic coefficient to the preset uniformity characteristic coefficient, and the adjustment coefficient is determined according to the product of the particle size ratio and the uniformity ratio, wherein the adjusted viscosity base value is determined according to the product of the adjustment coefficient and the viscosity base value, and the adjusted coating hardening time is determined according to the product of the adjustment coefficient and the coating hardening time.

[0097] It can be understood that if the particle size characteristic coefficient is greater than the preset particle size characteristic coefficient, it indicates that the particle size of each dry granular material is relatively large, which will make the particles difficult to disperse in the coating system. If the dispersion is poor, the particles will aggregate locally and form stress concentration points in the coating. When subjected to external force, these stress concentration points are prone to cause cracks to form and expand; if the particle size characteristic coefficient is less than or equal to the preset particle size characteristic coefficient, it indicates that the particle size of each dry granular material is relatively small. Small-size dry granular materials have a larger specific surface area, which means that they have more contact area with the coating matrix (such as resin) and can produce stronger interaction, but are prone to agglomeration. Once agglomerated, these particle clusters cannot be evenly dispersed in the coating, resulting in excessively high particle concentrations in local areas and insufficient particle distribution in other areas. The sedimentation rate of small-size particles in the coating system is relatively slow, but due to their violent Brownian motion, flocculation may occur during storage, affecting the stability of the coating. If flocculation occurs in the coating before construction, it will cause uneven coating thickness and affect the consistency of hardness; the uniformity characteristic coefficient is less than the preset uniformity characteristic coefficient, indicating that the particle density The particle size is relatively small and difficult to resist external forces. After being subjected to strong friction and impact for a long time, the coating may quickly wear and deform and cannot provide lasting protection. In addition, there are many tiny gaps inside the coating, which reduces the density of the coating and affects the hardness. The uniformity characteristic coefficient is greater than or equal to the preset uniformity characteristic coefficient, indicating that the particle density is relatively large and can effectively bear the externally applied stress, but it is difficult to disperse in the coating system. If good dispersion is not achieved during the preparation process, the particles are easy to agglomerate together to form local stress concentration areas. These agglomerates will become the starting points of cracks when the coating is subjected to external forces, resulting in premature damage to the coating and reduced hardness. In addition, high-density particles are more likely to settle. If the sedimentation phenomenon is serious, it will cause uneven distribution of particles in the upper and lower layers of the coating, inconsistent performance of the formed coating, and reduced local hardness. Therefore, if the particle size characteristic coefficient is greater than the preset particle size characteristic coefficient, and the uniformity characteristic coefficient is less than the preset uniformity characteristic coefficient, the viscosity base value is adjusted; if the particle size characteristic coefficient is less than or equal to the preset particle size characteristic coefficient, and / or the uniformity characteristic coefficient is greater than or equal to the preset uniformity characteristic coefficient, the coating hardening time is adjusted.

[0098] The present invention adjusts the basic viscosity value and / or the coating hardening time according to the particle size characteristics and uniformity characteristics of each dry granular material. By adjusting the basic viscosity value, the rheological properties of the coating can be improved to prevent sagging; adjusting the hardening time can enable the coating to form a uniform structure during the drying process, avoid cracking caused by uneven internal stress, and ensure the hardness and quality of the coating.

[0099] Specifically, after step S6, the method further includes: determining an effective thickness threshold of the coating based on the distribution characteristics of each of the dry particulate materials.

[0100] It can be understood that the effective thickness threshold is the highest height to which the dry particles float to the surface of the composite coating after painting. If the dry particles are still enriched in the coating after painting and do not float to the surface of the coating, the hardness cannot be effectively improved. Therefore, during actual painting, the actual thickness of the coating should be less than or equal to the effective thickness threshold of the coating to ensure that the dry particles are enriched on the surface of the coating and significantly improve the hardness and quality of the coating.

[0101] In implementation, several training samples are generated based on the distribution characteristics corresponding to several types of dry particulate materials in composite coatings that have passed qualification tests in historical data, and the effective thickness threshold of the composite coating is used as the sample label of the corresponding training sample to obtain a second training sample set. The initial neural network model is trained based on the second training sample set to obtain a second neural network model, and the distribution characteristics of each of the dry particulate materials are input into the second neural network model to obtain the effective thickness threshold of the composite coating output by the second neural network model.

[0102] It is understandable that those skilled in the art know that any neural network model in the prior art that can obtain the maximum thickness and effective thickness threshold of the composite coating falls within the protection scope of the present invention and will not be described in detail here.

[0103] The present invention determines the effective thickness threshold according to the distribution characteristics of each dry granular material, thereby ensuring that the distribution of the dry granular material is relatively stable within the thickness range, thereby ensuring the hardness of the coating and the quality of the coating.

[0104] The present invention can clarify the motion characteristics of different dry granular materials in a dispersant of standard viscosity by obtaining the floating characteristics and floating difference values ​​of a single dry granular material in the preparation raw material in a dispersant of standard viscosity. The viscosity base value and maximum thickness of the composite coating are determined based on the floating characteristics and floating difference values ​​of each dry granular material, and the basic ratio of each dry granular material in the preparation raw material is determined based on this, so that accurate proportioning can be achieved. The appropriate granular material ratio helps to form a tight and orderly structure in the coating, enhance the interaction between particles, and thus improve the hardness and coating quality of the coating. By judging whether the prepared composite coating meets the preset standard based on the fluidity-hardening curve of the composite coating, and adjusting it when it does not meet the standard, the appropriate fluidity can ensure that the coating can be evenly spread during the construction process, fill the tiny pores on the surface of the substrate, and form a smooth coating, and the appropriate hardening speed can enable the coating to reach the required hardness and performance within a suitable time. If the fluidity does not match the hardening speed, surface defects such as sagging, orange peel, and poor drying may occur. By analyzing and adjusting based on the fluidity-hardening curve, the coating quality and overall performance can be effectively improved. By adjusting the viscosity base value and / or adjusting the coating hardening time based on the distribution characteristics of each dry particulate material, the uniform distribution of the dry particulate material in the coating can be ensured, and the difference in coating performance caused by local aggregation or uneven dispersion of particles can be avoided, thereby improving the coating hardness and coating quality.

[0105] Embodiment 1:

[0106] This embodiment provides a composite high-hardness coating prepared by the preparation method of the present invention. The raw materials for the preparation are 55% epoxy resin, 6% ethylenediamine, 1% fatty acid salt, 18% quartz sand and 20% silicon nitride. The hardness comparison at different coating thicknesses is shown in Table 1.

[0107] Embodiment 2:

[0108] This embodiment provides a composite high-hardness coating prepared by the preparation method of the present invention. The raw materials for the preparation are 54% epoxy resin, 6% ethylenediamine, 2% fatty acid salt, 18% quartz sand and 20% silicon nitride. The hardness comparison at different coating thicknesses is shown in Table 1.

[0109] Embodiment 3:

[0110] This embodiment provides a composite high-hardness coating prepared by the preparation method of the present invention, but its dispersant ratio is different from the dispersant ratio range of the present invention. The preparation raw materials are 51% epoxy resin, 6% ethylenediamine, 5% fatty acid salt, 18% quartz sand and 20% silicon nitride. The hardness comparison at different coating thicknesses is shown in Table 1.

[0111] Embodiment 4:

[0112] This embodiment provides a composite high-hardness coating prepared by a common method. The raw materials for the preparation are 55% epoxy resin, 6% ethylenediamine, 1% fatty acid salt, 10% quartz sand and 28% silicon nitride. The hardness comparison at different coating thicknesses is shown in Table 1.

[0113] Table 1 Comparison of hardness of composite high hardness coating prepared by the present invention at different coating thicknesses

[0114]

[0115] Table 1 shows that the hardness of the composite high-hardness coating prepared by the preparation method of the present invention at different coating thicknesses is significantly better than the hardness of the coating prepared by the conventional method at different coating thicknesses. Due to the different proportions of dispersants in the preparation raw materials of the composite high-hardness coating prepared by the preparation method of the present invention, the viscosity of the composite coating is different, resulting in different coating hardnesses after painting. The hardness of the composite high-hardness coating prepared in Example 1 and Example 2 is significantly better than the hardness of the composite high-hardness coating prepared in Example 3.

[0116] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A method for preparing a composite high-hardness coating, characterized in that: include: Step S1, obtaining the floating characteristics of a single dry granular material in the preparation raw material and the floating difference values ​​of each dry granular material in a dispersant of standard viscosity, wherein the floating characteristics include floating time and floating height; Step S2, determining the viscosity base value and maximum thickness of the composite coating based on the floating characteristics and floating difference values ​​of each of the dry particulate materials; Step S3, determining the basic proportion of each of the dry granular materials in the raw material for preparation based on the basic viscosity value and the maximum thickness; Step S4, preparing a composite coating based on the basic ratio, and obtaining a fluidity-hardening curve of the composite coating; Step S5, judging whether the prepared composite coating meets the preset standard based on the fluidity-hardening curve, and if not, detecting the distribution characteristics of each of the dry particulate materials in the hardened composite coating, wherein the distribution characteristics include particle size characteristics and uniformity characteristics; Step S6, adjusting the viscosity base value and / or adjusting the coating hardening time based on the distribution characteristics of each of the dry particulate materials.

2. The method for preparing the composite high-hardness coating according to claim 1, characterized in that: In the step S1, it includes: Step S11, determining a time difference value corresponding to each dry granular material based on the floating time of each dry granular material; Step S12, determining a height difference value corresponding to each dry granular material based on the floating height of each dry granular material; Step S13, determining a floating difference value corresponding to a single type of dry granular material based on each of the time difference values ​​and each of the height difference values.

3. The method for preparing the composite high-hardness coating according to claim 2, characterized in that: In the step S2, it includes: Step S21, determining the floating index of the dry granular material based on each of the floating characteristics and the floating difference value; Step S22, determining the basic viscosity value and the maximum thickness of the composite coating based on the floating index.

4. The method for preparing the composite high-hardness coating according to claim 3, characterized in that: In the step S22, it includes: Step S221, determining a basic viscosity value of the composite coating based on the floating index and the standard viscosity; Step S222, determining the maximum thickness of the composite coating based on the floating index and the viscosity base value.

5. The method for preparing the composite high-hardness coating according to claim 4, characterized in that: In the step S3, it includes: Step S31, determining a proportionality coefficient based on the viscosity base value and the maximum thickness; Step S32, determining the basic proportion of each dry granular material in the raw material based on the proportion coefficient and the floating difference value of each dry granular material.

6. The method for preparing the composite high-hardness coating according to claim 5, characterized in that: In the step S5, it includes: Step S51, determining a key change region based on the fluidity-hardening curve; Step S52: judging whether the prepared composite coating meets a preset standard based on the duration of the key change region and the key flow index corresponding to the key change region.

7. The method for preparing the composite high-hardness coating according to claim 6, characterized in that: In the step S52, it includes: Based on the comparison result of the duration with the preset duration and the comparison result of the key flow index with the preset flow index, it is judged whether the prepared composite coating meets the preset standard.

8. The method for preparing the composite high-hardness coating according to claim 7, characterized in that: In the step S6, it includes: Step S61, determining a particle size characteristic coefficient based on the particle size characteristic of each of the dry granular materials, and determining a uniformity characteristic coefficient based on the uniformity characteristic of each of the dry granular materials; Step S62, adjusting the viscosity base value and / or adjusting the coating curing time based on the particle size characteristic coefficient and the uniformity characteristic coefficient.

9. The method for preparing the composite high-hardness coating according to claim 8, characterized in that: In the step S62, it includes: The particle size characteristic coefficient is compared with a preset particle size characteristic coefficient, and the uniformity characteristic coefficient is compared with a preset uniformity characteristic coefficient, and the viscosity base value and / or the coating curing time are adjusted according to the comparison results.

10. The method for preparing the composite high-hardness coating according to claim 9, characterized in that: After step S6, the method further includes: determining an effective thickness threshold of the coating based on the distribution characteristics of each of the dry particulate materials.

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