A magnesium alloy protective coating life prediction method, device, equipment and medium

Abstract

The application relates to the technical field of coating life prediction. A magnesium alloy protective coating life prediction method, device, equipment and medium are provided. The method comprises the following steps: acquiring coating parameters and corrosion medium parameters; based on a pre-set coating moisture diffusion model, the diffusion time of moisture in the coating is calculated according to the coating parameters and the corrosion medium parameters; based on a pre-set coating adhesion decay model and a corrosion hydrogen evolution induced additional stress increase model, the coating failure time is determined according to the coating parameters and the corrosion medium parameters; and the coating predicted life is calculated according to the diffusion time of moisture in the coating and the coating failure time. Based on the in-depth understanding of the magnesium alloy corrosion process and the full understanding of the organization and performance evolution law of the coating failure process, the magnesium alloy protective coating life can be accurately and quickly predicted.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of coating life prediction, in particular to a magnesium alloy protective coating life prediction method, device, equipment and medium. BACKGROUND

[0002] At present, there are two main types of coating life prediction technology: one is based on a large amount of data for machine learning or establishing empirical formula, the internal relationship is often not clear, and accurate prediction can be realized within the scope of existing data, but the model is invalid beyond the existing data range, and prediction cannot be realized; the other is based on the accurate understanding of coating organization, performance and failure process, and the mechanism model is constructed, which has a large degree of freedom and can be extrapolated to the existing data, but it is difficult to clearly understand all the coating organization evolution and performance evolution law at present.

[0003] The applicable object of the existing coating life prediction technology is traditional metal materials such as steel and aluminum alloy, which cannot be applied to the protective coating life prediction of magnesium alloy, and the main reason is that the cathode reaction of the corrosion process of traditional metal materials is dominated by oxygen absorption corrosion, while magnesium alloy is a typical hydrogen evolution corrosion as the cathode reaction, and under the effect of negative difference number effect, the coating corrosion failure speed is faster, and the existing coating life prediction technology cannot be applied.

[0004] Therefore, it has been a difficult problem in the industry to find a magnesium alloy protective coating life prediction method. SUMMARY

[0005] In view of the above problems, the embodiments of the present application provide a magnesium alloy protective coating life prediction method, device, equipment and medium, which aims to solve the above problems or at least partially solve the above problems.

[0006] The present application provides a magnesium alloy protective coating life prediction method, device, equipment and medium, which comprises:

[0007] In a first aspect, a magnesium alloy protective coating life prediction method is provided, comprising:

[0008] obtaining coating parameters and corrosion medium parameters;

[0009] Based on the pre-set coating moisture diffusion model, the diffusion time of moisture in the coating is calculated according to the coating parameters and the corrosion medium parameters;

[0010] Based on the pre-set coating adhesion decay model and corrosion hydrogen evolution induced additional stress increase model, the coating failure time is determined according to the coating parameters and the corrosion medium parameters;

[0011] According to the diffusion time of the moisture in the coating and the coating failure time, the coating predicted life is calculated.

[0012] Preferably, the coating parameters include coating thickness.

[0013] The corrosion medium parameters include corrosion medium temperature, corrosion medium humidity, and corrosion medium concentration.

[0014] Preferably, the coating moisture diffusion model includes an organic coating moisture diffusion model and an inorganic coating moisture diffusion model.

[0015] According to the coating parameters and the corrosion medium parameters, the diffusion time of the moisture in the coating is calculated based on the pre-set coating moisture diffusion model, including:

[0016] According to the corrosion medium parameters, the diffusion time of the moisture in the organic coating is calculated based on the organic coating moisture diffusion model.

[0017] According to the coating parameters and the corrosion medium parameters, the diffusion time of the moisture in the inorganic coating is calculated based on the inorganic coating moisture diffusion model.

[0018] According to the diffusion time of the moisture in the organic coating and the diffusion time of the moisture in the inorganic coating, the diffusion time of the moisture in the coating is calculated.

[0019] Preferably, according to the coating parameters and the corrosion medium parameters, the diffusion time of the moisture in the organic coating is calculated based on the organic coating moisture diffusion model, including:

[0020] The relationship between the water absorption rate of the organic coating and temperature, and the relationship between the saturated water absorption rate of the organic coating and temperature are obtained.

[0021] According to the relationship between the water absorption rate of the organic coating and temperature, the relationship between the saturated water absorption rate of the organic coating and temperature, and the corrosion medium parameters, the diffusion time of the moisture in the organic coating is calculated.

[0022] Preferably, according to the coating parameters and the corrosion medium parameters, the diffusion time of the moisture in the inorganic coating is calculated based on the inorganic coating moisture diffusion model, including:

[0023] The relationship between the diffusion coefficient of the moisture in the inorganic coating and temperature is obtained.

[0024] According to the relationship between the diffusion coefficient of the moisture in the inorganic coating and temperature, the relationship between the diffusion distance of the moisture in the inorganic coating and the complete diffusion time of the moisture in the inorganic coating is determined.

[0025] According to the relationship between the diffusion distance of moisture in the inorganic coating and the complete diffusion time of moisture in the inorganic coating, and the coating parameters and the corrosion medium parameters, the diffusion time of moisture in the inorganic coating is calculated.

[0026] Preferably, the coating failure time is determined according to the pre-set coating adhesion decay model and the corrosion hydrogen evolution induced additional stress increase model, based on the coating parameters and the corrosion medium parameters, comprising:

[0027] The hydrogen gas parameters, the magnesium alloy parameters, the composite relationship of adhesion and temperature and time, and the composite relationship of corrosion hydrogen evolution induced internal stress and temperature and time are obtained.

[0028] According to the composite relationship of adhesion and temperature and time and the corrosion medium parameters, the coating wet-state adhesion is calculated.

[0029] According to the composite relationship of corrosion hydrogen evolution induced internal stress and temperature and time, the hydrogen gas parameters, the magnesium alloy parameters and the corrosion medium parameters, the corrosion hydrogen evolution induced additional stress is calculated.

[0030] According to the coating wet-state adhesion and the corrosion hydrogen evolution induced additional stress, the coating failure time is determined.

[0031] Preferably, the coating predicted life is calculated according to the diffusion time of moisture in the coating and the coating failure time, comprising:

[0032] The coating theoretical life is calculated according to the diffusion time of moisture in the coating and the coating failure time.

[0033] The corrosion medium theoretical parameters and the corrosion medium actual parameters are determined, and the conversion coefficient is calculated according to the corrosion medium theoretical parameters and the corrosion medium actual parameters.

[0034] The coating predicted life is calculated according to the coating theoretical life and the conversion coefficient.

[0035] In the second aspect, a magnesium alloy protective coating life prediction device is provided, comprising:

[0036] The acquisition module is used to acquire coating parameters and corrosion medium parameters.

[0037] The diffusion calculation module is used to calculate the diffusion time of moisture in the coating according to the coating parameters and the corrosion medium parameters based on the pre-set coating moisture diffusion model.

[0038] The failure calculation module is used to determine the coating failure time according to the coating parameters and the corrosion medium parameters based on the pre-set coating adhesion decay model and the corrosion hydrogen evolution induced additional stress increase model.

[0039] a life prediction module configured to calculate a predicted life of the coating according to the diffusion time of the moisture in the coating and the coating failure time.

[0040] In a third aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the magnesium alloy protective coating life prediction method according to the first aspect when executing the computer program.

[0041] In a fourth aspect, a computer readable storage medium is provided, wherein the computer readable storage medium stores a computer program, and the computer program, when executed by a processor, implements the steps of the magnesium alloy protective coating life prediction method according to the first aspect.

[0042] The above at least one technical solution adopted by the embodiments of the present application can achieve the following beneficial effects:

[0043] Based on the in-depth understanding of the magnesium alloy corrosion process and the full understanding of the organization and performance evolution law of the coating failure process, the present application provides a coating moisture diffusion model, a coating adhesion force decay model, and an additional stress increase model induced by corrosion hydrogen evolution, and can accurately and quickly predict the life of the magnesium alloy protective coating by using actual coating parameters and corrosion medium parameters. BRIEF DESCRIPTION OF DRAWINGS

[0044] The accompanying drawings, which are included to provide a further understanding of the present application, constitute a part of the present application and illustrate the illustrative embodiments of the present application and their description serve to explain the present application, and do not constitute improper limitations on the present application. In the drawings:

[0045] Figure 1 is a schematic diagram of an application corrosion medium of the magnesium alloy protective coating life prediction method in an embodiment of the present application;

[0046] Figure 2 is a schematic diagram of a magnesium alloy composite coating corrosion failure process in an embodiment of the present application;

[0047] Figure 3 is a flowchart of the magnesium alloy protective coating life prediction method in an embodiment of the present application;

[0048] Figure 4 is a process schematic diagram of the acquisition of the polarization resistance and the acquisition of the complete diffusion time by the graphical method in an embodiment of the present application;

[0049] Figure 5 is a schematic diagram of the coating failure induced by corrosion hydrogen evolution in an embodiment of the present application;

[0050] Figure 6is a schematic diagram of coating adhesion force decay and hydrogen evolution additional stress increase in an embodiment of the present application;

[0051] Figure 7 is a schematic diagram of water film formation time device for laminated electrode test in an embodiment of the present application;

[0052] Figure 8 is a schematic diagram of Weibull function distribution of micro-arc oxidation coating and composite coating in an embodiment of the present application;

[0053] Figure 9 is a schematic diagram of micro-creep loading device structure in an embodiment of the present application;

[0054] Figure 10 is a schematic diagram of magnesium alloy and dissimilar metal connection in an embodiment of the present application;

[0055] Figure 11 is a schematic diagram of magnesium alloy protective coating life prediction device structure in an embodiment of the present application;

[0056] Figure 12 is a schematic diagram of computer device structure in an embodiment of the present application;

[0057] Figure 13 is another schematic diagram of computer device structure in an embodiment of the present application. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical scheme and advantages of the present application clearer, the technical scheme of the present application will be described clearly and completely below in combination with specific embodiments of the present application and corresponding drawings. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0059] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that such use can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the term "comprising" and its variants are to be interpreted as meaning "including but not limited to" an open term.

[0060] The technical scheme provided by each embodiment of the present application will be described in detail below in combination with the drawings.

[0061] As mentioned earlier, current coating life prediction technologies are mostly based on the analysis of massive amounts of data, which cannot achieve long-term life prediction and extrapolation. Furthermore, they are applicable to traditional metal materials such as steel or aluminum alloys, but not to magnesium alloys. To address this technical problem, this application provides a method for predicting the life of protective coatings on magnesium alloys.

[0062] The magnesium alloy protective coating life prediction method provided in this invention can be applied to, for example... Figure 1 In this application environment, the device communicates with the server via a network. The server can obtain coating parameters and corrosion medium parameters from the device. Based on a pre-set coating moisture diffusion model, it calculates the diffusion time of moisture in the coating according to the coating parameters and corrosion medium parameters. Based on a pre-set coating adhesion decay model and corrosion hydrogen evolution induced additional stress increase model, it determines the coating failure time according to the coating parameters and corrosion medium parameters. Based on the moisture diffusion time and coating failure time, it calculates the predicted coating lifetime. This application, based on a deep understanding of the magnesium alloy corrosion process and a full understanding of the organization and performance evolution laws of the coating failure process, provides a coating moisture diffusion model, a coating adhesion decay model, and a corrosion hydrogen evolution induced additional stress increase model. Using actual coating parameters and corrosion medium parameters, it can accurately and quickly predict the lifetime of magnesium alloy protective coatings. The device can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be implemented using a standalone server or a server cluster composed of multiple servers. The invention will be described in detail below through specific embodiments.

[0063] Specifically, such as Figure 2 As shown, magnesium alloy protective coatings can be composite coatings (organic and inorganic coatings). The failure process of magnesium alloy protective coatings includes: First stage: When the composite coating is exposed to a corrosive medium, an electrolyte layer forms on the coating surface due to the adsorption of water molecules. This layer contains corrosive ions (such as Cl-). - and SO4 2- The formation process of the electrolyte layer is initially slow and unstable because evaporation and deposition occur simultaneously on the coating surface (e.g., Figure 2 (a) Second stage: Once the electrolyte layer deposition becomes dominant, the penetration of corrosive electrolytes is triggered. The slow water absorption within the organic coating not only hinders the migration of corrosive ions, but also affects the mechanical properties of the coating, as the breakage of polymer chains leads to a deterioration in the coating's mechanical strength and density. Similarly, once the organic coating is saturated with water, corrosive media begin to migrate. Inorganic coatings, such as plasma electrolyte coatings and conversion coatings, are rich in cracks and pores, which are pathways for the penetration of corrosive electrolytes (e.g.,Figure 2 Meanwhile, the entry of the corrosive electrolyte into the inorganic coating also reduces the adhesion strength of the coating. The third stage: when the corrosive medium reaches the metal / coating interface, an electrochemical reaction will be triggered, and the evolution of hydrogen gas will accumulate. The accumulation of gas will generate tensile stress, eventually exceeding the tensile strength of the composite coating, and causing the composite coating to crack, which means the rupture of the composite coating (such as Figure 2 c) in the foregoing.

[0064] Further, the second stage and the third stage of the failure process of the composite coating can also be divided into: the first process: the diffusion process of water in the organic electrophoretic coating: the diffusion of the corrosive medium in the organic coating is mainly determined by the temperature. Due to the existence of certain pores and defects in the organic coating, the diffusion will preferentially proceed along the defects. The organic coating mainly plays a role in hindering the transmission of water in the coating failure. The second process: the diffusion of water in the inorganic micro-arc oxidation coating: when the corrosive medium passes through the organic coating to reach the micro-arc oxidation coating, the corrosive medium will also preferentially diffuse along the pores of the micro-arc oxidation. The third process: corrosion-induced hydrogen evolution causes the coating to crack: the corrosion-induced hydrogen evolution process is jointly affected by two factors, namely 1) the wet adhesion of the coating during immersion will decay with the extension of the service time; 2) the magnesium alloy will produce corrosion holes and induce the generation of hydrogen gas due to its special corrosion property, and the continuous accumulation of hydrogen gas causes the additional stress of the coating to reach and exceed the wet adhesion, and finally the coating cracks and fails.

[0065] It should be noted that the magnesium alloy protective coating can also be a single layer, for example, only containing an inorganic coating. At this time, the failure process of the magnesium alloy protective coating only includes the above-mentioned second process and third process.

[0066] Based on the above processes, a coating water diffusion model, a coating adhesion decay model, and a corrosion-induced hydrogen evolution additional stress increase model are established, and using actual coating parameters and corrosive medium parameters, the life of the magnesium alloy protective coating can be accurately and quickly predicted.

[0067] Referring to FIG. 1, Figure 3 a flowchart of a magnesium alloy protective coating life prediction method provided by an embodiment of the present application is shown, which includes the following steps: Figure 3 S100: Obtain coating parameters and corrosive medium parameters.

[0068] Specifically, the coating parameters include the coating thickness, and specifically include the inorganic coating thickness.

[0069] The corrosive medium parameters include the corrosive medium temperature, the corrosive medium humidity, and the corrosive medium concentration.

[0070]

[0071] ​In the experiment, the corrosion medium is water, and in the actual application, the corrosion medium is air.

[0072] S200: calculating the diffusion time of water in the coating according to the coating parameters and the corrosion medium parameters based on the pre-set coating water diffusion model.

[0073] Specifically, the coating water diffusion model includes an organic coating water diffusion model and an inorganic coating water diffusion model.

[0074] Specifically, step S200 calculates the diffusion time of water in the coating according to the coating parameters and the corrosion medium parameters based on the pre-set coating water diffusion model, including:

[0075] S210: calculating the diffusion time L1 of water in the organic coating according to the corrosion medium parameters based on the organic coating water diffusion model; the organic coating water diffusion model in step S210 is established based on the first process of the failure process of the magnesium alloy protective coating.

[0076] S220: calculating the diffusion time L2 of water in the inorganic coating according to the coating parameters and the corrosion medium parameters based on the inorganic coating water diffusion model; the inorganic coating water diffusion model in step S220 is established based on the second process of the failure process of the magnesium alloy protective coating.

[0077] S230: calculating the diffusion time of water in the coating according to the diffusion time of water in the organic coating and the diffusion time of water in the inorganic coating.

[0078] Specifically, step S210 calculates the diffusion time of water in the organic coating according to the coating parameters and the corrosion medium parameters based on the organic coating water diffusion model, including:

[0079] S211: obtaining the relationship between the water absorption rate of the organic coating and the temperature, and the relationship between the saturated water absorption rate of the organic coating and the temperature;

[0080] S212: calculating the diffusion time of water in the organic coating according to the relationship between the water absorption rate of the organic coating and the temperature, the relationship between the saturated water absorption rate of the organic coating and the temperature, and the corrosion medium parameters.

[0081] Specifically, the relationship between the water absorption rate of the organic coating and the temperature is shown in formula (1-1):

[0082]

[0083] In the formula, η is the water absorption rate of the organic coating, A1 is a function related to the temperature For example, A = 0.018T + 0.085; m1 is a temperature-dependent function m1 = φ(T), for example, m1 = -0.0003T + 0.0541; t1 is the corrosion time of the organic coating; and T is the temperature of the corrosion medium.

[0084] Formula (1-1) can be expressed as formula (1-2):

[0085]

[0086] Specifically, the relationship between the saturated water absorption of the organic coating and the temperature is shown in formula (1-3):

[0087] η s = χ(T) (1-3)

[0088] wherein the value of η s can be obtained by weighing experiments. The diffusion time L1 of moisture in the organic coating can be calculated by the following formula (1-4):

[0089]

[0090] It should be noted that the corrosion time t1 of the organic coating when formula (1-4) is established is the diffusion time L1 of moisture in the organic coating.

[0091] Before step S200 calculates the diffusion time of moisture in the coating based on the pre-set coating moisture diffusion model according to the coating parameters and the corrosion medium parameters, the method further comprises:

[0092] S011: setting a plurality of test temperatures, obtaining the organic coating weight and the saturated weight of the organic coating of the organic coating at each test temperature;

[0093] S012: determining a reference temperature and an organic coating reference weight of the organic coating at the reference temperature, and determining the organic coating weight change amount and the saturated weight change amount of the organic coating of the organic coating at each test temperature according to the organic coating weight, the saturated weight of the organic coating and the organic coating reference weight;

[0094] S013: obtaining the relationship between the water absorption of the organic coating and the temperature and the relationship between the saturated water absorption of the organic coating and the temperature according to the organic coating weight change amount and the saturated weight change amount of the organic coating;

[0095] S014: establishing the moisture diffusion model of the organic coating according to the relationship between the water absorption of the organic coating and the temperature and the relationship between the saturated water absorption of the organic coating and the temperature.

[0096] Specifically, the organic coating weight and the organic coating saturation weight of the organic coating at different test temperatures are tested by using the soaking method, the organic coating reference weight of the organic coating at the reference temperature is determined, the organic coating weight change amount and the organic coating saturation weight change amount of the organic coating at each test temperature are determined, and the general formula for corrosion weight gain is used to fit the above data to obtain formula (1-2).

[0097] Specifically, step S220 calculates the diffusion time of water in the inorganic coating based on the inorganic coating water diffusion model according to the coating parameters and the corrosion medium parameters, including:

[0098] S221: obtaining the relationship between the diffusion coefficient of water in the inorganic coating and the temperature;

[0099] S222: determining the relationship between the diffusion distance of water in the inorganic coating and the complete diffusion time of water in the inorganic coating according to the relationship between the diffusion coefficient of water in the inorganic coating and the temperature;

[0100] S223: calculating the diffusion time of water in the inorganic coating according to the relationship between the diffusion distance of water in the inorganic coating and the complete diffusion time of water in the inorganic coating, and the coating parameters and the corrosion medium parameters.

[0101] Specifically, the relationship between the diffusion coefficient of water in the inorganic coating and the temperature is shown in formula (1-5):

[0102]

[0103] In the formula: D is the diffusion coefficient of water in the inorganic coating; D0 is the diffusion pre-coefficient, which is generally a function related to the corrosion medium concentration D0=F2(C); E a1 is the diffusion activation energy, which is generally a function related to the corrosion medium concentration E a1 =F1(C); R is the ideal gas constant; T is the corrosion medium temperature.

[0104] Specifically, the relationship between the diffusion distance of water in the inorganic coating and the complete diffusion time of water in the inorganic coating is shown in formula (1-6):

[0105] d 2 =D×t2 (1-6)

[0106] In the formula: d is the thickness of the inorganic coating, i.e. the diffusion distance of water in the inorganic coating; D is the diffusion coefficient of water in the inorganic coating; t2 is the complete diffusion time of water in the inorganic coating.

[0107] According to formula (1-6), the diffusion time L2 of water in the inorganic coating can be calculated:

[0108]

[0109] The complete diffusion time t2 of moisture in the inorganic coating is the same as the diffusion time L2(d,T,C) of moisture in the inorganic coating.

[0110] Before step S200, which calculates the diffusion time of moisture in the coating based on a pre-set coating moisture diffusion model and according to the coating parameters and the corrosive medium parameters, the method further includes:

[0111] S021: Set multiple test times and obtain the coating impedance spectrum at each test time;

[0112] S022: Calculate the polarization resistance at each test time based on the coating impedance spectrum at each test time;

[0113] S023: Determine the complete diffusion time of moisture in the inorganic coating based on the polarization resistance at multiple test times;

[0114] S024: Based on the complete diffusion time of moisture in the inorganic coating and the thickness of the inorganic coating, determine the diffusion coefficient of moisture in the inorganic coating and the relationship between the diffusion distance of moisture in the inorganic coating and the complete diffusion time of moisture in the inorganic coating.

[0115] S025: Determine the relationship between the diffusion coefficient of moisture in inorganic coatings and temperature based on the diffusion coefficient of moisture in inorganic coatings;

[0116] S026: Based on the relationship between the diffusion distance of moisture in the inorganic coating and the complete diffusion time of moisture in the inorganic coating, and the relationship between the diffusion coefficient of moisture in the inorganic coating and temperature, a moisture diffusion model for the inorganic coating is established.

[0117] Specifically, in one particular embodiment, the determination of the complete diffusion time of moisture in the inorganic coating is as follows: Figure 4 As shown, the diffusion kinetics of corrosive electrolytes in inorganic coatings are determined based on electrochemical impedance measurements. Figure 4 The 'a' in the text indicates a certain temperature and a certain Cl. - Electrochemical impedance spectroscopy was performed at a certain concentration and for a specific immersion time. The experimental results are as follows: Figure 4 Examples of impedance spectra (a) and (b) are shown. Fitting is performed according to a suitable equivalent circuit diagram, and the polarization resistance R at this test time is calculated. p The R values ​​obtained at different test times p By creating the image, you can obtain Figure 4 The result shown in c is the polarization resistance (R). p Typical changes with immersion time. Figure 4The double logarithmic transformation of the coordinate axis of the middle c can obviously distinguish R p The falling stage and the stable stage, the linear fitting of the two stages obtains the tangent, and the intersection of the two tangents is determined as the complete diffusion time of the water in the inorganic coating under the condition, such as Figure 4 The diffusion coefficient of the water in the inorganic coating is calculated according to formula (1-6) according to the determined complete diffusion time of the water in the inorganic coating, and the pre-diffusion coefficient and the diffusion activation energy are calculated according to formula (1-5), and the formula (1-5) and formula (1-6) suitable for the water diffusion model in the inorganic coating are determined.

[0118] S300: Based on the pre-set coating adhesion decay model and the corrosion hydrogen-induced additional stress increase model, the coating failure time is determined according to the coating parameters and the corrosion medium parameters.

[0119] Specifically, according to the third process of the composite coating failure process, based on 1) the wet adhesion of the coating will decay with the extension of the service time during the immersion process, the coating adhesion decay model is established; Based on 2) the magnesium alloy will produce corrosion holes and induce hydrogen production during the corrosion process due to its special corrosion, and the continuous accumulation of hydrogen leads to that the additional stress of the coating reaches and exceeds the wet adhesion, the corrosion hydrogen-induced additional stress increase model is established.

[0120] Specifically, step S300: Based on the pre-set coating adhesion decay model and the corrosion hydrogen-induced additional stress increase model, the coating failure time is determined according to the coating parameters and the corrosion medium parameters, including:

[0121] S310: Obtain the hydrogen parameter, the magnesium alloy parameter, the composite relationship of adhesion and temperature and time, and obtain the composite relationship of corrosion hydrogen-induced internal stress and temperature and time;

[0122] S320: According to the composite relationship of adhesion and temperature and time and the corrosion medium parameters, the wet adhesion of the coating is calculated and obtained;

[0123] S330: According to the composite relationship of corrosion hydrogen-induced internal stress and temperature and time, the hydrogen parameter, the magnesium alloy parameter and the corrosion medium parameter, the corrosion hydrogen-induced additional stress is calculated and obtained;

[0124] S340: According to the wet adhesion of the coating and the corrosion hydrogen-induced additional stress, the coating failure time is determined.

[0125] It can be understood that the hydrogen parameter and the magnesium alloy parameter can be pre-set.

[0126] Specifically, the composite relationship of adhesion and temperature and time is shown in formula (1-8):

[0127]

[0128] In the formula: F1 is the adhesion force; ζ(T) is a function related to the corrosion temperature; ξ(T) is a function related to the corrosion temperature; t3 is the adhesion force change time; r0 is the indenter radius of the adhesion device.

[0129] Specifically, the combined relationship between corrosion-induced hydrogen evolution internal stress and temperature and time is shown in equation (1-9):

[0130]

[0131] In the formula: F2 is the internal stress induced by hydrogen evolution due to corrosion; ρ is the density; M Mg M is the molar mass of Mg; H2 Let be the molar mass of the hydrogen gas produced; R be the ideal gas constant; T be the temperature of the corrosive medium; and n be the amount of dissolved substance in the magnesium alloy. Based on the principles of corrosion electrochemistry, the amount of hydrogen gas can also be assumed to satisfy the following formula:

[0132]

[0133]

[0134] In the formula: Q is the amount of hydrogen evolution (L); Q0 is the pre-exponential coefficient of hydrogen evolution; C is the concentration of the corrosive medium; T is the temperature of the corrosive medium. E a2 t'3 is the hydrogen evolution activation energy, t'3 is a constant; t'3 is the hydrogen evolution time.

[0135] The time when the adhesion force F1 equals the internal stress F2 induced by hydrogen evolution from corrosion is the coating failure time L3.

[0136] Before determining the coating failure time in step S300 based on the pre-set coating adhesion attenuation model and corrosion hydrogen evolution induced additional stress increase model, according to the coating parameters and the corrosive medium parameters, the method includes:

[0137] S031: Set multiple test times and test temperatures, and use the acoustic emission scratch method to obtain the wet adhesion of multiple coatings;

[0138] S032: Based on the wet adhesion of multiple coatings, obtain the composite relationship between adhesion, temperature, and time;

[0139] S033: The pressure generated by hydrogen is obtained using the ideal gas law, and the pit opening area is obtained using the law of conservation of dissolved magnesium mass.

[0140] S034: Based on the pressure generated by hydrogen and the pit opening area of ​​the corrosion pit, obtain the composite relationship between the internal stress induced by hydrogen evolution due to corrosion and temperature and time.

[0141] S035: Establishing a coating adhesion decay model according to the combined relationship of adhesion with temperature and time;

[0142] S036: Establishing a corrosion hydrogen-induced additional stress increase model according to the combined relationship of corrosion hydrogen-induced internal stress with temperature and time.

[0143] Specifically, in combination with Figure 5 and Figure 6 , in the process of establishing the coating adhesion decay model, the coating adhesion change trend can be tested by preparing a corrosion solution and adjusting different test temperatures, and using acoustic emission scratch method at different test times. The general formula of adhesion decay σ = Ke bt is used for fitting, and the adhesion pre-exponential factor K and the adhesion exponential factor b under different test temperatures are obtained, and the temperature is taken as the variable for fitting: K = ζ(T), b = ξ(T). Finally, the trend of wet bonding strength changing with time is obtained:

[0144]

[0145] Considering that the acoustic emission scratch method tests the adhesion with a half-round indenter radius r0 = 200 μm, the wet bonding strength can be converted to adhesion by the following formula:

[0146] F1 = σ × πr0 2 (1-14)

[0147] According to formula (1-13) and formula (1-14), formula (1-8) can be obtained.

[0148] In the process of establishing the corrosion hydrogen-induced additional stress increase model, the basic process can be simplified as follows: when the corrosion medium reaches the surface of the magnesium alloy, an electrochemical reaction occurs. The anodic reaction corresponds to the dissolution of Mg and other alloy elements, producing hemispherical corrosion pits; the cathodic reaction is the hydrogen evolution reaction, and the hydrogen gas produced cannot overflow under the blocking action of the coating, resulting in additional stress (such as Figure 5 ) inside the coating. Therefore, the corrosion hydrogen-induced additional stress increase model can use the ideal gas state equation to obtain the pressure

[0149]

[0150] where V p is the volume of the corrosion pit, which can be solved by using the mass conservation law of magnesium dissolution:

[0151]

[0152] The above two formulas can be obtained by combining:

[0153]

[0154] The volume of the hemispherical corrosion pit can also be solved by using the volume formula:

[0155]

[0156] Therefore, the radius of the corrosion pit is:

[0157]

[0158] The pit opening area of the corrosion pit is:

[0159]

[0160] Therefore, the final expression of the internal stress induced by corrosion and hydrogen evolution is:

[0161]

[0162] The above formulas can be combined to obtain formula (1-9).

[0163] The relationship between the amount of hydrogen evolution Q and the immersion test time can be obtained by hydrogen evolution test experiment. The general formula for corrosion weight gain is used By fitting the curves of the amount of hydrogen evolution with time under different concentrations of corrosion medium, A2 and m2 under different concentrations can be obtained, and then the trend of A2 and m2 with concentration can be mathematically fitted: A2 = f(C), The relationship between the amount of hydrogen evolution and time can be obtained, and formula (1-10) is obtained.

[0164] On this basis, the Arrhenius formula By extrapolating the above formula, the amount of hydrogen evolution at any test temperature can be obtained, and formula (1-11) is obtained.

[0165] S400: calculating the predicted service life of the coating according to the diffusion time of the moisture in the coating and the failure time of the coating.

[0166] Since the inorganic coating moisture diffusion model, the organic coating moisture diffusion model, the coating adhesion decay model and the additional stress increase model induced by corrosion and hydrogen evolution are obtained by immersion experiment, but in fact, the magnesium alloy samples after coating are all served in an atmospheric environment with a certain relative humidity and a certain corrosion medium concentration, so it is necessary to convert the laboratory environment to the atmospheric environment.

[0167] Specifically, step S400 calculates the predicted service life of the coating according to the diffusion time of the moisture in the coating and the failure time of the coating, including:

[0168] S410: Calculate the theoretical lifespan of the coating based on the diffusion time of the moisture in the coating and the coating failure time;

[0169] S420: Determine the theoretical parameters and actual parameters of the corrosive medium, and calculate the conversion factor based on the theoretical parameters and actual parameters of the corrosive medium;

[0170] S430: Calculate the predicted life of the coating based on the theoretical life of the coating and the conversion factor.

[0171] Specifically, in step S410, when calculating the theoretical lifetime of the coating, the theoretical lifetime of a single coating (containing only the inorganic coating - micro-arc oxidation layer) is determined by formula (1-22):

[0172] L'=L2+γ1L3 (1-22)

[0173] The theoretical lifespan of the composite coating is determined by formula (1-23):

[0174] L'=L1+γ2(L2+L3) (1-23)

[0175] Wherein, coefficient γ1 is the interface corrosion reduction factor for a single coating, which is generally taken as 100. Coefficient γ2 is the superposition effect factor of the organic and inorganic coatings in the composite coating, and its value is equal to the reciprocal of the saturated water absorption rate of the organic coating.

[0176] Specifically, the process for determining the conversion factor in step S420 is as follows:

[0177] To achieve the conversion between laboratory environment and atmospheric environment, a simplified BET multilayer adsorption formula is adopted:

[0178]

[0179]

[0180] Where θ is the amount of water molecules adsorbed; RH is the relative humidity; E1, E n Let be the adsorption energy of water molecules in the 1st and nth layers. If we assume that the adsorption energies of water molecules from the 1st to the nth layer are all the same, then we have:

[0181]

[0182] Then there is a conversion factor:

[0183]

[0184] Where θ1 is the amount of water molecules adsorbed in the atmospheric environment; RH1 is the humidity in the atmospheric environment; θ2 is the amount of water molecules adsorbed in the laboratory environment; and RH2 is the humidity in the laboratory environment.

[0185] Specifically, the coating life prediction in step S430 is

[0186] L = a-L' (1-28)

[0187] The conversion method has been verified by testing the water film formation time of the electrode surface of the laminated electrode under different temperature and humidity conditions (as shown in Figure 7 The basic principle is that if a water film is formed between the regions of the laminated electrode, the surface resistance between adjacent electrodes will drop sharply, and this time corresponds to the water film formation time under the temperature and humidity conditions. Figure 7 B1 is the test end; B2 is the standby test end; and B0 is the contact resistance signal input end.

[0188] Further, specifically, the step S400 of calculating the coating life prediction according to the diffusion time of the moisture in the coating and the coating failure time further comprises:

[0189] Obtaining the relationship between the actual area of the coating, the actual area and the basic area;

[0190] According to the actual area of the coating, the relationship between the actual area and the basic area, the theoretical life of the coating and the conversion coefficient, the coating life prediction is calculated.

[0191] Specifically, the relationship between the actual area and the basic area is shown in formula (1-29):

[0192]

[0193] Where A0 is the basic area; A is the actual area; t0 is a constant; and u is a coefficient related to the basic area, the actual area, the theoretical life of the coating and the conversion coefficient, which can be directly obtained by experimental data fitting.

[0194] The determination process of the relationship between the actual area and the basic area is as follows:

[0195] Considering that the overall life of the coating depends not only on the properties of the coating itself, but also on the surface area of the coating, the Weibull probability distribution is used to realize the conversion of area and life in this embodiment. The probability function of Weibull distribution is:

[0196]

[0197] Where u and t0 are both constants; and t' is the life of a large-area component. By transforming the above formula, we can obtain:

[0198]

[0199] Where Weibull operator. It can be seen that the Weibull operator is linearly related to the failure time lnt'. From the perspective of mathematical model, a large-area component can be equivalently divided into multiple small-area components. That is, the failure life of a large-area component can be regarded as the failure life of a small-area component under a small probability. In this embodiment, 20 sets of experimental samples are provided, and the area of the experimental samples is the basic area A0. The area of the large-area component is the actual area A, and the equivalent small-probability failure probability of the actual area is F(t') = A0 / A. At this time, the Weibull distribution function is formula (1-29). At this time, the coating life of different areas can be converted according to linear interpolation. Figure 8 Weibull distribution function of a single coating (only inorganic coating - micro-arc oxidation layer) and Weibull distribution function of a composite coating (micro-arc oxidation layer + electrophoretic paint coating).

[0200] Further, in one embodiment, as shown in Figure 9 Magnesium alloy structural components often need to be connected with a large number of steel / titanium alloy / aluminum alloy fasteners, which can cause serious galvanic corrosion and accelerate the failure process of the coating. At this time, the above-mentioned model needs to be modified, and the relationship curve between the amount of hydrogen evolution Q and time needs to be re-measured and determined in the modified corrosion hydrogen evolution induced additional stress increase model. The fitting formula of the amount of hydrogen evolution Q is as follows:

[0201]

[0202] Further, in one embodiment, magnesium alloy structural components often face complex structural stresses. For a composite coating, the micro-arc oxidation coating contains a large amount of ceramic phase and is therefore more brittle, which can easily produce cracks under the action of structural stress, thereby changing the transmission dynamics of moisture in the inorganic coating and the decay dynamics of the wet adhesion of the coating. Therefore, the influence of micro-creep on the coating life needs to be simulated. A four-point bending micro-creep loader (such as Figure 10 ) with a load of 10Mpa is used to load the micro-arc oxidation coating or composite coating magnesium alloy component with a size of 100mm*10mm*5mm for 24 hours. According to the experimental results, the inorganic coating moisture diffusion model and the coating adhesion decay model are modified to obtain the modified inorganic coating moisture diffusion model and the modified coating adhesion decay model. Figure 10 In the formula, H1 is the thickness of the sample, H2 is the span of the outer two points, H3 is the distance between the adjacent two points, and H4 is the deflection displacement of the sample.

[0203] It can be seen that, in the above scheme, based on the in-depth understanding of the corrosion process of the magnesium alloy and the full understanding of the organization and performance evolution law of the coating failure process, the coating water diffusion model, the coating adhesion decay model and the corrosion hydrogen evolution induced additional stress increase model are provided. The actual coating parameters and the corrosion medium parameters can be used to accurately and quickly predict the service life of the magnesium alloy protective coating.

[0204] It should be understood that the size of the serial number of each step in the above embodiment does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0205] In an embodiment, a magnesium alloy protective coating service life prediction device is provided, which corresponds to the magnesium alloy protective coating service life prediction method in the above embodiment. As shown in the figure, the magnesium alloy protective coating service life prediction device includes an acquisition module 101, a diffusion calculation module 102, a failure calculation module 103 and a service life prediction module 104. The functions of each module are described in detail as follows: Figure 11

[0206] The acquisition module 101 is configured to acquire coating parameters and corrosion medium parameters.

[0207] The diffusion calculation module 102 is configured to calculate the diffusion time of water in the coating based on the pre-set coating water diffusion model according to the coating parameters and the corrosion medium parameters.

[0208] The failure calculation module 103 is configured to determine the coating failure time based on the pre-set coating adhesion decay model and the corrosion hydrogen evolution induced additional stress increase model according to the coating parameters and the corrosion medium parameters.

[0209] The service life prediction module 104 is configured to calculate the coating predicted service life according to the diffusion time of water in the coating and the coating failure time.

[0210] Specifically, the acquisition module 101 is configured to acquire the coating thickness, the corrosion medium temperature, the corrosion medium humidity and the corrosion medium concentration.

[0211] Specifically, the diffusion calculation module 102 is further configured to,

[0212] calculate the diffusion time of water in the organic coating based on the corrosion medium parameters according to the organic coating water diffusion model;

[0213] calculate the diffusion time of water in the inorganic coating based on the coating parameters and the corrosion medium parameters according to the inorganic coating water diffusion model;

[0214] ​According to the diffusion time of the moisture in the organic coating and the diffusion time of the moisture in the inorganic coating, the diffusion time of the moisture in the coating is calculated.

[0215] Specifically, the diffusion calculation module 102 is further configured to,

[0216] obtain the relationship between the water absorption rate of the organic coating and temperature, and the relationship between the saturated water absorption rate of the organic coating and temperature;

[0217] According to the relationship between the water absorption rate of the organic coating and temperature, and the relationship between the saturated water absorption rate of the organic coating and temperature, and the corrosion medium parameters, the diffusion time of the moisture in the organic coating is calculated.

[0218] Specifically, refer to formulas (1-1) to (1-4).

[0219] Specifically, the diffusion calculation module 102 further includes a modified version of the inorganic coating moisture diffusion model and different coefficients in the inorganic coating moisture diffusion model.

[0220] Specifically, the diffusion calculation module 102 is further configured to,

[0221] obtain the relationship between the diffusion coefficient of the moisture in the inorganic coating and temperature;

[0222] According to the relationship between the diffusion coefficient of the moisture in the inorganic coating and temperature, the relationship between the diffusion distance of the moisture in the inorganic coating and the complete diffusion time of the moisture in the inorganic coating is determined;

[0223] According to the relationship between the diffusion distance of the moisture in the inorganic coating and the complete diffusion time of the moisture in the inorganic coating, and the coating parameters and the corrosion medium parameters, the diffusion time of the moisture in the inorganic coating is calculated.

[0224] Specifically, refer to formulas (1-5) to (1-7).

[0225] Specifically, the failure calculation module 103 is further configured to:

[0226] obtain the hydrogen parameters, the magnesium alloy parameters, the combined relationship of adhesion and temperature and time, and the combined relationship of corrosion-induced internal stress and temperature and time;

[0227] According to the combined relationship of adhesion and temperature and time and the corrosion medium parameters, the wet-state adhesion of the coating is calculated.

[0228] According to the combined relationship of corrosion-induced internal stress and temperature and time, the hydrogen parameters, the magnesium alloy parameters and the corrosion medium parameters, the corrosion-induced additional stress is calculated.

[0229] According to the wet adhesion of the coating and the additional stress induced by corrosion hydrogen evolution, the coating failure time is determined.

[0230] Specifically, refer to formula (1-8) to formula (1-12).

[0231] Specifically, the failure calculation module 103 also contains a modified version of the additional stress induced by corrosion hydrogen evolution increase model, and the hydrogen evolution amount Q calculation formula in the modified version of the additional stress induced by corrosion hydrogen evolution increase model and the additional stress induced by corrosion hydrogen evolution increase model is different.

[0232] Specifically, the failure calculation module 103 also contains a modified version of the coating adhesion decay model, and the coefficients in the modified version of the coating adhesion decay model and the coating adhesion decay model are different.

[0233] Specifically, the life prediction module 104 is also used for:

[0234] According to the diffusion time of the moisture in the coating and the coating failure time, the coating theoretical life is calculated;

[0235] The corrosion medium theoretical parameters and the corrosion medium actual parameters are determined, and the conversion coefficient is calculated according to the corrosion medium theoretical parameters and the corrosion medium actual parameters;

[0236] According to the coating theoretical life and the conversion coefficient, the coating predicted life is calculated.

[0237] Specifically, refer to formula (1-22) to formula (1-28).

[0238] Specifically, the life prediction module 104 is also used for:

[0239] The actual area of the coating, the relationship between the actual area and the basic area are obtained;

[0240] According to the actual area of the coating, the relationship between the actual area and the basic area, the coating theoretical life and the conversion coefficient, the coating predicted life is calculated.

[0241] Specifically, refer to formula (1-29).

[0242] The application provides a magnesium alloy protective coating life prediction device, based on the in-depth understanding of the magnesium alloy corrosion process and the sufficient understanding of the organization and performance evolution law of the coating failure process, the coating moisture diffusion model, the coating adhesion decay model and the additional stress induced by corrosion hydrogen evolution increase model are provided, using the actual coating parameters and the corrosion medium parameters, the life of the magnesium alloy protective coating can be accurately and quickly predicted.

[0243] The specific limitations of the magnesium alloy protective coating service life prediction device can refer to the limitations of the magnesium alloy protective coating service life prediction method described above, which will not be repeated here. Each module in the magnesium alloy protective coating service life prediction device described above can be realized by software, hardware and their combination in whole or in part. The above-mentioned modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in software form, so as to call and execute the operations corresponding to the above-mentioned modules by the processor.

[0244] Further, an example of magnesium alloy micro-arc oxidation coating sample service life prediction:

[0245] The single-coating service life prediction of the micro-arc oxidation coating sample with a thickness of 25 μm in the atmosphere environment of temperature 25℃, humidity 60%, Cl - Concentration 110 ppm is carried out by calling the inorganic coating moisture diffusion model, coating adhesion force attenuation model and corrosion hydrogen evolution induced additional stress increase model for calculation:

[0246] In the calculation of the diffusion time L2 of moisture in the inorganic coating:

[0247] The formula (1-7) is:

[0248]

[0249] The calculation can obtain L2=40h;

[0250] In the determination of the coating failure time L3:

[0251] The formula (1-8) is:

[0252] ζ(T)=24.53-0.13(T-20);

[0253] ξ(T)=[-4.5+0.005(T-20)]×10 -3 ;

[0254] r0=200 μm;

[0255]

[0256] The formula (1-9) is:

[0257] M Mg =24 g / mol;

[0258] M H2 =2 g / mol;

[0259] ρ H2 =0.084×10 -3 g / m 3 ;

[0260] p Mg = 1.74 g / cm 3 ;

[0261]

[0262] f(C) = e -0.00302C-3.48 ;

[0263]

[0264] E a2 = 0.59C 2 - 108.28C + 7093.3;

[0265]

[0266] When F1 = F2, L3 = 7.61h can be obtained;

[0267] In the calculation of the conversion coefficient:

[0268] Equation (1-27):

[0269]

[0270] Therefore, the single-coat predicted life in this example is L = a(L2 + γL3) = 6.03 years

[0271] Further, an example of a magnesium alloy composite coating sample under micro-creep conditions is given:

[0272] A 25 μm thick composite coating sample is under the action of 10 MPa micro-creep (such as Figure 10 ), and under the load of coating life prediction in the atmospheric environment of temperature 25℃, humidity 60%, Cl - concentration 110 ppm. The organic coating moisture diffusion model, the modified inorganic coating moisture diffusion model, the modified coating adhesion decay model and the corrosion hydrogen evolution induced additional stress increase model are called to calculate:

[0273] In the calculation of the diffusion time L1 of moisture in the organic coating:

[0274] Equation (1-2) is:

[0275] η = (0.018T + 0.085) t1 (-0.0003T+0.0541)

[0276] Equation (1-3) is η s = 0.03T = 0.75%,

[0277] L1 = t1 = 1407 h according to equation (1-4);

[0278] In calculating the diffusion time of water in the inorganic coating L2:

[0279] Equation (1-7) is: E a1 = F1(C) = 14428 - 155C; D0= 3.4 x 10 -14 ; d = 25 μm;

[0280] L2 = 13.5 h can be calculated;

[0281] In determining the coating failure time L3:

[0282] Equation (1-8) is:

[0283] ζ(T) = 79.33 + 0.58T;

[0284] ξ(T) = -(2.30 + 0.243T) x 10 -4 ;

[0285] r0= 200 μm;

[0286]

[0287] Equation (1-9) is:

[0288] M Mg = 24 g / mol;

[0289] M H2 = 2 g / mol;

[0290] ρ H2 = 0.084 x 10 -3 g / m 3 ;

[0291] ρ Mg = 1.74 g / cm 3 ;

[0292]

[0293] f(C) = e -0.00302C-3.48 ;

[0294]

[0295] E a2 = 0.59C 2 - 108.28C + 7093.3;

[0296]

[0297] When F1=F2, L3=7.61h can be obtained;

[0298] In the calculation of the conversion coefficient:

[0299] Formula (1-27):

[0300] RH1=60%, RH2=99%,

[0301] Therefore, the predicted life of the composite coating under the micro-creep condition is:

[0302] L=α[L1+γ(L2+L3)]=31.81 years

[0303] Further, an example of a magnesium alloy composite coating sample under the condition of micro-creep plus dissimilar metal connection life prediction:

[0304] The thickness of the 25μm composite coating sample is placed at the aluminum nail / aluminum plate (structure as Figure 9 ), and the coating life prediction under the load of the atmosphere environment at temperature 25℃, humidity 60%, Cl - Concentration 110ppm. The organic coating moisture diffusion model, the modified inorganic coating moisture diffusion model, the modified coating adhesion decay model and the modified corrosion hydrogen evolution induced additional stress increase model are called for calculation:

[0305] In the calculation of the diffusion time L1 of moisture in the organic coating:

[0306] Formula (1-2) is:

[0307] η=(0.018T+0.085)t1 (-0.0003T+0.0541)

[0308] Formula (1-3) is η s =0.03T=0.75%,

[0309] According to formula (1-4), L1=t1=1407h can be calculated;

[0310] In the calculation of the diffusion time L2 of moisture in the inorganic coating:

[0311] Formula (1-7) is: E a1 =F1(C)=14428-155C; D0=3.4×10 -14 ; d=25μm;

[0312] L2=13.5h can be calculated;

[0313] In the determination of the coating failure time L3:

[0314] Equation (1-8) is:

[0315] ζ(T) = 79.33 + 0.58T;

[0316] ξ(T) = -(2.30 + 0.243T) x 10 -4 ;

[0317] r0= 200 μm;

[0318]

[0319] Equation (1-9) is:

[0320] M Mg = 24 g / mol;

[0321] M H2 = 2 g / mol;

[0322] ρ H2 = 0.084 x 10 -3 g / m 3 ;

[0323] ρ Mg = 1.74 g / cm 3 ;

[0324]

[0325] f(C) = e -0.00302C-3.48 ;

[0326]

[0327] E a2 = 0.59C 2 - 108.28C + 7093.3;

[0328] Q = e -0.00302C-3.48 t'3 0.41+0.00207C

[0329] When F1 = F2, L3 = 1.51 h can be obtained;

[0330] In calculating the conversion factor:

[0331] Equation (1-27):

[0332] RH1 = 60%, RH2 = 99%,

[0333] Therefore, the predicted life of the composite coating under the condition of dissimilar metal connection is:

[0334] L = a [L1 + γ (L2 + L3)] = 25.77 years

[0335] Further, a magnesium alloy composite coated member having a surface area of 2m 2 is exemplified in the life prediction under the condition of micro-creep plus dissimilar metal joining:

[0336] A composite coated sample having a thickness of 25 μm is subjected to micro-creep at 10 MPa (as in Figure 10 ), and the coated life is predicted under the load in an atmosphere having a temperature of 25°C, a humidity of 60%, and a Cl - concentration of 110 ppm. The calculation is performed using an organic coating moisture diffusion model, a modified inorganic coating moisture diffusion model, a modified coating adhesion force decay model, and a modified corrosion hydrogen evolution induced additional stress increase model:

[0337] In calculating the diffusion time L1 of moisture in the organic coating:

[0338] Equation (1-2) is:

[0339] η = (0.018T + 0.085) t1 (-0.0003T+0.0541)

[0340] Equation (1-3) is η s = 0.03T = 0.75%,

[0341] Calculation according to Equation (1-4) gives L1 = t1 = 1407 h;

[0342] In calculating the diffusion time L2 of moisture in the inorganic coating:

[0343] Equation (1-7) is:

[0344] E a1 = F1(C) = 14428 - 155C; D0= 3.4 x 10 -14 ; d = 25 μm;

[0345] Calculation gives L2 = 13.5 h;

[0346] In determining the coating failure time L3:

[0347] Equation (1-8) is:

[0348] ζ(T) = 79.33 + 0.58T;

[0349] ξ(T) = -(2.30 + 0.243T) x 10 -4 ;

[0350] r0= 200 μm;

[0351]

[0352] Formula (1-9) is:

[0353] M Mg =24 g / mol;

[0354] M H2 =2g / mol;

[0355] ρ H2 =0.084×10 -3 g / m 3 ;

[0356] ρ Mg =1.74g / cm 3 ;

[0357]

[0358] f(C) = e -0.00302C-3.48 ;

[0359]

[0360] E a2 =0.59C 2 -108.28°C +7093.3°C;

[0361] Q = e -0.00302C-3 . 48 t'3 0.41+0.00207C

[0362] When F1 = F2, we can obtain L3 = 1.51h;

[0363] When calculating the conversion factor:

[0364] Formula (1-27):

[0365] RH1 = 60%, RH2 = 99%,

[0366] Therefore, the predicted lifespan at this time is:

[0367] L=α[L1+γ(L2+L3)]=25.77 years

[0368] The Weibull distribution curve of this sample, determined using 20 parallel samples, is as follows: Figure 8 As shown:

[0369] The Weibull distribution relationship of the composite coating corresponding to formula (1-31) can be obtained as follows:

[0370] u = 7.98; ulnt0 = 75.76;

[0371]

[0372] Therefore, for 2m 2 The predicted life of the composite coating of the component, after correction, is t' = 9.03 years.

[0373] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 12 As shown. The computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides the necessary operating medium for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used for communication with external devices via a network connection. When executed by the processor, the computer program implements the functions or steps of a magnesium alloy protective coating life prediction method on the server side.

[0374] In one embodiment, a computer device is provided, which may be a device terminal, and its internal structure diagram may be as follows: Figure 13 As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides the necessary operating medium for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with an external server via a network connection. When executed by the processor, the computer program implements the functions or steps of a magnesium alloy protective coating life prediction method on the device side.

[0375] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps:

[0376] Obtain coating parameters and corrosive medium parameters;

[0377] Based on a pre-set coating moisture diffusion model, the diffusion time of moisture in the coating is calculated according to the coating parameters and the corrosive medium parameters.

[0378] determining a coating failure time according to the coating parameters and the corrosion medium parameters based on a preset coating adhesion force attenuation model and a corrosion hydrogen evolution induced additional stress increase model;

[0379] calculating a coating predicted life according to the water diffusion time in the coating and the coating failure time.

[0380] In one embodiment, a computer readable storage medium is provided, and a computer program is stored on the computer readable storage medium, and the computer program is executed by a processor to implement the following steps:

[0381] obtaining coating parameters and corrosion medium parameters;

[0382] calculating a water diffusion time in the coating according to the coating parameters and the corrosion medium parameters based on a preset coating water diffusion model;

[0383] determining a coating failure time according to the coating parameters and the corrosion medium parameters based on a preset coating adhesion force attenuation model and a corrosion hydrogen evolution induced additional stress increase model;

[0384] calculating a coating predicted life according to the water diffusion time in the coating and the coating failure time.

[0385] It should be noted that the functions or steps that the computer readable storage medium or the computer device can implement above can be referred to the related descriptions of the server side and the device side in the foregoing method embodiments, and for the sake of avoiding repetition, they will not be described one by one here.

[0386] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when executed, can include the processes of the above-mentioned embodiment methods. Any reference to memory, storage, database or other medium used in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0387] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is exemplified, and in actual application, the above-mentioned functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

[0388] The above-mentioned embodiments are only used to illustrate the technical solutions of the present application, but not limit it. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features. The modification or replacement does not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method for lifetime prediction of a protective coating of a magnesium alloy, characterized in that, The method comprises the following steps: acquiring coating parameters and corrosion medium parameters; calculating the diffusion time of moisture in the coating according to the coating parameters and the corrosion medium parameters based on a pre-set moisture diffusion model of the coating; determining the coating failure time according to the coating parameters and the corrosion medium parameters based on a pre-set coating adhesion decay model and a pre-set additional stress increase model induced by corrosion hydrogen evolution; calculating the coating predicted life according to the diffusion time of moisture in the coating and the coating failure time; the step of calculating the coating predicted life according to the diffusion time of moisture in the coating and the coating failure time comprises the following steps: calculating the coating theoretical life according to the diffusion time of moisture in the coating and the coating failure time; wherein, when the coating is a single coating, the diffusion time of moisture in the coating is the diffusion time of moisture in the inorganic coating, the coating failure time is the time when the adhesion is equal to the internal stress induced by corrosion hydrogen evolution, and the coating theoretical life L' is determined by the following formula: L' = L2 + γ1L3 in the formula, L2 is the diffusion time of moisture in the inorganic coating; L3 is the coating failure time; γ1 is the interface corrosion deceleration factor when the coating is a single coating; when the coating is a composite coating, the diffusion time of moisture in the coating is the diffusion time of moisture in the inorganic coating and the diffusion time of moisture in the organic coating, and the coating failure time is the time when the adhesion is equal to the internal stress induced by corrosion hydrogen evolution; the coating theoretical life L' is determined by the following formula: L' = L1 + γ2(L2 + L3) in the formula, L1 is the diffusion time of moisture in the organic coating; L2 is the diffusion time of moisture in the inorganic coating; L3 is the coating failure time; γ2 is the superposition effect factor of the organic coating and the inorganic coating after being combined in the composite coating; determining the corrosion medium theoretical parameters and the corrosion medium actual parameters, and calculating the conversion coefficient according to the corrosion medium theoretical parameters and the corrosion medium actual parameters; calculating the coating predicted life according to the coating theoretical life and the conversion coefficient.

2. The magnesium alloy protective coating life prediction method according to claim 1, wherein the coating parameters comprise coating thickness; the corrosion medium parameters comprise corrosion medium temperature, corrosion medium humidity and corrosion medium concentration.

3. The magnesium alloy protective coating life prediction method according to claim 1, wherein the coating moisture diffusion model comprises an organic coating moisture diffusion model and an inorganic coating moisture diffusion model; the step of calculating the diffusion time of moisture in the coating according to the coating parameters and the corrosion medium parameters based on the pre-set coating moisture diffusion model comprises the following steps: calculating the diffusion time of moisture in the organic coating according to the corrosion medium parameters based on the organic coating moisture diffusion model; calculating the diffusion time of moisture in the inorganic coating according to the coating parameters and the corrosion medium parameters based on the inorganic coating moisture diffusion model; calculating the diffusion time of moisture in the coating according to the diffusion time of moisture in the organic coating and the diffusion time of moisture in the inorganic coating.

4. The method of claim 3, wherein the calculating the diffusion time of water in the organic coating based on the water diffusion model of the organic coating and the coating parameters and the corrosion medium parameters comprises: obtaining a relationship between water absorption of the organic coating and temperature, and a relationship between saturated water absorption of the organic coating and temperature; and calculating the diffusion time of water in the organic coating based on the relationship between water absorption of the organic coating and temperature, the relationship between saturated water absorption of the organic coating and temperature, and the corrosion medium parameters.

5. The method of claim 3, wherein the calculating the diffusion time of water in the inorganic coating based on the water diffusion model of the inorganic coating and the coating parameters and the corrosion medium parameters comprises: obtaining a relationship between a diffusion coefficient of water in the inorganic coating and temperature; determining a relationship between a diffusion distance of water in the inorganic coating and a complete diffusion time of water in the inorganic coating based on the relationship between the diffusion coefficient of water in the inorganic coating and temperature; and calculating the diffusion time of water in the inorganic coating based on the relationship between the diffusion distance of water in the inorganic coating and the complete diffusion time of water in the inorganic coating, the coating parameters, and the corrosion medium parameters.

6. The method of claim 1, wherein the determining the coating failure time based on the pre-set coating adhesion decay model and the corrosion-induced additional stress increase model and the coating parameters and the corrosion medium parameters comprises: obtaining a hydrogen parameter, a magnesium alloy parameter, a relationship between adhesion and temperature and time, and a relationship between corrosion-induced internal stress and temperature and time; calculating a wet-state adhesion of the coating based on the relationship between adhesion and temperature and time and the corrosion medium parameters; calculating corrosion-induced additional stress based on the relationship between corrosion-induced internal stress and temperature and time, the hydrogen parameter, the magnesium alloy parameter, and the corrosion medium parameters; and determining the coating failure time based on the wet-state adhesion of the coating and the corrosion-induced additional stress.

7. The method of claim 1, further comprising: obtaining the coating parameters and the corrosion medium parameters; calculating the diffusion time of water in the coating based on the pre-set coating water diffusion model and the coating parameters and the corrosion medium parameters; determining the coating failure time based on the pre-set coating adhesion decay model and the corrosion-induced additional stress increase model and the coating parameters and the corrosion medium parameters; and calculating the coating predicted life based on the diffusion time of water in the coating and the coating failure time. ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ 7. A magnesium alloy protective coating service life prediction device characterized by comprising: ​ ​ ​ ​ ​ The life prediction module is further configured to calculate a theoretical life of the coating according to the diffusion time of the moisture in the coating and a coating failure time; when the coating is a single coating, the diffusion time of the moisture in the coating is a diffusion time of the moisture in the inorganic coating, the coating failure time is a time when the adhesion is equal to the corrosion-induced internal stress of the hydrogen, and the theoretical life L' of the coating is determined by the following formula: L' = L2 + γ1L3 In the formula, L2 is the diffusion time of the moisture in the inorganic coating; L3 is the coating failure time; and γ1 is an interface corrosion deceleration factor when the coating is a single coating. When the coating is a composite coating, the diffusion time of the moisture in the coating is a diffusion time of the moisture in the inorganic coating and a diffusion time of the moisture in the organic coating, the coating failure time is a time when the adhesion is equal to the corrosion-induced internal stress of the hydrogen, and the theoretical life L' of the coating is determined by the following formula: L' = L1 + γ2(L2 + L3) In the formula, L1 is the diffusion time of the moisture in the organic coating; L2 is the diffusion time of the moisture in the inorganic coating; L3 is the coating failure time; and γ2 is a superposition effect factor of the organic coating and the inorganic coating after being combined in the composite coating; the corrosion medium theoretical parameter and the corrosion medium actual parameter are determined, and a conversion coefficient is calculated according to the corrosion medium theoretical parameter and the corrosion medium actual parameter; and a predicted life of the coating is calculated according to the theoretical life of the coating and the conversion coefficient.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor implements the steps of the magnesium alloy protective coating life prediction method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium storing a computer program, the computer-readable storage medium comprising: The computer program implements the steps of the magnesium alloy protective coating life prediction method according to any one of claims 1 to 6 when executed by the processor.

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