Anti-icing test method, device and equipment for super-hydrophobic surface structure of energy equipment and storage medium

Abstract

The invention discloses an anti-icing testing method, device and equipment for a super-hydrophobic surface structure of energy equipment and a storage medium, and relates to the technical field of super-hydrophobic surface testing. Designing a super-hydrophobic surface structure based on the environmental main control factor to obtain a structure parameter set; simulating the super-hydrophobic surface structure by using an environment load condition determined based on the environment working condition matrix and a structure parameter set to obtain an equipment critical vibration frequency, and determining a current surface structure morphology based on the structure parameter set and the equipment critical vibration frequency; and determining a morphology simulation error based on the current surface structure morphology and the actual surface structure morphology of the super-hydrophobic surface structure, and monitoring the super-hydrophobic surface structure based on the morphology simulation error, the structure parameter set, the equipment critical vibration frequency and the preset control mechanical excitation frequency to obtain the ice growth rate and the ice adhesion work. The efficiency of anti-icing testing of the super-hydrophobic surface structure is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of super-hydrophobic surface testing, and in particular relates to a super-hydrophobic surface structure anti-icing test method, device, equipment and storage medium for energy equipment. BACKGROUND

[0002] At present, in target environments such as the polar region and the plateau, energy equipment such as wind power and solar power is easily affected by icing, which reduces power generation efficiency and even causes equipment failure, safety accidents, and affects stable energy supply. Super-hydrophobic surfaces can reduce the contact between the surface and water, inhibit water droplet adhesion and freezing, and provide a new way for energy equipment anti-icing. Through special microstructure and macrostructure design, combined with appropriate surface chemical properties, super-hydrophobic effect can be achieved. Target environments include low temperature, strong wind, high humidity, and sunlight changes, and various complex factors are coupled with each other, which has a comprehensive influence on the anti-icing performance of super-hydrophobic surfaces.

[0003] Current mainstream technologies include:

[0004] Contact angle and roll angle test technology: the hydrophobicity of the surface is evaluated by measuring the contact angle and roll angle of the water droplet on the super-hydrophobic surface.

[0005] Thermal imaging monitoring test technology: thermal imaging equipment is used to monitor the temperature distribution of the super-hydrophobic surface in the target environment in real time.

[0006] Simulated environment cycle test technology: the super-hydrophobic surface of the equipment is tested for multiple cycles in a test box that can simulate various target environment conditions.

[0007] Among them, the test results obtained by the above technologies are easily affected by factors such as water droplet size, surface roughness, humidity and temperature of the test environment, and cannot directly obtain information such as microstructure changes of the surface and growth rate of the ice layer, which has limitations for in-depth understanding of the anti-icing mechanism of super-hydrophobic surfaces. In addition, the simulated environment cycle test requires test equipment that can accurately control temperature, humidity, wind speed and other environmental parameters, and the complexity and precision requirements of the equipment are high. Therefore, the traditional super-hydrophobic surface structure anti-icing test of energy equipment does not consider enough comprehensive factors, has great limitations in test environment, and has insufficient test precision.

[0008] From the above, how to improve the efficiency of anti-icing test of the super-hydrophobic surface structure of energy equipment in the target environment during the super-hydrophobic surface structure anti-icing test of energy equipment is a problem to be solved at present. SUMMARY

[0009] Therefore, the present application aims to provide an energy equipment super-hydrophobic surface structure anti-icing test method, device, equipment and storage medium, which can improve the efficiency of anti-icing test of the super-hydrophobic surface structure of the energy equipment in the target environment during the anti-icing test of the super-hydrophobic surface structure of the energy equipment, thereby improving the safety of the production process. The specific scheme is as follows:

[0010] In a first aspect, the present application provides an energy equipment super-hydrophobic surface structure anti-icing test method, comprising:

[0011] An environment feature map for characterizing parameter changes of a target environment is constructed, and an environment working condition matrix including a plurality of environment parameter combinations is constructed based on the environment feature map. Then, an environment master control factor affecting the anti-icing performance of the super-hydrophobic surface structure is extracted from the environment working condition matrix, and a gradient fractal surface design is performed on the super-hydrophobic surface structure of the energy equipment based on the environment master control factor, to obtain a super-hydrophobic surface structure parameter set; the target environment is an environment satisfying a preset extreme environment judgment condition;

[0012] An environment load condition is determined based on the environment working condition matrix, and a fluid-structure-thermal coupling simulation is performed on the super-hydrophobic surface structure based on the super-hydrophobic surface structure parameter set and the environment load condition, to obtain an equipment critical vibration frequency. Then, a preset preparation process control system is utilized and a laser scanning and simulation are performed based on the super-hydrophobic surface structure parameter set and the equipment critical vibration frequency, to obtain a current surface structure morphology;

[0013] A morphology simulation error is determined based on the current surface structure morphology and an actual surface structure morphology corresponding to the super-hydrophobic surface structure, and a dynamic ice layer monitoring is performed on the super-hydrophobic surface structure based on the morphology simulation error, the super-hydrophobic surface structure parameter set, the equipment critical vibration frequency and a preset control mechanical excitation frequency, to obtain a corresponding ice growth rate and ice adhesion work.

[0014] Optionally, the construction of the environment feature map for characterizing parameter changes of the target environment and the construction of the environment working condition matrix including a plurality of environment parameter combinations based on the environment feature map comprise:

[0015] The monitoring data of the energy equipment in the target environment is obtained; the monitoring data includes temperature data, humidity data, wind speed data, droplet diameter data, energy equipment super-hydrophobic surface inclination angle data, energy equipment vibration frequency spectrum data and solar intensity data;

[0016] determine target equal-probability division intervals based on the corresponding value ranges of the monitoring data, divide the monitoring data into a plurality of non-overlapping subintervals using the target equal-probability division intervals, and then randomly extract a preset number of sample values in each of the subintervals according to a preset random sampling rule to construct an environmental working condition matrix based on the preset number of sample values.

[0017] Optionally, the extracting, from the environmental working condition matrix, of environmental master control factors that affect the ice-repellent performance of the super-hydrophobic surface structure includes:

[0018] determining temperature data in the environmental working condition matrix, determining temperature difference values between different spatial points in the super-hydrophobic surface structure based on the temperature data, and determining a temperature gradient based on the spatial distances between the different spatial points in the super-hydrophobic surface structure and the corresponding temperature difference values, and setting the temperature gradient as a first environmental master control factor;

[0019] determining wind speed data in the environmental working condition matrix, determining kinetic energy ratios of the wind speed data using a preset kinetic energy ratio calculation formula to obtain kinetic energy ratio results, and setting the kinetic energy ratio results as a second environmental master control factor;

[0020] determining energy equipment vibration frequency spectrum data in the environmental working condition matrix, determining power densities of the energy equipment vibration frequency spectrum data using a preset frequency spectrum analysis method to obtain corresponding vibration power densities, and setting the vibration power densities as a third environmental master control factor.

[0021] Optionally, the gradient fractal surface design of the super-hydrophobic surface structure of the energy equipment based on the environmental master control factors to obtain a super-hydrophobic surface structure parameter set includes:

[0022] developing a bi-scale fractal model for determining the curvature radius of a macroscopic flow channel and the diameter of a microscopic columnar array and a mixed integer programming model for determining a super-hydrophobic surface structure parameter set;

[0023] determining an apparent contact angle, a Young contact angle, an intrinsic contact angle, a maximum droplet diameter, and a proportion of the super-hydrophobic surface structure occupied by ice corresponding to the super-hydrophobic surface structure, determining a surface structure minimum height based on the intrinsic contact angle and the maximum droplet diameter, and determining constraint conditions based on the apparent contact angle, the Young contact angle, and the proportion;

[0024] determining an air resistance, a heat conduction loss, a resistance under a reference working condition, and a heat conduction value under the reference working condition corresponding to the super-hydrophobic surface structure, and determining a first weight factor corresponding to the air resistance and a second weight factor corresponding to the heat conduction loss;

[0025] determine a macroscopic gutter curvature radius and a microscopic column array diameter based on the energy equipment super-hydrophobic surface inclination angle data and the wind speed data, and then determine surface geometric features and material properties based on the mixed integer programming model and the constraint conditions, the air resistance, the heat conduction loss, the resistance under the benchmark working condition, the heat conduction value under the benchmark working condition, the first weight factor and the second weight factor;

[0026] determine a super-hydrophobic surface structure parameter set based on the surface geometric features, the material properties, the surface structure minimum height, the macroscopic gutter curvature radius and the microscopic column array diameter.

[0027] Optionally, the environment load conditions are determined based on the environment working condition matrix, and a fluid-structure-thermal coupling simulation is performed on the super-hydrophobic surface structure based on the super-hydrophobic surface structure parameter set and the environment load conditions to obtain an equipment critical vibration frequency, including:

[0028] determine environment load conditions based on the environment working condition matrix, and determine surface geometric features and material properties corresponding to the super-hydrophobic surface structure based on the super-hydrophobic surface structure parameter set, and then construct a quality matrix, a damping matrix and a stiffness matrix based on the super-hydrophobic surface structure parameter set, the surface geometric features and the material properties by using a preset matrix construction rule;

[0029] determine a liquid phase volume fraction, a fluid velocity vector field, a time advance amount in transient simulation and a preset Hamiltonian operator corresponding to the super-hydrophobic surface structure to construct a joint model, and determine a displacement vector, a velocity vector, an acceleration vector, an ice layer load force and an aerodynamic load force corresponding to the super-hydrophobic surface structure to establish a coupled structure vibration equation based on the quality matrix, the damping matrix and the stiffness matrix;

[0030] determine an equipment critical vibration frequency based on the quality matrix, the environment load conditions and the stiffness matrix by using the joint model, a preset vibration frequency determination equation and the coupled structure vibration equation.

[0031] Optionally, a laser scanning and simulation are performed based on the super-hydrophobic surface structure parameter set and the equipment critical vibration frequency by using a preset preparation process control system to obtain a current surface structure topography, including:

[0032] set the super-hydrophobic surface structure parameter set as a manufacturing benchmark, and then determine a scanning speed and a target plating layer thickness based on the manufacturing benchmark by using a preset laser scanning path adjustment strategy;

[0033] setting the equipment critical vibration frequency as a constraint condition, and then determining a scanning path corresponding to the time advancing amount by using a preset anti-resonance modulation mechanism and based on the constraint condition, the equipment critical vibration frequency, the scanning speed and the time advancing amount;

[0034] establishing an atomic layer deposition thickness feedback control model, to determine a reaction cycle number corresponding to a completed scan by using the atomic layer deposition thickness feedback control model and a preset preparation process control system and based on the target coating thickness, the scanning speed and a current deposition cavity temperature, and obtaining a current surface structure topography based on the reaction cycle number and the scanning path.

[0035] Optionally, a topography simulation error is determined based on the current surface structure topography and an actual surface structure topography corresponding to the super-hydrophobic surface structure, and a dynamic ice layer monitoring is performed on the super-hydrophobic surface structure based on the topography simulation error, the super-hydrophobic surface structure parameter set, the equipment critical vibration frequency and a preset control mechanical excitation frequency, to obtain a corresponding ice growth rate and ice adhesion work, including:

[0036] determining an actual surface structure topography corresponding to the super-hydrophobic surface structure, and determining a topography simulation error based on the current surface structure topography and the actual surface structure topography, and then determining an ice layer thickness increment in a preset time interval of the super-hydrophobic surface structure, an ice layer containing phase difference, an ice layer free phase difference and a terahertz wave angular frequency;

[0037] determining the ice growth rate by using a preset target thickness detection function and based on the ice layer thickness increment in the preset time interval, the ice layer containing phase difference, the ice layer free phase difference and the terahertz wave angular frequency;

[0038] acquiring ice layer surface images by using a preset digital image correlation method, and obtaining a first displacement field and a second displacement field corresponding to a horizontal direction and a vertical direction respectively by an image matching algorithm, and calculating a strain field of the ice layer on the super-hydrophobic surface structure in the horizontal direction based on the first displacement field and the second displacement field;

[0039] extracting a critical debonding length corresponding to the strain field by using a preset control mechanical excitation frequency, and determining the ice adhesion work of the super-hydrophobic surface structure based on an ice layer elastic modulus corresponding to the super-hydrophobic surface structure and the ice layer thickness increment; wherein a value corresponding to the preset control mechanical excitation frequency is not greater than the equipment critical vibration frequency.

[0040] In a second aspect, the present application provides a super-hydrophobic surface structure anti-icing testing device of energy equipment, including:

[0041] The feature map construction module is configured to construct an environment feature map for characterizing parameter changes of a target environment, construct an environment working condition matrix including a plurality of environment parameter combinations based on the environment feature map, then extract an environment master control factor affecting the ice prevention performance of the super-hydrophobic surface structure from the environment working condition matrix, and perform gradient fractal surface design on the super-hydrophobic surface structure of the energy equipment based on the environment master control factor, to obtain a super-hydrophobic surface structure parameter set;

[0042] The surface structure morphology determination module is configured to determine an environment load condition based on the environment working condition matrix, and perform fluid-thermal coupling simulation on the super-hydrophobic surface structure based on the super-hydrophobic surface structure parameter set and the environment load condition, to obtain an equipment critical vibration frequency, then perform laser scanning and simulation based on the super-hydrophobic surface structure parameter set and the equipment critical vibration frequency by using a preset preparation process control system, to obtain a current surface structure morphology.

[0043] The morphology simulation error determination module is configured to determine a morphology simulation error based on the current surface structure morphology and an actual surface structure morphology corresponding to the super-hydrophobic surface structure, and perform dynamic ice layer monitoring on the super-hydrophobic surface structure based on the morphology simulation error, the super-hydrophobic surface structure parameter set, the equipment critical vibration frequency, and a preset control mechanical excitation frequency, to obtain a corresponding ice growth rate and ice adhesion work.

[0044] In a third aspect, the present application provides an electronic device, comprising:

[0045] A memory configured to save a computer program;

[0046] A processor configured to execute the computer program to implement the super-hydrophobic surface structure ice prevention test method of the energy equipment.

[0047] In a fourth aspect, the present application provides a computer readable storage medium configured to save a computer program, wherein the computer program is executed by a processor to implement the super-hydrophobic surface structure ice prevention test method of the energy equipment.

[0048] As can be seen from the above, before the anti-icing test of the super-hydrophobic surface structure of the energy equipment is performed, the application needs to construct an environment characteristic map for characterizing parameter changes of a target environment, and construct an environment working condition matrix including a plurality of environment parameter combinations based on the environment characteristic map, then extract an environment master control factor affecting the anti-icing performance of the super-hydrophobic surface structure from the environment working condition matrix, and perform gradient fractal surface design on the super-hydrophobic surface structure of the energy equipment based on the environment master control factor to obtain a super-hydrophobic surface structure parameter set; determine an environment load condition based on the environment working condition matrix, and perform fluid-thermal coupling simulation on the super-hydrophobic surface structure based on the super-hydrophobic surface structure parameter set and the environment load condition to obtain an equipment critical vibration frequency, then perform laser scanning and simulation based on the super-hydrophobic surface structure parameter set and the equipment critical vibration frequency by using a preset preparation process control system to obtain a current surface structure morphology; determine a morphology simulation error based on the current surface structure morphology and an actual surface structure morphology corresponding to the super-hydrophobic surface structure, and perform dynamic ice layer monitoring on the super-hydrophobic surface structure based on the morphology simulation error, the super-hydrophobic surface structure parameter set, the equipment critical vibration frequency and a preset control mechanical excitation frequency to obtain a corresponding ice growth rate and ice adhesion work.

[0049] As can be seen from the above, before the anti-icing test of the super-hydrophobic surface structure of the energy equipment is performed, the application needs to construct an environment characteristic map for characterizing parameter changes of a target environment, and construct an environment working condition matrix including a plurality of environment parameter combinations based on the environment characteristic map, then extract an environment master control factor affecting the anti-icing performance of the super-hydrophobic surface structure from the environment working condition matrix, and perform gradient fractal surface design on the super-hydrophobic surface structure of the energy equipment based on the environment master control factor to obtain a super-hydrophobic surface structure parameter set; determine an environment load condition based on the environment working condition matrix, and perform fluid-thermal coupling simulation on the super-hydrophobic surface structure based on the super-hydrophobic surface structure parameter set and the environment load condition to obtain an equipment critical vibration frequency, then perform laser scanning and simulation based on the super-hydrophobic surface structure parameter set and the equipment critical vibration frequency by using a preset preparation process control system to obtain a current surface structure morphology; determine a morphology simulation error based on the current surface structure morphology and an actual surface structure morphology corresponding to the super-hydrophobic surface structure, and perform dynamic ice layer monitoring on the super-hydrophobic surface structure based on the morphology simulation error, the super-hydrophobic surface structure parameter set, the equipment critical vibration frequency and a preset control mechanical excitation frequency to obtain a corresponding ice growth rate and ice adhesion work. In this way, the efficiency of the anti-icing test of the super-hydrophobic surface structure of the energy equipment under the target environment is improved during the anti-icing test of the super-hydrophobic surface structure of the energy equipment, and the safety of the production process is further improved. BRIEF DESCRIPTION OF DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only constitute a part of the embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of the provided drawings.

[0051] Figure 1 A flow chart of an ice prevention test method for a super-hydrophobic surface structure of an energy equipment disclosed in the present application;

[0052] Figure 2 A structural schematic diagram of an ice prevention test device for a super-hydrophobic surface structure of an energy equipment disclosed in the present application;

[0053] Figure 3 A structural diagram of an electronic device disclosed in the present application. DETAILED DESCRIPTION

[0054] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only constitute a part of the embodiments of the present application, rather than 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.

[0055] At present, in the polar, plateau and other extreme environments, the energy equipment such as wind energy and solar energy is easily affected by icing, which reduces the power generation efficiency, even causes equipment failure, safety accidents, and affects the stable supply of energy. The super-hydrophobic surface can reduce the contact between the surface and water, inhibit the adhesion and freezing of water droplets, and provide a new way for the ice prevention of energy equipment. The test results obtained by using the current mainstream technology are easily affected by factors such as the size of water droplets, surface roughness, humidity and temperature of the test environment, and the information such as the microstructure change of the surface and the growth rate of the ice layer cannot be directly obtained, which has limitations for in-depth understanding of the ice prevention mechanism of the super-hydrophobic surface. Therefore, the present application provides an ice prevention test method for a super-hydrophobic surface structure of an energy equipment, which can improve the efficiency of ice prevention test for the super-hydrophobic surface structure of the energy equipment in the target environment during the ice prevention test of the super-hydrophobic surface structure of the energy equipment, and further improve the safety of the production process.

[0056] Referring to Figure 1 The embodiments of the present application disclose an ice prevention test method for a super-hydrophobic surface structure of an energy equipment, which comprises:

[0057] Step S11, constructing an environment feature map for characterizing parameter changes of a target environment, and constructing an environment working condition matrix including a plurality of environment parameter combinations based on the environment feature map, then extracting an environment master control factor affecting the ice prevention performance of the super-hydrophobic surface structure of the energy equipment from the environment working condition matrix, and performing gradient fractal surface design on the super-hydrophobic surface structure of the energy equipment based on the environment master control factor, to obtain a super-hydrophobic surface structure parameter set; the target environment is an environment meeting a preset extreme environment judgment condition.

[0058] In this embodiment, during the ice prevention test of the super-hydrophobic surface structure of the energy equipment, the extreme environment scene monitoring data is first obtained, including the extreme environment scene monitoring temperature , the extreme environment scene monitoring humidity , the extreme environment scene monitoring wind speed , the extreme environment scene monitoring droplet diameter , the extreme environment scene monitoring energy equipment super-hydrophobic surface inclination angle , the extreme environment scene monitoring energy equipment vibration spectrum , and the extreme environment scene monitoring solar intensity .

[0059] Subsequently, the Latin hypercube sampling method is used to generate an extreme environment working condition matrix, that is, the value range of the extreme environment scene monitoring data is divided into 500 non-overlapping subintervals, and a sample value is randomly extracted in each subinterval of the extreme environment scene monitoring data, and then the above sampling step is repeated until 500 samples are obtained, and then the extreme environment working condition matrix is generated:

[0060] ;

[0061] wherein, is an index variable, representing the kth data sample in the working condition matrix, is the extreme environment scene monitoring temperature of the kth data sample, is the extreme environment scene monitoring humidity of the kth data sample, is the extreme environment scene monitoring wind speed of the kth data sample, is the extreme environment scene monitoring droplet diameter of the kth data sample, is the extreme environment scene monitoring energy equipment super-hydrophobic surface inclination angle of the kth data sample, is the extreme environment scene monitoring energy equipment vibration spectrum of the kth data sample, is the extreme environment scene monitoring solar intensity of the kth data sample.

[0062] Specifically, the environment feature map for characterizing parameter changes of the target environment is constructed, and the environment working condition matrix including a plurality of environment parameter combinations is constructed based on the environment feature map, which can include: obtaining monitoring data of the energy equipment in the target environment; the monitoring data includes temperature data, humidity data, wind speed data, liquid droplet diameter data, energy equipment super-hydrophobic surface inclination angle data, energy equipment vibration frequency spectrum data, and sunshine intensity data; determining a target equal-probability division interval based on a corresponding value range of each monitoring data, and dividing the monitoring data into a plurality of non-overlapping subintervals by using the target equal-probability division interval, and then randomly extracting a preset number of sample values in each subinterval according to a preset random sampling rule, to construct the environment working condition matrix based on the preset number of sample values.

[0063] That is, the extreme environment feature is comprehensively described by obtaining extreme environment scene monitoring data covering temperature, humidity, wind speed and the like. These data serve as a basis for subsequent research to consider various influencing factors in the environment, avoid missing important conditions, and ensure that the research on the extreme environment is closer to the actual situation.

[0064] Further, the data organization in the working condition matrix is standardized by explicitly indicating the index variable and the data representation method, which facilitates accurate processing and use of data in subsequent analysis processes such as extraction of extreme environment master factors, thereby improving the accuracy of analysis results in the entire research process. Furthermore, the Latin hypercube sampling is used to generate the working condition matrix to subdivide and randomly sample the value range of each parameter, ensuring that the samples uniformly cover the parameter space. The selected 500 groups of samples are used to represent various possible working condition combinations, so that the subsequent analysis and research results based on the working condition matrix are more universal and reliable, providing solid data support for the ice prevention test of the super-hydrophobic surface structure of the energy equipment in the extreme environment.

[0065] In this embodiment, principal component analysis is performed on the extreme environment working condition matrix to extract three master factors, including a temperature gradient , a kinetic energy ratio KE and a vibration power density . It is worth mentioning that for the monitoring temperature of each extreme environment scene in the extreme environment working condition matrix , the temperature difference between different spatial points can be calculated, and the temperature gradient is calculated according to the spatial distance; for the monitoring wind speed of each extreme environment scene in the extreme environment working condition matrix , the kinetic energy ratio KE can be calculated based on the kinetic energy ratio calculation formula , wherein is the air density; for the monitoring wind speed of each extreme environment scene in the extreme environment working condition matrix Each of the extreme environment scene groups monitors the energy equipment vibration spectrum, and the embodiment of the present application can use the Welch method to calculate the vibration power density, and then convert the time domain vibration signal into a frequency domain signal through fast Fourier transform to calculate the vibration power density .

[0066] Specifically, the environmental master factor affecting the ice prevention performance of the super-hydrophobic surface structure is extracted from the environmental condition matrix, which can include: determining the temperature data in the environmental condition matrix, determining the temperature difference between different spatial points in the super-hydrophobic surface structure based on the temperature data, and then determining the temperature gradient based on the spatial distance between the different spatial points in the super-hydrophobic surface structure and the corresponding temperature difference, so as to set the temperature gradient as the first environmental master factor; determining the wind speed data in the environmental condition matrix, and determining the kinetic energy ratio of each wind speed data by using a preset kinetic energy ratio calculation formula to obtain a kinetic energy ratio result, and then setting the kinetic energy ratio result as the second environmental master factor; determining the energy equipment vibration spectrum data in the environmental condition matrix, and determining the power density of each energy equipment vibration spectrum data by using a preset frequency spectrum analysis method to obtain the corresponding vibration power density, and setting the vibration power density as the third environmental master factor.

[0067] It is worth mentioning that the extreme environment working condition matrix contains multiple sets of complex monitoring data. Through principal component analysis dimension reduction, three main control factors of temperature gradient, kinetic energy ratio and vibration power density are extracted from numerous variables to remove data redundancy, convert high-dimensional data into low-dimensional representation, make subsequent analysis and processing more convenient, and reduce calculation cost and analysis difficulty. Among them, the above-mentioned main control factors are key physical quantities refined from a large number of environmental parameters, which can reflect the important aspects of extreme environment on the structure of super-hydrophobic surface of energy equipment. For example, temperature gradient affects heat transfer and surface physical state change, kinetic energy ratio reflects the effect of fluid kinetic energy on surface dynamics characteristics, vibration power density is related to the stability and dynamic response of surface structure, focusing on these factors can more accurately study the anti-icing problem. Subsequently, after determining the main control factors, in the subsequent research on the design, simulation and performance evaluation of the super-hydrophobic surface structure of energy equipment, these key factors can be focused on, so that the research is more targeted, improves the research efficiency and the practical application value of research results, and helps to more effectively solve the anti-icing problem of energy equipment in extreme environment. Then, after obtaining the extreme environment main control factors, the embodiment of the present application can design the gradient fractal surface structure of the super-hydrophobic surface structure of energy equipment based on the extreme environment main control factors, and output the parameter set of the super-hydrophobic surface structure of energy equipment to the simulation model. The simulation model includes but is not limited to ANSYS DesignModeler (i.e. ANSYS geometric modeling tool), ANSYS Fluent+Mechanical (i.e. ANSYS fluid calculation software and structural mechanics simulation module) and MATLAB (Matrix Laboratory, i.e. Matrix Laboratory).

[0068] In this embodiment, a double-scale fractal model needs to be established, and the expression of the curvature radius corresponding to the macroscopic guide groove is as follows:

[0069] ;

[0070] Among them, is the acceleration of gravity;

[0071] Then, the expression of the diameter of the micro column array that needs to be determined by the embodiment of the present application is as follows:

[0072] ;

[0073] Among them, is the capillary length, is the diameter;

[0074] Subsequently, the embodiment of the present application needs to develop a mixed integer programming model, and the expression is as follows:

[0075] ;

[0076] wherein, is the air resistance caused by the surface structure, is the heat conduction loss of the candidate surface, is the resistance under the reference working condition, is the heat conduction value under the reference working condition, is the set weight factor of the air resistance, is the set weight factor of the heat conduction loss;

[0077] Subsequently, the embodiment of the present application needs to determine the constraint condition of Cassie-Baxter equation, and the expression is as follows:

[0078] ;

[0079] wherein, is the apparent contact angle, is the Young contact angle, is the proportion of the surface structure occupied by ice;

[0080] Subsequently, the minimum height of the surface structure needs to be determined, and the expression is as follows:

[0081] ;

[0082] wherein, is the minimum height of the surface structure, is the intrinsic contact angle, is the maximum droplet diameter;

[0083] Finally, the parameter set of the energy equipment super-hydrophobic surface structure is output to the simulation model.

[0084] Specifically, based on the environment master factor to the super-hydrophobic surface structure of energy equipment gradient fractal surface design, get the super-hydrophobic surface structure parameter set, can include: develop for determining the macroscopic flow groove curvature radius and micro column array diameter double scale fractal model and for determining the super-hydrophobic surface structure parameter set mixed integer programming model;Determine the apparent contact angle, Young contact angle, intrinsic contact angle, maximum droplet diameter and the proportion of super-hydrophobic surface structure occupied by ice corresponding to the super-hydrophobic surface structure, and determine the minimum height of the surface structure based on the intrinsic contact angle and the maximum droplet diameter, and then determine the constraint condition based on the apparent contact angle, Young contact angle and the proportion;Determine the air resistance, heat loss, resistance under the reference working condition and heat transfer value under the reference working condition corresponding to the super-hydrophobic surface structure, and determine the first weight factor corresponding to the air resistance and the second weight factor corresponding to the heat loss;Determine the macroscopic flow groove curvature radius and micro column array diameter by using double scale fractal model and based on the energy equipment super-hydrophobic surface inclination angle data and wind speed data, then determine the surface geometric characteristics and material properties by using mixed integer programming model and based on the constraint condition, air resistance, heat loss, resistance under the reference working condition, heat transfer value under the reference working condition, first weight factor and second weight factor;Determine the super-hydrophobic surface structure parameter set based on the surface geometric characteristics, material properties, minimum height of the surface structure, macroscopic flow groove curvature radius and micro column array diameter.

[0085] Step S12, determine the environmental load condition based on the environmental working condition matrix, and perform fluid-solid-thermal coupling simulation on the super-hydrophobic surface structure based on the super-hydrophobic surface structure parameter set and the environmental load condition, obtain the equipment critical vibration frequency, then use the preset preparation process control system and based on the super-hydrophobic surface structure parameter set and the equipment critical vibration frequency to perform laser scanning and simulation, obtain the current surface structure topography.

[0086] In this embodiment, the process of fluid-solid-thermal coupling simulation on the super-hydrophobic surface structure of energy equipment is as follows: first, use the super-hydrophobic surface structure parameter set of energy equipment Define the super-hydrophobic surface geometric characteristics and material properties of the simulation model energy equipment;Then, use the extreme environmental working condition matrix Define the environmental load condition to drive the multi-physical field coupling in the simulation model;

[0087] Subsequently, based on the super-hydrophobic surface structure parameter set of energy equipment, construct the mass matrix M, the damping matrix C and the stiffness matrix ;

[0088] Then, establish the improved VOF-Level Set joint model, and the expression is as follows:

[0089] ;

[0090] wherein, is the liquid volume fraction, is the fluid velocity vector field, t is the time advancement in the transient simulation, is the partial derivative symbol, is the Hamiltonian operator, denotes the liquid volume fraction the partial derivative with respect to the time advancement t in the transient simulation;

[0091] Further, the coupled structural vibration equation is established:

[0092] ;

[0093] wherein, is the displacement vector, is the velocity vector, is the acceleration vector, is the ice layer load force, i.e. the stress resulting from the ice layer growth calculated by the phase change model, is the aerodynamic load force obtained by the surface pressure integral output by the fluid simulation;

[0094] Finally, the critical vibration frequency of the energy equipment is obtained by an eigenvalue analysis technique, and the critical vibration frequency of the energy equipment is input into the preparation process control system, and the expression is as follows:

[0095] ;

[0096] wherein, is the pi, is the critical vibration frequency of the energy equipment;

[0097] Specifically, the environmental load condition is determined based on the environmental working condition matrix, and the fluid-structure-thermal coupling simulation is performed on the super-hydrophobic surface structure based on the super-hydrophobic surface structure parameter set and the environmental load condition to obtain the equipment critical vibration frequency, which can include: determining the environmental load condition based on the environmental working condition matrix, and determining the surface geometric features and material properties corresponding to the super-hydrophobic surface structure based on the super-hydrophobic surface structure parameter set, and then constructing a predetermined matrix rule and constructing a mass matrix, a damping matrix and a stiffness matrix based on the super-hydrophobic surface structure parameter set, the surface geometric features and the material properties; determining the liquid volume fraction, the fluid velocity vector field, the time advancement in the transient simulation and the predetermined Hamiltonian operator corresponding to the super-hydrophobic surface structure to construct a joint model, and determining the displacement vector, the velocity vector, the acceleration vector, the ice layer load force and the aerodynamic load force corresponding to the super-hydrophobic surface structure based on the mass matrix, the damping matrix and the stiffness matrix to establish the coupled structural vibration equation; the joint model, the predetermined vibration frequency determination equation and the coupled structural vibration equation are determined based on the mass matrix, the environmental load condition and the stiffness matrix, and the critical vibration frequency of the equipment is determined.

[0098] In the embodiment, the energy equipment super-hydrophobic surface structure parameter set is set as a simulation manufacturing reference to determine a laser scanning path and an ALD (Atomic Layer Deposition, a thin film deposition technology) coating thickness, and a critical vibration frequency of the energy equipment is taken as a simulation manufacturing constraint condition to dynamically adjust the laser scanning path and introduce an anti-resonance modulation:

[0099] ;

[0100] wherein, is the critical vibration frequency of the energy equipment, is a basic scanning speed, and a laser scanning speed is obtained as a path changing with time advancing ; ;

[0101] Subsequently, an ALD deposition thickness feedback control is established:

[0102] ;

[0103] wherein e is a natural constant, is a number of times of completing a complete ALD reaction cycle, is a target coating thickness, is an ALD single-cycle growth rate, is a deposition cavity temperature.

[0104] Specifically, the laser scanning and simulation are performed by using a preset preparation process control system and based on the super-hydrophobic surface structure parameter set and the critical vibration frequency of the equipment to obtain a current surface structure topography, which can include: setting the super-hydrophobic surface structure parameter set as a manufacturing reference, and then determining a scanning speed and a target coating thickness based on the manufacturing reference by using a preset laser scanning path adjustment strategy; setting the critical vibration frequency of the equipment as a constraint condition, and then determining a scanning path corresponding to a time advancing amount based on the constraint condition, the critical vibration frequency of the equipment, the scanning speed and the time advancing amount by using a preset anti-resonance modulation mechanism; establishing an atomic layer deposition thickness feedback control model to determine a number of times of completing a reaction cycle corresponding to scanning by using the atomic layer deposition thickness feedback control model and the preset preparation process control system and based on the target coating thickness, the scanning speed and a current deposition cavity temperature, and obtaining the current surface structure topography based on the number of times of completing a reaction cycle and the scanning path.

[0105] Step S13: Determine the morphology simulation error based on the current surface structure morphology and the actual surface structure morphology corresponding to the superhydrophobic surface structure, and perform dynamic ice layer monitoring on the superhydrophobic surface structure based on the morphology simulation error, the superhydrophobic surface structure parameter set, the critical vibration frequency of the equipment and the preset control mechanical excitation frequency to obtain the corresponding ice growth rate and ice adhesion work.

[0106] In this embodiment, it is necessary to detect the simulation error of the superhydrophobic surface structure morphology of the energy equipment online, and the expression is as follows:

[0107] ;

[0108] in, For the first The actual structural parameter measurements at the detection locations of the superhydrophobic surface structure of energy equipment. For the first Target parameter values ​​for the detection location of the superhydrophobic surface structure of energy equipment. To reduce simulation errors in the superhydrophobic surface morphology of energy equipment, The locations for detecting superhydrophobic surface structures on energy equipment are numbered, among which, =1,2,3,...,n, where n is the total number of detection locations for the superhydrophobic surface structure of energy equipment;

[0109] In one specific implementation, it is required that Otherwise, process parameter adjustments will be triggered:

[0110] Subsequently, in this embodiment, the simulation error of the superhydrophobic surface structure of the energy equipment needs to be fed back to the simulation model to correct the material constitutive equation, so as to update the elastic modulus and thermal expansion coefficient, and recalculate the critical vibration frequency of the energy equipment, so as to adjust the subsequent laser-ALD co-simulation manufacturing parameters based on the critical vibration frequency of the energy equipment.

[0111] In this embodiment, the present application embodiment can control the mechanical excitation frequency during the monitoring process based on the superhydrophobic surface structure parameter set of energy equipment, the simulation error of the superhydrophobic surface structure morphology of energy equipment, the critical vibration frequency of energy equipment and the actual surface morphology data, and perform dynamic ice layer monitoring:

[0112] First, thickness is measured based on terahertz time-domain spectroscopy, and the expression is as follows:

[0113] ;

[0114] in, To improve the ice growth rate of superhydrophobic surface structures for energy equipment, To be in the time interval The increase in the thickness of the inner ice layer, to monitor the time interval, to the phase difference of the ice layer, to the phase difference of the ice layer, to the angular frequency of the terahertz wave;

[0115] Further, the embodiment of the present application needs to measure the ice layer strain field by using the digital image correlation method, and the expression is as follows:

[0116] ;

[0117] wherein, is the x-direction displacement field obtained by the image matching algorithm, and g is the y-direction displacement field obtained by the image matching algorithm, is the x-direction strain;

[0118] Then, the ice adhesion work is determined:

[0119] ;

[0120] wherein, is the elastic modulus of the ice layer, is the critical debonding length, is the thickness of the ice layer, is the ice adhesion work of the energy equipment super-hydrophobic surface structure.

[0121] Specifically, based on the current surface structure morphology and the actual surface structure morphology corresponding to the super-hydrophobic surface structure, the morphology simulation error is determined, and based on the morphology simulation error, the super-hydrophobic surface structure parameter set, the equipment critical vibration frequency and the preset control mechanical excitation frequency, the super-hydrophobic surface structure is dynamically monitored, and the corresponding ice growth rate and ice adhesion work are obtained, which can include: determining the actual surface structure morphology corresponding to the super-hydrophobic surface structure, and determining the morphology simulation error based on the current surface structure morphology and the actual surface structure morphology, and then determining the ice layer thickness increment, the ice layer phase difference, the ice-free layer phase difference and the terahertz wave angular frequency in the preset time interval of the super-hydrophobic surface structure; using the preset target thickness detection function and based on the ice layer thickness increment, the ice layer phase difference, the ice-free layer phase difference and the terahertz wave angular frequency in the preset time interval to determine the ice growth rate; using the preset digital image correlation method to collect the ice layer surface image, and obtaining the first displacement field and the second displacement field corresponding to the horizontal direction and the vertical direction by the image matching algorithm respectively, and calculating the strain field of the ice layer on the super-hydrophobic surface structure in the horizontal direction based on the first displacement field and the second displacement field; using the preset control mechanical excitation frequency to extract the critical debonding length corresponding to the strain field, and based on the elastic modulus of the ice layer corresponding to the super-hydrophobic surface structure and the ice layer thickness increment, the ice adhesion work of the super-hydrophobic surface structure is determined; wherein the numerical value of the preset control mechanical excitation frequency is not greater than the equipment critical vibration frequency.

[0122] It is worth mentioning that the embodiments of the present application need to construct the objective function:

[0123] ;

[0124] wherein, is the upper limit of integration in time, that is, the total duration of the anti-icing performance evaluation, is the time identifier of the anti-icing performance evaluation, is the ice growth rate of the super-hydrophobic surface structure of the energy equipment, is the ice adhesion work of the super-hydrophobic surface structure of the energy equipment, is the anti-icing performance weight, is the ice shedding efficiency weight, is the comprehensive evaluation index of the anti-icing performance;

[0125] Then, the sensitivity is determined:

[0126] ;

[0127] wherein, is the adjoint variable, is the matrix transpose, is the control equation residual, is the integrand in the objective function, that is, , is the parameter set of the super-hydrophobic surface structure of the energy equipment, is the derivative of the control equation residual with respect to the parameter, is the direct derivative of the objective function with respect to the parameter, is the sensitivity;

[0128] Then, the embodiments of the present application can generate a structure correction instruction based on the sensitivity, to feed back and update the parameter set of the super-hydrophobic surface structure of the energy equipment using the structure correction instruction, wherein the expression of the structure correction instruction is as follows:

[0129] ;

[0130] wherein, is the structure correction instruction, is the learning rate, is the Hessian matrix;

[0131] Then, the is set as the correction amount, to feed back and update the parameter set of the super-hydrophobic surface structure of the energy equipment:

[0132] ;

[0133] wherein, constructing a parameter set of a super-hydrophobic surface structure of an energy equipment, constructing a parameter set of a super-hydrophobic surface structure of an energy equipment.

[0134] As can be seen from the above, before the anti-icing test of the super-hydrophobic surface structure of the energy equipment, the embodiment of the present application first needs to construct an environment characteristic map for characterizing parameter changes of a target environment, and construct an environment working condition matrix including a plurality of environment parameter combinations based on the environment characteristic map, then extract an environment master control factor affecting the anti-icing performance of the super-hydrophobic surface structure from the environment working condition matrix, and perform gradient fractal surface design on the super-hydrophobic surface structure of the energy equipment based on the environment master control factor, to obtain a super-hydrophobic surface structure parameter set; secondly, determine an environment load condition based on the environment working condition matrix, and perform fluid-structure-thermal coupling simulation on the super-hydrophobic surface structure based on the super-hydrophobic surface structure parameter set and the environment load condition, to obtain an equipment critical vibration frequency, then perform laser scanning and simulation based on the super-hydrophobic surface structure parameter set and the equipment critical vibration frequency by using a preset preparation process control system, to obtain a current surface structure morphology; finally, determine a morphology simulation error based on the current surface structure morphology and an actual surface structure morphology corresponding to the super-hydrophobic surface structure, and perform dynamic ice layer monitoring on the super-hydrophobic surface structure based on the morphology simulation error, the super-hydrophobic surface structure parameter set, the equipment critical vibration frequency and a preset control mechanical excitation frequency, to obtain a corresponding ice growth rate and ice adhesion work. In this way, the efficiency of the anti-icing test of the super-hydrophobic surface structure of the energy equipment under the target environment is improved in the process of the anti-icing test of the super-hydrophobic surface structure of the energy equipment, and the safety of the production process is further improved.

[0135] Correspondingly, referring to Figure 2 The present application also provides a super-hydrophobic surface structure anti-icing test device of an energy equipment, comprising:

[0136] The characteristic map construction module 11 is configured to construct an environment characteristic map for characterizing parameter changes of a target environment, and construct an environment working condition matrix including a plurality of environment parameter combinations based on the environment characteristic map, then extract an environment master control factor affecting the anti-icing performance of the super-hydrophobic surface structure from the environment working condition matrix, and perform gradient fractal surface design on the super-hydrophobic surface structure of the energy equipment based on the environment master control factor, to obtain a super-hydrophobic surface structure parameter set;

[0137] The surface structure morphology determination module 12 is configured to determine an environment load condition based on the environment working condition matrix, and perform fluid-structure-thermal coupling simulation on the super-hydrophobic surface structure based on the super-hydrophobic surface structure parameter set and the environment load condition, to obtain an equipment critical vibration frequency, then perform laser scanning and simulation based on the super-hydrophobic surface structure parameter set and the equipment critical vibration frequency by using a preset preparation process control system, to obtain a current surface structure morphology;

[0138] The topography simulation error determination module 13 is configured to determine a topography simulation error based on the current surface structure topography and an actual surface structure topography corresponding to the super-hydrophobic surface structure of the equipment, and perform dynamic ice layer monitoring on the super-hydrophobic surface structure based on the topography simulation error, the super-hydrophobic surface structure parameter set, the critical vibration frequency of the equipment, and a preset control mechanical excitation frequency, to obtain a corresponding ice growth rate and ice adhesion work.

[0139] As can be seen from the above, before the super-hydrophobic surface structure anti-icing test of the energy equipment is performed, the embodiment of the present application first needs to construct an environment feature map for characterizing parameter changes of a target environment, and construct an environment working condition matrix including a plurality of environment parameter combinations based on the environment feature map, then extract an environment master control factor affecting the anti-icing performance of the super-hydrophobic surface structure from the environment working condition matrix, and perform gradient fractal surface design on the super-hydrophobic surface structure of the energy equipment based on the environment master control factor, to obtain a super-hydrophobic surface structure parameter set; secondly, determine an environment load condition based on the environment working condition matrix, and perform fluid-thermal coupling simulation on the super-hydrophobic surface structure based on the super-hydrophobic surface structure parameter set and the environment load condition, to obtain a critical vibration frequency of the equipment, then perform laser scanning and simulation based on the super-hydrophobic surface structure parameter set and the critical vibration frequency of the equipment by using a preset preparation process control system, to obtain a current surface structure topography; finally, determine a topography simulation error based on the current surface structure topography and an actual surface structure topography corresponding to the super-hydrophobic surface structure of the equipment, and perform dynamic ice layer monitoring on the super-hydrophobic surface structure based on the topography simulation error, the super-hydrophobic surface structure parameter set, the critical vibration frequency of the equipment, and a preset control mechanical excitation frequency, to obtain a corresponding ice growth rate and ice adhesion work. In this way, the efficiency of the anti-icing test of the super-hydrophobic surface structure of the energy equipment under the target environment is improved during the anti-icing test of the super-hydrophobic surface structure of the energy equipment, and the safety of the production process is improved.

[0140] In some specific embodiments, the feature map construction module 11 can specifically include:

[0141] The monitoring data acquisition unit is configured to acquire monitoring data of the energy equipment under the target environment; the monitoring data includes temperature data, humidity data, wind speed data, liquid droplet diameter data, energy equipment super-hydrophobic surface inclination angle data, energy equipment vibration frequency spectrum data, and solar radiation intensity data;

[0142] The interval division unit is configured to determine a target equiprobability interval based on a value range corresponding to each of the monitoring data, divide the monitoring data into a plurality of non-overlapping subintervals by using the target equiprobability interval, and then randomly extract a preset number of sample values in each of the subintervals according to a preset random sampling rule, so as to construct an environmental condition matrix based on the preset number of sample values.

[0143] In some embodiments, the feature map construction module 11 can specifically include:

[0144] The temperature difference determination unit is configured to determine temperature data in the environmental condition matrix, determine a temperature difference between different spatial points in the super-hydrophobic surface structure based on the temperature data, and determine a temperature gradient based on a spatial distance between the different spatial points in the super-hydrophobic surface structure and the corresponding temperature difference, so as to set the temperature gradient as a first environmental master control factor.

[0145] The kinetic energy ratio result determination unit is configured to determine wind speed data in the environmental condition matrix, determine a kinetic energy ratio of each of the wind speed data by using a preset kinetic energy ratio calculation formula, obtain a kinetic energy ratio result, and set the kinetic energy ratio result as a second environmental master control factor.

[0146] The vibration power density determination unit is configured to determine energy equipment vibration frequency spectrum data in the environmental condition matrix, determine a vibration power density of each of the energy equipment vibration frequency spectrum data by using a preset frequency spectrum analysis method, and set the vibration power density as a third environmental master control factor.

[0147] In some embodiments, the feature map construction module 11 can specifically include:

[0148] The model development unit is configured to develop a double-scale fractal model for determining a macroscopic flow guide groove curvature radius and a microscopic columnar array diameter, and a mixed integer programming model for determining a super-hydrophobic surface structure parameter set.

[0149] The constraint condition determination unit is configured to determine an apparent contact angle, a Young contact angle, an intrinsic contact angle, a maximum droplet diameter, and a proportion of the super-hydrophobic surface structure occupied by ice corresponding to the super-hydrophobic surface structure, determine a surface structure minimum height based on the intrinsic contact angle and the maximum droplet diameter, and determine a constraint condition based on the apparent contact angle, the Young contact angle, and the proportion.

[0150] a structure parameter determination unit configured to determine air resistance, heat conduction loss, resistance under a reference working condition, and heat conduction value under the reference working condition corresponding to the super-hydrophobic surface structure, and determine a first weight factor corresponding to the air resistance and a second weight factor corresponding to the heat conduction loss;

[0151] a geometric feature determination unit configured to determine a macroscopic gutter curvature radius and a microscopic column array diameter by using the double-scale fractal model and based on the energy equipment super-hydrophobic surface inclination angle data and the wind speed data, and then determine surface geometric features and material properties by using the mixed integer programming model and based on the constraint condition, the air resistance, the heat conduction loss, the resistance under the reference working condition, the heat conduction value under the reference working condition, the first weight factor, and the second weight factor;

[0152] a structure parameter set determination unit configured to determine a super-hydrophobic surface structure parameter set based on the surface geometric features, the material properties, the surface structure minimum height, the macroscopic gutter curvature radius, and the microscopic column array diameter.

[0153] In some embodiments, the surface structure topography module 12 can specifically include:

[0154] an environmental load condition determination unit configured to determine an environmental load condition based on the environmental working condition matrix, and determine surface geometric features and material properties corresponding to the super-hydrophobic surface structure based on the super-hydrophobic surface structure parameter set, and then construct a mass matrix, a damping matrix, and a stiffness matrix based on the super-hydrophobic surface structure parameter set, the surface geometric features, and the material properties by using a preset matrix construction rule;

[0155] a structure vibration equation establishment unit configured to determine a liquid phase volume fraction, a fluid velocity vector field, a time advancement amount in transient simulation, and a preset Hamiltonian operator construction joint model corresponding to the super-hydrophobic surface structure, and determine a displacement vector, a velocity vector, an acceleration vector, an ice layer load force, and an aerodynamic load force corresponding to the super-hydrophobic surface structure based on the mass matrix, the damping matrix, and the stiffness matrix to establish a coupled structure vibration equation;

[0156] a vibration frequency determination unit configured to determine an equipment critical vibration frequency by using the joint model, a preset vibration frequency determination equation, and the coupled structure vibration equation based on the mass matrix, the environmental load condition, and the stiffness matrix.

[0157] In some embodiments, the surface structure topography module 12 can specifically include:

[0158] The scanning speed determination unit is configured to set the super-hydrophobic surface structure parameter set as a manufacturing reference, and then determine a scanning speed and a target coating thickness based on the manufacturing reference by using a preset laser scanning path adjustment strategy;

[0159] The scanning path determination unit is configured to set the equipment critical vibration frequency as a constraint condition, and then determine a scanning path corresponding to the time advancement amount by using a preset anti-resonance modulation mechanism and based on the constraint condition, the equipment critical vibration frequency, the scanning speed and the time advancement amount.

[0160] The reaction cycle number determination unit is configured to establish an atomic layer deposition thickness feedback control model, to determine a reaction cycle number corresponding to a complete scan by using the atomic layer deposition thickness feedback control model and a preset preparation process control system and based on the target coating thickness, the scanning speed and a current deposition cavity temperature, and obtain a current surface structure topography based on the reaction cycle number and the scanning path.

[0161] In some embodiments, the topography simulation error determination module 13 can specifically include:

[0162] The topography simulation error determination unit is configured to determine an actual surface structure topography corresponding to the super-hydrophobic surface structure, and determine a topography simulation error based on the current surface structure topography and the actual surface structure topography, and then determine an ice layer thickness increment, an ice layer containing phase difference, an ice layer free phase difference and a terahertz wave angular frequency in a preset time interval of the super-hydrophobic surface structure.

[0163] The ice growth rate determination unit is configured to determine the ice growth rate by using a preset target thickness detection function and based on the ice layer thickness increment, the ice layer containing phase difference, the ice layer free phase difference and the terahertz wave angular frequency in the preset time interval.

[0164] The strain field generation unit is configured to acquire an ice layer surface image by using a preset digital image correlation method, and obtain a first displacement field and a second displacement field corresponding to a horizontal direction and a vertical direction respectively by an image matching algorithm, and calculate a strain field of the ice layer on the super-hydrophobic surface structure in the horizontal direction based on the first displacement field and the second displacement field.

[0165] The ice adhesion work determination unit is configured to extract a critical debonding length corresponding to the strain field by using a preset control mechanical excitation frequency, and determine the ice adhesion work of the super-hydrophobic surface structure based on an ice layer elastic modulus corresponding to the super-hydrophobic surface structure and the ice layer thickness increment; wherein a value corresponding to the preset control mechanical excitation frequency is not greater than the equipment critical vibration frequency.

[0166] Further, the embodiments of the present application also disclose an electronic device,Figure 3 is shown according to an exemplary embodiment, and the content in the figure cannot be considered as any limitation to the application. The electronic device 20 can specifically include at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25 and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the related steps in the anti-icing test method for the super-hydrophobic surface structure of the energy equipment disclosed in any of the preceding embodiments. In addition, the electronic device 20 in the embodiment can be an electronic computer.

[0167] In the embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol followed by the communication interface 24 can be any communication protocol applicable to the technical solution of the application, which is not limited here; the input / output interface 25 is used to obtain external input data or output data to the outside, and the specific interface type can be selected according to the specific application needs, which is not limited here.

[0168] In addition, the memory 22 as a carrier of resource storage can be a read-only memory, a random access memory, a magnetic disk or an optical disk, etc., and the resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage mode can be temporary storage or permanent storage.

[0169] The operating system 221 is used to manage and control each hardware device on the electronic device 20 and the computer program 222, and can be Windows Server, Netware, Unix, Linux, etc. In addition to the computer program capable of completing the anti-icing test method for the super-hydrophobic surface structure of the energy equipment executed by the electronic device 20 disclosed in any of the preceding embodiments, the computer program 222 can further include a computer program capable of completing other specific work.

[0170] Further, the application also discloses a computer readable storage medium for storing a computer program; wherein the computer program is executed by the processor to implement the anti-icing test method for the super-hydrophobic surface structure of the energy equipment disclosed above. The specific steps of the method can refer to the corresponding content disclosed in the preceding embodiments, which will not be repeated here.

[0171] The various embodiments described in the specification are progressive in nature, and each embodiment highlights the differences from other embodiments. The same or similar parts among the various embodiments can be mutually referred to. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method part.

[0172] Those skilled in the art will further appreciate that the individual steps of the examples described in connection with the embodiments disclosed herein can be embodied in electronic hardware, computer software, or combinations of both. The various examples have been described in relation to the described embodiments, as a means of generalizing the interchangeability of hardware and software under the principles mentioned above. The particular implementation of an individual example in either hardware or software can be determined by the particular application and design constraints imposed on the overall system. Skilled artisans will appreciate that the principles described herein can be practiced in a variety of system environments, and that the described embodiments are merely examples and are not meant to limit the scope of the application.

[0173] The steps of a method or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module can reside in random access memory (RAM), flash memory, read-only memory (ROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0174] Finally, it needs to be pointed out that, in this document, the relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or device including the element.

[0175] The above describes the technical solutions provided by the present application in detail, and the principles and implementation manners of the present application are described by using specific examples. The above description of the embodiments is only used to help understand the method and core idea of the present application; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation manner and application range can be changed; and the above description of the specification should not be understood as limiting the present application.

Claims

1. A method for testing the anti-icing properties of superhydrophobic surface structures in energy equipment, characterized in that, include: An environmental feature map is constructed to characterize parameter changes in the target environment. Based on the environmental feature map, an environmental condition matrix including several combinations of environmental parameters is constructed. Then, the main environmental control factors affecting the anti-icing performance of the superhydrophobic surface structure are extracted from the environmental condition matrix. Based on the main environmental control factors, gradient fractal surface design is performed on the superhydrophobic surface structure of the energy equipment to obtain a set of superhydrophobic surface structure parameters. The target environment is an environment that meets the preset extreme environment judgment conditions. Based on the environmental condition matrix, the environmental load conditions are determined, and based on the superhydrophobic surface structure parameter set and the environmental load conditions, the superhydrophobic surface structure is subjected to fluid-structure-thermal coupling simulation to obtain the critical vibration frequency of the equipment. Then, the preset manufacturing process control system is used to perform laser scanning and simulation based on the superhydrophobic surface structure parameter set and the critical vibration frequency of the equipment to obtain the current surface structure morphology. Based on the current surface structure morphology and the actual surface structure morphology corresponding to the superhydrophobic surface structure, the morphology simulation error is determined. Based on the morphology simulation error, the superhydrophobic surface structure parameter set, the critical vibration frequency of the equipment, and the preset control mechanical excitation frequency, dynamic ice layer monitoring is performed on the superhydrophobic surface structure to obtain the corresponding ice growth rate and ice adhesion work.

2. The anti-icing test method for superhydrophobic surface structures of energy equipment according to claim 1, characterized in that, The construction of an environmental feature map to characterize parameter changes in the target environment, and the construction of an environmental condition matrix including several combinations of environmental parameters based on the environmental feature map, includes: Acquire monitoring data of the energy equipment under the target environment; the monitoring data includes temperature data, humidity data, wind speed data, droplet diameter data, superhydrophobic surface tilt angle data of the energy equipment, vibration spectrum data of the energy equipment, and solar radiation intensity data; Based on the value range corresponding to each of the monitoring data, the target equally probable division interval is determined, and the monitoring data is divided into several non-overlapping sub-intervals using the target equally probable division interval. Then, a preset number of sample values ​​are randomly selected from each of the sub-intervals according to a preset random sampling rule, and an environmental condition matrix is ​​constructed based on the preset number of sample values.

3. The anti-icing test method for superhydrophobic surface structures of energy equipment according to claim 2, characterized in that, The extraction of key environmental factors affecting the anti-icing performance of superhydrophobic surface structures from the environmental condition matrix includes: The temperature data in the environmental condition matrix is ​​determined, and the temperature difference between different spatial points in the superhydrophobic surface structure is determined based on the temperature data. Then, the temperature gradient is determined based on the spatial distance between different spatial points in the superhydrophobic surface structure and the corresponding temperature difference, so as to set the temperature gradient as the first environmental control factor. The wind speed data in the environmental condition matrix is ​​determined, and the kinetic energy ratio of each wind speed data is determined using a preset kinetic energy ratio calculation formula to obtain the kinetic energy ratio result. Then, the kinetic energy ratio result is set as the second environmental control factor. The vibration spectrum data of the energy equipment in the environmental condition matrix are determined, and the power density of each vibration spectrum data of the energy equipment is determined by a preset spectrum analysis method to obtain the corresponding vibration power density, and the vibration power density is set as the third environmental control factor.

4. The anti-icing test method for superhydrophobic surface structures of energy equipment according to claim 3, characterized in that, The gradient fractal surface design of the superhydrophobic surface structure of the energy equipment based on the environmental controlling factors yields a set of superhydrophobic surface structure parameters, including: Develop a biscale fractal model for determining the curvature radius of macroscopic guide channels and the diameter of microscopic columnar arrays, and a hybrid integer programming model for determining the parameter set of superhydrophobic surface structures; The apparent contact angle, Young's contact angle, intrinsic contact angle, maximum droplet diameter, and the proportion of ice occupying the superhydrophobic surface structure corresponding to the superhydrophobic surface structure are determined. The minimum height of the surface structure is determined based on the intrinsic contact angle and the maximum droplet diameter. Then, the constraint conditions are determined based on the apparent contact angle, Young's contact angle, and the proportion. Determine the air resistance, heat conduction loss, resistance under reference conditions, and heat conduction value under reference conditions corresponding to the superhydrophobic surface structure, and determine the first weighting factor corresponding to the air resistance and the second weighting factor corresponding to the heat conduction loss; The curvature radius of the macroscopic guide channel and the diameter of the microscopic columnar array are determined using the dual-scale fractal model and based on the tilt angle data of the superhydrophobic surface of the energy equipment and the wind speed data. Then, the surface geometric features and material properties are determined using the mixed integer programming model and based on the constraints, air resistance, heat conduction loss, resistance under the reference condition, heat conduction value under the reference condition, the first weighting factor and the second weighting factor. The set of superhydrophobic surface structure parameters is determined based on the surface geometry, material properties, minimum height of the surface structure, radius of curvature of the macroscopic channel, and diameter of the microscopic columnar array.

5. The anti-icing test method for superhydrophobic surface structures of energy equipment according to claim 4, characterized in that, The process of determining environmental load conditions based on the environmental condition matrix, and performing fluid-structure-thermal coupling simulation on the superhydrophobic surface structure based on the superhydrophobic surface structure parameter set and the environmental load conditions to obtain the critical vibration frequency of the equipment includes: The environmental load conditions are determined based on the environmental condition matrix, and the surface geometric features and material properties corresponding to the superhydrophobic surface structure are determined based on the superhydrophobic surface structure parameter set. Then, the mass matrix, damping matrix and stiffness matrix are constructed using the preset matrix construction rules based on the superhydrophobic surface structure parameter set, the surface geometric features and the material properties. A joint model is constructed by determining the liquid volume fraction, fluid velocity vector field, time advance in transient simulation, and preset Hamiltonian operator corresponding to the superhydrophobic surface structure. Based on the mass matrix, damping matrix, and stiffness matrix, the displacement vector, velocity vector, acceleration vector, ice load force, and aerodynamic load force corresponding to the superhydrophobic surface structure are determined to establish the vibration equation of the coupled structure. The critical vibration frequency of the equipment is determined by using the joint model, the preset vibration frequency determination equation, and the coupled structure vibration equation, based on the mass matrix, the environmental load conditions, and the stiffness matrix.

6. The anti-icing test method for superhydrophobic surface structures of energy equipment according to claim 5, characterized in that, The process involves using a preset fabrication process control system and performing laser scanning and simulation based on the superhydrophobic surface structure parameter set and the critical vibration frequency of the equipment to obtain the current surface structure morphology, including: The superhydrophobic surface structure parameter set is set as the manufacturing benchmark, and then the scanning speed and target coating thickness are determined based on the preset laser scanning path adjustment strategy and the manufacturing benchmark. The critical vibration frequency of the equipment is set as a constraint condition. Then, a preset anti-resonance modulation mechanism is used to determine the scanning path corresponding to the time advance amount based on the constraint condition, the critical vibration frequency of the equipment, the scanning speed, and the time advance amount. An atomic layer deposition thickness feedback control model is established to utilize the atomic layer deposition thickness feedback control model and a preset preparation process control system to determine the number of reaction cycles corresponding to the completion of the scan based on the target coating thickness, the scanning speed and the current deposition chamber temperature, and to obtain the current surface structure morphology based on the number of reaction cycles and the scanning path.

7. The anti-icing test method for the superhydrophobic surface structure of energy equipment according to any one of claims 1 to 6, characterized in that, The process involves determining the morphology simulation error based on the current surface morphology and the actual surface morphology corresponding to the superhydrophobic surface structure, and dynamically monitoring the ice layer of the superhydrophobic surface structure based on the morphology simulation error, the superhydrophobic surface structure parameter set, the critical vibration frequency of the equipment, and the preset control mechanical excitation frequency to obtain the corresponding ice growth rate and ice adhesion work, including: The actual surface structure morphology corresponding to the superhydrophobic surface structure is determined, and the morphology simulation error is determined based on the current surface structure morphology and the actual surface structure morphology. Then, the ice layer thickness increment, ice-containing phase difference, ice-free phase difference and terahertz wave angular frequency are determined within a preset time interval of the superhydrophobic surface structure. The ice growth rate is determined by using a preset target thickness detection function and based on the ice layer thickness increment within the preset time interval, the phase difference of the ice-containing layer, the phase difference of the ice-free layer, and the terahertz wave angular frequency. Images of the ice surface are acquired using a preset digital image correlation method, and a first displacement field and a second displacement field corresponding to the horizontal and vertical directions are obtained by an image matching algorithm. Based on the first displacement field and the second displacement field, the strain field of the ice layer on the superhydrophobic surface structure in the horizontal direction is calculated. The critical debonding length corresponding to the strain field is extracted using a preset controlled mechanical excitation frequency, and the ice adhesion work of the superhydrophobic surface structure is determined based on the ice layer elastic modulus corresponding to the superhydrophobic surface structure and the ice layer thickness increment; wherein, the value corresponding to the preset controlled mechanical excitation frequency is not greater than the critical vibration frequency of the equipment.

8. A superhydrophobic surface structure anti-icing testing device for energy equipment, characterized in that, include: The feature map construction module is used to construct an environmental feature map to characterize the parameter changes of the target environment, and to construct an environmental condition matrix including several combinations of environmental parameters based on the environmental feature map. Then, the main environmental control factors affecting the anti-icing performance of the superhydrophobic surface structure are extracted from the environmental condition matrix, and gradient fractal surface design is performed on the superhydrophobic surface structure of the energy equipment based on the main environmental control factors to obtain a set of superhydrophobic surface structure parameters. The surface structure morphology determination module is used to determine the environmental load conditions based on the environmental condition matrix, and to perform fluid-structure-thermal coupling simulation on the superhydrophobic surface structure based on the superhydrophobic surface structure parameter set and the environmental load conditions to obtain the critical vibration frequency of the equipment. Then, the module uses a preset manufacturing process control system and performs laser scanning and simulation based on the superhydrophobic surface structure parameter set and the critical vibration frequency of the equipment to obtain the current surface structure morphology. The morphology simulation error determination module is used to determine the morphology simulation error based on the current surface structure morphology and the actual surface structure morphology corresponding to the superhydrophobic surface structure, and to perform dynamic ice layer monitoring on the superhydrophobic surface structure based on the morphology simulation error, the superhydrophobic surface structure parameter set, the critical vibration frequency of the equipment and the preset control mechanical excitation frequency, so as to obtain the corresponding ice growth rate and ice adhesion work.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the anti-icing test method for the superhydrophobic surface structure of energy equipment as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store a computer program, wherein the computer program, when executed by a processor, implements the anti-icing test method for superhydrophobic surface structures of energy equipment as described in any one of claims 1 to 7.

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