Prediction method and system for spraying thickness uniformity of anticorrosive coating of offshore wind turbine tower drum

Abstract

The invention relates to an offshore wind turbine tower anticorrosive coating spraying thickness uniformity prediction method and system, and relates to the technical field of coating repair treatment.The method comprises the steps that firstly, a single-point spraying material adhesion amount model of a tower is established according to relevant parameters during spraying so as to reduce single-point prediction errors; then, a spraying track is deeply researched and analyzed, and a discretization technology is utilized to discretize a curved surface corresponding to the surface of the tower drum into grid units; and finally, realizing thickness and uniformity prediction by utilizing a three-dimensional curved surface superposition algorithm, predicting the coating thickness of each grid unit, and determining the total thickness of the coating through accumulated integration, so as to generate a thickness distribution cloud picture. Therefore, the method can accurately quantify the influence of complex geometric features on coating diffusion, predicts the coating thickness distribution of a complex curved surface through the track superposition and curved surface projection technology, achieves accurate uniformity quantitative evaluation, and achieves high-consistency thickness prediction from local to overall.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of coating repair processing, in particular to a method and system for predicting the uniformity of the spraying thickness of offshore wind turbine tower anticorrosive coating. BACKGROUND

[0002] In the related art, the wind turbine tower (offshore wind turbine tower) is an important component of the wind power generation system. It is exposed to harsh natural environments for a long time, such as strong winds, salt spray, ultraviolet radiation, and extreme temperature differences. These factors pose a serious challenge to the material and structure of the tower. Therefore, effective corrosion protection measures are crucial to ensure the safe operation of the wind turbine tower, prolong its service life, and improve the overall economic benefits of the wind power project.

[0003] Coating corrosion is the most widely used and mature method of wind turbine tower corrosion protection. This method forms a physical barrier by coating one or more layers of anticorrosive paint on the surface of the tower, thereby isolating the tower substrate from direct contact with the external corrosive environment, achieving the purpose of corrosion protection. In the field of offshore wind turbine tower anticorrosive coating spraying, the prediction of coating thickness and uniformity is crucial to ensure corrosion protection performance.

[0004] The existing anticorrosive coating thickness and uniformity prediction method uses a simplified circular or elliptical spraying cross-section model to directly predict the thickness during spraying and perform material spraying. However, the existing technology does not consider the influence of curved surface geometry on material diffusion, and there is no corresponding in-depth study of the influence of some related parameters (such as spraying distance, related parameters of the spray gun, etc.) during spraying, resulting in large thickness prediction errors and the inability to accurately predict thickness and uniformity. SUMMARY

[0005] The present application provides a method and system for predicting the uniformity of the spraying thickness of offshore wind turbine tower anticorrosive coating. By using trajectory superposition and curved surface projection technology, the coating thickness distribution of complex curved surfaces is predicted, accurate uniformity quantitative evaluation is achieved, and high consistency thickness prediction from local to global is realized, solving the problem that existing technology cannot accurately predict thickness and uniformity.

[0006] In a first aspect, the present application provides a method for predicting the uniformity of the spraying thickness of offshore wind turbine tower anticorrosive coating, comprising:

[0007] Based on fluid dynamics and boundary layer theory, a single-point spraying thickness distribution function for offshore wind turbine tower anticorrosive coating is established, and a single-point spraying material adhesion amount model is obtained;

[0008] The single-point spraying material adhesion amount model is subjected to spraying trajectory superposition analysis, and the spraying trajectory during anticorrosive spraying of the offshore wind turbine tower is obtained;

[0009] Discretely analyze a tower surface of the offshore wind turbine tower according to each spraying trajectory, and discretize each curved surface of the tower surface into a grid unit;

[0010] Analyze coating thickness and uniformity of each grid unit by using a three-dimensional curved surface superposition algorithm, and predict total coating thickness during spraying;

[0011] Map total coating thickness of the grid unit to a three-dimensional curved surface, and generate a thickness distribution cloud map.

[0012] Optionally, a single-point spraying thickness distribution function for the offshore wind turbine tower corrosion-resistant coating is established based on fluid dynamics and boundary layer theory, and a single-point spraying material adhesion amount model is obtained, including:

[0013] Based on fluid dynamics and boundary layer theory, according to A single-point spraying thickness distribution function is established, and a single-point spraying material adhesion amount model is obtained;

[0014] Wherein, h(r, θ) refers to the layer thickness when the radial distance of the spraying point is r and the inclination angle of the spray gun is θ, Q is the coating flow rate affecting the coating deposition rate, v is the spray gun moving speed affecting the local coating thickness, h0 is the reference thickness, R0 is the peak radius, σ r is the radial diffusion coefficient, and σ θ is the tangential diffusion coefficient.

[0015] Optionally, the single-point spraying material adhesion amount model is subjected to spraying trajectory superposition analysis, and a spraying trajectory for corrosion-resistant spraying of the offshore wind turbine tower is obtained, including:

[0016] According to the preset thickness fluctuation of the overlapping area and the trajectory superposition relationship, the trajectory information of the single-point spraying material adhesion model is analyzed by using the trajectory superposition principle, and the spraying trajectory is obtained;

[0017] Based on the spraying trajectory, the spraying trajectory is updated according to the preset row spacing dynamic adjustment rule for uniformity adjustment.

[0018] Optionally, based on the spraying trajectory, the spraying trajectory is updated according to the preset row spacing dynamic adjustment rule for uniformity adjustment, including:

[0019] Based on the spraying trajectory, analyze the region type of the offshore wind turbine tower surface region, and the region type includes a flat region and a high-curvature region;

[0020] According to the preset dynamic adjustment rule, the spraying trajectory of the flat region is subjected to uniformity adjustment, and the spraying trajectory of the high-curvature region is subjected to local curvature adjustment, and each spraying trajectory is updated.

[0021] Optionally, according to each of the spraying trajectories, the tower surface of the offshore wind turbine tower is discretely analyzed, and each curved surface of the tower surface is discretized into a grid unit, comprising:

[0022] Based on the discretization processing of each of the spraying trajectories, a discrete path point is obtained, and the discrete path point corresponds to a local spraying parameter;

[0023] A curved surface parameterization technology is used to map the discrete path point to a three-dimensional grid corresponding to the tower surface of the offshore wind turbine tower, and a grid unit discretized by a curved surface is constructed;

[0024] The shape type of the grid unit includes a triangular grid and a quadrilateral grid, each of the grid units records a local curvature, a normal vector, and a spraying parameter, and the grid unit corresponds to a curved surface area of the tower surface one by one.

[0025] Optionally, a curved surface parameterization technology is used to map the discrete path point to a three-dimensional grid corresponding to the tower surface of the offshore wind turbine tower, and a grid unit discretized by a curved surface is constructed, comprising:

[0026] A curved surface parameterization technology is used to construct a curved surface model of the offshore wind turbine tower, and the curved surface of the tower surface in the curved surface model is discretized into a grid unit;

[0027] Each of the discrete path points is mapped to the corresponding grid unit, and each of the grid units is updated.

[0028] Optionally, a three-dimensional curved surface superposition algorithm is used to analyze the coating thickness and uniformity of each of the grid units, and the total coating thickness during spraying is predicted, comprising:

[0029] Based on the cumulative integration of the curved surface grid, the single-point spraying thickness distribution function is used to calculate the coating thickness of each of the grid units;

[0030] The overlapping area of each of the grid units during spraying is analyzed, and based on the coating thickness, the coating is superimposed on the overlapping area through numerical integration, and the total coating thickness related to uniformity is calculated.

[0031] Optionally, based on the cumulative integration of the curved surface grid, the single-point spraying thickness distribution function is used to calculate the coating thickness of each of the grid units, comprising:

[0032] Based on each of the grid units, a single-point spraying influence domain modeling is performed using a single-point spraying thickness distribution function, and the influence domain of single-point spraying is defined as a dynamic elliptical area, the long axis direction of the dynamic elliptical area is consistent with the moving direction of the spray gun, and the short axis is determined based on the coating diffusion characteristics;

[0033] In the dynamic elliptical area, the coating material generated by a single discrete path point is calculated and the coating thickness of the corresponding grid unit is updated.

[0034] Optionally, analyzing the overlapping areas of the grid units during spraying, and performing coating superposition on the overlapping areas by numerical integration based on the coating thickness, to calculate the total coating thickness related to uniformity, including:

[0035] Based on the coating thickness of each grid unit, Calculate the contribution of all spray points covering the same grid cell to obtain the total thickness;

[0036] Among them, G i represents the i-th grid unit, and N represents the covering grid G i Number of spray points, A j ∩G i Represents the influence area of ​​the j-th spraying point and the grid unit G i The intersection area, k represents the surface curvature, κ j represents the local curvature at the j-th spraying point.

[0037] In a second aspect, the present application provides a system for predicting the thickness uniformity of anti-corrosion coating spraying on offshore wind turbine towers, comprising:

[0038] A single-point spray model construction module is used to establish a single-point spray thickness distribution function for the anti-corrosion coating on offshore wind turbine towers based on fluid dynamics and boundary layer theory, and to obtain a single-point spray material adhesion model;

[0039] a spray trajectory superposition analysis module, configured to perform spray trajectory superposition analysis on the single-point spray material attachment amount model to obtain a spray trajectory when performing anti-corrosion spraying on the offshore wind turbine tower;

[0040] a discrete analysis module, configured to perform discrete analysis on the tower surface of the offshore wind turbine tower according to each of the spraying trajectories, and discretize each curved surface of the tower surface into grid units;

[0041] A coating thickness prediction module is used to analyze the coating thickness and uniformity of each grid unit using a three-dimensional surface superposition algorithm to predict the total coating thickness during spraying;

[0042] A mapping module is used to map the total coating thickness accumulated by the grid cells to a three-dimensional surface to generate a thickness distribution cloud map.

[0043] In summary, the embodiment of the present application firstly establishes a single-point spraying material adhesion amount model of the tower drum according to the related parameters during spraying, so as to reduce the single-point prediction error. Then, the spraying trajectory is analyzed in depth, and the corresponding curved surface of the tower drum surface is discretized into grid units by using the discretization technology. Finally, the thickness and uniformity prediction is realized by using the three-dimensional curved surface superposition algorithm, the coating thickness of each grid unit is predicted, and the total coating thickness is determined by integral accumulation, so as to generate a thickness distribution cloud diagram. On the one hand, the present application quantifies the influence of complex geometric characteristics on coating diffusion, and establishes a single-point spraying material adhesion amount model, so as to break through the limitation of the traditional static model and significantly improve the single-point spraying thickness prediction accuracy. On the other hand, the present application predicts the coating thickness distribution of the complex curved surface by using the trajectory superposition and curved surface projection technology, realizes the accurate uniformity quantitative evaluation, realizes the high consistency thickness prediction from the local to the whole, and solves the problem that the prior art cannot accurately predict the thickness and uniformity. BRIEF DESCRIPTION OF DRAWINGS

[0044] The accompanying drawings, which are incorporated into and form a part of the specification, illustrate an embodiment consistent with the present application and, together with the description, serve to explain the principles of the application.

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0046] Figure 1 A flowchart of a marine wind turbine tower anticorrosion coating spraying thickness uniformity prediction method provided by an embodiment of the present application;

[0047] Figure 2 A step flowchart of a marine wind turbine tower anticorrosion coating spraying thickness uniformity prediction method provided by an optional embodiment of the present application;

[0048] Figure 3 A single-point coating thickness distribution diagram provided by an example of the present application;

[0049] Figure 4 A coating superposition diagram provided by an example of the present application;

[0050] Figure 5 A thickness distribution cloud diagram provided by an example of the present application;

[0051] Figure 6 A structural block diagram of a marine wind turbine tower anticorrosion coating spraying thickness uniformity prediction system provided by an embodiment of the present application. DETAILED DESCRIPTION

[0052] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0053] In order to facilitate the understanding of the embodiments of the present application, further explanation and description will be made below in combination with the drawings and specific embodiments, and the embodiments do not constitute a limitation on the embodiments of the present application.

[0054] Figure 1 A flowchart of a method for predicting the uniformity of the spraying thickness of a corrosion-resistant coating of an offshore wind turbine tower provided by the embodiments of the present application is shown in FIG. 1. As shown in FIG. 1, the method for predicting the uniformity of the spraying thickness of the corrosion-resistant coating of the offshore wind turbine tower provided by the embodiments of the present application can specifically include the following steps: Figure 1

[0055] Step 110: Based on the fluid dynamics and the boundary layer theory, a single-point spraying thickness distribution function for the corrosion-resistant coating of the offshore wind turbine tower is established to obtain a single-point spraying material adhesion amount model.

[0056] Step 120: The single-point spraying material adhesion amount model is subjected to spraying trajectory superposition analysis to obtain the spraying trajectory when the offshore wind turbine tower is subjected to corrosion-resistant spraying.

[0057] Step 130: According to each spraying trajectory, the tower surface of the offshore wind turbine tower is subjected to discrete analysis, and each curved surface of the tower surface is discretized into a grid unit.

[0058] Step 140: A three-dimensional curved surface superposition algorithm is used to analyze the coating thickness and uniformity of each grid unit to predict the total coating thickness when spraying.

[0059] Step 150: The total coating thickness accumulated by the grid unit is mapped to a three-dimensional curved surface to generate a thickness distribution cloud chart.

[0060] The steps 110-150 are described uniformly as follows:

[0061] ​In a specific implementation, the embodiment first establishes a single-point spraying thickness distribution function based on fluid dynamics and boundary layer theory, with spraying dynamics parameters during material spraying, and fuses the surface curvature of the tower drum, and the like, to build a single-point spraying material adhesion amount model (which can be referred to as a single-point spraying model). The single-point spraying model is used as an optimization model, fully considers the influence of surface geometric features on material diffusion, and the multi-parameter coupling mechanism of multiple process parameters (such as spraying distance, spraying speed, coating viscosity, and the like), and effectively reduces the single-point prediction error.

[0062] Then, based on the built single-point spraying model, the spraying trajectory during spraying is analyzed by using the trajectory superposition principle, and the trajectory overlapping condition is analyzed. The thickness of the overlapping area between different spraying trajectories and the single-point spraying is analyzed to optimize and update the spraying trajectory. Subsequently, the spraying related parameters are analyzed according to the spraying trajectory, which can include but is not limited to: flow, speed, inclination angle, and related data during spraying (such as the influence area during single-point spraying), and the like. The curved surface of the tower drum is discretized into grid units, and the spraying parameters are updated to the corresponding grid units, so as to calculate the thickness of the coating of a single grid unit. Through iterative calculation, the coating thickness corresponding to all grid units can be obtained. Finally, by using a three-dimensional curved surface superposition algorithm, such as a superposition integral formula, the coating thickness and uniformity of the grid units are predicted and analyzed, including the influence area during spraying of different grid units, and the like, to obtain the total coating thickness, effectively quantifying the coating distribution difference on the three-dimensional curved surface. The total coating thickness is mapped to the three-dimensional area, and a thickness distribution cloud map can be generated.

[0063] It can be seen that the embodiment of the application breaks through the limitations of the traditional static model and significantly improves the single-point spraying thickness prediction accuracy. Based on the dynamic material deposition equation and the curved surface adaptive integral algorithm, the influence of complex geometric features on coating diffusion can be accurately quantified, effectively solving the deviation problem of the prior art in predicting the coating thickness uniformity in the concave-convex surface and weld area, and realizing high-consistency thickness prediction from local to global.

[0064] Referring to Figure 2 , a step flowchart of a method for predicting the spraying thickness uniformity of the offshore wind turbine tower drum corrosion-resistant coating is shown. The method can specifically include the following steps:

[0065] In step 210, a single-point spraying thickness distribution function for the offshore wind turbine tower drum corrosion-resistant coating is established based on fluid dynamics and boundary layer theory, and a single-point spraying material adhesion amount model is obtained.

[0066] In the related art, for single-point spraying prediction, the existing technical solutions mainly use a simplified spraying cross-section model, but do not consider the influence of the geometric characteristics of the curved surface on material diffusion, resulting in a large thickness prediction error. Some existing solutions also have independent influence analysis for parameters such as spraying distance, spraying gun moving speed, and coating viscosity, but do not deeply explore the mechanism of the coupling effect of multiple parameters. For example, when the wind speed and the spraying distance change at the same time, the complexity of the coating diffusion law causes the existing model to fail.

[0067] To solve the above technical problems, the embodiment deeply studies the influence of the geometric characteristics of the curved surface on material diffusion, and deeply studies the synergistic effect of multiple process parameters, explores the mechanism of the coupling effect of multiple parameters, analyzes the mutual influence between different parameters, and the complexity of the coating diffusion law. Specifically, the embodiment deeply analyzes the influence of the coating characteristics, the related parameters of the spraying gun during spraying, the coating and air pressure parameters, the influence of the diffusion coefficient in different directions, and the influence of the curvature of the curved surface on diffusion, so as to obtain the coupling of multiple parameters. Based on the fluid dynamics and boundary layer theory, a dynamic material deposition equation is used to establish a single-point spraying thickness distribution function and obtain a single-point spraying model. In the embodiment, the single-point spraying model fuses the curvature of the curved surface, the spraying angle, the coating viscosity, etc. as a multi-parameter coupling model, which can significantly improve the single-point spraying thickness prediction accuracy, accurately quantify the influence of complex geometric characteristics on coating diffusion, and ensure the usability of the model.

[0068] Optionally, the embodiment of the application establishes a single-point spraying thickness distribution function for offshore wind turbine tower corrosion-resistant coating based on fluid dynamics and boundary layer theory, and obtains a single-point spraying material deposition amount model, which can include: based on fluid dynamics and boundary layer theory, according to A single-point spraying thickness distribution function is established to obtain a single-point spraying material deposition amount model; wherein h(r, θ) refers to the layer thickness when the radial distance of the spraying point is r and the spraying gun angle is θ, Q is the coating flow rate affecting the coating deposition rate, v is the spraying gun moving speed affecting the local coating thickness, h0 is the reference thickness, R0 is the peak radius, σ r is the radial diffusion coefficient, and σ θ is the tangential diffusion coefficient.

[0069] To realize the coupling of multiple parameters and construct a single-point spraying thickness distribution function that can accurately predict the spraying thickness, the embodiment uses a dynamic material deposition equation, that is, the formula of the above embodiment.

[0070] The parameters of the formula in the above embodiment are explained as follows:

[0071] h(r, θ), unit: μm; paint flow rate Q, unit: mL / min; spray gun moving speed v, unit: m / s, the local thickness increases when the speed v decreases; reference thickness h0, unit: μm, determined by paint properties (such as solid content) and air pressure parameters; peak radius R0, unit: m, a function of spray distance d, and satisfies R0 = 0.2d; radial diffusion coefficient σ r , unit: m, affected by spray inclination θ (unit: °) and curvature κ; tangential diffusion coefficient σ θ , unit: m, is the diffusion range perpendicular to the spray gun moving direction. Wherein, curvature κ, unit: m -1 , convex (κ > 0) expands diffusion, concave (κ < 0) inhibits diffusion.

[0072] Wherein, parameters such as spray gun inclination, spray gun moving speed, air pressure parameters, spray gun moving direction, curvature, spray distance, etc. can be measured and obtained by sensors, inclination gyroscopes, laser range finders and other equipment.

[0073] Step 220, according to the preset thickness fluctuation of the overlapping area and the trajectory superposition relationship, the trajectory information of the single-point spraying material adhesion model is analyzed by using the trajectory superposition principle to obtain the spraying trajectory.

[0074] In a specific implementation, by using the established single-point spraying model, the coating superposition and row spacing optimization method is used to analyze the spraying trajectory and the area superposition.

[0075] Firstly, in the single-point spraying model, the spraying trajectory is analyzed by using the trajectory superposition principle, including the row spacing of adjacent spraying trajectories, and the single-point spraying radius is analyzed. Then, according to the analyzed spraying trajectory and single-point spraying radius, the area thickness fluctuation is determined.

[0076] In actual implementation, the row spacing S of adjacent trajectories and the single-point spraying radius R satisfy the relationship (trajectory superposition relationship): S = 0.7R, so as to ensure that the fluctuation of the overlapping area is ≤5%, and the optimized spraying trajectory is obtained.

[0077] Step 230, based on the spraying trajectory, the uniformity is adjusted according to the preset row spacing dynamic adjustment rule, and the spraying trajectory is updated.

[0078] In actual implementation, the trajectory adjustment algorithm is updated based on the consideration of uniform coverage and diffusion difference, and the curvature of different areas of the tower drum surface is fully considered. The row spacing dynamic adjustment rule is constructed. The spraying trajectory is analyzed by using the rule, the spraying trajectory is adjusted, including adjusting the row spacing between adjacent spraying trajectories, such as expanding the row spacing, fixing the row spacing, and reducing the row spacing, etc., so as to update the spraying trajectory.

[0079] In an optional embodiment, the above-mentioned dynamic adjustment of uniformity based on the spraying trajectory according to the preset row spacing adjustment rule updates the spraying trajectory, and specifically can include: based on the spraying trajectory, analyzing the region type of the offshore wind turbine tower surface region, the region type including a flat region and a high-curvature region; according to the preset dynamic adjustment rule, adjusting the spraying trajectory of the flat region for uniformity, and adjusting the spraying trajectory of the high-curvature region for local curvature, updating each spraying trajectory.

[0080] Specifically, the curved surface region of the tower surface exists in two types, i.e. flat region and high-curvature region. This embodiment respectively presets the corresponding dynamic adjustment rule for the flat region and the high-curvature region. For the flat region, it is generally necessary to ensure the uniformity coverage of the flat region, so the row spacing of the flat region is fixed as 0.7R. For the high-curvature region, the curvature affects the diffusion coefficient. When the curvature is high (convex), the diffusion of the coating is enlarged when the material is sprayed, and when the curvature is low (concave), the diffusion is inhibited. Therefore, the row spacing of the high-curvature region is adjusted according to the local curvature κ. Specifically, for every increase of 0.1mm -1 , the row spacing is reduced by 5%-10% to compensate for the diffusion difference. Finally, the spraying trajectory is updated by using the dynamic adjustment of the row spacing.

[0081] Thus, in view of the problem in the related art that the spraying uniformity evaluation mainly relies on manual sampling detection or two-dimensional image gray scale analysis, and the coating distribution difference on the three-dimensional curved surface cannot be quantified, this embodiment fully analyzes the diffusion difference of different curvature surfaces on the three-dimensional curved surface to represent the coating distribution difference, and solves the problem of uneven coating distribution thickness.

[0082] Step 240: based on each spraying trajectory, discrete path points are obtained through discretization processing.

[0083] The discrete path points correspond to local spraying parameters.

[0084] Step 250: using a curved surface parameterization technology, the discrete path points are mapped to a three-dimensional grid corresponding to the tower surface of the offshore wind turbine tower, and a grid unit of the curved surface is constructed.

[0085] The shape type of the grid unit includes a triangular grid and a quadrilateral grid, and each grid unit records local curvature, a normal vector and spraying parameters. The grid unit corresponds to the curved surface region of the tower surface one by one.

[0086] The steps 240-250 are described uniformly as follows:

[0087] In a specific implementation, the present embodiment discretizes the spraying trajectory into path points, each of which corresponds to local spraying parameters (flow rate, speed, inclination). Then, the NURBS surface parameterization technology is used to discretize the surface of the tower drum into grid cells, each of which is a three-dimensional grid. The discrete path points are mapped to the three-dimensional grid, so that each grid cell can correspond to a coating thickness, and the thickness of the grid cell can be calculated subsequently.

[0088] Optionally, the present embodiment uses the surface parameterization technology to map the discrete path points to the three-dimensional grid corresponding to the tower surface of the offshore wind turbine tower drum, and constructs the grid cells discretized by the surface. This can include: using the surface parameterization technology to construct a surface model of the offshore wind turbine tower drum, and discretizing the surface of the tower surface in the surface model into grid cells; mapping each of the discrete path points to the corresponding grid cell, and updating each of the grid cells.

[0089] Step 260, based on the cumulative integration of the surface grid, the coating thickness of each grid cell is calculated using the single-point spraying thickness distribution function.

[0090] Reference Figure 3 In the present embodiment, since the discrete path points have been mapped to the three-dimensional grid, each grid cell has corresponding spraying parameters, i.e. each grid cell records local curvature, normal vector and spraying parameters. Therefore, based on the parameters recorded by each grid cell, the single-point spraying thickness distribution function can be used to calculate the coating thickness corresponding to each grid cell. Each grid cell can correspond to a coating thickness.

[0091] In an optional embodiment, the above-mentioned cumulative integration based on the surface grid uses the single-point spraying thickness distribution function to calculate the coating thickness of each grid cell, which can specifically include: based on each of the grid cells, using the single-point spraying thickness distribution function to model the single-point spraying influence domain, defining the influence domain of single-point spraying as a dynamic elliptical region, the long axis direction of the dynamic elliptical region is consistent with the moving direction of the spray gun, and the short axis is determined based on the coating diffusion characteristics; within the dynamic elliptical region, the coating material generated by a single discrete path point is calculated, and the coating thickness of the corresponding grid cell is updated.

[0092] In the specific implementation, when calculating the coating thickness of the grid unit, the single-point spraying influence domain modeling is mainly used for analysis, and the influence domain of the spray diffusion during single-point spraying is defined as a dynamic elliptical area. The dynamic elliptical area is divided into the major axis (ellipse major axis) direction area and the minor axis (ellipse minor axis) direction area. The major axis direction is consistent with the direction of movement of the spray gun, and the minor axis direction is mainly determined by the diffusion characteristics of the coating. Then, within the dynamic elliptical area, with the relevant parameters as input, the single-point spraying thickness distribution function is used to calculate the coating material generated by a single discrete path point and update the coating thickness of the corresponding grid unit.

[0093] In actual implementation, this embodiment obtains the coating thickness of all grids on the entire surface by iteratively calculating the coating materials generated by all path points.

[0094] Therefore, this embodiment implements a three-dimensional uniformity prediction algorithm: through trajectory superposition and surface projection technology, the coating thickness distribution of complex surfaces is predicted, and uniformity quantitative evaluation is achieved. The influence of complex geometric features on coating diffusion can be accurately quantified, and the prediction deviation problem of existing technologies in concave and convex surfaces, welds and other areas can be effectively solved, and highly consistent thickness prediction from local to overall is achieved.

[0095] Step 270 , analyzing the overlapping areas of the grid units during spraying, and based on the coating thickness, performing coating superposition on the overlapping areas by numerical integration to calculate the total coating thickness related to uniformity.

[0096] In the specific implementation, refer to Figure 4 As shown, this embodiment analyzes the overlapping area between the grid units of each adjacent spraying point, and superimposes the coating interfaces of the adjacent spraying points within the grid (such as Figure 4 Then, the overlapping area is integrated and the total thickness is calculated by numerical integration to obtain the coating superposition result (refer to Figure 4 As shown in the figure on the right), this can eliminate local overspray or underspray.

[0097] Optionally, the embodiment of the present application analyzes the overlapping area of ​​each grid unit during spraying, and based on the coating thickness, performs coating superposition on the overlapping area by numerical integration to calculate the total coating thickness related to uniformity, which may specifically include: taking the coating thickness of each grid unit as a reference, according to Calculate the contribution value of all spray points covering the same grid unit to get the total thickness; where G i represents the i-th grid unit, and N represents the covering grid G i Number of spray points, A j ∩G i Represents the influence area of ​​the j-th spraying point and the grid unit G i The intersection area, κ represents the surface curvature, κj Rj represents the local curvature at the jth spraying point.

[0098] In this embodiment, in order to accurately quantify the influence of complex geometric features on coating diffusion, predict the coating thickness distribution of complex surfaces, and realize uniformity quantitative evaluation, for each grid cell G i , first, all spraying points affecting the grid cell are analyzed and determined, and the influence domain of each spraying point, i.e. other grid cells affected by the spraying point, is further analyzed to determine the intersection area thereof with the grid cell G i . Then, the local curvature at the spraying point is analyzed. With the local curvature and the intersection area as inputs, the contribution values of all spraying points covering the cell are calculated according to the formula , and the cumulative thickness h total (coating total thickness) is calculated by superposition.

[0099] Thus, based on the dynamic material deposition equation and the surface adaptive integral algorithm, the embodiment can accurately quantify the influence of complex geometric features on coating diffusion, effectively solve the prediction deviation problem of the prior art in concave-convex surfaces and welds, and realize high-consistency thickness prediction from the local to the whole.

[0100] Step 280: mapping the coating total thickness accumulated by the grid cell to a three-dimensional surface to generate a thickness distribution cloud chart.

[0101] In a specific implementation, referring to Figure 5 , the cumulative thickness h total is mapped to a three-dimensional surface to generate a thickness distribution cloud chart.

[0102] To sum up, the embodiment of the application firstly establishes a single-point spraying material adhesion amount model of the tower drum according to the related parameters during spraying, so as to reduce the single-point prediction error. Then, the spraying trajectory is deeply researched and analyzed, and the discrete technology is used to discretize the corresponding curved surface of the tower drum surface into grid units. Finally, the three-dimensional curved surface superposition algorithm is used to realize thickness and uniformity prediction, predict the coating thickness of each grid unit, and determine the total thickness of the coating by integral calculation, so as to generate a thickness distribution cloud chart. It can be seen that the embodiment of the application realizes: ①improve the single-point spraying model precision: establish a coating adhesion amount model integrating the curvature of the curved surface and the spraying dynamics parameters, accurately quantify the influence of complex geometric features on the coating diffusion, break through the limitations of the traditional static model, and reduce the single-point prediction error; ②realize dynamic parameter adaptive correction: integrate various sensors, inclinometer and laser range finder, construct a real-time parameter feedback mechanism, obtain parameters such as spraying gun moving speed, coating flow, air pressure parameter, spraying gun spraying angle, etc., and use them to construct a single-point spraying thickness distribution function, so as to improve the precision; ③develop a three-dimensional uniformity prediction algorithm: predict the coating thickness distribution of the complex curved surface through the trajectory superposition and curved surface projection technology, realize the quantitative evaluation of the uniformity, realize the high consistency thickness prediction from the local to the whole, and solve the problem that the prior art cannot accurately predict the thickness and uniformity.

[0103] It should be noted that, for the method embodiment, in order to simply describe, it is expressed as a series of action combinations, but those skilled in the art should know that the embodiment of the application is not limited by the described action sequence, because according to the embodiment of the application, certain steps can be performed in other order or simultaneously.

[0104] As shown in Figure 6 The embodiment of the application also provides a marine wind turbine tower corrosion protection coating spraying thickness uniformity prediction system 600, which comprises:

[0105] A single-point spraying model construction module 610 is configured to construct a single-point spraying thickness distribution function for the marine wind turbine tower corrosion protection coating based on the fluid dynamics and the boundary layer theory, and obtain a single-point spraying material adhesion amount model.

[0106] A spraying trajectory superposition analysis module 620 is configured to perform spraying trajectory superposition analysis on the single-point spraying material adhesion amount model, and obtain the spraying trajectory during the corrosion protection spraying of the marine wind turbine tower.

[0107] A discrete analysis module 630 is configured to perform discrete analysis on the tower drum surface of the marine wind turbine tower according to the spraying trajectories, and discretize each curved surface of the tower drum surface into a grid unit.

[0108] The coating thickness prediction module 640 is configured to utilize a three-dimensional curved surface superposition algorithm to analyze the coating thickness and uniformity of each grid unit, and predict the total coating thickness during spraying.

[0109] The mapping module 650 is configured to map the total coating thickness accumulated by the grid units to a three-dimensional curved surface, and generate a thickness distribution cloud map.

[0110] Optionally, the single-point spraying model construction module is specifically configured to: based on fluid dynamics and boundary layer theory, according to establish a single-point spraying thickness distribution function to obtain a single-point spraying material adhesion amount model; wherein h(r, θ) refers to the layer thickness when the radial distance of the spraying point is r and the inclination angle of the spray gun is θ, Q is the coating flow rate affecting the coating deposition rate, v is the spray gun moving speed affecting the local coating thickness, h0 is the reference thickness, R0 is the peak radius, σ r is the radial diffusion coefficient, and σ θ is the tangential diffusion coefficient.

[0111] Optionally, the spraying trajectory superposition analysis module includes:

[0112] The trajectory analysis submodule is configured to utilize a trajectory superposition principle, analyze the trajectory information of the single-point spraying material adhesion model according to a preset thickness fluctuation in the overlapping area and a trajectory superposition relationship, and obtain a spraying trajectory.

[0113] The trajectory updating submodule is configured to update the spraying trajectory based on the spraying trajectory and according to a preset row spacing dynamic adjustment rule for uniformity adjustment.

[0114] Optionally, the trajectory updating submodule includes:

[0115] The area analysis unit is configured to analyze the area type of the offshore wind turbine tower surface area based on the spraying trajectory, and the area type includes a flat area and a high-curvature area.

[0116] The uniformity adjustment unit is configured to perform uniformity adjustment on the spraying trajectory of the flat area and local curvature adjustment on the spraying trajectory of the high-curvature area according to a preset dynamic adjustment rule, and update each spraying trajectory.

[0117] Optionally, the discrete analysis module includes:

[0118] The discrete processing submodule is configured to perform discrete processing based on each spraying trajectory to obtain discrete path points, and the discrete path points correspond to local spraying parameters.

[0119] The grid cell construction submodule is configured to map the discrete path points to a three-dimensional grid corresponding to the tower surface of the offshore wind turbine tower by using a surface parameterization technique to construct the grid cells of the discrete surface; wherein the shape type of the grid cells includes triangular grids and quadrilateral grids, each of the grid cells records a local curvature, a normal vector, and a spraying parameter, and the grid cells correspond to the surface regions of the tower surface one by one.

[0120] Optionally, the grid cell construction submodule comprises:

[0121] The discrete unit is configured to construct a surface model of the offshore wind turbine tower by using a surface parameterization technique, and to discretize the surface of the tower surface in the surface model into grid cells;

[0122] The grid updating unit is configured to map each of the discrete path points to the corresponding grid cell to update each of the grid cells.

[0123] Optionally, the coating thickness prediction module comprises:

[0124] The grid cell thickness prediction submodule is configured to calculate the coating thickness of each of the grid cells by using the single-point spraying thickness distribution function based on the cumulative integration of the surface grid;

[0125] The coating superposition prediction submodule is configured to analyze the overlapping regions of each of the grid cells when spraying is performed, and to calculate the total thickness of the coating related to uniformity by numerically integrating the coating superposition in the overlapping regions based on the coating thickness.

[0126] Optionally, the grid cell thickness prediction submodule comprises:

[0127] The spraying influence domain modeling unit is configured to model the single-point spraying influence domain by using the single-point spraying thickness distribution function based on each of the grid cells, and to define the influence domain of single-point spraying as a dynamic elliptical region, wherein the long axis direction of the dynamic elliptical region is consistent with the spraying gun moving direction, and the short axis is determined based on the coating diffusion characteristics;

[0128] The coating thickness updating unit is configured to calculate the coating material generated by a single discrete path point in the dynamic elliptical region to update the coating thickness of the corresponding grid cell.

[0129] Optionally, the coating superposition prediction submodule is specifically configured to: take the coating thickness of each of the grid cells as a reference, and calculate the contribution value of all spraying points covering the same grid cell according to to obtain the total thickness; wherein G i represents the i-th grid cell, N represents the number of spraying points covering the grid G i , and A j ∩G irepresents the intersection area of the jth spraying point influence domain and the grid cell G i represents the intersection area of the jth spraying point influence domain and the grid cell G j represents the intersection area of the jth spraying point influence domain and the grid cell G

[0130] It should be noted that the offshore wind turbine tower anticorrosive coating spraying thickness uniformity prediction system provided by the embodiments of the present application can execute the offshore wind turbine tower anticorrosive coating spraying thickness uniformity prediction method provided by any embodiment of the present application, and has the corresponding functions and beneficial effects of the execution method.

[0131] It should be noted that in this document, relational terms such as“first” and“second”, and the like, are used solely to distinguish one entity or action from another entity or action, without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms“comprises”,“comprising”, or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by“comprises a...” does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0132] The above description is merely that of a specific implementation of the present application, to enable a person skilled in the art to understand or implement the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for predicting the thickness uniformity of anti-corrosion coating spraying on offshore wind turbine towers, characterized in that: include: Based on fluid dynamics and boundary layer theory, a single-point spray thickness distribution function for the anti-corrosion coating on offshore wind turbine towers was established, and a single-point spray material adhesion model was obtained. Performing a spray trajectory superposition analysis on the single-point spray material attachment amount model to obtain a spray trajectory when performing anti-corrosion spraying on the offshore wind turbine tower; performing a discrete analysis on the tower surface of the offshore wind turbine tower according to each of the spraying trajectories, and discretizing each curved surface of the tower surface into grid units; Using a three-dimensional surface superposition algorithm, the coating thickness and uniformity of each grid unit are analyzed to predict the total coating thickness during spraying; The total coating thickness accumulated by the grid cells is mapped to a three-dimensional surface to generate a thickness distribution cloud map.

2. The method according to claim 1, characterized in that Based on fluid dynamics and boundary layer theory, a single-point spraying thickness distribution function for the anti-corrosion coating on offshore wind turbine towers was established, and a single-point spraying material adhesion model was obtained, including: Based on fluid dynamics and boundary layer theory, The single-point spraying thickness distribution function is established to obtain the single-point spraying material adhesion model; Where h(r,θ) refers to the layer thickness when the radial distance of the spray point is r and the spray gun inclination angle is θ, Q is the paint flow rate that affects the coating deposition rate, v is the spray gun movement speed that affects the local coating thickness, h0 is the reference thickness, R0 is the peak radius, σ r is the radial diffusion coefficient, σ θ is the tangential diffusion coefficient.

3. The method according to claim 1, characterized in that Performing a spray trajectory superposition analysis on the single-point spray material attachment model to obtain a spray trajectory when performing anti-corrosion spraying on the offshore wind turbine tower, including: Adopting the trajectory superposition principle, according to the preset overlapping area thickness fluctuation and trajectory superposition relationship, the trajectory information of the single-point spraying material attachment model is analyzed to obtain the spraying trajectory; Based on the spraying trajectory, uniformity adjustment is performed according to a preset line spacing dynamic adjustment rule to update the spraying trajectory.

4. The method according to claim 3, characterized in that Based on the spraying trajectory, uniformity adjustment is performed according to a preset line spacing dynamic adjustment rule, and the spraying trajectory is updated, including: Analyzing the region types of the surface area of ​​the offshore wind turbine tower based on the spraying trajectory, where the region types include flat regions and high curvature regions; According to the preset dynamic adjustment rules, the uniformity of the spraying trajectory in the flat area is adjusted, and the local curvature of the spraying trajectory in the high curvature area is adjusted, and each of the spraying trajectories is updated.

5. The method according to claim 1, wherein According to each of the spraying trajectories, a discrete analysis is performed on the tower surface of the offshore wind turbine tower, and each curved surface of the tower surface is discretized into grid units, including: Discretization processing is performed based on each of the spraying trajectories to obtain discrete path points, wherein the discrete path points correspond to local spraying parameters; Using surface parameterization technology, the discrete path points are mapped to a three-dimensional grid corresponding to the tower surface of the offshore wind turbine tower to construct surface discrete grid units. The shape types of the grid units include triangular grids and quadrilateral grids, each of the grid units records local curvature, normal vectors and spraying parameters, and the grid units correspond one-to-one to the curved surface areas of the tower surface.

6. The method according to claim 5, characterized in that Using surface parameterization technology, the discrete path points are mapped to a three-dimensional grid corresponding to the tower surface of the offshore wind turbine tower, and the surface discrete grid units are constructed, including: Surface parameterization technology is used to construct a surface model of the offshore wind turbine tower, and the surface of the tower in the surface model is discretized into grid units. Map each of the discrete path points to the corresponding grid unit, and update each of the grid units.

7. The method according to claim 1, characterized in that Using a three-dimensional surface superposition algorithm, the coating thickness and uniformity of each grid unit are analyzed to predict the total coating thickness during spraying, including: Based on the cumulative integral of the surface grid, the coating thickness of each grid unit is calculated using the single-point spraying thickness distribution function; The overlapping areas of the grid units during spraying are analyzed, and based on the coating thickness, the overlapping areas are coated by numerical integration to calculate the total coating thickness related to uniformity.

8. The method according to claim 7, characterized in that Based on the cumulative integral of the surface grid, the coating thickness of each grid unit is calculated using the single-point spraying thickness distribution function, including: Based on each of the grid cells, a single-point spraying influence domain is modeled using a single-point spraying thickness distribution function, and the influence domain of the single-point spraying is defined as a dynamic elliptical region, wherein the major axis direction of the dynamic elliptical region is consistent with the movement direction of the spray gun, and the minor axis is determined based on the diffusion characteristics of the coating; In the dynamic elliptical area, the coating material generated by a single discrete path point is calculated and the coating thickness of the corresponding grid unit is updated.

9. The method according to claim 1, characterized in that Analyzing the overlapping areas of the grid cells during spraying, and performing coating superposition on the overlapping areas by numerical integration based on the coating thickness, and calculating the total coating thickness related to uniformity, including: Based on the coating thickness of each grid unit, Calculate the contribution of all spray points covering the same grid cell to obtain the total thickness; Among them, G i represents the i-th grid unit, and N represents the covering grid G i Number of spray points, A j ∩G i Represents the influence area of ​​the j-th spraying point and the grid unit G i The intersection area, κ represents the surface curvature, κ j represents the local curvature at the j-th spraying point.

10. A system for predicting the thickness uniformity of anti-corrosion coating spraying on offshore wind turbine towers, characterized in that: include: A single-point spray model construction module is used to establish a single-point spray thickness distribution function for the anti-corrosion coating on offshore wind turbine towers based on fluid dynamics and boundary layer theory, and to obtain a single-point spray material adhesion model; a spray trajectory superposition analysis module, configured to perform spray trajectory superposition analysis on the single-point spray material attachment amount model to obtain a spray trajectory when performing anti-corrosion spraying on the offshore wind turbine tower; a discrete analysis module, configured to perform discrete analysis on the tower surface of the offshore wind turbine tower according to each of the spraying trajectories, and discretize each curved surface of the tower surface into grid units; A coating thickness prediction module is used to analyze the coating thickness and uniformity of each grid unit using a three-dimensional surface superposition algorithm to predict the total coating thickness during spraying; A mapping module is used to map the total coating thickness accumulated by the grid cells to a three-dimensional surface to generate a thickness distribution cloud map.

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