A fully automatic spraying production line control method and system

Abstract

The application belongs to the technical field of spraying, and discloses a full-automatic spraying production line control method and system, the method comprising: acquiring real-time rheological property data of paint; the real-time rheological property data comprises an apparent viscosity curve representing the change of apparent viscosity of paint with shearing rate; acquiring local geometric feature information of a local area where a current spraying point of a workpiece to be sprayed is located; determining a target shearing rate range corresponding to the local area where the current spraying point is located according to the local geometric feature information; calculating spraying parameters according to the real-time rheological property data and the target shearing rate range; controlling spraying equipment of the full-automatic spraying production line to perform spraying work according to the spraying parameters; thereby the spraying parameters can be dynamically adjusted according to the real-time rheological property of paint and the local geometric feature of the workpiece, and the spraying quality is improved.

Description

Technical Field

[0001] The present application relates to the field of spraying technology, and in particular to a control method and system for a fully automatic spraying production line. Background Art

[0002] Fully automated spray coating lines are widely used in modern industry to coat the surfaces of various parts. These parts vary widely in material, size, and geometry, ranging from large structural components to small, precision decorative pieces, with complex and diverse surface features. Currently, fully automated spray coating lines typically employ a control strategy based on preset parameters. This strategy uses a database to retrieve the appropriate spray parameters based on workpiece recognition results, guiding the spray equipment for automated coating. This approach ensures a certain degree of repeatability in production and consistent coating quality.

[0003] However, in the actual industrial spraying process, the effective application of coatings faces many challenges, especially the complex interaction between the rheological properties of the coatings and the microscopic features of the workpiece surface. Coatings used in industrial spraying, especially high-performance coatings, generally exhibit non-Newtonian fluid properties, among which shear thinning behavior is particularly significant, that is, the apparent viscosity of the coating decreases with increasing shear rate. The shear rate experienced by the coating during the spraying process varies dramatically, from lower shear in the paint tank and feed pipe, to extremely high shear during atomization at the nozzle, to a rapid decrease in shear rate when leaving the nozzle and entering the air, until it finally hits the workpiece surface and spreads and levels. The local shear rate it experiences is also affected by the microscopic geometry of the workpiece surface and the dynamic behavior of the droplet itself.

[0004] Different workpiece types have significantly different surface micro-geometric features, such as surface roughness, texture, porosity, and sharp edges or deep grooves. These micro-features exert different local shear forces on the coating at the moment of coating droplet impact and spreading, resulting in dynamic differences in the apparent viscosity of the coating in different areas of the workpiece surface.

[0005] The control systems of existing production lines typically optimize preset spray parameters based on the coating's viscosity characteristics under a certain "average" or "ideal" shear state. These parameters fail to fully account for the dynamic impact of the workpiece's surface microgeometry on the coating's local apparent viscosity. This means that regardless of the workpiece's surface microscopic features, the system will spray in the same manner, ignoring the coating's actual rheological response in different areas.

[0006] This lack of matching between the rheological properties of the paint and the micro-features of the workpiece surface directly leads to the non-uniformity of the paint film formed on the workpiece surface, and further causes non-optimal paint consumption and product quality defects. For example, when spraying a workpiece with sharp edges, the apparent viscosity of the paint at the edges may drop sharply, and the paint is prone to flow away from the edges, resulting in defects such as too thin paint film or "bare spots". In order to compensate for these weak areas, the system or operator often has to increase the overall paint output or increase the number of spraying passes, which can cause the paint film thickness to exceed the standard in other areas of the workpiece (such as flat surfaces or internal areas), resulting in problems such as sagging, orange peel, or slow surface drying, causing paint waste. Conversely, when spraying a workpiece with fine textures or high porosity, if the apparent viscosity of the paint is too high in these areas due to low shear, the paint may not be able to fully wet and penetrate, resulting in uneven paint film, incomplete coverage of textures, or even "dry spraying", which also requires increased paint volume or rework, thereby indirectly increasing paint consumption.

[0007] The existing system lacks the ability to accurately assess and adaptively adjust the real-time apparent viscosity changes of the paint on different areas of the workpiece surface during the spraying process. It cannot dynamically adjust the spraying parameters (such as spray gun speed, paint output, atomization pressure, or even spray shape) according to the local geometric features and surface texture of the workpiece to ensure that the paint adheres and levels at the optimal effective viscosity state in different areas. The lack of such control mechanisms makes it difficult for production lines to achieve precise paint matching and consumption optimization when handling multiple varieties of complex surface workpieces, and it is also difficult to maintain high consistency in product quality.

[0008] The existing technology needs to be improved in view of the above problems. SUMMARY

[0009] The purpose of the present application is to provide a fully automatic spraying production line control method and system that can dynamically adjust the spraying parameters according to the real-time rheological properties of the paint and the local geometric features of the workpiece, thereby improving the spraying quality.

[0010] In a first aspect, the present application provides a fully automatic spraying production line control method, the steps of which include:

[0011] A1. Obtain real-time rheological property data of the paint; the real-time rheological property data includes an apparent viscosity curve representing the change of the apparent viscosity of the paint with the shear rate;

[0012] A2. Obtain local geometric feature information of the local area where the current spraying point of the workpiece to be sprayed is located;

[0013] A3. Determine a target shear rate range corresponding to the local area where the current spraying point is located according to the local geometric feature information;

[0014] A4. calculating spraying parameters according to the real-time rheological property data and the target shear rate range;

[0015] A5. controlling spraying equipment of the full-automatic spraying production line to perform spraying operation according to the spraying parameters.

[0016] Preferably, step A1 comprises:

[0017] A101. acquiring pressure information and flow information of the coating in the conveying pipeline to determine a shear rate of the coating in the conveying pipeline;

[0018] A102. determining an apparent viscosity of the coating at the shear rate according to the pressure information, the flow information and the shear rate;

[0019] A103. continuously acquiring a plurality of shear rates and corresponding apparent viscosities to form a preliminary apparent viscosity curve and determine a functional relationship between the apparent viscosity and the shear rate;

[0020] A104. generating an apparent viscosity curve segment corresponding to an extended shear rate range according to the functional relationship, denoted as an extended curve segment; the extended shear rate range is a shear rate range outside the acquired shear rate range;

[0021] A105. integrating the preliminary apparent viscosity curve and the extended curve segment to form a final apparent viscosity curve.

[0022] Preferably, step A2 comprises:

[0023] A201. acquiring overall geometric data of a workpiece to be sprayed;

[0024] A202. acquiring spatial coordinate information of the current spraying point;

[0025] A203. determining a local area corresponding to the current spraying position from the overall geometric data according to the spatial coordinate information;

[0026] A204. extracting design geometric feature information of the determined local area from a preset feature information library to obtain local geometric feature information of the determined local area.

[0027] Preferably, step A3 comprises:

[0028] A301. extracting a geometric feature type of the local area where the current spraying point is located from the local geometric feature information;

[0029] A302. According to the geometric feature type, an initial shear rate range associated with the geometric feature type is obtained from a preset geometric-rheological rule library;

[0030] A303. According to a geometric parameter contained in the local geometric feature information, the initial shear rate range is adjusted to obtain the target shear rate range.

[0031] Preferably, step A303 comprises:

[0032] Obtaining local geometric feature information of a current spraying point and a preset number of previous spraying points of the current spraying point;

[0033] According to the local geometric feature information of the current spraying point and the previous spraying points of the current spraying point, a variation trend of a local geometric parameter is determined;

[0034] According to the variation trend, the initial shear rate range is smoothly adjusted to obtain the target shear rate range.

[0035] Preferably, the step of adjusting the initial shear rate range according to the variation trend to obtain the target shear rate range comprises:

[0036] B1. According to the variation trend, a variation gradient of the local geometric parameter is calculated;

[0037] B2. A current moving speed of a spraying device is obtained;

[0038] B3. According to the variation gradient and the current moving speed, an adjustment parameter for smoothly adjusting the initial shear rate range is determined; the adjustment parameter comprises an adjustment amount of at least one of a center position, a width, an upper limit, and a lower limit of a shear rate range;

[0039] B4. According to the adjustment parameter, the initial shear rate range is adjusted to obtain the target shear rate range.

[0040] Preferably, step B3 comprises:

[0041] B301. According to the variation gradient, a gradient level corresponding to the variation gradient is determined;

[0042] B302. According to the current moving speed, a speed level corresponding to the current moving speed is determined;

[0043] B303. According to the gradient level and the speed level, the adjustment parameter is obtained from a preset adjustment parameter mapping relationship.

[0044] Preferably, step A4 comprises:

[0045] A401. Obtain the correlation data between the spraying parameters and the actual shear rate of the coating on the workpiece surface, and the correlation data between the spraying parameters and the paint film uniformity and the coating utilization rate;

[0046] A402. According to the real-time rheological property data and the target shear rate range, and in combination with the correlation data between the spraying parameters and the actual shear rate, determine a spraying parameter combination that meets the target shear rate range, and form a spraying parameter set;

[0047] A403. According to each spraying parameter combination in the spraying parameter set, in combination with the correlation data between the spraying parameters and the paint film uniformity and the coating utilization rate, evaluate the paint film uniformity and the coating utilization rate of each spraying parameter combination;

[0048] A404. According to the paint film uniformity and the coating utilization rate, determine an optimal spraying parameter combination as the spraying parameter.

[0049] Preferably, step A402 comprises:

[0050] According to the real-time rheological property data, determine a target apparent viscosity range corresponding to the target shear rate range;

[0051] Within the adjustable range of the spraying parameters of the spraying equipment, set multiple discrete values of each spraying parameter;

[0052] Arrange and combine the discrete values of each spraying parameter to obtain multiple candidate spraying parameter combinations;

[0053] For each of the candidate spraying parameter combinations, calculate the actual shear rate of the coating on the workpiece surface using the correlation data between the spraying parameters and the actual shear rate, and record it as a first shear rate;

[0054] According to the real-time rheological property data, determine the apparent viscosity of the coating at the first shear rate, and record it as a first apparent viscosity;

[0055] The candidate spraying parameter combination in which the first shear rate falls within the target shear rate range and the first apparent viscosity falls within the target apparent viscosity range is taken as the final spraying parameter combination, and a spraying parameter set is formed.

[0056] In a second aspect, the present application provides a full-automatic spraying production line control system, which comprises:

[0057] A data acquisition module for acquiring real-time rheological property data of the coating; the real-time rheological property data comprises an apparent viscosity curve representing the change of the apparent viscosity of the coating with the shear rate;

[0058] The feature acquisition module is configured to acquire local geometric feature information of a local region where a current spraying point of the workpiece to be sprayed is located.

[0059] The range determination module is configured to determine a target shear rate range corresponding to the local region where the current spraying point is located according to the local geometric feature information.

[0060] The parameter calculation module is configured to calculate a spraying parameter according to the real-time rheological property data and the target shear rate range.

[0061] The control module is configured to control a spraying device of the full-automatic spraying production line to perform a spraying operation according to the spraying parameter.

[0062] Beneficial effects: The full-automatic spraying production line control method and system provided by the application can realize accurate matching of the rheological property of the coating and the micro feature of the workpiece surface by acquiring the coating rheological property data and the local geometric feature information of the workpiece in real time and dynamically calculating and adjusting the spraying parameter according to the two, so as to dynamically adjust the spraying parameter according to the real-time rheological property of the coating and the local geometric feature of the workpiece, and improve the spraying quality. BRIEF DESCRIPTION OF DRAWINGS

[0063] Figure 1 The full-automatic spraying production line control method provided by the embodiment of the application is shown in the flowchart.

[0064] Figure 2 The structure schematic diagram of the full-automatic spraying production line control system provided by the embodiment of the application is shown.

[0065] Label explanation: 1, data acquisition module; 2, feature acquisition module; 3, range determination module; 4, parameter calculation module; 5, control module. DETAILED DESCRIPTION

[0066] The technical model in the application will be described clearly and completely by combining the drawings in the application. Obviously, the described embodiments are only part of the embodiments of the application, but not all the embodiments. The components of the application described and shown in the drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the application provided in the drawings is not intended to limit the scope of the claimed application, but only represents selected embodiments of the application. Based on the embodiments of the application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of the application.

[0067] It should be noted that similar reference numbers and letters refer to similar items in the following drawings, and therefore, once an item is defined in one drawing, it need not be further defined and explained in subsequent drawings. Meanwhile, in the description of the present application, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0068] Reference Figure 1 The present application proposes a full-automatic spraying production line control method, the steps of the method comprising:

[0069] A1. Obtain real-time rheological property data of the coating; the real-time rheological property data comprises an apparent viscosity curve representing the change of apparent viscosity of the coating with shear rate;

[0070] A2. Obtain local geometric feature information of a local area where a current spraying point of the workpiece to be sprayed is located;

[0071] A3. Determine a target shear rate range corresponding to the local area where the current spraying point is located according to the local geometric feature information;

[0072] A4. Calculate a spraying parameter according to the real-time rheological property data and the target shear rate range;

[0073] A5. Control the spraying equipment of the full-automatic spraying production line to perform spraying operation according to the spraying parameter.

[0074] Wherein, the real-time rheological property data refers to the viscosity characteristics of the coating under different shear rates, which can be obtained by means of online rheological measurement unit, viscosity sensor combined with pressure flow sensor, etc., such as by measuring the pressure and flow of the coating in the conveying pipeline to calculate the shear rate and apparent viscosity, which is mainly to obtain the dynamic viscosity variation law of the coating in the actual spraying process.

[0075] Wherein, the local geometric feature information refers to the geometric form data of the area around a specific spraying point on the workpiece to be sprayed, which can be obtained by means of three-dimensional scanner, machine vision system or extraction from CAD model, such as by identifying the roughness, texture, porosity, sharp edge or deep groove of the workpiece surface, etc., which is mainly to identify the microstructure of the workpiece surface that affects the rheological behavior of the coating.

[0076] Wherein, the target shear rate range refers to the shear rate interval that the coating needs to reach in order to achieve the paint film quality and coating utilization rate when spraying in a specific local area of the workpiece, which can be obtained according to the preset geometric-rheological rule library or by model derivation, such as setting a lower shear rate range for sharp edge area to prevent sagging, which is mainly to convert the local geometric characteristics of the workpiece into rheological targets of the coating.

[0077] The spraying parameters refer to various adjustable variables for controlling the spraying equipment to work, which can include part or all of the spraying gun moving speed, paint output, atomization pressure, spraying width shape, etc., which are mainly to directly control the actual shearing state and deposition effect of the paint on the workpiece surface.

[0078] The core innovation of the present application is that the real-time rheological property data of the paint is associated with the local geometric feature information of the workpiece to be sprayed, and the spraying parameters are dynamically calculated based on this, thereby solving the problem that the spraying parameters in the prior art cannot adapt to the dynamic rheological properties of the paint and the local geometric differences of the workpiece, and achieving the effect of improving the spraying quality.

[0079] Specifically, the method first acquires real-time rheological property data of the paint, which reflects the law of apparent viscosity change with shearing rate, ensuring the mastery of the paint state. At the same time, the local geometric feature information of the local area where the current spraying point of the workpiece to be sprayed is located is acquired, and the microstructure of the workpiece surface that affects the paint rheological behavior is identified. Subsequently, according to the local geometric feature information, the target shearing rate range that the paint needs to reach when sprayed in the local area is determined, and the physical properties of the workpiece are converted into the rheological target of the paint. Then, combined with the acquired real-time rheological property data of the paint and the determined target shearing rate range, the system calculates the appropriate spraying parameter combination that can make the paint reach the target shearing rate range in the local area. Finally, according to the calculated spraying parameters, the spraying equipment of the full-automatic spraying production line is controlled to perform the spraying work. The whole process forms a closed loop, so that the spraying equipment can be self-adaptively adjusted according to the real-time state of the paint and the local requirements of the workpiece, ensuring that the paint is sprayed in a manner suitable for the current local area of the workpiece and the real-time state of the paint itself.

[0080] Through the above scheme, the present application solves the problem that the existing full-automatic spraying production line control method cannot dynamically adjust the spraying parameters according to the real-time rheological properties of the paint and the local geometric features of the workpiece. The method can ensure that the paint spreads on the workpiece surface in different areas with appropriate apparent viscosity, thereby avoiding the occurrence of defects such as uneven paint film, sagging, bare bottom or dry spraying, and improving the overall quality and consistency of the paint film. At the same time, by controlling the rheological behavior of the paint in different areas, unnecessary waste of paint can be reduced, and the utilization efficiency of the paint can be improved, thereby reducing the production cost.

[0081] In some embodiments, step A1 includes:

[0082] A101. Acquire the pressure information and flow information of the paint in the conveying pipeline to determine the shearing rate of the paint in the conveying pipeline;

[0083] A102. determining the apparent viscosity of the coating at the shear rate according to the pressure information, the flow information, and the shear rate;

[0084] A103. continuously acquiring a plurality of shear rates and their corresponding apparent viscosities to form a preliminary apparent viscosity curve, and determining a functional relationship between the apparent viscosity and the shear rate;

[0085] A104. generating an apparent viscosity curve segment corresponding to an extended shear rate range according to the functional relationship, denoted as an extended curve segment; the extended shear rate range is a shear rate range outside the acquired shear rate range;

[0086] A105. integrating the preliminary apparent viscosity curve and the extended curve segment to form a final apparent viscosity curve.

[0087] wherein the pressure information refers to the pressure value borne by the coating when flowing in the conveying pipeline, which can be monitored in real time by a pressure sensor installed on the pipeline.

[0088] wherein the flow information refers to the volume or mass of coating flowing through the conveying pipeline per unit time, which can be measured in real time by a flow meter.

[0089] wherein the shear rate refers to the velocity gradient between adjacent layers inside the fluid, reflecting the strength of the shear force experienced by the fluid, which can be calculated according to the pipeline geometry, flow rate, and fluid type through fluid mechanics formulas in pipeline flow. For example, for laminar flow in a circular pipeline, the shear rate can be calculated using the Poiseuille law for Newtonian fluids or the modified formula for non-Newtonian fluids.

[0090] wherein the apparent viscosity refers to the viscosity exhibited by a non-Newtonian fluid at a specific shear rate, which is not a constant but varies with shear rate, and can be derived from the pressure loss in the pipeline (calculated by the difference between the pressure information at the inlet and outlet of the pipeline), flow rate, and shear rate through rheological principles.

[0091] wherein the functional relationship refers to the mathematical mapping relationship between the apparent viscosity and the shear rate, which can be established using polynomial fitting, exponential fitting, power-law model, Herschel-Bulkley model, and other rheological models to describe the viscosity behavior of the coating under different shear conditions.

[0092] wherein the extended shear rate range refers to the shear rate interval that the coating may experience during actual spraying but for which data has not been acquired through direct measurement, such as extremely high shear rate (e.g., during nozzle atomization) or extremely low shear rate (e.g., during coating spreading and leveling on the workpiece surface).

[0093] The method first obtains pressure information and flow information of the coating in the conveying pipeline through step A101. These information are parameters that are easy to obtain on the production line and can reflect the flow state of the coating in the pipeline in real time. Based on these information, the shear rate of the coating in the conveying pipeline can be determined in step A101, and the apparent viscosity of the coating under the current shear rate can be determined in real time and indirectly in step A102 according to the pressure information, flow information and determined shear rate. This indirect measurement method avoids the difficulty of directly measuring complex measurements at a wide range of shear rates, providing basic and real-time measurement data points for subsequent viscosity curve construction. On this basis, step A103 continuously obtains a plurality of shear rates and their corresponding apparent viscosities, thereby forming a preliminary apparent viscosity curve. More importantly, this step further determines the functional relationship between the apparent viscosity and the shear rate. The establishment of this functional relationship is the core, which converts discrete measurement data points into a continuous mathematical model, providing a mathematical basis for subsequent viscosity prediction and curve extension in the shear rate range that has not been directly measured, overcoming the limitations of relying only on discrete measurement point data. Subsequently, step A104 generates an apparent viscosity curve segment corresponding to an extended shear rate range according to the functional relationship determined in step A103. The extended shear rate range here refers to the shear rate range beyond the shear rate range that has been obtained, such as the extremely high shear rate during spraying atomization or the extremely low shear rate during the spreading of the coating on the workpiece surface. This means that even in the case of the coating experiencing these difficult-to-directly-accurately-measure shear rates, reasonable inference and supplementation can be made through the mathematical model, thereby obtaining more complete viscosity curve data. Finally, step A105 integrates the preliminary apparent viscosity curve and the extended curve segment (such as directly splicing or further smoothing the splicing position) to form the final apparent viscosity curve. This integration ensures that the final apparent viscosity curve contains both data based on actual measurements and extended shear rate ranges covered by the model.

[0094] In this way, the present method can provide more comprehensive and accurate real-time rheological property data of the coating. When this comprehensive and accurate real-time rheological property data is applied to subsequent spraying parameter calculation, the calculated spraying parameters can more accurately match the actual rheological behavior of the coating in different regions of the workpiece surface, thereby improving the level of fine control of spraying control and ensuring that the dynamic behavior of the coating under different shear conditions is fully considered, thereby optimizing the spraying quality and coating utilization efficiency.

[0095] In some embodiments, step A2 comprises:

[0096] A201. Obtain the overall geometric data of the workpiece to be sprayed;

[0097] A202. Obtain the spatial coordinate information of the current spraying point;

[0098] A203. determining, according to the spatial coordinate information, a local region corresponding to the current spraying position from the overall geometric data;

[0099] A204. extracting, according to the determined local region, design geometric feature information corresponding to the local region from a preset feature information library, to obtain local geometric feature information of the determined local region.

[0100] The preset feature information library can be a structured data storage system, such as a database or a predefined CAD model library, which stores classified and parameterized geometric feature data related to workpiece design. These data can include accurate geometric parameters and attributes of different geometric feature types (such as planes, curved surfaces, sharp edges, grooves, and textured areas). Further, the design geometric feature information refers to the geometric feature types and corresponding geometric parameters and attributes defined based on the workpiece design intent and engineering specifications, such as the curvature radius, chamfer angle, groove depth, texture type, or surface roughness parameter. These information are different from simple surface point cloud data or general geometric description, and they are directly related to the rheological behavior of the paint on these specific geometric structures, providing more accurate and precise input for subsequent spraying parameter optimization.

[0101] The present application realizes accurate acquisition of local geometric feature information of the workpiece through the above refinement steps. Specifically, the overall geometric data of the workpiece is first acquired, which lays a foundation for a comprehensive understanding of the geometric shape of the workpiece. Subsequently, by acquiring the spatial coordinate information of the current spraying point, the system can accurately locate the current position of the spraying operation. Based on these spatial coordinate information, the local region closely related to the current spraying position can be intelligently identified and determined from the vast overall geometric data, thereby avoiding unnecessary processing of the entire workpiece data and improving the efficiency and pertinence of data processing. More critically, after determining the local region, the system no longer relies on general surface features, but extracts design geometric feature information matching the local region from a preset feature information library containing rich design details. These design geometric feature information are key information that have been optimized and directly affect the rheological behavior of the paint. In this way, the acquired local geometric feature information not only reflects the physical form of the workpiece, but also contains key geometric parameters that have a direct impact on the rheological properties of the paint. As a result, this accurate and instructive local geometric feature information can provide a solid data foundation for subsequent determination of the target shear rate range. When these accurate local geometric feature information are used to determine the target shear rate range, the actual shear state of the paint on the surface of the workpiece in different regions can be more accurately predicted.

[0102] The accurate prediction of the shearing state, combined with real-time rheological property data of the paint, enables the calculation and optimization of spraying parameters to be more in line with the actual geometric conditions of the workpiece and the rheological response of the paint. Therefore, by providing highly accurate and relevant local geometric feature information, the accuracy of the spraying parameter optimization is significantly improved, effectively solving the problem of poor spraying effect caused by inaccurate or incomplete local geometric feature information, ensuring that the paint forms a uniform paint film on the surface of complex workpieces, and reducing paint waste.

[0103] As a preferred implementation, when obtaining the overall geometric data of the workpiece to be sprayed, a computer-aided design (CAD) model can be used, or an actual workpiece can be scanned by a high-precision three-dimensional scanning device (such as a laser scanner or a structured light scanner) to generate point cloud data or a triangular mesh model. When obtaining the spatial coordinate information of the current spraying point, the encoder feedback system of the spraying device (such as a spraying robot) itself can be used, or a vision positioning system can be used to track the end of the spray gun in real time to obtain its accurate position in the workpiece coordinate system. According to the design scheme of the workpiece, the surface of the workpiece can be divided into a plurality of local regions with consistent internal geometric features, and the position information and design geometric feature information of each local region can be stored in a preset feature information library. When determining the local region corresponding to the current spraying position from the overall geometric data according to the spatial coordinate information, the accurate position of the current spraying point in the workpiece coordinate system can be identified according to the position information of each preset local region. Further, the design geometric feature information of the corresponding local region is extracted from the preset feature information library according to the determined local region as the local geometric feature information.

[0104] In some embodiments, step A3 comprises:

[0105] A301. From the local geometric feature information, the geometric feature type of the local region where the current spraying point is located is extracted;

[0106] A302. According to the geometric feature type, an initial shear rate range associated with the geometric feature type is obtained from a preset geometric-rheological rule library;

[0107] A303. According to the geometric parameters contained in the local geometric feature information, the initial shear rate range is adjusted to obtain the target shear rate range.

[0108] Wherein, the geometric feature type refers to the identification of the classification of the geometric shape of the local region of the workpiece, such as a plane, an edge, a hole, a groove, a protrusion, etc., which can be implemented by using predefined enumeration values, string labels or classification codes.

[0109] The geometry-rheology rule base refers to a knowledge base that stores the correlation between different geometric feature types and the corresponding paint rheological behavior (especially the shear rate range). It can be implemented using a lookup table, a database, or a mapping relationship based on a machine learning model.

[0110] The initial shear rate range refers to the shear rate interval obtained from the geometry-rheology rule base without fine adjustment according to the identified geometric feature type, which can be represented as a pair of minimum and maximum shear rates or a central value and an allowed deviation range.

[0111] The geometric parameters refer to specific numerical values that quantitatively describe the geometric feature types, such as the curvature radius of the edge, the depth, width, and angle of the groove, or the roughness value of the surface, which can be represented in the form of numerical values, vectors, or structured data.

[0112] In this scheme, when determining the target shear rate range, first, according to the local geometric feature information, the geometric feature type of the local area where the current spraying point is located is determined, and the complex local geometry of the workpiece is classified into a processable category, such as distinguishing between a plane, an edge, or a groove. Subsequently, the system obtains the initial shear rate range associated with the type from the pre-set geometry-rheology rule base according to the determined geometric feature type. This rule base pre-establishes empirical or experimental data of paint rheological behavior under different geometric feature types, thereby providing a baseline shear rate interval for specific geometric shapes. On this basis, in order to further improve the accuracy, the scheme uses the geometric parameters contained in the local geometric feature information to fine-tune the initial shear rate range, and finally obtains the target shear rate range. This adjustment takes into account the subtle influence of the same geometric feature type, such as edges with different curvature radii or grooves with different depths, on the rheological behavior of the paint.

[0113] Through this step-by-step refinement, from macro-type identification to micro-parameter adjustment, it is ensured that the determined target shear rate range can highly match the actual local geometric features of the workpiece. This accurate matching enables the subsequent calculation of spraying parameters to more accurately reflect the actual rheological response of the paint in different areas of the workpiece surface, thereby effectively solving the problems of uneven paint film and paint waste caused by the lack of matching between the rheological characteristics of the paint and the micro features of the workpiece surface.

[0114] Preferably, step A303 can include:

[0115] Obtaining the local geometric feature information of the current spraying point and its preset number of previous spraying points;

[0116] Determining the variation trend of the local geometric parameters according to the local geometric feature information of the current spraying point and its previous spraying points;

[0117] According to the change trend, the initial shear rate range is adjusted smoothly to obtain the target shear rate range.

[0118] Wherein, the change trend of the local geometric parameter refers to the continuous change rule or direction of the geometric characteristics of the workpiece surface on the spraying path, such as curvature, slope or edge proximity, as the spraying point moves, which can be identified by mathematical analysis of a series of continuous local geometric parameter data, such as calculating difference, derivative, or applying regression analysis, moving average, etc.

[0119] Wherein, the smooth adjustment refers to the modification process of the initial shear rate range, so that the adjusted target shear rate range presents gradual and continuous change between continuous spraying points, avoiding sudden change, which can introduce adjustment parameters based on change trend, change gradient or spraying speed, and apply them to the center position, width, upper limit or lower limit of the initial shear rate range, or by applying filtering algorithm or interpolation algorithm to ensure the continuity of the adjustment process.

[0120] The scheme no longer limits to the instantaneous geometric characteristics of the current spraying point when determining the target shear rate range, but by obtaining the local geometric feature information of the current spraying point and its preset number of previous spraying points, a dynamic evolution data stream of the workpiece surface geometric parameters on the spraying path is established. Based on these continuous geometric feature information, the system can deeply analyze and determine the change trend of the local geometric parameter. This identification of the change trend enables the system to predict the future trend of the workpiece surface geometry, such as whether the curvature is gradually increasing or decreasing, or whether an edge will be encountered. It is precisely due to this forward-looking trend judgment that the system can adjust the initial shear rate range obtained from the preset rule library smoothly. This smooth adjustment mechanism ensures that the change of the target shear rate range is gradual and continuous, avoiding the jump adjustment of the shear rate range caused by the sudden change of the geometric characteristics. In this way, the adjustment of the spraying parameters also becomes more stable, so that the paint can maintain more stable flow and uniform film thickness on the workpiece surface, especially in the transition area of the geometric characteristics. Compared with the scheme of adjusting only according to the current point geometric parameter, the stability of the spraying process and the film quality are significantly improved, effectively avoiding defects such as sagging, uneven thickness, etc., so as to realize continuous spraying with high quality.

[0121] Further, the step of adjusting the initial shear rate range smoothly according to the change trend to obtain the target shear rate range can include:

[0122] B1. According to the change trend, the change gradient of the local geometric parameter is calculated;

[0123] B2. Obtain a current moving speed of the spraying device;

[0124] B3. Determine an adjustment parameter for smoothing adjusting the initial shear rate range according to the variation gradient and the current moving speed; the adjustment parameter comprises an adjustment amount of at least one of a center position, a width, an upper limit, and a lower limit of the shear rate range;

[0125] B4. Adjust the initial shear rate range according to the adjustment parameter to obtain the target shear rate range.

[0126] Wherein, the variation gradient of the local geometric parameter refers to the rate of change of the local geometric parameter in space or time, which quantifies the degree and direction of the change of the geometric feature. It can be obtained by differential calculation on the continuously collected local geometric parameter data, derivative calculation after curve fitting, or edge detection algorithm based on image processing.

[0127] Wherein, the adjustment parameter refers to a specific numerical value or a proportional factor for fine-tuning the initial shear rate range, which can be determined by a preset lookup table, inference rules based on fuzzy logic, or a function relationship trained by a machine learning model.

[0128] The scheme specifically and finely adjusts the step of smoothing the initial shear rate range according to the change trend. First, the system calculates the change gradient of the local geometric parameter according to the change trend of the local geometric parameter. This gradient information quantifies the abstract change trend and provides the rate and severity of the dynamic change of the geometric features of the workpiece surface. For example, when the spraying device moves rapidly from a flat area to a sharp edge, the change gradient will significantly increase, indicating that the coating will experience a severe shear environment change in a short time. At the same time, the system obtains the current moving speed of the spraying device. The moving speed of the spraying device directly affects the actual shear time and intensity of the coating on the workpiece surface, and high-speed movement may require faster or larger amplitude adjustment of the shear rate range; while low-speed movement allows more fine adjustment. Subsequently, the system uses the calculated change gradient and the obtained current moving speed to determine the adjustment parameters for smoothing the initial shear rate range. These adjustment parameters are specific quantitative values, which can include the adjustment amount of the center position, width, upper limit or lower limit of the shear rate range. The comprehensive consideration of this multi-dimensional dynamic information enables the adjustment strategy to more intelligently and accurately adapt to the dynamic changes of the geometric features of the workpiece and the real-time motion state of the spraying device. For example, when the change gradient is large and the moving speed is fast, the adjustment parameters may indicate that the shear rate range needs to be shifted or expanded more significantly to ensure that the coating can maintain an appropriate effective viscosity in the rapidly changing geometric area. Finally, the system accurately adjusts the initial shear rate range according to these determined adjustment parameters, thereby obtaining a target shear rate range that is finely smoothed and dynamically optimized. This target range can more accurately reflect the shear environment that the coating should withstand at the current spraying point, thereby guiding the calculation of subsequent spraying parameters.

[0129] In this way, based on the identification of the change trend of the local geometric parameter, the scheme further introduces the change gradient and the device moving speed as two key dynamic factors, so that the determination of the target shear rate range is no longer a simple trend adjustment, but an adaptive optimization based on quantitative data and real-time state. This ensures that the coating can be attached and leveled with the best effective viscosity state in different areas of the workpiece surface, thereby significantly improving the uniformity of the paint film and the utilization rate of the coating, and solving the problem of insufficient adjustment accuracy caused by trend judgment alone. This fine adjustment mechanism, combined with the previous steps of obtaining real-time rheological property data, local geometric feature information, and determining the initial shear rate range based on these information, forms a more perfect and adaptive spraying control closed loop, so that the entire spraying process can dynamically respond to the complex changes of the workpiece and the device, and realize precise matching and efficient utilization of the coating.

[0130] Further, step B3 can include:

[0131] B301. According to the change gradient, determine the gradient level corresponding to the change gradient;

[0132] B302. According to the current moving speed, determine the speed level corresponding to the current moving speed;

[0133] B303. Obtain the adjustment parameter from a preset adjustment parameter mapping relationship according to the gradient level and the speed level.

[0134] The gradient level refers to the classification level obtained by discretizing the continuous gradient of local geometric parameter changes, which can be achieved by using preset threshold range division, cluster analysis or fuzzy logic rules.

[0135] The speed grade refers to the classification level obtained by discretizing the current moving speed of the spraying equipment, which can be achieved by fixed interval division, dynamic segmentation or grade division based on the statistical distribution of historical data.

[0136] Among them, the adjustment parameter mapping relationship refers to a data structure that stores the adjustment parameters corresponding to different gradient level and speed level combinations, which can be implemented using a lookup table, a two-dimensional array, a rule base, or a decision tree model. It stores the specific adjustment parameters corresponding to each gradient level and speed level combination. For example, when the gradient level is high and the speed level is fast, the mapping relationship will directly give the corresponding adjustment parameter value. This level mapping-based mechanism avoids complex real-time calculations at runtime, thereby greatly improving the real-time performance and efficiency of adjustment parameter determination.

[0137] By converting continuous gradient and velocity information into discrete levels and utilizing a pre-set mapping relationship, this solution can effectively incorporate a large amount of experimental data, simulation results, or expert experience. This empirical knowledge can be pre-solidified in the mapping relationship, allowing the system to quickly and accurately obtain optimized and verified adjustment parameters when faced with different working conditions. This method not only simplifies the parameter determination process but also ensures the accuracy and stability of the adjustment parameters, making the smooth adjustment of the initial shear rate range more precise and effective. Ultimately, this precise and effective adjustment helps improve paint film uniformity and optimize paint utilization.

[0138] In one specific embodiment, to determine the adjustment parameter for smoothing the initial shear rate range, the following approach can be adopted. Firstly, for the variation gradient of the local geometry parameter, a series of threshold values can be set to divide the gradient levels. For example, when the variation gradient is less than a certain first gradient threshold, it can be classified as a low gradient level; when the variation gradient is between the first and second gradient thresholds, it can be classified as a medium gradient level; when the variation gradient is greater than the second gradient threshold, it can be classified as a high gradient level. These gradient thresholds can be set according to the complexity of the geometry of the actual workpiece being sprayed and experience. At the same time, for the current moving speed of the spraying equipment, similar threshold values can also be set to divide the speed levels. For example, when the moving speed is lower than a certain first speed threshold, it can be classified as a slow speed level; when the moving speed is between the first and second speed thresholds, it can be classified as a medium speed level; when the moving speed is higher than the second speed threshold, it can be classified as a fast speed level. These speed thresholds can be set according to the performance of the spraying equipment and the cycle time requirements of the production line. Once the gradient level and speed level are determined, the system can obtain the adjustment parameter from a pre-set two-dimensional lookup table. The row index of the lookup table can correspond to different gradient levels, and the column index can correspond to different speed levels. Each cell of the lookup table stores a specific adjustment parameter value corresponding to the combination of the gradient level and the speed level, such as the adjustment amount of the center position of the shear rate range, the adjustment amount of the width, etc. In actual operation, the control system can directly query the lookup table according to the real-time determined gradient level and speed level, thereby quickly obtaining the required adjustment parameter, and then adjusting the initial shear rate range.

[0139] In some embodiments, step A4 comprises:

[0140] A401. Obtain the correlation data between the spraying parameters and the actual shear rate experienced by the paint on the surface of the workpiece, and the correlation data between the spraying parameters and the paint film uniformity and paint utilization rate;

[0141] A402. According to the real-time rheological property data and the target shear rate range, in combination with the correlation data between the spraying parameters and the actual shear rate, determine a spraying parameter combination that satisfies the target shear rate range, forming a spraying parameter set;

[0142] A403. According to each spraying parameter combination in the spraying parameter set, in combination with the correlation data between the spraying parameters and the paint film uniformity and paint utilization rate, evaluate the paint film uniformity and paint utilization rate of each spraying parameter combination;

[0143] A404. Determine an optimal spraying parameter combination according to the paint film uniformity and the paint utilization rate as the spraying parameter.

[0144] The correlation data between the spraying parameters and the actual shear rate of the coating on the workpiece surface refers to a set of data or a model describing how the various operating parameters of the spraying equipment affect the shear rate of the coating during the spreading and leveling process on the workpiece surface, which can be established and represented by experimental data, simulation models or machine learning models.

[0145] The correlation data between the spraying parameters and the film uniformity and the coating utilization rate refers to a set of data or a model describing how the various operating parameters of the spraying equipment affect the thickness uniformity of the paint film and the efficiency of the coating utilization during the spraying process, which can be established and represented by historical production data, quality inspection data or prediction algorithms.

[0146] The spraying parameter combination refers to a configuration of a set of spraying parameters that take effect simultaneously, such as a combination of a spraying gun speed, a paint output and a atomization pressure.

[0147] The optimal spraying parameter combination refers to a spraying parameter combination in the spraying parameter set that, after evaluation, performs to achieve the target or meets the preset optimization target in terms of film uniformity and coating utilization rate.

[0148] The scheme further introduces the use of correlation data between spraying parameters and spraying effects, as well as the evaluation and optimized selection of spraying parameter combinations, on the basis of calculating spraying parameters according to real-time rheological property data and target shear rate range in the basic method. Specifically, first, by obtaining the correlation data between spraying parameters and the actual shear rate of the coating on the workpiece surface, as well as the correlation data between spraying parameters and paint film uniformity and coating utilization rate, a data foundation is laid for subsequent parameter calculation and optimization. These correlation data enable the system to predict the rheological behavior of the coating and the spraying quality under different spraying parameters. Second, the system selects the spraying parameter combination that makes the coating on the workpiece surface reach the target shear rate range, according to the real-time rheological property data of the coating and the target shear rate range determined for the local area of the workpiece, combined with the established correlation data between spraying parameters and actual shear rate, thereby forming a set containing multiple available parameter combinations. This process ensures that the selected parameter combination makes the coating exhibit target rheological properties during spraying to adapt to the needs of the local geometric features of the workpiece. On this basis, the system evaluates the effect of each parameter combination in the set, predicts the film uniformity and coating utilization efficiency that each combination can achieve in spraying, using the correlation data between spraying parameters and paint film uniformity and coating utilization rate. This evaluation enables the system to compare the pros and cons of different parameter combinations. Finally, the system selects the combination that performs in line with the target from the spraying parameter set as the spraying parameter, according to the evaluated film uniformity and coating utilization rate.

[0149] This multi-stage screening, evaluation and optimization process ensures that the determined spraying parameters not only meet the requirements of the rheological properties of the coating on the workpiece surface, but also ensure that the spraying operation achieves high levels of paint film quality and coating consumption efficiency. Therefore, by comprehensively considering the real-time rheological properties of the coating, the local geometric features of the workpiece, and the influence of spraying parameters on paint film quality and coating utilization rate, the scheme forms a closed-loop optimization mechanism, thereby solving the problem of difficult to ensure that the film uniformity and coating utilization rate reach the expected level in traditional methods, improving the spraying quality and reducing the coating consumption.

[0150] In a specific implementation, in order to obtain the correlation data between the spraying parameters and the actual shear rate of the coating on the workpiece surface, and the correlation data between the spraying parameters and the film uniformity and the coating utilization rate, a series of controlled experiments or simulations can be performed in advance. For example, the spraying parameters such as the spray gun speed, the paint output, the atomization gas pressure, etc. can be systematically changed, the spraying is performed on the workpiece surface of different geometrical shapes, and the actual shear rate of the coating on the workpiece surface, the film thickness distribution, and the actual consumption of the coating are measured synchronously. These experimental data or simulation results can be sorted into a lookup table, or used to train a model, such as a model based on regression analysis or neural network, to establish the mapping relationship between the spraying parameters and these performance indicators. These correlation data can be stored in the database of the control system for real-time query and use. When determining the spraying parameter combination that meets the target shear rate range and forming the spraying parameter set, the system can first determine an expected coating apparent viscosity range according to the real-time obtained coating rheological property data and the target shear rate range of the current local area of the workpiece. Subsequently, the system can set multiple discrete values for each spraying parameter such as the spray gun speed, the paint output, the atomization gas pressure, etc. within the parameter adjustment range of the spraying equipment, and arrange and combine these discrete values to generate multiple candidate spraying parameter combinations. For each candidate combination, the system can use the pre-established correlation model of the spraying parameters and the actual shear rate to predict the actual shear rate that the coating can be subjected to on the workpiece surface. Only those candidate combinations whose predicted shear rate falls within the target shear rate range will be included in the spraying parameter set. Further, when evaluating the film uniformity and the coating utilization rate of each spraying parameter combination in the spraying parameter set, the system will call the pre-established correlation model of the spraying parameters and the film uniformity and the coating utilization rate for each spraying parameter combination in the set. These models can output the predicted film uniformity score (such as a uniformity index) and the coating utilization rate percentage according to the input spraying parameter combination. These predicted values provide an evaluation of the performance of each parameter combination. Finally, when determining an optimal spraying parameter combination according to the film uniformity and the coating utilization rate, the system can adopt a pre-set optimization strategy. For example, a score function can be defined, which sums the film uniformity score and the coating utilization rate with weights that can be adjusted according to production needs. The system traverses all combinations in the spraying parameter set, calculates their scores, and selects the combination with the highest score as the optimal spraying parameter combination. This optimal combination is then sent to the actuators of the spraying equipment to guide the spraying operation.

[0151] Preferably, step A402 can comprise:

[0152] determining, according to the real-time rheological property data, a target apparent viscosity range corresponding to the target shear rate range;

[0153] a plurality of discrete values of each spraying parameter are set within the adjustable range of the spraying parameters of the spraying equipment;

[0154] a plurality of candidate spraying parameter combinations are obtained by arranging and combining the discrete values of each spraying parameter;

[0155] for each candidate spraying parameter combination, the actual shear rate of the coating on the workpiece surface is calculated using the correlation data of the spraying parameters and the actual shear rate, and is denoted as a first shear rate;

[0156] the apparent viscosity of the coating at the first shear rate is determined according to the real-time rheological property data, and is denoted as a first apparent viscosity;

[0157] the candidate spraying parameter combination in which the first shear rate falls within the target shear rate range and the first apparent viscosity falls within the target apparent viscosity range is taken as the final spraying parameter combination, thereby forming the spraying parameter set.

[0158] The target apparent viscosity range refers to the appropriate viscosity range that the coating should exhibit on the workpiece surface corresponding to the target shear rate range, which can be directly mapped or calculated according to the target shear rate range through the apparent viscosity curve in the real-time rheological property data.

[0159] The adjustable range of the spraying parameters of the spraying equipment refers to the physical limits of the spraying gun speed, paint output, atomization pressure, and spraying width that can be set in actual operation of the spraying equipment, which can be determined through technical specifications provided by the equipment manufacturer or actual operation tests.

[0160] The discrete values refer to a limited number of discrete specific values set for each spraying parameter within the adjustable range of the spraying parameters, which can be selected through equal interval sampling, based on empirical values, or optimization algorithms.

[0161] The candidate spraying parameter combination refers to a potential spraying parameter configuration obtained by arranging and combining all possible permutations of the discrete values of each spraying parameter, which can be generated through an exhaustive method or a combination generator based on a specific algorithm.

[0162] The first shear rate refers to the actual shear rate of the coating on the workpiece surface under the action of a specific candidate spraying parameter combination, which can be obtained by consulting the correlation data of the spraying parameters and the actual shear rate or by a real-time calculation model.

[0163] The first apparent viscosity refers to the apparent viscosity exhibited by the coating at the first shear rate, which can be directly queried or interpolated and calculated according to the first shear rate through the apparent viscosity curve in the real-time rheological property data.

[0164] The present application can solve the problems of poor film uniformity and non-optimal paint utilization in the prior art by considering not only the actual shear rate of the paint on the workpiece surface when determining the spraying parameter combination, but also introducing a double constraint on the apparent viscosity of the paint. Specifically, the scheme first uses real-time rheological property data to determine a target apparent viscosity range corresponding to the target shear rate range determined according to the local geometric characteristics of the workpiece. This pre-step is the key to the present scheme, which closely combines the rheological properties of the paint with the actual requirements of the workpiece, providing a more complete rheological basis for subsequent parameter screening. On this basis, the system systematically sets multiple discrete values for each spraying parameter within the adjustable range of the spraying equipment, and generates a series of potential candidate spraying parameter combinations through permutation and combination, thereby constructing a complete parameter search space. For each candidate spraying parameter combination, the system accurately calculates the first shear rate that the paint may be subjected to on the workpiece surface under the combination using the pre-acquired correlation data between the spraying parameters and the actual shear rate. Then, the system determines the first apparent viscosity of the paint actually exhibited at the first shear rate using real-time rheological property data. This series of calculation steps ensures accurate prediction of the actual rheological state of the paint on the workpiece surface under each candidate parameter combination. Finally, the core of the present scheme lies in its screening logic: only when the first shear rate falls within the preset target shear rate range and the first apparent viscosity also falls within the pre-determined target apparent viscosity range, the candidate spraying parameter combination will be identified as the final spraying parameter combination that meets the requirements and be included in the spraying parameter set.

[0165] This double-constraint screening mechanism ensures that the selected spraying parameter combination can not only ensure that the paint is subjected to appropriate shear force on the workpiece surface, but also that its apparent viscosity is in an appropriate state, thereby better adapting to the local geometric characteristics of the workpiece, such as avoiding sagging at sharp edges and fully wetting at fine textures. In this way, the present scheme further refines the control of the rheological behavior of the paint based on the original determination of spraying parameters according to shear rate, enabling the spraying process to more accurately match the paint properties with the workpiece requirements, thereby improving the film uniformity and paint utilization.

[0166] Reference Figure 2 The present application provides a full-automatic spraying production line control system, which comprises:

[0167] A data acquisition module 1 is used to acquire real-time rheological property data of the paint; the real-time rheological property data includes an apparent viscosity curve representing the change of the apparent viscosity of the paint with the shear rate (the specific process can refer to step A1 in the foregoing text).

[0168] a feature acquisition module 2 configured to acquire local geometric feature information of a local region where a current spraying point of a workpiece to be sprayed is located (for a specific process, refer to step A2 in the foregoing description) ;

[0169] a range determination module 3 configured to determine a target shear rate range corresponding to the local region where the current spraying point is located according to the local geometric feature information (for a specific process, refer to step A3 in the foregoing description) ;

[0170] a parameter calculation module 4 configured to calculate a spraying parameter according to the real-time rheological characteristic data and the target shear rate range (for a specific process, refer to step A4 in the foregoing description) ;

[0171] a control module 5 configured to control a spraying device of an automatic spraying production line to perform a spraying operation according to the spraying parameter (for a specific process, refer to step A5 in the foregoing description).

[0172] The above merely describes embodiments of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A fully automatic spraying production line control method, characterized in that: The steps of the method include: A1 obtains real-time rheological property data of the coating; the real-time rheological property data includes an apparent viscosity curve indicating that the apparent viscosity of the coating changes with shear rate; A2. Obtaining local geometric feature information of the local area where the current spraying point of the workpiece to be sprayed is located; A3. Determine the target shear rate range corresponding to the local area where the current spray point is located based on the local geometric feature information; A4. Calculate spray parameters based on the real-time rheological data and the target shear rate range; A5. According to the spraying parameters, control the spraying equipment of the automatic spraying production line to perform the spraying operation; Step A4 includes: A401 obtains the correlation data between the spraying parameters and the actual shear rate of the coating on the workpiece surface, as well as the correlation data between the spraying parameters and the paint film uniformity and coating utilization; A402. Based on the real-time rheological characteristic data and the target shear rate range, combined with the associated data of the spraying parameters and the actual shear rate, determine a spraying parameter combination that meets the target shear rate range to form a spraying parameter set; A403. Evaluate the paint film uniformity and paint utilization rate of each spray parameter combination based on the spray parameter combination in the spray parameter set, combined with the associated data of the spray parameter and the paint film uniformity and paint utilization rate; A404. Determine an optimal spraying parameter combination based on the paint film uniformity and the paint utilization rate as the spraying parameter, Step A402 includes: determining a target apparent viscosity range corresponding to the target shear rate range based on the real-time rheological property data; Within the adjustable range of the spraying parameters of the spraying equipment, multiple discrete values ​​of each spraying parameter are set; Arrange and combine the discrete values ​​of each spraying parameter to obtain multiple candidate spraying parameter combinations; For each candidate spray parameter combination, using the correlation data between the spray parameters and the actual shear rate, calculate the actual shear rate of the coating on the workpiece surface, which is recorded as the first shear rate; Determining the apparent viscosity of the coating at the first shear rate based on the real-time rheological characteristic data, which is recorded as a first apparent viscosity; The candidate spraying parameter combination in which the first shear rate falls within the target shear rate range and the first apparent viscosity falls within the target apparent viscosity range is taken as the final spraying parameter combination to form the spraying parameter set.

2. A fully automatic spraying production line control method according to claim 1, characterized in that: Step A1 includes: A101. Obtain pressure and flow information of the coating in the delivery pipeline to determine the shear rate of the coating in the delivery pipeline; A102. Determine the apparent viscosity of the coating at the shear rate based on the pressure information, the flow information, and the shear rate; A103. Continuously acquire multiple shear rates and their corresponding apparent viscosities to form a preliminary apparent viscosity curve and determine the functional relationship between apparent viscosity and shear rate; A104. Generate an apparent viscosity curve segment corresponding to an extended shear rate range based on the functional relationship, denoted as an extended curve segment; the extended shear rate range is a shear rate range outside the acquired shear rate range; A105. Integrate the preliminary apparent viscosity curve and the extended curve segment to form a final apparent viscosity curve.

3. A fully automatic spraying production line control method according to claim 1, characterized in that: Step A2 includes: A201 obtains the overall geometric data of the workpiece to be sprayed; A202. Get the spatial coordinate information of the current spraying point; A203. According to the spatial coordinate information, determining the local area corresponding to the current spraying position from the overall geometric data; A204. According to the determined local area, extract the design geometric feature information corresponding to the local area from a preset feature information library to obtain the local geometric feature information of the determined local area.

4. A fully automatic spraying production line control method according to claim 1, characterized in that: Step A3 includes: A301. Extracting the geometric feature type of the local area where the current spray point is located from the local geometric feature information; A302. According to the geometric feature type, obtaining an initial shear rate range associated with the geometric feature type from a preset geometric-rheological rule library; A303. Adjust the initial shear rate range according to the geometric parameters included in the local geometric feature information to obtain the target shear rate range.

5. A fully automatic spraying production line control method according to claim 4, characterized in that: Step A303 includes: Obtaining local geometric feature information of a current spraying point and a preset number of previous spraying points; Determining a change trend of local geometric parameters based on local geometric feature information of the current spraying point and its previous spraying points; According to the change trend, the initial shear rate range is smoothly adjusted to obtain the target shear rate range.

6. A fully automatic spraying production line control method according to claim 5, characterized in that: The step of smoothly adjusting the initial shear rate range according to the change trend to obtain the target shear rate range includes: B1. Calculating the gradient of the local geometric parameters according to the change trend; B2. Get the current moving speed of the spraying equipment; B3. Determine, based on the change gradient and the current moving speed, an adjustment parameter for smoothly adjusting the initial shear rate range; the adjustment parameter includes an adjustment amount of at least one of the center position, width, upper limit, and lower limit of the shear rate range; B4. Adjust the initial shear rate range according to the adjustment parameters to obtain the target shear rate range.

7. A fully automatic spraying production line control method according to claim 6, characterized in that: Step B3 includes: B301. According to the change gradient, determine the gradient level corresponding to the change gradient; B302. According to the current moving speed, determine the speed level corresponding to the current moving speed; B303. Obtain the adjustment parameter from a preset adjustment parameter mapping relationship according to the gradient level and the speed level.

8. A fully automatic spraying production line control system, characterized in that: The system includes: A data acquisition module for acquiring real-time rheological property data of the coating; the real-time rheological property data includes an apparent viscosity curve representing the change of the apparent viscosity of the coating with shear rate; A feature acquisition module is used to obtain local geometric feature information of the local area where the current spraying point of the workpiece to be sprayed is located; a range determination module, configured to determine a target shear rate range corresponding to the local area where the current spraying point is located based on the local geometric feature information; A parameter calculation module, configured to calculate spraying parameters based on real-time rheological property data and the target shear rate range; A control module, used to control the spraying equipment of the fully automatic spraying production line to perform spraying operations according to the spraying parameters; The method for calculating the spraying parameters according to the real-time rheological property data and the target shear rate range includes: A401 obtains the correlation data between the spraying parameters and the actual shear rate of the coating on the workpiece surface, as well as the correlation data between the spraying parameters and the paint film uniformity and coating utilization; A402. Based on the real-time rheological characteristic data and the target shear rate range, combined with the associated data of the spraying parameters and the actual shear rate, determine a spraying parameter combination that meets the target shear rate range to form a spraying parameter set; A403. Evaluate the paint film uniformity and paint utilization rate of each spray parameter combination based on the spray parameter combination in the spray parameter set, combined with the associated data of the spray parameter and the paint film uniformity and paint utilization rate; A404. Determine an optimal spray parameter combination based on the paint film uniformity and the coating utilization rate as the spray parameter; Step A402 includes: determining a target apparent viscosity range corresponding to the target shear rate range based on the real-time rheological property data; Within the adjustable range of the spraying parameters of the spraying equipment, multiple discrete values ​​of each spraying parameter are set; Arrange and combine the discrete values ​​of each spraying parameter to obtain multiple candidate spraying parameter combinations; For each candidate spray parameter combination, using the correlation data between the spray parameters and the actual shear rate, calculate the actual shear rate of the coating on the workpiece surface, which is recorded as the first shear rate; Determining the apparent viscosity of the coating at the first shear rate based on the real-time rheological characteristic data, which is recorded as a first apparent viscosity; The candidate spraying parameter combination in which the first shear rate falls within the target shear rate range and the first apparent viscosity falls within the target apparent viscosity range is taken as the final spraying parameter combination to form the spraying parameter set.

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