Full-automatic spraying production line control method and system

Abstract

The invention belongs to the technical field of spraying, and discloses a full-automatic spraying production line control method and system, and the method comprises the steps: obtaining real-time rheological property data of a coating; the real-time rheological characteristic data comprises an apparent viscosity curve representing that the apparent viscosity of the coating changes along with the shear rate, and local geometric characteristic information of a local area where a current spraying point of the to-be-sprayed workpiece is located is obtained; according to the local geometric feature information, determining a target shearing rate range corresponding to a local area where the current spraying point is located; according to the real-time rheological characteristic data and the target shearing rate range, spraying parameters are obtained through calculation; according to the spraying parameters, spraying equipment of the full-automatic spraying production line is controlled to conduct spraying operation; therefore, the spraying parameters can be dynamically adjusted according to the real-time rheological characteristics of the coating and the local geometrical characteristics 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 a clear understanding of the relationship between the coating's rheological properties and the workpiece's surface microscopic features directly leads to uneven film formation on the workpiece surface, which in turn causes suboptimal coating consumption and product quality defects. For example, when spraying workpieces with sharp edges, the coating's apparent viscosity can drop dramatically at these edges, causing the paint to easily flow away from the edges, resulting in a thin film or "showing" defects. To compensate for these weak areas, the system or operator is often forced to increase the overall paint output or the number of spray passes. This can lead to excessive film thickness in other areas of the workpiece (such as flat surfaces or interior areas), causing problems such as sagging, orange peel, or slow drying, resulting in paint waste. Conversely, when spraying workpieces with fine texture or high porosity, if the coating's apparent viscosity is too high in these areas due to low shear, the paint may not fully wet and penetrate the workpiece, resulting in an uneven film, incomplete coverage of the texture, or even "dry spraying." This also requires increased paint volume or rework, indirectly increasing coating consumption.

[0007] Existing systems lack the ability to accurately assess and adaptively adjust the real-time apparent viscosity changes of the paint on different areas of the workpiece during the spraying process. They are unable to dynamically adjust spray parameters (such as gun speed, paint output, atomization pressure, and even spray pattern) based on the workpiece's local geometry and surface texture to ensure that the paint adheres and flows at the optimal effective viscosity across different areas. This lack of control mechanism makes it difficult to achieve precise paint matching and consumption optimization when processing a wide variety of workpieces with complex surfaces, and it also makes it difficult to maintain high product quality consistency.

[0008] In view of the above problems, the existing technology is in urgent need of improvement. Summary of the Invention

[0009] The purpose of this application is to provide a fully automatic spraying production line control method and system, which can dynamically adjust the spraying parameters according to the real-time rheological properties of the coating and the local geometric characteristics 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 method comprising the steps of: 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 fully automatic spraying production line to perform the spraying operation.

[0011] Preferably, 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.

[0012] Preferably, 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.

[0013] Preferably, 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.

[0014] Preferably, 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.

[0015] Preferably, 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.

[0016] Preferably, 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.

[0017] Preferably, 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.

[0018] Preferably, 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.

[0019] In a second aspect, the present application provides a fully automatic spraying production line control system, the system comprising: 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 the real-time rheological characteristic data and the target shear rate range; The control module is used to control the spraying equipment of the fully automatic spraying production line to perform spraying operations according to the spraying parameters.

[0020] Beneficial effects: The present application provides a fully automatic spray production line control method and system, which achieves precise matching of the rheological characteristics of the coating and the microscopic characteristics of the workpiece surface by acquiring the rheological characteristics data of the coating and the local geometric characteristics of the workpiece in real time, and dynamically calculating and adjusting the spray parameters based on the two, thereby being able to dynamically adjust the spray parameters according to the real-time rheological characteristics of the coating and the local geometric characteristics of the workpiece, thereby improving the spraying quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 Flowchart of the fully automatic spraying production line control method provided in an embodiment of the present application.

[0022] Figure 2 This is a schematic diagram of the structure of the fully automatic spraying production line control system provided in an embodiment of the present application.

[0023] Explanation of the reference numbers: 1. Data acquisition module; 2. Feature acquisition module; 3. Range determination module; 4. Parameter calculation module; 5. Control module. DETAILED DESCRIPTION

[0024] The technical model in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. The components of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for protection, but merely represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work fall within the scope of protection of this application.

[0025] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0026] refer to Figure 1 , this application proposes a fully automatic spraying production line control method, 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 fully automatic spraying production line to perform the spraying operation.

[0027] Among them, real-time rheological property data refers to the viscosity characteristics of the coating at different shear rates, which can be obtained by using an online rheological measurement unit, a viscosity sensor combined with a pressure flow sensor, etc. For example, the shear rate and apparent viscosity can be inferred by measuring the pressure and flow of the coating in the conveying pipeline. Its main purpose is to obtain the dynamic viscosity change law of the coating during the actual spraying process.

[0028] Among them, local geometric feature information refers to the geometric data of the area around a specific spraying point on the workpiece to be sprayed, which can be obtained by using a three-dimensional scanner, a machine vision system or extracted from a CAD model. For example, by identifying the roughness, texture, porosity, sharp edges or deep grooves on the workpiece surface, it is mainly to identify the microstructure of the workpiece surface that affects the rheological behavior of the coating.

[0029] Among them, the target shear rate range refers to the shear rate range required to achieve paint film quality and paint utilization when the paint is sprayed on a specific local area of ​​the workpiece. It can be obtained based on a preset geometric-rheological rule library or through model deduction. For example, a lower shear rate range is set for sharp edge areas to prevent sagging. Its main purpose is to convert the local geometric characteristics of the workpiece into the rheological targets of the coating.

[0030] Among them, spraying parameters refer to the various adjustable variables that control the operation of the spraying equipment, which may include part or all of the spray gun movement speed, paint output, atomization pressure, spray width shape, etc., which are mainly used to directly control the actual shear state and deposition effect of the coating on the workpiece surface.

[0031] The core innovation of this application lies in that by associating the real-time rheological properties data of the coating with the local geometric feature information of the workpiece to be sprayed, and obtaining the spraying parameters based on this dynamic calculation, the problem in the existing technology that the spraying parameters cannot adapt to the dynamic rheological properties of the coating and the local geometric differences of the workpiece is solved, thereby achieving the effect of improving the spraying quality.

[0032] Specifically, this method first obtains the real-time rheological property data of the coating, which reflects the law of change of the apparent viscosity of the coating with shear rate, ensuring the understanding of the coating state. At the same time, the local geometric feature information of the local area of ​​the current spraying point of the workpiece to be sprayed is obtained to identify the microstructure of the workpiece surface that affects the rheological behavior of the coating. Subsequently, based on this local geometric feature information, the target shear rate range required for the coating to be sprayed in this local area is determined, and the physical properties of the workpiece are converted into the rheological target of the coating. Then, combining the obtained real-time rheological property data of the coating and the determined target shear rate range, the system calculates the appropriate spray parameter combination that can enable the coating to reach the target shear rate range in this local area. Finally, based on the calculated spray parameters, the spray equipment of the fully automatic spray production line is controlled to perform the spraying operation. The entire process forms a closed loop, allowing the spray equipment to be adaptively adjusted according to the real-time state of the coating and the local needs of the workpiece, ensuring that the coating is sprayed in a manner suitable for the current local area of ​​the workpiece and the real-time state of the coating itself.

[0033] Through the above scheme, this application solves the problem that existing fully automatic spray production line control methods are unable to dynamically adjust spray parameters according to the real-time rheological properties of the coating and the local geometric characteristics of the workpiece. This method can ensure that the coating is spread with an appropriate apparent viscosity in different areas of the workpiece surface, thereby avoiding the occurrence of defects such as uneven paint film, sagging, exposed 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 coating in different areas, unnecessary paint waste can be reduced, the utilization efficiency of the coating can be improved, and production costs can be reduced.

[0034] In some embodiments, step A1 comprises: 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.

[0035] The pressure information refers to the pressure value that the paint bears when flowing in the conveying pipeline, and can be monitored in real time using a pressure sensor installed on the pipeline.

[0036] The flow rate information refers to the volume or mass of paint flowing through the delivery pipeline per unit time, which can be measured in real time using a flow meter.

[0037] Shear rate refers to the velocity gradient between adjacent layers within a fluid, reflecting the shear strength experienced by the fluid. In pipeline flow, it can be calculated using fluid mechanics formulas based on the pipeline geometry, flow rate, and fluid type. For example, for laminar flow in a circular pipeline, the shear rate can be calculated using Poiseuille's law for Newtonian fluids or a modified formula for non-Newtonian fluids.

[0038] Among them, apparent viscosity refers to the viscosity of non-Newtonian fluid at a specific shear rate. It is not a constant, but changes with the shear rate. It can be derived through rheological principles based on the pressure loss of the fluid in the pipeline (which can be obtained by calculating the difference in pressure information between the inlet and outlet of the pipeline), flow rate and shear rate.

[0039] Among them, the functional relationship refers to the mathematical mapping relationship between apparent viscosity and shear rate, which can be established using rheological models such as polynomial fitting, exponential fitting, power law model, Herschel-Bulkley model, etc. to describe the viscosity behavior of the coating under different shear conditions.

[0040] Among them, the extended shear rate range refers to the shear rate range that the coating may experience during the actual spraying process but the data is not obtained through direct measurement, such as extremely high shear rates (such as during nozzle atomization) or extremely low shear rates (such as when the coating spreads and flows flat on the workpiece surface).

[0041] The method first obtains the pressure information and flow information of the paint 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 paint in the pipeline in real time. Based on this information, the shear rate of the paint in the conveying pipeline can be determined in step A101, and the apparent viscosity of the paint at the current shear rate can be determined indirectly in real time based on the pressure information, flow information and the determined shear rate in step A102. This indirect measurement method avoids the difficulty of performing complex measurements directly under a wide range of shear rates and provides basic, real-time measurement data points for the subsequent construction of the viscosity curve. On this basis, step A103 continuously obtains multiple shear rates and their corresponding apparent viscosities, thereby forming a preliminary apparent viscosity curve. More importantly, this step further determines the functional relationship between apparent viscosity and 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 a shear rate range that is not directly measured, overcoming the limitations of relying solely on discrete measurement point data. Subsequently, step A104 generates an apparent viscosity curve segment corresponding to the extended shear rate range based on the functional relationship determined in step A103. The extended shear rate range here specifically refers to the shear rate range outside the acquired shear rate range, such as the extremely high shear rates during spray atomization or the extremely low shear rates when the coating is spreading on the workpiece surface. This means that even when the coating experiences these shear rates that are difficult to directly and accurately measure, reasonable inferences and supplementation can be made through mathematical models to obtain more complete viscosity curve data. Finally, step A105 integrates the preliminary apparent viscosity curve and the extended curve segment (for example, by directly splicing them or further smoothing the splicing position) to form the final apparent viscosity curve. This integration ensures that the final apparent viscosity curve not only includes data based on actual measurements, but also covers a wider shear rate range through model expansion.

[0042] In this way, this method can provide more comprehensive and accurate real-time rheological property data of the coating. When applied to the subsequent calculation of spray parameters, the calculated spray parameters can more accurately match the actual rheological behavior of the coating on different areas of the workpiece surface, thereby improving the refinement of spray control and ensuring that the dynamic behavior of the coating under different shear conditions is fully considered, thereby optimizing spray quality and coating utilization efficiency.

[0043] In some embodiments, step A2 comprises: 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.

[0044] Among them, 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 the workpiece design. These data can contain precise geometric parameters and properties of different geometric feature types (such as planes, curved surfaces, sharp edges, grooves, and textured areas). Furthermore, the design geometric feature information refers to the geometric feature types and corresponding geometric parameters and properties defined based on the workpiece design intent and engineering specifications, such as curvature radius, chamfer angle, groove depth, texture type, or surface roughness parameters. This information is different from simple surface point cloud data or general geometric descriptions. They are directly related to the rheological behavior of the coating on these specific geometric structures, providing more refined and accurate input for subsequent spray parameter optimization.

[0045] Through the above-mentioned refinement steps, this application achieves accurate acquisition of local geometric feature information of a workpiece. Specifically, the overall geometric data of the workpiece is first acquired, which lays the foundation for a comprehensive understanding of the workpiece's geometric morphology. Subsequently, by obtaining the spatial coordinate information of the current spraying point, the system can accurately locate the current position of the spraying operation. Based on this spatial coordinate information, the local area 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 targetedness of data processing. More importantly, after determining the local area, the system no longer relies solely on general surface features, but instead extracts design geometric feature information that matches the local area from a preset feature information library containing rich design details. This design geometric feature information is key information that has been engineered and directly affects the rheological behavior of the coating. In this way, the acquired local geometric feature information not only reflects the physical morphology of the workpiece, but also includes optimized key geometric parameters that have a direct impact on the rheological properties of the coating. As a result, this precise and instructive local geometric feature information can provide a solid data foundation for the subsequent determination of the target shear rate range. When this precise local geometric feature information is used to determine the target shear rate range, the actual shear state of the coating at different areas of the workpiece surface can be more accurately predicted.

[0046] This precise prediction of the shear state, combined with real-time rheological data from the coating, allows the calculation and optimization of spray parameters to be more accurately tailored to the workpiece's actual geometry and the coating's rheological response. Therefore, by providing highly accurate and relevant local geometric feature information, this solution significantly improves the accuracy of spray parameter optimization, effectively resolving the problem of poor spraying results caused by inaccurate or incomplete local geometric feature information. This ensures a uniform paint film on complex workpiece surfaces and reduces paint waste.

[0047] As a preferred embodiment, when acquiring the overall geometric data of the workpiece to be sprayed, a computer-aided design (CAD) model can be used, or the actual workpiece can be scanned using a high-precision 3D scanning device (such as a laser scanner or structured light scanner) to generate point cloud data or a triangular mesh model. When acquiring the spatial coordinate information of the current spray point, the encoder feedback system of the spraying device (such as a spray robot) can be utilized, or a visual positioning system can be combined to track the spray gun tip in real time to obtain its precise position in the workpiece coordinate system. Based on the workpiece design, the workpiece surface can be pre-divided into multiple local regions with consistent internal geometric features. The position information and design geometric feature information of each local region can be stored in a preset feature information library. When the local region corresponding to the current spray position is determined from the overall geometric data based on the spatial coordinate information, the position information of each preset local region can be used to identify the preset local region within which the precise position of the current spray point in the workpiece coordinate system falls. Furthermore, based on the determined local region, the design geometric feature information corresponding to the local region can be extracted from the preset feature information library as the local geometric feature information.

[0048] In some embodiments, step A3 comprises: 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.

[0049] The geometric feature type refers to the identification for classifying the geometric shape of the local area of ​​the workpiece, such as plane, edge, hole, groove, protrusion, etc., which can be implemented using predefined enumeration values, string labels or classification codes.

[0050] The geometry-rheology rule base refers to a knowledge base that stores the association between different geometric feature types and the corresponding coating rheological behavior (especially the shear rate range). It can be implemented using a lookup table, a database, or a mapping relationship built based on a machine learning model.

[0051] The initial shear rate range refers to the shear rate interval obtained from the geometry-rheology rule library according to the identified geometric feature type and has not been fine-tuned. It can be expressed as a pair of minimum and maximum shear rates, or a center value and an allowable deviation range.

[0052] Among them, geometric parameters refer to specific numerical values ​​that quantitatively describe the type of geometric features, such as the curvature radius of the edge, the depth, width, angle of the groove, or the roughness value of the surface, etc., which can be expressed in the form of numerical values, vectors or structured data.

[0053] When determining the target shear rate range, this solution first determines the geometric feature type of the local area where the current spraying point is located based on the local geometric feature information, and classifies the complex local geometric forms of the workpiece into manageable categories, such as distinguishing planes, edges or grooves. Subsequently, the system obtains the initial shear rate range associated with the type from the preset geometric-rheological rule library based on the determined geometric feature type. This rule library pre-establishes empirical or experimental data on the rheological behavior of the coating under different geometric feature types, thereby providing a benchmark shear rate range for specific geometric forms. On this basis, in order to further improve the accuracy, this solution uses the geometric parameters contained in the local geometric feature information to fine-tune the initial shear rate range and finally obtain the target shear rate range. This adjustment takes into account the subtle effects on the rheological behavior of the coating under the same geometric feature type, such as edges with different curvature radii or grooves of different depths.

[0054] This step-by-step refinement, from macroscopic type identification to microscopic parameter adjustment, ensures that the target shear rate range closely matches the actual local geometric features of the workpiece. This precise match enables the subsequent calculation of spray parameters to more accurately reflect the actual rheological response of the coating on different areas of the workpiece surface, effectively resolving the problems of uneven paint films and paint waste caused by a mismatch between the coating's rheological properties and the workpiece's surface microscopic features.

[0055] Preferably, step A303 may include: 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.

[0056] Among them, the changing trend of local geometric parameters refers to the continuous changing pattern or direction of the geometric characteristic parameters of the workpiece surface on the spraying path, such as curvature, slope or edge proximity, as the spraying point moves. It can be identified by mathematical analysis of a series of continuous local geometric parameter data, such as calculating differences, derivatives, or applying regression analysis, moving average and other algorithms.

[0057] Among them, smooth adjustment refers to the correction process of the initial shear rate range, so that the adjusted target shear rate range shows gradual and continuous changes between consecutive spraying points to avoid sudden changes. It can be achieved by introducing adjustment parameters. These parameters can be calculated based on factors such as change trend, change gradient or spraying speed, and applied 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.

[0058] This solution no longer relies solely on the instantaneous geometric characteristics of the current spray point when determining the target shear rate range. Instead, it acquires local geometric characteristics from the current spray point and a preset number of previous spray points, thereby establishing a data stream that dynamically evolves the workpiece surface geometry along the spray path. Based on this continuous geometric feature information, the system can deeply analyze and determine the changing trends of local geometric parameters. This identification of changing trends enables the system to predict the future direction of the workpiece surface geometry, such as whether the curvature will gradually increase or decrease, or whether an edge is about to be encountered. This forward-looking trend assessment enables the system to smoothly adjust the initial shear rate range obtained from a preset rule base. This smooth adjustment mechanism ensures that the target shear rate range is changed gradually and continuously, avoiding abrupt adjustments in the shear rate range caused by sudden changes in geometric characteristics. This approach also enables smoother adjustment of spray parameters, ensuring more stable leveling and uniform film thickness on the workpiece surface, especially in the transition areas between geometric features. Compared with the solution that only adjusts according to the current point geometric parameters, this significantly improves the stability of the spraying process and the quality of the paint film, effectively avoids defects such as sagging and uneven thickness, and thus achieves high-quality continuous spraying.

[0059] Furthermore, the step of smoothly adjusting the initial shear rate range according to the change trend to obtain the target shear rate range may include: 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.

[0060] The gradient of a local geometric parameter refers to the rate of change of the local geometric parameter in space or time. It quantifies the severity and direction of the change in the geometric feature. It can be obtained by performing differential calculations on continuously collected local geometric parameter data, derivative calculations after curve fitting, or edge detection algorithms based on image processing.

[0061] Among them, the adjustment parameter refers to the specific numerical value or proportional factor used to fine-tune the initial shear rate range, which can be determined by a preset lookup table, an inference rule based on fuzzy logic, or a functional relationship obtained through machine learning model training.

[0062] This solution specifies and refines the steps for smoothly adjusting the initial shear rate range based on the changing trend. First, the system calculates the gradient of the local geometric parameters based on their changing trends. This gradient information quantifies the abstract changing trend, providing information on the rate and intensity of dynamic changes in the workpiece surface geometry. For example, when the sprayer moves rapidly from a flat area to a sharp edge, the gradient increases significantly, indicating that the coating will experience a dramatic change in the shear environment within a short period of time. Simultaneously, the system obtains the current speed of the sprayer. The speed of the sprayer directly affects the actual shear duration and intensity of the coating on the workpiece surface. High speeds may require faster or larger adjustments to the shear rate range, while low speeds allow for more precise adjustments. The system then combines the calculated gradient with the current speed to determine the adjustment parameters for smoothly adjusting the initial shear rate range. These adjustment parameters are specific, quantified values ​​and can include adjustments to the center position, width, and upper or lower limits of the shear rate range. This comprehensive consideration of multi-dimensional dynamic information enables the adjustment strategy to more intelligently and precisely adapt to the dynamic changes in workpiece geometry and the real-time motion of the sprayer. For example, when the gradient is large and the movement 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 paint can still maintain the appropriate effective viscosity in the rapidly changing geometric area. Ultimately, the system accurately adjusts the initial shear rate range based on these determined adjustment parameters to obtain a target shear rate range that has been finely smoothed and dynamically optimized. This target range can more accurately reflect the shear environment that the paint should withstand at the current spraying point, thereby guiding the calculation of subsequent spraying parameters.

[0063] In this way, this solution, based on the identification of the trend of changes in local geometric parameters, further introduces two key dynamic factors: the change gradient and the equipment movement speed. This makes the determination of the target shear rate range no longer a simple trend adjustment, but an adaptive optimization based on quantitative data and real-time status. This ensures that the paint can adhere and level at 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 paint, and solving the problem of insufficient adjustment accuracy due to trend judgment alone. This refined adjustment mechanism is 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 this information to form a more complete and adaptive spray control closed loop, which enables the entire spray process to dynamically respond to the complex changes of the workpiece and equipment, and achieve accurate matching and efficient utilization of the paint.

[0064] Furthermore, step B3 may include: 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.

[0065] 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.

[0066] 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.

[0067] 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.

[0068] 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.

[0069] In a specific embodiment, in order to determine the adjustment parameters for smoothly adjusting the initial shear rate range, the following method can be used. First, a series of thresholds can be set for the gradient of the local geometric parameters to divide the gradient level. For example, when the gradient is less than a first gradient threshold, it can be classified as a low gradient level; when the gradient is between the first gradient threshold and the second gradient threshold, it can be classified as a medium gradient level; and when the gradient is greater than the second gradient threshold, it can be classified as a high gradient level. These gradient thresholds can be set based on the geometric complexity of the actual sprayed workpiece and experience. At the same time, similar thresholds can be set for the current movement speed of the spraying equipment to divide the speed level. For example, when the movement speed is less than a first speed threshold, it can be classified as a slow speed level; when the movement speed is between the first speed threshold and the second speed threshold, it can be classified as a medium speed level; and when the movement speed is greater than the second speed threshold, it can be classified as a fast speed level. These speed thresholds can be set based on 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 parameters from a preset two-dimensional lookup table. The lookup table's row indices can correspond to different gradient levels, and its column indices can correspond to different speed levels. Each cell in the lookup table stores a specific adjustment parameter value for the corresponding gradient level and speed level combination, such as the adjustment amount for the center position of the shear rate range or the adjustment amount for the width. In actual operation, the control system can directly query the lookup table based on the gradient level and speed level determined in real time, quickly obtaining the required adjustment parameters and adjusting the initial shear rate range.

[0070] In some embodiments, step A4 comprises: 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.

[0071] Among them, the correlation data between the spraying parameters and the actual shear rate of the coating on the workpiece surface refers to the data set or model that describes 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. It can be established and represented by experimental data, simulation models or machine learning models.

[0072] Among them, the correlation data between spraying parameters and paint film uniformity and paint utilization rate refers to the data set or model that describes how the various operating parameters of the spraying equipment affect the thickness uniformity of the paint film and the efficiency of the paint utilization during the spraying process. It can be established and represented by historical production data, quality inspection data or prediction algorithms.

[0073] A spray parameter combination refers to a set of simultaneously effective spray parameter configurations, such as a spray gun speed, a paint output, and an atomization pressure. A spray parameter set refers to a collection of multiple spray parameter combinations that meet certain conditions. These combinations are feasible spray solutions under certain constraints.

[0074] Among them, the optimal spraying parameter combination refers to the spraying parameter combination in the spraying parameter set that, after evaluation, achieves the target or meets the preset optimization target in terms of paint film uniformity and paint utilization.

[0075] Building on the basic method of calculating spray parameters based on real-time rheological data and a target shear rate range, this solution further utilizes data correlating spray parameters with spray results, as well as evaluating and optimizing spray parameter combinations. Specifically, by first acquiring data correlating spray parameters with the actual shear rate experienced by the coating on the workpiece surface, as well as data correlating spray parameters with paint film uniformity and coating utilization, this system lays the data foundation for subsequent parameter calculation and optimization. This correlation data enables the system to predict the rheological behavior and spray quality of the coating under different spray parameters. Secondly, based on the real-time coating rheological data and the target shear rate range determined for the localized area of ​​the workpiece, combined with established data correlating spray parameters with actual shear rates, the system selects spray parameter combinations that achieve the target shear rate range on the workpiece surface, thereby forming a set of multiple available parameter combinations. This process ensures that the selected parameter combination results in the coating exhibiting the desired rheological properties during the spraying process, tailored to the local geometry of the workpiece. On this basis, the system evaluates the effectiveness of each parameter combination in the set. Using data related to spray parameters, paint film uniformity, and paint utilization, it predicts the film uniformity and paint utilization efficiency that each combination can achieve during spraying. This evaluation enables the system to compare the pros and cons of different parameter combinations. Ultimately, based on the evaluated paint film uniformity and paint utilization, the system selects the combination from the spray parameter set that meets the target performance as the spray parameter.

[0076] This multi-stage screening, evaluation, and optimization process ensures that the determined spray parameters not only meet the coating's rheological properties on the workpiece surface, but also ensure high levels of paint film quality and paint consumption efficiency during the spraying process. Therefore, this solution comprehensively considers the effects of the coating's real-time rheological properties, the workpiece's local geometric characteristics, and the spraying parameters on paint film quality and paint utilization, forming a closed-loop optimization mechanism. This solves the problem of traditional methods struggling to ensure the desired paint film uniformity and paint utilization, thereby improving spray quality and reducing paint consumption.

[0077] 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, as well as the correlation data between the spraying parameters and the paint film uniformity and the coating utilization rate, a series of controlled experiments or simulations can be carried out in advance. For example, the spraying parameters such as the spray gun speed, the paint output, the atomizing air pressure can be systematically changed, and the coating can be sprayed on the surface of the workpiece with different geometric shapes, and the actual shear rate of the coating on the workpiece surface, the paint film thickness distribution and the actual consumption of the coating can be measured synchronously. These experimental data or simulation results can be organized into a lookup table, or used to train a model, such as a model based on regression analysis or a neural network, so as to establish a 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 a spraying parameter set, the system can first determine a desired coating apparent viscosity range based on the real-time obtained coating rheological property data and the target shear rate range of the current workpiece local area. The system then sets multiple discrete values ​​for various spray parameters, such as spray gun speed, paint output, and atomizing pressure, within the spray equipment's parameter adjustment range. These discrete values ​​are then permuted and combined to generate multiple candidate spray parameter combinations. For each candidate combination, the system uses a pre-established model linking spray parameters to actual shear rates to predict the actual shear rate the paint may experience on the workpiece surface. Only those candidate combinations whose predicted shear rates fall within the target shear rate range are included in the spray parameter set. Furthermore, when evaluating the paint film uniformity and paint utilization efficiency of each spray parameter combination in the set, the system invokes pre-established models linking spray parameters to these factors for each spray parameter combination. These models output a predicted paint film uniformity score (e.g., a uniformity index) and paint utilization percentage based on the input spray parameter combination. These predicted values ​​provide an assessment of the performance of each parameter combination. Finally, the system employs a pre-defined optimization strategy to determine the optimal spray parameter combination based on paint film uniformity and paint utilization efficiency. For example, a scoring function can be defined that takes the weighted sum of the paint film uniformity score and paint utilization rate, with the weights adjusted based on production needs. The system then iterates over all combinations of spray parameters, calculates their scores, and selects the one with the highest score as the optimal spray parameter combination. This optimal combination is then sent to the actuator of the spray equipment to guide the spraying operation.

[0078] Preferably, step A402 may include: 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.

[0079] 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. It can be directly mapped or calculated based on the target shear rate range using the apparent viscosity curve in the real-time rheological property data.

[0080] Among them, the adjustable range of the spraying parameters of the spraying equipment refers to the physical limits that can be set for parameters such as spray gun speed, paint output, atomization pressure, and spray width during actual operation of the spraying equipment. It can be determined through technical specifications provided by the equipment manufacturer or actual operation tests.

[0081] The discrete value refers to a limited number of discontinuous specific values ​​set for each spray parameter within the adjustable range of the spray parameter, which can be selected through equal-interval sampling, based on empirical values ​​or optimization algorithms.

[0082] The candidate spray parameter combination refers to a potential spray parameter configuration obtained by performing all possible permutations and combinations of discrete values ​​of each spray parameter, which can be generated by an exhaustive method or a combination generator based on a specific algorithm.

[0083] The first shear rate refers to the shear rate that the coating actually experiences on the workpiece surface under the action of a specific candidate spray parameter combination, which can be obtained by consulting the correlation data between the spray parameters and the actual shear rate or through a real-time calculation model.

[0084] The first apparent viscosity refers to the apparent viscosity of the coating at the first shear rate, which can be obtained by directly querying or interpolating the apparent viscosity curve in the real-time rheological property data according to the first shear rate.

[0085] This application not only takes into account the actual shear rate to which the coating is subjected on the workpiece surface when determining the spray parameter combination, but also further introduces a dual constraint on the apparent viscosity of the coating, thereby being able to solve the problems of poor paint film uniformity and non-optimal coating utilization in the prior art. Specifically, the solution first uses real-time rheological property data to synchronously determine a target apparent viscosity range corresponding to the shear rate range based on the target shear rate range determined by the local geometric characteristics of the workpiece. This pre-step is the key to this solution. It closely combines the rheological properties of the coating with the actual needs 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 spray parameter within the adjustable parameter range of the spray equipment, and generates a series of potential candidate spray parameter combinations through permutations and combinations, thereby constructing a complete parameter search space. For each candidate spray parameter combination, the system uses the pre-acquired correlation data between the spray parameters and the actual shear rate to accurately calculate the first shear rate that the coating may withstand on the workpiece surface under this combination. Next, the system will again use the real-time rheological property data to determine the first apparent viscosity of the coating at the shear rate based on the calculated first shear rate. This series of calculation steps ensures an accurate prediction of the actual rheological state of the coating on the workpiece surface under each candidate parameter combination. Ultimately, the core of this solution lies in its screening logic: only when the first shear rate falls within the preset target shear rate range, and at the same time, the first apparent viscosity also falls within the predetermined target apparent viscosity range, will the candidate spray parameter combination be identified as the final spray parameter combination that meets the requirements and be included in the spray parameter set.

[0086] This dual-constraint screening mechanism ensures that the selected spray parameter combination not only ensures that the coating withstands appropriate shear forces on the workpiece surface, but also maintains an appropriate apparent viscosity, allowing it to better adapt to the workpiece's local geometric characteristics, such as avoiding sagging at sharp edges and fully wetting subtle textures. In this way, this solution further refines the control of the coating's rheological behavior, building on the existing method of determining spray parameters based on shear rate. This allows the spray process to more accurately match coating properties with workpiece requirements, thereby improving paint film uniformity and coating utilization.

[0087] refer to Figure 2 , the present application provides a fully automatic spraying production line control system, the system includes: Data acquisition module 1 is used to acquire 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 (the specific process can be referred to step A1 above); Feature acquisition module 2, used to obtain local geometric feature information of the local area where the current spraying point of the workpiece to be sprayed is located (the specific process can be referred to step A2 above); Range determination module 3, for determining a target shear rate range corresponding to the local area where the current spraying point is located based on the local geometric feature information (for details, please refer to step A3 above); Parameter calculation module 4, used to calculate spraying parameters based on the real-time rheological characteristic data and the target shear rate range (the specific process can be referred to step A4 above); The control module 5 is used to control the spraying equipment of the full-automatic spraying production line to perform spraying operations according to the spraying parameters (the specific process can be referred to the above step A5).

[0088] The above description is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, various modifications and variations of the present application are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection 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 fully automatic spraying production line to perform the spraying operation.

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. The method for controlling a fully automatic spraying production line according to claim 1, characterized in that: 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.

9. A fully automatic spraying production line control method according to claim 8, characterized in that: 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.

10. 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 the real-time rheological characteristic data and the target shear rate range; The control module is used to control the spraying equipment of the fully automatic spraying production line to perform spraying operations according to the spraying parameters.

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