A method and system for real-time monitoring of the thickness of electrostatically sprayed powder coating deposits

Abstract

This application relates to the technical field of intelligent control for electrostatic powder coating spraying, and provides a method and system for real-time monitoring of the deposition thickness of electrostatic powder coatings. The method includes constructing and storing the calculation relationship between the electrostatic powder deposition thickness and the cured coating film thickness in an intelligent agent; acquiring real-time powder deposition thickness information at 2-20 locations within a target area; determining the average real-time powder deposition thickness information for the target area; and then, based on this, the intelligent agent calculates the expected film thickness according to the relationship, compares it with the target film thickness in real time, and generates and executes spray gun control commands: if the thickness is less than the target film thickness, spraying continues; if the thickness is equal to or greater than the target film thickness, spraying stops immediately. This application can reduce the high dependence on human experience, avoid uneven film thickness, improve the overall uniformity of the powder coating and the level of intelligent spraying, improve the reliability and uniformity of the spraying process, ensure the stability of product quality, and reduce the impact of human factors on production efficiency.

Description

Technical Field

[0001] This application relates to the technical field of intelligent control of electrostatic powder coating, and more specifically, to a method and system for real-time monitoring of the deposition thickness of electrostatic powder coating.

[0002] This method and system are applicable to automated spraying production lines, and are especially suitable for powder coating scenarios with high requirements for coating thickness consistency, uniformity and production stability, such as electrostatic powder coating processes for workpieces such as appliance casings, building profiles, metal components and mechanical parts. Background Technology

[0003] Electrostatic powder coating technology is an advanced process that uses electrostatic principles to uniformly spray powder coatings onto the surface of a workpiece. This technology is not only environmentally friendly and solvent-free, reducing the emission of harmful gases, but also achieves a powder utilization rate of over 90%, minimizing material waste. Its coatings possess excellent wear resistance and corrosion resistance, and are suitable for a variety of colors and effects, meeting diverse design needs and making it an important choice for modern coating processes.

[0004] Currently, electrostatic powder coating processes are highly dependent on manual experience. Operators need to adjust parameters such as spray gun voltage, powder flow rate, spraying time, and spray gun movement trajectory based on their own experience. After spraying, the workpiece enters a curing oven for high-temperature curing, and then the film thickness is measured using a film thickness gauge to determine whether the coating meets design requirements. This process not only relies heavily on manual experience—the timing of stopping spraying is usually judged by the operator based on experience, leading to significant differences in operation between different personnel and making it difficult to ensure batch consistency—but also, film thickness testing is usually performed after curing. Once insufficient or excessive film thickness is found, it is difficult to repair, requiring rework or scrapping, resulting in low production efficiency. In addition, the lack of a real-time data feedback mechanism makes it difficult to deeply integrate with automated spraying equipment, MES systems, and intelligent manufacturing systems.

[0005] Therefore, how to obtain real-time powder deposition thickness information during the spraying process, and predict and control the final expected paint film thickness based on this information, so as to achieve active control of coating quality during the spraying stage, has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0006] Based on this, the present application provides a method and system for real-time monitoring of the deposition thickness of electrostatic powder coatings, in order to solve the problems of reliance on manual experience, detection lag, and poor film thickness consistency in the existing powder coating process.

[0007] In a first aspect, embodiments of this application provide a method for real-time monitoring of the deposition thickness of electrostatic powder coatings, the method comprising:

[0008] Obtain the experimental dataset, construct the target relationship information based on the experimental dataset, and store the target relationship information in the preset intelligent agent. The target relationship information is used to describe the calculated relationship between the electrostatic spraying powder deposition thickness and the coating film thickness after curing. In response to the start spraying command, real-time powder deposition thickness information is obtained based on three or more measurement sensors. The real-time powder deposition thickness information is obtained by laser measurement, ultrasonic measurement, electromagnetic wave measurement and / or AI vision measurement. The three or more measurement sensors use the same or different test methods and are all pre-installed on the target spray gun. Based on real-time powder deposition thickness information and target relationship information, the expected paint film thickness information is generated; Based on the expected paint film thickness information and the reference film thickness information, spray gun control commands are generated and executed.

[0009] Compared with existing technologies, the beneficial effects are as follows: The real-time monitoring method for electrostatic powder coating deposition thickness provided in this application allows the terminal device to first acquire experimental datasets, construct target relationship information based on the experimental datasets, and store the target relationship information in a preset intelligent agent. Then, in response to the start spraying command, it acquires real-time powder deposition thickness information based on three or more measurement sensors. Based on the real-time powder deposition thickness information and the target relationship information, it generates expected paint film thickness information. Finally, based on the expected paint film thickness information and the reference film thickness information, it generates and executes spray gun control commands. This avoids the situation of high dependence on human experience, reduces uneven film thickness distribution, significantly improves production reliability, and realizes the prediction and control of the final expected paint film thickness. This enables real-time closed-loop control of the spray gun spraying process, improves the reliability, uniformity, and intelligence level of the spraying process, and to a certain extent solves the problems of current powder spraying processes relying on human experience, detection lag, and poor film thickness consistency.

[0010] Secondly, embodiments of this application provide a real-time monitoring system for the deposition thickness of electrostatic powder coatings, the system comprising: Target Relationship Information Construction Module: This module is used to acquire experimental datasets, construct target relationship information based on the experimental datasets, and store the target relationship information in a preset intelligent agent. The target relationship information is used to describe the calculated relationship between the electrostatic spraying powder deposition thickness and the coating film thickness after curing. Real-time powder deposition thickness information acquisition module: In response to the start spraying command, it acquires real-time powder deposition thickness information based on three or more measurement sensors. The acquisition methods for real-time powder deposition thickness information include laser measurement, ultrasonic measurement, electromagnetic wave measurement and / or AI vision measurement. The three or more measurement sensors adopt the same or different test methods and are all pre-installed on the target spray gun. Expected paint film thickness information generation module: used to generate expected paint film thickness information based on real-time powder deposition thickness information and target relationship information; Spray gun control command generation module: used to generate and execute spray gun control commands based on expected paint film thickness information and reference film thickness information.

[0011] Thirdly, embodiments of this application provide a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in the first aspect above.

[0012] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described in the first aspect above.

[0013] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.

[0015] Figure 1 This is a schematic flowchart of a real-time film thickness monitoring method provided in an embodiment of this application; Figure 2 This is a schematic diagram of a target spray gun provided in an embodiment of this application; Figure 3 This is a flowchart illustrating step S100 in a real-time film thickness monitoring method provided in an embodiment of this application. Figure 4 This is a flowchart illustrating the process after step S130 in a real-time film thickness monitoring method provided in an embodiment of this application. Figure 5 This is a flowchart illustrating step S200 in a real-time film thickness monitoring method provided in an embodiment of this application; Figure 6 This is a flowchart illustrating step S300 in a real-time film thickness monitoring method provided in an embodiment of this application; Figure 7 This is a flowchart illustrating the process after step S300 in a real-time film thickness monitoring method provided in an embodiment of this application. Figure 8 This is a block diagram of a real-time film thickness monitoring system provided in one embodiment of this application; Figure 9 This is a schematic diagram of a terminal device provided in an embodiment of this application.

[0016] Explanation of reference numerals in the attached figures: 1. Measurement sensor first point; 2. Measurement sensor second point; 3. Rotary cup nozzle; 4. High pressure generator; 5. Robotic arm fixing point; 6. Powder pipe. Detailed Implementation

[0017] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0018] In the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0019] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0020] To illustrate the technical solution described in this application, specific embodiments are provided below.

[0021] Please see Figure 1 , Figure 1This is a flowchart illustrating the real-time monitoring method for the deposition thickness of electrostatic powder coatings provided in this embodiment. In this embodiment, the execution subject of the real-time monitoring method is a terminal device. It is understood that the types of terminal devices include, but are not limited to, tablet computers, laptops, Ultra-Mobile Personal Computers (UMPCs), netbooks, Personal Digital Assistants (PDAs), etc. This embodiment does not impose any restrictions on the specific type of terminal device.

[0022] Please see Figure 1 The real-time monitoring method provided in this application includes, but is not limited to, the following steps: In S100, an experimental dataset is acquired, and based on the experimental dataset, target relationship information is constructed and stored in a preset intelligent agent.

[0023] Specifically, the terminal device can first acquire the experimental dataset, then construct the target relationship information based on the experimental dataset, and then store the target relationship information in a preset intelligent agent. The target relationship information is used to describe the calculated relationship between the electrostatic spraying powder deposition thickness and the coating film thickness after curing.

[0024] In S200, in response to the start of spraying command, real-time powder deposition thickness information is acquired based on three or more measurement sensors.

[0025] Specifically, the terminal device can first respond to the spraying start command and acquire real-time powder deposition thickness information based on three or more measurement sensors. The spraying start command is used to instruct the target spray gun to start, so that the target spray gun sprays out coating based on electrostatic powder. Specifically, the methods for acquiring real-time powder deposition thickness information include laser measurement, ultrasonic measurement, electromagnetic wave measurement, and / or AI vision measurement. Three or more measurement sensors use the same or different test methods, and all three or more measurement sensors are pre-installed on the target spray gun.

[0026] Without loss of generality, please refer to Figure 2This real-time film thickness monitoring method can target a spray gun, which includes a first measurement sensor point 1 and a second measurement sensor point 2. Both the first measurement sensor point 1 and the second measurement sensor point 2 are used to install multiple sensors to detect the current film thickness. The target spray gun also includes a rotary cup nozzle 3, a high-pressure generator 4, a robotic arm fixing point 5, and a powder pipe 6. The rotary cup nozzle 3 is used to increase the coverage area of ​​the coating, the high-pressure generator 4 is used to increase the spraying speed of the coating, the robotic arm fixing point 5 is used to connect to the robotic arm, and the robotic arm can be controlled by the terminal equipment. The powder pipe 6 can be connected to a fluidized bed and is used to transport the coating.

[0027] Specifically, the measurement ranges of three or more measurement sensors all cover the spraying area of ​​the target spray gun head, and there are overlapping measurement areas between the measurement ranges of each measurement sensor.

[0028] In some possible implementations, for accurate acquisition of real-time powder deposition thickness information, please refer to [link to relevant documentation]. Figure 3 Step S100 includes, but is not limited to, the following steps: In S210, in response to the start of the spraying command, the measurement overlap area is obtained.

[0029] Specifically, the terminal device can respond to the spraying start command and obtain the measurement overlap area, thus being applicable to workpieces with various different surfaces to be sprayed. The measurement overlap area is used to describe the measurement area that overlaps between the measurement sensors.

[0030] Without loss of generality, the measurement coverage of all measurement sensors is within the spray coverage of the target spray gun, and there is a measurement overlap area between the measurement coverage of all measurement sensors.

[0031] In S220, the overlapping measurement areas are divided into equal-area sections to generate multiple candidate area information.

[0032] Specifically, after the terminal device acquires the measurement overlap area, the terminal device can perform equal area division processing on the measurement overlap area, dividing the measurement overlap area into multiple equal area sub-regions, generating multiple candidate area information, where the candidate area information is used to describe a single sub-region after the equal area division processing.

[0033] In S230, based on a preset random algorithm, the target overlapping area is determined according to information from multiple candidate areas.

[0034] Specifically, after the terminal device generates multiple candidate area information, the terminal device can randomly select an area from the multiple candidate area information based on a preset random algorithm, thereby effectively determining the target overlapping area.

[0035] In S240, in response to the start spraying command, real-time powder deposition thickness information of the target overlapping area is acquired based on the measurement sensor.

[0036] Specifically, after the terminal device determines the target overlapping area, the terminal device can respond to the start spraying command and effectively obtain the real-time powder deposition thickness information of the target overlapping area based on the measurement sensor.

[0037] For example, after the terminal device determines the target overlapping area, the terminal device can respond to the start spraying command and acquire real-time powder deposition thickness information A of the target overlapping area based on measurement sensor A. The real-time powder deposition thickness information A is used to describe the expected paint film thickness obtained by measurement sensor A. After the terminal device acquires the real-time film thickness information A, the terminal device can acquire other real-time expected paint film thickness information of the target overlapping area based on other measurement sensors. By acquiring measurement data from multiple sensors, the accuracy of the film thickness information can be improved, and a more reliable basis can be provided for subsequent film thickness prediction.

[0038] For further improvements in measurement efficiency and effectiveness, please refer to some possible implementation methods. Figure 4 After step S230, the method further includes, but is not limited to, the following steps: In S231, retrieve the historical selection area.

[0039] Specifically, after the terminal device determines the target overlapping area, the terminal device can obtain the historical selection area, which is used to describe the historical selection area determined in the previous spraying process.

[0040] In S232, it is determined whether the historical selection area and the target overlapping area are the same.

[0041] Specifically, after the terminal device obtains the historical selection area, it can determine whether the historical selection area and the target overlapping area are the same.

[0042] In S233, if the historical selected area and the target overlapping area are the same, then any other candidate area information adjacent to the target overlapping area is selected as the new target overlapping area.

[0043] Specifically, if the historical selection area and the target overlapping area are the same, it means that the detection area temporarily determined in the current spraying process is the same as the historical selection area determined in the previous spraying process. Therefore, the terminal device can select any other candidate area information adjacent to the target overlapping area as the target overlapping area, thereby improving the effectiveness and accuracy of detection.

[0044] In S234, if the historical selection area and the target overlapping area are not the same, the target overlapping area is retained.

[0045] Specifically, if the historical selection area and the target overlapping area are not the same, it means that the detection area temporarily determined in the current spraying process is different from the historical selection area determined in the previous spraying process. Therefore, the terminal equipment can retain the target overlapping area.

[0046] In S300, the expected paint film thickness information is generated based on real-time powder deposition thickness information and target relationship information.

[0047] Specifically, after the terminal device acquires a large amount of real-time powder deposition thickness information, it can calculate and determine the expected paint film thickness information based on the real-time powder deposition thickness information and the target relationship information, thereby improving the accuracy of the measurement data through a composite measurement mechanism.

[0048] In some possible implementations, to improve the accuracy of the measurement data, please refer to [link / reference needed]. Figure 5 Step S300 includes, but is not limited to, the following steps: In S310, the real-time powder deposition thickness information is compared with the preset average real-time powder deposition thickness value.

[0049] Specifically, the terminal device can compare the real-time powder deposition thickness information with the preset average real-time powder deposition thickness value.

[0050] In S320, if the real-time powder deposition thickness information detected by all measuring sensors is equal to the average real-time powder deposition thickness value, or if the error between the real-time powder deposition thickness information detected by all measuring sensors and the average real-time powder deposition thickness value is within ±5%, then the expected paint film thickness information is generated based on the average real-time powder deposition thickness value and the target relationship information.

[0051] Specifically, if the error between the real-time powder deposition thickness information detected by all the measuring sensors is small, the terminal device can determine the real-time powder deposition thickness information as the target expected coating film thickness value.

[0052] In S330, if there is a measurement sensor whose real-time powder deposition thickness information is not equal to the average real-time powder deposition thickness value, and the error between the real-time powder deposition thickness information and the average real-time powder deposition thickness value is greater than ±5%, then after removing the real-time powder deposition thickness information with the largest error, the average real-time powder deposition thickness value is recalculated, and the expected paint film thickness information is generated based on the new average real-time powder deposition thickness value.

[0053] In S340, if half or more of the powder deposition thickness information corresponding to the measurement sensors is not equal to the average real-time powder deposition thickness value, and the error between the real-time powder deposition thickness information and the average real-time powder deposition thickness value is greater than ±5%, then after re-measuring all the powder deposition thickness information, the comparison between the real-time powder deposition thickness information and the preset average real-time powder deposition thickness value is performed again based on the new powder deposition thickness information.

[0054] Specifically, if there is a large error between the real-time powder deposition thickness information detected by all the measuring sensors, it indicates that the data is biased due to the hardware accuracy of the measuring equipment. Therefore, the terminal equipment can analyze the detected real-time powder deposition thickness information, recalculate the average powder deposition thickness information, or send a signal to remeasure.

[0055] In S400, spray gun control commands are generated and executed based on the expected paint film thickness information and the reference film thickness information.

[0056] Specifically, after the terminal device determines the expected paint film thickness information and the reference film thickness information, the terminal device can generate and execute spray gun control commands based on the expected paint film thickness information and the reference film thickness information. The spray gun control commands include a continue spraying command or a stop spraying command. The continue spraying command is used to instruct the target spray gun to continue spraying, and the stop spraying command is used to instruct the target spray gun to stop spraying.

[0057] In some possible implementations, to improve the uniformity of spraying, please refer to [link / reference]. Figure 6 Step S400 includes, but is not limited to, the following steps: In S410, the expected film thickness information is compared with the reference film thickness information.

[0058] Specifically, the terminal device can compare the expected paint film thickness information with the reference film thickness information, where the reference film thickness information is used to describe the film thickness corresponding to the workpiece production requirements.

[0059] In S420, if the expected paint film thickness information is equal to the reference film thickness information, a stop spraying command is generated and executed.

[0060] Specifically, if the expected film thickness information is equal to the reference film thickness information, it indicates that the production requirements are met, so the terminal equipment can generate and execute a stop spraying command.

[0061] In S430, if the expected paint film thickness information is not equal to the reference film thickness information, a continue spraying command is generated and executed.

[0062] Specifically, if the expected film thickness information is equal to the reference film thickness information, it indicates that the production requirements are not yet met. Therefore, the terminal equipment can generate and execute a continue spraying instruction until the expected film thickness information continuously increases to the reference film thickness information.

[0063] In some possible implementations, the terminal device can also adaptively adjust the spraying parameters through a preset AI algorithm.

[0064] For some possible implementations, please refer to [link / reference needed] for better management of production data. Figure 7 After step S400, the method further includes, but is not limited to, the following steps: In S510, the execution time information of the spray gun control command is obtained, and the real-time powder deposition thickness information corresponding to the execution time information is also obtained.

[0065] Specifically, after the terminal device generates and executes the spray gun control command, the terminal device can obtain the execution time information of the spray gun control command, and obtain the real-time powder deposition thickness information corresponding to the execution time information.

[0066] In S520, execution time information and real-time powder deposition thickness information are sent to a preset production database.

[0067] Specifically, after the terminal device obtains the execution time information and the real-time powder deposition thickness information, the terminal device can send the execution time information and the real-time powder deposition thickness information to the preset production database, which is conducive to combining the MES system to realize data uploading and equipment health prediction.

[0068] In some possible implementations, the terminal device can also learn the parameter patterns of different powder formulations through an AI model. This real-time film thickness monitoring method can also be extended to liquid coating and ceramic spraying processes.

[0069] The implementation principle of the real-time monitoring method for electrostatic powder coating deposition thickness in this application embodiment is as follows: The terminal device can first respond to the start spraying command and accurately obtain real-time powder deposition thickness information. Then, based on the real-time powder deposition thickness information, it can effectively determine the expected paint film thickness information. Finally, based on the expected paint film thickness information and the reference film thickness information, it can quickly generate and execute the spray gun control command, thereby avoiding the situation of high dependence on human experience, reducing the situation of uneven film thickness distribution, improving coating uniformity and intelligence level, and greatly improving production reliability and detection efficiency.

[0070] It should be noted that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0071] Embodiments of this application also provide a real-time monitoring system for the deposition thickness of electrostatic powder coatings. For ease of explanation, only the parts relevant to this application are shown, such as... Figure 8 As shown, the system 80 includes: Target Relationship Information Construction Module 81: Used to acquire experimental datasets, construct target relationship information based on experimental datasets, and store the target relationship information in a preset intelligent agent. The target relationship information is used to describe the calculated relationship between the electrostatic spraying powder deposition thickness and the coating film thickness after curing. Real-time powder deposition thickness information acquisition module 82: In response to the start spraying command, it acquires real-time powder deposition thickness information based on three or more measurement sensors. The real-time powder deposition thickness information acquisition methods include laser measurement, ultrasonic measurement, electromagnetic wave measurement and / or AI vision measurement. The three or more measurement sensors adopt the same or different test methods, and the three or more measurement sensors are all pre-installed on the target spray gun. Expected paint film thickness information generation module 83: used to generate expected paint film thickness information based on real-time powder deposition thickness information and target relationship information; Spray gun control command generation module 84: used to generate and execute spray gun control commands based on expected paint film thickness information and reference film thickness information.

[0072] Optionally, the above-mentioned expected paint film thickness information generation module 83 includes: Real-time powder deposition thickness information comparison submodule: used to compare real-time powder deposition thickness information with preset average real-time powder deposition thickness value; The expected paint film thickness information generation submodule is used to generate expected paint film thickness information based on the average real-time powder deposition thickness value and the target relationship information if the real-time powder deposition thickness information detected by all measurement sensors is equal to the average real-time powder deposition thickness value, or the error between the real-time powder deposition thickness information detected by all measurement sensors and the average real-time powder deposition thickness value is within ±5%. The expected paint film thickness information generation submodule is used to: if there is a measurement sensor whose real-time powder deposition thickness information is not equal to the average real-time powder deposition thickness value, and the error between the real-time powder deposition thickness information and the average real-time powder deposition thickness value is greater than ±5%, then after removing the real-time powder deposition thickness information with the largest error, recalculate the average real-time powder deposition thickness value, and generate the expected paint film thickness information based on the new average real-time powder deposition thickness value; Remeasurement submodule: If half or more of the powder deposition thickness information corresponding to the measurement sensors is not equal to the average real-time powder deposition thickness value, and the error between the real-time powder deposition thickness information and the average real-time powder deposition thickness value is greater than ±5%, then after remeasurement of all powder deposition thickness information, the real-time powder deposition thickness information and the preset average real-time powder deposition thickness value will be compared again based on the new powder deposition thickness information. Accordingly, the spray gun control commands include a continue spraying command or a stop spraying command; the aforementioned spray gun control command generation module 84 includes, Expected paint film thickness information comparison submodule: used to compare expected paint film thickness information with baseline film thickness information; Stop spraying command generation submodule: Used to generate and execute a stop spraying command if the expected paint film thickness information is equal to the reference film thickness information; Continue spraying instruction generation submodule: Used to generate and execute continue spraying instructions if the expected paint film thickness information is not equal to the reference film thickness information.

[0073] Optionally, the measurement ranges of three or more measurement sensors all cover the spraying area of ​​the target spray gun head, and there is an overlapping measurement area between the measurement ranges of each measurement sensor; the aforementioned real-time powder deposition thickness information acquisition module 82 includes: Measurement overlap area acquisition submodule: used to acquire the measurement overlap area in response to the start spraying command; Candidate Area Information Generation Submodule: Used to perform equal area division processing on the overlapping measurement areas and generate multiple candidate area information; The target overlapping region determination submodule is used to determine the target overlapping region based on a preset random algorithm and information from multiple candidate regions. Real-time powder deposition thickness information acquisition submodule: In response to the start spraying command, it acquires real-time powder deposition thickness information of the target overlapping area based on the measurement sensor.

[0074] Optionally, the system 80 also includes: Historical selection area acquisition module: used to acquire historical selection areas; Historical selection area judgment module: used to determine whether the historical selection area and the target overlapping area are the same; Target overlapping area selection module: If the historical selection area and the target overlapping area are the same, then select any other candidate area information adjacent to the target overlapping area as the new target overlapping area; The target overlapping area retention module is used to retain the target overlapping area if the historical selection area and the target overlapping area are not the same.

[0075] Optionally, the system 80 also includes: Execution time information acquisition module: used to acquire the execution time information of the spray gun control command, and to acquire the real-time powder deposition thickness information corresponding to the execution time information; Execution time information sending module: used to send execution time information and real-time powder deposition thickness information to the preset production database.

[0076] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0077] This application also provides a terminal device, such as... Figure 9 As shown, the terminal device 90 of this embodiment includes: a processor 91, a memory 92, and a computer program 93 stored in the memory 92 and executable on the processor 91. When the processor 91 executes the computer program 93, it implements the steps described in the real-time monitoring method embodiment, for example... Figure 1 Steps S100 to S400 are shown; or, when processor 91 executes computer program 93, it implements the functions of each module in the above-described device, for example... Figure 8 The functions of modules 81 to 84 are shown.

[0078] The terminal device 90 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. The terminal device 90 includes, but is not limited to, a processor 91 and a memory 92. Those skilled in the art will understand that... Figure 9 This is merely an example of terminal device 90 and does not constitute a limitation on terminal device 90. It may include more or fewer components than shown, or combine certain components, or different components. For example, terminal device 90 may also include input / output devices, network access devices, buses, etc.

[0079] The processor 91 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.; the general-purpose processor can be a microprocessor or any conventional processor, etc.

[0080] The memory 92 can be an internal storage unit of the terminal device 90, such as the hard disk or memory of the terminal device 90. The memory 92 can also be an external storage device of the terminal device 90, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device 90. Furthermore, the memory 92 can include both internal storage units and external storage devices of the terminal device 90. The memory 92 can also store computer program 93 and other programs and data required by the terminal device 90. The memory 92 can also be used to temporarily store data that has been output or will be output.

[0081] One embodiment of this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0082] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the methods, principles and structures of this application should be covered within the scope of protection of this application.

Claims

1. A method for real-time monitoring of the deposition thickness of electrostatic powder coatings, applied to a target spray gun, characterized in that, The method includes: Obtain experimental datasets, construct target relationship information based on the experimental datasets, and store the target relationship information in a preset intelligent agent, wherein the target relationship information is used to describe the calculated relationship between the electrostatic spraying powder deposition thickness and the coating film thickness after curing; In response to the start spraying command, real-time powder deposition thickness information is acquired based on three or more measurement sensors. The real-time powder deposition thickness information is acquired by laser measurement, ultrasonic measurement, electromagnetic wave measurement and / or AI vision measurement. The three or more measurement sensors adopt the same or different test methods and are all pre-installed on the target spray gun. Based on the real-time powder deposition thickness information and target relationship information, the expected paint film thickness information is generated; Based on the expected paint film thickness information and the reference film thickness information, spray gun control commands are generated and executed.

2. The method according to claim 1, characterized in that, The step of generating expected paint film thickness information based on the real-time powder deposition thickness information and target relationship information includes: Compare the real-time powder deposition thickness information with the preset average real-time powder deposition thickness value; If the real-time powder deposition thickness information detected by all measuring sensors is equal to the average real-time powder deposition thickness value, or if the error between the real-time powder deposition thickness information detected by all measuring sensors and the average real-time powder deposition thickness value is within ±5%, then the expected paint film thickness information is generated based on the average real-time powder deposition thickness value and the target relationship information. If there exists a measurement sensor whose real-time powder deposition thickness information is not equal to the average real-time powder deposition thickness value, and the error between the real-time powder deposition thickness information and the average real-time powder deposition thickness value is greater than ±5%, then after removing the real-time powder deposition thickness information with the largest error, the average real-time powder deposition thickness value is recalculated, and the expected paint film thickness information is generated based on the new average real-time powder deposition thickness value. If half or more of the powder deposition thickness information corresponding to the measurement sensors is not equal to the average real-time powder deposition thickness value, and the error between the real-time powder deposition thickness information and the average real-time powder deposition thickness value is greater than ±5%, then after re-measuring all the powder deposition thickness information, the comparison between the real-time powder deposition thickness information and the preset average real-time powder deposition thickness value is performed again based on the new powder deposition thickness information. Accordingly, the spray gun control commands include a continue spraying command or a stop spraying command; the process of generating and executing spray gun control commands based on the expected paint film thickness information and the reference film thickness information... Compare the expected film thickness information with the reference film thickness information; If the expected film thickness information is equal to the reference film thickness information, then the stop spraying command is generated and executed; If the expected film thickness information is not equal to the reference film thickness information, then the continue spraying command is generated and executed.

3. The method according to claim 1, characterized in that, The measurement range of the three or more measuring sensors all covers the spraying area of ​​the target spray gun head, and there is an overlapping area between the measurement ranges of each measuring sensor. In response to the start spraying command, real-time powder deposition thickness information is acquired based on three or more measurement sensors, including: In response to the start spraying command, the measurement overlap area is acquired; The overlapping measurement areas are divided into equal-area sections to generate multiple candidate area information. Based on a preset random algorithm, the target overlapping region is determined according to multiple candidate region information; In response to the start spraying command, the real-time powder deposition thickness information of the target overlapping area is obtained based on the measurement sensor.

4. The method according to claim 3, characterized in that, After determining the target overlapping region based on the preset random algorithm and multiple candidate region information, the method further includes: Get the historical selection area; Determine whether the historical selection area and the target overlapping area are the same; If the historical selection area and the target overlapping area are the same, then any other candidate area information adjacent to the target overlapping area is selected as the new target overlapping area. If the historical selection area and the target overlapping area are not the same, then the target overlapping area is retained.

5. The method according to claim 1, characterized in that, After generating and executing the spray gun control command based on the expected paint film thickness information and the reference film thickness information, the process includes: Obtain the execution time information of the spray gun control command, and obtain the real-time powder deposition thickness information corresponding to the execution time information; The execution time information and real-time powder deposition thickness information are sent to a preset production database.

6. A real-time monitoring system for the deposition thickness of electrostatic powder coatings, characterized in that, The system includes: Target Relationship Information Construction Module: Used to acquire experimental datasets, construct target relationship information based on the experimental datasets, and store the target relationship information in a preset intelligent agent, wherein the target relationship information is used to describe the calculated relationship between the electrostatic spraying powder deposition thickness and the coating film thickness after curing; Real-time powder deposition thickness information acquisition module: In response to the start spraying command, it acquires real-time powder deposition thickness information based on three or more measurement sensors. The acquisition methods of the real-time powder deposition thickness information include laser measurement, ultrasonic measurement, electromagnetic wave measurement and / or AI vision measurement. The three or more measurement sensors adopt the same or different test methods and are all pre-installed on the target spray gun. Expected paint film thickness information generation module: used to generate expected paint film thickness information based on the real-time powder deposition thickness information and target relationship information; Spray gun control command generation module: used to generate and execute spray gun control commands based on the expected paint film thickness information and the reference film thickness information.

7. The system according to claim 6, characterized in that, The expected paint film thickness information generation module includes: Real-time powder deposition thickness information comparison submodule: used to compare the real-time powder deposition thickness information with the preset average real-time powder deposition thickness value; The first submodule for generating expected paint film thickness information is used to generate expected paint film thickness information based on the average real-time powder deposition thickness value and the target relationship information if the real-time powder deposition thickness information detected by all measuring sensors is equal to the average real-time powder deposition thickness value, or the error between the real-time powder deposition thickness information detected by all measuring sensors and the average real-time powder deposition thickness value is within ±5%. The second sub-module for expected paint film thickness information is used to: if there is a measurement sensor whose real-time powder deposition thickness information is not equal to the average real-time powder deposition thickness value, and the error between the real-time powder deposition thickness information and the average real-time powder deposition thickness value is greater than ±5%, then after removing the real-time powder deposition thickness information with the largest error, recalculate the average real-time powder deposition thickness value, and generate expected paint film thickness information based on the new average real-time powder deposition thickness value; The submodule is executed again: if half or more of the powder deposition thickness information corresponding to the measurement sensors is not equal to the average real-time powder deposition thickness value, and the error between the real-time powder deposition thickness information and the average real-time powder deposition thickness value is greater than ±5%, then after re-measuring all the powder deposition thickness information, the comparison between the real-time powder deposition thickness information and the preset average real-time powder deposition thickness value is executed again based on the new powder deposition thickness information.

8. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 5.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.

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