Engine paint quality detection method, device, storage medium and electronic equipment

Abstract

The present application provides a method, device, storage medium and electronic device for detecting the quality of engine painting. It includes: constructing a digital twin model of an engine and a painting robot, obtaining an engine model and a robot model, controlling the initial placement and initial movement of the virtual robot in the robot model to be consistent with the painting robot; when the engine reaches the real painting position, controlling the engine model to move to the virtual painting position; after the engine reaches the real painting position, controlling the movement of the painting robot and obtaining the movement data and the painting robot's spraying data and environmental data, and going to the digital twin platform, controlling the movement of the virtual robot according to the movement data, determining the engine paint film thickness and the paint drying time according to the spraying data and the environmental data, and determining the paint quality value according to the engine paint film thickness and the paint drying time. It solves the problem that the prior art lacks a real-time monitoring solution for the painting quality of the engine painting scene.

Description

Technical Field

[0001] The present application relates to the technical field of detecting engine paint quality, and in particular, to a method, device, storage medium and electronic device for detecting engine paint quality. Background Art

[0002] As an advanced technology that integrates virtual simulation, physical models and real-time data analysis, digital twin technology has shown great potential in industrial applications.

[0003] Engine manufacturing includes assembly, test running and assembly. Real-time detection of relevant key processes can effectively improve the quality of engine products.

[0004] The prior art retrieved includes patent number CN112547352A, which discloses a method and system for automatic spray monitoring remote operation based on digital twins. However, CN112547352A does not disclose the specific technical solution from data generation to application on the twin platform; and the spraying object of CN112547352A is not limited to the engine. Therefore, the existing solutions lack a solution for real-time monitoring of the paint quality of the engine painting scene. Summary of the invention

[0005] The main purpose of the present application is to provide a method, device, storage medium and electronic device for detecting engine paint quality, so as to at least solve the problem that the prior art lacks a real-time monitoring solution for engine painting scenes.

[0006] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a method for detecting the quality of engine paint is provided, comprising: constructing a digital twin model of an engine and a digital twin model of a paint robot on a digital twin platform to obtain an engine model and a robot model, and controlling the initial placement position and initial movement of the virtual robot in the robot model to be consistent with those of the paint robot; when the engine reaches the real paint position, controlling the engine model to move to the virtual paint position of the digital twin platform; after the engine reaches the real paint position, controlling the movement of the paint robot and obtaining movement data as well as the spraying data and environmental data of the paint robot, and transmitting the movement data, spraying data and environmental data to the digital twin platform, wherein the spraying data includes paint flow rate, paint nozzle area, spraying distance, and nozzle moving speed; controlling the movement of the virtual robot of the digital twin platform according to the movement data, and using the digital twin platform to determine the engine paint film thickness and paint drying time according to the spraying data and the environmental data, and determining the paint quality value according to the engine paint film thickness and the paint drying time.

[0007] Optionally, the digital twin platform is used to determine the engine paint film thickness and the paint drying time according to the spraying data and the environmental data, including: determining the engine paint film thickness according to a first formula: T_c= (V / A×D) / (M_v), wherein T_c is the engine paint film thickness, V is the paint flow rate, A is the paint nozzle area, D is the spraying distance, and M_v is the nozzle moving speed; according to a second formula: , determine the paint drying time, wherein the environmental data includes ambient temperature and relative air humidity, T_d is the paint drying time, T is the ambient temperature, RH is the relative air humidity, and C is a constant.

[0008] Optionally, after determining the paint quality value according to the engine paint film thickness and the paint drying time, the method further includes: obtaining a paint quality threshold from a knowledge base, and determining whether the paint quality value is greater than the paint quality threshold; when it is determined that the paint quality value is greater than the paint quality threshold, generating an alarm message on the digital twin platform, wherein the alarm message is used to indicate that the paint quality is unqualified.

[0009] Optionally, before controlling the virtual robot in the robot model to be consistent with the initial placement position and initial action of the painting robot, it includes: controlling the painting robot to establish communication with the PLC to transmit the axis angle data of the painting robot to the PLC, and then transmitting the axis angle data to the digital twin platform via Kepsever's MQTT Client and MQTT Server.

[0010] Optionally, before the engine reaches the actual painting position, the method further includes: determining whether first position data is activated; and if it is determined that the first position data is activated, determining that the engine reaches the actual painting position, wherein the first position data is collected by an inductive sensor at the beginning of the actual painting position.

[0011] Optionally, after determining the paint quality value according to the engine paint film thickness and the paint drying time, the method further includes: determining whether the second position data is activated, and if it is determined that the second position data is activated, determining that the engine leaves the actual painting position, wherein the second position data is collected by an inductive sensor at the end of the actual painting position; controlling the engine model to move out of the painting position of the digital twin platform, and destroying the engine model.

[0012] Optionally, a digital twin model of the engine and a digital twin model of the painting robot are constructed on the digital twin platform, including: using Unreal Engine to construct the digital twin model of the engine and the digital twin model of the painting robot on the digital twin platform.

[0013] According to another aspect of the present application, a device for detecting the quality of engine paint spraying is provided, comprising: a construction unit, configured to construct a digital twin model of an engine and a digital twin model of a paint spraying robot on a digital twin platform, obtain an engine model and a robot model, and control the initial placement position and initial movement of the virtual robot in the robot model to be consistent with those of the paint spraying robot; a first determination unit, configured to control the engine model to move to a virtual paint spraying position of the digital twin platform when the engine reaches a real paint spraying position; a control unit, configured to control the movement of the paint spraying robot and obtain movement data and the spraying data and environmental data of the paint spraying robot after the engine reaches the real paint spraying position, and transmit the movement data, spraying data and environmental data to the digital twin platform, wherein the spraying data includes a paint flow rate, a paint nozzle area, a spraying distance, and a nozzle moving speed; a monitoring unit, configured to control the movement of the virtual robot of the digital twin platform according to the movement data, and use the digital twin platform to determine the engine paint film thickness and the paint drying time according to the spraying data and the environmental data, and determine the paint quality value according to the engine paint film thickness and the paint drying time.

[0014] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is run, the device where the computer-readable storage medium is located is controlled to execute any one of the engine paint quality detection methods.

[0015] According to another aspect of the present application, an electronic device is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a method for executing any one of the engine paint quality detection methods.

[0016] By applying the technical solution of the present application, a digital twin model of the engine and a digital twin model of the paint robot are constructed on the digital twin platform to obtain the engine model and the robot model, and the initial placement position and initial movement of the virtual robot in the robot model are controlled to be consistent with those of the paint robot; when the engine reaches the real paint spraying position, the engine model is controlled to move to the virtual paint spraying position of the digital twin platform; after the engine reaches the real paint spraying position, the movement of the paint spraying robot is controlled to obtain the movement data as well as the spraying data and environmental data of the paint spraying robot, and the movement data, spraying data and environmental data are transmitted to the digital twin platform, wherein the spraying data includes the paint flow rate, the paint nozzle area, the spraying distance, and the nozzle movement speed; the movement of the virtual robot of the digital twin platform is controlled according to the movement data, and the digital twin platform is used to determine the engine paint film thickness and the paint drying time according to the spraying data and the environmental data, and the paint quality value is determined according to the engine paint film thickness and the paint drying time. By simulating the motion trajectory of the painting robot in the paint shop in real time to monitor the robot's motion status in real time, simulating the motion position of the engine to be painted in real time to monitor the engine's spraying status in real time, and monitoring the spraying data and environmental data in real time to provide real-time feedback on the painting quality, online monitoring and management of the engine painting process is achieved to meet the needs of safe and efficient automated operations, and solve the problem that the existing technology lacks a real-time monitoring solution for engine painting scenarios, resulting in low quality of the engine finished product. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings constituting part of the present application are used to provide a further understanding of the present application. The exemplary embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 A hardware structure block diagram of a mobile terminal for executing a method for detecting engine paint quality provided in an embodiment of the present application is shown;

[0019] Figure 2 A schematic flow chart of a method for detecting engine paint quality provided according to an embodiment of the present application is shown;

[0020] Figure 3 The digital twin platform architecture diagram of the engine manufacturing painting scene provided according to the embodiment of the present application is shown;

[0021] Figure 4 A schematic diagram of a signal data analysis technology solution for driving a mechanical arm to interact with virtual reality according to an embodiment of the present application is shown;

[0022] Figure 5 A schematic diagram of a process for implementing real-time tracking using engine position data provided in an embodiment of the present application is shown;

[0023] Figure 6 A schematic diagram of a paint quality alarm solution process based on digital twins provided according to an embodiment of the present application is shown;

[0024] Figure 7 A structural block diagram of a device for detecting engine paint quality provided according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0025] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0026] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0027] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] For the convenience of description, some nouns or terms involved in the embodiments of the present application are explained below:

[0029] Digital twin: A virtual model of a real-world object or system built using real-time data and simulation technology. This model is continuously updated to reflect the current state of the entity, so that it can be used to analyze, optimize and predict its performance and behavior.

[0030] AI Behavior Tree: is a tool for managing complex AI behaviors. It decomposes the decision-making process of AI into a tree structure, allowing developers to design and adjust the behavior of AI in a modular way. The behavior tree contains nodes such as conditional judgments, actions, and selectors. Through the combination of these nodes, AI can make appropriate responses in different situations. In this solution, AI refers to the engine to be painted.

[0031] As introduced in the background technology, the prior art lacks a real-time monitoring solution for engine painting scenes. In order to solve the problem that the prior art lacks a real-time monitoring solution for engine painting scenes, the embodiments of the present application provide an engine paint quality detection method, device, storage medium and electronic device.

[0032] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0033] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 FIG. 1 is a hardware structure block diagram of a mobile terminal for a method for detecting engine paint quality according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is for illustration only and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0034] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the engine paint quality detection method in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0035] In this embodiment, a method for detecting the quality of engine paint that runs on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that shown here.

[0036] Figure 2 FIG. 1 is a flow chart of a method for detecting engine paint quality according to an embodiment of the present application. Figure 2 As shown, the method comprises the following steps:

[0037] Step S201, constructing a digital twin model of the engine and a digital twin model of the painting robot on the digital twin platform, obtaining an engine model and a robot model, and controlling the initial placement and initial movement of the virtual robot in the robot model to be consistent with those of the painting robot;

[0038] Among them, the painting robot is a multi-axis robotic arm.

[0039] Specifically, the initial placement position of the robotic arm model in the digital twin platform is highly consistent with the real robotic arm. After a certain axis of the real robotic arm rotates a certain angle, the twin model obtains the angle data in real time and adjusts the angle of the corresponding axis to the corresponding position, realizing the virtual and real linkage of the robotic arm.

[0040] Step S202, when the engine reaches the real painting position, control the engine model to move to the virtual painting position of the digital twin platform;

[0041] Specifically, the position of the engine is determined by judging whether the passing point signal is triggered. When triggered, it is determined that the engine has reached the actual painting position, thereby driving the twin platform engine position change to track the engine status in real time.

[0042] Step S203, after the engine reaches the actual painting position, control the movement of the painting robot and obtain the movement data as well as the spraying data and environmental data of the painting robot, and transmit the movement data, spraying data and environmental data to the digital twin platform, wherein the spraying data includes the paint flow rate, the paint nozzle area, the spraying distance, and the nozzle moving speed;

[0043] Specifically, the environmental data includes ambient temperature and relative humidity of the air, and the motion data is the rotation data of each axis of the robotic arm. The motion data is transmitted to the digital twin platform, realizing the virtual-real linkage of the robotic arm; the paint data and environmental data are transmitted to the digital twin platform, realizing the monitoring of the engine paint quality on the digital twin platform.

[0044] Step S204, controlling the virtual robot action of the digital twin platform according to the action data, and using the digital twin platform to determine the engine paint film thickness and paint drying time according to the spraying data and environmental data, and determining the paint quality value according to the engine paint film thickness and paint drying time.

[0045] Specifically, the engine paint film thickness and paint drying time are determined based on the spraying data and environmental data. With the help of the twin platform's visualization technology, the paint quality threshold in the knowledge base is read to display the current engine paint quality in real time. When the paint quality exceeds the established threshold, the digital twin platform's real-time paint quality monitoring platform can provide timely prompts or alarms.

[0046] Through this embodiment, a digital twin model of the engine and a digital twin model of the paint robot are constructed on the digital twin platform to obtain the engine model and the robot model, and the initial placement position and initial movement of the virtual robot in the robot model are controlled to be consistent with those of the paint robot; when the engine reaches the real paint spraying position, the engine model is controlled to move to the virtual paint spraying position of the digital twin platform; after the engine reaches the real paint spraying position, the movement of the paint spraying robot is controlled to obtain movement data as well as the spraying data and environmental data of the paint spraying robot, and the movement data, spraying data and environmental data are transmitted to the digital twin platform, wherein the spraying data includes paint flow rate, paint nozzle area, spraying distance, and nozzle movement speed; the virtual robot movement of the digital twin platform is controlled according to the movement data, and the digital twin platform is used to determine the engine paint film thickness and paint drying time according to the spraying data and environmental data, and the paint quality value is determined according to the engine paint film thickness and paint drying time. By simulating the motion trajectory of the painting robot in the paint shop in real time to monitor the robot's motion status in real time, simulating the motion position of the engine to be painted in real time to monitor the engine's spraying status in real time, and monitoring the spraying data and environmental data in real time to provide real-time feedback on the painting quality, online monitoring and management of the engine painting process is achieved to meet the needs of safe and efficient automated operations, and solve the problem that the existing technology lacks a real-time monitoring solution for engine painting scenarios, resulting in low quality of the engine finished product.

[0047] In the specific implementation process, the digital twin platform is used to determine the engine paint film thickness and paint drying time according to the spraying data and environmental data, including: according to the first formula: T_c= (V / A×D) / (M_v), the engine paint film thickness is determined, where T_c is the engine paint film thickness, V is the paint flow rate, A is the paint nozzle area, D is the spraying distance, and M_v is the nozzle moving speed; according to the second formula: , determine the paint drying time, where the environmental data includes ambient temperature and relative air humidity, T_d is the paint drying time, T is the ambient temperature, RH is the relative air humidity, and C is a constant.

[0048] The first and second formulas of this method are adjusted and optimized according to experimental data and the characteristics of the coating. Compared with the existing drying time calculation formula, the second formula of this scheme introduces the influence of ambient temperature on drying time. The calculated parameters are stored in the knowledge base, and the corresponding quality inspection indicators are adjusted dynamically in real time according to the changes in the spraying environment and related parameter data. Among them, the estimation of coating drying time and the control of coating thickness are two important parameter indicators. Efficient and real-time monitoring of these parameters can help improve engine performance and durability, and improve engine quality and consistency.

[0049] Specifically, after determining the paint quality value according to the engine paint film thickness and the paint drying time, the method also includes: obtaining a paint quality threshold from a knowledge base, and determining whether the paint quality value is greater than the paint quality threshold; when it is determined that the paint quality value is greater than the paint quality threshold, generating an alarm message on the digital twin platform, wherein the alarm message is used to indicate that the paint quality is unqualified.

[0050] This method determines the paint quality value based on the engine paint film thickness and paint drying time. By reading the paint quality threshold in the knowledge base, the current engine paint quality can be displayed in real time. When the paint quality value exceeds the established threshold, the digital twin platform can promptly issue relevant prompts or alarms. This can replace manual inspection and quality verification, effectively ensuring the quality and consistency of paint.

[0051] More specifically, before the initial placement and initial movement of the virtual robot and the painting robot in the control robot model are consistent, it includes: controlling the painting robot to establish communication with the PLC to transmit the axis angle data of the painting robot to the PLC, and then transmitting the axis angle data to the digital twin platform via Kepsever's MQTT Client and MQTT Server.

[0052] This method first establishes communication between the PLC and the robotic arm to obtain the six-axis angle data of the servo motor of the robot controller, and then transmits the data to the twin development platform through the Kepsever's MQTT Client and the independently built MQTT Server. In the digital twin platform, the initial placement position of the robotic arm model and the placement position of the actual robotic arm must be highly consistent. After a certain axis of the actual robotic arm rotates a certain angle, the twin model obtains the angle data in real time and adjusts the angle of the corresponding axis to the corresponding position, realizing the virtual-real linkage of the robotic arm.

[0053] Furthermore, before the engine reaches the actual painting position, the method also includes: determining whether the first position data is activated; if it is determined that the first position data is activated, determining that the engine reaches the actual painting position, wherein the first position data is collected by an inductive sensor at the beginning of the actual painting position.

[0054] Furthermore, after determining the paint quality value based on the engine paint film thickness and the paint drying time, the method also includes: determining whether the second position data is activated, and when it is determined that the second position data is activated, determining that the engine leaves the actual painting position, wherein the second position data is collected by the inductive sensor at the end of the actual painting position; controlling the engine model to move out of the painting position of the digital twin platform, and destroying the engine model.

[0055] This method can track the position of the engine in the paint room in real time, and only requires two data: the engine arrival signal and the engine leaving the paint room signal. The detection system monitors the status of the two signal data in real time when it starts running, and determines whether the engine arrival data is activated. If it is activated, it is considered that the engine has arrived at the paint position, and the system will drive the twin model to the specified paint position. If it is not activated, the system will determine the activation status of the engine leaving the paint position signal. When the departure signal is activated, the algorithm will assume that the current engine has been painted and starts to leave the paint position. The system will drive the twin model to leave the specified paint position. When the engine leaves the paint position and drives out of the paint room, the system will destroy the current engine model and generate a new engine model at the engine entry position to start a new engine painting process detection. This algorithm can still accurately monitor the paint position of the engine even when the engine position data is missing and the system startup time is uncertain, and realize the key parameter monitoring and management of the engine painting process.

[0056] Specifically, a digital twin model of the engine and a digital twin model of the painting robot are constructed on the digital twin platform, including: using Unreal Engine to construct the digital twin model of the engine and the digital twin model of the painting robot on the digital twin platform.

[0057] This method uses Unreal Engine to build digital twin models of the engine and the paint robot. Unreal Engine is a powerful, stable and reliable game engine that can ensure the running effect and stable performance of the twin model. Unreal Engine has powerful rendering capabilities and visual effects, which can present realistic graphics and light and shadow effects, making the twin model more realistic and vivid. Unreal Engine provides intuitive visual editing tools that can easily build and edit twin models, making the model production process more efficient and convenient. Unreal Engine supports multiple platforms, including PC, mobile devices, etc., which can realize the display and application of twin models on different devices, improving the availability and applicability of the model.

[0058] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the implementation process of the engine paint quality detection method of the present application will be described in detail below in combination with specific embodiments.

[0059] This embodiment relates to a specific method for detecting the quality of engine paint spraying, such as Figure 3 As shown, the following steps are included:

[0060] The existing technology has real-time monitoring of the automatic painting site through a sensor network and establishing a real-time enhanced model on site; based on the abnormality detected in the automatic painting process, the fault is diagnosed to determine the type and cause of the fault. The above-mentioned existing technical solutions only involve the process operation of the painting process monitoring implementation, and the detailed technical solutions involved in each specific link are not provided, such as: the specific implementation technical principles and solutions from data generation to application on the twin platform; in addition, the mention of "monitoring abnormalities in the automatic painting process, diagnosing the fault according to the knowledge base" also does not provide a specific implementation technical solution.

[0061] The prior art also discloses the use of a three-dimensional visual inspection subsystem to use a visual system to model the automobile body in white and plan the spraying trajectory, which is used to spray the automobile body in white, and after the spraying is completed, the spraying quality of the automobile body in white is inspected; the above-mentioned prior art scheme only involves the inspection of the spraying quality of a single automobile, lacks monitoring and inspection of the entire spraying scene; the entire technical scheme description is only a procedural description, and each link lacks detailed technical principle support.

[0062] Engine manufacturing includes assembly, test run and assembly, and real-time detection of relevant key processes can effectively improve the quality of engine finished products. The data of the painting process in the assembly process is complex, involving temperature, humidity, air pressure, paint flow, drying speed, color and texture changes and other parameters and variables. In order to ensure the reliability of the painting process parameters and the consistency of the painting quality, this embodiment builds an online painting quality detection system based on digital twin technology to realize online real-time monitoring and alarm of painting data. This system can monitor the movement state of the robot in real time by simulating the movement trajectory of the painting robot in the painting room in real time, simulate the movement position of the engine to be painted in real time to monitor the painting state of the engine in real time, monitor the paint flow rate and the temperature and air pressure of the painting room in real time to feedback the painting quality in real time, set the alarm threshold through the knowledge base and feedback the alarm information in time, realize the online monitoring and management of the engine painting process, and meet the needs of safe and efficient automated operations.

[0063] This embodiment relates to a specific method for detecting engine paint quality, which specifically includes the following contents:

[0064] Figure 3 This is the architecture diagram of the digital twin platform for engine manufacturing and painting scenarios. It can be divided into five stages according to the data transmission process: data generation, data classification, data transmission, data application, and deployment application.

[0065] Depending on the data type and data transmission method, different application scenarios and forms of data determine the business value of the entire platform. This embodiment meets the business needs for monitoring paint room data from aspects such as real-time driving of robot arm and engine position data, real-time monitoring of paint data, and real-time transmission and calculation of paint room temperature, air pressure, and humidity data.

[0066] This embodiment builds a signal data analysis method for driving the virtual-real interaction of the robotic arm based on Unreal Engine: First, the PLC establishes communication with the robotic arm to obtain the six-axis angle data of the servo motor of the robot controller, and then the data is transmitted to the twin development platform through the self-built MQTT Server via Kepsever's MQTT Client. In the digital twin platform, the initial placement position of the robotic arm model is highly consistent with the real robotic arm. After a certain axis of the real robotic arm rotates a certain angle, the twin model obtains the angle data in real time and adjusts the angle of the corresponding axis to the corresponding position, realizing the virtual-real linkage of the robotic arm. The principle diagram of the technical solution is shown in the figure. Figure 4 shown.

[0067] This embodiment uses the real-time engine position tracking algorithm based on the Unreal Engine AI behavior tree to match the engine position in the paint booth with the physical entity in the digital twin platform. The input signal of the algorithm is the engine passing point position signal collected by the paint booth sensor and transmitted to the PLC. The position of the engine is determined by judging whether the passing point signal is triggered, thereby driving the twin platform engine position change to track the engine status in real time. This method has obvious advantages when the paint booth engine position data is missing and there are only two passing point signal data. It can solve the problem that the engine position cannot be displayed in real time and coherently. The specific algorithm flow is as follows: Figure 5 As shown, real-time tracking of the engine position in the paint room only requires two types of data: the engine arrival at the paint position signal and the engine leaving the paint position signal. The detection system monitors the status of the two signal data in real time at the beginning of operation to determine whether the engine arrival at the paint position data is activated. If activated, it is considered that the engine has arrived at the paint position, and the system will drive the twin model to the specified paint position. If not activated, the system will determine the activation status of the engine leaving the paint position signal. When the departure signal is activated, the algorithm will assume that the current engine has been painted and begins to leave the paint position. The system will drive the twin model to leave the specified paint position. When the engine leaves the paint position and drives out of the paint room, the system will destroy the current engine model and generate a new engine model at the engine entry position to start a new engine painting process detection. This algorithm can still accurately monitor the paint position of the engine even when the engine position data is missing and the system startup time is uncertain, and realize the key parameter monitoring and management of the engine painting process.

[0068] Among them, the estimation of paint drying time and the control of coating thickness are two important parameter indicators. In order to efficiently and in real time monitor these parameters to help improve engine performance and durability, improve engine quality and consistency, a paint parameter calculation formula for the engine quality inspection digital twin platform is created.

[0069] Among them, the control calculation formula for the engine paint film thickness is: , where T_c is the engine paint film thickness, V is the paint flow rate, A is the paint nozzle area, D is the spraying distance, and M_v is the nozzle moving speed.

[0070] The formula for estimating the drying time of a coating is: , where T_d is the coating drying time, T is the ambient temperature, RH is the relative humidity of the air, and C is a constant.

[0071] The above formula is usually adjusted and optimized based on experimental data and the characteristics of the coating. Compared with the existing drying time calculation formula, this formula introduces the influence of ambient temperature on drying time. The calculated parameters are stored in the knowledge base, and the corresponding quality inspection indicators are adjusted dynamically in real time according to the changes in the spraying environment and related parameter data.

[0072] The quality alarm scheme of this embodiment is as follows Figure 6 As shown, according to the above calculation formula, with the help of the visualization technology of the twin platform, by reading the paint quality threshold in the knowledge base, the current engine paint quality can be displayed in real time. When the paint quality exceeds the established threshold, the digital twin platform can promptly issue relevant prompts or alarms.

[0073] This embodiment builds a real-time engine quality detection system based on digital twin technology. The system has the functions of real-time driving of the robot arm, real-time tracking of the engine position, and real-time online monitoring of the painting quality. The key ideas are as follows:

[0074] 1) Based on the Unreal Engine AI behavior tree function module, a process algorithm for real-time tracking of engine position information was designed, which enabled real-time online monitoring and management of key links in the engine manufacturing spraying process;

[0075] 2) Monitoring and detection of paint quality and consistency is the core of the entire paint quality detection system. This embodiment uses two key formulas, paint film thickness and paint drying time, to monitor the engine paint quality in real time through digital twin technology, and uses the threshold management of paint film thickness and paint drying time in the knowledge base to achieve online alarm of paint quality.

[0076] The embodiment of the present application also provides a device for detecting the quality of engine paint. It should be noted that the device for detecting the quality of engine paint in the embodiment of the present application can be used to execute the detection method for the quality of engine paint provided in the embodiment of the present application. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0077] The following is an introduction to the engine paint quality detection device provided in the embodiment of the present application.

[0078] Figure 7 Schematic diagram of a device for detecting engine paint quality according to an embodiment of the present application. Figure 7 As shown, the device includes: a construction unit 71, a first determination unit 72, a control unit 73, and a monitoring unit 74.

[0079] A construction unit 71 is used to construct a digital twin model of the engine and a digital twin model of the painting robot on the digital twin platform, obtain an engine model and a robot model, and control the initial placement and initial movement of the virtual robot in the robot model to be consistent with those of the painting robot;

[0080] Specifically, the initial placement position of the robotic arm model in the digital twin platform is highly consistent with the real robotic arm. After a certain axis of the real robotic arm rotates a certain angle, the twin model obtains the angle data in real time and adjusts the angle of the corresponding axis to the corresponding position, realizing the virtual and real linkage of the robotic arm.

[0081] A first determination unit 72 is used to control the engine model to move to the virtual painting position of the digital twin platform when the engine reaches the real painting position;

[0082] Specifically, the position of the engine is determined by judging whether the passing point signal is triggered. When triggered, it is determined that the engine has reached the actual painting position, thereby driving the twin platform engine position change to track the engine status in real time.

[0083] The control unit 73 is used to control the movement of the painting robot and obtain the movement data and the spraying data and environmental data of the painting robot after the engine reaches the real painting position, and transmit the movement data, spraying data and environmental data to the digital twin platform, wherein the spraying data includes the paint flow rate, the paint nozzle area, the spraying distance, and the nozzle moving speed;

[0084] Specifically, the environmental data includes ambient temperature and relative humidity of the air, and the motion data is the rotation data of each axis of the robotic arm. The motion data is transmitted to the digital twin platform, realizing the virtual-real linkage of the robotic arm; the paint data and environmental data are transmitted to the digital twin platform, realizing the monitoring of the engine paint quality on the digital twin platform.

[0085] The monitoring unit 74 is used to control the virtual robot action of the digital twin platform according to the action data, and use the digital twin platform to determine the engine paint film thickness and paint drying time according to the spraying data and environmental data, and determine the paint quality value according to the engine paint film thickness and paint drying time.

[0086] Specifically, the engine paint film thickness and paint drying time are determined based on the spraying data and environmental data. With the help of the twin platform's visualization technology, the paint quality threshold in the knowledge base is read to display the current engine paint quality in real time. When the paint quality exceeds the established threshold, the digital twin platform's real-time paint quality monitoring platform can provide timely prompts or alarms.

[0087] In this embodiment, a construction unit is used to construct a digital twin model of the engine and a digital twin model of the painting robot on the digital twin platform to obtain the engine model and the robot model, and control the initial placement position and initial movement of the virtual robot in the robot model to be consistent with those of the painting robot; a first determination unit is used to control the engine model to move to the virtual painting position of the digital twin platform when the engine reaches the real painting position; a control unit is used to control the movement of the painting robot and obtain movement data and the spraying data and environmental data of the painting robot after the engine reaches the real painting position, and transmit the movement data, spraying data and environmental data to the digital twin platform, wherein the spraying data includes paint flow rate, paint nozzle area, spraying distance, and nozzle moving speed; a monitoring unit is used to control the movement of the virtual robot of the digital twin platform according to the movement data, and use the digital twin platform to determine the engine paint film thickness and paint drying time according to the spraying data and environmental data, and determine the paint quality value according to the engine paint film thickness and paint drying time. By simulating the motion trajectory of the painting robot in the paint shop in real time to monitor the robot's motion status in real time, simulating the motion position of the engine to be painted in real time to monitor the engine's spraying status in real time, and monitoring the spraying data and environmental data in real time to provide real-time feedback on the painting quality, online monitoring and management of the engine painting process is achieved to meet the needs of safe and efficient automated operations, and solve the problem that the existing technology lacks a real-time monitoring solution for engine painting scenarios, resulting in low quality of the engine finished product.

[0088] As an optional solution, the monitoring unit includes a first determination module and a second determination module; the first determination module is used to determine the engine paint film thickness according to the first formula: T_c= (V / A×D) / (M_v), wherein T_c is the engine paint film thickness, V is the paint flow rate, A is the paint nozzle area, D is the spraying distance, and M_v is the nozzle moving speed; the second determination module is used to determine the engine paint film thickness according to the second formula: , determine the paint drying time, where the environmental data includes ambient temperature and relative air humidity, T_d is the paint drying time, T is the ambient temperature, RH is the relative air humidity, and C is a constant.

[0089] Specifically, the first formula and the second formula are adjusted and optimized according to the experimental data and the characteristics of the coating. Compared with the existing drying time calculation formula, the second formula of this embodiment introduces the influence of ambient temperature on the drying time. The calculated parameters are stored in the knowledge base, and the corresponding quality inspection indicators are adjusted dynamically in real time according to the changes in the spraying environment and related parameter data. Among them, the estimation of the coating drying time and the control of the coating thickness are two important parameter indicators. Efficient and real-time monitoring of these parameters helps to improve engine performance and durability, and improve engine quality and consistency.

[0090] An optional solution, the device also includes an acquisition unit and a generation unit; the acquisition unit is used to obtain a paint quality threshold from a knowledge base after determining the paint quality value based on the engine paint film thickness and the paint drying time, and determine whether the paint quality value is greater than the paint quality threshold; the generation unit is used to generate an alarm message on the digital twin platform when it is determined that the paint quality value is greater than the paint quality threshold, wherein the alarm message is used to indicate that the paint quality is unqualified.

[0091] Specifically, the paint quality value is determined based on the engine paint film thickness and paint drying time. By reading the paint quality threshold in the knowledge base, the current engine paint quality can be displayed in real time. When the paint quality value exceeds the established threshold, the digital twin platform can promptly issue relevant prompts or alarms. This can replace manual inspection and quality verification, effectively ensuring the quality and consistency of paint.

[0092] An optional solution, the device also includes a transmission unit, which is used to control the painting robot to establish communication with the PLC before the initial placement position and initial movement of the virtual robot in the control robot model are consistent with the painting robot, so as to transmit the angle data of each axis of the painting robot to the PLC, and then transmit the angle data of each axis to the digital twin platform via Kepsever's MQTT Client and MQTT Server.

[0093] Specifically, the PLC first establishes communication with the robotic arm to obtain the six-axis angle data of the servo motor of the robot controller, and then the data is transmitted to the twin development platform via Kepsever's MQTT Client through the self-built MQTT Server. In the digital twin platform, the initial placement position of the robotic arm model and the placement position of the actual robotic arm must be highly consistent. After a certain axis of the actual robotic arm rotates a certain angle, the twin model obtains the angle data in real time and adjusts the angle of the corresponding axis to the corresponding position, thereby realizing the virtual-real linkage of the robotic arm.

[0094] In an optional solution, the device also includes a second determination unit, which is used to determine whether the first position data is activated before the engine reaches the actual paint spraying position, and determine that the engine has reached the actual paint spraying position when it is determined that the first position data is activated, wherein the first position data is collected by an induction sensor at the beginning of the actual paint spraying position.

[0095] An optional solution, the device also includes a third determination unit and a destruction unit, the third determination unit is used to determine whether the second position data is activated after determining the paint quality value according to the engine paint film thickness and the paint drying time, and when it is determined that the second position data is activated, determine that the engine leaves the actual painting position, wherein the second position data is collected by the induction sensor at the end of the actual painting position; the destruction unit is used to control the engine model to move out of the painting position of the digital twin platform and destroy the engine model.

[0096] Specifically, to achieve real-time tracking of the engine's position in the paint room, only two data are needed: the engine's arrival at the paint position signal and the engine's departure from the paint position signal. The detection system monitors the status of the two signal data in real time at the beginning of operation, and determines whether the engine's arrival at the paint position data is activated. If activated, it is considered that the engine has arrived at the paint position, and the system will drive the twin model to the designated paint position. If not activated, the system will determine the activation status of the engine's departure from the paint position signal. When the departure signal is activated, the algorithm will assume that the current engine has been painted and begins to leave the paint position. The system will drive the twin model to leave the designated paint position. When the engine leaves the paint position and drives out of the paint room, the system will destroy the current engine model and generate a new engine model at the engine's entry position, and start a new engine painting process detection. This algorithm can still accurately monitor the engine's paint position when the engine position data is missing and the system startup time is uncertain, and realize the key parameter monitoring and management of the engine painting process.

[0097] An optional solution, the building unit includes a building module, which is used to use the Unreal Engine to build a digital twin model of the engine and a digital twin model of the painting robot on the digital twin platform.

[0098] Specifically, Unreal Engine is used to build the digital twin model of the engine and the digital twin model of the paint robot. Among them, Unreal Engine is a powerful, stable and reliable game engine that can ensure the operation effect and performance stability of the twin model. Unreal Engine has powerful rendering capabilities and visual effects, and can present realistic graphics and light and shadow effects, making the twin model more realistic and vivid.

[0099] The engine paint quality detection device includes a processor and a memory. The construction unit, the first determination unit, the control unit, the monitoring unit, etc. are all stored in the memory as program units, and the processor executes the program units stored in the memory to implement corresponding functions. The modules are all located in the same processor; or, the modules are located in different processors in any combination.

[0100] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the problem of the lack of a real-time monitoring solution for the painting quality of the engine painting scene in the prior art is solved by adjusting the kernel parameters.

[0101] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0102] An embodiment of the present invention provides a computer-readable storage medium, which includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the engine paint quality detection method.

[0103] Specifically, the engine paint quality detection method includes:

[0104] Step S201, constructing a digital twin model of the engine and a digital twin model of the painting robot on the digital twin platform, obtaining an engine model and a robot model, and controlling the initial placement and initial movement of the virtual robot in the robot model to be consistent with those of the painting robot;

[0105] Step S202, when the engine reaches the real painting position, control the engine model to move to the virtual painting position of the digital twin platform;

[0106] Step S203, after the engine reaches the actual painting position, control the movement of the painting robot and obtain the movement data as well as the spraying data and environmental data of the painting robot, and transmit the movement data, spraying data and environmental data to the digital twin platform, wherein the spraying data includes the paint flow rate, the paint nozzle area, the spraying distance, and the nozzle moving speed;

[0107] Step S204, controlling the virtual robot action of the digital twin platform according to the action data, and using the digital twin platform to determine the engine paint film thickness and paint drying time according to the spraying data and environmental data, and determining the paint quality value according to the engine paint film thickness and paint drying time.

[0108] An embodiment of the present invention provides a processor, and the processor is used to run a program, wherein the program executes the method for detecting the engine paint quality when running.

[0109] Specifically, the engine paint quality detection method includes:

[0110] Step S201, constructing a digital twin model of the engine and a digital twin model of the painting robot on the digital twin platform, obtaining an engine model and a robot model, and controlling the initial placement and initial movement of the virtual robot in the robot model to be consistent with those of the painting robot;

[0111] Step S202, when the engine reaches the real painting position, control the engine model to move to the virtual painting position of the digital twin platform;

[0112] Step S203, after the engine reaches the actual painting position, control the movement of the painting robot and obtain the movement data as well as the spraying data and environmental data of the painting robot, and transmit the movement data, spraying data and environmental data to the digital twin platform, wherein the spraying data includes the paint flow rate, the paint nozzle area, the spraying distance, and the nozzle moving speed;

[0113] Step S204, controlling the virtual robot action of the digital twin platform according to the action data, and using the digital twin platform to determine the engine paint film thickness and paint drying time according to the spraying data and environmental data, and determining the paint quality value according to the engine paint film thickness and paint drying time.

[0114] An embodiment of the present invention provides a device, the device including a processor, a memory, and a program stored in the memory and executable on the processor, and when the processor executes the program, at least the following steps are implemented:

[0115] Step S201, constructing a digital twin model of the engine and a digital twin model of the painting robot on the digital twin platform, obtaining an engine model and a robot model, and controlling the initial placement and initial movement of the virtual robot in the robot model to be consistent with those of the painting robot;

[0116] Step S202, when the engine reaches the real painting position, control the engine model to move to the virtual painting position of the digital twin platform;

[0117] Step S203, after the engine reaches the actual painting position, control the movement of the painting robot and obtain the movement data as well as the spraying data and environmental data of the painting robot, and transmit the movement data, spraying data and environmental data to the digital twin platform, wherein the spraying data includes the paint flow rate, the paint nozzle area, the spraying distance, and the nozzle moving speed;

[0118] Step S204, controlling the virtual robot action of the digital twin platform according to the action data, and using the digital twin platform to determine the engine paint film thickness and paint drying time according to the spraying data and environmental data, and determining the paint quality value according to the engine paint film thickness and paint drying time.

[0119] The devices in this article can be servers, PCs, PADs, mobile phones, etc.

[0120] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program for initializing at least the following method steps:

[0121] Step S201, constructing a digital twin model of the engine and a digital twin model of the painting robot on the digital twin platform, obtaining an engine model and a robot model, and controlling the initial placement and initial movement of the virtual robot in the robot model to be consistent with those of the painting robot;

[0122] Step S202, when the engine reaches the real painting position, control the engine model to move to the virtual painting position of the digital twin platform;

[0123] Step S203, after the engine reaches the actual painting position, control the movement of the painting robot and obtain the movement data as well as the spraying data and environmental data of the painting robot, and transmit the movement data, spraying data and environmental data to the digital twin platform, wherein the spraying data includes the paint flow rate, the paint nozzle area, the spraying distance, and the nozzle moving speed;

[0124] Step S204, controlling the virtual robot action of the digital twin platform according to the action data, and using the digital twin platform to determine the engine paint film thickness and paint drying time according to the spraying data and environmental data, and determining the paint quality value according to the engine paint film thickness and paint drying time.

[0125] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0126] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0127] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0128] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0129] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0130] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0131] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0132] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0133] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0134] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0135] 1) The engine paint quality detection method of the present application includes: constructing a digital twin model of the engine and a digital twin model of the paint robot on a digital twin platform to obtain an engine model and a robot model, and controlling the initial placement position and initial movement of the virtual robot in the robot model to be consistent with those of the paint robot; when the engine reaches the real paint position, controlling the engine model to move to the virtual paint position of the digital twin platform; after the engine reaches the real paint position, controlling the movement of the paint robot and obtaining movement data as well as the spraying data and environmental data of the paint robot, and transmitting the movement data, spraying data and environmental data to the digital twin platform, wherein the spraying data includes paint flow rate, paint nozzle area, spraying distance, and nozzle movement speed; controlling the virtual robot movement of the digital twin platform according to the movement data, and using the digital twin platform to determine the engine paint film thickness and paint drying time according to the spraying data and environmental data, and determining the paint quality value according to the engine paint film thickness and paint drying time. By simulating the motion trajectory of the painting robot in the paint shop in real time to monitor the robot's motion status in real time, simulating the motion position of the engine to be painted in real time to monitor the engine's spraying status in real time, and monitoring the spraying data and environmental data in real time to provide real-time feedback on the painting quality, online monitoring and management of the engine painting process is achieved to meet the needs of safe and efficient automated operations, and solve the problem that the existing technology lacks a real-time monitoring solution for engine painting scenarios, resulting in low quality of the engine finished product.

[0136] 2) The engine paint quality detection device of the present application includes: a construction unit, which is used to construct a digital twin model of the engine and a digital twin model of the paint robot on a digital twin platform to obtain an engine model and a robot model, and control the initial placement position and initial movement of the virtual robot in the robot model to be consistent with those of the paint robot; a first determination unit, which is used to control the engine model to move to the virtual paint position of the digital twin platform when the engine reaches the real paint position; a control unit, which is used to control the movement of the paint robot and obtain movement data and the spraying data and environmental data of the paint robot after the engine reaches the real paint position, and transmit the movement data, spraying data and environmental data to the digital twin platform, wherein the spraying data includes paint flow rate, paint nozzle area, spraying distance, and nozzle moving speed; a monitoring unit, which is used to control the virtual robot movement of the digital twin platform according to the movement data, and use the digital twin platform to determine the engine paint film thickness and paint drying time according to the spraying data and environmental data, and determine the paint quality value according to the engine paint film thickness and paint drying time. By simulating the motion trajectory of the painting robot in the paint shop in real time to monitor the robot's motion status in real time, simulating the motion position of the engine to be painted in real time to monitor the engine's spraying status in real time, and monitoring the spraying data and environmental data in real time to provide real-time feedback on the painting quality, online monitoring and management of the engine painting process is achieved to meet the needs of safe and efficient automated operations, and solve the problem that the existing technology lacks a real-time monitoring solution for engine painting scenarios, resulting in low quality of the engine finished product.

[0137] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for detecting engine paint quality, characterized in that: include: Constructing a digital twin model of the engine and a digital twin model of the painting robot on the digital twin platform to obtain an engine model and a robot model, and controlling the initial placement and initial movement of the virtual robot in the robot model to be consistent with those of the painting robot; When the engine reaches the real painting position, controlling the engine model to move to the virtual painting position of the digital twin platform; After the engine reaches the real painting position, the painting robot is controlled to move and obtain the movement data and the spraying data and environmental data of the painting robot, and the movement data, spraying data and environmental data are transmitted to the digital twin platform, wherein the spraying data includes the paint flow rate, the paint nozzle area, the spraying distance, and the nozzle moving speed; Controlling the virtual robot action of the digital twin platform according to the action data, and using the digital twin platform to determine the engine paint film thickness and paint drying time according to the spraying data and the environmental data, and determining the paint quality value according to the engine paint film thickness and the paint drying time; Wherein, the digital twin platform is used to determine the engine paint film thickness and the paint drying time according to the spraying data and the environmental data, including: according to the first formula: T_c= (V / A×D) / (M_v), the engine paint film thickness is determined, wherein T_c is the engine paint film thickness, V is the paint flow rate, A is the paint nozzle area, D is the spraying distance, M_v is the nozzle moving speed, according to the second formula: , determine the coating drying time, wherein the environmental data includes the environmental temperature and the relative humidity of the air, T_d is the coating drying time, T is the environmental temperature, RH is the relative humidity of the air, and C is a constant; Before the engine reaches the real painting position, the method further includes: determining whether first position data is activated, and if it is determined that the first position data is activated, determining that the engine reaches the real painting position, wherein the first position data is collected by an induction sensor at the beginning of the real painting position; After determining the paint quality value according to the engine paint film thickness and the paint drying time, the method further includes: determining whether the second position data is activated, and if it is determined that the second position data is activated, determining that the engine leaves the actual painting position, wherein the second position data is collected by an inductive sensor at the end of the actual painting position; controlling the engine model to move out of the painting position of the digital twin platform, and destroying the engine model.

2. The method according to claim 1, characterized in that After determining the paint quality value according to the engine paint film thickness and the paint drying time, the method further includes: Obtaining a paint quality threshold from a knowledge base, and determining whether the paint quality value is greater than the paint quality threshold; When it is determined that the paint quality value is greater than the paint quality threshold, an alarm message is generated on the digital twin platform, wherein the alarm message is used to indicate that the paint quality is unqualified.

3. The method according to claim 1, characterized in that: Before controlling the virtual robot in the robot model to have the same initial placement position and initial movement as the painting robot, the method includes: The painting robot is controlled to establish communication with the PLC to transmit the angle data of each axis of the painting robot to the PLC, and then the angle data of each axis is transmitted to the digital twin platform via Kepsever's MQTT Client and MQTT Server.

4. The method according to claim 1, characterized in that The digital twin models of the engine and the painting robot are built on the digital twin platform, including: Unreal Engine is used to build digital twin models of the engine and the painting robot on the digital twin platform.

5. A device for detecting the quality of engine paint spraying, characterized in that: include: A construction unit is used to construct a digital twin model of the engine and a digital twin model of the painting robot on the digital twin platform, obtain an engine model and a robot model, and control the initial placement and initial movement of the virtual robot in the robot model to be consistent with those of the painting robot; A first determination unit, configured to control the engine model to move to a virtual painting position of the digital twin platform when the engine reaches a real painting position; A control unit, for controlling the movement of the painting robot and acquiring movement data and the spraying data and environmental data of the painting robot after the engine reaches the real painting position, and transmitting the movement data, spraying data and environmental data to the digital twin platform, wherein the spraying data includes the paint flow rate, the paint nozzle area, the spraying distance, and the nozzle moving speed; A monitoring unit, used to control the virtual robot action of the digital twin platform according to the action data, and use the digital twin platform to determine the engine paint film thickness and the paint drying time according to the spraying data and the environmental data, and determine the paint quality value according to the engine paint film thickness and the paint drying time; The monitoring unit includes a first determination module and a second determination module, wherein the first determination module is used to determine the engine paint film thickness according to a first formula: T_c= (V / A×D) / (M_v), wherein T_c is the engine paint film thickness, V is the paint flow rate, A is the paint nozzle area, D is the spraying distance, and M_v is the nozzle moving speed, and the second determination module is used to determine the engine paint film thickness according to a second formula: , determine the coating drying time, wherein the environmental data includes the environmental temperature and the relative humidity of the air, T_d is the coating drying time, T is the environmental temperature, RH is the relative humidity of the air, and C is a constant; The device further includes a second determination unit, configured to determine whether the first position data is activated, and if it is determined that the first position data is activated, determine that the engine has reached the real painting position, wherein the first position data is collected by an induction sensor at the start of the real painting position; The device also includes a third determination unit and a destruction unit. The third determination unit is used to determine whether the second position data is activated. When it is determined that the second position data is activated, it is determined that the engine leaves the real painting position, wherein the second position data is collected by the induction sensor at the end of the real painting position; the destruction unit is used to control the engine model to move out of the painting position of the digital twin platform and destroy the engine model.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the engine paint quality detection method according to any one of claims 1 to 4.

7. An electronic device, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a method for executing the engine paint quality detection method described in any one of claims 1 to 4.

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