AI-based self-adaptive coating control system of vacuum nano coating machine
By using AI -driven self -adaptive coating control systems on vacuum nano -coating machines, the traditional coating machine operations are complex and dependent on manual problems, and the stability of coating quality and improvement of production efficiency are achieved.
Patent Information
- Application Number
- CN202411335267.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-24
- Publication Date
- 2025-01-21
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The traditional Perryl vacuum coating machine has complex operation and is highly dependent on manual monitoring and adjustment, resulting in uneven coating thickness and large fluctuations in process parameters, which affects product performance and reliability, increases labor costs, and limits the expansion of production scale.
The adaptive coating control system based on AI -based vacuum nano -coating machines includes configuration modules, analysis modules, and adjustment modules, collecting working parameters in real time through the sensor group, analyzing abnormal information based on AI, and automatically adjusting coating parameters.
The adaptive adjustment of the vacuum nano -coating machine is realized, the stability and production efficiency of the coating quality are improved, the cost of labor is reduced, and the production scale is expanded.
Smart Images
Figure CN119332232A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of coating control technology, and in particular to an adaptive coating control system of a vacuum nano coating machine based on AI. Background Art
[0002] In the electronics field, parylene is often used to protect precision electronic components from moisture, dust and corrosive gases, effectively extending the service life of the equipment while maintaining stable signal transmission. In the medical field, its excellent biocompatibility makes parylene an ideal choice for surface coatings of implantable medical devices, such as pacemakers and neurostimulators, which can reduce inflammatory responses after implantation and improve patient comfort and safety. In the aerospace field, parylene is used to protect key components from extreme environmental conditions and ensure the stable operation of aircraft due to its lightweight and high temperature resistance.
[0003] However, the traditional Parylene vacuum coating machine has a complex operation process and is highly dependent on manual monitoring and adjustment. This situation undoubtedly poses a challenge to production efficiency, cost control and the stability of coating quality. Specifically, manual operation may cause uneven coating thickness and large fluctuations in process parameters due to human factors, which in turn affects the overall performance and reliability of the product. In addition, long-term monitoring and adjustment also increase labor costs and limit the expansion of production scale. Summary of the invention
[0004] The purpose of the present invention is to provide an adaptive coating control system for a vacuum nano-coating machine based on AI to solve the shortcomings of the background technology.
[0005] In order to achieve the above-mentioned purpose, the present invention provides the following technical solution: an adaptive coating control system of a vacuum nano-coating machine based on AI, comprising: A configuration module, used for configuring a sensor group corresponding to the vacuum nano coating machine, and collecting working parameters of the vacuum nano coating machine in real time based on the sensor group; An analysis module, connected to the configuration module, is used to analyze the working parameters of the vacuum nano coating machine based on AI to obtain abnormal information of the working parameters of the vacuum nano coating machine; The adjustment module is connected to the analysis module and is used to provide abnormal information to the user end and automatically adjust the working parameters of the vacuum nano coating machine.
[0006] In a preferred embodiment, the configuration module includes: An information collection unit, used to collect physical information of the vacuum nano-coating machine, wherein the physical information includes equipment shape, equipment size and equipment basic parameters; A construction unit, used for constructing a device model of a vacuum nano coating machine based on physical information, and determining and marking coating range information of the vacuum nano coating machine in the device model; A configuration unit, used for selecting a configuration position of a sensor based on a device model, configuring the corresponding sensor to an actual vacuum nano coating machine based on the configuration position to obtain a sensor group, and aligning the sensor group to the corresponding configuration position; The real-time acquisition unit is used to acquire the working parameters of the vacuum nano coating machine in real time through the sensor group, and mark the working parameters in the equipment model.
[0007] In a preferred embodiment, the building block comprises: A determination unit is used to construct a spatial model, describe the physical information of the vacuum nano-coating machine in a single shape to obtain multiple single lines, mark the multiple single lines in the spatial model, and limit the marked multiple single lines in the spatial model according to the positions between the multiple single lines to obtain a device model; A marking unit is used to determine the coating chamber of the vacuum nano coating machine, obtain multiple single lines of the coating chamber and determine the positions of the multiple single lines of the coating chamber in the equipment model, and use the partial model corresponding to the multiple single lines of the coating chamber in the equipment model as the coating range information and mark it in the equipment model.
[0008] In a preferred embodiment, the marking unit comprises: A storage unit, used for storing a plurality of single lines as a line database; A first configuration unit is used to configure corresponding traction keys for a plurality of single lines in the line database, wherein the traction keys include ports and port channels; The second configuration unit is used to configure the unit library corresponding to the multiple single lines in the device model, and establish the corresponding relationship between the multiple single lines in the device model and the multiple single lines in the line database; A relationship establishing unit, used for establishing a connection between a unit library of a single line configuration in a device model and a port of a single line in a corresponding line database through a port channel based on the corresponding relationship; The model marking unit is used to determine the multiple single lines corresponding to the coating room in the line database, connect the ports of the coating room corresponding to the multiple single lines in the line database with the corresponding unit library in the equipment model, enable the corresponding single lines through the unit library to obtain the partial model corresponding to the equipment model, use the partial model as the coating range information and mark it in the equipment model.
[0009] In a preferred embodiment, the real-time acquisition unit includes: The acquisition and determination unit is used to determine the monitoring range of the sensor group, obtain the corresponding single line within the monitoring range of the sensor group, and bind the single line within the monitoring range of the sensor group to the corresponding sensor; A data acquisition unit is used to collect the working parameters of the vacuum nano coating machine in real time through a sensor group, and store the working parameters in a unit library through a port by corresponding a single line of the database to the working parameters; Marking display unit is used to mark on the equipment model by displaying the working parameters in the unit library.
[0010] In a preferred embodiment, the analysis module comprises: The training unit is used to collect and train a large amount of historical data of the vacuum nano coating machine based on the AI algorithm, extract features from the historical data and output accordingly to obtain a trained AI algorithm, wherein the historical data is the working parameters in the unit library corresponding to a single line in the history; The analysis unit is used to input the working parameters of the vacuum nano-coating machine collected in real time into the trained AI algorithm to obtain abnormal information of the working parameters of the vacuum nano-coating machine.
[0011] In a preferred embodiment, the adjustment module includes: An adjustment unit, used for adjusting corresponding parameters of the vacuum nano coating machine according to the abnormal information until the working parameters of the vacuum nano coating machine are in a normal state; The providing unit is used to provide abnormal information and data of adjusting working parameters of the vacuum nano coating machine to the user end.
[0012] In a preferred embodiment, the providing unit comprises: A data storage unit, used to store abnormal information and data on adjustment of working parameters of the vacuum nano coating machine into a unit library corresponding to a single line; The marking unit is used to mark the abnormal information and the data of adjusting the working parameters of the vacuum nano-coating machine on the equipment model through the unit library and provide it to the user end.
[0013] In the above technical solution, the technical effects and advantages provided by the present invention are: The present invention can connect the port of a single line in the line database with the corresponding unit library of the single line through the port channel. The connection between the port, the port channel and the corresponding unit library here is not used for information transmission, but as a directional correspondence, it can efficiently realize an enabling indexing function, and can directly jump to the device model through the information of the line database. It has a good involvement effect, can differentiate the storage and display of data, refine the working parameters, and more carefully display the working parameters of the vacuum nano coating machine in a multi-range, so that the data is displayed in a smaller range more accurately, and the working parameters of the vacuum nano coating machine can be adaptively adjusted by itself. BRIEF DESCRIPTION OF THE DRAWINGS
[0014] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.
[0015] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION
[0016] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0017] Example 1, please refer to Figure 1 As shown, the adaptive coating control system of the vacuum nano coating machine based on AI in this embodiment includes: A configuration module, used for configuring a sensor group corresponding to the vacuum nano coating machine, and collecting working parameters of the vacuum nano coating machine in real time based on the sensor group; An analysis module, connected to the configuration module, is used to analyze the working parameters of the vacuum nano coating machine based on AI to obtain abnormal information of the working parameters of the vacuum nano coating machine; An adjustment module, connected to the analysis module, is used to provide abnormal information to the user end and automatically adjust the working parameters of the vacuum nano coating machine; It should be noted that in the electronics field, parylene is often used to protect precision electronic components from moisture, dust and corrosive gases, effectively extending the service life of the equipment while maintaining stable signal transmission. In the medical field, its excellent biocompatibility makes parylene an ideal choice for surface coatings of implantable medical devices, such as pacemakers and neurostimulators, which can reduce inflammatory responses after implantation and improve patient comfort and safety. In the aerospace field, parylene is used to protect key components from extreme environmental conditions and ensure the stable operation of aircraft due to its lightweight and high temperature resistance.
[0018] However, the traditional Parylene vacuum coating machine has a complex operation process and is highly dependent on manual monitoring and adjustment. This situation undoubtedly poses a challenge to production efficiency, cost control and the stability of coating quality. Specifically, manual operation may cause uneven coating thickness and large fluctuations in process parameters due to human factors, which in turn affects the overall performance and reliability of the product. In addition, long-term monitoring and adjustment also increase labor costs and limit the expansion of production scale.
[0019] In the present application, the port of a single line in the line database can be connected to the corresponding unit library of a single line through a port channel. The connection between the port, the port channel and the corresponding unit library is not used for information transmission, but as a directional correspondence, it can efficiently realize an enabling indexing function, and can directly jump to the device model through the information in the line database. It has a good involvement effect, can differentiate the storage and display of data, refine the working parameters, and more carefully display the working parameters of the vacuum nano coating machine in a multi-range, so that the data can be displayed in a smaller range more accurately, and the working parameters of the vacuum nano coating machine can be adaptively adjusted by itself.
[0020] In one embodiment, the configuration module includes: An information collection unit, used to collect physical information of the vacuum nano-coating machine, wherein the physical information includes equipment shape, equipment size and equipment basic parameters; A construction unit, used for constructing a device model of a vacuum nano coating machine based on physical information, and determining and marking coating range information of the vacuum nano coating machine in the device model; A configuration unit, used for selecting a configuration position of a sensor based on a device model, configuring the corresponding sensor to an actual vacuum nano coating machine based on the configuration position to obtain a sensor group, and aligning the sensor group to the corresponding configuration position; A real-time acquisition unit, used to acquire the working parameters of the vacuum nano coating machine in real time through a sensor group, and mark the working parameters in the equipment model; It should be noted that the vacuum nano-coating machine is a specially designed industrial equipment, and its appearance is usually carefully constructed according to functional requirements. The equipment may have a rectangular or approximately cubic main structure to maximize the utilization of the internal coating space, and is equipped with various precision interfaces and components to meet the needs of vacuum processing and nano-coating; specifically, the size of the equipment, the vacuum nano-coating machine usually has clear length, width and height parameters. These size parameters not only determine the physical space occupied by the equipment, but also directly affect the processing capacity and efficiency in the coating room. For example, its length may reach several meters, and the width and height vary according to the specific model and design, which together constitute the overall volume scale of the equipment. In order to better control the coating of the vacuum nano-coating machine, the equipment model of the vacuum nano-coating machine is constructed here through physical information, and then the sensor group needs to be configured on the equipment model. The sensor group here includes: temperature sensor, pressure sensor and gas flow sensor, which can reflect the working status of the vacuum nano-coating machine. Among them, the temperature sensor is usually installed on or near the inner wall of the coating chamber, and near the key components that may directly affect the coating temperature, such as heating elements or cooling devices, to monitor the temperature changes in the coating chamber in real time, to ensure that the coating process is carried out within the set temperature range, and to avoid coating quality problems caused by too high or too low temperature; the pressure sensor is usually installed at the connection between the vacuum chamber and the exhaust system, or directly installed on the inner wall of the vacuum chamber, so as to accurately measure the pressure changes in the coating chamber, to monitor the vacuum degree in the coating chamber, to ensure that the required vacuum environment is maintained during the coating process, and to avoid interference of gas molecules on the coating process; the gas flow sensor is usually installed at the gas inlet and outlet of the coating chamber, such as on the air inlet and exhaust pipes, to measure and control the gas flow in and out of the coating chamber, to monitor and control the flow of gas required during the coating process in real time, and to ensure the stability and consistency of the coating process. The configuration position of high-precision sensors in vacuum nano coating machines is determined according to the monitoring objects (temperature, pressure, gas flow) and coating process requirements. The temperature needs to be collected and controlled in the evaporation chamber, cracking chamber, deposition chamber, and cold trap of the vacuum nano coating machine; vacuum pumps, roots pumps, and chassis motors are used to adjust the gas flow rate. These sensors provide accurate data support for the coating process by real-time monitoring of key parameters in the coating chamber to ensure coating quality and efficiency.At the same time, the installation position of the sensor also needs to consider its possible interference and impact on the coating process to ensure the accuracy and reliability of the monitoring results. Therefore, during the coating process, it is necessary to collect temperature, pressure, and gas flow as a data reference for the coating status. After the equipment model is constructed, since the coating chamber is the location of the coating operation, the coating range information of the vacuum nano coating machine is determined in the equipment model for marking, and then the corresponding sensor is configured to the actual vacuum nano coating machine based on the configuration position to obtain the sensor group. After setting the sensor group, the working parameters of the vacuum nano coating machine are collected in real time through the sensor group, and the working parameters are marked in the equipment model, which can better monitor the vacuum nano coating machine during the working process, and then perform subsequent coating control according to the actual working parameters, so that the coating quality is higher;. In one embodiment, the building block comprises: A determination unit is used to construct a spatial model, describe the physical information of the vacuum nano-coating machine in a single shape to obtain multiple single lines, mark the multiple single lines in the spatial model, and limit the marked multiple single lines in the spatial model according to the positions between the multiple single lines to obtain a device model; A marking unit, used to determine a coating chamber of the vacuum nano coating machine, obtain a plurality of single lines of the coating chamber and determine the positions of the plurality of single lines of the coating chamber in the equipment model, and use the partial models corresponding to the plurality of single lines of the coating chamber in the equipment model as coating range information and mark them in the equipment model; It should be noted that, first, a space is constructed for establishing a device model, and the space is a three-dimensional blank space. The physical information of the vacuum nano-coating machine is collected, and the physical information is the shape and corresponding size of the vacuum nano-coating machine. Then, a single description of the shape of the vacuum nano-coating machine is performed. Here, it is equivalent to disassembling the vacuum nano-coating machine to obtain multiple single lines, and the multiple single lines are marked in the space model. The multiple single lines marked in the space model are limited according to the positions between the multiple single lines to obtain the device model. The positions between the multiple single lines here are the corresponding positional relationships of the multiple single lines on the vacuum nano-coating machine. For example, the vertical relationship of two lines intersecting at one end on the vacuum nano-coating machine is used as the position between the multiple single lines, which can locate The positional relationship between multiple single lines is combined to obtain a device model, which can better fit the actual vacuum nano coating machine for more accurate model construction, and then obtain the device model. Since the coating chamber is an important location for coating of the vacuum nano coating machine, the substrate is set in the coating chamber for coating treatment, and then it is necessary to determine the model corresponding to the coating chamber in the device model as the coating range information and mark it in the device model. Here, when determining the coating range information in the device model, it is necessary to determine the corresponding single line in the device model through a single line, and use the partial model surrounded by multiple single lines in the device model as the coating range information, which has a better model determination effect, can quickly obtain the actual vacuum nano coating machine corresponding to the position in the model, and can improve the corresponding efficiency of the model; In one embodiment, the marking unit comprises: A storage unit, used for storing a plurality of single lines as a line database; A first configuration unit is used to configure corresponding traction keys for a plurality of single lines in the line database, wherein the traction keys include ports and port channels; The second configuration unit is used to configure the unit library corresponding to the multiple single lines in the device model, and establish the corresponding relationship between the multiple single lines in the device model and the multiple single lines in the line database; A relationship establishing unit, used for establishing a connection between a unit library of a single line configuration in a device model and a port of a single line in a corresponding line database through a port channel based on the corresponding relationship; The model marking unit is used to determine the multiple single lines in the line database corresponding to the coating room, connect the ports of the multiple single lines in the line database corresponding to the coating room with the corresponding unit library in the equipment model, enable the corresponding single lines through the unit library to obtain the partial model corresponding to the equipment model, and use the partial model as the coating range information and mark it in the equipment model; It should be noted that, in order to quickly obtain the corresponding position of the coating room in the model, multiple single lines corresponding to the coating room can be quickly obtained through the line database, and the multiple single lines in the line database are configured with corresponding traction keys. The traction keys include ports and port channels. Through the traction keys, they can be connected to the unit library corresponding to the single line in the equipment model, and then can be quickly matched to the equipment model, and the position of the coating room on the equipment model can be quickly obtained. The corresponding model can be quickly established, and in the subsequent monitoring of the coating room, it can be more quickly reflected in the equipment model, thereby improving the reaction efficiency of the equipment model to the coating room. When setting the port, the single line is used as the port. The carrier sets the corresponding communication terminal, and then the unit library corresponding to the single line configuration in the equipment model is equivalent to a unit library storing a single line. The unit libraries corresponding to multiple single lines in the coating room can be combined to reflect the parameter information in the coating room, so that it is easier to display it through the equipment model later. The port of the single line in the line database can be connected to the corresponding unit library of the single line through the port channel. The connection between the port, the port channel and the corresponding unit library here is not used for information transmission. Here, it serves as a directional corresponding role, which can efficiently realize an enabling indexing role, and can directly jump to the equipment model through the information in the line database, which has a good involvement effect; In one embodiment, the real-time acquisition unit includes: The acquisition and determination unit is used to determine the monitoring range of the sensor group, obtain the corresponding single line within the monitoring range of the sensor group, and bind the single line within the monitoring range of the sensor group to the corresponding sensor; A data acquisition unit is used to collect the working parameters of the vacuum nano coating machine in real time through a sensor group, and store the working parameters in a unit library through a port by corresponding a single line of the database to the working parameters; A marking display unit is used to mark on the equipment model by displaying the working parameters in the unit library; It should be noted that the collection of sensor information has a range. By determining the monitoring range corresponding to the sensor in the sensor group, a single line within the monitoring range can be obtained. The single line can represent the spatial position in the vacuum nano coating machine. Binding the single line within the monitoring range of the sensor group with the corresponding sensor can facilitate the subsequent display and storage of the monitoring information collected in the vacuum nano coating machine. The sensor group includes a temperature sensor, a pressure sensor and a gas flow sensor, which are used to collect and monitor the information of the equipment during the operation of the vacuum nano coating machine. The collected working parameters are corresponded to a single line, and stored in the unit library corresponding to the single line through the port corresponding to the single line. The unit library can store the working parameters and display them as data output on the device model at the same time. Displaying the working parameters on the device model can differentiate the storage and display of data, refine the working parameters, and more carefully display the working parameters of the vacuum nano coating machine in multiple ranges, so that the data is displayed in a smaller range and more accurately.
[0021] In one embodiment, the analysis module comprises: The training unit is used to collect and train a large amount of historical data of the vacuum nano coating machine based on the AI algorithm, extract features from the historical data and output accordingly to obtain a trained AI algorithm, wherein the historical data is the working parameters in the unit library corresponding to a single line in the history; An analysis unit, used for inputting the real-time collected working parameters of the vacuum nano coating machine into the trained AI algorithm to obtain abnormal information of the working parameters of the vacuum nano coating machine; It should be noted that after the AI algorithm (such as machine learning model, deep learning network, etc.) is trained, the actual parameters (also called input data or features) are input into the algorithm for processing. For classification problems, the algorithm will output one or more category labels, indicating the category to which the input data is most likely to belong; for regression problems, the algorithm will output a continuous value, which is the predicted value of the target variable corresponding to the input data. Some algorithms or tools can display the processing results in a visual form, such as heat map, scatter plot, decision tree diagram, etc., so that users can more intuitively understand the behavior and prediction results of the model. The prediction structure can reflect the abnormal information of the working parameters of the vacuum nano coating machine and give the corresponding optimization information, and then the working status of the vacuum nano coating machine can be understood according to the abnormal information, which is used for the subsequent parameter understanding of the vacuum nano coating machine. It has a good control effect on the vacuum nano coating machine, can achieve precise control of the vacuum nano coating machine, and improve the uniformity and adhesion of the parylene film. In one embodiment, the adjustment module includes: An adjustment unit, used for adjusting corresponding parameters of the vacuum nano coating machine according to the abnormal information until the working parameters of the vacuum nano coating machine are in a normal state; A providing unit, used for providing abnormal information and data for adjusting working parameters of the vacuum nano coating machine to a user terminal; It should be noted that the corresponding parameters of the vacuum nano coating machine are adjusted according to the abnormal information until the working parameters of the vacuum nano coating machine are in a normal state. Here, the vacuum nano coating machine is adjusted by optimizing the information and the abnormal information, which can make the stability of the parameters in the coating process of the substrate qualified and improve the uniformity and adhesion of the parylene film. After that, the adjustment process, that is, the data of the working parameter adjustment of the vacuum nano coating machine (optimization information) and the abnormal information are provided to the user end, which can be understood by the user end. At the same time, the working parameters of the vacuum nano coating machine can be adaptively adjusted by the user end.
[0022] In one embodiment, the providing unit comprises: A data storage unit, used to store abnormal information and data on adjustment of working parameters of the vacuum nano coating machine into a unit library corresponding to a single line; A marking unit, used to mark abnormal information and data on adjustment of working parameters of the vacuum nano coating machine on a device model through a unit library and provide the data to a user end; It should be noted that the abnormal information and the data on the adjustment of the working parameters of the vacuum nano-coating machine are bound according to the single lines corresponding to the sensor groups and stored in the unit library corresponding to the single lines. The abnormal information and the data on the adjustment of the working parameters of the vacuum nano-coating machine can be marked and displayed in the equipment model through the unit library, and displayed to the user end through the equipment model. The working parameters of the vacuum nano-coating machine can also be adjusted by human intervention through the user end. The actual vacuum nano-coating machine has an automated conveying system for automatically loading and unloading substrates to be coated; at least one sensor for monitoring key parameters in the coating chamber; data processing for receiving and analyzing sensor data; automatically adjusting the coating parameters according to the analysis results of the data processing unit through an adaptive control system; and a user interface for displaying real-time data of the coating process and receiving user instructions.
[0023] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.
Claims
1. The AI-based adaptive coating control system for vacuum nano-coating machines is characterized by: include: A configuration module, used for configuring a sensor group corresponding to the vacuum nano coating machine, and collecting working parameters of the vacuum nano coating machine in real time based on the sensor group; An analysis module, connected to the configuration module, is used to analyze the working parameters of the vacuum nano coating machine based on AI to obtain abnormal information of the working parameters of the vacuum nano coating machine; The adjustment module is connected to the analysis module and is used to provide abnormal information to the user end and automatically adjust the working parameters of the vacuum nano coating machine.
2. The AI-based adaptive coating control system for vacuum nano-coating machines according to claim 1, characterized in that: The configuration module includes: An information collection unit, used to collect physical information of the vacuum nano-coating machine, wherein the physical information includes equipment shape, equipment size and equipment basic parameters; A construction unit, used for constructing a device model of a vacuum nano coating machine based on physical information, and determining and marking coating range information of the vacuum nano coating machine in the device model; A configuration unit, used for selecting a configuration position of a sensor based on a device model, configuring the corresponding sensor to an actual vacuum nano coating machine based on the configuration position to obtain a sensor group, and aligning the sensor group to the corresponding configuration position; The real-time acquisition unit is used to acquire the working parameters of the vacuum nano coating machine in real time through the sensor group, and mark the working parameters in the equipment model.
3. The AI-based adaptive coating control system for vacuum nano-coating machines according to claim 2 is characterized in that: The building block comprises: A determination unit is used to construct a spatial model, describe the physical information of the vacuum nano-coating machine in a single shape to obtain multiple single lines, mark the multiple single lines in the spatial model, and limit the marked multiple single lines in the spatial model according to the positions between the multiple single lines to obtain a device model; A marking unit is used to determine the coating chamber of the vacuum nano coating machine, obtain multiple single lines of the coating chamber and determine the positions of the multiple single lines of the coating chamber in the equipment model, and use the partial model corresponding to the multiple single lines of the coating chamber in the equipment model as the coating range information and mark it in the equipment model.
4. The AI-based adaptive coating control system for vacuum nano-coating machine according to claim 3 is characterized in that: The marking unit comprises: A storage unit, used for storing a plurality of single lines as a line database; A first configuration unit is used to configure corresponding traction keys for a plurality of single lines in the line database, wherein the traction keys include ports and port channels; The second configuration unit is used to configure the unit library corresponding to the multiple single lines in the device model, and establish the corresponding relationship between the multiple single lines in the device model and the multiple single lines in the line database; A relationship establishing unit, used for establishing a connection between a unit library of a single line configuration in a device model and a port of a single line in a corresponding line database through a port channel based on the corresponding relationship; The model marking unit is used to determine the multiple single lines corresponding to the coating room in the line database, connect the ports of the coating room corresponding to the multiple single lines in the line database with the corresponding unit library in the equipment model, enable the corresponding single lines through the unit library to obtain the partial model corresponding to the equipment model, use the partial model as the coating range information and mark it in the equipment model.
5. The AI-based adaptive coating control system for vacuum nano-coating machine according to claim 2, characterized in that: The real-time acquisition unit comprises: The acquisition and determination unit is used to determine the monitoring range of the sensor group, obtain the corresponding single line within the monitoring range of the sensor group, and bind the single line within the monitoring range of the sensor group to the corresponding sensor; A data acquisition unit is used to collect the working parameters of the vacuum nano coating machine in real time through a sensor group, and store the working parameters in a unit library through a port by corresponding a single line of the database to the working parameters; Marking display unit is used to mark on the equipment model by displaying the working parameters in the unit library.
6. The AI-based adaptive coating control system for vacuum nano-coating machine according to claim 1, characterized in that: The analysis module comprises: The training unit is used to collect and train a large amount of historical data of the vacuum nano coating machine based on the AI algorithm, extract the features in the historical data and output them accordingly to obtain a trained AI algorithm, wherein the historical data is the working parameters in the unit library corresponding to a single line in the history; The analysis unit is used to input the working parameters of the vacuum nano-coating machine collected in real time into the trained AI algorithm to obtain abnormal information of the working parameters of the vacuum nano-coating machine.
7. The AI-based adaptive coating control system for vacuum nano-coating machine according to claim 1, characterized in that: The adjustment module comprises: An adjustment unit, used for adjusting corresponding parameters of the vacuum nano coating machine according to the abnormal information until the working parameters of the vacuum nano coating machine are in a normal state; The providing unit is used to provide abnormal information and data of adjusting working parameters of the vacuum nano coating machine to the user end.
8. The AI-based adaptive coating control system of the vacuum nano-coating machine according to claim 7, characterized in that: The providing unit comprises: A data storage unit, used to store abnormal information and data on adjustment of working parameters of the vacuum nano coating machine into a unit library corresponding to a single line; The marking unit is used to mark the abnormal information and the data of adjusting the working parameters of the vacuum nano-coating machine on the equipment model through the unit library and provide it to the user end.