A method and system for adaptively adjusting operating parameters of a vacuum coating machine

Abstract

The present invention discloses a method and system for adaptively adjusting the operating parameters of a vacuum coating machine, and relates to the technical field of operating parameter control of a vacuum coating machine. The system includes a data collection module, a control strategy generation module, a real-time monitoring and analysis module, and a data interaction module. The data collection module is used to collect the operating parameters of the vacuum coating machine, the control strategy generation module is used to produce optimal parameters, and the real-time monitoring and analysis module is used to monitor the production process. The method analyzes the main operating parameters of the vacuum coating machine through the control strategy generation module combined with the historical data collection unit, and determines the important parameters, constructs the operating model of the vacuum coating machine with the important parameters, sets the output conditions, obtains the optimal collection of important parameters, and outputs the specific indicators of each parameter to the data interaction module, and performs vacuum coating with these parameters, thereby ensuring the uniformity of vacuum coating parameters and the relatively stable coating quality of all products.

Description

Technical Field

[0001] The present invention relates to the technical field of vacuum coating machine operating parameter control, and in particular to a method and system for adaptively adjusting operating parameters of a vacuum coating machine. Background Art

[0002] With the rapid development of society, in order to improve the durability of workpieces, coating technology, as a way to form a dense protective layer on the surface of workpieces, is constantly being improved.

[0003] As we all know, vacuum coating refers to a method of heating metal or non-metal materials under high vacuum conditions to evaporate and condense on the surface of the coated object (metal, semiconductor or insulator) to form a thin film. Since vacuum coating can coat objects more evenly, its use is becoming more and more frequent.

[0004] The existing vacuum coating is mainly completed by a vacuum coating machine, which generally includes four parts: a coating cylinder, a cracking chamber, an evaporation chamber and a vacuum pumping device. Among them, the coating cylinder has a accommodating cavity for placing the workpiece to be plated, the evaporation chamber is used to evaporate the coating material, the cracking chamber is used to crack the coating material, and the vacuum pumping device is used to vacuum the coating cylinder. Therefore, when the vacuum coating machine is working, the vacuum pumping device first performs vacuuming to make the coating cylinder, the evaporation chamber and the cracking chamber each in a vacuum state, and then the coating material is evaporated by the evaporation chamber, and the evaporated coating material enters the cracking chamber, and the evaporated coating material is cracked by the cracking chamber, and the cracked coating material enters the coating cylinder, so that a layer of coating material will be attached to the surface of the workpiece to be plated in the coating cylinder, thereby achieving the purpose of coating;

[0005] However, the existing vacuum coating machines currently only have professional staff to adjust the parameters, which cannot meet the current diversified processing and production conditions. That is, the parameter adjustment relies too much on the subjective experience and judgment of the staff. The experience and judgment of different staff may differ, resulting in inconsistent parameter adjustment results, affecting the quality and stability of the product. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a method and system for adaptively adjusting the operating parameters of a vacuum coating machine, which has the advantages of adaptively adjusting the processing parameters of the vacuum coating machine and solves the above-mentioned technical problems.

[0007] To achieve the above-mentioned object, the present invention provides the following technical solutions: an adaptive adjustment system for operating parameters of a vacuum coating machine, comprising a data collection module, a control strategy generation module, a real-time monitoring and analysis module and a data interaction module;

[0008] The data collection module is used to collect the operating parameters of the vacuum coating machine. The data collection module includes a historical data collection unit and a real-time data collection unit. The historical data collection unit is used to collect various parameters of the vacuum coating machine in the historical coating process and send the collected parameters to the control strategy generation module. The real-time data collection unit is used to collect data in the real-time coating process of the vacuum coating machine, and the real-time data collection unit sends the data to the real-time monitoring and analysis module.

[0009] The control strategy generation module is used to analyze the main operating parameters of the vacuum coating machine in combination with the historical data collection unit, and determine the important parameters, build an operating model of the vacuum coating machine with the important parameters, set output conditions, and obtain the optimal set of important parameters, as well as the specific indicators of each parameter to output to the data interaction module, and perform vacuum coating with this parameter;

[0010] The real-time monitoring and analysis module is used to collect the operating parameters of the vacuum coating machine during the coating process according to the control strategy generation module, and send abnormal data to the data interaction module for early warning;

[0011] The data interaction module includes a collection of important parameters output by the control strategy generation module as execution conditions to operate the vacuum coating machine. At the same time, the staff changes the output conditions in the control strategy generation module through the data interaction module to use different production parameters for different products. The data interaction module also includes feedback of the early warning conditions in the real-time monitoring and analysis module to the staff, reminding the staff to inspect and maintain the vacuum coating machine.

[0012] As a preferred technical solution of the present invention, the historical data collection unit collects the operating parameters of the vacuum coating machine and constructs a vacuum coating machine operating parameter set. , the specific expression is as follows:

[0013]

[0014] in, Respectively The operating parameters of different vacuum coating machines.

[0015] As a preferred technical solution of the present invention, the control strategy generation module reads the vacuum coating machine operating parameter set , and the specific steps for generating the control strategy are as follows:

[0016] A1. Use principal component analysis to analyze the vacuum coating machine operating parameter set After the analysis is completed, select the top ranking data, conduct secondary analysis, and select the top data as important parameters and The data constitutes the important parameter data set ;

[0017] A2. Based on important parameter data sets Establish the optimal parameter model;

[0018] A3. Solve the optimal parameter model established in step A2 to obtain a set of optimal parameters.

[0019] As a preferred technical solution of the present invention, the principal component analysis method is used in step A1 to analyze the vacuum coating machine operating parameter set. The steps to perform the analysis are as follows:

[0020] In step A1, the principal component analysis method is used to analyze the operating parameter set of the vacuum coating machine. After the analysis is completed, select the top ranking data, conduct secondary analysis, and select the top data as important parameters and The data constitutes the important parameter data set The specific steps are as follows:

[0021] A1.1. Set the operating parameters of the vacuum coating machine Calculate the mean of each parameter in the data and remove the mean of each element;

[0022] A1.2. Calculate the eigenvalues ​​and corresponding eigenvectors of the covariance matrix;

[0023] A1.3. Before selection The parameters corresponding to the characteristic values ​​are calculated one by one. Remove Parameters other than eigenvalues ​​and The similarity between the parameters corresponding to the eigenvalues ​​is expressed as follows:

[0024]

[0025] in, Represents the operating parameter set of the vacuum coating machine Remove Parameters other than eigenvalues ​​and The similarity between the kth parameters in the eigenvalues, Represents the operating parameter set of the vacuum coating machine Remove The i-th parameter other than the eigenvalue, represents the modulo operation, express The kth parameter among the parameters corresponding to the eigenvalues;

[0026] A1.4. Similarity of the i-th parameter After the calculation is completed, it is divided into the class with the highest similarity, and steps A1.3-A1.4 are performed on all parameters in turn until all parameters are divided and obtained. Each data corresponds to a group;

[0027] A1.5. Selection The corresponding groups in the data are ranked first data as important parameters ( ), and this The data constitutes the important parameter data set .

[0028] As a preferred technical solution of the present invention, the important parameter data set The specific expression is as follows:

[0029]

[0030] in, Respectively different important parameters.

[0031] As a preferred technical solution of the present invention, the specific expression of the optimal parameter model established in step A2 is as follows:

[0032]

[0033] in, Respectively represent 1~m different important parameters, represents the balance coefficient, Respectively represent the weights corresponding to 1~m different important parameters, Express The optimal parameter model, Indicates the output target.

[0034] As a preferred technical solution of the present invention, the real-time monitoring and analysis module includes monitoring the vacuum degree, power, temperature, evaporation source pressure, flow, liquid level and oscillation of the vacuum coating machine.

[0035] As a preferred technical solution of the present invention, the real-time monitoring and analysis module compares the vacuum degree, power, temperature, evaporation source pressure, flow rate, liquid level and oscillation of the vacuum coating machine with the set values ​​in turn. If one of the values ​​of the vacuum degree, power, temperature, evaporation source pressure, flow rate, liquid level and oscillation of the vacuum coating machine is not within the initially set range, and the error with the set value is greater than 5%, an early warning message is sent to the data interaction module.

[0036] As a preferred technical solution of the present invention, the expressions of the vacuum degree and oscillation of the vacuum coating machine are as follows:

[0037] Vacuum degree:

[0038]

[0039] Shock situation:

[0040]

[0041] in, Indicates the vacuum degree, Indicates the initial vacuum degree, Indicates the number of valid sites. represents the effective volume, Indicates the processing time, Indicates the vibration situation. Indicates the duration of the oscillation exceeding the threshold. Indicates the total processing time.

[0042] The present invention also provides a method for adaptively adjusting operating parameters of a vacuum coating machine, comprising the following steps:

[0043] S1. Collect various parameters of the vacuum coating machine in the historical coating process through the historical data collection unit in the data collection module, and send the collected parameters to the control strategy generation module;

[0044] S2. The control strategy generation module analyzes the main operating parameters of the vacuum coating machine in combination with the historical data collection unit, and determines the important parameters, constructs the operation model of the vacuum coating machine with the important parameters, sets the output conditions, and obtains the optimal set of important parameters, and outputs the specific indicators of each parameter to the data interaction module, and performs vacuum coating with these parameters;

[0045] S3, then collect the data of the real-time coating process of the vacuum coating machine through the real-time data collection unit in the data collection module, and send the real-time data collection unit to the real-time monitoring and analysis module;

[0046] S4, the real-time monitoring and analysis module sends abnormal data to the data interaction module for early warning;

[0047] S5. The staff changes the output conditions in the control strategy generation module through the data interaction module.

[0048] Compared with the prior art, the present invention provides a method and system for adaptively adjusting the operating parameters of a vacuum coating machine, which has the following beneficial effects:

[0049] 1. The present invention uses a control strategy generation module to analyze the main operating parameters of the vacuum coating machine in combination with a historical data collection unit, and determines important parameters. The operation model of the vacuum coating machine is constructed with the important parameters, and output conditions are set to obtain the optimal set of important parameters, as well as the specific indicators of each parameter, which are output to the data interaction module. Vacuum coating is performed using these parameters, thereby ensuring the uniformity of vacuum coating parameters and the relatively stable coating quality of all products.

[0050] 2. The present invention collects the vacuum degree, power, temperature, evaporation source pressure, flow, liquid level and oscillation of the vacuum coating machine during the coating process according to the control strategy generation module through the real-time monitoring and analysis module, and sends the abnormal data to the data interaction module for early warning, thereby effectively judging the situation of the vacuum coating machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a schematic diagram of the system framework of the present invention;

[0052] Figure 2 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0054] See also Figure 1 , Figure 2 ,The present invention provides the following technical solutions: an adaptive adjustment system for operating parameters of a vacuum coating machine, comprising a data collection module, a control strategy generation module, a real-time monitoring and analysis module and a data interaction module;

[0055] The data collection module is used to collect the operating parameters of the vacuum coating machine. The data collection module includes a historical data collection unit and a real-time data collection unit. The historical data collection unit is used to collect various parameters of the vacuum coating machine in the historical coating process and send the collected parameters to the control strategy generation module. The real-time data collection unit is used to collect data in the real-time coating process of the vacuum coating machine, and the real-time data collection unit sends the data to the real-time monitoring and analysis module;

[0056] The control strategy generation module is used to analyze the main operating parameters of the vacuum coating machine in combination with the historical data collection unit, and determine the important parameters, build the operation model of the vacuum coating machine with the important parameters, set the output conditions, and obtain the optimal set of important parameters, as well as the specific indicators of each parameter, and output them to the data interaction module, and perform vacuum coating with these parameters;

[0057] The real-time monitoring and analysis module is used to collect the operating parameters of the vacuum coating machine during the coating process according to the control strategy generation module, and send abnormal data to the data interaction module for early warning;

[0058] The data interaction module includes a collection of important parameters output by the control strategy generation module as execution conditions to operate the vacuum coating machine. At the same time, the staff changes the output conditions in the control strategy generation module through the data interaction module to use different production parameters for different products. The data interaction module also includes feedback of early warning conditions in the real-time monitoring and analysis module to the staff, reminding them to inspect and maintain the vacuum coating machine.

[0059] The historical data collection unit collects the operating parameters of the vacuum coating machine and constructs the operating parameter set of the vacuum coating machine. , the specific expression is as follows:

[0060]

[0061] in, Respectively The control strategy generation module reads the operating parameter set of the vacuum coating machine. , and the specific steps for generating the control strategy are as follows:

[0062] A1. Use principal component analysis to analyze the vacuum coating machine operating parameter set After the analysis is completed, select the top ranking data, conduct secondary analysis, and select the top data as important parameters and The data constitutes the important parameter data set ;

[0063] The specific process is:

[0064] A1.1. Set the operating parameters of the vacuum coating machine Calculate the mean of each parameter in the data and remove the mean of each element;

[0065] A1.2. Calculate the eigenvalues ​​and corresponding eigenvectors of the covariance matrix;

[0066] A1.3. Before selection The parameters corresponding to the characteristic values ​​are calculated one by one. Remove Parameters other than eigenvalues ​​and The similarity between the parameters corresponding to the eigenvalues ​​is expressed as follows:

[0067]

[0068] in, Represents the operating parameter set of the vacuum coating machine Remove Parameters other than eigenvalues ​​and The similarity between the kth parameters in the eigenvalues, Represents the operating parameter set of the vacuum coating machine Remove The i-th parameter other than the eigenvalue, represents the modulo operation, express The kth parameter among the parameters corresponding to the eigenvalues;

[0069] A1.4. Similarity of the i-th parameter After the calculation is completed, it is divided into the class with the highest similarity, and steps A1.3-A1.4 are performed on all parameters in turn until all parameters are divided and obtained. Each data corresponds to a group;

[0070] A1.5. Selection The data corresponding to the group ranking data as important parameters ( ), and this The data constitutes the important parameter data set ,

[0071] Important parameter data sets The specific expression is as follows:

[0072]

[0073] in, Respectively Different important parameters;

[0074] A2. Based on important parameter data sets Establish the optimal parameter model;

[0075] The specific expression of the optimal parameter model established in step A2 is as follows:

[0076]

[0077] in, Respectively represent 1~m different important parameters, represents the balance coefficient, Respectively represent the weights corresponding to 1~m different important parameters, Express The optimal parameter model, Indicates output targets, e.g. when overall processing energy consumption needs to be prioritized Specifically , when overall utilization and efficiency are prioritized, Specifically , so the When giving priority to the overall processing energy consumption, the specific energy consumption value of the corresponding parameters of energy consumption is given, giving priority to the overall utilization rate and efficiency They represent utilization rate and processing efficiency respectively;

[0078] A3. Solve the optimal parameter model established in step A2 to obtain a set of optimal parameters.

[0079] At the same time, the real-time monitoring and analysis module compares the vacuum degree, power, temperature, evaporation source pressure, flow rate, liquid level and oscillation of the vacuum coating machine with the set values ​​in turn. If any of the values ​​of the vacuum degree, power, temperature, evaporation source pressure, flow rate, liquid level and oscillation of the vacuum coating machine is not within the initial set range, and the error with the set value is greater than 5%, an early warning message is sent to the data interaction module.

[0080] Based on the above process, the expressions of vacuum degree and oscillation of the vacuum coating machine are as follows:

[0081] Vacuum degree:

[0082]

[0083] Shock situation:

[0084]

[0085] in, Indicates the vacuum degree, Indicates the initial vacuum degree, Indicates the number of valid sites. represents the effective volume, Indicates the processing time, Indicates the vibration situation. Indicates the duration of the oscillation exceeding the threshold. Indicates the total processing time.

[0086] The present invention also provides a method for adaptively adjusting operating parameters of a vacuum coating machine, comprising the following steps:

[0087] S1. Collect various parameters of the vacuum coating machine in the historical coating process through the historical data collection unit in the data collection module, and send the collected parameters to the control strategy generation module;

[0088] S2. The control strategy generation module is used to analyze the main operating parameters of the vacuum coating machine in combination with the historical data collection unit, and determine the important parameters, build the operation model of the vacuum coating machine with the important parameters, set the output conditions, and obtain the optimal set of important parameters, and output the specific indicators of each parameter to the data interaction module, and perform vacuum coating with this parameter;

[0089] S3, then collect the data of the real-time coating process of the vacuum coating machine through the real-time data collection unit in the data collection module, and send the real-time data collection unit to the real-time monitoring and analysis module;

[0090] S4, the real-time monitoring and analysis module sends abnormal data to the data interaction module for early warning;

[0091] S5. The staff changes the output conditions in the control strategy generation module through the data interaction module;

[0092] For example, when overall processing energy consumption needs to be prioritized Specifically , when overall utilization and efficiency are prioritized, Specifically .

[0093] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An adaptive adjustment system for operating parameters of a vacuum coating machine, characterized in that: It includes data collection module, control strategy generation module, real-time monitoring and analysis module and data interaction module; The data collection module is used to collect the operating parameters of the vacuum coating machine. The data collection module includes a historical data collection unit and a real-time data collection unit. The historical data collection unit is used to collect various parameters of the vacuum coating machine in the historical coating process and send the collected parameters to the control strategy generation module. The real-time data collection unit is used to collect data in the real-time coating process of the vacuum coating machine, and the real-time data collection unit sends the data to the real-time monitoring and analysis module. The historical data collection unit collects the operating parameters of the vacuum coating machine and constructs the operating parameter set X of the vacuum coating machine. The specific expression is as follows: X=[X1,X2,…,X i ,…,X n ] Among them, X1, X2, …, X i ,…,X n Respectively represent the operating parameters of 1 to n different vacuum coating machines; The control strategy generation module is used to analyze the main operating parameters of the vacuum coating machine in combination with the historical data collection unit, and determine the important parameters, build an operating model of the vacuum coating machine with the important parameters, set output conditions, and obtain the optimal set of important parameters, as well as the specific indicators of each parameter to output to the data interaction module, and perform vacuum coating with this parameter; The control strategy generation module reads the vacuum coating machine operating parameter set X and generates a control strategy in the following specific steps: A1. Use the principal component analysis method to analyze the vacuum coating machine operating parameter set X. After the analysis is completed, select the top K data after the analysis is completed, perform secondary analysis, and select the top m data after the secondary analysis as important parameters, and these m data constitute the important parameter data set X. m ; A2. Based on important parameter data set X m Establish the optimal parameter model; A3. Solve the optimal parameter model established in step A2 to obtain a set of optimal parameters; the real-time monitoring and analysis module is used to collect the operating parameters of the vacuum coating machine during the coating process according to the control strategy generation module, and send abnormal data to the data interaction module for early warning; The data interaction module includes a collection of important parameters output by the control strategy generation module as execution conditions to operate the vacuum coating machine. At the same time, the staff changes the output conditions in the control strategy generation module through the data interaction module to use different production parameters for different products. The data interaction module also includes feedback of the early warning conditions in the real-time monitoring and analysis module to the staff, reminding the staff to inspect and maintain the vacuum coating machine.

2. The self-adaptive adjustment system for operating parameters of a vacuum coating machine according to claim 1, characterized in that: In step A1, the principal component analysis method is used to analyze the vacuum coating machine operating parameter set X. After the analysis is completed, the top K data are selected for secondary analysis, and the top m data after the secondary analysis are selected as important parameters, and these m data constitute the important parameter data set X. m The specific steps are as follows: A1.

1. Calculate the mean of each parameter in the data of the vacuum coating machine operating parameter set X, and remove the mean of each element; A1.

2. Calculate the eigenvalues ​​and corresponding eigenvectors of the covariance matrix; A1.

3. Select the parameters corresponding to the first K eigenvalues, and calculate the similarity between the parameters in the vacuum coating machine operating parameter set X excluding the K eigenvalues ​​and the parameters corresponding to the K eigenvalues ​​one by one. The specific expression is as follows: Among them, R i / K→k represents the similarity between the parameters other than K eigenvalues ​​in the vacuum coating machine operating parameter set X and the kth parameter in the K eigenvalues, X i / K represents the i-th parameter in the vacuum coating machine operating parameter set X except for K eigenvalues, |*| represents the modular operation, X k Represents the kth parameter among the parameters corresponding to K eigenvalues; A1.

4. Similarity R of the i-th parameter i / K→k After the calculation is completed, it is divided into a class with the highest similarity, and steps A1.3-A1.4 are performed on all parameters in turn until all parameters are divided and K data corresponding groups are obtained; A1.

5. Select the top m data of the corresponding group from K data as important parameters, where K ≥ m, and use these m data to form the important parameter data set X. m .

3. The self-adaptive adjustment system for operating parameters of a vacuum coating machine according to claim 2, characterized in that: The important parameter data set X m The specific expression is as follows: X m =[x1,x2,…,x j ,...,x m ] Among them, x1,x2,…,x j ,…,x m They represent 1 to m different important parameters respectively.

4. The self-adaptive adjustment system for operating parameters of a vacuum coating machine according to claim 3, characterized in that: The specific expression of the optimal parameter model established in step A2 is as follows: f(Y)=α0+α1x1+α2x2+…+α j x j +…+a m x m Among them, x1,x2,…,x j ,…,x m They represent 1 to m different important parameters respectively, α0 represents the balance coefficient, α1, α2, … α j ,…,α m They represent the weights corresponding to 1 to m different important parameters respectively, f(Y) represents the optimal parameter model for Y, and Y represents the output target.

5. The self-adaptive adjustment system for operating parameters of a vacuum coating machine according to claim 4, characterized in that: The real-time monitoring and analysis module includes monitoring the vacuum degree, power, temperature, evaporation source pressure, flow, liquid level and oscillation of the vacuum coating machine.

6. The self-adaptive adjustment system for operating parameters of a vacuum coating machine according to claim 5, characterized in that: The real-time monitoring and analysis module compares the vacuum degree, power, temperature, evaporation source pressure, flow rate, liquid level and oscillation of the vacuum coating machine with the set values ​​in turn. If any of the values ​​of the vacuum degree, power, temperature, evaporation source pressure, flow rate, liquid level and oscillation of the vacuum coating machine is not within the initially set range, and the error with the set value is greater than 5%, an early warning message is sent to the data interaction module.

7. The self-adaptive adjustment system for operating parameters of a vacuum coating machine according to claim 6, characterized in that: The expressions of the vacuum degree and oscillation of the vacuum coating machine are as follows: Vacuum degree: Shock situation: Among them, P represents the vacuum degree, P0 represents the initial vacuum degree, S represents the number of effective stations, V represents the effective volume, t represents the processing time, ZD represents the oscillation situation, DD represents the duration of the oscillation exceeding the threshold, and JGS represents the total processing time.

8. A method for adaptively adjusting operating parameters of a vacuum coating machine, based on a system for adaptively adjusting operating parameters of a vacuum coating machine according to any one of claims 1 to 7, characterized in that: The following steps are involved: S1. Collect various parameters of the vacuum coating machine in the historical coating process through the historical data collection unit in the data collection module, and send the collected parameters to the control strategy generation module; S2. The control strategy generation module is used to analyze the main operating parameters of the vacuum coating machine in combination with the historical data collection unit, and determine the important parameters, build the operation model of the vacuum coating machine with the important parameters, set the output conditions, and obtain the optimal set of important parameters, and output the specific indicators of each parameter to the data interaction module, and perform vacuum coating with this parameter; S3, then collect the data of the real-time coating process of the vacuum coating machine through the real-time data collection unit in the data collection module, and send the real-time data collection unit to the real-time monitoring and analysis module; S4, the real-time monitoring and analysis module sends abnormal data to the data interaction module for early warning; S5. The staff changes the output conditions in the control strategy generation module through the data interaction module.

Images