CN115793437A - Efficient drying method and system for chemical wet cleaning - Google Patents
Efficient drying method and system for chemical wet cleaning Download PDFInfo
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Abstract
The invention discloses a high-efficiency drying method and a high-efficiency drying system for chemical wet cleaning, which relate to the field of drying control, wherein the method comprises the following steps: generating an optical element surface image acquisition result; generating characteristic parameters of the residual liquid; uploading a drying control parameter set according to the wind power drying equipment; sending the drying control parameter set to a drying control module to generate a drying control parameter optimization vector space; inputting the distribution position characteristics of the residual liquid and the geometric characteristics of the residual liquid into a drying control parameter optimization vector space to generate a drying control parameter optimization result; sending the feedback information to a display interface of the control terminal to generate first feedback information; and conveying the optical element to be dried to a preset drying area of the wind power drying device according to the confirmed drying instruction. The method achieves the technical effects of improving the accuracy of the drying control parameters of the optical element cleaned by the chemical wet method, improving the drying control quality of the optical element cleaned by the chemical wet method and the like.
Description
Technical Field
The invention relates to the field of drying control, in particular to a high-efficiency drying method and a high-efficiency drying system for chemical wet cleaning.
Background
Wet chemical cleaning has been widely used in semiconductor production, optical element protection, and other fields. The chemical wet cleaning is a powerful means for removing pollutants such as micro-dust, particles, impurities and the like on the surface of the optical element. After chemical wet cleaning of optical elements, it is often necessary to dry the optical elements, and in this case, if drying is not properly controlled, irreversible damage often occurs to the optical elements. With the wide application of chemical wet cleaning, people pay attention to how to effectively control the drying of optical elements after chemical wet cleaning.
In the prior art, the technical problem that the drying control effect of the optical element cleaned by the chemical wet method is poor due to the fact that the accuracy of the drying control parameter of the optical element cleaned by the chemical wet method is not high exists.
Disclosure of Invention
The application provides a high-efficiency drying method and a high-efficiency drying system for chemical wet cleaning. The technical problem that in the prior art, the accuracy of the drying control parameters of the optical element cleaned by the chemical wet method is not high, and the drying control effect of the optical element cleaned by the chemical wet method is poor is solved.
In view of the above problems, the present application provides a high-efficiency drying method and system for chemical wet cleaning.
In a first aspect, the present application provides a high efficiency drying method for chemical wet cleaning, wherein the method is applied to a high efficiency drying system for chemical wet cleaning, and the method includes: calling an image acquisition device to acquire an image of an optical element to be dried, which is cleaned by a chemical wet method, so as to generate an optical element surface image acquisition result; performing feature extraction on the surface image acquisition result of the optical element to generate residual liquid feature parameters, wherein the residual liquid feature parameters comprise residual liquid distribution position features and residual liquid geometric features; uploading a drying control parameter set according to the wind power drying equipment; sending the drying control parameter set to a drying control module to generate a drying control parameter optimization vector space; inputting the residual liquid distribution position characteristics and the residual liquid geometric characteristics into the drying control parameter optimization vector space to generate a drying control parameter optimization result; sending the drying control parameter optimization result to a display interface of a control terminal to generate first feedback information, wherein the first feedback information comprises a drying confirmation instruction; and conveying the optical element to be dried to a preset drying area of the wind power drying equipment according to the drying confirmation instruction.
In a second aspect, the present application further provides a high efficiency drying system for chemical wet cleaning, wherein the system comprises: the image acquisition module is used for calling the image acquisition device to acquire an image of the optical element to be dried, which is cleaned by the chemical wet method, so as to generate an image acquisition result of the surface of the optical element; the characteristic extraction module is used for carrying out characteristic extraction on the surface image acquisition result of the optical element to generate residual liquid characteristic parameters, wherein the residual liquid characteristic parameters comprise residual liquid distribution position characteristics and residual liquid geometric characteristics; the drying control parameter uploading module is used for uploading a drying control parameter set according to the wind power drying equipment; the optimized space generation module is used for sending the drying control parameter set to the drying control module to generate a drying control parameter optimized vector space; the optimization result generation module is used for inputting the residual liquid distribution position characteristics and the residual liquid geometric characteristics into the drying control parameter optimization vector space to generate a drying control parameter optimization result; the feedback generation module is used for sending the drying control parameter optimization result to a display interface of a control terminal to generate first feedback information, wherein the first feedback information comprises a drying confirmation instruction; and the conveying module is used for conveying the optical element to be dried to a preset drying area of the wind power drying equipment according to the drying confirmation instruction.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
carrying out image acquisition on the optical element to be dried which is cleaned by the chemical wet method through an image acquisition device to generate an optical element surface image acquisition result; performing feature extraction on the surface image acquisition result of the optical element to generate a residual liquid feature parameter; uploading a drying control parameter set according to the wind power drying equipment; sending the data to a drying control module to generate a drying control parameter optimization vector space; inputting the distribution position characteristics of the residual liquid and the geometric characteristics of the residual liquid into the drying control parameter optimization vector space to generate a drying control parameter optimization result; sending the drying control parameter optimization result to a display interface of a control terminal to generate first feedback information; and conveying the optical element to be dried to a preset drying area of the wind power drying device according to the confirmed drying instruction. The accuracy of the drying control parameters of the optical element cleaned by the chemical wet method is improved, and the drying control quality of the optical element cleaned by the chemical wet method is improved; meanwhile, the optical element cleaned by the chemical wet method is efficiently, accurately and reliably dried and controlled, and the technical effect of reducing the damage to the optical element cleaned by the chemical wet method due to improper drying control is achieved.
Drawings
FIG. 1 is a schematic flow diagram of a high efficiency drying method for chemical wet cleaning in accordance with the present application;
FIG. 2 is a schematic flow chart of an uploading drying control parameter set in a high-efficiency drying method for chemical wet cleaning according to the present application;
fig. 3 is a schematic structural diagram of a high-efficiency drying system for chemical wet cleaning according to the present application.
Description of reference numerals: the system comprises an image acquisition module 11, a feature extraction module 12, a drying control parameter uploading module 13, an optimization space generation module 14, an optimization result generation module 15, a feedback generation module 16 and a conveying module 17.
Detailed Description
The application provides an efficient drying method and system for chemical wet cleaning. The technical problem that in the prior art, the accuracy of drying control parameters of the optical element cleaned by the chemical wet method is not high, and therefore the drying control effect of the optical element cleaned by the chemical wet method is poor is solved. The accuracy of the drying control parameters of the optical element cleaned by the chemical wet method is improved, and the drying control quality of the optical element cleaned by the chemical wet method is improved; meanwhile, the optical element cleaned by the chemical wet method is efficiently, accurately and reliably dried and controlled, and the technical effect of reducing the damage to the optical element cleaned by the chemical wet method due to improper drying control is achieved.
Example one
Referring to fig. 1, the present application provides a high efficiency drying method for chemical wet cleaning, wherein the method is applied to a high efficiency drying system for chemical wet cleaning, the system includes a drying control module, the drying control module is communicatively connected to a wind power drying device, the system is communicatively connected to an image capturing device, and the method specifically includes the following steps:
step S100: calling an image acquisition device to acquire an image of an optical element to be dried, which is cleaned by a chemical wet method, so as to generate an optical element surface image acquisition result;
step S200: performing feature extraction on the surface image acquisition result of the optical element to generate residual liquid feature parameters, wherein the residual liquid feature parameters comprise residual liquid distribution position features and residual liquid geometric features;
specifically, the image acquisition device is used for acquiring an image of the optical element to be dried after the optical element is cleaned by the chemical wet method, so that an image acquisition result of the surface of the optical element is obtained, and the characteristic extraction is carried out on the image acquisition result, so that the characteristic parameter of the residual liquid is obtained. Wherein, the image acquisition device is in communication connection with the high-efficiency drying system for chemical wet cleaning. The image capturing device may be any type of camera device capable of capturing the acquired image information or a combination thereof. The chemical wet cleaning method is used for effectively removing pollutants such as micro dust, particles, impurities and the like on the surface of a device by using a chemical solution on the premise of not damaging the characteristics of the device. The optical element to be dried may be any optical element after completion of the chemical wet cleaning. For example, when manufacturing lenses, contaminants such as particles, fingerprints, etc. are often attached to the lens surface. After the lens is chemically wet-cleaned, it can be used as an optical element to be dried. And the optical element surface image acquisition result comprises image data information corresponding to the optical element to be dried which is cleaned by the chemical wet method. The residual liquid characteristic parameters comprise residual liquid distribution position characteristics and residual liquid geometric characteristics. The residual liquid distribution position characteristics comprise position information of residual liquid of the optical element to be dried in the surface image acquisition result of the optical element. The geometric characteristics of the residual liquid comprise geometric characteristic parameter information such as the shape, the size, the area and the like of the residual liquid of the optical element to be dried in the surface image acquisition result of the optical element. Illustratively, when feature extraction is performed on the optical element surface image acquisition result, a historical optical element surface image acquisition result can be acquired, the historical optical element surface image acquisition result is trained to be in a convergence state based on a neural network, a residual liquid feature recognition model is obtained, the optical element surface image acquisition result is used as input information, and the residual liquid feature parameter can be obtained by inputting the residual liquid feature recognition model. The technical effects that the image acquisition device acquires the image of the optical element to be dried to obtain the surface image acquisition result of the optical element, extracts the characteristics of the surface image acquisition result to determine the characteristic parameters of the residual liquid and lays a foundation for the subsequent drying control of the optical element to be dried are achieved.
Step S300: uploading a drying control parameter set according to the wind power drying equipment;
further, as shown in fig. 2, step S300 of the present application further includes:
step S310: uploading optical element control parameters according to the wind power drying equipment, wherein the optical element control parameters comprise optical element positioning point parameters and optical element posture positioning parameters;
step S320: uploading drying environment control parameters according to the wind power drying equipment, wherein the drying environment control parameters comprise a drying environment temperature parameter and a drying environment humidity parameter;
step S330: uploading drying wind power control parameters according to the wind power drying equipment, wherein the drying wind power control parameters comprise a blowing temperature parameter, a blowing vector parameter, a gas flow parameter, a blowing time parameter and a cycle period parameter;
step S340: adding the optical element positioning point parameter, the optical element attitude positioning parameter, the drying environment temperature parameter, the drying environment humidity parameter, the blowing temperature parameter, the blowing vector parameter, the gas flow parameter, the blowing duration parameter and the cycle period parameter into the drying control parameter set.
Specifically, based on the wind power drying equipment, the optical element control parameters, the drying environment control parameters and the drying wind power control parameters are uploaded to obtain a drying control parameter set. The wind drying equipment can be a wind drying device such as a wind dryer, a wind dryer and the like in the prior art. The drying control parameter set comprises optical element control parameters, drying environment control parameters and drying wind power control parameters. The optical element control parameters comprise optical element positioning point parameters and optical element posture positioning parameters. The drying environment control parameters comprise a drying environment temperature parameter and a drying environment humidity parameter. The drying wind power control parameters comprise blowing temperature parameters, blowing vector parameters, gas flow parameters, blowing duration parameters and cycle period parameters. The optical element positioning point parameters comprise position data information of the optical element to be dried. The optical element posture positioning parameters comprise placing mode data information of the optical element to be dried. The drying environment temperature parameter comprises environment temperature data information corresponding to the optical element to be dried. The drying environment humidity parameter comprises environment humidity data information corresponding to the optical element to be dried. The blowing temperature parameters comprise a plurality of blowing temperature data information for carrying out wind power drying on the optical element to be dried by using the wind power drying equipment. The blowing vector parameters comprise a plurality of blowing sizes, a plurality of blowing directions and a plurality of blowing position data information for carrying out wind power drying on the optical element to be dried by using wind power drying equipment. The gas flow parameters comprise a plurality of gas flow rates and a plurality of gas flows for performing wind drying on the optical element to be dried by using the wind drying equipment. The blowing time length parameter comprises a plurality of blowing time length information corresponding to a plurality of blowing positions for carrying out wind power drying on the optical element to be dried by using wind power drying equipment. The cycle period parameter comprises cycle time information between a plurality of blowing positions for wind drying the optical element to be dried by using the wind drying equipment. The technical effects of determining the drying control parameter set and providing data support for the subsequent generation of the drying control parameter optimization vector space are achieved.
Step S400: sending the drying control parameter set to a drying control module to generate a drying control parameter optimization vector space;
further, step S400 of the present application further includes:
step S410: matching a wind power drying record data set based on big data according to the wind power drying equipment and the drying control parameter set, wherein the wind power drying record data set comprises residual liquid distribution position record data, residual liquid geometric characteristic record data and drying control parameter record data;
step S420: performing cluster analysis on the drying control parameter record data according to the residual liquid distribution position record data and the residual liquid geometric characteristic record data to generate a plurality of groups of drying control parameter cluster results;
specifically, the obtained set of drying control parameters is transmitted to the drying control module. And then, acquiring a wind power drying record data set through big data query based on the wind power drying equipment. And further, performing cluster analysis on the drying control parameter recorded data according to the residual liquid distribution position recorded data and the residual liquid geometric characteristic recorded data to obtain a plurality of groups of drying control parameter cluster results. Wherein, the drying control module is included in the high-efficiency drying system for chemical wet cleaning. And the drying control module is in communication connection with the wind power drying equipment and is used for intelligently controlling the wind power drying equipment. The wind power drying record data set comprises residual liquid distribution position record data, residual liquid geometric characteristic record data and drying control parameter record data. The residual liquid distribution position recording data includes position data information of a plurality of historical residual liquids for drying the optical element by using the wind power drying equipment. The residual liquid geometric characteristic record data comprises historical geometric characteristic parameter information such as the shape, the size, the area and the like of a plurality of historical residual liquids for drying the optical element by using the wind power drying equipment. The drying control parameter recording data comprises corresponding historical optical element control parameters, historical drying environment control parameters and historical drying wind power control parameters of a plurality of historical residual liquids for drying the optical element by using the wind power drying equipment. In the cluster analysis, similar research objects are classified when facing more complex research objects, so that individuals in the same class have larger similarity and the difference between individuals in different classes is large. In the multiple groups of drying control parameter clustering results, the drying control parameter recording data of the same group of drying control parameter clustering results correspond to the same residual liquid distribution position recording data and residual liquid geometric characteristic recording data. The drying control parameter recording data of different groups of drying control parameter clustering results correspond to different residual liquid distribution position recording data and residual liquid geometric characteristic recording data. The method achieves the technical effects of performing cluster analysis on the drying control parameter recorded data according to the residual liquid distribution position recorded data and the residual liquid geometric characteristic recorded data, determining a plurality of groups of drying control parameter cluster results, and classifying the drying control parameter recorded data with the same residual liquid distribution position recorded data and residual liquid geometric characteristic recorded data into one type, thereby improving the efficiency of drying control on the optical element cleaned by the chemical wet method and laying a foundation for efficient drying control on the optical element cleaned by the large-scale chemical wet method.
Step S430: and constructing the drying control parameter optimization vector space according to the clustering results of the multiple groups of drying control parameters.
Further, step S430 of the present application further includes:
step S431: according to the multiple groups of drying control parameter clustering results, obtaining a first group of drying control parameter clustering results, a second group of drying control parameter clustering results till an Mth group of drying control parameter clustering results;
step S432: constructing a first scene optimization vector subspace according to the first group of drying control parameter clustering results;
step S433: constructing an Mth scene optimization vector subspace according to the Mth group of drying control parameter clustering results;
specifically, a first group of drying control parameter clustering results and a second group of drying control parameter clustering results … … and an Mth group of drying control parameter clustering results are extracted from the obtained multiple groups of drying control parameter clustering results, and based on the results, a first scene optimization vector subspace and a second scene optimization vector subspace are constructed, wherein the first scene optimization vector subspace and the second scene optimization vector subspace are … … and the Mth scene optimization vector subspace. The first scene optimization vector subspace is a data storage space corresponding to the first group of drying control parameter clustering results, and the first scene optimization vector subspace comprises the first group of drying control parameter clustering results. The second scene optimization vector quantum space is a data storage space corresponding to the second group of drying control parameter clustering results, and the second scene optimization vector quantum space comprises the second group of drying control parameter clustering results. And the Mth scene optimization vector subspace is a data storage space corresponding to the Mth group of drying control parameter clustering results, and the Mth scene optimization vector subspace comprises the Mth group of drying control parameter clustering results. The technical effects of determining the first scene optimization vector subspace and the second scene optimization vector subspace … … Mth scene optimization vector subspace and generating a compaction basis for the drying control parameter optimization vector space subsequently are achieved.
Step S434: and combining the first scene optimization vector subspace, the second scene optimization vector subspace and the Mth scene optimization vector subspace to generate the drying control parameter optimization vector space.
Further, step S434 of the present application further includes:
step S4341: limiting the drying control parameter set according to the optical element to be dried to generate a drying control parameter sensitive characteristic value;
step S4342: adding the drying control parameter sensitive characteristic value into a first tabu sublist of a tabu table, wherein data in the tabu table are forbidden to be selected for optimization design;
step S4343: constructing a second tabu table of the tabu table, wherein an initial value of the second tabu table is null;
specifically, the efficient drying system for chemical wet cleaning is used for inquiring the sensitive characteristic value of the optical element to be dried to obtain the sensitive characteristic value of the drying control parameter, adding the sensitive characteristic value to a first tabu list of a tabu list and then constructing a second tabu list of the tabu list. Wherein the drying control parameter sensitive characteristic value comprises a plurality of sensitive characteristic values of the optical element to be dried. Illustratively, the obtained drying control parameter sensitive characteristic value includes a certain blowing temperature parameter when the optical element to be dried has a performance change at the blowing temperature parameter. The maximum blowing time parameter of the optical element to be dried is a, and the obtained sensitive characteristic value of the drying control parameter comprises the maximum blowing time parameter a. The tabu table comprises a first tabu sub-table and a second tabu sub-table. And the data in the tabu table is prohibited from being selected for optimal design. The first tabu table includes drying control parameter sensitive characteristic values. The initial value of the second tabu table is null. The technical effects of determining the first tabu sub-table and the second tabu sub-table and improving the accuracy and reliability of limiting the scene optimization to the quantum space in the follow-up process are achieved.
Step S4344: and limiting the first scene optimization vector subspace, the second scene optimization vector subspace and the Mth scene optimization vector subspace according to the first tabu sub table and the second tabu sub table to generate the drying control parameter optimization vector space.
Further, step S4344 of the present application further includes:
step S43441: sending the drying control parameter set to a display interface of the control terminal to obtain second feedback information, wherein the second feedback information comprises a value constraint interval of the drying control parameter set;
step S43442: constructing a screening fitness function:
wherein, P k Characterizing the fitness of the kth set of control parameters, f k Characterizing the selection frequency, C, of the kth set of control parameters in the recorded data k0 Characterizing the initial residual fluid geometric characteristic value, C k1 Characterizing kth set of control parametersGeometric characteristic values of the dried residual liquid, wherein alpha and beta are weight indexes, and alpha + beta =1;
step S43443: and limiting the first scene optimization vector quantum space, the second scene optimization vector quantum space and the Mth scene optimization vector quantum space according to the screening fitness function and the drying control parameter set value constraint interval to generate the drying control parameter optimization vector space.
Specifically, the obtained drying control parameter set is sent to a display interface of the control terminal, and second feedback information is obtained. Further, the first scene optimization vector subspace and the second scene optimization vector subspace are limited according to the screening fitness function and the drying control parameter set value constraint interval in the second feedback information, and the Mth scene optimization vector subspace of the second scene optimization vector space … … is limited to generate a drying control parameter optimization vector space. And the second feedback information comprises a drying control parameter set value constraint interval. For example, the drying control parameter set may be transmitted to the control terminal, and the expert group of the control terminal limits the parameter value range of the drying control parameter set, so as to obtain the value constraint interval of the drying control parameter set. The control terminal is in communication connection with the efficient drying system for chemical wet cleaning, and has the functions of intelligently controlling the drying of the optical element to be dried, receiving and processing information and the like. The drying control parameter optimization vector space comprises a scene optimization vector subspace corresponding to the drying control parameter set value-taking constraint interval in a first scene optimization vector subspace, a second scene optimization vector subspace … … Mth scene optimization vector subspace, and a selected frequency characteristic value, an initial residual liquid geometric characteristic value and a dried residual liquid geometric characteristic value corresponding to the scene optimization vector subspace. In screening the fitness function, f k The frequency of selection in the recorded data for the k-th set of preset control parameters. C k0 For a preset initial residual liquid geometric characteristic value, C k1 And the preset kth set of control parameters are geometric characteristic values of the residual liquid after drying, alpha and beta are preset weight indexes, and alpha + beta =1. Achieves the purpose of being suitable for screeningThe stress function and the drying control parameter set value constraint interval limit a first scene optimization vector subspace and a second scene optimization vector subspace … … Mth scene optimization vector subspace, so that a reliable and reasonable drying control parameter optimization vector space is obtained, and the accuracy of the obtained drying control parameter optimization result is improved; meanwhile, powerful support is provided for obtaining a large-scale drying control parameter optimization result, and therefore the technical effect of improving the efficiency of drying control of the optical element is achieved.
Step S500: inputting the residual liquid distribution position characteristics and the residual liquid geometric characteristics into the drying control parameter optimization vector space to generate a drying control parameter optimization result;
further, step S500 of the present application further includes:
step S510: inputting the residual liquid distribution position characteristics and the residual liquid geometric characteristics into the drying control parameter optimization vector space, and activating an m-th scene optimization vector subspace;
step S520: randomly taking values from the drying control parameter set value-taking constraint interval to generate a k control parameter selection result;
step S530: inputting the k-th control parameter selection result into the m-th scene optimization vector subspace to match and select a frequency characteristic value, an initial residual liquid geometric characteristic value and a dried residual liquid geometric characteristic value;
step S540: inputting the selected frequency characteristic value, the initial residual liquid geometric characteristic value and the dried residual liquid geometric characteristic value into the screening fitness function to obtain a kth fitness;
step S550: acquiring a k-1 fitness, and judging whether the k fitness is greater than or equal to the k-1 fitness;
step S560: if the k-1 control parameter is larger than or equal to the k-1 control parameter, adding a k-1 control parameter selection result into an eliminated data set, and continuing iteration on the basis of the k-th fitness;
step S570: and when the first preset iteration number is met, generating a drying control parameter optimization result.
Specifically, the obtained residual liquid distribution position characteristics and the obtained residual liquid geometric characteristics are used as input information, a drying control parameter optimization vector space is input, and an m-th scene optimization vector subspace is activated. Further, a k control parameter selection result is obtained by randomly taking values of the drying control parameter set value restriction interval. And then, inputting the k-th control parameter selection result as input information into the m-th scene optimization vector subspace to obtain a selected frequency characteristic value, an initial residual liquid geometric characteristic value and a dried residual liquid geometric characteristic value, and inputting the selected frequency characteristic value, the initial residual liquid geometric characteristic value and the dried residual liquid geometric characteristic value as input information into a screening fitness function to obtain the k-th fitness. And judging whether the kth fitness is greater than or equal to the kth-1 fitness, if the kth fitness is greater than or equal to the kth-1 fitness, adding a kth-1 control parameter selection result to the eliminated data set, continuing iteration according to the kth fitness, if the k value meets a first preset iteration number, directly taking the kth control parameter selection result corresponding to the kth fitness as a drying control parameter optimization result, and if the k value does not meet the first preset iteration number, continuing to perform iterative optimization according to the kth control parameter selection result.
And the mth scene optimization vector subspace is the scene optimization vector subspace with the closest residual liquid distribution position characteristic and residual liquid geometric characteristic in the drying control parameter optimization vector space. The kth control parameter selection result and the kth-1 control parameter selection result are all any drying control parameters in the drying control parameter set value constraint interval, and the kth control parameter selection result is different from the kth-1 control parameter selection result. The kth fitness is the same as the kth-1 fitness in an obtaining mode and is obtained by matching the selected frequency characteristic value, the initial residual liquid geometric characteristic value, the dried residual liquid geometric characteristic value and a screening fitness function. And the eliminated data set comprises a k-1 control parameter selection result corresponding to the k-1 fitness when the k-th fitness is greater than or equal to the k-1 fitness. The first preset iteration number is an iteration number of iteration convergence preset by the expert group. And the drying control parameter optimization result comprises a kth control parameter selection result corresponding to the kth fitness meeting the first preset iteration number. The technical effects of optimizing the vector space through the drying control parameters, obtaining the drying control parameter optimization result with higher accuracy and improving the accuracy and reliability of drying control on the optical element to be dried are achieved.
Further, step S550 of the present application further includes:
step S551: if the k-th fitness is smaller than the k-1 fitness, adding the k-th control parameter selection result into the elimination data set;
step S552: judging whether the k-1 fitness iteration winning number meets a second preset iteration number or not;
step S553: if yes, adding the result of the k-1 control parameter selection into the second tabu table, and continuing iteration;
step S554: when the storage time of the k-1 control parameter selection result in the second tabu table meets a third preset iteration number, taking the k-1 control parameter selection result out of the second tabu table, and continuing iteration, wherein the first preset iteration number is greater than the third preset iteration number and is greater than the second preset iteration number;
step S555: and when the first preset iteration number is met, generating a drying control parameter optimization result.
Specifically, when judging whether the k-th fitness is greater than or equal to the k-1-th fitness, if the k-th fitness is less than the k-1-th fitness, the k-th control parameter selection result is added to the eliminated data set. And further, judging whether the k-1 fitness iteration winning number meets a second preset iteration number, if so, adding a k-1 control parameter selection result into a second tabu table, and randomly taking a value from a drying control parameter set value restriction interval and carrying out iteration optimization. And then, when the iterative optimization times at the moment meet a third preset iterative times, namely the iterative optimization times after the k-1 control parameter selection result is added into the second tabu table meet the third preset iterative times, taking out the k-1 control parameter selection result from the second tabu table, and randomly taking values and iteratively optimizing from a drying control parameter set value restriction interval. And then, when the iterative optimization times at the moment meet first preset iterative times, namely the iterative optimization times after the k-1 control parameter selection result is taken out from the second tabu table meet the first preset iterative times, obtaining a drying control parameter optimization result. And the number of times of iteration winning of the k-1 th fitness is the number of times that the k fitness is smaller than the k-1 th fitness. The second preset iteration number and the third preset iteration number are determined by the self-adaptive setting of the efficient drying system for chemical wet cleaning. And the first preset iteration times are larger than the third preset iteration times and larger than the second preset iteration times. The technical effects of carrying out repeated iteration optimization when the k-th fitness is smaller than the k-1 th fitness, improving the accuracy of the optimization result of the drying control parameter and reducing the chance are achieved.
Step S600: sending the drying control parameter optimization result to a display interface of a control terminal to generate first feedback information, wherein the first feedback information comprises a drying confirmation instruction;
step S700: and conveying the optical element to be dried to a preset drying area of the wind power drying device according to the confirmed drying instruction.
Specifically, the obtained drying control parameter optimization result is sent to a display interface of the control terminal, at this time, whether the drying control parameter optimization result damages the optical element to be dried can be judged by a plurality of optical element experts, and when the judgment result is that the drying control parameter optimization result does not damage the optical element to be dried, first feedback information is obtained. And then, conveying the optical element to be dried to a preset drying area of the wind power drying equipment according to a drying confirmation instruction in the first feedback information, and performing drying control on the optical element to be dried according to a drying control parameter optimization result. Wherein the first feedback information comprises an acknowledge dry instruction. The drying confirmation instruction is instruction information for rechecking and confirming the drying control parameter optimization result. The preset drying area comprises area position information of the optical element to be dried, which corresponds to the optimization result of the drying control parameters, for drying control. The technical effects of performing efficient, accurate and reliable drying control on the optical element to be dried and improving the drying control quality of the optical element cleaned by the chemical wet method are achieved.
In summary, the efficient drying method for chemical wet cleaning provided by the present application has the following technical effects:
1. carrying out image acquisition on the optical element to be dried, which is cleaned by the chemical wet method, by using an image acquisition device to generate an image acquisition result on the surface of the optical element; performing feature extraction on the surface image acquisition result of the optical element to generate a residual liquid feature parameter; uploading a drying control parameter set according to the wind power drying equipment; sending the data to a drying control module to generate a drying control parameter optimization vector space; inputting the distribution position characteristics of the residual liquid and the geometric characteristics of the residual liquid into the drying control parameter optimization vector space to generate a drying control parameter optimization result; sending the drying control parameter optimization result to a display interface of a control terminal to generate first feedback information; and conveying the optical element to be dried to a preset drying area of the wind power drying device according to the confirmed drying instruction. The accuracy of the drying control parameters of the optical element cleaned by the chemical wet method is improved, and the drying control quality of the optical element cleaned by the chemical wet method is improved; meanwhile, the optical element cleaned by the chemical wet method is efficiently, accurately and reliably dried and controlled, and the technical effect of reducing the damage to the optical element cleaned by the chemical wet method due to improper drying control is achieved.
2. And performing cluster analysis on the drying control parameter recorded data according to the residual liquid distribution position recorded data and the residual liquid geometric characteristic recorded data, determining a plurality of groups of drying control parameter cluster results, and classifying the drying control parameter recorded data with the same residual liquid distribution position recorded data and residual liquid geometric characteristic recorded data into one class, so that the drying control efficiency of the optical element after chemical wet cleaning is improved, and a foundation is laid for efficient drying control of the optical element after large-scale chemical wet cleaning.
Example two
Based on the same inventive concept as the efficient drying method for chemical wet cleaning in the foregoing embodiment, the present invention further provides an efficient drying system for chemical wet cleaning, referring to fig. 3, where the system includes:
the image acquisition module 11 is used for calling the image acquisition device to acquire an image of the optical element to be dried, which is cleaned by the chemical wet method, and generating an image acquisition result of the surface of the optical element;
the characteristic extraction module 12 is configured to perform characteristic extraction on the optical element surface image acquisition result to generate residual liquid characteristic parameters, where the residual liquid characteristic parameters include residual liquid distribution position characteristics and residual liquid geometric characteristics;
the drying control parameter uploading module 13 is used for uploading a drying control parameter set according to the wind drying equipment by the drying control parameter uploading module 13;
the optimized space generation module 14 is configured to send the drying control parameter set to a drying control module, and generate a drying control parameter optimized vector space;
an optimization result generating module 15, wherein the optimization result generating module 15 is configured to input the residual liquid distribution position characteristics and the residual liquid geometric characteristics into the drying control parameter optimization vector space, and generate a drying control parameter optimization result;
a feedback generation module 16, where the feedback generation module 16 is configured to send the drying control parameter optimization result to a display interface of a control terminal, and generate first feedback information, where the first feedback information includes a drying confirmation instruction;
a conveying module 17, wherein the conveying module 17 is configured to convey the optical element to be dried to a preset drying area of the wind power drying device according to the confirmed drying instruction.
Further, the system further comprises:
the optical element control parameter uploading module is used for uploading optical element control parameters according to the wind power drying equipment, wherein the optical element control parameters comprise optical element positioning point parameters and optical element posture positioning parameters;
the drying environment control parameter uploading module is used for uploading drying environment control parameters according to the wind power drying equipment, wherein the drying environment control parameters comprise a drying environment temperature parameter and a drying environment humidity parameter;
the drying wind power control parameter uploading module is used for uploading drying wind power control parameters according to the wind power drying equipment, wherein the drying wind power control parameters comprise a blowing temperature parameter, a blowing vector parameter, a gas flow parameter, a blowing duration parameter and a cycle period parameter;
a drying control parameter set determining module, configured to add the optical element positioning point parameter, the optical element posture positioning parameter, the drying environment temperature parameter, the drying environment humidity parameter, the blowing temperature parameter, the blowing vector parameter, the gas flow parameter, the blowing duration parameter, and the cycle period parameter into the drying control parameter set.
Further, the system further comprises:
the wind power drying record data set matching module is used for matching a wind power drying record data set based on big data according to the wind power drying equipment and the drying control parameter set, wherein the wind power drying record data set comprises residual liquid distribution position record data, residual liquid geometric characteristic record data and drying control parameter record data;
the drying control parameter clustering result generating module is used for carrying out clustering analysis on the drying control parameter record data according to the residual liquid distribution position record data and the residual liquid geometric characteristic record data to generate a plurality of groups of drying control parameter clustering results;
and the first execution module is used for constructing the drying control parameter optimization vector space according to the clustering results of the multiple groups of drying control parameters.
Further, the system further comprises:
the second execution module is used for acquiring a first group of drying control parameter clustering results and a second group of drying control parameter clustering results till the Mth group of drying control parameter clustering results according to the multiple groups of drying control parameter clustering results;
the first space construction module is used for constructing a first scene optimization vector subspace according to the first group of drying control parameter clustering results;
the Mth space construction module is used for constructing an Mth scene optimization vector subspace according to the Mth group of drying control parameter clustering results;
a third execution module to combine the first scene optimization vector subspace, the second scene optimization vector subspace, and the Mth scene optimization vector subspace to generate the drying control parameter optimization vector space.
Further, the system further comprises:
the sensitive characteristic value generating module is used for limiting the drying control parameter set according to the optical element to be dried to generate a drying control parameter sensitive characteristic value;
the system comprises a first tabu table construction module, a second tabu table construction module and a third tabu table construction module, wherein the first tabu table construction module is used for adding a drying control parameter sensitive characteristic value into a first tabu table of the tabu table, and data in the tabu table are forbidden to be selected for optimal design;
a second tabu table construction module, configured to construct a second tabu table of the tabu table, where an initial value of the second tabu table is null;
a fourth execution module, configured to define the first scene optimization vector subspace, the second scene optimization vector subspace, and the mth scene optimization vector subspace according to the first tabu table and the second tabu table, and generate the drying control parameter optimization vector space.
Further, the system further comprises:
the second feedback information acquisition module is used for sending the drying control parameter set to a display interface of the control terminal to acquire second feedback information, wherein the second feedback information comprises a drying control parameter set value constraint interval;
a function construction module for constructing a screening fitness function:
wherein, P k Characterizing the fitness of the kth set of control parameters, f k Characterizing the selection frequency, C, of the kth set of control parameters in the recorded data k0 Characterization of the initial residual fluid geometric characteristic value, C k1 Characterizing geometric characteristic values of the residual liquid after the kth group of control parameters are dried, wherein alpha and beta are weight indexes, and alpha + beta =1;
a fifth execution module, configured to limit the first scene optimization vector subspace, the second scene optimization vector subspace, and the mth scene optimization vector subspace according to the screening fitness function and the drying control parameter set value constraint interval, and generate the drying control parameter optimization vector space.
Further, the system further comprises:
a spatial activation module, configured to input the residual liquid distribution position feature and the residual liquid geometric feature into the drying control parameter optimization vector space, and activate an mth scene optimization vector subspace;
a random value taking module, which is used for taking a value from the drying control parameter set to a constrained interval, taking a value randomly and generating a kth control parameter selection result;
a characteristic value determination module, configured to input the kth control parameter selection result into the mth scene optimization vector subspace matching selection frequency characteristic value, an initial residual liquid geometric characteristic value, and a dried residual liquid geometric characteristic value;
a fitness determining module, configured to input the selected frequency characteristic value, the initial residual liquid geometric characteristic value, and the dried residual liquid geometric characteristic value into the screening fitness function, so as to obtain a kth fitness;
the judging module is used for acquiring the k-1 fitness and judging whether the k fitness is greater than or equal to the k-1 fitness;
the iteration module is used for adding the result selected by the k-1 control parameter into an elimination data set if the result is greater than or equal to the k fitness and continuing iteration based on the k fitness;
a sixth execution module, configured to generate the drying control parameter optimization result when a first preset number of iterations is met.
Further, the system further comprises:
an eliminated data set determining module, configured to add the k-th control parameter selection result to the eliminated data set if the k-th fitness is smaller than the k-1-th fitness;
the frequency judging module is used for judging whether the k-1 fitness iteration winning frequency meets a second preset iteration frequency or not;
a seventh execution module, configured to, if the result is satisfied, add the k-1 control parameter selection result to the second tabu table, and continue iteration;
an eighth execution module, configured to, when a storage time of the k-1 control parameter selection result in the second tabu table satisfies a third preset iteration number, take the k-1 control parameter selection result out of the second tabu table, and continue the iteration, where the first preset iteration number is greater than the third preset iteration number and is greater than the second preset iteration number;
a ninth execution module to generate the drying control parameter optimization result when the first preset number of iterations is met.
The application provides a high-efficiency drying method for chemical wet cleaning, wherein the method is applied to a high-efficiency drying system for chemical wet cleaning, and the method comprises the following steps: carrying out image acquisition on the optical element to be dried which is cleaned by the chemical wet method through an image acquisition device to generate an optical element surface image acquisition result; performing feature extraction on the surface image acquisition result of the optical element to generate a residual liquid feature parameter; uploading a drying control parameter set according to the wind power drying equipment; sending the data to a drying control module to generate a drying control parameter optimization vector space; inputting the distribution position characteristics of the residual liquid and the geometric characteristics of the residual liquid into the drying control parameter optimization vector space to generate a drying control parameter optimization result; sending the drying control parameter optimization result to a display interface of a control terminal to generate first feedback information; and conveying the optical element to be dried to a preset drying area of the wind power drying device according to the confirmed drying instruction. The technical problem that in the prior art, the accuracy of the drying control parameters of the optical element cleaned by the chemical wet method is not high, and the drying control effect of the optical element cleaned by the chemical wet method is poor is solved. The accuracy of the drying control parameters of the optical element cleaned by the chemical wet method is improved, and the drying control quality of the optical element cleaned by the chemical wet method is improved; meanwhile, the optical element cleaned by the chemical wet method is efficiently, accurately and reliably dried and controlled, and the technical effect of reducing the damage to the optical element cleaned by the chemical wet method due to improper drying control is achieved.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The specification and drawings are merely illustrative of the present application, and it is intended that the present invention cover modifications and variations of this invention provided they come within the scope of the invention and their equivalents.
Claims (9)
1. A high-efficiency drying method for chemical wet cleaning, which is characterized in that the method applies a high-efficiency drying system for chemical wet cleaning, the system comprises a drying control module, the drying control module is in communication connection with a wind power drying device, the system is in communication connection with an image acquisition device, and the method comprises the following steps:
calling an image acquisition device to acquire an image of an optical element to be dried, which is cleaned by a chemical wet method, so as to generate an optical element surface image acquisition result;
performing feature extraction on the surface image acquisition result of the optical element to generate residual liquid feature parameters, wherein the residual liquid feature parameters comprise residual liquid distribution position features and residual liquid geometric features;
uploading a drying control parameter set according to the wind power drying equipment;
sending the drying control parameter set to a drying control module to generate a drying control parameter optimization vector space;
inputting the residual liquid distribution position characteristics and the residual liquid geometric characteristics into the drying control parameter optimization vector space to generate a drying control parameter optimization result;
sending the drying control parameter optimization result to a display interface of a control terminal to generate first feedback information, wherein the first feedback information comprises a drying confirmation instruction;
and conveying the optical element to be dried to a preset drying area of the wind power drying device according to the confirmed drying instruction.
2. Method according to claim 1, wherein said uploading a set of drying control parameters according to a pneumatic drying apparatus comprises:
uploading optical element control parameters according to the wind power drying equipment, wherein the optical element control parameters comprise optical element positioning point parameters and optical element posture positioning parameters;
uploading drying environment control parameters according to the wind power drying equipment, wherein the drying environment control parameters comprise a drying environment temperature parameter and a drying environment humidity parameter;
uploading drying wind power control parameters according to the wind power drying equipment, wherein the drying wind power control parameters comprise a blowing temperature parameter, a blowing vector parameter, a gas flow parameter, a blowing time parameter and a cycle period parameter;
adding the optical element positioning point parameter, the optical element attitude positioning parameter, the drying environment temperature parameter, the drying environment humidity parameter, the blowing temperature parameter, the blowing vector parameter, the gas flow parameter, the blowing duration parameter, and the cycle period parameter into the drying control parameter set.
3. The method of claim 2, wherein sending the set of drying control parameters to a drying control module, generating a drying control parameter optimization vector space, comprises:
matching a wind power drying record data set based on big data according to the wind power drying equipment and the drying control parameter set, wherein the wind power drying record data set comprises residual liquid distribution position record data, residual liquid geometric characteristic record data and drying control parameter record data;
performing cluster analysis on the drying control parameter record data according to the residual liquid distribution position record data and the residual liquid geometric characteristic record data to generate a plurality of groups of drying control parameter cluster results;
and constructing the drying control parameter optimization vector space according to the clustering results of the multiple groups of drying control parameters.
4. The method of claim 3, wherein the constructing the drying control parameter optimization vector space according to the plurality of groups of drying control parameter clustering results comprises:
according to the multiple groups of drying control parameter clustering results, obtaining a first group of drying control parameter clustering results, a second group of drying control parameter clustering results till an Mth group of drying control parameter clustering results;
constructing a first scene optimization vector subspace according to the first group of drying control parameter clustering results;
constructing an Mth scene optimization vector subspace according to the Mth group of drying control parameter clustering results;
and combining the first scene optimization vector subspace, the second scene optimization vector subspace and the Mth scene optimization vector subspace to generate the drying control parameter optimization vector space.
5. The method of claim 4, wherein the merging the first scene optimization vector subspace, the second scene optimization vector subspace, and the Mth scene optimization vector subspace to generate the drying control parameter optimization vector space, comprises:
limiting the drying control parameter set according to the optical element to be dried to generate a drying control parameter sensitive characteristic value;
adding the drying control parameter sensitive characteristic value into a first taboo sublist of a taboo table, wherein data in the taboo table are forbidden to be selected for optimization design;
constructing a second taboo sublist of the taboo list, wherein the initial value of the second taboo sublist is null;
and limiting the first scene optimization vector subspace, the second scene optimization vector subspace and the Mth scene optimization vector subspace according to the first tabu sub table and the second tabu sub table to generate the drying control parameter optimization vector space.
6. The method of claim 5, wherein the defining the first scene optimization vector subspace, the second scene optimization vector subspace, and the Mth scene optimization vector subspace according to the first tabu table and the second tabu table to generate the drying control parameter optimization vector space comprises:
sending the drying control parameter set to a display interface of the control terminal to obtain second feedback information, wherein the second feedback information comprises a drying control parameter set value constraint interval;
constructing a screening fitness function:
wherein, P k Characterizing the fitness of the kth set of control parameters, f k Characterizing the selection frequency, C, of the kth set of control parameters in the recorded data k0 Characterizing the initial residual fluid geometric characteristic value, C k1 Characterizing geometric characteristic values of the residue liquid after drying of the kth group of control parameters, wherein alpha and beta are weight indexes, and alpha + beta =1;
and limiting the first scene optimization vector quantum space, the second scene optimization vector quantum space and the Mth scene optimization vector quantum space according to the screening fitness function and the drying control parameter set value constraint interval to generate the drying control parameter optimization vector space.
7. The method of claim 6, wherein said inputting said residual fluid distribution positional features and said residual fluid geometric features into said drying control parameter optimization vector space to generate a drying control parameter optimization result comprises:
inputting the residual liquid distribution position characteristics and the residual liquid geometric characteristics into the drying control parameter optimization vector space, and activating an m-th scene optimization vector subspace;
randomly taking values from the drying control parameter set value-taking constraint interval to generate a k control parameter selection result;
inputting the k-th control parameter selection result into the m-th scene optimization vector subspace to match and select a frequency characteristic value, an initial residual liquid geometric characteristic value and a dried residual liquid geometric characteristic value;
inputting the selected frequency characteristic value, the initial residual liquid geometric characteristic value and the dried residual liquid geometric characteristic value into the screening fitness function to obtain a kth fitness;
acquiring a k-1 fitness, and judging whether the k fitness is greater than or equal to the k-1 fitness;
if the k-1 control parameter is larger than or equal to the k-1 control parameter, adding the selected result of the k-1 control parameter into an eliminated data set, and continuing iteration based on the k-th fitness;
and generating the drying control parameter optimization result when the first preset iteration number is met.
8. The method of claim 7, wherein said determining whether the k-th fitness is greater than or equal to the k-1 th fitness comprises:
if the k-th fitness is smaller than the k-1 fitness, adding the k-th control parameter selection result into the elimination data set;
judging whether the k-1 fitness iteration winning number meets a second preset iteration number or not;
if yes, adding the result of the k-1 control parameter selection into the second tabu table, and continuing iteration;
when the storage time of the k-1 control parameter selection result in the second tabu table meets a third preset iteration number, taking the k-1 control parameter selection result out of the second tabu table, and continuing iteration, wherein the first preset iteration number is greater than the third preset iteration number and is greater than the second preset iteration number;
and when the first preset iteration number is met, generating a drying control parameter optimization result.
9. An efficient drying system for chemical wet cleaning, characterized in that, the system includes a drying control module, the drying control module is connected with a wind drying device in communication, the system is connected with an image acquisition device in communication, the system includes:
the image acquisition module is used for calling the image acquisition device to acquire an image of the optical element to be dried, which is cleaned by the chemical wet method, so as to generate an image acquisition result of the surface of the optical element;
the characteristic extraction module is used for carrying out characteristic extraction on the surface image acquisition result of the optical element to generate residual liquid characteristic parameters, wherein the residual liquid characteristic parameters comprise residual liquid distribution position characteristics and residual liquid geometric characteristics;
the drying control parameter uploading module is used for uploading a drying control parameter set according to the wind power drying equipment;
the optimized space generation module is used for sending the drying control parameter set to the drying control module to generate a drying control parameter optimized vector space;
the optimization result generation module is used for inputting the residual liquid distribution position characteristics and the residual liquid geometric characteristics into the drying control parameter optimization vector space to generate a drying control parameter optimization result;
the feedback generation module is used for sending the drying control parameter optimization result to a display interface of a control terminal to generate first feedback information, wherein the first feedback information comprises a drying confirmation instruction;
and the conveying module is used for conveying the optical element to be dried to a preset drying area of the wind power drying equipment according to the drying confirmation instruction.
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