Fluorine oil cleaning method and device for precision electronics

Abstract

The invention discloses a fluorine oil cleaning method and device for precision electronics, and relates to the field related to intelligent cleaning.The method comprises the steps that target component characteristics are collected to determine target fluorine oil, and first cleaning control data of soaking and cleaning a target precision electronic component through the target fluorine oil are obtained, analyzing the first cleaning control data through a soak cleaning evaluation model, obtaining a first soak cleaning cleanliness index as an analogy screening constraint, screening historical fluorine oil cleaning records to obtain a target historical record, and introducing a cleaning fitness function as an optimization evaluation function, and taking the target historical record as an optimization space to obtain second cleaning control data to perform ultrasonic cleaning on the target precision electronic component. The technical problem that the cleaning effect is poor due to the fact that tiny stains or residues on the surfaces of precision electronic parts cannot be thoroughly removed through a traditional precision electronic cleaning mode is solved, and the technical effects that dirt on the surfaces of the precision electronic parts is effectively removed, and the performance of the parts is not affected by cleaning are achieved.

Description

Technical Field

[0001] The present application relates to the field of intelligent cleaning, and in particular to a fluorine oil cleaning method and device for precision electronics. Background Art

[0002] During the manufacturing and maintenance of electronic equipment, various pollutants such as dust, oil, moisture, oxidation and corrosive gases may cause "comprehensive pollution" to the circuits in the equipment, resulting in equipment performance degradation, failure or other serious accidents. In addition, the electromagnetic field distribution in the normal operation of communication equipment and the long-term friction accumulation of the air supply system may also cause "accumulated static electricity", further increasing the failure rate of the equipment. However, the traditional cleaning method of precision electronics cannot completely remove the tiny stains or residues on the surface of precision electronic parts, resulting in technical problems with poor cleaning effects. Summary of the invention

[0003] The present application provides a fluorine oil cleaning method and device for precision electronics, thereby solving the technical problem that traditional precision electronics cleaning methods cannot completely remove tiny stains or residues on the surface of precision electronic parts, resulting in poor cleaning effects. The application achieves the technical effect of effectively removing dirt and contaminants on the surface of precision electronics, so that cleaning does not affect the performance of components.

[0004] The present application provides a fluorine oil cleaning method for precision electronics, the method being applied to a fluorine oil cleaning system for precision electronics, comprising: collecting target component characteristics of a target precision electronic component, the target component characteristics comprising target contamination characteristics and target material characteristics;

[0005] Using the target pollution characteristics and the target material characteristics as traversal constraints, traversing and analyzing in the fluorine oil database to determine the target fluorine oil;

[0006] Acquire first cleaning control data of immersing and cleaning the target precision electronic component with the target fluorine oil;

[0007] Analyzing the first cleaning control data by using an immersion cleaning evaluation model to obtain a first immersion cleaning cleanliness index of the target precision electronic component;

[0008] Using the first immersion cleaning cleanliness index as an analogy screening constraint to screen historical fluorine oil cleaning records, to obtain target historical records;

[0009] Introducing a cleaning fitness function as an optimization evaluation function, and using the target historical record as an optimization space, to obtain second cleaning control data;

[0010] The target precision electronic component is ultrasonically cleaned according to the second cleaning control data.

[0011] In a possible implementation, the following processing is performed: multiple pollution levels of multiple pollutants in the target pollution feature after weighted normalization are obtained to obtain a target pollution level value;

[0012] Obtaining a target material compatibility value by weighting and normalizing a plurality of performance parameters corresponding to a plurality of material properties in the target material characteristics;

[0013] The target contamination level value and the target material compatibility value are used as the traversal constraints.

[0014] In a possible implementation, the following processing is performed: extracting a first fluorine oil type from the fluorine oil database, wherein the first fluorine oil type has a mapping relationship with a first fluorine oil property, and the first fluorine oil property includes a first fluorine oil purity and a first fluorine oil viscosity;

[0015] The first fluorine oil purity and the first fluorine oil viscosity after weighted normalization are used to obtain a first cleaning ability value;

[0016] Obtaining a first material compatibility value of the first fluoro oil type;

[0017] When the first cleaning ability value is greater than or equal to the target contamination level value in the traversal constraint, and the first material compatibility value is greater than or equal to the target material compatibility value in the traversal constraint, the first fluorine oil type is used as the target fluorine oil.

[0018] In a possible implementation, the following processing is performed: obtaining a historical fluorine oil immersion cleaning record in the historical fluorine oil cleaning record, wherein the historical fluorine oil immersion cleaning record includes a first historical immersion cleaning record;

[0019] Reading a predetermined soaking index, and screening the first historical soaking cleaning record based on the predetermined soaking index to obtain first historical cleaning control data;

[0020] Reading a predetermined cleaning feature, and screening the first historical immersion cleaning record based on the predetermined cleaning feature to obtain first historical cleaning feature data;

[0021] Analyze the first historical cleaning characteristic data to obtain a first historical immersion cleaning cleanliness index, and form a first historical data group with the first historical cleaning control data;

[0022] The first historical data set is subjected to supervised training and learning, and the immersion cleaning evaluation model is obtained by verification.

[0023] In a possible implementation, the following process is performed: the predetermined soaking index includes soaking temperature and soaking time.

[0024] In a possible implementation, the following processing is performed: the predetermined cleanliness feature refers to the type of residue and the amount of residue.

[0025] In a possible implementation, the following processing is performed: obtaining a historical fluorine oil ultrasonic cleaning record in the historical fluorine oil cleaning record;

[0026] When the index difference between the first historical immersion cleaning cleanliness index and the first immersion cleaning cleanliness index is within a predetermined difference limit, matching a first historical ultrasonic cleaning record corresponding to the first historical immersion cleaning record in the historical fluorine oil ultrasonic cleaning record;

[0027] The first historical ultrasonic cleaning record is added to the target historical record.

[0028] In a possible implementation, the following processing is performed: the expression of the cleaning fitness function is as follows:

[0029]

[0030] Among them, f(x) refers to the fitness of the cleaning control data x, t(x), d(x) and r(x) respectively refer to the cleaning time, dryness after washing and dirt residue of the target precision electronic component under the cleaning control data x, a, b and c are all weight coefficients, and a+b+c=1.

[0031] In a possible implementation, the following processing is performed: acquiring an ultrasonic signal under the second cleaning control data;

[0032] The ultrasonic signal is analyzed to obtain an ultrasonic vibration index, and the ultrasonic vibration index is used to perform feedback adjustment on the cleaning adaptability of the second cleaning control data.

[0033] The present application also provides a fluorine oil cleaning system for precision electronics, comprising: a first feature acquisition module, the first feature acquisition module being used to acquire target component features of a target precision electronic component, the target component features including target contamination features and target material features;

[0034] A first analysis module, the first analysis module is used to perform traversal analysis in the fluorine oil database using the target pollution characteristics and the target material characteristics as traversal constraints to determine the target fluorine oil;

[0035] A first cleaning module, the first cleaning module is used to obtain first cleaning control data for immersing and cleaning the target precision electronic component with the target fluorine oil;

[0036] a second analysis module, the second analysis module being used to analyze the first cleaning control data through an immersion cleaning evaluation model to obtain a first immersion cleaning cleanliness index of the target precision electronic component;

[0037] A record screening module, the record screening module is used to screen the historical fluorine oil cleaning records by using the first immersion cleaning cleanliness index as an analogy screening constraint to obtain target historical records;

[0038] A first optimization module, wherein the first optimization module is used to introduce a cleaning fitness function as an optimization evaluation function and use the target historical record as an optimization space to obtain second cleaning control data;

[0039] A second cleaning module, wherein the second cleaning module is used to perform ultrasonic cleaning on the target precision electronic component according to the second cleaning control data.

[0040] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0041] The fluorine oil cleaning method and device for precision electronics provided in the present application relate to the field of intelligent cleaning technology, and solve the technical problem that the traditional cleaning method of precision electronics cannot completely remove the tiny stains or residues on the surface of precision electronic parts, resulting in poor cleaning effect, and achieve the technical effect of effectively removing dirt and contaminants on the surface of precision electronics, so that cleaning does not affect the performance of components. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0043] Figure 1 A schematic flow chart of a fluorine oil cleaning method for precision electronics provided in an embodiment of the present application;

[0044] Figure 2 A schematic diagram of the structure of a fluorine oil cleaning system for precision electronics provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0046] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0047] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0048] The present application provides a fluorine oil cleaning method for precision electronics, and the method is applied to a fluorine oil cleaning system for precision electronics, such as Figure 1 As shown, the method includes:

[0049] Step A100, collecting target component characteristics of the target precision electronic component, wherein the target component characteristics include target contamination characteristics and target material characteristics; determining the target precision electronic component based on component type, component model, and component batch. Before collecting the target component characteristics of the target precision electronic component, it is also necessary to obtain information such as production process, use environment, known contamination types, etc., to help better obtain possible contamination and material characteristics of the target component.

[0050] Furthermore, the target components can be inspected visually, and the observed contamination type (such as dust, grease, oxides, etc.), degree of contamination and distribution can be recorded simultaneously. The contaminants on the surface of the target components can also be sampled and analyzed using chemical reagents through surface sampling, solution extraction, chromatography analysis and other methods to determine the chemical composition and properties of the contaminants, and the target contamination characteristics on the surface of the target precision electronic components can be collected by measuring the physical properties of the contaminants (such as hardness, adhesion, etc.).

[0051] Furthermore, the material of the target component can be identified by using material analysis instruments (such as energy spectrometer, X-ray diffractometer, etc.) to determine its chemical composition, crystal structure and other basic information. The material characteristics of the target precision electronic component can also be obtained by measuring the physical properties of the target component (such as hardness, elastic modulus, thermal expansion coefficient, etc.). The collected target contamination characteristics and target material characteristics data can be sorted and analyzed to form a complete target component characteristic database, and the target component characteristics can be output.

[0052] Execute step A200, use the target contamination characteristics and the target material characteristics as traversal constraints to traverse and analyze in the fluorine oil database to determine the target fluorine oil; in one possible implementation, step A200 further includes step A210, obtain a target contamination degree value by weighted normalized multiple contamination degrees of multiple pollutants in the target contamination characteristics; execute step A220, obtain a target material compatibility value by weighted normalized multiple performance parameters corresponding to multiple material properties in the target material characteristics; execute step A230, use the target contamination degree value and the target material compatibility value as the traversal constraints.

[0053] Using the target pollution characteristics and target material characteristics obtained above as traversal constraints means weighted normalization of the target pollution characteristics and target material characteristics respectively, and the process may be: based on the target pollution characteristics, the types of pollutants (such as dust, grease, oxides, etc.) existing on the target component and the pollution degree of each pollutant are determined, and then the corresponding weight is set according to the influence of each pollutant on the performance of the component. The greater the set weight, the greater the influence of the pollutant on the performance of the component. Finally, the pollution degree of each pollutant is multiplied by its corresponding weight, and then all weighted pollution degree values ​​are added to obtain the total pollution degree value, and then the total pollution degree value is divided by the sum of all weights to obtain the normalized target pollution degree value.

[0054] Then, based on the target material characteristics, the material performance parameters of the target element, such as hardness, elastic modulus, thermal expansion coefficient, etc., are determined, and then the corresponding weights are set according to the degree of influence of each performance parameter on the cleaning process. The greater the weight set, the greater the influence of the performance parameter on the cleaning process. Then, the value of each performance parameter is multiplied by its corresponding weight, and then all weighted performance parameter values ​​are added together to obtain the total material performance value. Next, the total material performance value is divided by the sum of all weights to obtain the normalized target material compatibility value.

[0055] Ultimately, the target contamination level value and the target material compatibility value can be used as constraints to traverse the cleaning scheme, which means that the cleaning agent and cleaning process that can effectively remove the corresponding pollutants can be selected according to the target contamination level value; at the same time, the cleaning agent and cleaning process that has no damage or less damage to the target component material can be selected according to the target material compatibility value.

[0056] In the process of traversing and analyzing the fluorine oil database to determine the target fluorine oil based on the traversal constraint, we need to screen and evaluate the fluorine oil in the fluorine oil database according to the target contamination degree value (indicating the contamination status of the target component) and the target material compatibility value (indicating the compatibility of the target component material with the cleaning agent) calculated previously. In a possible implementation, step A200 further includes step A240, extracting a first fluorine oil type from the fluorine oil database, wherein the first fluorine oil type has a mapping relationship with the first fluorine oil performance, and the first fluorine oil performance includes the first fluorine oil purity and the first fluorine oil viscosity; executing step A250, weighting and normalizing the first fluorine oil type. The first fluoro oil purity and the first fluoro oil viscosity are used to obtain a first cleaning ability value; the first fluoro oil type is searched and extracted in the fluoro oil database, and the first fluoro oil type and the first fluoro oil performance have a mapping relationship, and then the first fluoro oil purity and the first fluoro oil viscosity associated with the first fluoro oil type are retrieved from the database, the first fluoro oil purity refers to the content of effective ingredients in the first fluoro oil type, and the higher the content of effective ingredients, the better the quality of the fluoro oil, and the first fluoro oil viscosity refers to the physical quantity of the intermolecular interaction force within the first fluoro oil type, and the first fluoro oil viscosity can resist shear deformation and cause viscous resistance. Furthermore, a weight value is set according to the degree of influence of the first fluoro oil purity on the fluoro oil cleaning ability. The higher the purity, the fewer impurities in the fluoro oil and the better the dirt cleaning ability. According to the influence of the first fluoro oil viscosity on the dirt cleaning ability of the fluoro oil, another weight value is set. The appropriate range of the first fluoro oil viscosity is crucial to ensure that the fluoro oil can fully penetrate and remove pollutants. Furthermore, the first fluoro oil purity and the first fluoro oil viscosity are multiplied by their corresponding weights to obtain the weighted value of the first fluoro oil purity and the weighted value of the first fluoro oil viscosity. Finally, the two weighted values ​​are added and then divided by the sum of the two weights to obtain the normalized first dirt cleaning ability value.

[0057] Execute step A260 to obtain the first material compatibility value of the first fluoro oil type; execute step A270, when the first cleaning ability value is greater than or equal to the target contamination level value in the traversal constraint, and the first material compatibility value is greater than or equal to the target material compatibility value in the traversal constraint, use the first fluoro oil type as the target fluoro oil.

[0058] Based on the first fluoro oil type, the fluoro oil database is traversed to obtain the first material compatibility value corresponding to the first fluoro oil type. The first material compatibility value is used to characterize the compatibility of the fluoro oil with a specific material (such as the material of the target electronic component). Then, according to the known purity and viscosity of the first fluoro oil and the previously set weight, the first dirt cleaning ability value is calculated using a weighted normalization method. The calculated first dirt cleaning ability value is compared with the target contamination degree value in the traversal constraint, and the extracted first material compatibility value is compared with the target material compatibility value in the traversal constraint. If the first dirt cleaning ability value is less than the target contamination degree value, and / or the first material compatibility value is greater than or equal to the target material compatibility value, it is considered that the first fluoro oil type at this time does not meet the conditions and the first fluoro oil type cannot be used as the target fluoro oil. At the same time, backtracking is performed to update and re-compare the first dirt cleaning ability value and the first material compatibility value. If the first dirt cleaning ability value is greater than or equal to the target contamination degree value, and the first material compatibility value is greater than or equal to the target material compatibility value, it is considered that the first fluoro oil type meets the conditions. When the first fluoro oil type meets the above conditions, it is determined as the target fluoro oil.

[0059] Execute step A300 to obtain first cleaning control data for immersion cleaning of the target precision electronic component with the target fluorine oil; collect characteristics based on the target fluorine oil, the collected characteristics may be cleaning ability, temperature range, chemical stability, etc., based on the characteristics of the target fluorine oil, the optimal use temperature and immersion time range of the target fluorine oil may be determined, further, the material of the target precision electronic component is analyzed to ensure that it will not chemically react with the fluorine oil or be damaged, and at the same time evaluate the structure and size of the component, determine the immersion method and container selection, further design the immersion cleaning steps, including pretreatment of the target precision electronic component (such as removing large particles of dirt), immersion, rinsing and drying, etc., and determine the order of immersion cleaning. If there are multiple components of the target precision electronic component that need to be cleaned, batch processing may need to be considered.

[0060] The cleaning control parameters of the target precision electronic components are further determined. The determined cleaning control parameters may include temperature parameters, time parameters, stirring parameters, rinsing parameters, drying parameters, etc. Before actual cleaning, a small amount of components may be used for trial cleaning to verify the validity of the cleaning control data, thereby outputting the first cleaning control data.

[0061] Execute step A400, analyze the first cleaning control data through the immersion cleaning evaluation model to obtain the first immersion cleaning cleanliness index of the target precision electronic component; in a possible implementation, step A400 further includes step A410, obtain the historical fluorine oil immersion cleaning record in the historical fluorine oil cleaning record, and the historical fluorine oil immersion cleaning record includes the first historical immersion cleaning record; execute step A420, read the predetermined immersion index, and filter the first historical immersion cleaning record based on the predetermined immersion index to obtain the first historical cleaning control data; in a possible implementation, step A420 further includes step A421, and the predetermined immersion index includes the immersion temperature and the immersion time.

[0062] All records related to immersion cleaning are retrieved from the historical fluorine oil cleaning record database, and the retrieved records are recorded as historical fluorine oil immersion cleaning records, which may include information such as the type of fluorine oil, the type of precision electronic components cleaned, cleaning conditions (such as temperature, duration, etc.) and cleaning effect, and the historical fluorine oil immersion cleaning records include the first historical immersion cleaning records, which means that among all historical immersion cleaning records, records similar to or identical to the current target fluorine oil and target precision electronic components are identified as the first historical immersion cleaning records.

[0063] Furthermore, a predetermined immersion index is read. The predetermined immersion index is set before the cleaning operation and is used to guide the standard for screening historical cleaning records. The predetermined immersion index may include immersion temperature and immersion time. The immersion temperature refers to the temperature parameter of the target precision electronic component during the immersion process, and the immersion time refers to the total immersion time of the target precision electronic component in the target fluorine oil. The predetermined immersion index (such as immersion temperature and immersion time) is used as a screening condition to screen the first historical immersion cleaning record, and the historical immersion record whose immersion temperature and immersion time are consistent with or close to the predetermined index is screened. At the same time, the first cleaning control data is extracted from the screened first historical immersion cleaning record. The first cleaning control data may include immersion temperature, immersion time, stirring speed, cleaning steps, etc.

[0064] Execute step A430, read the predetermined clean characteristics, and screen the first historical immersion cleaning record based on the predetermined clean characteristics to obtain first historical clean characteristic data; in a possible implementation, step A430 further includes step A431, and the predetermined clean characteristics refer to the type of residue and its residual amount.

[0065] First, the predetermined clean characteristics are read. The predetermined clean characteristics are usually the standards that are expected to be achieved during the cleaning process, such as specific types of residues and the upper limit of their residual amounts. The predetermined clean characteristics are the types of residues and their residual amounts. All records related to immersion cleaning are retrieved from the historical fluorine oil cleaning record database, which may include information such as the types of residues before and after cleaning, the residual amounts, and cleaning conditions. Among all historical immersion cleaning records, records that are similar or identical to the current target fluorine oil and target precision electronic components are identified as the first historical immersion cleaning records.

[0066] Further, using predetermined clean characteristics (such as the type of residue and the upper limit of its residual amount) as screening conditions, the first historical immersion cleaning records are screened, and records whose types and amounts of residues after cleaning meet the predetermined clean characteristic requirements are obtained. Relevant clean characteristic data are extracted from the screened first historical immersion cleaning records and recorded as the first historical clean characteristic data, which may include the types of residues before and after cleaning, the residual amount and the corresponding cleaning conditions (such as immersion temperature, duration, etc.).

[0067] Execute step A440, analyze the first historical clean feature data to obtain a first historical immersion cleaning cleanliness index, and form a first historical data group with the first historical cleaning control data; execute step A450, perform supervised training learning on the first historical data group, and verify to obtain the immersion cleaning evaluation model.

[0068] Analyze the types and amounts of residues after cleaning contained in the first historical clean feature data, and define one or more cleanliness indexes, such as total residues, specific residue ratios, etc., based on the types and amounts of residues. On this basis, calculate a cleanliness index for each historical record. This index can be a score from 0 to 10. At the same time, pair the first historical cleaning control data (such as soaking temperature, duration, etc.) of each historical record with its corresponding cleanliness index to obtain a data set containing multiple samples, namely the first historical data group, and each sample contains a pair of cleaning control data-cleanliness index. Further, most of the data in the first historical data group is used as a training set to train the model to learn the relationship between the cleaning control data and the cleanliness index. The remaining data is used as a validation set or a test set to evaluate the performance of the model. Various indicators such as mean square error can be used to evaluate the performance of the model on the validation set or the test set to test the generalization ability of the soaking cleaning evaluation model. When the soaking cleaning evaluation model passes the verification, it is output.

[0069] Analyzing the first cleaning control data through the immersion cleaning evaluation model means taking the first cleaning control data as input and passing it to the above-mentioned trained immersion cleaning evaluation model. The immersion cleaning evaluation model will predict the corresponding cleanliness index based on the input cleaning control data using the mapping relationship or rules learned internally. The result of the model output is the first immersion cleaning cleanliness index of the target precision electronic component. The first immersion cleaning cleanliness index reflects the cleanliness of the component after cleaning under the given cleaning control data.

[0070] Next, step A500 is performed to filter the historical fluorine oil cleaning records using the first immersion cleaning cleanliness index as an analogy screening constraint to obtain target historical records; a screening threshold is set according to the first immersion cleaning cleanliness index, and the set screening threshold can be used to filter out records with a similar or better cleanliness level than the current target from the historical fluorine oil cleaning records, and at the same time, the historical fluorine oil cleaning record database is sorted to ensure that each historical fluorine oil cleaning record contains cleaning control data and corresponding cleanliness characteristic data (such as the type and amount of residues after cleaning); further, the calculated historical cleanliness index is compared with the set screening threshold to filter out those historical records whose cleanliness index meets or exceeds the screening threshold, and these historical records are recorded as target historical records for output.

[0071] Execute step A600, introduce the cleaning fitness function as the optimization evaluation function, and use the target history record as the optimization space to obtain the second cleaning control data; by introducing the cleaning fitness function as the optimization evaluation function, in a possible implementation, step A600 further includes step A640, and the expression of the cleaning fitness function is as follows:

[0072]

[0073] Among them, f(x) refers to the fitness of the cleaning control data x, t(x), d(x) and r(x) respectively refer to the cleaning time, dryness after washing and dirt residue of the target precision electronic component under the cleaning control data x, a, b and c are all weight coefficients, and a+b+c=1.

[0074] In one possible implementation, step A600 further includes step A610, obtaining a historical fluorine oil ultrasonic cleaning record in the historical fluorine oil cleaning record; executing step A620, when the index difference between the first historical immersion cleaning cleanliness index and the first immersion cleaning cleanliness index is within a predetermined difference limit, matching the first historical ultrasonic cleaning record corresponding to the first historical immersion cleaning record in the historical fluorine oil ultrasonic cleaning record; executing step A630, adding the first historical ultrasonic cleaning record to the target historical record.

[0075] First, all records related to ultrasonic cleaning are retrieved from the historical fluorine oil cleaning record database, that is, historical fluorine oil ultrasonic cleaning records, which may include ultrasonic cleaning parameters (such as power, frequency, duration, etc.) and cleanliness characteristic data after cleaning, and then the difference between the first historical immersion cleaning cleanliness index and the current or latest first immersion cleaning cleanliness index is calculated, and the difference is used to characterize the difference between the historical cleaning effect and the current or latest cleaning effect, and the first historical immersion cleaning cleanliness index and the index difference of the first immersion cleaning cleanliness index are compared with the predetermined difference limit. When the index difference is within the predetermined difference limit, it is considered that the historical immersion cleaning effect is similar to the current or latest immersion cleaning effect. At the same time, in the historical fluorine oil ultrasonic cleaning records, by comparing parameters such as the type of components cleaned, the degree of contamination, and the cleaning time, the first historical ultrasonic cleaning record corresponding to or similar to the first historical immersion cleaning record, that is, the historical record similar to the current or latest immersion cleaning effect, is searched, and finally the matched first historical ultrasonic cleaning record is added to the target historical record, and the target historical record can be used as part of the optimization space for subsequent optimization or analysis.

[0076] Furthermore, the target historical records (including the first historical immersion cleaning record and the corresponding first historical ultrasonic cleaning record) are used to construct an optimization space. The constructed optimization space is a data set containing multiple historical cleaning records, and the data set contains cleaning effects under different cleaning parameters and conditions. Then, a set of initial cleaning control data is randomly selected or generated in the optimization space as a candidate solution set. The candidate solution set is a data set that can cover different areas in the optimization space. Then, the candidate solution can be applied to the cleaning process through simulation or actual experiments, and the cleanliness, cleaning time and other data after cleaning are collected. For each candidate solution, that is, a set of cleaning control data, a cleaning fitness function is used to evaluate its corresponding cleaning effect, and the candidate solution is applied to the cleaning process (which can be achieved through simulation or actual experiments), and the cleanliness, cleaning time and other data after cleaning are collected, and the fitness value of each candidate solution is calculated according to the cleaning fitness function. On this basis, the candidate solution with the best fitness value is selected as the second cleaning control data. The second cleaning control data is the best solution obtained by searching the optimization algorithm in the optimization space composed of the target historical records, and it is expected to obtain better cleaning effects in the actual cleaning process.

[0077] In one possible implementation, step A600 further includes step A650, acquiring an ultrasonic signal under the second cleaning control data; executing step 660, analyzing the ultrasonic signal to obtain an ultrasonic vibration index, and using the ultrasonic vibration index to perform feedback adjustment on the cleaning adaptability of the second cleaning control data.

[0078] The ultrasonic signal generated by the ultrasonic cleaning device can be recorded by connecting the signal output port of the ultrasonic cleaning device to the data acquisition system during the cleaning operation using the second cleaning control data, and the collected ultrasonic signal can be processed and analyzed, which can include signal preprocessing (such as filtering, amplification, etc.), feature extraction and parameter calculation and other analysis methods. Furthermore, the ultrasonic vibration index can be calculated based on parameters such as amplitude, frequency, duration, etc. in the signal, and the ultrasonic vibration index is closely related to the effect of ultrasonic cleaning. The ultrasonic vibration index can affect the performance of electronic components, that is, the greater the ultrasonic vibration, the lower the cleaning adaptability. At the same time, the ultrasonic vibration index can be used to reflect key information such as the intensity, frequency distribution or energy distribution of the ultrasonic signal.

[0079] Furthermore, the calculated ultrasonic vibration index is combined with the cleaning fitness function to evaluate the cleaning effect of the current second cleaning control data. When the ultrasonic vibration index indicates that the cleaning effect is not good, for example, the vibration intensity is insufficient or the frequency distribution is unreasonable, the cleaning fitness function can be adjusted based on this information. The feedback adjustment may include modifying the weights of relevant parameters in the cleaning fitness function, adding new evaluation indicators, or adjusting the thresholds of the evaluation criteria.

[0080] Finally, step A700 is executed to perform ultrasonic cleaning on the target precision electronic component according to the second cleaning control data.

[0081] According to the second cleaning control data, the corresponding cleaning liquid is obtained to ensure that the cleaning liquid is compatible with the material of the target precision electronic component, and the temperature, concentration and other parameters of the cleaning liquid are adjusted according to the requirements in the second cleaning control data. Further, the ultrasonic cleaning machine is set, and the setting process can be: gently place the target precision electronic component into the cleaning tank, ensure that the component will not collide violently with the bottom or side wall of the cleaning tank, pour in the prepared cleaning liquid, ensure that the liquid level does not exceed the maximum capacity mark of the cleaning tank, and further adjust the power, frequency, time and other parameters of the ultrasonic cleaning machine according to the second cleaning control data, and start ultrasonic cleaning. At the same time, in order to maintain the accuracy and consistency of the data, the detection equipment and methods should be calibrated and maintained regularly, so as to achieve the technical effect of effectively removing dirt and contaminants on the surface of precision electronics so that cleaning does not affect the performance of components.

[0082] The embodiments of the present application solve the technical problem that traditional precision electronic cleaning methods cannot completely remove tiny stains or residues on the surface of precision electronic parts, resulting in poor cleaning effects, and achieve the technical effect of effectively removing dirt and contaminants on the surface of precision electronic parts, so that cleaning does not affect the performance of components.

[0083] In the above, refer to Figure 1The fluorine oil cleaning method for precision electronics according to an embodiment of the present invention is described in detail. Figure 2 A fluorine oil cleaning system for precision electronics according to an embodiment of the present invention is described.

[0084] The fluorine oil cleaning system for precision electronics according to the embodiment of the present invention is used to solve the technical problem that the traditional cleaning method for precision electronics cannot completely remove the tiny stains or residues on the surface of precision electronic parts, resulting in poor cleaning effect, and achieves the technical effect of effectively removing dirt and contaminants on the surface of precision electronics, so that the cleaning does not affect the performance of components. The fluorine oil cleaning system for precision electronics includes: a first feature acquisition module 10, a first analysis module 20, a first cleaning module 30, a second analysis module 40, a record screening module 50, a first optimization module 60, and a second cleaning module 70.

[0085] A first feature acquisition module 10, the first feature acquisition module 10 is used to acquire target component features of a target precision electronic component, the target component features including target contamination features and target material features;

[0086] A first analysis module 20, the first analysis module 20 is used to perform traversal analysis in the fluorine oil database using the target pollution characteristics and the target material characteristics as traversal constraints to determine the target fluorine oil;

[0087] A first cleaning module 30, the first cleaning module 30 is used to obtain first cleaning control data for immersing and cleaning the target precision electronic component with the target fluorine oil;

[0088] A second analysis module 40, the second analysis module 40 is used to analyze the first cleaning control data through an immersion cleaning evaluation model to obtain a first immersion cleaning cleanliness index of the target precision electronic component;

[0089] A record screening module 50, the record screening module 50 is used to screen the historical fluorine oil cleaning records by using the first immersion cleaning cleanliness index as an analog screening constraint to obtain a target historical record;

[0090] A first optimization module 60, wherein the first optimization module 60 is used to introduce a cleaning fitness function as an optimization evaluation function and use the target historical record as an optimization space to obtain second cleaning control data;

[0091] The second cleaning module 70 is used to perform ultrasonic cleaning on the target precision electronic component according to the second cleaning control data.

[0092] The specific configuration of the first analysis module 20 will be described in detail below. As described above, the first analysis module 20 may further include: a first calculation unit for weighting and normalizing multiple pollution levels of multiple pollutants in the target pollution feature to obtain a target pollution level value; a second calculation unit for weighting and normalizing multiple performance parameters corresponding to multiple material properties in the target material feature to obtain a target material compatibility value; and a first traversal unit for using the target pollution level value and the target material compatibility value as the traversal constraint.

[0093] The specific configuration of the first cleaning module 30 will be described in detail below. As described above, the first cleaning module 30 may further include: a first extraction unit for extracting the first fluoro oil type from the fluoro oil database, the first fluoro oil type having a mapping relationship with the first fluoro oil performance, the first fluoro oil performance including the first fluoro oil purity and the first fluoro oil viscosity; a third calculation unit for weighting and normalizing the first fluoro oil purity and the first fluoro oil viscosity to obtain a first cleaning ability value; a compatibility value acquisition unit for acquiring a first material compatibility value of the first fluoro oil type; and a first judgment unit for using the first fluoro oil type as the target fluoro oil when the first cleaning ability value is greater than or equal to the target contamination level value in the traversal constraint and the first material compatibility value is greater than or equal to the target material compatibility value in the traversal constraint.

[0094] The specific configuration of the second analysis module 40 will be described in detail below. As described above, the second analysis module 40 may further include: a first record acquisition unit for acquiring the historical fluorine oil immersion cleaning record in the historical fluorine oil cleaning record, wherein the historical fluorine oil immersion cleaning record includes a first historical immersion cleaning record; a first reading unit for reading a predetermined immersion index, and filtering the first historical immersion cleaning record based on the predetermined immersion index to obtain first historical cleaning control data; a second reading unit for reading a predetermined clean feature, and filtering the first historical immersion cleaning record based on the predetermined clean feature to obtain first historical clean feature data; a third analysis unit for analyzing the first historical clean feature data to obtain a first historical immersion cleaning cleanliness index, and forming a first historical data group with the first historical cleaning control data; a learning unit for performing supervised training learning on the first historical data group, and verifying to obtain the immersion cleaning evaluation model.

[0095] The specific configuration of the first reading unit will be described in detail below. As described above, the first reading unit may further include: an indicator unit for the predetermined soaking indicator including soaking temperature and soaking time.

[0096] The specific configuration of the second reading unit will be described in detail below. As described above, the second reading unit may further include: a feature unit for the predetermined clean feature to be the type of residue and its residual amount.

[0097] The specific configuration of the first optimization module 60 will be described in detail below. As described above, the first optimization module 60 may further include: a second record acquisition unit for acquiring a historical fluorine oil ultrasonic cleaning record in the historical fluorine oil cleaning record; a first matching unit for matching a first historical ultrasonic cleaning record corresponding to the first historical immersion cleaning record in the historical fluorine oil ultrasonic cleaning record when the index difference between the first historical immersion cleaning cleanliness index and the first immersion cleaning cleanliness index is within a predetermined difference limit; and a first adding unit for adding the first historical ultrasonic cleaning record to the target historical record.

[0098] The specific configuration of the first optimization module 60 will be described in detail below. As described above, the first optimization module 60 may further include: the fourth calculation unit is used for the expression of the cleaning fitness function as follows:

[0099]

[0100] Among them, f(x) refers to the fitness of the cleaning control data x, t(x), d(x) and r(x) respectively refer to the cleaning time, dryness after washing and dirt residue of the target precision electronic component under the cleaning control data x, a, b and c are all weight coefficients, and a+b+c=1.

[0101] The specific configuration of the first optimization module 60 will be described in detail below. As described above, the first optimization module 60 may further include: a signal acquisition unit for acquiring an ultrasonic signal under the second cleaning control data; a fourth analysis unit for analyzing the ultrasonic signal to obtain an ultrasonic vibration index, and using the ultrasonic vibration index to feedback and adjust the cleaning adaptability of the second cleaning control data.

[0102] The fluorine oil cleaning system for precision electronics provided by the embodiment of the present invention can execute the fluorine oil cleaning method for precision electronics provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0103] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0104] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A fluorine oil cleaning method for precision electronics, characterized in that: include: Collecting target component characteristics of a target precision electronic component, wherein the target component characteristics include target contamination characteristics and target material characteristics; Using the target pollution characteristics and the target material characteristics as traversal constraints, traversing and analyzing in the fluorine oil database to determine the target fluorine oil; Acquire first cleaning control data of immersing and cleaning the target precision electronic component with the target fluorine oil; Analyzing the first cleaning control data by using an immersion cleaning evaluation model to obtain a first immersion cleaning cleanliness index of the target precision electronic component; Using the first immersion cleaning cleanliness index as an analogy screening constraint, screening historical fluorine oil cleaning records to obtain target historical records; Introducing a cleaning fitness function as an optimization evaluation function, and using the target historical record as an optimization space, to obtain second cleaning control data; The target precision electronic component is ultrasonically cleaned according to the second cleaning control data.

2. The fluorine oil cleaning method for precision electronics according to claim 1, characterized in that the method include: Obtaining a target pollution degree value by weighted normalization of multiple pollution degrees of multiple pollutants in the target pollution feature; Obtaining a target material compatibility value by weighting and normalizing a plurality of performance parameters corresponding to a plurality of material properties in the target material characteristics; The target contamination level value and the target material compatibility value are used as the traversal constraints.

3. The fluorine oil cleaning method for precision electronics according to claim 1, characterized in that the method include: Extracting a first fluorine oil type from the fluorine oil database, wherein the first fluorine oil type has a mapping relationship with a first fluorine oil property, and the first fluorine oil property includes a first fluorine oil purity and a first fluorine oil viscosity; The first fluorine oil purity and the first fluorine oil viscosity after weighted normalization are used to obtain a first cleaning ability value; Obtaining a first material compatibility value of the first fluoro oil type; When the first cleaning ability value is greater than or equal to the target contamination level value in the traversal constraint, and the first material compatibility value is greater than or equal to the target material compatibility value in the traversal constraint, the first fluorine oil type is used as the target fluorine oil.

4. The fluorine oil cleaning method for precision electronics according to claim 1, characterized in that the method include: Acquire a historical fluorine oil immersion cleaning record in the historical fluorine oil cleaning record, wherein the historical fluorine oil immersion cleaning record includes a first historical immersion cleaning record; Reading a predetermined soaking index, and screening the first historical soaking cleaning record based on the predetermined soaking index to obtain first historical cleaning control data; Reading a predetermined cleaning feature, and screening the first historical immersion cleaning record based on the predetermined cleaning feature to obtain first historical cleaning feature data; Analyze the first historical cleaning characteristic data to obtain a first historical immersion cleaning cleanliness index, and form a first historical data group with the first historical cleaning control data; The first historical data set is subjected to supervised training and learning, and the immersion cleaning evaluation model is obtained by verification.

5. The fluorine oil cleaning method for precision electronics according to claim 4, characterized in that: The predetermined soaking indexes include soaking temperature and soaking time.

6. The fluorine oil cleaning method for precision electronics according to claim 4, characterized in that: The predetermined cleanliness characteristics refer to the types of residues and their residual amounts.

7. The fluorine oil cleaning method for precision electronics according to claim 4, characterized in that the method include: Obtaining historical fluorine oil ultrasonic cleaning records from the historical fluorine oil cleaning records; When the index difference between the first historical immersion cleaning cleanliness index and the first immersion cleaning cleanliness index is within a predetermined difference limit, matching a first historical ultrasonic cleaning record corresponding to the first historical immersion cleaning record in the historical fluorine oil ultrasonic cleaning record; The first historical ultrasonic cleaning record is added to the target historical record.

8. The fluorine oil cleaning method for precision electronics according to claim 1, characterized in that: The expression of the cleaning fitness function is as follows: Among them, f(x) refers to the fitness of the cleaning control data x, t(x), d(x) and r(x) respectively refer to the cleaning time, dryness after washing and dirt residue of the target precision electronic component under the cleaning control data x, a, b and c are all weight coefficients, and a+b+c=1.

9. The fluorine oil cleaning method for precision electronics according to claim 1, characterized in that: The method also includes: Acquiring an ultrasonic signal under the second cleaning control data; The ultrasonic signal is analyzed to obtain an ultrasonic vibration index, and the ultrasonic vibration index is used to perform feedback adjustment on the cleaning adaptability of the second cleaning control data.

10. Fluorine oil cleaning device for precision electronics, characterized in that: The system is used to implement the fluorine oil cleaning method for precision electronics according to any one of claims 1 to 9, comprising: A first feature acquisition module, the first feature acquisition module is used to acquire target component features of a target precision electronic component, the target component features including target contamination features and target material features; A first analysis module, the first analysis module is used to perform traversal analysis in a fluorine oil database using the target pollution characteristics and the target material characteristics as traversal constraints to determine a target fluorine oil; A first cleaning module, the first cleaning module is used to obtain first cleaning control data for immersing and cleaning the target precision electronic component with the target fluorine oil; a second analysis module, the second analysis module being used to analyze the first cleaning control data through an immersion cleaning evaluation model to obtain a first immersion cleaning cleanliness index of the target precision electronic component; A record screening module, the record screening module is used to screen the historical fluorine oil cleaning records by using the first immersion cleaning cleanliness index as an analogy screening constraint to obtain target historical records; A first optimization module, wherein the first optimization module is used to introduce a cleaning fitness function as an optimization evaluation function and use the target historical record as an optimization space to obtain second cleaning control data; A second cleaning module, wherein the second cleaning module is used to perform ultrasonic cleaning on the target precision electronic component according to the second cleaning control data.

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