Fluoro-oil cleaning method and apparatus for precision electronics

Abstract

The application discloses a fluorine oil cleaning method and device for precision electronics, and relates to the field of intelligent cleaning. The method comprises the following steps: collecting target element characteristics to determine target fluorine oil; obtaining first cleaning control data of the target fluorine oil for soaking and cleaning the target precision electronic element; analyzing the first cleaning control data through a soaking and cleaning evaluation model to obtain a first soaking and cleaning cleanliness index as an analog screening constraint; screening historical fluorine oil cleaning records to obtain target historical records; introducing a cleaning fitness function as an optimization evaluation function; and obtaining second cleaning control data from the target historical records as an optimization space to perform ultrasonic cleaning on the target precision electronic element. The method solves the technical problem that the conventional cleaning method for precision electronics cannot completely remove small stains or residues on the surface of precision electronic parts, resulting in poor cleaning effect, and effectively removes dirt on the surface of precision electronics without affecting the performance of the components.

Description

Technical Field

[0001] This application relates to the field of intelligent cleaning, and in particular to a fluorinated oil cleaning method and apparatus for precision electronics. Background Technology

[0002] During the manufacturing and repair of electronic equipment, various pollutants such as dust, oil, moisture, oxidizing agents, and corrosive gases can create "comprehensive contamination" of the internal circuitry, leading to performance degradation, failure, or other serious accidents. Furthermore, the electromagnetic field distribution during normal operation of communication equipment and the long-term friction accumulation in the ventilation system can cause "static electricity buildup," further exacerbating the equipment's failure rate. Traditional cleaning methods for precision electronics cannot thoroughly remove minute stains or residues from the surfaces of precision electronic components, resulting in poor cleaning effectiveness. Summary of the Invention

[0003] This application provides a fluorinated oil cleaning method and apparatus for precision electronics, which solves the technical problem that traditional cleaning methods for precision electronics cannot completely remove tiny stains or residues from the surface of precision electronic parts, resulting in poor cleaning effects. It achieves the technical effect of effectively removing dirt and grime from the surface of precision electronic parts, so that cleaning does not affect the performance of the components.

[0004] This application provides a fluorinated oil cleaning method for precision electronics. The method is applied to a fluorinated oil cleaning device for precision electronics and includes: collecting target component characteristics of a target precision electronic component, wherein the target component characteristics include target contamination characteristics and target material characteristics.

[0005] The target fluorinated oil is determined by performing a traversal analysis in the fluorinated oil database using the target pollution characteristics and the target material characteristics as traversal constraints.

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

[0007] The first cleaning control data is analyzed by an immersion cleaning evaluation model to obtain the first immersion cleaning cleanliness index of the target precision electronic component.

[0008] Using the first immersion cleaning cleanliness index as an analogy for screening historical fluorinated oil cleaning records, the target historical records are obtained.

[0009] A cleaning fitness function is introduced as an optimization evaluation function, and the target historical record is used as the optimization space to obtain the 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 process is performed: multiple pollution levels of various pollutants in the target pollution feature after weighted normalization are used to obtain the target pollution level value;

[0012] The target material compatibility value is obtained by taking multiple performance parameters corresponding to multiple material properties in the target material characteristics after weighted normalization.

[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 process is performed: extracting the first fluorinated oil type from the fluorinated oil database, wherein the first fluorinated oil type has a mapping relationship with the first fluorinated oil performance, and the first fluorinated oil performance includes the first fluorinated oil purity and the first fluorinated oil viscosity.

[0015] The first detergency value is obtained by weighted and normalized purity and viscosity of the first fluorinated oil.

[0016] Obtain the first material compatibility value for the first type of fluorinated oil;

[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 fluorinated oil type is taken as the target fluorinated oil.

[0018] In a possible implementation, the following process is performed: obtaining historical fluorinated oil immersion cleaning records from the historical fluorinated oil cleaning records, wherein the historical fluorinated oil immersion cleaning records include a first historical immersion cleaning record;

[0019] Read the predetermined soaking index, and filter the first historical soaking and cleaning records based on the predetermined soaking index to obtain the first historical cleaning control data;

[0020] Read the predetermined cleanliness characteristics, and filter the first historical soaking and cleaning records based on the predetermined cleanliness characteristics to obtain the first historical cleanliness characteristic data;

[0021] The first historical cleanliness characteristic data is analyzed to obtain the first historical soaking and cleaning cleanliness index, and it is combined with the first historical cleaning control data to form the first historical data group.

[0022] The first historical data set was subjected to supervised training and learning, and the obtained soaking and cleaning evaluation model was tested.

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

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

[0025] In a possible implementation, the following process is performed: acquiring historical ultrasonic cleaning records of fluorinated oil from the historical fluorinated oil cleaning records;

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

[0027] Add the first historical ultrasonic cleaning record to the target historical record.

[0028] In a possible implementation, the following process is performed: acquiring the ultrasonic signal under the second cleaning control data;

[0029] The ultrasonic vibration index is obtained by analyzing the ultrasonic signal, and the cleaning adaptability of the second cleaning control data is adjusted based on the ultrasonic vibration index.

[0030] This application also provides a fluorinated oil cleaning device 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;

[0031] The first analysis module is used to perform traversal analysis in the fluorinated oil database using the target pollution characteristics and the target material characteristics as traversal constraints to determine the target fluorinated oil.

[0032] The first cleaning module is used to acquire first cleaning control data for immersing the target precision electronic component in the target fluorinated oil for cleaning.

[0033] The second analysis module is used to analyze the first cleaning control data through an immersion cleaning evaluation model to obtain the first immersion cleaning cleanliness index of the target precision electronic component.

[0034] The record filtering module is used to filter historical fluorinated oil cleaning records by analogy with the first soaking and cleaning cleanliness index to obtain target historical records.

[0035] The first optimization module is used to introduce a cleaning fitness function as an optimization evaluation function and use the target historical record as the optimization space to obtain the second cleaning control data.

[0036] The second cleaning module is used to perform ultrasonic cleaning on the target precision electronic component according to the second cleaning control data.

[0037] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0038] The fluorinated oil cleaning method and apparatus for precision electronics provided in this application relate to the field of intelligent cleaning technology. It solves the technical problem that traditional cleaning methods for precision electronics cannot completely remove tiny stains or residues from the surface of precision electronic parts, resulting in poor cleaning effects. It achieves the technical effect of effectively removing dirt and grime from the surface of precision electronic components, so that cleaning does not affect the performance of the components. Attached Figure Description

[0039] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the apparatus according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0040] Figure 1 A schematic flowchart of a fluorinated oil cleaning method for precision electronics provided in an embodiment of this application;

[0041] Figure 2 This is a schematic diagram of the structure of a fluorinated oil cleaning device for precision electronics provided in an embodiment of this application. Detailed Implementation

[0042] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application.

[0043] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application will be provided in conjunction with the accompanying drawings. The described embodiments should not be considered as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0044] In the following description, references to "some embodiments" describe a subset of all possible embodiments. However, it is understood that "some embodiments" may be the same or different subsets of all possible embodiments and may be combined with each other without conflict. The terms "first" and "second" are used merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or apparatuses. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.

[0045] This application provides a fluorinated oil cleaning method for precision electronics, wherein the method is applied to a fluorinated oil cleaning device for precision electronics, such as... Figure 1 As shown, the method includes:

[0046] Step A100: Collect target component characteristics of the target precision electronic component. The target component characteristics include target contamination characteristics and target material characteristics. The target precision electronic component is determined 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, usage environment, and known contamination types, which helps to better obtain the potential contamination and material characteristics of the target component.

[0047] Furthermore, the target components can be visually inspected, and the observed types of contamination (such as dust, grease, oxides, etc.), degree of contamination, and distribution can be recorded simultaneously. Surface sampling, solution extraction, chromatographic analysis, and other methods can be used to sample and analyze contaminants on the surface of the target components using chemical reagents to determine the chemical composition and properties of the contaminants. Additionally, the target contamination characteristics on the surface of the precision electronic components can be collected by measuring the physical properties of the contaminants (such as hardness, adhesion, etc.).

[0048] Furthermore, the materials of the target components can be identified using material analysis instruments (such as energy dispersive spectroscopy, X-ray diffractometer, etc.) to determine their basic information such as chemical composition and crystal structure. The material properties of the target precision electronic components can also be obtained by measuring their physical properties (such as hardness, elastic modulus, coefficient of thermal expansion, etc.). The collected target contamination characteristics and target material characteristics data can be organized and analyzed to form a complete target component characteristic database, and the target component characteristics can be output.

[0049] Step A200 involves performing a traversal analysis in the fluorinated oil database using the target pollution characteristics and the target material characteristics as traversal constraints to determine the target fluorinated oil. In one possible implementation, step A200 further includes step A210, where multiple pollution levels of various pollutants in the weighted and normalized target pollution characteristics are used to obtain a target pollution level value. Step A220 involves performing a weighted and normalized analysis of multiple performance parameters corresponding to multiple material properties in the target material characteristics to obtain a target material compatibility value. Step A230 involves using the target pollution level value and the target material compatibility value as the traversal constraints.

[0050] Using the target pollution characteristics and target material characteristics obtained above as traversal constraints means that the target pollution characteristics and target material characteristics are weighted and normalized respectively. The process can be as follows: Based on the target pollution characteristics, the types of pollutants (such as dust, grease, oxides, etc.) present on the target component and the degree of pollution of each pollutant are determined. Then, according to the degree of influence of each pollutant on the component performance, a corresponding weight is set. The larger the weight set, the greater the influence of the pollutant on the component performance. Finally, the degree of pollution of each pollutant is multiplied by its corresponding weight, and then all weighted pollution degree values ​​are added together to obtain the total pollution degree value. Finally, the total pollution degree value is divided by the sum of all weights to obtain the normalized target pollution degree value.

[0051] Next, based on the characteristics of the target material, the material performance parameters of the target component, such as hardness, elastic modulus, and coefficient of thermal expansion, are determined. Then, according to the degree of influence of each performance parameter on the cleaning process, a corresponding weight is assigned. The larger the assigned weight, 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 all weighted performance parameter values ​​are summed to obtain the total material performance value. Finally, the total material performance value is divided by the sum of all weights to obtain the normalized target material compatibility value.

[0052] Ultimately, the target contamination level and target material compatibility value can be used as constraints to iterate through the cleaning solutions. This means that cleaning agents and cleaning processes that can effectively remove the corresponding contaminants can be selected based on the target contamination level; at the same time, cleaning agents and cleaning processes that do not damage or cause minimal damage to the target component materials can be selected based on the target material compatibility value.

[0053] In the process of determining the target fluorinated oil through traversal analysis of the fluorinated oil database based on traversal constraints, we need to screen and evaluate the fluorinated oils in the database based on the previously calculated target contamination level value (representing the contamination status of the target component) and target material compatibility value (representing the compatibility of the target component material with the cleaning agent). In one possible implementation, step A200 further includes step A240, extracting the first fluorinated oil type from the fluorinated oil database. The first fluorinated oil type has a mapping relationship with the first fluorinated oil performance, which includes the first fluorinated oil purity and the first fluorinated oil viscosity. Step A250 is then executed to perform weighted normalization of the first fluorinated oil... The first cleaning ability value is obtained from the purity of the oil and the viscosity of the first fluorinated oil. The first fluorinated oil type is searched and extracted from the fluorinated oil database, and the first fluorinated oil type has a mapping relationship with the performance of the first fluorinated oil. Then, the purity and viscosity of the first fluorinated oil associated with the first fluorinated oil type are retrieved from the database. The purity of the first fluorinated oil refers to the content of the effective components in the first fluorinated oil type. The higher the content of the effective components, the better the quality of the fluorinated oil. The viscosity of the first fluorinated oil refers to the physical quantity of the intermolecular interaction force within the first fluorinated oil type. The viscosity of the first fluorinated oil can resist shear deformation and cause viscous resistance. Furthermore, a weight value is set according to the degree of influence of the purity of the first fluorinated oil on the cleaning ability of the fluorinated oil. Higher purity means fewer impurities in the fluorinated oil, resulting in better cleaning ability. Based on the influence of the viscosity of the first fluorinated oil on its cleaning ability, another weight value is set. The appropriate range of the viscosity of the first fluorinated oil is crucial to ensuring that the fluorinated oil can fully penetrate and remove contaminants. Furthermore, the purity and viscosity of the first fluorinated oil are multiplied by their corresponding weights to obtain the weighted value of the purity and the weighted value of the viscosity of the first fluorinated oil. Finally, the two weighted values ​​are added together and then divided by the sum of the two weights to obtain the normalized first cleaning ability value.

[0054] Execute step A260 to obtain the first material compatibility value of the first fluorinated 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, the first fluorinated oil type is taken as the target fluorinated oil.

[0055] Based on the first fluorinated oil type, the fluorinated oil database is traversed to obtain the first material compatibility value corresponding to the first fluorinated oil type. The first material compatibility value is used to characterize the compatibility of the fluorinated oil with specific materials (such as the material of the target electronic component). Then, based on the known purity and viscosity of the first fluorinated oil, and the previously set weights, a weighted normalization method is used to calculate the first cleaning ability value. The calculated first cleaning ability value is compared with the target contamination level value in the traversal constraints, and the extracted first material compatibility value is compared with the target material compatibility value in the traversal constraints. If the first cleaning ability value is less than the target contamination level value, and / or the first material compatibility value is greater than or equal to the target material compatibility value, then the first fluorinated oil type is considered not to meet the conditions and cannot be used as the target fluorinated oil. At the same time, backtracking is performed to update the first cleaning ability value and the first material compatibility value and compare them again. If the first cleaning ability value is greater than or equal to the target contamination level value, and the first material compatibility value is greater than or equal to the target material compatibility value, then the first fluorinated oil type is considered to meet the conditions. When the first fluorinated oil type meets the above conditions, it is determined as the target fluorinated oil.

[0056] Step A300 involves acquiring first cleaning control data for immersion cleaning of the target precision electronic component using the target fluorinated oil. Based on the characteristics of the target fluorinated oil, such as cleaning ability, temperature range, and chemical stability, the optimal operating temperature and immersion time range can be determined. Furthermore, the material of the target precision electronic component is analyzed to ensure it does not chemically react with or become damaged by the fluorinated oil. Simultaneously, the component's structure and dimensions are evaluated to determine the immersion method and container selection. The immersion cleaning steps are further designed, including pretreatment of the target precision electronic component (e.g., removal of large particulate matter), immersion, rinsing, and drying, and the immersion cleaning sequence is determined. If multiple target precision electronic components require cleaning, batch processing may be considered.

[0057] Further determination of the cleaning control parameters for the target precision electronic components is required. The determined cleaning control parameters may include temperature parameters, time parameters, stirring parameters, rinsing parameters, drying parameters, etc. Before actual cleaning, a small number of components can be used for trial cleaning to verify the effectiveness of the cleaning control data, thereby outputting the first cleaning control data.

[0058] Step A400 involves analyzing the first cleaning control data using an immersion cleaning evaluation model to obtain a first immersion cleaning cleanliness index for the target precision electronic component. In one possible implementation, step A400 further includes step A410, acquiring historical fluorinated oil immersion cleaning records from the historical fluorinated oil cleaning records, wherein the historical fluorinated oil immersion cleaning records include a first historical immersion cleaning record. Step A420 involves reading a predetermined immersion index and filtering the first historical immersion cleaning records based on the predetermined immersion index to obtain first historical cleaning control data. In one possible implementation, step A420 further includes step A421, wherein the predetermined immersion index includes immersion temperature and immersion duration.

[0059] Retrieve all records related to immersion cleaning from the historical fluorinated oil cleaning record database. Records retrieved are designated as historical fluorinated oil immersion cleaning records. These records may include information such as fluorinated oil type, type of precision electronic component being cleaned, cleaning conditions (e.g., temperature, duration), and cleaning effect. The historical fluorinated oil immersion cleaning records include first historical immersion cleaning records, which are records among all historical immersion cleaning records that are similar to or identical to the current target fluorinated oil and target precision electronic component.

[0060] Furthermore, predetermined immersion indicators are read. These predetermined immersion indicators are set before the cleaning operation and are used to guide the screening of historical cleaning records. The predetermined immersion indicators may include immersion temperature and immersion time. Immersion temperature refers to the temperature parameter of the target precision electronic component during the immersion process, and immersion time refers to the total immersion time of the target precision electronic component in the target fluorinated oil. The predetermined immersion indicators (such as immersion temperature and immersion time) are used as screening conditions to screen the first historical immersion cleaning records. For historical immersion records whose immersion temperature and immersion time are consistent with or close to the predetermined indicators, the first cleaning control data is extracted from the screened first historical immersion cleaning records. The first cleaning control data may include immersion temperature, immersion time, stirring speed, cleaning steps, etc.

[0061] Execute step A430, read the predetermined cleanliness characteristics, and filter the first historical soaking and cleaning records based on the predetermined cleanliness characteristics to obtain the first historical cleanliness characteristic data; in one possible implementation, step A430 further includes step A431, where the predetermined cleanliness characteristics refer to the type and amount of residue.

[0062] First, the predetermined cleanliness characteristics are read. The predetermined cleanliness characteristics are usually the standards that are expected to be achieved during the cleaning process, such as the upper limit of specific types of residues and their residual amounts. The predetermined cleanliness characteristics are the types of residues and their residual amounts. All records related to immersion cleaning are retrieved from the historical fluorinated oil cleaning record database. These records may include information such as the types and amounts of residues before and after cleaning, as well as cleaning conditions. Among all historical immersion cleaning records, records that are similar to or the same as the current target fluorinated oil and target precision electronic components are identified as the first historical immersion cleaning record.

[0063] Further, the first historical soaking and cleaning records are screened using predetermined cleanliness characteristics (such as the types of residues and their upper limits) as screening criteria. Records that meet the predetermined cleanliness characteristics requirements after cleaning are obtained. Relevant cleanliness characteristic data are extracted from the screened first historical soaking and cleaning records and recorded as the first historical cleanliness characteristic data. This data may include the types and amounts of residues before and after cleaning, as well as the corresponding cleaning conditions (such as soaking temperature, duration, etc.).

[0064] Execute step A440, analyze the first historical clean feature data to obtain the first historical soaking cleaning cleanliness index, and form a first historical data group with the first historical cleaning control data; execute step A450, perform supervised training on the first historical data group, and verify the obtained soaking cleaning evaluation model.

[0065] This study analyzes the types and amounts of residues after cleaning contained in the first historical cleanliness feature data. Based on these residue types and amounts, one or more cleanliness indicators are defined, such as total residue amount or specific residue proportion. A cleanliness index is then calculated for each historical record. This index can be a score from 0 to 10. Simultaneously, the first historical cleaning control data (such as soaking temperature and duration) for each historical record is paired with its corresponding cleanliness index to obtain a dataset containing multiple samples, i.e., the first historical data set. Each sample contains a cleaning control data-cleanliness index pair. The majority of the data in the first historical data set is used as the training set to train the model to learn the relationship between cleaning control data and the cleanliness index. The remaining data is used as a validation or test set to evaluate the model's performance. Various metrics, such as mean squared error, can be used to evaluate the model's performance on the validation or test set, verifying the generalization ability of the immersion cleaning evaluation model. Once the immersion cleaning evaluation model passes validation, it is output.

[0066] Analyzing the first cleaning control data using the immersion cleaning evaluation model means taking the first cleaning control data as input and passing it to the trained immersion cleaning evaluation model. The immersion cleaning evaluation model will predict the corresponding cleanliness index based on the input cleaning control data and using the mapping relationship or rules it has learned internally. The result output by the model 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.

[0067] Next, step A500 is executed, where historical fluorinated oil cleaning records are filtered using the first immersion cleaning cleanliness index as an analogy screening constraint to obtain target historical records. A screening threshold is set based on the first immersion cleaning cleanliness index. The set screening threshold can be used to select records from historical fluorinated oil cleaning records that are similar to or better than the current target cleanliness level. At the same time, the historical fluorinated oil cleaning record database is organized to ensure that each historical fluorinated oil cleaning record contains cleaning control data and corresponding cleanliness characteristic data (such as the type and amount of residue after cleaning). Furthermore, the calculated historical cleanliness index is compared with the set screening threshold, and those historical records whose cleanliness index meets or exceeds the screening threshold are selected and recorded as target historical records for output.

[0068] Step A600 involves introducing a cleaning fitness function as an optimization evaluation function and using the target historical record as the optimization space to obtain second cleaning control data. In one possible implementation, by introducing the cleaning fitness function as the optimization evaluation function, step A600 further includes step A610, obtaining historical fluorinated oil ultrasonic cleaning records from the historical fluorinated oil cleaning records. Step A620 involves matching the first historical ultrasonic cleaning record corresponding to the first historical immersion cleaning record in the historical fluorinated oil ultrasonic cleaning records when the difference between the first historical immersion cleaning cleanliness index and the first historical immersion cleaning cleanliness index is within a predetermined difference limit. Step A630 involves adding the first historical ultrasonic cleaning record to the target historical record.

[0069] First, all records related to ultrasonic cleaning are retrieved from the historical fluorinated oil cleaning record database, i.e., historical fluorinated oil ultrasonic cleaning records. These records may include ultrasonic cleaning parameters (such as power, frequency, duration, etc.) and post-cleaning cleanliness characteristics data. Then, the difference between the first historical immersion cleaning cleanliness index and the current or latest first immersion cleaning cleanliness index is calculated. This difference is used to characterize the difference between the historical cleaning effect and the current or latest cleaning effect. The first historical immersion cleaning cleanliness index and the index difference of the first immersion cleaning cleanliness index are compared with a predetermined difference limit. When the index difference is within the predetermined difference limit, the historical immersion cleaning effect is considered to be similar to the current or latest immersion cleaning effect. At the same time, in the historical fluorinated oil ultrasonic cleaning records, by comparing parameters such as the type of component cleaned, the degree of contamination, and the cleaning time, historical records similar to the first historical immersion cleaning record, i.e., the current or latest immersion cleaning effect, are searched. Corresponding or similar first historical ultrasonic cleaning records are then added to the target historical records. The target historical records can be used as part of the optimization space for subsequent optimization or analysis.

[0070] Furthermore, a search space is constructed using target historical records (including first historical immersion cleaning records and corresponding first historical ultrasonic cleaning records). The constructed search space is a dataset containing multiple historical cleaning records, which includes cleaning effects under different cleaning parameters and conditions. Then, an initial set of cleaning control data is randomly selected or generated in the search space as a candidate solution set. The candidate solution set is a dataset that can cover different areas in the search space. The candidate solutions can then be applied to the cleaning process through simulation or actual experiments, and data such as cleanliness and cleaning time after cleaning are collected. For each candidate solution, i.e., a set of cleaning control data, a cleaning fitness function is used to evaluate its corresponding cleaning effect. The candidate solutions are applied to the cleaning process (which can be achieved through simulation or actual experiments), and data such as cleanliness and cleaning time after cleaning are collected. The fitness value of each candidate solution is calculated according to the cleaning fitness function. Based on this, 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 through optimization algorithms in the search space composed of target historical records, which is expected to achieve better cleaning effects in the actual cleaning process.

[0071] In one possible implementation, step A600 further includes step A650, acquiring the ultrasonic signal under the second cleaning control data; executing step 660, analyzing the ultrasonic signal to obtain the ultrasonic vibration index, and using the ultrasonic vibration index to make feedback adjustments to the cleaning adaptability of the second cleaning control data.

[0072] By connecting the signal output port of the ultrasonic cleaning equipment to the data acquisition system, the ultrasonic signals generated by the ultrasonic cleaning equipment can be recorded during the cleaning operation using the second cleaning control data. The acquired ultrasonic signals can be processed and analyzed, including signal preprocessing (such as filtering and amplification), feature extraction, and parameter calculation. Furthermore, the ultrasonic vibration index can be calculated based on parameters such as amplitude, frequency, and duration in the signal. The ultrasonic vibration index is closely related to the ultrasonic cleaning effect and 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.

[0073] 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 weight of relevant parameters in the cleaning fitness function, adding new evaluation indicators, or adjusting the threshold of the evaluation criteria.

[0074] Finally, step A700 is executed, in which the target precision electronic component is ultrasonically cleaned according to the second cleaning control data.

[0075] Based on the second cleaning control data, the corresponding cleaning solution is obtained to ensure that the cleaning solution is compatible with the material of the target precision electronic component. The temperature, concentration, and other parameters of the cleaning solution are adjusted according to the requirements in the second cleaning control data. Furthermore, the ultrasonic cleaner is set up. The setting process may be as follows: the target precision electronic component is gently placed into the cleaning tank, ensuring that the component does not violently collide with the bottom or side wall of the cleaning tank. The prepared cleaning solution is poured in, ensuring that the liquid level does not exceed the maximum capacity mark of the cleaning tank. Further, based on the second cleaning control data, the power, frequency, time, and other parameters of the ultrasonic cleaner are adjusted, and ultrasonic cleaning is started. At the same time, in order to maintain the accuracy and consistency of the data, the testing equipment and methods should be calibrated and maintained regularly to achieve the technical effect of effectively removing dirt and contaminants from the surface of precision electronic components, so that the cleaning does not affect the performance of the components.

[0076] This application addresses the technical problem that traditional cleaning methods for precision electronics cannot completely remove minute stains or residues from the surface of precision electronic components, resulting in poor cleaning effects. It achieves the technical effect of effectively removing dirt and grime from the surface of precision electronic components, ensuring that cleaning does not affect the performance of the components.

[0077] In the above text, refer to Figure 1A fluorinated oil cleaning method for precision electronics according to embodiments of the present invention has been described in detail. Next, reference will be made to... Figure 2 A fluorinated oil cleaning apparatus for precision electronics is described according to an embodiment of the present invention.

[0078] The fluorinated oil cleaning device for precision electronics according to embodiments of the present invention addresses the technical problem that traditional cleaning methods for precision electronics cannot thoroughly remove minute stains or residues from the surface of precision electronic components, resulting in poor cleaning effects. The device effectively removes dirt and contaminants from the surface of precision electronic components, ensuring that cleaning does not affect the performance of the components. The fluorinated oil cleaning device 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 recording and screening module 50, a first optimization module 60, and a second cleaning module 70.

[0079] The first feature acquisition module 10 is used to acquire the target component features of the target precision electronic component, the target component features including target contamination features and target material features;

[0080] The first analysis module 20 is used to perform traversal analysis in the fluorinated oil database using the target pollution characteristics and the target material characteristics as traversal constraints to determine the target fluorinated oil.

[0081] The first cleaning module 30 is used to acquire first cleaning control data for immersing the target precision electronic component in the target fluorinated oil for cleaning.

[0082] The second analysis module 40 is used to analyze the first cleaning control data through an immersion cleaning evaluation model to obtain the first immersion cleaning cleanliness index of the target precision electronic component.

[0083] The record filtering module 50 is used to filter historical fluorinated oil cleaning records by analogy with the first soaking and cleaning cleanliness index to obtain target historical records.

[0084] 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 the optimization space to obtain the second cleaning control data.

[0085] The second cleaning module 70 is used to perform ultrasonic cleaning on the target precision electronic component according to the second cleaning control data.

[0086] The specific configuration of the first analysis module 20 will be described in detail below. As mentioned above, the first analysis module 20 may further include: a first calculation unit for obtaining a target pollution degree value by weighting and normalizing multiple pollution degrees of multiple pollutants in the target pollution feature; a second calculation unit for obtaining a target material compatibility value by weighting and normalizing multiple performance parameters corresponding to multiple material properties in the target material feature; and a first traversal unit for using the target pollution degree value and the target material compatibility value as the traversal constraints.

[0087] The specific configuration of the first cleaning module 30 will be described in detail below. As mentioned above, the first cleaning module 30 may further include: a first extraction unit for extracting a first fluorinated oil type from the fluorinated oil database, wherein the first fluorinated oil type has a mapping relationship with the first fluorinated oil performance, and the first fluorinated oil performance includes the first fluorinated oil purity and the first fluorinated oil viscosity; a third calculation unit for obtaining a first cleaning ability value by weighting and normalizing the first fluorinated oil purity and the first fluorinated oil viscosity; a compatibility value acquisition unit for obtaining a first material compatibility value of the first fluorinated oil type; and a first judgment unit for determining the first fluorinated oil type as the target fluorinated oil when the first cleaning ability value is greater than or equal to the target contamination degree 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.

[0088] The specific configuration of the second analysis module 40 will be described in detail below. As mentioned above, the second analysis module 40 may further include: a first record acquisition unit for acquiring historical fluorinated oil immersion cleaning records from the historical fluorinated oil cleaning records, the historical fluorinated oil immersion cleaning records including first historical immersion cleaning records; a first reading unit for reading predetermined immersion indicators and filtering the first historical immersion cleaning records based on the predetermined immersion indicators to obtain first historical cleaning control data; a second reading unit for reading predetermined cleanliness characteristics and filtering the first historical immersion cleaning records based on the predetermined cleanliness characteristics to obtain first historical cleanliness characteristic data; a third analysis unit for analyzing the first historical cleanliness characteristic data to obtain a first historical immersion cleaning cleanliness index, and forming a first historical data group with the first historical cleaning control data; and a learning unit for performing supervised training on the first historical data group and verifying the obtained immersion cleaning evaluation model.

[0089] The specific configuration of the first reading unit will be described in detail below. As mentioned above, the first reading unit may further include: an index unit for the predetermined soaking index, including soaking temperature and soaking time.

[0090] The specific configuration of the second reading unit will be described in detail below. As mentioned above, the second reading unit may further include: a feature unit for the predetermined cleanliness feature, which refers to the type and amount of residue.

[0091] The specific configuration of the first optimization module 60 will be described in detail below. As mentioned above, the first optimization module 60 may further include: a second record acquisition unit for acquiring historical fluorinated oil ultrasonic cleaning records from the historical fluorinated oil cleaning records; a first matching unit for matching the first historical ultrasonic cleaning record corresponding to the first historical immersion cleaning record in the historical fluorinated oil ultrasonic cleaning records when the 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.

[0092] The specific configuration of the first optimization module 60 will be described in detail below. As mentioned above, the first optimization module 60 may further include: a signal acquisition unit for acquiring ultrasonic signals under the second cleaning control data; and a fourth analysis unit for analyzing the ultrasonic signals to obtain an ultrasonic vibration index, and using the ultrasonic vibration index to provide feedback adjustment to the cleaning adaptability of the second cleaning control data.

[0093] The fluorinated oil cleaning device for precision electronics provided in this embodiment of the invention can perform the fluorinated oil cleaning method for precision electronics provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for performing the method.

[0094] Although this application makes various references to certain modules in the apparatus according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. 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 each functional unit are only for easy distinction between each other and are not intended to limit the scope of protection of this invention.

[0095] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand 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 within the scope of protection of this application.

Claims

1. A fluorinated oil cleaning method for precision electronics, characterized in that, include: Collect target component characteristics of the target precision electronic component, including target contamination characteristics and target material characteristics; The target fluorinated oil is determined by performing a traversal analysis in the fluorinated oil database using the target pollution characteristics and the target material characteristics as traversal constraints. Acquire first cleaning control data for immersing and cleaning the target precision electronic component with the target fluorinated oil; The first cleaning control data is analyzed by an immersion cleaning evaluation model to obtain the first immersion cleaning cleanliness index of the target precision electronic component. Using the first immersion cleaning cleanliness index as an analogy for screening historical fluorinated oil cleaning records, the target historical records are obtained. A cleaning fitness function is introduced as an optimization evaluation function, and the target historical record is used as the optimization space to obtain the second cleaning control data; The target precision electronic component is ultrasonically cleaned according to the second cleaning control data.

2. The fluorinated oil cleaning method for precision electronics according to claim 1, characterized in that the method... include: The target pollution level value is obtained by weighting and normalizing multiple pollution levels of various pollutants in the target pollution characteristics; The target material compatibility value is obtained by taking multiple performance parameters corresponding to multiple material properties in the target material characteristics after weighted normalization. The target contamination level value and the target material compatibility value are used as the traversal constraints.

3. The fluorinated oil cleaning method for precision electronics according to claim 2, characterized in that the method... include: Extract the first fluorinated oil type from the fluorinated oil database. The first fluorinated oil type has a mapping relationship with the first fluorinated oil performance, which includes the first fluorinated oil purity and the first fluorinated oil viscosity. The first detergency value is obtained by weighted and normalized purity and viscosity of the first fluorinated oil. Obtain the first material compatibility value for the first type of fluorinated 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, the first fluorinated oil type is taken as the target fluorinated oil.

4. The fluorinated oil cleaning method for precision electronics according to claim 1, characterized in that the method... include: Obtain the historical fluorinated oil immersion cleaning record from the historical fluorinated oil cleaning record, the historical fluorinated oil immersion cleaning record including the first historical immersion cleaning record; Read the predetermined soaking index, and filter the first historical soaking and cleaning records based on the predetermined soaking index to obtain the first historical cleaning control data; Read the predetermined cleanliness characteristics, and filter the first historical soaking and cleaning records based on the predetermined cleanliness characteristics to obtain the first historical cleanliness characteristic data; The first historical cleanliness characteristic data is analyzed to obtain the first historical soaking and cleaning cleanliness index, and it is combined with the first historical cleaning control data to form the first historical data group. The first historical data set was subjected to supervised training and learning, and the obtained soaking and cleaning evaluation model was tested.

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

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

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

8. The fluorinated oil cleaning method for precision electronics according to claim 1, characterized in that, The method also includes: Acquire the ultrasonic signal under the second cleaning control data; The ultrasonic vibration index is obtained by analyzing the ultrasonic signal, and the cleaning adaptability of the second cleaning control data is adjusted based on the ultrasonic vibration index.

9. A fluorinated oil cleaning device for precision electronics, characterized in that, The apparatus is used to implement the fluorinated oil cleaning method for precision electronics according to any one of claims 1-8, comprising: A 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; The first analysis module is used to perform traversal analysis in the fluorinated oil database using the target pollution characteristics and the target material characteristics as traversal constraints to determine the target fluorinated oil. The first cleaning module is used to acquire first cleaning control data for immersing the target precision electronic component in the target fluorinated oil for cleaning. The second analysis module is used to analyze the first cleaning control data through an immersion cleaning evaluation model to obtain the first immersion cleaning cleanliness index of the target precision electronic component. The record filtering module is used to filter historical fluorinated oil cleaning records by analogy with the first soaking and cleaning cleanliness index to obtain target historical records. The first optimization module is used to introduce a cleaning fitness function as an optimization evaluation function and use the target historical record as the optimization space to obtain the second cleaning control data. 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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