Method for improving efficient cleaning of intelligent gold bonding wire cleaning system

Abstract

The invention relates to the technical field of gold bonding wires, and discloses a method for improving efficient cleaning of an intelligent gold bonding wire cleaning system, and the method comprises the steps: calculating the cleaning rate of a cleaning object in a cleaning node; cleaning influence factors of the cleaning objects in the cleaning nodes are excavated, and parameter adjustment is performed on node parameters so as to execute optimization processing on the cleaning process to obtain an optimized process; screening out key data from the cleaned data, and dividing the key data into external data and internal data; calculating the surface cleaning degree of the cleaning equipment when the cleaning equipment performs cleaning treatment on the cleaning object, and calculating the internal cleaning degree of the cleaning equipment when the cleaning equipment performs cleaning treatment on the cleaning object; and adjusting equipment parameters of the cleaning equipment when the cleaning equipment performs cleaning treatment on the cleaning object to perform equipment optimization on the cleaning equipment to obtain optimized equipment, and generating an optimized gold bonding wire cleaning method. The intelligent gold bonding wire cleaning system mainly aims at solving the problem that an intelligent gold bonding wire cleaning system is low in cleaning efficiency.

Description

Technical Field

[0001] The invention relates to a method for improving the efficient cleaning of an intelligent gold bonding wire cleaning system, and belongs to the technical field of gold bonding wires. Background Art

[0002] The intelligent gold bonding wire cleaning system is a device that combines chemical cleaning with mechanical cleaning to clean contaminants on the surface of gold bonding wires. It can quickly and thoroughly remove dirt and impurities on the gold bonding wires. However, due to the low utilization rate of the cleaning system and the aging of some cleaning equipment, the cleaning efficiency and quality are difficult to guarantee. The cleaning efficiency of the intelligent gold bonding wire cleaning system can be improved to increase the utilization rate of the cleaning system.

[0003] At present, the cleaning efficiency of the intelligent bonding wire cleaning system can be improved by improving the cleaning process. However, when using the cleaning equipment, some factors affect the cleaning parameters of the cleaning equipment, resulting in a problem of too low cleaning rate, which leads to low cleaning efficiency of the intelligent bonding wire cleaning system. Therefore, a method is needed to improve the high-efficiency cleaning efficiency of the intelligent bonding wire cleaning system. Summary of the invention

[0004] The present invention provides a method for improving the cleaning efficiency of an intelligent gold bonding wire cleaning system, and its main purpose is to solve the problem of low cleaning efficiency of the intelligent gold bonding wire cleaning system.

[0005] To achieve the above object, the present invention provides a method for improving the efficient cleaning of an intelligent bonding wire cleaning system, comprising:

[0006] Acquire a bonding wire cleaning system to be optimized and a cleaning object thereof, and identify a cleaning process and a cleaning device when the bonding wire cleaning system is used to clean the cleaning object;

[0007] Identifying a cleaning node of the cleaning process, extracting node parameters of the cleaning node, and calculating a cleaning rate of the cleaning object in the cleaning node based on the node parameters;

[0008] When the cleaning rate is less than a preset threshold, based on the node parameters, the cleaning influencing factors of the cleaning objects in the cleaning nodes are mined, and according to the cleaning influencing factors, the node parameters are adjusted to perform optimization processing on the cleaning process to obtain an optimized process;

[0009] Collecting cleaning data when the cleaning device performs cleaning processing on the cleaning object, and calculating the data entropy of each data in the cleaning data, screening out key data from the cleaning data according to the data entropy, and dividing the key data into external data and internal data;

[0010] Calculating the surface cleaning degree of the cleaning device when performing the cleaning process on the cleaning object based on the external data, and calculating the internal cleaning degree of the cleaning device when performing the cleaning process on the cleaning object based on the internal data, and analyzing the cleaning effect of the cleaning device when performing the cleaning process on the cleaning object according to the surface cleaning degree and the internal cleaning degree;

[0011] When the cleaning effect does not meet the preset effect, the equipment parameters of the cleaning equipment when performing the cleaning process on the cleaning object are adjusted to perform equipment optimization of the cleaning equipment to obtain an optimized equipment, and based on the optimization process and the optimized equipment, an optimized bonding wire cleaning method is generated.

[0012] Optionally, the identifying a cleaning process and a cleaning device when the cleaning object is cleaned by the bonding wire cleaning system includes:

[0013] Querying the operation scenario corresponding to the cleaning object, and identifying the environmental factors in the operation scenario;

[0014] Based on the environmental factors, analyzing the scenario characteristics corresponding to the operating scenario;

[0015] Based on the scene characteristics, determining the cleaning standard corresponding to the cleaning object;

[0016] Obtaining system cleaning equipment in the bonding wire cleaning system and its corresponding cleaning effect description;

[0017] Calculating the adaptation index between the cleaning performance description and the cleaning standard, and performing equipment screening processing on the system cleaning equipment based on the adaptation index to obtain target cleaning equipment;

[0018] Analyzing a device interaction mode between the target cleaning devices, and determining a device cleaning logic corresponding to the target cleaning device based on the device interaction mode;

[0019] By combining the equipment cleaning logic and the target cleaning equipment, a cleaning process and a cleaning equipment are obtained when the bonding wire cleaning system performs a cleaning process on the cleaning object.

[0020] Optionally, the calculating the adaptation index between the cleaning effectiveness description and the cleaning standard includes:

[0021] Recognize the character information in the cleaning performance description and the cleaning standard to obtain description character information and standard character information;

[0022] Respectively extracting the representation information in the explanatory character information and the standard character information to obtain first representation information and second representation information;

[0023] The information adaptability between the first representation information and the second representation information is calculated by the following formula:

[0024]

[0025] Where A represents the information adaptability between the first representation information and the second representation information, n represents the comparison frequency between the first representation information and the second representation information, and B a represents the information value corresponding to the ath information in the first representation information, a represents the sequence number of the first representation information, C b represents the information value corresponding to the bth information in the second representation information, b represents the sequence number corresponding to the second representation information, MAX(B a , C b ) represents taking the maximum value of the information value corresponding to the a-th information in the first representation information and the information value corresponding to the b-th information in the second representation information;

[0026] Based on the information fit, a fit index between the cleaning performance description and the cleaning standard is calculated.

[0027] Optionally, the calculating, based on the node parameter, a cleaning rate of the cleaning object in the cleaning node includes:

[0028] Extracting the cleaning time, cleaning temperature, initial quality and cleaning quality of the cleaning object from the node parameters;

[0029] In combination with the cleaning time, the cleaning temperature, the initial mass and the cleaning mass, the cleaning rate of the cleaning object in the cleaning node is calculated using the following formula:

[0030]

[0031] Wherein, D represents the cleaning rate of the cleaning object in the cleaning node, E represents the initial quality, Indicates the cleaning quality, F indicates the cleaning temperature, represents the reference cleaning temperature, G represents the cleaning time, Indicates reference cleaning time.

[0032] Optionally, combining the node parameter and the cleaning rate to mine the cleaning influencing factor of the cleaning object in the cleaning node includes:

[0033] Extracting parameter labels corresponding to the node parameters, performing dimensionality reduction processing on the parameter labels, and obtaining target parameter labels;

[0034] Calculating the correlation coefficient between the target parameter label and the cleaning object, and constructing a cleaning correlation matrix corresponding to the target parameter label by combining the correlation coefficient and the cleaning rate;

[0035] Calculate the matrix eigenvalues ​​corresponding to the cleaning association matrix, and mine the cleaning influencing factors of the cleaning object in the cleaning node from the target parameter labels based on the matrix eigenvalues.

[0036] Optionally, calculating the data entropy of each data in the cleaned data includes:

[0037] Normalizing the cleaning data to obtain standard cleaning data;

[0038] Counting the data frequency and total number of data corresponding to the standard cleaning data;

[0039] Calculate the data frequency corresponding to the cleaned data based on the data frequency and the total number of data;

[0040] Based on the data frequency, the data entropy of each data in the cleaned data is calculated by the following formula:

[0041]

[0042] Q represents the data entropy of each data in the cleaned data, f(d) represents the data frequency corresponding to the d-th data in the cleaned data, d represents the data sequence number corresponding to the cleaned data, and r represents the number of data in the cleaned data.

[0043] Optionally, screening out key data from the cleaned data according to the data entropy includes:

[0044] The data similarity between the cleaned data is calculated, and the data coupling degree between the cleaned data is calculated by combining the data similarity and the data entropy through the following formula:

[0045]

[0046] Among them, H represents the data coupling degree between the cleaned data, Q d represents the data entropy corresponding to the dth data in the cleaned data, d represents the data sequence number of the cleaned data, and r represents the number of data in the cleaned data. Indicates the data similarity between the dth data and the d+1th data in the cleaned data;

[0047] Based on the data coupling degree, key data is screened out from the cleaned data.

[0048] Optionally, the calculating, based on the external data, the surface cleaning degree of the cleaning device when performing the cleaning process on the cleaning object includes:

[0049] Extracting features from the external data to obtain object apparent attributes of the cleaning object, performing redundancy removal processing on the object apparent attributes to obtain target apparent attributes;

[0050] Based on the apparent properties, calculating a cleaning deviation index corresponding to the cleaning object;

[0051] Based on the cleaning deviation index, the surface cleanliness degree of the cleaning device when performing the cleaning process on the cleaning object is calculated.

[0052] Optionally, the calculating, based on the apparent properties, a cleaning deviation index corresponding to the cleaning object includes:

[0053] Acquire a standard reference image corresponding to the cleaning object, and extract standard apparent properties of the cleaning object from the standard reference image;

[0054] Calculating the attribute weight corresponding to the apparent attribute;

[0055] Combining the apparent attribute, the attribute weight and the standard apparent attribute, the cleaning deviation index corresponding to the cleaning object is calculated by the following formula:

[0056]

[0057] Where M represents the cleaning deviation index corresponding to the cleaning object, k i Indicates the attribute weight corresponding to the i-th attribute in the apparent attribute, L i represents the attribute value corresponding to the i-th attribute in the apparent attribute, P i It represents the attribute value of the standard apparent attribute corresponding to the i-th attribute, i represents the sequence number of the apparent attribute, and x represents the attribute quantity of the apparent attribute.

[0058] A device for improving the efficient cleaning of an intelligent bonding wire cleaning system, characterized in that the device comprises:

[0059] A system analysis module, used to obtain a bonding wire cleaning system to be optimized and a cleaning object thereof, and to identify a cleaning process and a cleaning device when the bonding wire cleaning system is used to perform a cleaning process on the cleaning object;

[0060] A cleaning rate calculation module, used for identifying a cleaning node of the cleaning process, extracting node parameters of the cleaning node, and calculating a cleaning rate of the cleaning object in the cleaning node based on the node parameters;

[0061] A process optimization module, configured to, when the cleaning rate is less than a preset threshold, mine the cleaning influencing factors of the cleaning object in the cleaning node based on the node parameters, and adjust the node parameters according to the cleaning influencing factors to perform optimization processing on the cleaning process to obtain an optimized process;

[0062] A data partitioning module, used for collecting cleaning data when the cleaning device performs cleaning processing on the cleaning object, and calculating the data entropy of each data in the cleaning data, filtering out key data from the cleaning data according to the data entropy, and dividing the key data into external data and internal data;

[0063] a cleaning effect analysis module, for calculating the surface cleaning degree of the cleaning device when performing the cleaning process on the cleaning object based on the external data, and calculating the internal cleaning degree of the cleaning device when performing the cleaning process on the cleaning object based on the internal data, and analyzing the cleaning effect of the cleaning device when performing the cleaning process on the cleaning object according to the surface cleaning degree and the internal cleaning degree;

[0064] A method generation module is used to adjust the equipment parameters of the cleaning equipment when performing the cleaning process on the cleaning object when the cleaning effect does not meet the preset effect, so as to perform equipment optimization of the cleaning equipment and obtain the optimized equipment, and generate an optimized bonding wire cleaning method based on the optimization process and the optimized equipment.

[0065] Compared with the problems described in the background technology, the present invention can obtain detailed cleaning steps and equipment required for cleaning by identifying the cleaning process and cleaning equipment when the bonding wire cleaning system is used to clean the cleaning object, thereby providing a basis for subsequent cleaning analysis of the cleaning object. The present invention calculates the cleaning rate of the cleaning object in the cleaning node based on the node parameters, and can accurately obtain the cleaning effect corresponding to the cleaning node, thereby facilitating the subsequent mining of the cleaning influencing factors of the cleaning object in the cleaning node. It should be understood that when the cleaning rate is less than a preset threshold, it means that the cleaning rate of the cleaning object has not reached the expected level. Then, in combination with the node parameters and the cleaning rate, the cleaning influencing factors of the cleaning object in the cleaning node are mined, so as to accurately find out the key factors affecting the cleaning effect. The present invention collects the cleaning equipment when cleaning the cleaning object. The cleaning data during processing can obtain the data recorded by the cleaning object during the cleaning process, calculate the data entropy of each data in the cleaning data, and understand the uncertainty degree of the cleaning data through the data entropy, which provides a basis for the subsequent screening of key data in the cleaning data. The present invention calculates the surface cleaning degree of the cleaning equipment when performing the cleaning process on the cleaning object based on the external data, and can understand the surface cleaning degree of the cleaning object through the surface cleaning degree, thereby providing a basis for the subsequent analysis of the cleaning effect. It should be understood that when the cleaning effect does not meet the preset effect, it indicates that the cleaning effect of the cleaning object is not good, then adjust the equipment parameters of the cleaning equipment when performing the cleaning process on the cleaning object to perform equipment optimization of the cleaning equipment, and then obtain the optimized equipment. Based on the optimization process and the optimized equipment, generate an optimized bonding wire cleaning method. Therefore, the method for improving the efficient cleaning of the intelligent bonding wire cleaning system proposed in the present invention improves the cleaning efficiency of the intelligent bonding wire cleaning system. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 A schematic flow chart of a method for improving efficient cleaning of an intelligent gold bonding wire cleaning system provided by an embodiment of the present invention;

[0067] Figure 2 A functional module diagram of a system for realizing efficient cleaning of an intelligent bonding wire cleaning system provided in accordance with an embodiment of the present invention.

[0068] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0069] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0070] The embodiment of the present application provides a method for improving the efficient cleaning of an intelligent gold bonding wire cleaning system. The execution subject of the method for improving the efficient cleaning of an intelligent gold bonding wire cleaning system includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for improving the efficient cleaning of an intelligent gold bonding wire cleaning system can be executed by software or hardware installed in a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0071] Embodiment 1:

[0072] Reference Figure 1 FIG. 1 is a flow chart of a method for improving the efficient cleaning of an intelligent bonding wire cleaning system according to an embodiment of the present invention. In this embodiment, the method for improving the efficient cleaning of an intelligent bonding wire cleaning system includes:

[0073] S1. Acquire a bonding wire cleaning system to be optimized and a cleaning object thereof, and identify a cleaning process and a cleaning device when the bonding wire cleaning system is used to clean the cleaning object.

[0074] The present invention can obtain detailed cleaning steps and required equipment by identifying the cleaning process and cleaning equipment when the cleaning object is cleaned by the bonding wire cleaning system, thereby providing a basis for subsequent cleaning analysis of the cleaning object.

[0075] It should be explained that the gold bonding wire cleaning system refers to a system used to clean the gold wire products used in the gold bonding wire process, the cleaning object refers to the gold bonding wire product cleaned by the gold bonding wire cleaning system, the cleaning process refers to a systematic cleaning process used to remove residual contaminants on the surface of the cleaning object to achieve predetermined cleaning standards, and the cleaning equipment refers to the equipment used in the gold bonding wire cleaning system to clean the cleaned object.

[0076] In detail, the identification of the cleaning process and cleaning equipment when the cleaning object is cleaned by the bonding wire cleaning system includes:

[0077] Querying the operation scenario corresponding to the cleaning object, and identifying the environmental factors in the operation scenario;

[0078] Based on the environmental factors, analyzing the scenario characteristics corresponding to the operating scenario;

[0079] Based on the scene characteristics, determining the cleaning standard corresponding to the cleaning object;

[0080] Obtaining system cleaning equipment in the bonding wire cleaning system and its corresponding cleaning effect description;

[0081] Calculating the adaptation index between the cleaning performance description and the cleaning standard, and performing equipment screening processing on the system cleaning equipment based on the adaptation index to obtain target cleaning equipment;

[0082] Analyzing a device interaction mode between the target cleaning devices, and determining a device cleaning logic corresponding to the target cleaning device based on the device interaction mode;

[0083] By combining the equipment cleaning logic and the target cleaning equipment, a cleaning process and a cleaning equipment are obtained when the bonding wire cleaning system performs a cleaning process on the cleaning object.

[0084] It should be explained that the operating scenario is the application environment corresponding to the cleaning object, the environmental factors are the influencing conditions in the operating scenario, the scenario characteristics are the specific characteristic manifestations corresponding to the operating scenario, the cleaning standards are the cleaning quality requirements corresponding to the cleaning objects, the system cleaning equipment is the related equipment for cleaning in the bonding wire cleaning system, the cleaning effectiveness description is the cleaning effect description of the system cleaning equipment, the adaptation index indicates the degree of adaptation between the cleaning effectiveness description and the cleaning standard, the target cleaning equipment is the equipment when the adaptation index corresponding to the system cleaning equipment is greater than the preset index, the equipment interaction mode is the collaboration mode between the target cleaning equipment, and the equipment cleaning logic is the working logic sequence corresponding to the target cleaning equipment.

[0085] Furthermore, the query of the operation scenario corresponding to the cleaning object can be realized by investigating the application field and use environment of the cleaning object, for example, understanding the specific application of the cleaning object, i.e., bonding gold wire, in different fields such as electronic packaging, semiconductor manufacturing, medical electronics, etc., as well as the status under different production links and working conditions; the identification of environmental factors in the operation scenario can be realized through field investigation, data analysis and industry experience summary, for example, measuring parameters such as temperature, humidity, pressure in the actual working environment, analyzing the impact of environmental factors on the cleaning object in historical data, and referring to the environmental characteristics of similar scenarios in the same industry; based on the environmental factors, the scenario characteristics corresponding to the operation scenario can be analyzed through logical reasoning, considering the combination of different environmental factors and their potential impact on the cleaning object, and inferring the unique characteristics of the operation scenario; based on the scene According to the scene characteristics, the cleaning standard corresponding to the cleaning object can be determined through professional knowledge, and the appropriate integrity, performance and other standards in specific scenarios can be determined in combination with the material characteristics, usage requirements and scene characteristics of the cleaning object; the system cleaning equipment in the bonding wire cleaning system and its corresponding cleaning performance description can be obtained through the equipment manual; the device interaction mode between the target cleaning devices can be analyzed through the functional analysis method, the actual operation of the equipment during the cleaning process can be observed, and the information transmission, collaboration mode and common influence on the cleaning effect between each device can be analyzed; the device cleaning logic corresponding to the target cleaning device can be determined according to the description content of the device interaction mode; the device cleaning logic and the target cleaning device are the cleaning process and cleaning equipment when the bonding wire cleaning system executes the cleaning process of the cleaning object.

[0086] Further, as an optional embodiment of the present invention, the calculating of the adaptation index between the cleaning effectiveness description and the cleaning standard includes:

[0087] Recognize the character information in the cleaning performance description and the cleaning standard to obtain description character information and standard character information;

[0088] Respectively extracting the representation information in the explanatory character information and the standard character information to obtain first representation information and second representation information;

[0089] The information adaptability between the first representation information and the second representation information is calculated by the following formula:

[0090]

[0091] Where A represents the information adaptability between the first representation information and the second representation information, n represents the comparison frequency between the first representation information and the second representation information, and B arepresents the information value corresponding to the ath information in the first representation information, a represents the sequence number of the first representation information, C b represents the information value corresponding to the bth information in the second representation information, b represents the sequence number corresponding to the second representation information, MAX(B a , C b ) represents taking the maximum value of the information value corresponding to the a-th information in the first representation information and the information value corresponding to the b-th information in the second representation information;

[0092] Based on the information fit, a fit index between the cleaning performance description and the cleaning standard is calculated.

[0093] It should be explained that the explanatory character information and the standard character information are respectively the specific description contents in the cleaning effectiveness description and the cleaning standard, the first characterization information and the second characterization information are respectively the representative information in the explanatory character information and the standard character information, the information adaptability indicates the degree of adaptability between the first characterization information and the second characterization information, and the information values ​​corresponding to the first characterization information and the second characterization information can be represented by corresponding information vectors.

[0094] Furthermore, the recognition of the character information in the cleaning effectiveness description and the cleaning standard can be achieved through OCR recognition technology; the extraction of representation information in the description character information and the standard character information can be achieved through natural language processing (NLP) technology, such as lexical analysis, syntactic analysis, etc.; the average value corresponding to the information fitness degree is calculated to obtain the fitness index between the cleaning effectiveness description and the cleaning standard.

[0095] S2. Identify a cleaning node of the cleaning process, extract node parameters of the cleaning node, and calculate a cleaning rate of the cleaning object in the cleaning node based on the node parameters.

[0096] The present invention calculates the cleaning rate of the cleaning object in the cleaning node based on the node parameters, so as to accurately obtain the cleaning effect corresponding to the cleaning node, thereby facilitating the subsequent mining of the cleaning influencing factors of the cleaning object in the cleaning node.

[0097] It should be explained that the cleaning node is the operation node of the cleaning process, the node parameters are various characteristic descriptions of the cleaning node, such as cleaning time or cleaning temperature, etc., and the cleaning rate represents the completion rate of the cleaning degree of the cleaning object in the cleaning node. Furthermore, the identification of the cleaning nodes of the cleaning process can be achieved through flowchart analysis; the extraction of the node parameters of the cleaning nodes can be achieved through sensors.

[0098] Specifically, the calculating the cleaning rate of the cleaning object in the cleaning node based on the node parameter includes:

[0099] Extracting the cleaning time, cleaning temperature, initial quality and cleaning quality of the cleaning object from the node parameters;

[0100] In combination with the cleaning time, the cleaning temperature, the initial mass and the cleaning mass, the cleaning rate of the cleaning object in the cleaning node is calculated using the following formula:

[0101]

[0102] Wherein, D represents the cleaning rate of the cleaning object in the cleaning node, E represents the initial quality, Indicates the cleaning quality, F indicates the cleaning temperature, represents the reference cleaning temperature, G represents the cleaning time, Indicates reference cleaning time.

[0103] It should be explained that the cleaning time is the time taken to clean the cleaning object recorded in the node parameters, the cleaning temperature is the environmental parameter of the cleaning object during the cleaning process recorded in the node parameters, the initial mass is the weight of the cleaning object before cleaning, the cleaning mass is the weight of the cleaning object after cleaning, the reference cleaning temperature and the reference cleaning time are respectively the reference standard values ​​of the cleaning object during the cleaning process, and the reference cleaning temperature and the reference cleaning time of the cleaning object can be queried through the cleaning standards of the relevant industry.

[0104] S3. When the cleaning rate is less than a preset threshold, the node parameters and the cleaning rate are combined to mine the cleaning impact factors of the cleaning object in the cleaning node, and the node parameters are adjusted according to the cleaning impact factors to perform optimization processing on the cleaning process to obtain an optimized process.

[0105] It should be understood that when the cleaning rate is less than a preset threshold, it indicates that the cleaning rate of the cleaning object has not reached the expected level. Then, the node parameters and the cleaning rate are combined to mine the cleaning influencing factors of the cleaning object in the cleaning node, so as to accurately find out the key factors affecting the cleaning effect.

[0106] It should be explained that the preset threshold is a reference value corresponding to the cleaning rate, such as 80%, or it can be a cleaning rate value determined based on past experience data that can ensure that the cleaning object reaches a basic level of cleanliness. The cleaning influencing factor is the influencing factor of the cleaning object in the cleaning node, such as the cleaning type and concentration.

[0107] In detail, the combining the node parameter and the cleaning rate to mine the cleaning influencing factor of the cleaning object in the cleaning node includes:

[0108] Extracting parameter labels corresponding to the node parameters, performing dimensionality reduction processing on the parameter labels, and obtaining target parameter labels;

[0109] Calculating the correlation coefficient between the target parameter label and the cleaning object, and constructing a cleaning correlation matrix corresponding to the target parameter label by combining the correlation coefficient and the cleaning rate;

[0110] Calculate the matrix eigenvalues ​​corresponding to the cleaning association matrix, and mine the cleaning influencing factors of the cleaning object in the cleaning node from the target parameter labels based on the matrix eigenvalues.

[0111] It should be explained that the parameter label is the identifier of the node parameter, the target parameter label is the label obtained after removing invalid information and unimportant information in the parameter label, the correlation coefficient represents the degree of correlation between the target parameter label and the cleaning object, the cleaning correlation matrix is ​​a matrix constructed by combining the correlation coefficient between each label in the target parameter label and the cleaning object and the corresponding cleaning rate, and the matrix eigenvalue represents the importance measure corresponding to the cleaning correlation matrix.

[0112] Furthermore, the extraction of parameter labels corresponding to the node parameters can be achieved through a label extraction tool, which is compiled by a scripting language, such as JS scripting language; the dimensionality reduction processing of the parameter labels can be achieved through a principal component analysis method; the calculation of the correlation coefficient between the target parameter label and the cleaning object can be achieved through the Pearson correlation coefficient, and the correlation between the target parameter label and the material requirement of the cleaning object is calculated; the construction of the cleaning association matrix corresponding to the target parameter label can be achieved through a matrix function, such as a zero matrix function; the calculation of the matrix eigenvalues ​​corresponding to the cleaning association matrix can be achieved through an iterative algorithm; based on the numerical value of the matrix eigenvalue, the cleaning influencing factors of the cleaning object in the cleaning node are mined from the target parameter label.

[0113] The present invention adjusts the node parameters according to the cleaning influence factor to perform optimization processing on the cleaning process to obtain an optimized process, so as to improve the processing efficiency of the cleaning process. Further, for example, if the cleaning influence factor indicates that a too low cleaning temperature will reduce the cleaning effect, the node parameter of the cleaning temperature can be appropriately increased. For another example, if it is found that the cleaning agent concentration is an important influencing factor and the current concentration is not appropriate, the cleaning agent concentration can be adjusted to optimize the cleaning process.

[0114] S4. Collect cleaning data when the cleaning device performs cleaning processing on the cleaning object, calculate the data entropy of each data in the cleaning data, filter out key data from the cleaning data according to the data entropy, and divide the key data into external data and internal data.

[0115] The present invention can obtain the data recorded by the cleaning object during the cleaning process by collecting the cleaning data when the cleaning device performs the cleaning process on the cleaning object, calculate the data entropy of each data in the cleaning data, and understand the degree of uncertainty of the cleaning data through the data entropy, thereby providing a basis for the subsequent processing of screening out key data from the cleaning data. It should be explained that the cleaning data is the data recorded by the cleaning object during the cleaning process, and the data entropy represents the degree of uncertainty of the cleaning data. Furthermore, the collection of cleaning data when the cleaning device performs the cleaning process on the cleaning object can be achieved through a data recorder.

[0116] In detail, the calculating the data entropy of each data in the cleaned data includes:

[0117] Normalizing the cleaning data to obtain standard cleaning data;

[0118] Counting the data frequency and total number of data corresponding to the standard cleaning data;

[0119] Calculate the data frequency corresponding to the cleaned data based on the data frequency and the total number of data;

[0120] Based on the data frequency, the data entropy of each data in the cleaned data is calculated by the following formula:

[0121]

[0122] Q represents the data entropy of each data in the cleaned data, f(d) represents the data frequency corresponding to the d-th data in the cleaned data, d represents the data sequence number corresponding to the cleaned data, and r represents the number of data in the cleaned data.

[0123] It should be explained that the standard cleaned data is the cleaned data converted into a unified form, that is, converted into data of a numerical type, the data frequency represents the occurrence probability corresponding to each data in the cleaned data, and the normalization processing of the cleaned data can be achieved through the minimum-maximum normalization method; the statistics of the data frequency and the total number of data corresponding to the standard cleaned data can be achieved through the counting method; the ratio between the data frequency and the total number of data is calculated to obtain the data frequency corresponding to the cleaned data.

[0124] The present invention screens out key data from the cleaning data based on the data entropy, and then obtains representative data in the cleaning data, thereby improving the efficiency of subsequent data analysis, and dividing the key data into external data and internal data, laying an important foundation for the subsequent calculation of surface cleaning degree and internal cleanliness. It should be explained that the key data is representative data in the cleaning data, the external data is data in the key data related to the external characteristics of the cleaning object, and the internal data is data in the key data related to the internal structure and state of the cleaning object; dividing the key data into external data and internal data can be achieved through a clustering method.

[0125] In detail, the step of screening out key data from the cleaned data according to the data entropy includes:

[0126] The data similarity between the cleaned data is calculated, and the data coupling degree between the cleaned data is calculated by combining the data similarity and the data entropy through the following formula:

[0127]

[0128] Among them, H represents the data coupling degree between the cleaned data, Q d represents the data entropy corresponding to the dth data in the cleaned data, d represents the data sequence number of the cleaned data, and r represents the number of data in the cleaned data. Indicates the data similarity between the dth data and the d+1th data in the cleaned data;

[0129] Based on the data coupling degree, key data is screened out from the cleaned data.

[0130] It should be explained that the data similarity indicates the degree of similarity between the cleaned data, and the data coupling indicates the mutual dependence between the cleaned data. Furthermore, the calculation of the data similarity between the cleaned data can be achieved by a cosine similarity algorithm. Based on the numerical value of the data coupling, key data is screened out from the cleaned data. If the data coupling degree of a certain data in the cleaned data is high with other data, it means that the data is important data, and the data is screened out as key data.

[0131] S5. Based on the external data, calculate the surface cleaning degree of the cleaning equipment when performing the cleaning process on the cleaning object, and based on the internal data, calculate the internal cleaning degree of the cleaning equipment when performing the cleaning process on the cleaning object, and analyze the cleaning effect of the cleaning equipment when performing the cleaning process on the cleaning object according to the surface cleaning degree and the internal cleaning degree.

[0132] The present invention calculates the surface cleaning degree of the cleaning equipment when performing the cleaning process on the cleaning object based on the external data. The surface cleaning degree can be used to understand the surface cleaning degree of the cleaning object, thereby providing a basis for the subsequent analysis of the cleaning effect. It should be explained that the surface cleaning degree indicates the surface cleaning degree of the cleaning object after being cleaned by the cleaning equipment.

[0133] Specifically, the calculating, based on the external data, the surface cleaning degree of the cleaning device when performing the cleaning process on the cleaning object includes:

[0134] Extracting features from the external data to obtain object apparent attributes of the cleaning object, performing redundancy removal processing on the object apparent attributes to obtain target apparent attributes;

[0135] Based on the apparent properties, calculating a cleaning deviation index corresponding to the cleaning object;

[0136] Based on the cleaning deviation index, the surface cleanliness degree of the cleaning device when performing the cleaning process on the cleaning object is calculated.

[0137] It should be explained that the object appearance attribute is the appearance feature corresponding to the cleaning object, the target appearance attribute is the attribute obtained after removing the redundant attributes in the object appearance attribute, and the cleaning deviation index represents the quantitative deviation between the actual cleaning degree of the cleaning object and the standard cleaning degree.

[0138] Furthermore, the feature extraction of the external data can be achieved through a convolutional neural network; the redundancy removal processing of the object's apparent attributes can be achieved through a feature selection algorithm, such as a variance selection method; a functional relationship can be established between the object cleaning deviation index in the historical cleaning data and the corresponding surface cleaning degree, and the linear relationship between the two can be analyzed; based on the cleaning deviation index and the linear relationship, the surface cleaning degree of the cleaning equipment when performing the cleaning process on the cleaning object can be calculated.

[0139] Further, as an optional embodiment of the present invention, the calculating of the cleaning deviation index corresponding to the cleaning object based on the apparent attribute includes:

[0140] Acquire a standard reference image corresponding to the cleaning object, and extract standard apparent properties of the cleaning object from the standard reference image;

[0141] Calculating the attribute weight corresponding to the apparent attribute;

[0142] Combining the apparent attribute, the attribute weight and the standard apparent attribute, the cleaning deviation index corresponding to the cleaning object is calculated by the following formula:

[0143]

[0144] Where M represents the cleaning deviation index corresponding to the cleaning object, k i Indicates the attribute weight corresponding to the i-th attribute in the apparent attribute, L i represents the attribute value corresponding to the i-th attribute in the apparent attribute, P i It represents the attribute value of the standard apparent attribute corresponding to the i-th attribute, i represents the sequence number of the apparent attribute, and x represents the attribute quantity of the apparent attribute.

[0145] It should be explained that the standard reference image is the image corresponding to the cleaning object when it is not in use, the standard apparent attribute is the reference standard corresponding to the apparent attribute, the attribute weight represents the importance corresponding to the apparent attribute, and the attribute value is the expression value corresponding to the apparent attribute and the standard apparent attribute.

[0146] Furthermore, the standard reference image corresponding to the cleaning object can be obtained through an industry standard database, and the standard apparent attributes of the cleaning object can be extracted from the standard reference image through an image feature extraction algorithm, such as SIFT, SURF, and HOG feature extraction algorithms; the attribute values ​​corresponding to the apparent attributes can be realized through an encoding algorithm, such as a one-hot encoding algorithm.

[0147] The present invention calculates the internal cleaning degree of the cleaning device when performing the cleaning process on the cleaning object based on the internal data, so that the internal cleanliness degree of the cleaning object can be understood, and the cleaning effect of the cleaning device when performing the cleaning process on the cleaning object can be analyzed according to the surface cleaning degree and the internal cleaning degree, so as to obtain the cleaning degree evaluation effect of the cleaning object.

[0148] It should be explained that the internal cleaning degree indicates the internal cleanliness degree of the cleaning equipment when performing the cleaning process on the cleaning object, and the cleaning effect indicates the evaluation effect of the overall cleaning degree of the cleaning equipment when performing the cleaning process on the cleaning object. Furthermore, the calculation principle of the internal cleaning degree is the same as that of the surface cleaning degree, which will not be elaborated here. Based on the surface cleaning degree and the internal cleaning degree, the cleaning effect of the cleaning equipment when performing the cleaning process on the cleaning object is analyzed. If both the surface cleaning degree and the internal cleaning degree are high, it means that the cleaning effect is good.

[0149] S6. When the cleaning effect does not meet the preset effect, adjust the equipment parameters of the cleaning equipment when performing the cleaning process on the cleaning object to perform equipment optimization on the cleaning equipment to obtain an optimized equipment, and generate an optimized bonding wire cleaning method based on the optimization process and the optimized equipment.

[0150] It should be understood that when the cleaning effect does not meet the preset effect, it indicates that the cleaning effect of the cleaning object is not good, then the equipment parameters of the cleaning equipment when executing the cleaning process of the cleaning object are adjusted to perform equipment optimization of the cleaning equipment, and then the optimized equipment is obtained. Based on the optimization process and the optimized equipment, the optimized bonding wire cleaning method is generated. It should be explained that the preset effect is the reference standard of the cleaning effect, the optimized equipment is the equipment after the equipment parameters are optimized and adjusted, and the cleaning effect corresponding to the equipment can achieve the preset effect. Further, when the cleaning effect does not meet the preset effect, the unfavorable reasons corresponding to the cleaning effect are analyzed, and the equipment parameters of the cleaning equipment when executing the cleaning process of the cleaning object are adjusted according to the unfavorable reasons. For example, if the unfavorable reason is that the concentration of the cleaning liquid is too low, the concentration parameters of the cleaning liquid can be appropriately increased. If it is found that the cleaning effect is poor due to the short cleaning time, the cleaning time of the cleaning equipment for the cleaning object can be extended. If the cleaning pressure is insufficient, then the pressure parameters of the cleaning equipment are increased to improve the cleaning effect.

[0151] Compared with the problems described in the background technology, the present invention can obtain detailed cleaning steps and equipment required for cleaning by identifying the cleaning process and cleaning equipment when the bonding wire cleaning system is used to clean the cleaning object, thereby providing a basis for subsequent cleaning analysis of the cleaning object. The present invention calculates the cleaning rate of the cleaning object in the cleaning node based on the node parameters, and can accurately obtain the cleaning effect corresponding to the cleaning node, thereby facilitating the subsequent mining of the cleaning influencing factors of the cleaning object in the cleaning node. It should be understood that when the cleaning rate is less than a preset threshold, it means that the cleaning rate of the cleaning object has not reached the expected level. Then, in combination with the node parameters and the cleaning rate, the cleaning influencing factors of the cleaning object in the cleaning node are mined, so as to accurately find out the key factors affecting the cleaning effect. The present invention collects the cleaning equipment when cleaning the cleaning object. The cleaning data during processing can obtain the data recorded by the cleaning object during the cleaning process, calculate the data entropy of each data in the cleaning data, and understand the uncertainty degree of the cleaning data through the data entropy, which provides a basis for the subsequent screening of key data in the cleaning data. The present invention calculates the surface cleaning degree of the cleaning equipment when performing the cleaning process on the cleaning object based on the external data, and can understand the surface cleaning degree of the cleaning object through the surface cleaning degree, thereby providing a basis for the subsequent analysis of the cleaning effect. It should be understood that when the cleaning effect does not meet the preset effect, it indicates that the cleaning effect of the cleaning object is not good, then adjust the equipment parameters of the cleaning equipment when performing the cleaning process on the cleaning object to perform equipment optimization of the cleaning equipment, and then obtain the optimized equipment. Based on the optimization process and the optimized equipment, generate an optimized bonding wire cleaning method. Therefore, the method for improving the efficient cleaning of the intelligent bonding wire cleaning system proposed in the present invention improves the cleaning efficiency of the intelligent bonding wire cleaning system.

[0152] Embodiment 2:

[0153] like Figure 2 1 is a functional module diagram of a device for improving the efficient cleaning of an intelligent bonding wire cleaning system provided by an embodiment of the present invention.

[0154] The device 100 for improving the efficient cleaning of the intelligent bonding wire cleaning system of the present invention can be installed in an electronic device. According to the functions implemented, the device 100 for improving the efficient cleaning of the intelligent bonding wire cleaning system can include a system analysis module 101, a cleaning rate calculation module 102, a process optimization module 103, a data partitioning module 104, a cleaning effect analysis module 105 and a method generation module 106. The module described in the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0155] In this embodiment, the functions of each module / unit are as follows:

[0156] The system analysis module 101 is used to obtain the bonding wire cleaning system to be optimized and its cleaning object, and identify the cleaning process and cleaning equipment when the bonding wire cleaning system performs the cleaning process on the cleaning object;

[0157] The cleaning rate calculation module 102 is used to identify the cleaning nodes of the cleaning process, extract the node parameters of the cleaning nodes, and calculate the cleaning rate of the cleaning object in the cleaning node based on the node parameters;

[0158] The process optimization module 103 is used to mine the cleaning influencing factors of the cleaning objects in the cleaning nodes based on the node parameters when the cleaning rate is less than a preset threshold, and adjust the node parameters according to the cleaning influencing factors to perform optimization processing on the cleaning process to obtain an optimized process;

[0159] The data division module 104 is used to collect cleaning data when the cleaning device performs cleaning processing on the cleaning object, calculate the data entropy of each data in the cleaning data, filter out key data from the cleaning data according to the data entropy, and divide the key data into external data and internal data;

[0160] The cleaning effect analysis module 105 is used to calculate the surface cleaning degree of the cleaning device when performing the cleaning process on the cleaning object based on the external data, and calculate the internal cleaning degree of the cleaning device when performing the cleaning process on the cleaning object based on the internal data, and analyze the cleaning effect of the cleaning device when performing the cleaning process on the cleaning object according to the surface cleaning degree and the internal cleaning degree;

[0161] The method generation module 106 is used to adjust the equipment parameters of the cleaning equipment when performing the cleaning process on the cleaning object when the cleaning effect does not meet the preset effect, so as to perform equipment optimization of the cleaning equipment and obtain the optimized equipment, and generate an optimized bonding wire cleaning method based on the optimization process and the optimized equipment.

[0162] In detail, each module described in the system 100 for improving the efficient cleaning of the intelligent bonding wire cleaning system described in the embodiment of the present application is used in the same manner as described above. Figure 1 The same technical means as described in a method for improving the efficient cleaning of an intelligent bonding wire cleaning system can produce the same technical effects, so they will not be repeated here.

[0163] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0164] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for improving the efficient cleaning of an intelligent bonding wire cleaning system, characterized in that: The method comprises: Acquire a bonding wire cleaning system to be optimized and a cleaning object thereof, and identify a cleaning process and a cleaning device when the bonding wire cleaning system is used to clean the cleaning object; Identifying a cleaning node of the cleaning process, extracting node parameters of the cleaning node, and calculating a cleaning rate of the cleaning object in the cleaning node based on the node parameters; When the cleaning rate is less than a preset threshold, based on the node parameters, the cleaning influencing factors of the cleaning objects in the cleaning nodes are mined, and according to the cleaning influencing factors, the node parameters are adjusted to perform optimization processing on the cleaning process to obtain an optimized process; Collecting cleaning data when the cleaning device performs cleaning processing on the cleaning object, and calculating the data entropy of each data in the cleaning data, screening out key data from the cleaning data according to the data entropy, and dividing the key data into external data and internal data; Calculating the surface cleaning degree of the cleaning device when performing the cleaning process on the cleaning object based on the external data, and calculating the internal cleaning degree of the cleaning device when performing the cleaning process on the cleaning object based on the internal data, and analyzing the cleaning effect of the cleaning device when performing the cleaning process on the cleaning object according to the surface cleaning degree and the internal cleaning degree; When the cleaning effect does not meet the preset effect, the equipment parameters of the cleaning equipment when performing the cleaning process on the cleaning object are adjusted to perform equipment optimization of the cleaning equipment to obtain an optimized equipment, and based on the optimization process and the optimized equipment, an optimized bonding wire cleaning method is generated.

2. The method for improving the efficient cleaning of the intelligent bonding wire cleaning system according to claim 1, characterized in that: The identification of a cleaning process and a cleaning device when the cleaning object is cleaned by the bonding wire cleaning system includes: Querying the operation scenario corresponding to the cleaning object, and identifying the environmental factors in the operation scenario; Based on the environmental factors, analyzing the scenario characteristics corresponding to the operating scenario; Based on the scene characteristics, determining the cleaning standard corresponding to the cleaning object; Obtaining system cleaning equipment in the bonding wire cleaning system and its corresponding cleaning effect description; Calculating the adaptation index between the cleaning performance description and the cleaning standard, and performing equipment screening processing on the system cleaning equipment based on the adaptation index to obtain target cleaning equipment; Analyzing a device interaction mode between the target cleaning devices, and determining a device cleaning logic corresponding to the target cleaning device based on the device interaction mode; By combining the equipment cleaning logic and the target cleaning equipment, a cleaning process and a cleaning equipment are obtained when the bonding wire cleaning system performs a cleaning process on the cleaning object.

3. The method for improving the efficient cleaning of the intelligent bonding wire cleaning system according to claim 2, characterized in that: The calculating of the matching index between the cleaning effectiveness description and the cleaning standard comprises: Recognize the character information in the cleaning performance description and the cleaning standard to obtain description character information and standard character information; Respectively extracting the representation information in the explanatory character information and the standard character information to obtain first representation information and second representation information; The information adaptability between the first representation information and the second representation information is calculated by the following formula: Where A represents the information adaptability between the first representation information and the second representation information, n represents the comparison frequency between the first representation information and the second representation information, and B a represents the information value corresponding to the ath information in the first representation information, a represents the sequence number of the first representation information, C b represents the information value corresponding to the bth information in the second representation information, b represents the sequence number corresponding to the second representation information, MAX(B a , C b ) represents taking the maximum value of the information value corresponding to the a-th information in the first representation information and the information value corresponding to the b-th information in the second representation information; Based on the information fit, a fit index between the cleaning performance description and the cleaning standard is calculated.

4. The method for improving the efficient cleaning of the intelligent bonding wire cleaning system according to claim 1, characterized in that: The calculating, based on the node parameter, the cleaning rate of the cleaning object in the cleaning node comprises: Extracting the cleaning time, cleaning temperature, initial quality and cleaning quality of the cleaning object from the node parameters; In combination with the cleaning time, the cleaning temperature, the initial mass and the cleaning mass, the cleaning rate of the cleaning object in the cleaning node is calculated using the following formula: Wherein, D represents the cleaning rate of the cleaning object in the cleaning node, E represents the initial quality, Indicates the cleaning quality, F indicates the cleaning temperature, represents the reference cleaning temperature, G represents the cleaning time, Indicates reference cleaning time.

5. The method for improving the efficient cleaning of the intelligent bonding wire cleaning system according to claim 1, characterized in that: The combining the node parameter and the cleaning rate to mine the cleaning influencing factor of the cleaning object in the cleaning node includes: Extracting parameter labels corresponding to the node parameters, performing dimensionality reduction processing on the parameter labels, and obtaining target parameter labels; Calculating the correlation coefficient between the target parameter label and the cleaning object, and constructing a cleaning correlation matrix corresponding to the target parameter label by combining the correlation coefficient and the cleaning rate; Calculate the matrix eigenvalues ​​corresponding to the cleaning association matrix, and mine the cleaning influencing factors of the cleaning object in the cleaning node from the target parameter labels based on the matrix eigenvalues.

6. The method for improving the efficient cleaning of the intelligent bonding wire cleaning system according to claim 1, characterized in that: The calculating the data entropy of each data in the cleaned data includes: Normalizing the cleaning data to obtain standard cleaning data; Counting the data frequency and total number of data corresponding to the standard cleaning data; Calculate the data frequency corresponding to the cleaned data based on the data frequency and the total number of data; Based on the data frequency, the data entropy of each data in the cleaned data is calculated by the following formula: Q represents the data entropy of each data in the cleaned data, f(d) represents the data frequency corresponding to the d-th data in the cleaned data, d represents the data sequence number corresponding to the cleaned data, and r represents the number of data in the cleaned data.

7. The method for improving the efficient cleaning of the intelligent bonding wire cleaning system according to claim 1, characterized in that: The step of screening out key data from the cleaned data according to the data entropy includes: The data similarity between the cleaned data is calculated, and the data coupling degree between the cleaned data is calculated by combining the data similarity and the data entropy through the following formula: Among them, H represents the data coupling degree between the cleaned data, Q d represents the data entropy corresponding to the dth data in the cleaned data, d represents the data sequence number of the cleaned data, and r represents the number of data in the cleaned data. Indicates the data similarity between the dth data and the d+1th data in the cleaned data; Based on the data coupling degree, key data is screened out from the cleaned data.

8. The method for improving the efficient cleaning of the intelligent bonding wire cleaning system according to claim 1, characterized in that: The step of calculating the surface cleaning degree of the cleaning device when performing a cleaning process on the cleaning object based on the external data includes: Extracting features from the external data to obtain object apparent attributes of the cleaning object, and performing redundancy removal processing on the object apparent attributes to obtain target apparent attributes; Based on the apparent properties, calculating a cleaning deviation index corresponding to the cleaning object; Based on the cleaning deviation index, the surface cleanliness degree of the cleaning device when performing the cleaning process on the cleaning object is calculated.

9. The method for improving the efficient cleaning of the intelligent bonding wire cleaning system according to claim 8, characterized in that: The step of calculating the cleaning deviation index corresponding to the cleaning object based on the apparent attribute includes: Acquire a standard reference image corresponding to the cleaning object, and extract standard apparent properties of the cleaning object from the standard reference image; Calculating the attribute weight corresponding to the apparent attribute; Combining the apparent attribute, the attribute weight and the standard apparent attribute, the cleaning deviation index corresponding to the cleaning object is calculated by the following formula: Where M represents the cleaning deviation index corresponding to the cleaning object, k i Indicates the attribute weight corresponding to the i-th attribute in the apparent attribute, L i represents the attribute value corresponding to the i-th attribute in the apparent attribute, P i It represents the attribute value of the standard apparent attribute corresponding to the i-th attribute, i represents the sequence number of the apparent attribute, and x represents the attribute quantity of the apparent attribute.

10. A device for improving the efficient cleaning of an intelligent bonding wire cleaning system, characterized in that: The device comprises: A system analysis module, used to obtain a bonding wire cleaning system to be optimized and a cleaning object thereof, and to identify a cleaning process and a cleaning device when the bonding wire cleaning system is used to perform a cleaning process on the cleaning object; A cleaning rate calculation module, used for identifying a cleaning node of the cleaning process, extracting node parameters of the cleaning node, and calculating a cleaning rate of the cleaning object in the cleaning node based on the node parameters; A process optimization module, configured to, when the cleaning rate is less than a preset threshold, mine the cleaning influencing factors of the cleaning object in the cleaning node based on the node parameters, and adjust the node parameters according to the cleaning influencing factors to perform optimization processing on the cleaning process to obtain an optimized process; A data partitioning module, used for collecting cleaning data when the cleaning device performs cleaning processing on the cleaning object, and calculating the data entropy of each data in the cleaning data, filtering out key data from the cleaning data according to the data entropy, and dividing the key data into external data and internal data; a cleaning effect analysis module, for calculating the surface cleaning degree of the cleaning device when performing the cleaning process on the cleaning object based on the external data, and calculating the internal cleaning degree of the cleaning device when performing the cleaning process on the cleaning object based on the internal data, and analyzing the cleaning effect of the cleaning device when performing the cleaning process on the cleaning object according to the surface cleaning degree and the internal cleaning degree; A method generation module is used to adjust the equipment parameters of the cleaning equipment when performing the cleaning process on the cleaning object when the cleaning effect does not meet the preset effect, so as to perform equipment optimization of the cleaning equipment and obtain the optimized equipment, and generate an optimized bonding wire cleaning method based on the optimization process and the optimized equipment.

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