Preparation method and system for realizing bonding silver wire

Abstract

The invention relates to the technical field of bonding silver wires, and discloses a preparation method and system for realizing bonding silver wires, and the method comprises the steps: obtaining a preparation starting material needed for preparing the bonding silver wires, determining a manufacturing technology instruction set corresponding to a silver wire processing equipment cluster, and formulating a quality reference factor corresponding to the silver wire processing equipment cluster; processing multidimensional features corresponding to the silver wire processing equipment cluster are mined, a quality actuarial gradient corresponding to the quality reference factor is calculated, and the equipment processing precision corresponding to the silver wire processing equipment cluster is evaluated; calculating quality reliability and validity corresponding to the bonding silver wire; collecting an ecological parameter variable vector set corresponding to the storage packaging ecology, and calculating a storage modal coefficient of the bonding silver wire under the storage packaging ecology; and formulating a preparation scheme corresponding to the bonding silver wire, and executing preparation treatment of the bonding silver wire in the silver wire processing equipment cluster to obtain a silver wire prepared finished product. The main purpose of the invention is to solve the problem of poor stability of the preparation quality of the bonded silver wire.

Description

Technical Field

[0001] The invention relates to a preparation method and a system for realizing silver bonding wires, and belongs to the technical field of silver bonding wires. Background Art

[0002] Silver bonding wire is a key material in the fields of electronic packaging. With the rapid development of the electronics industry, the market demand for silver bonding wire has continued to rise. In order to meet the production requirements of high-precision and high-quality silver bonding wire, it is particularly important to optimize and intelligently control its preparation method and system.

[0003] The existing silver bonding wire preparation method and system mainly rely on the traditional process control process. First, the various process indicators and control parameters that need to be achieved in the preparation process of the silver bonding wire are determined, such as the ratio of raw materials, heating temperature, wire drawing speed, etc., and the appropriate processing equipment is selected according to these requirements. The relevant instruments and meters are installed and debugged, and various sensors are connected to monitor key data such as temperature, pressure, flow, etc., and actuators such as motors and valves are connected. The technicians write the control program based on past experimental data and production experience, and usually use a specific programming language to set the timing and quantity of raw material addition, the control logic of heating and cooling, and the tension adjustment during the wire drawing process. During the production process, the system collects sensor data according to the set program and parameters, and controls the action of the actuator accordingly. However, this method is mainly based on historical experience data to write programs, and it is difficult to quickly adapt to subtle changes in raw material properties, fluctuations in the production environment, and new process requirements. The control adaptability of the current silver bonding wire preparation system is low, resulting in poor stability in the preparation quality of the silver bonding wire. Summary of the invention

[0004] The present invention provides a method and system for preparing bonding silver wires, the main purpose of which is to solve the problem of poor preparation quality stability of the bonding silver wires.

[0005] To achieve the above object, the present invention provides a method for preparing a bonding silver wire, comprising:

[0006] Obtaining the preparation starting materials required for preparing the bonding silver wire, querying the silver wire processing equipment cluster in the preparation process, determining the manufacturing process instruction set corresponding to the silver wire processing equipment cluster, and formulating the quality reference factor corresponding to the silver wire processing equipment cluster based on the manufacturing process instruction set;

[0007] Collecting multidimensional processing data of the silver wire processing equipment cluster during the preparation process, mining the multidimensional processing features corresponding to the silver wire processing equipment cluster based on the multidimensional processing data, calculating the quality actuarial gradient corresponding to the quality reference factor based on the multidimensional processing features, and evaluating the equipment processing accuracy corresponding to the silver wire processing equipment cluster based on the quality actuarial gradient;

[0008] Collecting the silver wire microstructure image and component spectrum diagram of the bonding silver wire in the silver wire processing equipment cluster, and calculating the quality reliability and validity corresponding to the bonding silver wire by combining the silver wire microstructure image and the component spectrum diagram;

[0009] Querying the storage packaging ecology corresponding to the bonding silver wire, collecting the ecological parameter vector set corresponding to the storage packaging ecology, and calculating the storage modal coefficient of the bonding silver wire under the storage packaging ecology based on the ecological parameter vector set;

[0010] Based on the equipment processing accuracy, the quality reliability and validity, and the storage modal coefficient, a preparation plan corresponding to the bonding silver wire is formulated, and based on the preparation plan, the preparation processing of the bonding silver wire in the silver wire processing equipment cluster is performed to obtain a finished silver wire product.

[0011] Optionally, formulating a quality reference factor corresponding to the silver wire processing equipment cluster based on the manufacturing process instruction set includes:

[0012] In detail, the quality reference factor corresponding to the silver wire processing equipment cluster is formulated based on the manufacturing process instruction set, including:

[0013] Identify instruction set character information in the manufacturing process instruction set, and clarify the instruction set semantic connotation corresponding to the instruction set character information;

[0014] Based on the semantic connotation of the instruction set, filtering out the quality description characters in the instruction set character information;

[0015] The key quality characters in the quality description characters are extracted, and based on the key quality characters, the quality reference factors corresponding to the silver wire processing equipment cluster are formulated.

[0016] Optionally, extracting the quality key characters from the quality description characters includes:

[0017] Performing character classification processing on the quality description characters to obtain classification description characters;

[0018] Counting the character frequency corresponding to each character in the classification description characters;

[0019] Based on the character frequency, the character information entropy corresponding to the target description character is calculated by the following formula:

[0020]

[0021] Among them, A represents the character information entropy corresponding to the target description character, b a Indicates the ath character in the target description, B(b a ) represents the character frequency corresponding to the ath character in the target description character, a represents the sequence number corresponding to the target character, and p represents the number of characters corresponding to the target character;

[0022] According to the character information entropy, quality key characters in the classification description characters are extracted.

[0023] Optionally, mining the multi-dimensional processing features corresponding to the silver wire processing equipment cluster based on the multi-dimensional processing data includes:

[0024] Performing data denoising processing on the multi-dimensional processed data to obtain denoised multi-dimensional processed data;

[0025] Extracting process identifiers from the noise-reduced multi-dimensional processing data to obtain a processing multi-dimensional process identifier;

[0026] Calculating the degree of coordination between the multi-dimensional processing flow identifications, and based on the degree of coordination, selecting the core flow identifications in the multi-dimensional processing flow identifications;

[0027] Based on the core process identifier, feature mining is performed on the noise reduction multi-dimensional processing data to obtain the processing multi-dimensional features corresponding to the silver wire processing equipment cluster.

[0028] Optionally, the calculating the degree of coordination between the multi-dimensional processing flow identifiers includes:

[0029] Counting the number of identifier interactions between the processing multi-dimensional process identifiers, and calculating the identifier interaction frequency between the processing multi-dimensional process identifiers based on the number of identifier interactions;

[0030] The identification correlation between the multi-dimensional processing flow identifications is calculated, and the coordination tightness between the multi-dimensional processing flow identifications is calculated by combining the identification correlation and the identification interaction frequency through the following formula:

[0031]

[0032] Among them, D represents the degree of coordination between the multi-dimensional process identifiers, E k，k+1 represents the degree of association between the kth and k+1th identifications in the multi-dimensional processing flow identification, k and k+1 both represent the serial numbers corresponding to the multi-dimensional processing flow identification, Fk，k+1 represents the frequency of interaction between the kth and k+1th identifications in the multi-dimensional process identification of the processing, represents the exponential decay factor, i represents the identification sequence number other than the kth and k+1th identifications in the processing multidimensional process identification, and n represents the number of identifications in the processing multidimensional process identification.

[0033] Optionally, the calculating the quality actuarial gradient corresponding to the quality reference factor based on the processing multi-dimensional feature includes:

[0034] Performing feature selection processing on the processing multi-dimensional features to obtain target multi-dimensional features;

[0035] Performing feature quantization processing on the target multidimensional features to obtain multidimensional feature values;

[0036] Calculate the dimension weight value corresponding to each feature in the target multidimensional feature, combine the dimension weight value and the multidimensional feature value, and calculate the quality actuarial gradient corresponding to the quality benchmark factor by the following formula:

[0037]

[0038] Among them, G represents the quality actuarial gradient corresponding to the quality reference factor, Indicates the dimension weight value corresponding to the dth feature in the target multidimensional feature, H d Represents the multidimensional feature value corresponding to the dth feature in the target multidimensional feature, Indicates the feature reference value corresponding to the dth feature in the target multidimensional feature.

[0039] Optionally, the combining the silver wire microstructure image and the component spectrum to calculate the quality reliability and validity corresponding to the bonding silver wire includes:

[0040] Analyzing the morphological characteristics corresponding to the bonding silver wire based on the silver wire microstructure image;

[0041] Smoothing the component spectrum to obtain a smoothed spectrum;

[0042] Performing peak position identification on the smoothed spectrum to obtain spectrum peak positions, and extracting peak position characteristic information corresponding to the spectrum peak positions;

[0043] Based on the peak position characteristic information, analyzing the chemical bonding characteristics corresponding to the bonding silver wire;

[0044] The quality reliability and validity of the bonded silver wire are calculated by combining the morphological characteristics and the chemical bonding characteristics.

[0045] Optionally, analyzing the morphological features corresponding to the bonding silver wires based on the silver wire microstructure image includes:

[0046] grayscale the silver wire microstructure image to obtain a grayscale microstructure image;

[0047] Performing edge detection processing on the grayscale microscopic tissue image to obtain a microscopic tissue edge image;

[0048] Performing topological analysis on the microscopic tissue edge image to obtain tissue edge features;

[0049] The characteristic fractal dimension corresponding to the tissue edge feature is calculated, and based on the characteristic fractal dimension, the morphological feature corresponding to the bonding silver wire is generated.

[0050] Optionally, the combining the morphological features and the chemical bonding features to calculate the quality reliability and validity corresponding to the bonded silver wire includes:

[0051] Performing vectorization processing on the morphological features and the chemical bonding features respectively to obtain a morphological feature vector and a chemical feature vector;

[0052] Normalizing the morphological feature vector and the chemical feature vector respectively to obtain a normalized morphological feature vector and a normalized chemical feature vector;

[0053] Combining the normalized morphological feature vector and the normalized chemical feature vector, the quality reliability and validity corresponding to the bonding silver wire is calculated by the following formula:

[0054]

[0055] Among them, Q represents the quality reliability and validity of the bonding silver wire, M g represents the gth vector in the normalized morphological feature vector, N h represents the hth vector in the normalized chemical feature vector, g and h represent the vector serial numbers corresponding to the normalized morphological feature vector and the normalized chemical feature vector, respectively, and x and y represent the number of vectors corresponding to the normalized morphological feature vector and the normalized chemical feature vector, respectively.

[0056] A system for preparing bonding silver wires, characterized in that the system comprises:

[0057] A quality reference factor formulation module is used to obtain the preparation starting materials required for preparing the bonding silver wire, query the silver wire processing equipment cluster in the preparation process, determine the manufacturing process instruction set corresponding to the silver wire processing equipment cluster, and formulate the quality reference factor corresponding to the silver wire processing equipment cluster based on the manufacturing process instruction set;

[0058] An equipment processing accuracy calculation module is used to collect multi-dimensional processing data of the silver wire processing equipment cluster during the preparation process, mine the processing multi-dimensional features corresponding to the silver wire processing equipment cluster based on the multi-dimensional processing data, calculate the quality actuarial gradient corresponding to the quality reference factor based on the processing multi-dimensional features, and evaluate the equipment processing accuracy corresponding to the silver wire processing equipment cluster based on the quality actuarial gradient;

[0059] A quality reliability and validity calculation module, used for collecting the silver wire microstructure image and component spectrum diagram of the bonding silver wire in the silver wire processing equipment cluster, and combining the silver wire microstructure image and the component spectrum diagram to calculate the quality reliability and validity corresponding to the bonding silver wire;

[0060] A storage modal coefficient calculation module, used to query the storage packaging ecology corresponding to the bonding silver wire, collect the ecological parameter vector set corresponding to the storage packaging ecology, and calculate the storage modal coefficient of the bonding silver wire under the storage packaging ecology based on the ecological parameter vector set;

[0061] A preparation processing module is used to formulate a preparation plan corresponding to the bonding silver wire based on the equipment processing accuracy, the quality reliability and validity, and the storage modal coefficient, and based on the preparation plan, execute the preparation processing of the bonding silver wire in the silver wire processing equipment cluster to obtain a finished silver wire preparation product.

[0062] Compared with the problems described in the background technology, the present invention formulates the quality reference factors corresponding to the silver wire processing equipment cluster based on the manufacturing process instruction set, so as to obtain the key parameters for quality control in the bonding silver wire processing process, thereby facilitating the subsequent precise standardization of the quality standards for silver wire processing. The present invention mines the multi-dimensional processing characteristics corresponding to the silver wire processing equipment cluster based on the multi-dimensional processing data, and can accurately sort out the architectural characteristic description of the silver wire processing equipment cluster in different processing aspects, thereby improving the calculation accuracy of the quality actuarial gradient corresponding to the subsequent quality reference factors. The present invention calculates the quality reliability and validity corresponding to the bonding silver wire by combining the silver wire microstructure image and the component spectrum diagram, and can understand the quality reliability of the bonding silver wire through the quality reliability and validity. degree, thereby improving the accuracy of the subsequent preparation plan corresponding to the bonding silver wire. The present invention calculates the storage modal coefficient of the bonding silver wire in the storage packaging ecology based on the ecological parameter vector set, and the stability state of the bonding silver wire in the storage packaging ecology can be understood through the storage modal coefficient, thereby providing a basis for the subsequent preparation plan corresponding to the bonding silver wire. The present invention formulates the preparation plan corresponding to the bonding silver wire based on the equipment processing accuracy, the quality reliability and validity, and the storage modal coefficient, and can obtain a more detailed preparation method for the bonding silver wire. Based on the preparation plan, the preparation process of the bonding silver wire in the silver wire processing equipment cluster is performed, which can improve the preparation quality stability of the bonding silver wire. Therefore, the present invention proposes a method and system for realizing the preparation of bonding silver wires, thereby improving the preparation quality stability of bonding silver wires. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 A schematic diagram of a process for preparing a bonding silver wire provided in one embodiment of the present invention;

[0064] Figure 2 A functional module diagram of a preparation system for bonding silver wires provided in accordance with an embodiment of the present invention.

[0065] 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

[0066] 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.

[0067] The embodiment of the present application provides a method for preparing a silver bonding wire. The execution subject of the method for preparing a silver bonding wire 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 preparing a silver bonding wire 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.

[0068] Embodiment 1:

[0069] Reference Figure 1 As shown, it is a schematic diagram of a process for preparing a bonding silver wire provided by an embodiment of the present invention.

[0070] In this embodiment, the preparation method for realizing bonding silver wire includes:

[0071] S1. Obtain the preparation starting materials required for preparing bonding silver wires, query the silver wire processing equipment cluster in the preparation process, determine the manufacturing process instruction set corresponding to the silver wire processing equipment cluster, and formulate the quality reference factor corresponding to the silver wire processing equipment cluster based on the manufacturing process instruction set.

[0072] The present invention formulates the quality reference factor corresponding to the silver wire processing equipment cluster based on the manufacturing process instruction set, and can obtain the key parameters for quality control in the bonding silver wire processing process, so as to facilitate the subsequent accurate standardization of the quality standards of silver wire processing. It should be explained that the preparation starting material is the processing raw material required for the bonding silver wire processing, and the silver wire processing equipment cluster is a core production equipment set for completing each processing step in the bonding silver wire preparation process. The manufacturing process instruction set is a detailed operation guide set corresponding to the silver wire processing equipment cluster that specifies the operation flow, parameter setting, etc. of each process, and the quality reference factor is a key reference indicator corresponding to the silver wire processing equipment cluster to measure whether the quality of the silver wire products produced by it meets the standards; further, the preparation starting material required for the preparation of bonding silver wire can be obtained through the supply data of professional suppliers; the silver wire processing equipment cluster in the preparation process can be queried in the enterprise production management system of the bonding silver wire; the determination of the manufacturing process instruction set corresponding to the silver wire processing equipment cluster can be achieved through the equipment production manual.

[0073] In detail, the quality reference factor corresponding to the silver wire processing equipment cluster is formulated based on the manufacturing process instruction set, including:

[0074] In detail, the quality reference factor corresponding to the silver wire processing equipment cluster is formulated based on the manufacturing process instruction set, including:

[0075] Identify instruction set character information in the manufacturing process instruction set, and clarify the instruction set semantic connotation corresponding to the instruction set character information;

[0076] Based on the semantic connotation of the instruction set, filtering out the quality description characters in the instruction set character information;

[0077] The key quality characters in the quality description characters are extracted, and based on the key quality characters, the quality reference factors corresponding to the silver wire processing equipment cluster are formulated.

[0078] It should be explained that the instruction set character information is the specific content expression presented in text form in the manufacturing process instruction set, the instruction set semantic connotation is the deep meaning contained in the instruction set character information regarding the requirements of each link in silver wire processing, quality standards, etc., the quality description character is the character part of the instruction set character information used to describe the quality-related attributes and requirements of silver wire products, and the quality key character is the character in the quality description character that is closely related to key quality control links, important quality indicators, etc. and plays an important role in formulating quality benchmark factors.

[0079] Furthermore, the instruction set character information in the manufacturing process instruction set can be identified through OCR recognition technology; the information semantics corresponding to the instruction set character information can be analyzed to determine the instruction set semantic connotation corresponding to the instruction set character information according to the information semantics; the instruction set semantic connotation is matched with the vocabulary in the preset quality keyword library based on the keyword matching method to screen out the quality description characters in the instruction set character information; based on the quality-related characters, the quality reference factor corresponding to the silver wire processing equipment cluster is formulated.

[0080] Further, as an optional embodiment of the present invention, the extracting the quality key characters in the quality description characters includes:

[0081] Performing character classification processing on the quality description characters to obtain classification description characters;

[0082] Counting the character frequency corresponding to each character in the classification description characters;

[0083] Based on the character frequency, the character information entropy corresponding to the target description character is calculated by the following formula:

[0084]

[0085] Among them, A represents the character information entropy corresponding to the target description character, b a Indicates the ath character in the target description, B(b a) represents the character frequency corresponding to the ath character in the target description character, a represents the sequence number corresponding to the target character, and p represents the number of characters corresponding to the target character;

[0086] According to the character information entropy, quality key characters in the classification description characters are extracted.

[0087] Among them, the classification description characters are the products of the quality description characters being divided according to certain rules (such as according to the silver wire processing procedures, quality attribute categories, etc.); the character frequency indicates the frequency of occurrence of each character in the classification description characters within a given text range; the character information entropy indicates a measure of the degree of uncertainty of the amount of information contained in the target description characters; further, the quality description characters can be classified according to the quality attribute classification standard to obtain the classification description characters; the character frequency corresponding to each character in the classification description characters can be counted by counting method; according to the character information entropy, the quality key characters in the classification description characters are extracted, such as in the instruction set of silver wire processing, there are classification description characters such as "silver wire diameter tolerance", "silver wire annealing temperature range", and "silver wire packaging materials", and the information entropy corresponding to "silver wire diameter tolerance" and "silver wire annealing temperature range" is relatively low, indicating that they are more precise and clear in expression, and the key quality information contained is more concentrated, so these two characters are extracted as quality key characters.

[0088] S2. Collect multi-dimensional processing data of the silver wire processing equipment cluster during the preparation process, mine the multi-dimensional processing features corresponding to the silver wire processing equipment cluster based on the multi-dimensional processing data, calculate the quality actuarial gradient corresponding to the quality reference factor based on the multi-dimensional processing features, and evaluate the equipment processing accuracy corresponding to the silver wire processing equipment cluster based on the quality actuarial gradient.

[0089] The present invention mines the processing multi-dimensional features corresponding to the silver wire processing equipment cluster based on the multi-dimensional processing data, and can accurately sort out the architectural characteristic descriptions of the silver wire processing equipment cluster in different processing aspects, thereby improving the calculation accuracy of the quality actuarial gradient corresponding to the subsequent quality reference factor. It should be explained that the multi-dimensional processing data is multi-dimensional data generated by the silver wire processing equipment cluster during the preparation process, including various processing-related parameters, process execution status, equipment operation status, etc. The processing multi-dimensional features are the processing features of multiple dimensions corresponding to the silver wire processing equipment cluster from raw material input to finished product output, involving equipment layout, process connection, process link association, etc., which reflect the systematicness and logic of the processing flow. Furthermore, the multi-dimensional processing data of the silver wire processing equipment cluster during the preparation process can be collected through data sensors.

[0090] Specifically, mining the multi-dimensional processing features corresponding to the silver wire processing equipment cluster based on the multi-dimensional processing data includes:

[0091] Performing data denoising processing on the multi-dimensional processed data to obtain denoised multi-dimensional processed data;

[0092] Extracting process identifiers from the noise-reduced multi-dimensional processing data to obtain a processing multi-dimensional process identifier;

[0093] Calculating the degree of coordination between the multi-dimensional processing flow identifications, and based on the degree of coordination, selecting the core flow identifications in the multi-dimensional processing flow identifications;

[0094] Based on the core process identifier, feature mining is performed on the noise reduction multi-dimensional processing data to obtain the processing multi-dimensional features corresponding to the silver wire processing equipment cluster.

[0095] It should be explained that the denoised multi-dimensional processing data is the data obtained after the multi-dimensional processing data is processed to remove abnormal data; the processing multi-dimensional process identifier is a related identifier extracted from the denoised multi-dimensional processing data and used to mark different processing links and reflect the characteristics and sequence of the processing process; the collaborative tightness is a quantitative indicator of the degree of mutual cooperation and coordination between the processing multi-dimensional process identifiers; the core process identifier is an identifier in the processing multi-dimensional process identifier that plays a key role in the silver wire processing quality, efficiency, etc. and occupies an important position in the entire processing architecture.

[0096] Furthermore, the multidimensional processing data can be subjected to data denoising by a filtering algorithm to obtain denoised multidimensional processing data; the process identifier can be extracted from the denoised multidimensional processing data by an identifier extraction tool to obtain a processing multidimensional process identifier, and the identifier extraction tool is compiled by a script language, such as JS script language; based on the synergy closeness, the core process identifier in the processing multidimensional process identifier is screened out, such as the high synergy closeness between "silver wire drawing" and "silver wire annealing" in the processing multidimensional process identifier, which means that the close cooperation between the two has a significant impact on the quality of the silver wire, and therefore "silver wire drawing" and "silver wire annealing" are screened as core process identifiers; the denoised multidimensional processing data corresponding to the core process identifier can be feature mined by a neural network model to obtain the processing multidimensional features corresponding to the silver wire processing equipment cluster, such as an association rule mining algorithm.

[0097] Further, as an optional embodiment of the present invention, the calculating the degree of coordination between the multi-dimensional processing flow identifiers includes:

[0098] Counting the number of identifier interactions between the processing multi-dimensional process identifiers, and calculating the identifier interaction frequency between the processing multi-dimensional process identifiers based on the number of identifier interactions;

[0099] The identification correlation between the multi-dimensional processing flow identifications is calculated, and the coordination tightness between the multi-dimensional processing flow identifications is calculated by combining the identification correlation and the identification interaction frequency through the following formula:

[0100]

[0101] Among them, D represents the degree of coordination between the multi-dimensional process identifiers, E k，k+1 represents the degree of association between the kth and k+1th identifications in the multi-dimensional processing flow identification, k and k+1 both represent the serial numbers corresponding to the multi-dimensional processing flow identification, F k，k+1 represents the frequency of interaction between the kth and k+1th identifications in the multi-dimensional process identification of the processing, represents the exponential decay factor, i represents the identification sequence number other than the kth and k+1th identifications in the processing multidimensional process identification, and n represents the number of identifications in the processing multidimensional process identification.

[0102] Furthermore, It is an exponential decay term, where i is the identification number other than the pair of process identifications for which the synergy closeness is to be calculated. This term reflects the influence of the relative position relationship of the multi-dimensional process identification in the entire process system on the synergy closeness.

[0103] Among them, the number of identifier interactions represents the cumulative number of actual interactions, information transfers or material handovers between the processing multi-dimensional process identifiers; the identifier interaction frequency represents the frequency of interactions between the processing multi-dimensional process identifiers within a unit time; and the identifier association degree represents the degree of mutual association between the data features of the processing multi-dimensional process identifiers.

[0104] Furthermore, the number of identifier interactions between the processing multi-dimensional process identifiers can be counted through the system log records of the silver wire processing equipment cluster, and the identifier interaction frequency between the processing multi-dimensional process identifiers can be obtained by dividing the number of identifier interactions by the corresponding statistical time interval length; the identifier association degree between the processing multi-dimensional process identifiers can be obtained by calculating the association degree between the data corresponding to the processing multi-dimensional process identifiers.

[0105] The present invention calculates the quality actuarial gradient corresponding to the quality reference factor based on the multi-dimensional characteristics of processing. The quality actuarial gradient can be used to understand the degree and trend of influence of the quality reference factor on the quality in the processing process, thereby laying a foundation for the subsequent evaluation of the equipment processing accuracy corresponding to the silver wire processing equipment. It should be explained that the quality actuarial gradient represents the sensitivity and trend of the quality reference factor on the processing of the silver wire processing equipment cluster, and the equipment processing accuracy represents the processing accuracy corresponding to each device in the silver wire processing equipment cluster. Furthermore, the equipment processing accuracy corresponding to the silver wire processing equipment cluster is evaluated according to the numerical value of the quality actuarial gradient. If the quality actuarial gradient is 0.8, it means that the equipment processing accuracy is excellent.

[0106] In detail, the calculating of the quality actuarial gradient corresponding to the quality reference factor based on the processing multi-dimensional feature includes:

[0107] Performing feature selection processing on the processing multi-dimensional features to obtain target multi-dimensional features;

[0108] Performing feature quantization processing on the target multidimensional features to obtain multidimensional feature values;

[0109] Calculate the dimension weight value corresponding to each feature in the target multidimensional feature, combine the dimension weight value and the multidimensional feature value, and calculate the quality actuarial gradient corresponding to the quality benchmark factor by the following formula:

[0110]

[0111] Among them, G represents the quality actuarial gradient corresponding to the quality reference factor, Indicates the dimension weight value corresponding to the dth feature in the target multidimensional feature, H d Represents the multidimensional feature value corresponding to the dth feature in the target multidimensional feature, Indicates the feature reference value corresponding to the dth feature in the target multidimensional feature.

[0112] Among them, the target multidimensional feature is a representative feature obtained after the processing multidimensional feature is selected, and the multidimensional feature value is the specific numerical embodiment corresponding to the target multidimensional feature. Furthermore, the processing multidimensional feature can be subjected to feature selection processing by the information gain method to obtain the target multidimensional feature; the target multidimensional feature can be subjected to feature quantization processing by the one-hot encoding method to obtain the multidimensional feature value.

[0113] S3. Collect the silver wire microstructure image and component spectrum diagram of the bonding silver wire in the silver wire processing equipment cluster, and calculate the quality reliability and validity corresponding to the bonding silver wire by combining the silver wire microstructure image and the component spectrum diagram.

[0114] The present invention calculates the quality reliability and validity corresponding to the bonded silver wire by combining the silver wire microstructure image and the component spectrum diagram. The quality reliability and validity can be used to understand the quality reliability degree of the bonded silver wire, thereby improving the accuracy of the subsequent formulation of the preparation plan corresponding to the bonded silver wire. It should be explained that the silver wire microstructure image is an image obtained by microscopic imaging technology in the silver wire processing equipment cluster; the component spectrum diagram is a spectrum obtained by using a spectral analysis instrument in the silver wire processing equipment cluster, which can reflect the various element components and their relative content ratios contained in the bonded silver wire. The quality reliability and validity represents a measurement value of the quality reliability degree corresponding to the bonded silver wire. Furthermore, the collection of the silver wire microstructure image and the component spectrum diagram of the bonded silver wire in the silver wire processing equipment cluster can be achieved by optical microscopes, atomic emission spectrometers and other equipment respectively.

[0115] In detail, the combining of the silver wire microstructure image and the component spectrum to calculate the quality reliability and validity corresponding to the bonding silver wire includes:

[0116] Analyzing the morphological characteristics corresponding to the bonding silver wire based on the silver wire microstructure image;

[0117] Smoothing the component spectrum to obtain a smoothed spectrum;

[0118] Performing peak position identification on the smoothed spectrum to obtain spectrum peak positions, and extracting peak position characteristic information corresponding to the spectrum peak positions;

[0119] Based on the peak position characteristic information, analyzing the chemical bonding characteristics corresponding to the bonding silver wire;

[0120] The quality reliability and validity of the bonded silver wire are calculated by combining the morphological characteristics and the chemical bonding characteristics.

[0121] Among them, the morphological characteristics are the characteristics related to the external and internal microstructural morphology of the bonding silver wire, such as grain size, grain boundary morphology, defects, etc., obtained through microstructure image analysis; the smoothed spectrum is the spectrum of the component spectrum after smoothing processing such as denoising and background subtraction, which is more conducive to analyzing the characteristic peaks of elements; the spectrum peak position is the position information of the characteristic peak of the element in the smoothed spectrum; the peak position characteristic information is the detailed characteristics corresponding to the spectrum peak position, including peak intensity, peak width, peak symmetry, etc., which are used to assist element identification and quantitative analysis; the chemical bonding characteristics are the characteristics of the bonding silver wire that reflect the bonding mode, bond energy, bond length and other bonding-related characteristics.

[0122] Furthermore, the component spectrum can be smoothed by a moving average method to obtain a smooth spectrum; the peak position of the smooth spectrum can be identified by a local maximum search algorithm to obtain a spectrum peak, and the peak position characteristic information corresponding to the spectrum peak can be extracted by spectrum analysis software, such as KnowItAll analysis software; based on the peak position characteristic information, the chemical bonding characteristics corresponding to the bonding silver wire are analyzed. For example, if the characteristic peak intensity of an element in the peak position characteristic information is high and the peak shape is sharp, it may indicate that the proportion of the element participating in chemical bonding in the bonding silver wire is large and the bonding is relatively stable.

[0123] Further, as an optional embodiment of the present invention, the analyzing the morphological features corresponding to the bonding silver wire based on the silver wire microstructure image includes:

[0124] grayscale the silver wire microstructure image to obtain a grayscale microstructure image;

[0125] Performing edge detection processing on the grayscale microscopic tissue image to obtain a microscopic tissue edge image;

[0126] Performing topological analysis on the microscopic tissue edge image to obtain tissue edge features;

[0127] The characteristic fractal dimension corresponding to the tissue edge feature is calculated, and based on the characteristic fractal dimension, the morphological feature corresponding to the bonding silver wire is generated.

[0128] Among them, the grayscale microstructure image is the image obtained by converting the silver wire microstructure image into an image containing only grayscale information; the microstructure edge image is the image of the boundary contours of different microstructure areas in the grayscale microstructure image; the tissue edge feature is the structural features such as the connection relationship and connectivity between the microstructure edges obtained by topological analysis of the microstructure edge image; the characteristic fractal dimension is a numerical indicator corresponding to the tissue edge feature that quantitatively describes the complexity and irregularity of the microstructure edge.

[0129] Furthermore, the silver wire microstructure image can be grayed by a pixel averaging method to obtain a grayscale microstructure image, the color average values ​​of the three channels of each pixel are calculated to obtain a grayscale value, and the grayscale value is used to perform grayscale processing on each pixel point; the grayscale microstructure image can be edge detected by an edge detection algorithm to obtain a microstructure edge image, and the edge detection algorithm includes a Canny edge detection algorithm; the microstructure edge image can be topologically analyzed by a morphological topological analysis method to obtain tissue edge features, such as obtaining the topological features of the microstructure edge image by calculating the Euler number, which is defined as the number of connected areas in the image minus the number of holes; the characteristic fractal dimension corresponding to the tissue edge feature can be calculated by a fractal algorithm, such as a box counting method; based on the characteristic fractal dimension, the morphological features corresponding to the bonding silver wire are generated, and if the characteristic fractal dimension is high, it indicates that the morphology of the bonding silver wire microstructure edge is complex and irregular.

[0130] Further, as an optional embodiment of the present invention, the combining the morphological features and the chemical bonding features to calculate the quality reliability and validity corresponding to the bonding silver wire includes:

[0131] Performing vectorization processing on the morphological features and the chemical bonding features respectively to obtain a morphological feature vector and a chemical feature vector;

[0132] Normalizing the morphological feature vector and the chemical feature vector respectively to obtain a normalized morphological feature vector and a normalized chemical feature vector;

[0133] Combining the normalized morphological feature vector and the normalized chemical feature vector, the quality reliability and validity corresponding to the bonding silver wire is calculated by the following formula:

[0134]

[0135] Among them, Q represents the quality reliability and validity of the bonding silver wire, M g represents the gth vector in the normalized morphological feature vector, N h represents the hth vector in the normalized chemical feature vector, g and h represent the vector serial numbers corresponding to the normalized morphological feature vector and the normalized chemical feature vector, respectively, and x and y represent the number of vectors corresponding to the normalized morphological feature vector and the normalized chemical feature vector, respectively.

[0136] Among them, the morphological feature vector and the chemical feature vector are respectively the vector representations formed by orderly organizing the relevant feature parameters through vectorization processing of the morphological feature and the chemical bonding feature; the normalized morphological feature vector and the normalized chemical feature vector are respectively the vector forms of the morphological feature vector and the chemical feature vector after normalization processing so that each element satisfies the specific normalization rule and is convenient for subsequent unified calculation and comparative analysis; further, the morphological feature and the chemical bonding feature can be vectorized by an auto-encoder neural network algorithm to obtain a morphological feature vector and a chemical feature vector; the morphological feature vector and the chemical feature vector are respectively divided by the corresponding vector modulus to achieve normalization processing to obtain a normalized morphological feature vector and a normalized chemical feature vector.

[0137] S4. Query the storage packaging ecology corresponding to the bonding silver wire, collect the ecological parameter vector set corresponding to the storage packaging ecology, and calculate the storage modal coefficient of the bonding silver wire under the storage packaging ecology based on the ecological parameter vector set.

[0138] The present invention calculates the storage modal coefficient of the bonding silver wire in the storage packaging ecology based on the ecological parameter vector set. The stability state of the bonding silver wire in the storage packaging ecology can be understood through the storage modal coefficient, thereby providing a basis for the subsequent formulation of the corresponding preparation plan for the bonding silver wire.

[0139] It should be explained that the storage packaging ecology is the external storage condition as a whole corresponding to the bonding silver wire, which includes packaging materials, storage environment temperature and humidity, gas composition and other factors; the ecological parameter vector set is a vector set corresponding to the storage packaging ecology, which combines various parameters affecting storage such as temperature and humidity change values, gas concentration changes, and packaging material performance parameter changes according to certain rules. The storage modal coefficient represents the stability measurement value of the bonding silver wire under the storage packaging ecology. Furthermore, the storage packaging ecology corresponding to the bonding silver wire can be queried through human-computer interaction, and can be obtained through various The environmental monitoring equipment collects the ecological parameter vector set corresponding to the storage packaging ecology, such as temperature and humidity sensors and gas composition analyzers; based on the ecological parameter vector set, the storage modal coefficient of the bonding silver wire in the storage packaging ecology is calculated, and the value of each vector in the ecological parameter vector set is subtracted from the corresponding standard value, and the difference is divided by the standard value to obtain the vector storage deviation corresponding to each vector, and the average deviation of the bonding silver wire in the storage packaging ecology is calculated according to the vector storage deviation, and the storage modal coefficient of the bonding silver wire in the storage packaging ecology is obtained by 1-average deviation.

[0140] S5. Based on the equipment processing accuracy, the quality reliability and validity, and the storage modal coefficient, a preparation plan corresponding to the bonding silver wire is formulated. Based on the preparation plan, the preparation process of the bonding silver wire in the silver wire processing equipment cluster is performed to obtain a finished silver wire product.

[0141] The present invention formulates a preparation plan corresponding to the bonding silver wire based on the equipment processing accuracy, the quality reliability and validity, and the storage modal coefficient, so as to obtain a more detailed preparation method of the bonding silver wire, and based on the preparation plan, performs the preparation processing of the bonding silver wire in the silver wire processing equipment cluster, so as to improve the preparation quality stability of the bonding silver wire. It should be explained that the preparation plan is a series of detailed preparation plan methods formulated by the bonding silver wire based on the equipment processing accuracy, the quality reliability and validity, and the storage modal coefficient. Furthermore, based on the equipment processing accuracy, the quality reliability and validity, and the storage modal coefficient, formulate a corresponding preparation plan for the bonding silver wire. If the equipment has high processing accuracy, a more precise range of silver wire drawing process parameters can be set in the preparation plan, such as strictly controlling the variation range of the drawing speed and force. According to the quality reliability, the temperature, pressure and time of the bonding link are accurately controlled to ensure excellent bonding effect. In combination with the storage modal coefficient, determine the appropriate packaging material and storage environment temperature and humidity range, such as using moisture-proof and antioxidant packaging, setting the storage temperature in a specific range, to ensure the quality stability of the bonding silver wire throughout the preparation and storage process, so as to obtain the corresponding preparation plan for the bonding silver wire.

[0142] Compared with the problems described in the background technology, the present invention formulates the quality reference factors corresponding to the silver wire processing equipment cluster based on the manufacturing process instruction set, so as to obtain the key parameters for quality control in the bonding silver wire processing process, thereby facilitating the subsequent precise standardization of the quality standards for silver wire processing. The present invention mines the multi-dimensional processing characteristics corresponding to the silver wire processing equipment cluster based on the multi-dimensional processing data, and can accurately sort out the architectural characteristic description of the silver wire processing equipment cluster in different processing aspects, thereby improving the calculation accuracy of the quality actuarial gradient corresponding to the subsequent quality reference factors. The present invention calculates the quality reliability and validity corresponding to the bonding silver wire by combining the silver wire microstructure image and the component spectrum diagram, and can understand the quality reliability of the bonding silver wire through the quality reliability and validity. degree, thereby improving the accuracy of the subsequent preparation plan corresponding to the bonding silver wire. The present invention calculates the storage modal coefficient of the bonding silver wire in the storage packaging ecology based on the ecological parameter vector set, and the stability state of the bonding silver wire in the storage packaging ecology can be understood through the storage modal coefficient, thereby providing a basis for the subsequent preparation plan corresponding to the bonding silver wire. The present invention formulates the preparation plan corresponding to the bonding silver wire based on the equipment processing accuracy, the quality reliability and validity, and the storage modal coefficient, and can obtain a more detailed preparation method for the bonding silver wire. Based on the preparation plan, the preparation process of the bonding silver wire in the silver wire processing equipment cluster is performed, which can improve the preparation quality stability of the bonding silver wire. Therefore, the present invention proposes a method for realizing the preparation of bonding silver wire, thereby improving the preparation quality stability of the bonding silver wire.

[0143] Embodiment 2:

[0144] like Figure 2 1 is a functional module diagram of a system for preparing bonding silver wires provided by an embodiment of the present invention.

[0145] The preparation system 100 for realizing bonding silver wires described in the present invention can be installed in an electronic device. According to the functions to be realized, the preparation system 100 for realizing bonding silver wires can include a quality reference factor formulation module 101, an equipment processing accuracy calculation module 102, a quality reliability calculation module 103, a storage modal coefficient calculation module 104 and a preparation processing module 105. The module described in the present invention can also be referred to as 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.

[0146] In this embodiment, the functions of each module / unit are as follows:

[0147] The quality reference factor formulation module 101 is used to obtain the preparation starting materials required for preparing the bonding silver wire, and query the silver wire processing equipment cluster in the preparation process, determine the manufacturing process instruction set corresponding to the silver wire processing equipment cluster, and formulate the quality reference factor corresponding to the silver wire processing equipment cluster based on the manufacturing process instruction set;

[0148] The equipment processing accuracy calculation module 102 is used to collect multi-dimensional processing data of the silver wire processing equipment cluster during the preparation process, mine the processing multi-dimensional features corresponding to the silver wire processing equipment cluster based on the multi-dimensional processing data, calculate the quality actuarial gradient corresponding to the quality reference factor based on the processing multi-dimensional features, and evaluate the equipment processing accuracy corresponding to the silver wire processing equipment cluster based on the quality actuarial gradient;

[0149] The quality reliability and validity calculation module 103 is used to collect the silver wire microstructure image and component spectrum diagram of the bonding silver wire in the silver wire processing equipment cluster, and calculate the quality reliability and validity corresponding to the bonding silver wire by combining the silver wire microstructure image and the component spectrum diagram;

[0150] The storage modal coefficient calculation module 104 is used to query the storage packaging ecology corresponding to the bonding silver wire, collect the ecological parameter vector set corresponding to the storage packaging ecology, and calculate the storage modal coefficient of the bonding silver wire under the storage packaging ecology based on the ecological parameter vector set;

[0151] The preparation processing module 105 is used to formulate a preparation plan corresponding to the bonding silver wire based on the equipment processing accuracy, the quality reliability and validity, and the storage modal coefficient, and based on the preparation plan, execute the preparation processing of the bonding silver wire in the silver wire processing equipment cluster to obtain a finished silver wire preparation product.

[0152] In detail, each module described in the system 100 for preparing silver bonding wires 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 the preparation method for bonding silver wire can produce the same technical effect, which will not be repeated here.

[0153] 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.

[0154] 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 preparing bonding silver wire, characterized in that: The method comprises: Obtaining the preparation starting materials required for preparing the bonding silver wire, querying the silver wire processing equipment cluster in the preparation process, determining the manufacturing process instruction set corresponding to the silver wire processing equipment cluster, and formulating the quality reference factor corresponding to the silver wire processing equipment cluster based on the manufacturing process instruction set; Collecting multidimensional processing data of the silver wire processing equipment cluster during the preparation process, mining the multidimensional processing features corresponding to the silver wire processing equipment cluster based on the multidimensional processing data, calculating the quality actuarial gradient corresponding to the quality reference factor based on the multidimensional processing features, and evaluating the equipment processing accuracy corresponding to the silver wire processing equipment cluster based on the quality actuarial gradient; Collecting the silver wire microstructure image and component spectrum diagram of the bonding silver wire in the silver wire processing equipment cluster, and calculating the quality reliability and validity corresponding to the bonding silver wire by combining the silver wire microstructure image and the component spectrum diagram; Querying the storage packaging ecology corresponding to the bonding silver wire, collecting the ecological parameter vector set corresponding to the storage packaging ecology, and calculating the storage modal coefficient of the bonding silver wire under the storage packaging ecology based on the ecological parameter vector set; Based on the equipment processing accuracy, the quality reliability and validity, and the storage modal coefficient, a preparation plan corresponding to the bonding silver wire is formulated, and based on the preparation plan, the preparation processing of the bonding silver wire in the silver wire processing equipment cluster is performed to obtain a finished silver wire product.

2. The method for preparing bonding silver wire according to claim 1, characterized in that: The step of formulating a quality reference factor corresponding to the silver wire processing equipment cluster based on the manufacturing process instruction set includes: In detail, the quality reference factor corresponding to the silver wire processing equipment cluster is formulated based on the manufacturing process instruction set, including: Identify instruction set character information in the manufacturing process instruction set, and clarify the instruction set semantic connotation corresponding to the instruction set character information; Based on the semantic connotation of the instruction set, filtering out the quality description characters in the instruction set character information; The key quality characters in the quality description characters are extracted, and based on the key quality characters, the quality reference factors corresponding to the silver wire processing equipment cluster are formulated.

3. The method for preparing bonding silver wire according to claim 2, characterized in that: The step of extracting the quality key characters from the quality description characters comprises: Performing character classification processing on the quality description characters to obtain classification description characters; Counting the character frequency corresponding to each character in the classification description characters; Based on the character frequency, the character information entropy corresponding to the target description character is calculated by the following formula: Among them, A represents the character information entropy corresponding to the target description character, b a Indicates the ath character in the target description, B(b a ) represents the character frequency corresponding to the ath character in the target description character, a represents the sequence number corresponding to the target character, and p represents the number of characters corresponding to the target character; According to the character information entropy, quality key characters in the classification description characters are extracted.

4. The method for preparing bonding silver wire according to claim 1, characterized in that: The mining of the processing multi-dimensional features corresponding to the silver wire processing equipment cluster based on the multi-dimensional processing data includes: Performing data denoising processing on the multi-dimensional processed data to obtain denoised multi-dimensional processed data; Extracting process identifiers from the noise-reduced multi-dimensional processing data to obtain a processing multi-dimensional process identifier; Calculating the degree of coordination between the multi-dimensional processing flow identifications, and based on the degree of coordination, selecting the core flow identifications in the multi-dimensional processing flow identifications; Based on the core process identifier, feature mining is performed on the noise reduction multi-dimensional processing data to obtain the processing multi-dimensional features corresponding to the silver wire processing equipment cluster.

5. The method for preparing bonding silver wire according to claim 4, characterized in that: The calculating the degree of coordination between the multi-dimensional processing flow identifiers includes: Counting the number of identifier interactions between the processing multi-dimensional process identifiers, and calculating the identifier interaction frequency between the processing multi-dimensional process identifiers based on the number of identifier interactions; The identification correlation between the multi-dimensional processing flow identifications is calculated, and the coordination tightness between the multi-dimensional processing flow identifications is calculated by combining the identification correlation and the identification interaction frequency through the following formula: Among them, D represents the degree of coordination between the multi-dimensional process identifiers, E k，k+1 represents the degree of association between the kth and k+1th identifications in the multi-dimensional processing flow identification, k and k+1 both represent the serial numbers corresponding to the multi-dimensional processing flow identification, F k，k+1 represents the frequency of interaction between the kth and k+1th identifications in the multi-dimensional process identification of the processing, represents the exponential decay factor, i represents the identification sequence number other than the kth and k+1th identifications in the processing multidimensional process identification, and n represents the number of identifications in the processing multidimensional process identification.

6. The method for preparing bonding silver wire according to claim 1, characterized in that: The step of calculating the quality actuarial gradient corresponding to the quality reference factor based on the multi-dimensional processing feature includes: Performing feature selection processing on the processing multi-dimensional features to obtain target multi-dimensional features; Performing feature quantization processing on the target multidimensional features to obtain multidimensional feature values; Calculate the dimension weight value corresponding to each feature in the target multidimensional feature, combine the dimension weight value and the multidimensional feature value, and calculate the quality actuarial gradient corresponding to the quality benchmark factor by the following formula: Among them, G represents the quality actuarial gradient corresponding to the quality reference factor, Indicates the dimension weight value corresponding to the dth feature in the target multidimensional feature, H d Represents the multidimensional feature value corresponding to the dth feature in the target multidimensional feature, Indicates the feature reference value corresponding to the dth feature in the target multidimensional feature.

7. The method for preparing bonding silver wire according to claim 1, characterized in that: The step of combining the silver wire microstructure image and the component spectrum to calculate the quality reliability and validity of the bonding silver wire includes: Analyzing the morphological characteristics corresponding to the bonding silver wire based on the silver wire microstructure image; Smoothing the component spectrum to obtain a smoothed spectrum; Performing peak position identification on the smoothed spectrum to obtain spectrum peak positions, and extracting peak position characteristic information corresponding to the spectrum peak positions; Based on the peak position characteristic information, analyzing the chemical bonding characteristics corresponding to the bonding silver wire; The quality reliability and validity of the bonded silver wire are calculated by combining the morphological characteristics and the chemical bonding characteristics.

8. The method for preparing bonding silver wire according to claim 7, characterized in that: The step of analyzing the morphological characteristics of the bonding silver wire based on the silver wire microstructure image includes: grayscale the silver wire microstructure image to obtain a grayscale microstructure image; Performing edge detection processing on the grayscale microscopic tissue image to obtain a microscopic tissue edge image; Performing topological analysis on the microscopic tissue edge image to obtain tissue edge features; The characteristic fractal dimension corresponding to the tissue edge feature is calculated, and based on the characteristic fractal dimension, the morphological feature corresponding to the bonding silver wire is generated.

9. The method for preparing bonding silver wire according to claim 7, characterized in that: The combining of the morphological characteristics and the chemical bonding characteristics to calculate the quality reliability and validity corresponding to the bonded silver wire includes: Performing vectorization processing on the morphological features and the chemical bonding features respectively to obtain a morphological feature vector and a chemical feature vector; Normalizing the morphological feature vector and the chemical feature vector respectively to obtain a normalized morphological feature vector and a normalized chemical feature vector; Combining the normalized morphological feature vector and the normalized chemical feature vector, the quality reliability and validity corresponding to the bonding silver wire is calculated by the following formula: Among them, Q represents the quality reliability and validity of the bonding silver wire, M g represents the gth vector in the normalized morphological feature vector, N h represents the hth vector in the normalized chemical feature vector, g and h represent the vector serial numbers corresponding to the normalized morphological feature vector and the normalized chemical feature vector, respectively, and x and y represent the number of vectors corresponding to the normalized morphological feature vector and the normalized chemical feature vector, respectively.

10. A system for preparing bonding silver wires, characterized in that: The system comprises: A quality reference factor formulation module is used to obtain the preparation starting materials required for preparing the bonding silver wire, query the silver wire processing equipment cluster in the preparation process, determine the manufacturing process instruction set corresponding to the silver wire processing equipment cluster, and formulate the quality reference factor corresponding to the silver wire processing equipment cluster based on the manufacturing process instruction set; An equipment processing accuracy calculation module is used to collect multi-dimensional processing data of the silver wire processing equipment cluster during the preparation process, mine the processing multi-dimensional features corresponding to the silver wire processing equipment cluster based on the multi-dimensional processing data, calculate the quality actuarial gradient corresponding to the quality reference factor based on the processing multi-dimensional features, and evaluate the equipment processing accuracy corresponding to the silver wire processing equipment cluster based on the quality actuarial gradient; A quality reliability and validity calculation module, used for collecting the silver wire microstructure image and component spectrum diagram of the bonding silver wire in the silver wire processing equipment cluster, and combining the silver wire microstructure image and the component spectrum diagram to calculate the quality reliability and validity corresponding to the bonding silver wire; A storage modal coefficient calculation module, used to query the storage packaging ecology corresponding to the bonding silver wire, collect the ecological parameter vector set corresponding to the storage packaging ecology, and calculate the storage modal coefficient of the bonding silver wire under the storage packaging ecology based on the ecological parameter vector set; A preparation processing module is used to formulate a preparation plan corresponding to the bonding silver wire based on the equipment processing accuracy, the quality reliability and validity, and the storage modal coefficient, and based on the preparation plan, execute the preparation processing of the bonding silver wire in the silver wire processing equipment cluster to obtain a finished silver wire preparation product.

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