CN118742009B - Intelligent mounting and welding control method and system for integrated circuit motherboard - Google Patents
Intelligent mounting and welding control method and system for integrated circuit motherboard Download PDFInfo
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- 238000003466 welding Methods 0.000 title claims abstract description 333
- 238000000034 method Methods 0.000 title claims abstract description 62
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- 238000005457 optimization Methods 0.000 claims description 43
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Abstract
The invention provides an intelligent mounting and welding control method and system for an integrated circuit motherboard, which relate to the technical field of welding control and comprise the following steps: collecting images of a plurality of welding spots on a circuit motherboard after coating soldering paste, and obtaining motherboard images; identifying, acquiring a plurality of solder paste amount information, combining the solder joint patterns, and calculating to acquire a plurality of solder paste accuracy information; optimizing the mounting pressure to obtain the optimal mounting pressure, and performing mounting control; after the mounting is completed, collecting mounting images of mounting elements of the circuit main board, and identifying to obtain mounting distance information; and optimizing the heating temperature and the welding time for welding the heating soldering paste to obtain the optimal heating temperature and the optimal welding time, and performing welding control. The invention solves the technical problems that the traditional mounting welding control method lacks accurate control on mounting welding parameters, which results in poor accuracy, stability and precision, and further results in reduced welding quality and production efficiency.
Description
Technical Field
The invention relates to the technical field of welding control, in particular to an intelligent mounting welding control method and system for an integrated circuit main board.
Background
The mounting welding is to coat solder paste in advance on the welding spot, such as tin, then mount the component on the welding spot of the PCB board, and melt the solder paste with an electric soldering iron or a heating furnace to realize welding, the mounting welding of the integrated circuit main board is generally carried out through automation at present, and is fixedly carried out through a preset automatic program, so that the problems of welding leakage and poor contact of the welding spot are easy to occur when the error occurs in the integrated circuit main board.
Disclosure of Invention
The application provides an intelligent mounting and welding control method for an integrated circuit main board, aiming at solving the technical problems that the accuracy, the stability and the precision are poor due to the lack of accurate control on mounting and welding parameters in the traditional mounting and welding control method, and further the welding quality and the production efficiency are reduced.
In view of the above problems, the present application provides an intelligent mounting and soldering control method and system for an integrated circuit motherboard.
The first aspect of the present disclosure provides an intelligent mounting and soldering control method for an integrated circuit motherboard, the method comprising: collecting images of a plurality of welding spots on a circuit main board to be subjected to mounting welding after the welding spots are coated with soldering paste, and obtaining a main board image; identifying the main board image, obtaining a plurality of solder paste quantity information, and calculating to obtain a plurality of solder paste accuracy information by combining the solder joint patterns of the plurality of solder joints; optimizing the mounting pressure of a mounting element which is mounted and welded on the circuit board according to the plurality of solder paste accuracy information to obtain the optimal mounting pressure, and performing mounting control on the mounting element; after the mounting is completed, collecting a mounting image of the circuit main board for mounting the mounting element, and identifying to obtain mounting distance information; and optimizing the heating temperature and the welding time for welding the heating soldering paste according to the mounting distance information and the accuracy information of the soldering paste, obtaining the optimal heating temperature and the optimal welding time, and performing welding control.
The second aspect of the present disclosure provides an intelligent mounting and soldering control system for an integrated circuit motherboard, where the system is used in the above intelligent mounting and soldering control method for an integrated circuit motherboard, and the system includes: the image acquisition module is used for acquiring images of a circuit main board to be subjected to mounting welding after a plurality of welding spots on the circuit main board are coated with soldering paste, so as to obtain a main board image; the image recognition module is used for recognizing the main board image, acquiring a plurality of solder paste quantity information, and calculating and acquiring a plurality of solder paste accuracy information by combining the solder joint patterns of the plurality of solder joints; the pressure optimization module is used for optimizing the mounting pressure of the mounting element which is mounted and welded on the circuit main board according to the plurality of solder paste accuracy information, obtaining the optimal mounting pressure and carrying out mounting control on the mounting element; the mounting distance acquisition module is used for acquiring mounting images of the mounting elements mounted on the circuit main board after the mounting is completed, and identifying the mounting images to obtain mounting distance information; and the welding control module is used for optimizing the heating temperature and the welding time for heating the soldering paste to weld according to the mounting distance information and the accuracy information of the soldering paste, obtaining the optimal heating temperature and the optimal welding time and performing welding control.
In a third aspect of the present disclosure, there is provided a computer device comprising a memory storing a computer program and a processor implementing any of the steps of the first aspect of the present disclosure when the computer program is executed by the processor.
In a fourth aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon a computer program which when executed by a processor performs any of the steps of the first aspect of the present disclosure.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
the method comprises the steps of acquiring images of a plurality of welding spots on a circuit main board after the welding spots are coated with the welding paste, acquiring a plurality of welding paste amount information by combining an image identification technology, and calculating to obtain a plurality of welding paste accuracy information, so that the coating condition of the welding paste and the positions of the welding spots can be effectively identified, and the welding accuracy is improved; according to the accuracy information of the solder paste, the mounting pressure is optimized to obtain the optimal mounting pressure, so that the mounting control of the mounting element is realized, the good bonding between the solder paste and the welding spot can be ensured, and the stability and reliability of welding are improved; after the mounting is completed, mounting images of the mounted elements are collected and identified, mounting distance information is obtained, so that the distance between the mounted elements and the circuit main board can be accurately mastered, and the welding precision and stability can be improved; according to the mounting distance information and the accuracy information of a plurality of soldering paste, the heating temperature and the welding time for heating the soldering paste are optimized, and the optimal heating temperature and the optimal welding time are obtained, so that the soldering paste can be fully melted and completely attached to the soldering points, and the quality and the stability of welding are improved. In conclusion, the method can effectively solve the problems of accuracy, stability, precision and the like in the traditional mounting and welding process, thereby improving the welding quality and the production efficiency.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
Fig. 1 is a schematic flow chart of an intelligent mounting and welding control method for an integrated circuit motherboard according to an embodiment of the present application;
Fig. 2 is a schematic structural diagram of an intelligent mounting and welding control system for an integrated circuit motherboard according to an embodiment of the present application;
fig. 3 is an internal structure diagram of a computer device according to an embodiment of the present application.
Reference numerals illustrate: the device comprises an image acquisition module 10, an image identification module 20, a pressure optimization module 30, a mounting distance acquisition module 40 and a welding control module 50.
Detailed Description
The embodiment of the application solves the technical problems that the accuracy, the stability and the precision are poor and the welding quality and the production efficiency are reduced due to the fact that the traditional mounting welding control method lacks accurate control on mounting welding parameters by providing the intelligent mounting welding control method for the integrated circuit main board.
Having described the basic principles of the present application, various non-limiting embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
As shown in fig. 1, an embodiment of the present application provides an intelligent mounting and soldering control method for an integrated circuit motherboard, where the method includes:
collecting images of a plurality of welding spots on a circuit main board to be subjected to mounting welding after the welding spots are coated with soldering paste, and obtaining a main board image;
Preparing a circuit main board to be subjected to mounting welding, and equipment for acquiring images, such as a high-definition camera, coating soldering paste on a plurality of soldering spot positions of the circuit main board to be welded, ensuring that each soldering spot is covered by a proper amount of soldering paste, acquiring the images of the circuit main board by using the camera after coating, ensuring high image definition during acquisition, enabling details of the soldering paste to be clearly visible, and storing the acquired images into a main board image file for later image recognition and analysis.
Identifying the main board image, obtaining a plurality of solder paste quantity information, and calculating to obtain a plurality of solder paste accuracy information by combining the solder joint patterns of the plurality of solder joints;
Based on the convolutional neural network, a solder paste amount identifier is constructed, and a solder paste area in the main board image is identified by using the identifier, so that solder paste amount information on each welding spot is obtained. The pattern recognition is performed on the plurality of solder joints, the position and shape of each solder joint are recognized, the solder paste amount information and the solder joint pattern information are combined, the accuracy information of the solder paste on each solder joint is calculated, for example, the accuracy of the solder paste can be evaluated by comparing the difference between the actual position and the ideal position of the solder paste and the difference between the actual shape and the expected shape of the solder paste, and the accuracy of the solder paste can be represented in a numerical manner, for example, in the form of a percentage or the like.
Further, identifying the motherboard image to obtain a plurality of solder paste amount information includes:
Preprocessing the main board image;
based on the mounting welding history data, acquiring a sample main board image set, identifying and marking the solder paste amounts of a plurality of welding spots in a sample main body image, and acquiring a plurality of sample solder paste amount information sets;
and constructing a solder paste amount identifier based on a convolutional neural network by adopting the sample motherboard image set and a plurality of sample solder paste amount information sets, and identifying the preprocessed motherboard image to obtain a plurality of solder paste amount information.
Preprocessing the main board image to improve accuracy and efficiency in subsequent image processing and analysis, wherein the preprocessing operation comprises denoising processing, such as removing noise in the image by applying a digital filter, so as to reduce interference of subsequent processing steps; adjusting the brightness and contrast of the image to enhance the visibility of key features such as welding spots, soldering paste and the like in the image; the image is smoothed using a smoothing technique, such as gaussian blur or mean filtering, to reduce details and noise in the image, making the solder joint and solder paste easier to identify. Thus, noise and interference in the image can be reduced, key features such as welding spots, soldering paste and the like are highlighted, and a foundation is provided for subsequent image recognition and analysis.
A series of sample master board images are collected from the mounting and soldering history data, and cover various soldering conditions to ensure the diversity of samples. The recognition of the solder paste amount information is performed on the solder joint area within each sample motherboard image, and the positions of the solder joints can be recognized using image processing and computer vision techniques such as threshold segmentation, edge detection, etc., and the solder paste amount, which can be expressed as a volume of solder paste, is marked. And arranging the solder paste amount information of a plurality of welding spots in each sample main board image into a sample solder paste amount information set, wherein each sample solder paste amount information corresponds to one sample main board image and is used for subsequent model training.
Integrating the sample main board image set and the corresponding sample soldering paste amount information set into construction data, dividing the construction data into a training set and a verification set, designing a Convolutional Neural Network (CNN) model suitable for an image recognition task, wherein the CNN comprises a convolutional layer, a pooling layer, a full-connection layer and other components, an input layer is matched with the sample main board image, and an output layer is matched with the sample soldering paste amount information.
And training the designed CNN model by using a training set, optimizing according to the sample main board image and corresponding solder paste amount information in the training process so as to minimize the error between the predicted value and the actual value, evaluating the performance of the trained model by using a verification set, evaluating the generalization capability and recognition performance of the model by calculating indexes such as the loss value, the accuracy and the like of the model on the verification set, and finally obtaining the model meeting the preset accuracy, namely the solder paste amount recognizer.
And the solder paste quantity identifier is used for identifying the preprocessed main board image, the identifier outputs a plurality of pieces of solder paste quantity information according to the learned mode, and the identified solder paste quantity information is associated with the solder joint positions on the main board image to obtain the solder paste quantity information of each solder joint.
Further, in combination with the solder joint patterns of the plurality of solder joints, a plurality of solder paste accuracy information is obtained through calculation, including:
according to the welding spot patterns of the welding spots on the welding spots, indexing to obtain a plurality of standard welding paste amount information;
and calculating and obtaining the solder paste accuracy information according to the standard solder paste amount information and the solder paste amount information.
Establishing a standard solder paste amount information index, specifically, acquiring a large number of different solder joints and corresponding standard solder paste amount information thereof from a known welding standard or welding quality authentication standard, correlating the standard solder paste amount information with corresponding solder joint patterns, establishing a database, and recording the standard solder paste amount information of each solder joint.
In the mounting process, the shape of a welding spot on a welding disc is obtained through an image processing technology, the shape of an actual welding spot is matched with an established database, standard solder paste quantity information corresponding to the actual welding spot is found, and a plurality of standard solder paste quantity information matched with a plurality of welding spots is obtained through indexes.
Optimizing the mounting pressure of a mounting element which is mounted and welded on the circuit board according to the plurality of solder paste accuracy information to obtain the optimal mounting pressure, and performing mounting control on the mounting element;
According to the calculated accuracy information of the solder paste, analyzing the condition of the solder paste on each solder joint, wherein the solder joint with small solder paste needs to increase the mounting pressure to ensure the bonding degree of the solder joint, otherwise, the solder joint with large solder paste needs to decrease the mounting pressure to avoid overflow of the solder paste. And (3) based on the analysis result of the solder paste quantity information, formulating a mounting pressure optimization strategy to obtain the optimal mounting pressure, and performing mounting control on the mounting element on the circuit main board according to the optimized mounting pressure, for example, by adjusting parameters of mounting equipment so as to realize the required mounting pressure and realize the accurate control on the mounting element, thereby ensuring the welding quality and stability.
Further, optimizing the mounting pressure of the mounting component mounted and soldered on the circuit board according to the solder paste accuracy information includes:
according to the solder paste accuracy information, constructing a mounting pressure function for optimizing the mounting pressure of the mounting element on the circuit main board, wherein the mounting pressure function comprises the following formula:
；
wherein pre is the pressure fitness, M is the number of a plurality of welding spots, For the weight of the i-th pad allocated according to the size of the plurality of solder paste accuracy information, the size of the solder paste accuracy information and the weight are positively correlated,The method is the amplitude of non-conforming of the soldering paste and the soldering spot graph after the ith soldering spot is attached under the attaching pressure;
randomly generating a first mounting pressure, combining the solder paste accuracy information, predicting and obtaining amplitude information of non-coincidence of the solder paste and the solder paste image after mounting a plurality of solder joints, and calculating and obtaining a first pressure fitness according to the mounting pressure function, wherein a solder paste mounting deviation identifier is constructed by adopting a sample mounting pressure set, a plurality of sample solder paste accuracy information sets and a plurality of sample deviation amplitude information sets, and predicting the amplitude of non-coincidence of the solder paste and the solder paste image after mounting is performed;
And continuing to randomly generate and optimize the mounting pressure until convergence, and obtaining the mounting pressure with the maximum pressure fitness as the optimal mounting pressure.
Specifically, the mounting pressure function is as follows:
；
the purpose of this function is to adjust the mounting pressure according to the accuracy information of the solder paste to minimize the magnitude of the solder paste not conforming to the solder joint pattern, wherein pre represents the degree of pressure adaptation, and the larger the degree of adaptation is, the more suitable the mounting pressure is; m represents the number of a plurality of welding spots; representing a weight of an i-th solder joint allocated according to the size of the plurality of solder paste accuracy information, the weight being positively correlated with the size of the solder paste accuracy information, i.e., the higher the accuracy, the greater the weight; The smaller the value is, the higher the matching degree of the soldering paste and the soldering spot pattern is, and the higher the adaptation degree is.
The goal of the mounting pressure function is to adjust the weightAmplitude of non-conforming solder paste to solder joint patternAs small as possible, so as to maximize the pressure fitness pre, such an optimization process may be implemented by various optimization algorithms, such as a genetic algorithm, a simulated annealing algorithm, a particle swarm optimization algorithm, etc., to implement an optimized mounting pressure, thereby improving the welding quality and stability.
And randomly generating first mounting pressure from a preset pressure range, using the constructed solder paste mounting deviation identifier as an initial value, predicting a plurality of pieces of solder paste accuracy information and the randomly generated first mounting pressure, and outputting amplitude information of solder paste which is not consistent with a solder paste image after a plurality of solder joints are mounted. The solder paste mounting deviation identifier can be obtained by training a model through sample data, the input of the model comprises solder paste accuracy information and mounting pressure, and the output is amplitude information of non-coincidence of solder paste and a solder joint image.
And substituting the predicted amplitude information, which is inconsistent with the solder paste and the solder paste image after the plurality of solder joints are attached, into the corresponding solder paste accuracy information according to the attaching pressure function, and calculating to obtain the first pressure fitness.
And randomly generating the next mounting pressure in a preset pressure range as a second mounting pressure, and calculating a second pressure fitness. And adjusting the mounting pressure according to the current pressure fitness and the selected optimization target, namely the maximum fitness, by using an optimization algorithm, such as a genetic algorithm, a simulated annealing algorithm, a particle swarm optimization algorithm and the like, and updating the value of the mounting pressure according to the larger value of the current second pressure fitness and the first pressure fitness by the optimization algorithm so as to expect to achieve better fitness.
Judging whether the optimization process is converged, namely whether the condition of stopping optimization is reached, for example, the change of the adaptability of a plurality of continuous iterations is smaller than a certain threshold value, or the preset maximum iteration number is reached, when the optimization process is converged, obtaining the optimal mounting pressure, wherein the corresponding adaptability is the maximum pressure adaptability, and the optimal mounting pressure can be used as the mounting pressure parameter in the subsequent mounting process, so that the mounting pressure can be ensured to be maximally adapted to the characteristics of the soldering paste and the soldering spot image, and the welding quality and stability are improved.
After the mounting is completed, collecting a mounting image of the circuit main board for mounting the mounting element, and identifying to obtain mounting distance information;
After the mounting is completed, the mounting elements on the circuit board are subjected to image acquisition by using a camera in the direction parallel to the circuit board to obtain a mounting image, and the mounting elements in the mounting image are identified and positioned by using a mounting distance identifier to obtain a mounting distance, namely the distance between the mounting elements and the surface of the circuit board.
Further, collecting the mounting image of the mounting element mounted on the circuit board, and identifying to obtain mounting distance information, including:
Collecting mounting images of the mounting elements of the circuit board in a direction parallel to the circuit board;
Preprocessing the mounting image;
Collecting a sample mounting image set according to mounting welding history data, and identifying and marking the distance between a circuit main board and a mounting element in the sample mounting image to obtain a sample mounting distance information set;
And constructing a mounting distance identifier based on a convolutional neural network by adopting the sample mounting image set and the sample mounting distance information set, and identifying the preprocessed mounting image to obtain the mounting distance information.
The camera device is placed in a direction parallel to the circuit motherboard and close to the motherboard surface sufficiently, and the angle and direction of the camera are adjusted to be perpendicular to the circuit motherboard surface so as to capture the distance information between the circuit motherboard and the mounting element to the greatest extent. And (3) using the laid image pickup equipment to collect images of the circuit board on which the mounting element is mounted, and obtaining mounting images.
Preprocessing the acquired mounting image, wherein the preprocessing aims at improving the image quality, reducing noise and enhancing characteristics so as to facilitate the subsequent operations of image recognition, distance measurement and the like, including graying processing, and converting a color image into a gray image so as to simplify the complexity of image processing; the image is de-noised using filters, such as gaussian filters, median filters, etc., to reduce the effects of noise in the image.
And collecting historical data generated in the process of mounting and welding, wherein the historical data comprises mounting images, and selecting a part of the collected historical data as a sample to establish a sample mounting image set which covers different types of mounting elements and mounting positions.
The sample mounting image is processed, and the distance between the circuit board and the mounting element is identified using image processing and computer vision techniques, for example, edge detection, feature extraction, etc. techniques may be used to determine the position of the mounting element and the contour of the surface of the board, and thus calculate the distance therebetween. And recording distance information between the circuit main board and the mounting element for each sample mounting image, and forming a sample mounting distance information set by the sample mounting image and the corresponding distance information.
And taking the sample mounting image set as training data, taking the sample mounting distance information set as a corresponding label, designing a convolutional neural network architecture, comprising a convolutional layer, a pooling layer, a full-connection layer and the like, determining the input and the output of the network, wherein the input is a mounting image, and the output is mounting distance information.
Training the convolutional neural network by using the sample mounting image set and the sample mounting distance information set, optimizing network parameters by minimizing a loss function in the training process, enabling the network to accurately predict the mounting distance, verifying the trained model by using a verification set, evaluating the performance of the model, and adjusting the super parameters of the model, such as learning rate, network structure and the like, according to the verification result so as to improve the generalization capability and accuracy of the model. And carrying out distance recognition on the preprocessed mounting image by using a trained mounting distance recognizer, and outputting mounting distance information.
And optimizing the heating temperature and the welding time for welding the heating soldering paste according to the mounting distance information and the accuracy information of the soldering paste, obtaining the optimal heating temperature and the optimal welding time, and performing welding control.
According to the mounting distance information and the solder paste accuracy information, an optimization strategy of heating temperature and welding time is formulated, wherein the heating temperature and the welding time are required to be increased for a welding spot with a larger mounting distance so as to ensure that the solder paste can be fully melted and fill a gap between the welding spot and an element; for inaccurate solder joint coating of the solder paste, the heating temperature and the welding time need to be adjusted to compensate the influence caused by insufficient or excessive coating of the solder paste; and at the same time, the components cannot be heated too much to cause damage. Based on the optimization strategy, the optimal heating temperature and the optimal welding time are determined through an optimization algorithm.
And performing welding control according to the calculated optimal heating temperature and optimal welding time, wherein the welding control comprises the steps of adjusting parameters of welding equipment, ensuring that solder paste melts and flows at the optimal heating temperature, completing a welding process, improving welding quality and stability, and ensuring reliable connection of a mounted element and a circuit main board.
Further, optimizing the heating temperature and the soldering time for soldering the heated solder paste according to the mounting distance information and the plurality of solder paste accuracy information, includes:
Correcting and calculating a preset optimizing step length for optimizing the heating temperature and the welding time according to the accuracy information of the solder paste to obtain an optimizing step length;
constructing a welding optimization function for optimizing the heating temperature and the welding time for welding the heating soldering paste, wherein the welding optimization function comprises the following formula:
；
Wherein wel is welding fitness, AndIn order to melt the weights and the component weights,AndThe sum of (2) is 1,The melting rate of the solder paste amount of the ith solder joint under the welding parameters is given, K is the mounting accuracy coefficient,In order to raise the temperature of the mounted element at the ith welding spot after welding according to the welding parameters,In order to attach the distance information to the board,The standard mounting distance is the standard mounting distance between the mounting element and the circuit main board;
randomly generating a first heating temperature and a first welding time as first welding parameters;
Adopting the first welding parameters, combining the solder paste quantity information and the mounting distance information, analyzing and obtaining the melting rate of the solder paste in the welded welding spots and the rising temperature of the mounting element, and calculating and obtaining a first welding fitness based on the welding optimization function;
And continuously optimizing the heating temperature and the welding time of the welding until convergence, outputting the welding parameter with the maximum welding fitness, and obtaining the optimal heating temperature and the optimal welding time.
An initial optimization step value is set, for example, an initial value is empirically set as a preset optimization step. For each welding spot, adjusting the optimization step length according to the corresponding welding paste accuracy information, wherein if the welding paste accuracy of a certain welding spot is higher, the welding spot is more sensitive to the adjustment of the heating temperature and the welding time, and the optimization step length of the welding spot can be properly increased; if the accuracy of the soldering paste of a certain soldering point is lower, the influence of the soldering paste on the adjustment of the heating temperature and the soldering time is smaller, and the optimization step length of the soldering point can be properly reduced. And correcting and calculating the optimization step length of each welding spot according to the welding paste accuracy information of each welding spot, so as to better guide the optimization process of the heating temperature and the welding time.
The welding optimization function is as follows:
；
Wherein wel is welding fitness, and represents an evaluation index of welding quality, and the larger the index is, the better the welding quality is; And Respectively melting weight and element weight, wherein the sum of the melting weight and the element weight is 1, and the two weights are used for adjusting the influence of different factors on the welding fitness; the melting rate of the solder paste amount for the i-th solder joint under the welding parameters represents the degree to which the solder paste is melted under the given welding parameters; k is a mounting accuracy coefficient, which is a value calculated according to welding parameters and reflects the rising temperature of a mounting element at an ith welding spot after welding, and K is calculated according to mounting distance information And the standard mounting distance between the mounting element and the circuit main boardIs segmented. The goal of the weld optimization function is to maximize the weld fitness wel by adjusting the heating temperature and weld time.
A reasonable range of heating temperatures and welding times is first determined, which can be determined based on practical circumstances and previous experience, ensuring that the parameters are within acceptable ranges. After the parameter range is determined, a random number generator is used to uniformly and randomly select a number value from the parameter range as an initial parameter, and the randomly generated heating temperature and welding time are used as initial parameters of the first welding.
And using the randomly generated first welding parameters to simulate the welding process in a simulation environment, recording the melting rate of the soldering paste and the rising temperature of the mounted element in the simulation process, substituting the melting rate and the rising temperature into a welding optimization function, and calculating to obtain first welding fitness serving as an evaluation index of the first welding so as to evaluate the quality of the first welding.
An iteration termination condition is set to determine when to stop the optimization process, which may be that a certain number of iterations is reached, or that the adaptation degree changes less than a threshold, or that the adaptation degree reaches a preset target value. And updating welding parameters, namely heating temperature and welding time according to welding fitness and an optimization algorithm, such as a gradient descent method, a genetic algorithm and the like, wherein the updated parameters are used for the next iteration, judging whether convergence conditions are met in each iteration, and if so, stopping the optimization process, and outputting the optimal welding parameters and the corresponding fitness. This ensures that the welding process is of optimal quality and improves the efficiency and stability of the weld.
Further, the analyzing to obtain the melting rate of the solder paste in the plurality of solder joints and the rising temperature of the mounted component after the soldering by adopting the first soldering parameter and combining the plurality of solder paste amount information and the mounting distance information includes:
according to the mounting welding history data, a sample welding parameter set, a sample soldering paste quantity information set and a sample mounting distance information set are obtained, and a sample melting rate information set and a sample rising temperature set are obtained;
the sample welding parameter set, the sample soldering paste amount information set and the sample mounting distance information set are used as sample input, the sample melting rate information set and the sample rising temperature set are used as sample output, and a welding simulation channel is obtained through training;
and based on the welding simulation channel, performing welding simulation analysis on the first welding parameters in combination with the solder paste quantity information and the mounting distance information to obtain a plurality of melting rates of the solder paste in the welding spots and a plurality of heating-up temperatures of the mounting element.
And collecting historical data of mounting welding, wherein the historical data comprises a sample welding parameter set, a sample soldering paste amount information set, a sample mounting distance information set, a corresponding sample melting rate information set and a sample rising temperature set under different welding parameters, and the historical data are used as input and labels of a training model and are used for constructing a welding simulation channel.
The sample welding parameter set comprises parameter combinations of different heating temperatures and welding times adopted in the history welding process; the sample solder paste amount information set records the solder paste coating amount condition under each sample welding parameter; the sample mounting distance information set comprises the distance condition between the mounting element and the circuit board under each sample welding parameter.
The sample melting rate information set records the melting rate of the soldering paste under each sample welding parameter, and can be obtained by statistics according to the actual welding condition or the welding result obtained by simulation; the sample rising temperature set records the rising temperature condition of the mounting component under each sample welding parameter, and the data can be obtained through actual measurement or simulation.
And taking the sample welding parameters, the soldering paste amount and the mounting distance as input characteristics, taking the sample melting rate and the rising temperature as output labels, constructing a training set, and selecting a proper machine learning model or a deep learning model, such as a neural network, for modeling the relationship between the melting rate and the rising temperature in the welding process.
The model parameters are optimized through a counter-propagation algorithm by training the model through the training set, so that the model can predict the melting rate of soldering paste and the rising temperature of the mounting element as accurately as possible, the performance of the model is estimated by using the verification set, whether the model can accurately predict the melting rate and the rising temperature in the welding process is checked, and the model is optimized according to the estimation result, such as adjusting the model structure, the super parameters and the like, so that the performance of the model is improved.
Through the training process, an accurate welding simulation channel can be obtained, and the melting rate of the soldering paste and the rising temperature of the mounted element can be accurately predicted according to given welding parameters, soldering paste quantity and mounting distance.
And inputting the first welding parameters, the solder paste quantity information and the mounting distance information into a trained welding simulation channel, performing simulation analysis on each welding spot by using the welding simulation channel, and predicting the melting rate of the solder paste in each welding spot and the rising temperature of the mounting element to obtain the prediction result of the melting rate of the solder paste in each welding spot and the rising temperature of the mounting element as the simulation analysis result under the current welding parameters.
In summary, the intelligent mounting and welding control method for the integrated circuit motherboard provided by the embodiment of the application has the following technical effects:
1. The method comprises the steps of acquiring images of a plurality of welding spots on a circuit main board after the welding spots are coated with the welding paste, acquiring a plurality of welding paste amount information by combining an image identification technology, and calculating to obtain a plurality of welding paste accuracy information, so that the coating condition of the welding paste and the positions of the welding spots can be effectively identified, and the welding accuracy is improved;
2. According to the accuracy information of the solder paste, the mounting pressure is optimized to obtain the optimal mounting pressure, so that the mounting control of the mounting element is realized, the good bonding between the solder paste and the welding spot can be ensured, and the stability and reliability of welding are improved;
3. after the mounting is completed, mounting images of the mounted elements are collected and identified, mounting distance information is obtained, so that the distance between the mounted elements and the circuit main board can be accurately mastered, and the welding precision and stability can be improved;
4. According to the mounting distance information and the accuracy information of a plurality of soldering paste, the heating temperature and the welding time for heating the soldering paste are optimized, and the optimal heating temperature and the optimal welding time are obtained, so that the soldering paste can be fully melted and completely attached to the soldering points, and the quality and the stability of welding are improved.
In conclusion, the method can effectively solve the problems of accuracy, stability, precision and the like in the traditional mounting and welding process, thereby improving the welding quality and the production efficiency.
Based on the same inventive concept as the intelligent mounting and welding control method of an integrated circuit motherboard in the foregoing embodiment, as shown in fig. 2, the present application provides an intelligent mounting and welding control system of an integrated circuit motherboard, the system includes:
The image acquisition module 10 is used for acquiring images of a circuit motherboard to be subjected to mounting welding after a plurality of welding spots on the circuit motherboard are coated with soldering paste, so as to obtain a motherboard image;
The image recognition module 20 is used for recognizing the main board image, acquiring a plurality of solder paste amount information, and calculating and acquiring a plurality of solder paste accuracy information by combining the solder joint patterns of the plurality of solder joints;
The pressure optimization module 30 is configured to optimize a mounting pressure of a mounting element mounted and welded on the circuit board according to the plurality of solder paste accuracy information, obtain an optimal mounting pressure, and perform mounting control on the mounting element;
the mounting distance acquisition module 40 is used for acquiring a mounting image of the circuit board for mounting the mounting element after the mounting is completed, and identifying the mounting image to obtain mounting distance information;
And the welding control module 50 is used for optimizing the heating temperature and the welding time for heating the soldering paste to weld according to the mounting distance information and the plurality of soldering paste accuracy information, obtaining the optimal heating temperature and the optimal welding time and performing welding control.
Further, the system further includes a solder paste amount information acquisition module to perform the following operation steps:
Preprocessing the main board image;
based on the mounting welding history data, acquiring a sample main board image set, identifying and marking the solder paste amounts of a plurality of welding spots in a sample main body image, and acquiring a plurality of sample solder paste amount information sets;
and constructing a solder paste amount identifier based on a convolutional neural network by adopting the sample motherboard image set and a plurality of sample solder paste amount information sets, and identifying the preprocessed motherboard image to obtain a plurality of solder paste amount information.
Further, the system further comprises a solder paste accuracy information acquisition module to perform the following operation steps:
according to the welding spot patterns of the welding spots on the welding spots, indexing to obtain a plurality of standard welding paste amount information;
and calculating and obtaining the solder paste accuracy information according to the standard solder paste amount information and the solder paste amount information.
Further, the system further comprises an optimal mounting pressure acquisition module for executing the following operation steps:
according to the solder paste accuracy information, constructing a mounting pressure function for optimizing the mounting pressure of the mounting element on the circuit main board, wherein the mounting pressure function comprises the following formula:
；
wherein pre is the pressure fitness, M is the number of a plurality of welding spots, For the weight of the i-th pad allocated according to the size of the plurality of solder paste accuracy information, the size of the solder paste accuracy information and the weight are positively correlated,The method is the amplitude of non-conforming of the soldering paste and the soldering spot graph after the ith soldering spot is attached under the attaching pressure;
randomly generating a first mounting pressure, combining the solder paste accuracy information, predicting and obtaining amplitude information of non-coincidence of the solder paste and the solder paste image after mounting a plurality of solder joints, and calculating and obtaining a first pressure fitness according to the mounting pressure function, wherein a solder paste mounting deviation identifier is constructed by adopting a sample mounting pressure set, a plurality of sample solder paste accuracy information sets and a plurality of sample deviation amplitude information sets, and predicting the amplitude of non-coincidence of the solder paste and the solder paste image after mounting is performed;
And continuing to randomly generate and optimize the mounting pressure until convergence, and obtaining the mounting pressure with the maximum pressure fitness as the optimal mounting pressure.
Further, the system further comprises a mounting distance information acquisition module for executing the following operation steps:
Collecting mounting images of the mounting elements of the circuit board in a direction parallel to the circuit board;
Preprocessing the mounting image;
Collecting a sample mounting image set according to mounting welding history data, and identifying and marking the distance between a circuit main board and a mounting element in the sample mounting image to obtain a sample mounting distance information set;
And constructing a mounting distance identifier based on a convolutional neural network by adopting the sample mounting image set and the sample mounting distance information set, and identifying the preprocessed mounting image to obtain the mounting distance information.
Further, the system also comprises an optimal welding parameter acquisition module for executing the following operation steps:
Correcting and calculating a preset optimizing step length for optimizing the heating temperature and the welding time according to the accuracy information of the solder paste to obtain an optimizing step length;
constructing a welding optimization function for optimizing the heating temperature and the welding time for welding the heating soldering paste, wherein the welding optimization function comprises the following formula:
；
Wherein wel is welding fitness, AndIn order to melt the weights and the component weights,AndThe sum of (2) is 1,The melting rate of the solder paste amount of the ith solder joint under the welding parameters is given, K is the mounting accuracy coefficient,In order to raise the temperature of the mounted element at the ith welding spot after welding according to the welding parameters,In order to attach the distance information to the board,The standard mounting distance is the standard mounting distance between the mounting element and the circuit main board;
randomly generating a first heating temperature and a first welding time as first welding parameters;
Adopting the first welding parameters, combining the solder paste quantity information and the mounting distance information, analyzing and obtaining the melting rate of the solder paste in the welded welding spots and the rising temperature of the mounting element, and calculating and obtaining a first welding fitness based on the welding optimization function;
And continuously optimizing the heating temperature and the welding time of the welding until convergence, outputting the welding parameter with the maximum welding fitness, and obtaining the optimal heating temperature and the optimal welding time.
Further, the system also comprises a welding simulation analysis module for executing the following operation steps:
according to the mounting welding history data, a sample welding parameter set, a sample soldering paste quantity information set and a sample mounting distance information set are obtained, and a sample melting rate information set and a sample rising temperature set are obtained;
the sample welding parameter set, the sample soldering paste amount information set and the sample mounting distance information set are used as sample input, the sample melting rate information set and the sample rising temperature set are used as sample output, and a welding simulation channel is obtained through training;
and based on the welding simulation channel, performing welding simulation analysis on the first welding parameters in combination with the solder paste quantity information and the mounting distance information to obtain a plurality of melting rates of the solder paste in the welding spots and a plurality of heating-up temperatures of the mounting element.
In the foregoing description of the method for controlling the intelligent mounting and soldering of an integrated circuit motherboard, it will be clear to those skilled in the art that the system for controlling the intelligent mounting and soldering of an integrated circuit motherboard in this embodiment is relatively simple in description, and the relevant points refer to the description of the method section.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 3. The computer device includes a processor, a memory, and a network interface connected by a system bus, wherein the processor of the computer device is configured to provide computing and control capabilities; the memory of the computer device includes a non-volatile storage medium storing an operating system, a computer program and a database, and an internal memory providing an environment for the operating system and the computer program in the non-volatile storage medium to run; the network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by the processor to implement an intelligent mounting and soldering control method for an integrated circuit motherboard.
It will be appreciated by those skilled in the art that the structure shown in FIG. 3 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. An intelligent mounting and welding control method for an integrated circuit motherboard is characterized by comprising the following steps:
collecting images of a plurality of welding spots on a circuit main board to be subjected to mounting welding after the welding spots are coated with soldering paste, and obtaining a main board image;
identifying the main board image, obtaining a plurality of solder paste quantity information, and calculating to obtain a plurality of solder paste accuracy information by combining the solder joint patterns of the plurality of solder joints;
Optimizing the mounting pressure of a mounting element which is mounted and welded on the circuit board according to the plurality of solder paste accuracy information to obtain the optimal mounting pressure, and performing mounting control on the mounting element;
After the mounting is completed, collecting a mounting image of the circuit main board for mounting the mounting element, and identifying to obtain mounting distance information;
optimizing the heating temperature and the welding time for welding the heating soldering paste according to the mounting distance information and the accuracy information of the plurality of soldering pastes, obtaining the optimal heating temperature and the optimal welding time, and performing welding control;
Wherein optimizing the mounting pressure of the mounting element mounted and soldered on the circuit board according to the plurality of solder paste accuracy information, comprises:
according to the solder paste accuracy information, constructing a mounting pressure function for optimizing the mounting pressure of the mounting element on the circuit main board, wherein the mounting pressure function comprises the following formula:
wherein pre is the pressure fitness, M is the number of a plurality of welding spots, For the weight of the i-th pad allocated according to the size of the plurality of solder paste accuracy information, the size of the solder paste accuracy information and the weight are positively correlated,The method is the amplitude of non-conforming of the soldering paste and the soldering spot graph after the ith soldering spot is attached under the attaching pressure;
randomly generating a first mounting pressure, combining the solder paste accuracy information, predicting and obtaining amplitude information of non-coincidence of the solder paste and the solder paste image after mounting a plurality of solder joints, and calculating and obtaining a first pressure fitness according to the mounting pressure function, wherein a solder paste mounting deviation identifier is constructed by adopting a sample mounting pressure set, a plurality of sample solder paste accuracy information sets and a plurality of sample deviation amplitude information sets, and predicting the amplitude of non-coincidence of the solder paste and the solder paste image after mounting is performed;
Continuously randomly generating and optimizing the mounting pressure until convergence, and obtaining the mounting pressure with the maximum pressure fitness as the optimal mounting pressure;
Wherein, according to the mounting distance information and the solder paste accuracy information, the heating temperature and the soldering time for soldering the heated solder paste are optimized, comprising:
Correcting and calculating a preset optimizing step length for optimizing the heating temperature and the welding time according to the accuracy information of the solder paste to obtain an optimizing step length;
constructing a welding optimization function for optimizing the heating temperature and the welding time for welding the heating soldering paste, wherein the welding optimization function comprises the following formula:
Wherein wel is welding fitness, AndIn order to melt the weights and the component weights,AndThe sum of (2) is 1,The melting rate of the solder paste amount of the ith solder joint under the welding parameters is given, K is the mounting accuracy coefficient,In order to raise the temperature of the mounted element at the ith welding spot after welding according to the welding parameters,In order to attach the distance information to the board,The standard mounting distance is the standard mounting distance between the mounting element and the circuit main board;
randomly generating a first heating temperature and a first welding time as first welding parameters;
Adopting the first welding parameters, combining the solder paste quantity information and the mounting distance information, analyzing and obtaining the melting rate of the solder paste in the welded welding spots and the rising temperature of the mounting element, and calculating and obtaining a first welding fitness based on the welding optimization function;
And continuously optimizing the heating temperature and the welding time of the welding until convergence, outputting the welding parameter with the maximum welding fitness, and obtaining the optimal heating temperature and the optimal welding time.
2. The method of claim 1, wherein identifying the motherboard image to obtain a plurality of solder paste amount information comprises:
Preprocessing the main board image;
based on the mounting welding history data, acquiring a sample main board image set, identifying and marking the solder paste amounts of a plurality of welding spots in a sample main body image, and acquiring a plurality of sample solder paste amount information sets;
and constructing a solder paste amount identifier based on a convolutional neural network by adopting the sample motherboard image set and a plurality of sample solder paste amount information sets, and identifying the preprocessed motherboard image to obtain a plurality of solder paste amount information.
3. The method of claim 1, wherein calculating a plurality of solder paste accuracy information in combination with the solder joint pattern of the plurality of solder joints comprises:
according to the welding spot patterns of the welding spots on the welding spots, indexing to obtain a plurality of standard welding paste amount information;
and calculating and obtaining the solder paste accuracy information according to the standard solder paste amount information and the solder paste amount information.
4. The method according to claim 1, wherein collecting a mounting image of the circuit board mounting the mounting component, and identifying, to obtain mounting distance information, comprises:
Collecting mounting images of the mounting elements of the circuit board in a direction parallel to the circuit board;
Preprocessing the mounting image;
Collecting a sample mounting image set according to mounting welding history data, and identifying and marking the distance between a circuit main board and a mounting element in the sample mounting image to obtain a sample mounting distance information set;
And constructing a mounting distance identifier based on a convolutional neural network by adopting the sample mounting image set and the sample mounting distance information set, and identifying the preprocessed mounting image to obtain the mounting distance information.
5. The method of claim 1, wherein analyzing to obtain the melting rate of solder paste in the plurality of solder joints and the temperature rise of the mounted component after soldering using the first soldering parameter in combination with the plurality of solder paste amount information and the mounting distance information, comprises:
according to the mounting welding history data, a sample welding parameter set, a sample soldering paste quantity information set and a sample mounting distance information set are obtained, and a sample melting rate information set and a sample rising temperature set are obtained;
the sample welding parameter set, the sample soldering paste amount information set and the sample mounting distance information set are used as sample input, the sample melting rate information set and the sample rising temperature set are used as sample output, and a welding simulation channel is obtained through training;
and based on the welding simulation channel, performing welding simulation analysis on the first welding parameters in combination with the solder paste quantity information and the mounting distance information to obtain a plurality of melting rates of the solder paste in the welding spots and a plurality of heating-up temperatures of the mounting element.
6. An intelligent mounting and soldering control system for an integrated circuit motherboard, for implementing the intelligent mounting and soldering control method for an integrated circuit motherboard according to any one of claims 1-5, said system comprising:
the image acquisition module is used for acquiring images of a circuit main board to be subjected to mounting welding after a plurality of welding spots on the circuit main board are coated with soldering paste, so as to obtain a main board image;
the image recognition module is used for recognizing the main board image, acquiring a plurality of solder paste quantity information, and calculating and acquiring a plurality of solder paste accuracy information by combining the solder joint patterns of the plurality of solder joints;
the pressure optimization module is used for optimizing the mounting pressure of the mounting element which is mounted and welded on the circuit main board according to the plurality of solder paste accuracy information, obtaining the optimal mounting pressure and carrying out mounting control on the mounting element;
The mounting distance acquisition module is used for acquiring mounting images of the mounting elements mounted on the circuit main board after the mounting is completed, and identifying the mounting images to obtain mounting distance information;
The welding control module is used for optimizing the heating temperature and the welding time for welding the heating soldering paste according to the mounting distance information and the plurality of soldering paste accuracy information, obtaining the optimal heating temperature and the optimal welding time and performing welding control;
the system further comprises an optimal mounting pressure acquisition module for executing the following operation steps:
according to the solder paste accuracy information, constructing a mounting pressure function for optimizing the mounting pressure of the mounting element on the circuit main board, wherein the mounting pressure function comprises the following formula:
wherein pre is the pressure fitness, M is the number of a plurality of welding spots, For the weight of the i-th pad allocated according to the size of the plurality of solder paste accuracy information, the size of the solder paste accuracy information and the weight are positively correlated,The method is the amplitude of non-conforming of the soldering paste and the soldering spot graph after the ith soldering spot is attached under the attaching pressure;
randomly generating a first mounting pressure, combining the solder paste accuracy information, predicting and obtaining amplitude information of non-coincidence of the solder paste and the solder paste image after mounting a plurality of solder joints, and calculating and obtaining a first pressure fitness according to the mounting pressure function, wherein a solder paste mounting deviation identifier is constructed by adopting a sample mounting pressure set, a plurality of sample solder paste accuracy information sets and a plurality of sample deviation amplitude information sets, and predicting the amplitude of non-coincidence of the solder paste and the solder paste image after mounting is performed;
Continuously randomly generating and optimizing the mounting pressure until convergence, and obtaining the mounting pressure with the maximum pressure fitness as the optimal mounting pressure;
the system further comprises an optimal welding parameter acquisition module for executing the following operation steps:
Correcting and calculating a preset optimizing step length for optimizing the heating temperature and the welding time according to the accuracy information of the solder paste to obtain an optimizing step length;
constructing a welding optimization function for optimizing the heating temperature and the welding time for welding the heating soldering paste, wherein the welding optimization function comprises the following formula:
Wherein wel is welding fitness, AndIn order to melt the weights and the component weights,AndThe sum of (2) is 1,The melting rate of the solder paste amount of the ith solder joint under the welding parameters is given, K is the mounting accuracy coefficient,In order to raise the temperature of the mounted element at the ith welding spot after welding according to the welding parameters,In order to attach the distance information to the board,The standard mounting distance is the standard mounting distance between the mounting element and the circuit main board;
randomly generating a first heating temperature and a first welding time as first welding parameters;
Adopting the first welding parameters, combining the solder paste quantity information and the mounting distance information, analyzing and obtaining the melting rate of the solder paste in the welded welding spots and the rising temperature of the mounting element, and calculating and obtaining a first welding fitness based on the welding optimization function;
And continuously optimizing the heating temperature and the welding time of the welding until convergence, outputting the welding parameter with the maximum welding fitness, and obtaining the optimal heating temperature and the optimal welding time.
7. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of a smart die bonding control method of an integrated circuit motherboard according to any of claims 1 to 5.
8. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the steps of a smart die bonding control method of an integrated circuit motherboard according to any one of claims 1 to 5.
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| CN117202532A (en) * | 2023-09-09 | 2023-12-08 | 北京强云创新科技有限公司 | Optimized control method and system for SMT (surface mounting technology) |
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| CN116206381A (en) * | 2023-05-04 | 2023-06-02 | 深圳市中际宏图科技有限公司 | Camera module production management monitoring analysis system based on machine vision |
| CN117202532A (en) * | 2023-09-09 | 2023-12-08 | 北京强云创新科技有限公司 | Optimized control method and system for SMT (surface mounting technology) |
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