Welding paste printing quality prediction method and system based on IGA-DNN

Abstract

The invention discloses a solder paste printing quality prediction method and system based on IGA-DNN, and the method comprises the steps: collecting solder paste printing key process parameters and solder paste printing relative volume original data, carrying out the preprocessing, determining a deep neural network topological structure according to the types of input and output variables, the solder paste printing relative volume predicted by the deep neural network is used as a fitness function of the genetic algorithm; finally, a genetic algorithm is used for optimizing and solving the weight and the threshold value of the deep neural network, algorithm model training is completed through a training sample. However, with a traditional neural network which adopts a gradient descent method to update hyper-parameters of the network, the network search speed is low, and local optimum is extremely prone to occurring. According to the method, the hyper-parameters of the deep neural network are initialized based on the genetic algorithm, the convergence speed and precision of the neural network are improved, high precision and stability of SMT solder paste printing quality prediction are achieved, and meanwhile corresponding technical method support is provided for SMT solder paste printing process parameter optimization.

Description

Technical field [0001] The present invention belongs to the field of surface mount detection, and in particular, the present invention relates to a prediction method and system of solder paste printing quality based on IgA-DNN. Background technique [0002] As one of the core technologies of the electronic manufacturing, Surface Mount Technology (SMT) has the advantages of compact structure, high assembly dimensions, small quality, good impact resistance, high production efficiency. Due to many SMT production processes, it has caused difficulty in print quality. In the actual production process, people, machines, materials, methods, and even changes in the environment can lead to instability of process quality, and solder paste printing quality will mainly affect the final surface mount. Quality, therefore is especially important for tin paste print quality control. The solder paste is a key quality standard for measuring the quality of print quality. The depth neural network opt...

AI Technical Summary

Problems solved by technology

The structural characteristics of the neural network itself lead to some disadvantages of the network, such as slow convergence speed, and it is easy to fall into a local minimum value. In this case, the prediction accuracy will decrease, which cannot meet the actual prediction requirements.

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