A machine learning-based defect classification method for injection molding products

Abstract

The present invention provides a method for classifying defects of injection molding products based on machine learning, which includes the following steps: collecting training samples; inputting the training samples into a classifier for training to obtain a trained classifier; The image of the product is preprocessed; the image of the product to be classified is input into the trained classifier to obtain the classification label, and then the one-hot encoding is transcoded to obtain the label matrix; the label matrix is ​​stacked to obtain the label containing the label information. Stacked matrix; separate the data of the stacked matrix to obtain a low-rank matrix and a sparse matrix, and decompose the sparse matrix into the noise of the training sample and the noise of the image of the product to be classified; iterate the low-rank matrix and take the optimal solution after iteration The corresponding label matrix is ​​used as the optimized label matrix; the injection molding product system converts the optimized label matrix into a machine signal to realize the control of the defect classification of the injection molding product by the machine on the production line.

Description

technical field [0001] The invention relates to the technical field of product defect classification, and more particularly, to a machine learning-based defect classification method for injection molding products. Background technique [0002] At present, the defects of injection molding machine products are mainly caused by the design of the mold, the manufacturing precision and the degree of wear. Since the injection molding cycle itself is very short, if the process conditions are not well mastered, a large number of waste products will be generated. [0003] An existing method for intelligent secondary inspection of injection molded products mainly judges whether the products are qualified by comparing preset image information, and then performs secondary detection on unqualified products to avoid false reductions or missed inspections. In the injection molding product inspection method, although the secondary inspection of unqualified products helps to improve the inspe...

AI Technical Summary

Problems solved by technology

In this injection molding product detection method, although the secondary detection of unqualified products helps to improve the detection accuracy, it increases the time cost

Another type of classification for injection molding products is based on physical judgment of whether the shapes are consistent. Therefore, there is a shortcoming of too single classification. When there are cases where the classified products have the same shape, effective classification cannot be carried out.

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