Tire inner side defect detector based on machine vision and deep learning algorithm

Abstract

A tire inner side defect detector based on machine vision and a deep learning algorithm relates to the technical field of tire quality detection and comprises a handle, a machine body, an automatic focusing camera, a searchlight, an embedded alarm single chip microcomputer, an embedded deep learning algorithm development board and a display screen. The embedded deep learning algorithm development board is provided with an image preprocessing module, an improved algorithm module based on classification optimization of a convolutional neural network and a support vector machine, and a defect identification and positioning module. According to the invention, automatically acquired tire inner side image information can be automatically interpreted to realize efficient and accurate identification of tire inner side defects, position information is automatically extracted, defect boundaries are drawn, defect area sizes are calculated, and alarm sounds are sent out, so that the detection and identification work of the tire inner side defects is simplified, automatic, intelligent and efficient, and the time and labor costs of tire inner side defect detection are reduced.

Description

technical field [0001] The invention relates to the technical field of tire quality detection, in particular to a tire inner defect detector based on machine vision and deep learning algorithms. Background technique [0002] During the manufacturing process of tires, due to factors such as operational errors or production equipment, various defects may appear, such as tire thinness, cord bending, impurity cracks, air bubbles, etc. In order to ensure the driving safety of the vehicle, various defect inspections will be carried out before the tire leaves the factory, with the purpose of selecting out the defective tires. [0003] Most of the existing tire defect detection technologies focus on the detection of the external defects of the tire, and the method of manual visual inspection is mostly used for the internal defects of the tire. Obviously, the defects inside the tire are also related to the driving safety of the vehicle, and because the inside of the tire is protecte...

AI Technical Summary

Problems solved by technology

[0005] 1. The identification process needs to be placed under the X-ray emitting instrument, which requires more equipment, complex system, poor flexibility, and high requirements for the environment, equipment and workers' operation process;

[0006] 2. It cannot adapt to the damage identification inside the tire; it can only target the surface defects of the tire, and the internal defects still need to be detected manually

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