Research On Retreadability Evaluation Technology Of Waste Tires Based On Machine Vision

In the production process of retreaded tires,it is often necessary to detect the defects of the recovered tires to judge whether they are suitable for retreading.At present,the defect detection of waste tires in the industry mainly depends on the traditional manual method.Manual detection efficiency is low,vision is easy to fatigue,and detection accuracy is easy to be affected by personal subjective factors.In industrial production and manufacturing industry,machine vision technology has the advantages of high detection accuracy and fast detection efficiency.It not only improves the automation degree of production and manufacturing industry,but also ensures the quality of products.It has been widely used at home and abroad.According to the screening requirements of retreaded tires,a retreadability detection system of waste tires is designed by using machine vision detection technology.The system can detect the inner surface defects of tires and measure the tread depth of tires,and judge the retreadability of waste tires according to the test results.It not only reduces the labor intensity and labor cost,but also improves the detection efficiency and accuracy.The main research contents of this paper are as follows:(1)The overall scheme design of waste tire retreadability detection technology is carried out.The detection system is divided into two detection systems: in tire defect detection and tread pattern depth detection.The hardware design,system software design and detection function of each system are completed.(2)The inner surface defect detection system of tire is designed.Based on the deep learning technology,the defects on the inner surface of tire are identified with pytorch deep learning framework and resnet50 based network framework.Finally,the identification results are analyzed and a conclusion is drawn.(3)With the help of the performance characteristics of high measurement accuracy and fast response speed of structured light and the increasingly mature three-dimensional vision detection technology,a structured light three-dimensional vision tire wear detection system is built to detect the tire tread depth.(4)Using Microsoft Visual c# to build the visual interface of waste tire retreadability detection system.The retreadability detection system of waste tires designed in this paper can detect the internal defects and tread depth of tires 360 °.The test results show that the detection accuracy of internal defects of tires can reach 99.24%,and the measurement error of tread depth is less than 0.15 mm.The system has certain engineering application value.