Jointly developed the tire X-ray defect intelligent detection system in Hefei through the scientific and technological achievements of the China Petroleum and Chemical Industry Federation. The appraisal* group agreed that the product technical indicators of the project are advanced and applicable, reaching international*. The application and promotion of the tire X-ray defect intelligent detection system will make China’s tire testing farewell to “artificial” and truly enter the intelligent era. Tire X-ray defect intelligent detection system has independent intellectual property rights. In addition to automatic detection of tire internal quality and greatly improved wheel defect identification efficiency, it can also save a lot of labor costs and make China’s tire testing equipment take new steps. Stairs. As is known to all, China’s rubber machinery industry testing equipment is far behind the development of rubber machinery in terms of intelligence, and it is difficult to meet the transformation and upgrading requirements of the tire industry. Among them, the X-ray defect detection equipment, one of the important testing equipments for tires, has long relied on manual observation on the display screen by the naked eye. The rate of missed detection and false detection is very high. Some tire companies purchase X-ray intelligent detection systems from abroad at high prices, but imported equipment is difficult to adapt to the actual requirements of China’s tire intelligent detection.
Based on this, Shenyang University of Technology and Guangzhou Ennsdan Industrial Equipment Co., Ltd., through collaborative research, successfully overcome the difficulties in the field of tire testing in China after more than a year of efforts. Systematic innovations in independent intellectual property rights. The project product has been used in Hefei Wanli Tire Co., Ltd. for more than half a year, which can greatly reduce the defect detection rate, improve the on-line detection efficiency of tires, meet the requirements of China’s tire testing, and improve the safety of tires. The tire X-ray defect intelligent detection system identified this time has the following innovations: the system uses a deep convolutional neural network to identify the tire X-ray image and constructs differently according to the complexity and detail characteristics of different defects. The network model; using the self-developed defect location algorithm to identify and locate the tire quality defects in the tire X-ray image, to solve the technical problem that the original all-steel radial tire internal quality detection is difficult to achieve automation and intelligence; The different characteristics of the area where the defect is located, the feature detectors of different scales are designed, thereby improving the defect positioning accuracy. In addition, the system also has automatic recognition and self-learning functions, which reduces the overall rate of missed recognition, thereby improving recognition speed and accuracy.
Through the pre-training model, the system also implements automatic assisted labeling of tire defects.
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