Intelligent Tire X-ray Defect Detection Passed the Certification

18 June 2019 | Source from China Rubber Journal


On March 26, China PetroleumChemical Industry Federation appraised the achievement of the “Intelligent Tire X-ray Defect Detection System” in Hefei,experts unanimously agreed that this product, with advanced technical indicatorsstrong applicability, had reached the international advanced level. This marks the Chinese intelligent tire X-ray defect detection technology walkingthe intelligent era.

Jointly researcheddeveloped by Shenyang Ligong UniversityGuangzhou Ainstant Industrial Equipment Co., Ltd., this technology, with independent intellectual property right, can automatically detect the inner quality of tires, which greatly improves the tire defect identification efficiencysaves labor costs, filling the gap of the Chinese intelligent tire X-ray defect detection system. After more than half a year of application by Hefei Wanli Tire Co., Ltd., the performance is stablereliable, which greatly reduces the rate of defect detection omissionimproves the efficiency of online tire testing, meeting the requirements of tire testingimproving the utilization safety of tires.

The innovation of this intelligent detection system is mainly reflected in the following: A deep convolutional neural network is used on tire X-ray image recognition for the first time in the world, which builds different network models according to the complexity of different defectscharacteristics of details with automatic identification and self-learning functions, reduces overall omission identification rate,improves the recognition speedaccuracy; by using the self-developed defect localization algorithm, the tire quality defects in the X-ray image are identifiedlocated, which solves the technical problems that the original internal quality detection of all-steel radial tires is difficult to achieve automationintelligence; accord-ing to the different characteristics of the tire defect area, characteristic detectors of different scales are designed to improve the accuracy of defect location;through the pretraining model, the automatic auxiliary marking of tire defects is realized. 

(Chen Weifang)