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Damage diagnosis in intelligent tires using time-domain and frequency-domain analysis

Abstract Tire durability plays an important role in road transportation safety and is taken very seriously by all tire manufacturers. Defects in tires can cause vehicle instability and create catastrophic accidents. In this article, a finite element model of the intelligent tire is developed using implicit dynamic analysis and is used for defect detection. Processing and analyzing the acceleration signals, measured at the center of the tire inner-liner, for the undamaged and damaged tires, can result in detecting the crack locations around the tire circumference. Additionally, prediction models used for damage diagnosis based on optimized number and location of sensors, was developed. Several sensors located at different locations around the circumference of the damaged tire and away from the crack surface, are used in order to assess sensor location sensitivity from the crack surface. It is observed that the radial component of the acceleration signal has the highest potential to be used as the signal of choice in defect detection as compared to circumferential acceleration signals.