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Damage diagnosis in intelligent tires using time-domain and frequency-domain analysis
Authors:Pooya Behroozinia  Seyedmeysam Khaleghian  Saied Taheri  Reza Mirzaeifar
Institution:1. Center for Tire Research (CenTiRe), Department of Mechanical Engineering, Virginia Tech, Blacksburg, VA, USA;2. Maxxis Technology Center, Suwanee, GA, USA;3. Department of Mechanical Engineering, Virginia Tech, Blacksburg, VA, USA
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.
Keywords:Finite element method  damage detection  intelligent tire  crack  acceleration signal
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