| Abstrakt: |
This paper introduces a novel hybrid vision-based modal analysis technique for tires, leveraging the capabilities of a low-cost smartphone in comparison with the high-cost digital image correlation (DIC) method. This approach significantly enhances accessibility and affordability for modal testing while delivering results that align closely with traditional experimental modal analysis (EMA) techniques. Additionally, we present a comprehensive experimental modal analysis of tires, examining various boundary conditions (fixed axle, suspended by bungee cord, and placed on foam), excitation sources (impact hammer and portable shaker), and operating conditions (different static loads and inflation pressures of 25, 30, and 35 psi). These boundary and loading conditions, along with the presented methodology for estimating modal parameters efficiently, offer a thorough study of the dynamic characteristics of tires—an aspect that has not been fully covered in previous studies. To further validate the findings, we conducted numerical simulations in Abaqus, demonstrating excellent agreement between the simulated and experimental mode shapes. This work provides a novel, cost-effective approach to tire modal analysis and contributes a detailed study of tire dynamics under varying conditions, offering valuable insights for researchers and engineers in the automotive industry to optimize tire performance. |
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