Deep Digital Image Correlation Based Strain Monitoring Inside Car Tire Using A Single Wireless Camera

Tire pressure monitoring systems (TPMS) are currently used to determine the pressure inside wheels and provide real-time monitoring. However, another critical safety aspect is understanding the load applied to a tire. For passenger vehicles, safety is of utmost importance. Higher loads result in increased contact surface between the tire and road, leading to greater friction and temperature rise. These factors can potentially cause tire bursts, posing significant risks. To mitigate such hazardous situations, this paper proposes a method to monitor strain inside a tire while in motion thereby understanding the load applied on wheels. The approach utilizes a novel dataset and incorporates a CNN-based Digital Image Correlation (DIC) technique for visualizing and analyzing strain experienced inside tire. To generate the dataset, an experimental device was developed using a wireless IP camera, which was positioned inside the rim of the wheel using a roller setup. The camera captured live video and continuous frames, which were wirelessly transmitted to an external computing device for further strain analysis.