Deep Learning-Based Intelligent Tire Wear Detection Method

In order to obtain real-time tire wear status of vehicles, this paper proposes a deep learning-based tire wear detection method. First, a PVDF piezoelectric film sensor is attached to the center of the tire airtight layer with different wear degrees to collect tire stress data under different working conditions. Secondly, the collected data is filtered, and the time domain feature information is extracted by principal component analysis to construct the feature data set. Finally, a deep regression model is established to train the feature data set to realize the real-time detection of tire damage. The results show that the tire wear detection error based on deep learning is less than 0.3mm, which has a high tire wear detection accuracy. It provides tire information for vehicle safe running and has high industrial application value.