Research on a 3D Diagnostic System for Electric Vehicle Surface Damage Based on Fiber Optic Sensors and CenterNet

This study aims to develop a 3D diagnostic system for electric vehicle surface damage, leveraging fiber optic sensors and the CenterNet algorithm, specifically designed to address the current issues of low efficiency and accuracy in damage diagnostics of electric vehicles. Traditional diagnostic methods rely on manual judgment, prone to errors, whereas the new system incorporates advanced sensing technology and image processing algorithms. By integrating 3D modeling and damage detection, the system significantly enhances diagnostic precision and efficiency. The methodology includes the utilization of fiber optic sensing technology combined with the CenterNet algorithm for precise identification and localization of damaged areas. Capable of swiftly and accurately identifying various types of surface damage, the system notably improves accuracy. The development of this system not only enhances operational efficiency in electric vehicle maintenance but also advances smart vehicle maintenance technology through precise and rapid damage diagnostics.